Cloud Data Loss Prevention (Cloud DLP) 現已併入機密資料保護。API 名稱維持不變：Cloud Data Loss Prevention API (DLP API)。如要瞭解構成 Sensitive Data Protection 的服務，請參閱「Sensitive Data Protection 總覽」。

將表格資料去識別化示例

Sensitive Data Protection 可偵測、分類及去識別化結構化資料中的機密資料。將內容去識別化為資料表時，結構和資料欄會為「機密資料保護」服務提供其他線索，讓服務在某些使用情況下取得更好的結果。舉例來說，您可以掃描單一資料欄的特定資料類型，而非整個資料表結構。

本主題提供範例，說明如何設定結構化文字中的機密資料去識別化功能。去識別化功能是透過記錄轉換啟用。這些轉換會套用到識別為特定 infoType 的表格文字資料中的值，或是整欄表格資料中的值。

本主題也提供使用密碼編譯雜湊方法轉換表格資料的範例。加密轉換方法需要加密金鑰，因此獨一無二。

下列範例中的 JSON 可插入任何去識別化要求內的"deidentifyConfig" (DeidentifyConfig) 屬性。按一下「APIs Explorer 範例」連結，即可在 APIs Explorer 中試用範例 JSON。

轉換資料欄 (不檢查)

如要轉換內容已知的特定資料欄，可以略過檢查，直接指定轉換方式。下表後方的範例會將「HAPPINESS SCORE」欄分組，每 10 分為一組。

輸入

轉換後的表格

年齡	PATIENT	快樂指數
101	查爾斯．狄更斯	95
22	珍奧斯汀	21
55	馬克吐溫	75

年齡	PATIENT	快樂指數
101	查爾斯．狄更斯	90:100
22	珍奧斯汀	20:30
55	馬克吐溫	70:80

C#

如要瞭解如何安裝及使用 Sensitive Data Protection 的用戶端程式庫，請參閱「Sensitive Data Protection 用戶端程式庫」。

如要向 Sensitive Data Protection 進行驗證，請設定應用程式預設憑證。詳情請參閱「為本機開發環境設定驗證機制」。


using System;
using Google.Api.Gax.ResourceNames;
using Google.Cloud.Dlp.V2;

public class DeidentifyUsingTableBucketing
{
    public static Table DeidentifyData(
        string projectId,
        Table tableToInspect = null)
    {
        // Instantiate dlp client.
        var dlp = DlpServiceClient.Create();

        // Construct the table if null.
        if (tableToInspect == null)
        {
            var row1 = new Value[]
            {
                new Value { StringValue = "101" },
                new Value { StringValue = "Charles Dickens" },
                new Value { StringValue = "95" }
            };
            var row2 = new Value[]
            {
                new Value { StringValue = "22" },
                new Value { StringValue = "Jane Austin" },
                new Value { StringValue = "21" }
            };
            var row3 = new Value[]
            {
                new Value { StringValue = "55" },
                new Value { StringValue = "Mark Twain" },
                new Value { StringValue = "75" }
            };

            tableToInspect = new Table
            {
                Headers =
                {
                    new FieldId { Name = "AGE" },
                    new FieldId { Name = "PATIENT" },
                    new FieldId { Name = "HAPPINESS SCORE" }
                },
                Rows =
                {
                    new Table.Types.Row { Values = { row1 } },
                    new Table.Types.Row { Values = { row2 } },
                    new Table.Types.Row { Values = { row3 } }
                }
            };
        }

        // Construct the table content item.
        var contentItem = new ContentItem { Table = tableToInspect };

        // Specify how the content should be de-identified.
        var fixedSizeBucketingConfig = new FixedSizeBucketingConfig
        {
            BucketSize = 10,
            LowerBound = new Value { IntegerValue = 0 },
            UpperBound = new Value { IntegerValue = 100 },
        };

        // Specify the fields to be encrypted.
        var fields = new FieldId[] { new FieldId { Name = "HAPPINESS SCORE" } };

        // Associate the encryption with the specified field.
        var fieldTransformation = new FieldTransformation
        {
            PrimitiveTransformation = new PrimitiveTransformation
            {
                FixedSizeBucketingConfig = fixedSizeBucketingConfig
            },
            Fields = { fields }
        };

        // Construct the deidentify config.
        var deidentifyConfig = new DeidentifyConfig
        {
            RecordTransformations = new RecordTransformations
            {
                FieldTransformations = { fieldTransformation }
            }
        };

        // Construct the request.
        var request = new DeidentifyContentRequest
        {
            ParentAsLocationName = new LocationName(projectId, "global"),
            DeidentifyConfig = deidentifyConfig,
            Item = contentItem,
        };

        // Call the API.
        var response = dlp.DeidentifyContent(request);

        // Inspect the response.
        Console.WriteLine(response.Item.Table);

        return response.Item.Table;
    }
}

Go

如要瞭解如何安裝及使用 Sensitive Data Protection 的用戶端程式庫，請參閱「Sensitive Data Protection 用戶端程式庫」。

如要向 Sensitive Data Protection 進行驗證，請設定應用程式預設憑證。詳情請參閱「為本機開發環境設定驗證機制」。

import (
	"context"
	"fmt"
	"io"

	dlp "cloud.google.com/go/dlp/apiv2"
	"cloud.google.com/go/dlp/apiv2/dlppb"
)

// deIdentifyTableBucketing de-identifies data using table bucketing
func deIdentifyTableBucketing(w io.Writer, projectID string) error {
	// projectId := "your-project-id"
	// table := "your-table-value"

	row1 := &dlppb.Table_Row{
		Values: []*dlppb.Value{
			{Type: &dlppb.Value_StringValue{StringValue: "22"}},
			{Type: &dlppb.Value_StringValue{StringValue: "Jane Austen"}},
			{Type: &dlppb.Value_StringValue{StringValue: "21"}},
		},
	}

	row2 := &dlppb.Table_Row{
		Values: []*dlppb.Value{
			{Type: &dlppb.Value_StringValue{StringValue: "55"}},
			{Type: &dlppb.Value_StringValue{StringValue: "Mark Twain"}},
			{Type: &dlppb.Value_StringValue{StringValue: "75"}},
		},
	}

	row3 := &dlppb.Table_Row{
		Values: []*dlppb.Value{
			{Type: &dlppb.Value_StringValue{StringValue: "101"}},
			{Type: &dlppb.Value_StringValue{StringValue: "Charles Dickens"}},
			{Type: &dlppb.Value_StringValue{StringValue: "95"}},
		},
	}

	table := &dlppb.Table{
		Headers: []*dlppb.FieldId{
			{Name: "AGE"},
			{Name: "PATIENT"},
			{Name: "HAPPINESS SCORE"},
		},
		Rows: []*dlppb.Table_Row{
			{Values: row1.Values},
			{Values: row2.Values},
			{Values: row3.Values},
		},
	}

	ctx := context.Background()

	// Initialize a client once and reuse it to send multiple requests. Clients
	// are safe to use across goroutines. When the client is no longer needed,
	// call the Close method to cleanup its resources.
	client, err := dlp.NewClient(ctx)
	if err != nil {
		return err
	}

	// Closing the client safely cleans up background resources.
	defer client.Close()

	// Specify what content you want the service to de-identify.
	contentItem := &dlppb.ContentItem{
		DataItem: &dlppb.ContentItem_Table{
			Table: table,
		},
	}

	// Specify how the content should be de-identified.
	fixedSizeBucketingConfig := &dlppb.FixedSizeBucketingConfig{
		BucketSize: 10,
		LowerBound: &dlppb.Value{
			Type: &dlppb.Value_IntegerValue{
				IntegerValue: 0,
			},
		},
		UpperBound: &dlppb.Value{
			Type: &dlppb.Value_IntegerValue{
				IntegerValue: 100,
			},
		},
	}
	primitiveTransformation := &dlppb.PrimitiveTransformation_FixedSizeBucketingConfig{
		FixedSizeBucketingConfig: fixedSizeBucketingConfig,
	}

	// Specify field to be encrypted.
	fieldId := &dlppb.FieldId{
		Name: "HAPPINESS SCORE",
	}

	// Associate the encryption with the specified field.
	fieldTransformation := &dlppb.FieldTransformation{
		Transformation: &dlppb.FieldTransformation_PrimitiveTransformation{
			PrimitiveTransformation: &dlppb.PrimitiveTransformation{
				Transformation: primitiveTransformation,
			},
		},
		Fields: []*dlppb.FieldId{
			fieldId,
		},
	}

	recordTransformations := &dlppb.RecordTransformations{
		FieldTransformations: []*dlppb.FieldTransformation{
			fieldTransformation,
		},
	}

	// Construct the de-identification request to be sent by the client.
	req := &dlppb.DeidentifyContentRequest{
		Parent: fmt.Sprintf("projects/%s/locations/global", projectID),
		DeidentifyConfig: &dlppb.DeidentifyConfig{
			Transformation: &dlppb.DeidentifyConfig_RecordTransformations{
				RecordTransformations: recordTransformations,
			},
		},
		Item: contentItem,
	}
	// Send the request.
	resp, err := client.DeidentifyContent(ctx, req)
	if err != nil {
		return err
	}

	// Print the results.
	fmt.Fprintf(w, "Table after de-identification : %v", resp.GetItem().GetTable())
	return nil
}

Java

如要瞭解如何安裝及使用 Sensitive Data Protection 的用戶端程式庫，請參閱「Sensitive Data Protection 用戶端程式庫」。

如要向 Sensitive Data Protection 進行驗證，請設定應用程式預設憑證。詳情請參閱「為本機開發環境設定驗證機制」。


import com.google.cloud.dlp.v2.DlpServiceClient;
import com.google.privacy.dlp.v2.ContentItem;
import com.google.privacy.dlp.v2.DeidentifyConfig;
import com.google.privacy.dlp.v2.DeidentifyContentRequest;
import com.google.privacy.dlp.v2.DeidentifyContentResponse;
import com.google.privacy.dlp.v2.FieldId;
import com.google.privacy.dlp.v2.FieldTransformation;
import com.google.privacy.dlp.v2.FixedSizeBucketingConfig;
import com.google.privacy.dlp.v2.LocationName;
import com.google.privacy.dlp.v2.PrimitiveTransformation;
import com.google.privacy.dlp.v2.RecordTransformations;
import com.google.privacy.dlp.v2.Table;
import com.google.privacy.dlp.v2.Table.Row;
import com.google.privacy.dlp.v2.Value;
import java.io.IOException;

public class DeIdentifyTableBucketing {

  public static void main(String[] args) throws IOException {
    // TODO(developer): Replace these variables before running the sample.
    String projectId = "your-project-id";
    Table tableToDeIdentify =
        Table.newBuilder()
            .addHeaders(FieldId.newBuilder().setName("AGE").build())
            .addHeaders(FieldId.newBuilder().setName("PATIENT").build())
            .addHeaders(FieldId.newBuilder().setName("HAPPINESS SCORE").build())
            .addRows(
                Row.newBuilder()
                    .addValues(Value.newBuilder().setStringValue("101").build())
                    .addValues(Value.newBuilder().setStringValue("Charles Dickens").build())
                    .addValues(Value.newBuilder().setStringValue("95").build())
                    .build())
            .addRows(
                Row.newBuilder()
                    .addValues(Value.newBuilder().setStringValue("22").build())
                    .addValues(Value.newBuilder().setStringValue("Jane Austen").build())
                    .addValues(Value.newBuilder().setStringValue("21").build())
                    .build())
            .addRows(
                Row.newBuilder()
                    .addValues(Value.newBuilder().setStringValue("55").build())
                    .addValues(Value.newBuilder().setStringValue("Mark Twain").build())
                    .addValues(Value.newBuilder().setStringValue("75").build())
                    .build())
            .build();

    deIdentifyTableBucketing(projectId, tableToDeIdentify);
  }

  public static Table deIdentifyTableBucketing(String projectId, Table tableToDeIdentify)
      throws IOException {
    // Initialize client that will be used to send requests. This client only needs to be created
    // once, and can be reused for multiple requests. After completing all of your requests, call
    // the "close" method on the client to safely clean up any remaining background resources.
    try (DlpServiceClient dlp = DlpServiceClient.create()) {
      // Specify what content you want the service to de-identify.
      ContentItem contentItem = ContentItem.newBuilder().setTable(tableToDeIdentify).build();

      // Specify how the content should be de-identified.
      FixedSizeBucketingConfig fixedSizeBucketingConfig =
          FixedSizeBucketingConfig.newBuilder()
              .setBucketSize(10)
              .setLowerBound(Value.newBuilder().setIntegerValue(0).build())
              .setUpperBound(Value.newBuilder().setIntegerValue(100).build())
              .build();
      PrimitiveTransformation primitiveTransformation =
          PrimitiveTransformation.newBuilder()
              .setFixedSizeBucketingConfig(fixedSizeBucketingConfig)
              .build();

      // Specify field to be encrypted.
      FieldId fieldId = FieldId.newBuilder().setName("HAPPINESS SCORE").build();

      // Associate the encryption with the specified field.
      FieldTransformation fieldTransformation =
          FieldTransformation.newBuilder()
              .setPrimitiveTransformation(primitiveTransformation)
              .addFields(fieldId)
              .build();
      RecordTransformations transformations =
          RecordTransformations.newBuilder().addFieldTransformations(fieldTransformation).build();

      DeidentifyConfig deidentifyConfig =
          DeidentifyConfig.newBuilder().setRecordTransformations(transformations).build();

      // Combine configurations into a request for the service.
      DeidentifyContentRequest request =
          DeidentifyContentRequest.newBuilder()
              .setParent(LocationName.of(projectId, "global").toString())
              .setItem(contentItem)
              .setDeidentifyConfig(deidentifyConfig)
              .build();

      // Send the request and receive response from the service.
      DeidentifyContentResponse response = dlp.deidentifyContent(request);

      // Print the results.
      System.out.println("Table after de-identification: " + response.getItem().getTable());

      return response.getItem().getTable();
    }
  }
}

Node.js

如要瞭解如何安裝及使用 Sensitive Data Protection 的用戶端程式庫，請參閱「Sensitive Data Protection 用戶端程式庫」。

如要向 Sensitive Data Protection 進行驗證，請設定應用程式預設憑證。詳情請參閱「為本機開發環境設定驗證機制」。

// Imports the Google Cloud Data Loss Prevention library
const DLP = require('@google-cloud/dlp');

// Initialize google DLP Client
const dlp = new DLP.DlpServiceClient();

// The project ID to run the API call under
// const projectId = 'my-project';

// Construct the tabular data
const tablularData = {
  headers: [{name: 'AGE'}, {name: 'PATIENT'}, {name: 'HAPPINESS SCORE'}],
  rows: [
    {
      values: [
        {integerValue: 101},
        {stringValue: 'Charles Dickens'},
        {integerValue: 95},
      ],
    },
    {
      values: [
        {integerValue: 22},
        {stringValue: 'Jane Austen'},
        {integerValue: 21},
      ],
    },
    {
      values: [
        {integerValue: 55},
        {stringValue: 'Mark Twain'},
        {integerValue: 75},
      ],
    },
  ],
};
async function deIdentifyTableBucketing() {
  // Specify field to be de-identified.
  const targetColumn = {name: 'HAPPINESS SCORE'};

  // Specify how the content should be de-identified.
  const bucketingConfig = {
    bucketSize: 10,
    lowerBound: {
      integerValue: 0,
    },
    upperBound: {
      integerValue: 100,
    },
  };

  const primitiveTransformation = {
    fixedSizeBucketingConfig: bucketingConfig,
  };

  // Combine configurations into a request for the service.
  const request = {
    parent: `projects/${projectId}/locations/global`,
    item: {
      table: tablularData,
    },
    deidentifyConfig: {
      recordTransformations: {
        fieldTransformations: [
          {
            fields: [targetColumn],
            primitiveTransformation,
          },
        ],
      },
    },
  };
  // Send the request and receive response from the service
  const [response] = await dlp.deidentifyContent(request);

  // Print the results.
  console.log(
    `Table after de-identification: ${JSON.stringify(response.item.table)}`
  );
}

deIdentifyTableBucketing();

PHP

如要瞭解如何安裝及使用 Sensitive Data Protection 的用戶端程式庫，請參閱「Sensitive Data Protection 用戶端程式庫」。

如要向 Sensitive Data Protection 進行驗證，請設定應用程式預設憑證。詳情請參閱「為本機開發環境設定驗證機制」。

use Google\Cloud\Dlp\V2\Client\DlpServiceClient;
use Google\Cloud\Dlp\V2\ContentItem;
use Google\Cloud\Dlp\V2\DeidentifyConfig;
use Google\Cloud\Dlp\V2\DeidentifyContentRequest;
use Google\Cloud\Dlp\V2\FieldId;
use Google\Cloud\Dlp\V2\FieldTransformation;
use Google\Cloud\Dlp\V2\FixedSizeBucketingConfig;
use Google\Cloud\Dlp\V2\PrimitiveTransformation;
use Google\Cloud\Dlp\V2\RecordTransformations;
use Google\Cloud\Dlp\V2\Table;
use Google\Cloud\Dlp\V2\Table\Row;
use Google\Cloud\Dlp\V2\Value;

/**
 * De-identify data using table bucketing
 * Transform a column without inspection. To transform a column in which the content is
 * already known, you can skip inspection and specify a transformation directly.
 *
 * @param string $callingProjectId      The Google Cloud project id to use as a parent resource.
 * @param string $inputCsvFile          The input file(csv) path  to deidentify
 * @param string $outputCsvFile         The oupt file path to save deidentify content
 *
 */
function deidentify_table_bucketing(
    // TODO(developer): Replace sample parameters before running the code.
    string $callingProjectId,
    string $inputCsvFile = './test/data/table2.csv',
    string $outputCsvFile = './test/data/deidentify_table_bucketing_output.csv'
): void {
    // Instantiate a client.
    $dlp = new DlpServiceClient();

    // Read a CSV file
    $csvLines = file($inputCsvFile, FILE_IGNORE_NEW_LINES);
    $csvHeaders = explode(',', $csvLines[0]);
    $csvRows = array_slice($csvLines, 1);

    // Convert CSV file into protobuf objects
    $tableHeaders = array_map(function ($csvHeader) {
        return (new FieldId)
            ->setName($csvHeader);
    }, $csvHeaders);

    $tableRows = array_map(function ($csvRow) {
        $rowValues = array_map(function ($csvValue) {
            return (new Value())
                ->setStringValue($csvValue);
        }, explode(',', $csvRow));
        return (new Row())
            ->setValues($rowValues);
    }, $csvRows);

    // Construct the table object
    $tableToDeIdentify = (new Table())
        ->setHeaders($tableHeaders)
        ->setRows($tableRows);

    // Specify what content you want the service to de-identify.
    $contentItem = (new ContentItem())
        ->setTable($tableToDeIdentify);

    // Specify how the content should be de-identified.
    $fixedSizeBucketingConfig = (new FixedSizeBucketingConfig())
        ->setBucketSize(10)
        ->setLowerBound((new Value())
            ->setIntegerValue(10))
        ->setUpperBound((new Value())
            ->setIntegerValue(100));

    $primitiveTransformation = (new PrimitiveTransformation())
        ->setFixedSizeBucketingConfig($fixedSizeBucketingConfig);

    // Specify the field to to apply bucketing transform on
    $fieldId = (new FieldId())
        ->setName('HAPPINESS_SCORE');

    // Associate the encryption with the specified field.
    $fieldTransformation = (new FieldTransformation())
        ->setPrimitiveTransformation($primitiveTransformation)
        ->setFields([$fieldId]);

    $recordTransformations = (new RecordTransformations())
        ->setFieldTransformations([$fieldTransformation]);

    // Create the deidentification configuration object
    $deidentifyConfig = (new DeidentifyConfig())
        ->setRecordTransformations($recordTransformations);

    $parent = "projects/$callingProjectId/locations/global";

    // Run request
    $deidentifyContentRequest = (new DeidentifyContentRequest())
        ->setParent($parent)
        ->setDeidentifyConfig($deidentifyConfig)
        ->setItem($contentItem);
    $response = $dlp->deidentifyContent($deidentifyContentRequest);

    // Print results
    $csvRef = fopen($outputCsvFile, 'w');
    fputcsv($csvRef, $csvHeaders);
    foreach ($response->getItem()->getTable()->getRows() as $tableRow) {
        $values = array_map(function ($tableValue) {
            return $tableValue->getStringValue();
        }, iterator_to_array($tableRow->getValues()));
        fputcsv($csvRef, $values);
    };
    printf($outputCsvFile);
}

Python

如要瞭解如何安裝及使用 Sensitive Data Protection 的用戶端程式庫，請參閱「Sensitive Data Protection 用戶端程式庫」。

如要向 Sensitive Data Protection 進行驗證，請設定應用程式預設憑證。詳情請參閱「為本機開發環境設定驗證機制」。

from typing import Dict, List, Union

import google.cloud.dlp
from google.cloud.dlp_v2 import types


def deidentify_table_bucketing(
    project: str,
    table_data: Dict[str, Union[List[str], List[List[str]]]],
    deid_content_list: List[str],
    bucket_size: int,
    bucketing_lower_bound: int,
    bucketing_upper_bound: int,
) -> types.dlp.Table:
    """Uses the Data Loss Prevention API to de-identify sensitive data in a
    table by replacing them with fixed size bucket ranges.
    Args:
        project: The Google Cloud project id to use as a parent resource.
        table_data: Dictionary representing table data.
        deid_content_list: A list of fields in table to de-identify.
        bucket_size: Size of each bucket for fixed sized bucketing
            (except for minimum and maximum buckets). So if ``bucketing_lower_bound`` = 10,
            ``bucketing_upper_bound`` = 89, and ``bucket_size`` = 10, then the
            following buckets would be used: -10, 10-20, 20-30, 30-40,
            40-50, 50-60, 60-70, 70-80, 80-89, 89+.
       bucketing_lower_bound: Lower bound value of buckets.
       bucketing_upper_bound:  Upper bound value of buckets.

    Returns:
       De-identified table is returned;
       the response from the API is also printed to the terminal.

    Example:
    >> $ python deidentify_table_bucketing.py \
        '{"header": ["email", "phone number", "age"],
        "rows": [["robertfrost@example.com", "4232342345", "35"],
        ["johndoe@example.com", "4253458383", "68"]]}' \
        ["age"] 10 0 100
        >>  '{"header": ["email", "phone number", "age"],
            "rows": [["robertfrost@example.com", "4232342345", "30:40"],
            ["johndoe@example.com", "4253458383", "60:70"]]}'
    """

    # Instantiate a client.
    dlp = google.cloud.dlp_v2.DlpServiceClient()

    # Convert the project id into a full resource id.
    parent = f"projects/{project}/locations/global"

    # Construct the `table`. For more details on the table schema, please see
    # https://cloud.google.com/dlp/docs/reference/rest/v2/ContentItem#Table
    headers = [{"name": val} for val in table_data["header"]]
    rows = []
    for row in table_data["rows"]:
        rows.append({"values": [{"string_value": cell_val} for cell_val in row]})

    table = {"headers": headers, "rows": rows}

    # Construct the `item`.
    item = {"table": table}

    # Construct fixed sized bucketing configuration
    fixed_size_bucketing_config = {
        "bucket_size": bucket_size,
        "lower_bound": {"integer_value": bucketing_lower_bound},
        "upper_bound": {"integer_value": bucketing_upper_bound},
    }

    # Specify fields to be de-identified
    deid_content_list = [{"name": _i} for _i in deid_content_list]

    # Construct Deidentify Config
    deidentify_config = {
        "record_transformations": {
            "field_transformations": [
                {
                    "fields": deid_content_list,
                    "primitive_transformation": {
                        "fixed_size_bucketing_config": fixed_size_bucketing_config
                    },
                }
            ]
        }
    }

    # Call the API.
    response = dlp.deidentify_content(
        request={"parent": parent, "deidentify_config": deidentify_config, "item": item}
    )

    # Print the results.
    print(f"Table after de-identification: {response.item.table}")

    # Return the response.
    return response.item.table

API Explorer 範例

"deidentifyConfig":{
  "recordTransformations":{
    "fieldTransformations":[
      {
        "fields":[
          {
            "name":"HAPPINESS SCORE"
          }
        ],
        "primitiveTransformation":{
          "fixedSizeBucketingConfig":{
            "bucketSize":10,
            "lowerBound":{
              "integerValue":"0"
            },
            "upperBound":{
              "integerValue":"100"
            }
          }
        }
      }
    ]
  }
}

根據其他資料欄的值轉換資料欄

您可以根據另一個資料欄的值轉換資料欄。這個範例會為所有 89 歲以上的病患遮蓋「HAPPINESS SCORE」。

輸入

轉換後的表格

年齡	PATIENT	快樂指數
101	查爾斯．狄更斯	95
22	珍奧斯汀	21
55	馬克吐溫	75

年齡	PATIENT	快樂指數
101	查爾斯．狄更斯	**
22	珍奧斯汀	21
55	馬克吐溫	75

C#

如要瞭解如何安裝及使用 Sensitive Data Protection 的用戶端程式庫，請參閱「Sensitive Data Protection 用戶端程式庫」。

如要向 Sensitive Data Protection 進行驗證，請設定應用程式預設憑證。詳情請參閱「為本機開發環境設定驗證機制」。


using System;
using Google.Api.Gax.ResourceNames;
using Google.Cloud.Dlp.V2;

public class DeidentifyTableUsingMaskingAndLogic
{
    public static Table DeidentifyTable(
        string projectId,
        Table tableToInspect = null)
    {
        // Instantiate the client.
        var dlp = DlpServiceClient.Create();

        // Construct the table if null.
        if (tableToInspect == null)
        {
            var row1 = new Value[]
            {
                new Value { StringValue = "101" },
                new Value { StringValue = "Charles Dickens" },
                new Value { StringValue = "95" },
                new Value { StringValue = "Charles Dickens name was a curse invented by Shakespeare." }
            };
            var row2 = new Value[]
            {
                new Value { StringValue = "22" },
                new Value { StringValue = "Jane Austin" },
                new Value { StringValue = "21" },
                new Value { StringValue = "There are 14 kisses in Jane Austen's novels." }
            };
            var row3 = new Value[]
            {
                new Value { StringValue = "55" },
                new Value { StringValue = "Mark Twain" },
                new Value { StringValue = "75" },
                new Value { StringValue = "Mark Twain loved cats." }
            };

            tableToInspect = new Table
            {
                Headers =
                {
                    new FieldId { Name = "AGE" },
                    new FieldId { Name = "PATIENT" },
                    new FieldId { Name = "HAPPINESS SCORE" },
                    new FieldId { Name = "FACTOID" }
                },
                Rows =
                {
                    new Table.Types.Row { Values = { row1 } },
                    new Table.Types.Row { Values = { row2 } },
                    new Table.Types.Row { Values = { row3 } }
                }
            };
        }

        // Construct the table content item.
        var contentItem = new ContentItem { Table = tableToInspect };

        //Specify how the content should be de-identified.
        var primitiveTransformation = new PrimitiveTransformation
        {
            CharacterMaskConfig = new CharacterMaskConfig
            {
                MaskingCharacter = "*"
            }
        };

        // Specify the fields to be de-identified.
        var fields = new FieldId[] { new FieldId { Name = "HAPPINESS SCORE" } };

        // Specify when the above fields should be de-identified using condition.
        var condition = new RecordCondition.Types.Conditions
        {
            Conditions_ =
            {
                new RecordCondition.Types.Condition
                {
                    Field = new FieldId { Name = "AGE" },
                    Operator = RelationalOperator.GreaterThan,
                    Value = new Value { IntegerValue = 89 }
                }
            }
        };

        // Apply the condition to records
        var recordCondition = new RecordCondition
        {
            Expressions = new RecordCondition.Types.Expressions
            {
                Conditions = condition
            }
        };

        // Associate the de-identification and conditions with the specified fields.
        var deidentifiedConfig = new DeidentifyConfig
        {
            RecordTransformations = new RecordTransformations
            {
                FieldTransformations =
                {
                    new FieldTransformation
                    {
                        PrimitiveTransformation = primitiveTransformation,
                        Fields = { fields },
                        Condition = recordCondition
                    }
                }
            }
        };

        // Construct the request.
        var request = new DeidentifyContentRequest
        {
            ParentAsLocationName = new LocationName(projectId, "global"),
            DeidentifyConfig = deidentifiedConfig,
            Item = contentItem
        };

        // Call the API.
        var response = dlp.DeidentifyContent(request);

        // Inspect the response.
        Console.WriteLine(response.Item.Table);
        return response.Item.Table;
    }
}

Go

如要瞭解如何安裝及使用 Sensitive Data Protection 的用戶端程式庫，請參閱「Sensitive Data Protection 用戶端程式庫」。

如要向 Sensitive Data Protection 進行驗證，請設定應用程式預設憑證。詳情請參閱「為本機開發環境設定驗證機制」。

import (
	"context"
	"fmt"
	"io"

	dlp "cloud.google.com/go/dlp/apiv2"
	"cloud.google.com/go/dlp/apiv2/dlppb"
)

// deidentifyTableMaskingCondition de-identifies the table data using masking
// and conditional logic
func deidentifyTableMaskingCondition(w io.Writer, projectID string) error {
	// projectId := "your-project-id"

	row1 := &dlppb.Table_Row{
		Values: []*dlppb.Value{
			{Type: &dlppb.Value_StringValue{StringValue: "22"}},
			{Type: &dlppb.Value_StringValue{StringValue: "Jane Austen"}},
			{Type: &dlppb.Value_StringValue{StringValue: "21"}},
		},
	}

	row2 := &dlppb.Table_Row{
		Values: []*dlppb.Value{
			{Type: &dlppb.Value_StringValue{StringValue: "55"}},
			{Type: &dlppb.Value_StringValue{StringValue: "Mark Twain"}},
			{Type: &dlppb.Value_StringValue{StringValue: "75"}},
		},
	}

	row3 := &dlppb.Table_Row{
		Values: []*dlppb.Value{
			{Type: &dlppb.Value_StringValue{StringValue: "101"}},
			{Type: &dlppb.Value_StringValue{StringValue: "Charles Dickens"}},
			{Type: &dlppb.Value_StringValue{StringValue: "95"}},
		},
	}

	table := &dlppb.Table{
		Headers: []*dlppb.FieldId{
			{Name: "AGE"},
			{Name: "PATIENT"},
			{Name: "HAPPINESS SCORE"},
		},
		Rows: []*dlppb.Table_Row{
			{Values: row1.Values},
			{Values: row2.Values},
			{Values: row3.Values},
		},
	}

	ctx := context.Background()

	// Initialize a client once and reuse it to send multiple requests. Clients
	// are safe to use across goroutines. When the client is no longer needed,
	// call the Close method to cleanup its resources.
	client, err := dlp.NewClient(ctx)
	if err != nil {
		return err
	}

	// Closing the client safely cleans up background resources.
	defer client.Close()

	// Specify what content you want the service to de-identify.
	contentItem := &dlppb.ContentItem{
		DataItem: &dlppb.ContentItem_Table{
			Table: table,
		},
	}

	// Specify how the content should be de-identified.
	charMaskConfig := &dlppb.CharacterMaskConfig{
		MaskingCharacter: "*",
	}
	primitiveTransformation := &dlppb.PrimitiveTransformation_CharacterMaskConfig{
		CharacterMaskConfig: charMaskConfig,
	}

	// Specify field to be de-identified.
	fieldId := &dlppb.FieldId{
		Name: "HAPPINESS SCORE",
	}

	// Apply the condition to the records present in table.
	recordCondition := &dlppb.RecordCondition_Condition{
		Field:    fieldId,
		Operator: dlppb.RelationalOperator_GREATER_THAN,
		Value: &dlppb.Value{
			Type: &dlppb.Value_IntegerValue{
				IntegerValue: 89,
			},
		},
	}

	expression := &dlppb.RecordCondition_Expressions{
		Type: &dlppb.RecordCondition_Expressions_Conditions{
			Conditions: &dlppb.RecordCondition_Conditions{
				Conditions: []*dlppb.RecordCondition_Condition{
					recordCondition,
				},
			},
		},
	}

	// Specify when the above field should be de-identified.
	condition := &dlppb.RecordCondition{
		// Apply the condition to records
		Expressions: expression,
	}

	// Associate the de-identification and conditions with the specified field.
	fieldTransformation := &dlppb.FieldTransformation{
		Fields: []*dlppb.FieldId{
			fieldId,
		},
		Transformation: &dlppb.FieldTransformation_PrimitiveTransformation{
			PrimitiveTransformation: &dlppb.PrimitiveTransformation{
				Transformation: primitiveTransformation,
			},
		},
		Condition: condition,
	}

	recordTransformations := &dlppb.RecordTransformations{
		FieldTransformations: []*dlppb.FieldTransformation{
			fieldTransformation,
		},
	}

	// Combine configurations into a request for the service.
	req := &dlppb.DeidentifyContentRequest{
		Parent: fmt.Sprintf("projects/%s/locations/global", projectID),
		DeidentifyConfig: &dlppb.DeidentifyConfig{
			Transformation: &dlppb.DeidentifyConfig_RecordTransformations{
				RecordTransformations: recordTransformations,
			},
		},
		Item: contentItem,
	}

	// Send the request.
	resp, err := client.DeidentifyContent(ctx, req)
	if err != nil {
		return err
	}

	// Print the results.
	fmt.Fprintf(w, "Table after de-identification : %v", resp.GetItem().GetTable())
	return nil

}

Java

如要瞭解如何安裝及使用 Sensitive Data Protection 的用戶端程式庫，請參閱「Sensitive Data Protection 用戶端程式庫」。

如要向 Sensitive Data Protection 進行驗證，請設定應用程式預設憑證。詳情請參閱「為本機開發環境設定驗證機制」。


import com.google.cloud.dlp.v2.DlpServiceClient;
import com.google.privacy.dlp.v2.CharacterMaskConfig;
import com.google.privacy.dlp.v2.ContentItem;
import com.google.privacy.dlp.v2.DeidentifyConfig;
import com.google.privacy.dlp.v2.DeidentifyContentRequest;
import com.google.privacy.dlp.v2.DeidentifyContentResponse;
import com.google.privacy.dlp.v2.FieldId;
import com.google.privacy.dlp.v2.FieldTransformation;
import com.google.privacy.dlp.v2.LocationName;
import com.google.privacy.dlp.v2.PrimitiveTransformation;
import com.google.privacy.dlp.v2.RecordCondition;
import com.google.privacy.dlp.v2.RecordCondition.Condition;
import com.google.privacy.dlp.v2.RecordCondition.Conditions;
import com.google.privacy.dlp.v2.RecordCondition.Expressions;
import com.google.privacy.dlp.v2.RecordTransformations;
import com.google.privacy.dlp.v2.RelationalOperator;
import com.google.privacy.dlp.v2.Table;
import com.google.privacy.dlp.v2.Table.Row;
import com.google.privacy.dlp.v2.Value;
import java.io.IOException;

public class DeIdentifyTableConditionMasking {

  public static void main(String[] args) throws IOException {
    // TODO(developer): Replace these variables before running the sample.
    String projectId = "your-project-id";
    Table tableToDeIdentify =
        Table.newBuilder()
            .addHeaders(FieldId.newBuilder().setName("AGE").build())
            .addHeaders(FieldId.newBuilder().setName("PATIENT").build())
            .addHeaders(FieldId.newBuilder().setName("HAPPINESS SCORE").build())
            .addRows(
                Row.newBuilder()
                    .addValues(Value.newBuilder().setStringValue("101").build())
                    .addValues(Value.newBuilder().setStringValue("Charles Dickens").build())
                    .addValues(Value.newBuilder().setStringValue("95").build())
                    .build())
            .addRows(
                Row.newBuilder()
                    .addValues(Value.newBuilder().setStringValue("22").build())
                    .addValues(Value.newBuilder().setStringValue("Jane Austen").build())
                    .addValues(Value.newBuilder().setStringValue("21").build())
                    .build())
            .addRows(
                Row.newBuilder()
                    .addValues(Value.newBuilder().setStringValue("55").build())
                    .addValues(Value.newBuilder().setStringValue("Mark Twain").build())
                    .addValues(Value.newBuilder().setStringValue("75").build())
                    .build())
            .build();

    deIdentifyTableConditionMasking(projectId, tableToDeIdentify);
  }

  public static Table deIdentifyTableConditionMasking(String projectId, Table tableToDeIdentify)
      throws IOException {
    // Initialize client that will be used to send requests. This client only needs to be created
    // once, and can be reused for multiple requests. After completing all of your requests, call
    // the "close" method on the client to safely clean up any remaining background resources.
    try (DlpServiceClient dlp = DlpServiceClient.create()) {
      // Specify what content you want the service to de-identify.
      ContentItem contentItem = ContentItem.newBuilder().setTable(tableToDeIdentify).build();

      // Specify how the content should be de-identified.
      CharacterMaskConfig characterMaskConfig =
          CharacterMaskConfig.newBuilder().setMaskingCharacter("*").build();
      PrimitiveTransformation primitiveTransformation =
          PrimitiveTransformation.newBuilder().setCharacterMaskConfig(characterMaskConfig).build();

      // Specify field to be de-identified.
      FieldId fieldId = FieldId.newBuilder().setName("HAPPINESS SCORE").build();

      // Specify when the above field should be de-identified.
      Condition condition =
          Condition.newBuilder()
              .setField(FieldId.newBuilder().setName("AGE").build())
              .setOperator(RelationalOperator.GREATER_THAN)
              .setValue(Value.newBuilder().setIntegerValue(89).build())
              .build();
      // Apply the condition to records
      RecordCondition recordCondition =
          RecordCondition.newBuilder()
              .setExpressions(
                  Expressions.newBuilder()
                      .setConditions(Conditions.newBuilder().addConditions(condition).build())
                      .build())
              .build();

      // Associate the de-identification and conditions with the specified field.
      FieldTransformation fieldTransformation =
          FieldTransformation.newBuilder()
              .setPrimitiveTransformation(primitiveTransformation)
              .addFields(fieldId)
              .setCondition(recordCondition)
              .build();
      RecordTransformations transformations =
          RecordTransformations.newBuilder().addFieldTransformations(fieldTransformation).build();

      DeidentifyConfig deidentifyConfig =
          DeidentifyConfig.newBuilder().setRecordTransformations(transformations).build();

      // Combine configurations into a request for the service.
      DeidentifyContentRequest request =
          DeidentifyContentRequest.newBuilder()
              .setParent(LocationName.of(projectId, "global").toString())
              .setItem(contentItem)
              .setDeidentifyConfig(deidentifyConfig)
              .build();

      // Send the request and receive response from the service.
      DeidentifyContentResponse response = dlp.deidentifyContent(request);

      // Print the results.
      System.out.println("Table after de-identification: " + response.getItem().getTable());

      return response.getItem().getTable();
    }
  }
}

Node.js

如要瞭解如何安裝及使用 Sensitive Data Protection 的用戶端程式庫，請參閱「Sensitive Data Protection 用戶端程式庫」。

如要向 Sensitive Data Protection 進行驗證，請設定應用程式預設憑證。詳情請參閱「為本機開發環境設定驗證機制」。

// Imports the Google Cloud Data Loss Prevention library
const DLP = require('@google-cloud/dlp');

// Initialize google DLP Client
const dlp = new DLP.DlpServiceClient();

// The project ID to run the API call under
// const projectId = 'my-project';

// Construct the tabular data
const tablularData = {
  headers: [{name: 'AGE'}, {name: 'PATIENT'}, {name: 'HAPPINESS SCORE'}],
  rows: [
    {
      values: [
        {integerValue: 101},
        {stringValue: 'Charles Dickens'},
        {integerValue: 95},
      ],
    },
    {
      values: [
        {integerValue: 22},
        {stringValue: 'Jane Austen'},
        {integerValue: 21},
      ],
    },
    {
      values: [
        {integerValue: 55},
        {stringValue: 'Mark Twain'},
        {integerValue: 75},
      ],
    },
  ],
};

async function deIdentifyTableConditionalCharMasking() {
  // Column that needs to be transformed
  const fieldIds = [{name: 'HAPPINESS SCORE'}];

  // Construct PrimitiveTransformation configuration
  const primitiveTransformation = {
    characterMaskConfig: {
      maskingCharacter: '*',
    },
  };

  // Construct condition
  const condition = {
    expressions: {
      conditions: {
        conditions: [
          {
            field: {name: 'AGE'},
            operator: 'GREATER_THAN',
            value: {integerValue: 89},
          },
        ],
      },
    },
  };

  // Construct RecordTransformations configurations
  const recordTransformations = {
    fieldTransformations: [
      {
        primitiveTransformation,
        fields: fieldIds,
        condition,
      },
    ],
  };

  // Combine configurations into a request for the service.
  const request = {
    parent: `projects/${projectId}/locations/global`,
    item: {
      table: tablularData,
    },
    deidentifyConfig: {
      recordTransformations,
    },
  };
  // Send the request and receive response from the service
  const [response] = await dlp.deidentifyContent(request);

  // Print the results
  console.log(
    `Table after de-identification: ${JSON.stringify(response.item.table)}`
  );
}

deIdentifyTableConditionalCharMasking();

PHP

如要瞭解如何安裝及使用 Sensitive Data Protection 的用戶端程式庫，請參閱「Sensitive Data Protection 用戶端程式庫」。

如要向 Sensitive Data Protection 進行驗證，請設定應用程式預設憑證。詳情請參閱「為本機開發環境設定驗證機制」。

use Google\Cloud\Dlp\V2\CharacterMaskConfig;
use Google\Cloud\Dlp\V2\Client\DlpServiceClient;
use Google\Cloud\Dlp\V2\ContentItem;
use Google\Cloud\Dlp\V2\DeidentifyConfig;
use Google\Cloud\Dlp\V2\DeidentifyContentRequest;
use Google\Cloud\Dlp\V2\FieldId;
use Google\Cloud\Dlp\V2\FieldTransformation;
use Google\Cloud\Dlp\V2\PrimitiveTransformation;
use Google\Cloud\Dlp\V2\RecordCondition;
use Google\Cloud\Dlp\V2\RecordCondition\Condition;
use Google\Cloud\Dlp\V2\RecordCondition\Conditions;
use Google\Cloud\Dlp\V2\RecordCondition\Expressions;
use Google\Cloud\Dlp\V2\RecordTransformations;
use Google\Cloud\Dlp\V2\RelationalOperator;
use Google\Cloud\Dlp\V2\Table;
use Google\Cloud\Dlp\V2\Table\Row;
use Google\Cloud\Dlp\V2\Value;

/**
 * De-identify table data using masking and conditional logic.
 * Transform a column based on the value of another column.
 *
 * @param string $callingProjectId      The Google Cloud project id to use as a parent resource.
 * @param string $inputCsvFile          The input file(csv) path  to deidentify
 * @param string $outputCsvFile         The oupt file path to save deidentify content
 */

function deidentify_table_condition_masking(
    // TODO(developer): Replace sample parameters before running the code.
    string $callingProjectId,
    string $inputCsvFile = './test/data/table2.csv',
    string $outputCsvFile = './test/data/deidentify_table_condition_masking_output.csv'
): void {
    // Instantiate a client.
    $dlp = new DlpServiceClient();

    $parent = "projects/$callingProjectId/locations/global";

    // Read a CSV file
    $csvLines = file($inputCsvFile, FILE_IGNORE_NEW_LINES);
    $csvHeaders = explode(',', $csvLines[0]);
    $csvRows = array_slice($csvLines, 1);

    // Convert CSV file into protobuf objects
    $tableHeaders = array_map(function ($csvHeader) {
        return (new FieldId)
            ->setName($csvHeader);
    }, $csvHeaders);

    $tableRows = array_map(function ($csvRow) {
        $rowValues = array_map(function ($csvValue) {
            return (new Value())
                ->setStringValue($csvValue);
        }, explode(',', $csvRow));
        return (new Row())
            ->setValues($rowValues);
    }, $csvRows);

    // Construct the table object
    $tableToDeIdentify = (new Table())
        ->setHeaders($tableHeaders)
        ->setRows($tableRows);

    // Specify what content you want the service to de-identify.
    $content = (new ContentItem())
        ->setTable($tableToDeIdentify);

    // Specify how the content should be de-identified.
    $characterMaskConfig = (new CharacterMaskConfig())
        ->setMaskingCharacter('*');
    $primitiveTransformation = (new PrimitiveTransformation())
        ->setCharacterMaskConfig($characterMaskConfig);

    // Specify field to be de-identified.
    $fieldId = (new FieldId())
        ->setName('HAPPINESS_SCORE');

    // Specify when the above fields should be de-identified.
    $condition = (new Condition())
        ->setField((new FieldId())
            ->setName('AGE'))
        ->setOperator(RelationalOperator::GREATER_THAN)
        ->setValue((new Value())
            ->setIntegerValue(89));

    // Apply the condition to records
    $recordCondition = (new RecordCondition())
        ->setExpressions((new Expressions())
                ->setConditions((new Conditions())
                        ->setConditions([$condition])
                )
        );

    // Associate the de-identification and conditions with the specified fields.
    $fieldTransformation = (new FieldTransformation())
        ->setPrimitiveTransformation($primitiveTransformation)
        ->setFields([$fieldId])
        ->setCondition($recordCondition);

    $recordtransformations = (new RecordTransformations())
        ->setFieldTransformations([$fieldTransformation]);

    $deidentifyConfig = (new DeidentifyConfig())
        ->setRecordTransformations($recordtransformations);

    // Run request
    $deidentifyContentRequest = (new DeidentifyContentRequest())
        ->setParent($parent)
        ->setDeidentifyConfig($deidentifyConfig)
        ->setItem($content);
    $response = $dlp->deidentifyContent($deidentifyContentRequest);

    // Print results
    $csvRef = fopen($outputCsvFile, 'w');
    fputcsv($csvRef, $csvHeaders);
    foreach ($response->getItem()->getTable()->getRows() as $tableRow) {
        $values = array_map(function ($tableValue) {
            return $tableValue->getStringValue();
        }, iterator_to_array($tableRow->getValues()));
        fputcsv($csvRef, $values);
    };
    printf('After de-identify the table data (Output File Location): %s', $outputCsvFile);
}

Python

如要瞭解如何安裝及使用 Sensitive Data Protection 的用戶端程式庫，請參閱「Sensitive Data Protection 用戶端程式庫」。

如要向 Sensitive Data Protection 進行驗證，請設定應用程式預設憑證。詳情請參閱「為本機開發環境設定驗證機制」。

from typing import Dict, List, Union

import google.cloud.dlp
from google.cloud.dlp_v2 import types


def deidentify_table_condition_masking(
    project: str,
    table_data: Dict[str, Union[List[str], List[List[str]]]],
    deid_content_list: List[str],
    condition_field: str = None,
    condition_operator: str = None,
    condition_value: int = None,
    masking_character: str = None,
) -> types.dlp.Table:
    """ Uses the Data Loss Prevention API to de-identify sensitive data in a
      table by masking them based on a condition.

    Args:
        project: The Google Cloud project id to use as a parent resource.
        table_data: Json string representing table data.
        deid_content_list: A list of fields in table to de-identify.
        condition_field: A table Field within the record this condition is evaluated against.
        condition_operator: Operator used to compare the field or infoType to the value. One of:
            RELATIONAL_OPERATOR_UNSPECIFIED, EQUAL_TO, NOT_EQUAL_TO, GREATER_THAN, LESS_THAN, GREATER_THAN_OR_EQUALS,
            LESS_THAN_OR_EQUALS, EXISTS.
        condition_value: Value to compare against. [Mandatory, except for ``EXISTS`` tests.].
        masking_character: The character to mask matching sensitive data with.

    Returns:
        De-identified table is returned;
        the response from the API is also printed to the terminal.

    Example:
    >> $ python deidentify_table_condition_masking.py \
    '{"header": ["email", "phone number", "age", "happiness_score"],
    "rows": [["robertfrost@example.com", "4232342345", "35", "21"],
    ["johndoe@example.com", "4253458383", "64", "34"]]}' \
    ["happiness_score"] "age" "GREATER_THAN" 50
    >> '{"header": ["email", "phone number", "age", "happiness_score"],
        "rows": [["robertfrost@example.com", "4232342345", "35", "21"],
        ["johndoe@example.com", "4253458383", "64", "**"]]}'
    """

    # Instantiate a client.
    dlp = google.cloud.dlp_v2.DlpServiceClient()

    # Construct the `table`. For more details on the table schema, please see
    # https://cloud.google.com/dlp/docs/reference/rest/v2/ContentItem#Table
    headers = [{"name": val} for val in table_data["header"]]
    rows = []
    for row in table_data["rows"]:
        rows.append({"values": [{"string_value": cell_val} for cell_val in row]})

    table = {"headers": headers, "rows": rows}

    # Construct the `item`
    item = {"table": table}

    # Specify fields to be de-identified
    deid_content_list = [{"name": _i} for _i in deid_content_list]

    # Construct condition list
    condition = [
        {
            "field": {"name": condition_field},
            "operator": condition_operator,
            "value": {"integer_value": condition_value},
        }
    ]

    # Construct deidentify configuration dictionary
    deidentify_config = {
        "record_transformations": {
            "field_transformations": [
                {
                    "primitive_transformation": {
                        "character_mask_config": {
                            "masking_character": masking_character
                        }
                    },
                    "fields": deid_content_list,
                    "condition": {
                        "expressions": {"conditions": {"conditions": condition}}
                    },
                }
            ]
        }
    }

    # Convert the project id into a full resource id.
    parent = f"projects/{project}/locations/global"

    # Call the API.
    response = dlp.deidentify_content(
        request={"parent": parent, "deidentify_config": deidentify_config, "item": item}
    )

    # Print the result
    print(f"Table after de-identification: {response.item.table}")

    # Return the response
    return response.item.table

API Explorer 範例

"deidentifyConfig":{
  "recordTransformations":{
    "fieldTransformations":[
      {
        "fields":[
          {
            "name":"HAPPINESS SCORE"
          }
        ],
        "primitiveTransformation":{
          "characterMaskConfig":{
            "maskingCharacter":"*"
          }
        },
        "condition":{
          "expressions":{
            "conditions":{
              "conditions":[
                {
                  "field":{
                    "name":"AGE"
                  },
                  "operator":"GREATER_THAN",
                  "value":{
                    "integerValue":"89"
                  }
                }
              ]
            }
          }
        }
      }
    ]
  }
}

轉換資料欄中的發現項目

您可以轉換只佔儲存格內容一部分或全部的發現。在本例中，PERSON_NAME 的所有執行個體都會經過匿名化處理。

輸入

轉換後的表格

年齡	PATIENT	快樂指數	FACTOID
101	查爾斯．狄更斯	95	查爾斯．狄更斯的名字是詛咒，可能是莎士比亞發明的。
22	珍奧斯汀	21	珍奧斯汀的小說中共有 14 個吻。
55	馬克吐溫	75	馬克吐溫很喜歡貓。

年齡	PATIENT	快樂指數	FACTOID
101	[PERSON_NAME]	95	[PERSON_NAME] 這個名字是詛咒，可能是莎士比亞發明的。
22	[PERSON_NAME]	21	[PERSON_NAME] 的小說中有 14 個吻。
55	[PERSON_NAME]	75	[PERSON_NAME] 很喜歡貓。

C#

如要瞭解如何安裝及使用 Sensitive Data Protection 的用戶端程式庫，請參閱「Sensitive Data Protection 用戶端程式庫」。

如要向 Sensitive Data Protection 進行驗證，請設定應用程式預設憑證。詳情請參閱「為本機開發環境設定驗證機制」。


using System;
using System.Collections.Generic;
using Google.Api.Gax.ResourceNames;
using Google.Cloud.Dlp.V2;

public class DeidentifyTableWithInfoTypes
{
    public static Table DeidentifyTable(
        string projectId,
        Table tableToInspect = null,
        IEnumerable<InfoType> infoTypes = null)
    {
        // Instantiate a client.
        var dlp = DlpServiceClient.Create();

        // Construct the table if null.
        if (tableToInspect == null)
        {
            var row1 = new Value[]
            {
                new Value { StringValue = "101" },
                new Value { StringValue = "Charles Dickens" },
                new Value { StringValue = "95" },
                new Value { StringValue = "Charles Dickens name was a curse invented by Shakespeare." }
            };
            var row2 = new Value[]
            {
                new Value { StringValue = "22" },
                new Value { StringValue = "Jane Austin" },
                new Value { StringValue = "21" },
                new Value { StringValue = "There are 14 kisses in Jane Austen's novels." }
            };
            var row3 = new Value[]
            {
                new Value { StringValue = "55" },
                new Value { StringValue = "Mark Twain" },
                new Value { StringValue = "75" },
                new Value { StringValue = "Mark Twain loved cats." }
            };

            tableToInspect = new Table
            {
                Headers =
                {
                    new FieldId { Name = "AGE" },
                    new FieldId { Name = "PATIENT" },
                    new FieldId { Name = "HAPPINESS SCORE" },
                    new FieldId { Name = "FACTOID" }
                },
                Rows =
                {
                    new Table.Types.Row { Values = { row1 } },
                    new Table.Types.Row { Values = { row2 } },
                    new Table.Types.Row { Values = { row3 } }
                }
            };
        }

        // Construct the table content item.
        var contentItem = new ContentItem { Table = tableToInspect };

        // Construct Replace With InfoTypes config to replace the match.
        var replaceInfoTypesConfig = new ReplaceWithInfoTypeConfig();

        // Construct Fields to be de-identified.
        var fieldIds = new FieldId[] { new FieldId { Name = "PATIENT" }, new FieldId { Name = "FACTOID" } };

        // Construct InfoType Transformation.
        var infoTypeTransformations = new InfoTypeTransformations
        {
            Transformations =
            {
                new InfoTypeTransformations.Types.InfoTypeTransformation
                {
                    PrimitiveTransformation = new PrimitiveTransformation
                    {
                        ReplaceWithInfoTypeConfig = replaceInfoTypesConfig
                    },
                    InfoTypes = { infoTypes ?? new InfoType[] { new InfoType { Name = "PERSON_NAME" } } }
                }
            }
        };

        // Construct the de-identify config using replace config.
        var deidentifyConfig = new DeidentifyConfig
        {
            RecordTransformations = new RecordTransformations
            {
                FieldTransformations =
                {
                    new FieldTransformation
                    {
                        InfoTypeTransformations = infoTypeTransformations,
                        Fields = { fieldIds }
                    }
                }
            }
        };

        // Construct the request.
        var request = new DeidentifyContentRequest
        {
            ParentAsLocationName = new LocationName(projectId, "global"),
            DeidentifyConfig = deidentifyConfig,
            Item = contentItem
        };

        // Call the API.
        var response = dlp.DeidentifyContent(request);

        // Inspect the response.
        Console.WriteLine(response.Item.Table);
        return response.Item.Table;
    }
}

Go

如要瞭解如何安裝及使用 Sensitive Data Protection 的用戶端程式庫，請參閱「Sensitive Data Protection 用戶端程式庫」。

如要向 Sensitive Data Protection 進行驗證，請設定應用程式預設憑證。詳情請參閱「為本機開發環境設定驗證機制」。

import (
	"context"
	"fmt"
	"io"

	dlp "cloud.google.com/go/dlp/apiv2"
	"cloud.google.com/go/dlp/apiv2/dlppb"
)

// deidentifyTableInfotypes de-identifies table data with info types
func deidentifyTableInfotypes(w io.Writer, projectID string) error {
	// projectId := "your-project-id"

	row1 := &dlppb.Table_Row{
		Values: []*dlppb.Value{
			{Type: &dlppb.Value_StringValue{StringValue: "22"}},
			{Type: &dlppb.Value_StringValue{StringValue: "Jane Austen"}},
			{Type: &dlppb.Value_StringValue{StringValue: "21"}},
			{Type: &dlppb.Value_StringValue{StringValue: "There are 14 kisses in Jane Austen's novels."}},
		},
	}

	row2 := &dlppb.Table_Row{
		Values: []*dlppb.Value{
			{Type: &dlppb.Value_StringValue{StringValue: "55"}},
			{Type: &dlppb.Value_StringValue{StringValue: "Mark Twain"}},
			{Type: &dlppb.Value_StringValue{StringValue: "75"}},
			{Type: &dlppb.Value_StringValue{StringValue: "Mark Twain loved cats."}},
		},
	}

	row3 := &dlppb.Table_Row{
		Values: []*dlppb.Value{
			{Type: &dlppb.Value_StringValue{StringValue: "101"}},
			{Type: &dlppb.Value_StringValue{StringValue: "Charles Dickens"}},
			{Type: &dlppb.Value_StringValue{StringValue: "95"}},
			{Type: &dlppb.Value_StringValue{StringValue: "Charles Dickens name was a curse invented by Shakespeare."}},
		},
	}

	table := &dlppb.Table{
		Headers: []*dlppb.FieldId{
			{Name: "AGE"},
			{Name: "PATIENT"},
			{Name: "HAPPINESS SCORE"},
			{Name: "FACTOID"},
		},
		Rows: []*dlppb.Table_Row{
			{Values: row1.Values},
			{Values: row2.Values},
			{Values: row3.Values},
		},
	}

	ctx := context.Background()

	// Initialize a client once and reuse it to send multiple requests. Clients
	// are safe to use across goroutines. When the client is no longer needed,
	// call the Close method to cleanup its resources.
	client, err := dlp.NewRESTClient(ctx)
	if err != nil {
		return err
	}

	// Closing the client safely cleans up background resources.
	defer client.Close()

	// Specify what content you want the service to de-identify.
	contentItem := &dlppb.ContentItem{
		DataItem: &dlppb.ContentItem_Table{
			Table: table,
		},
	}

	// Specify how the content should be de-identified.
	// Select type of info to be replaced.
	infoTypes := []*dlppb.InfoType{
		{Name: "PERSON_NAME"},
	}

	// Specify that findings should be replaced with corresponding info type name.
	replaceWithInfoTypeConfig := &dlppb.ReplaceWithInfoTypeConfig{}
	primitiveTransformation := &dlppb.PrimitiveTransformation{
		Transformation: &dlppb.PrimitiveTransformation_ReplaceWithInfoTypeConfig{
			ReplaceWithInfoTypeConfig: replaceWithInfoTypeConfig,
		},
	}

	// Associate info type with the replacement strategy
	infoTypeTransformations := &dlppb.InfoTypeTransformations{
		Transformations: []*dlppb.InfoTypeTransformations_InfoTypeTransformation{
			{
				InfoTypes:               infoTypes,
				PrimitiveTransformation: primitiveTransformation,
			},
		},
	}

	// Specify fields to be de-identified.
	fields := []*dlppb.FieldId{
		{Name: "PATIENT"},
		{Name: "FACTOID"},
	}

	// Associate the de-identification and conditions with the specified field.
	fieldTransformation := &dlppb.FieldTransformation{
		Fields: fields,
		Transformation: &dlppb.FieldTransformation_InfoTypeTransformations{
			InfoTypeTransformations: infoTypeTransformations,
		},
	}

	recordTransformations := &dlppb.RecordTransformations{
		FieldTransformations: []*dlppb.FieldTransformation{
			fieldTransformation,
		},
	}

	// Construct the de-identification request to be sent by the client.
	req := &dlppb.DeidentifyContentRequest{
		Parent: fmt.Sprintf("projects/%s/locations/global", projectID),
		DeidentifyConfig: &dlppb.DeidentifyConfig{
			Transformation: &dlppb.DeidentifyConfig_RecordTransformations{
				RecordTransformations: recordTransformations,
			},
		},
		Item: contentItem,
	}

	// Send the request.
	resp, err := client.DeidentifyContent(ctx, req)
	if err != nil {
		return err
	}

	// Print the results.
	fmt.Fprintf(w, "Table after de-identification : %v", resp.GetItem().GetTable())
	return nil
}

Java

如要瞭解如何安裝及使用 Sensitive Data Protection 的用戶端程式庫，請參閱「Sensitive Data Protection 用戶端程式庫」。

如要向 Sensitive Data Protection 進行驗證，請設定應用程式預設憑證。詳情請參閱「為本機開發環境設定驗證機制」。


import com.google.cloud.dlp.v2.DlpServiceClient;
import com.google.privacy.dlp.v2.ContentItem;
import com.google.privacy.dlp.v2.DeidentifyConfig;
import com.google.privacy.dlp.v2.DeidentifyContentRequest;
import com.google.privacy.dlp.v2.DeidentifyContentResponse;
import com.google.privacy.dlp.v2.FieldId;
import com.google.privacy.dlp.v2.FieldTransformation;
import com.google.privacy.dlp.v2.InfoType;
import com.google.privacy.dlp.v2.InfoTypeTransformations;
import com.google.privacy.dlp.v2.InfoTypeTransformations.InfoTypeTransformation;
import com.google.privacy.dlp.v2.LocationName;
import com.google.privacy.dlp.v2.PrimitiveTransformation;
import com.google.privacy.dlp.v2.RecordTransformations;
import com.google.privacy.dlp.v2.ReplaceWithInfoTypeConfig;
import com.google.privacy.dlp.v2.Table;
import com.google.privacy.dlp.v2.Table.Row;
import com.google.privacy.dlp.v2.Value;
import java.io.IOException;
import java.util.List;
import java.util.stream.Collectors;
import java.util.stream.Stream;

public class DeIdentifyTableInfoTypes {

  public static void main(String[] args) throws IOException {
    // TODO(developer): Replace these variables before running the sample.
    String projectId = "your-project-id";
    Table tableToDeIdentify =
        Table.newBuilder()
            .addHeaders(FieldId.newBuilder().setName("AGE").build())
            .addHeaders(FieldId.newBuilder().setName("PATIENT").build())
            .addHeaders(FieldId.newBuilder().setName("HAPPINESS SCORE").build())
            .addHeaders(FieldId.newBuilder().setName("FACTOID").build())
            .addRows(
                Row.newBuilder()
                    .addValues(Value.newBuilder().setStringValue("101").build())
                    .addValues(Value.newBuilder().setStringValue("Charles Dickens").build())
                    .addValues(Value.newBuilder().setStringValue("95").build())
                    .addValues(
                        Value.newBuilder()
                            .setStringValue(
                                "Charles Dickens name was a curse invented by Shakespeare.")
                            .build())
                    .build())
            .addRows(
                Row.newBuilder()
                    .addValues(Value.newBuilder().setStringValue("22").build())
                    .addValues(Value.newBuilder().setStringValue("Jane Austen").build())
                    .addValues(Value.newBuilder().setStringValue("21").build())
                    .addValues(
                        Value.newBuilder()
                            .setStringValue("There are 14 kisses in Jane Austen's novels.")
                            .build())
                    .build())
            .addRows(
                Row.newBuilder()
                    .addValues(Value.newBuilder().setStringValue("55").build())
                    .addValues(Value.newBuilder().setStringValue("Mark Twain").build())
                    .addValues(Value.newBuilder().setStringValue("75").build())
                    .addValues(Value.newBuilder().setStringValue("Mark Twain loved cats.").build())
                    .build())
            .build();

    deIdentifyTableInfoTypes(projectId, tableToDeIdentify);
  }

  public static Table deIdentifyTableInfoTypes(String projectId, Table tableToDeIdentify)
      throws IOException {
    // Initialize client that will be used to send requests. This client only needs to be created
    // once, and can be reused for multiple requests. After completing all of your requests, call
    // the "close" method on the client to safely clean up any remaining background resources.
    try (DlpServiceClient dlp = DlpServiceClient.create()) {
      // Specify what content you want the service to de-identify.
      ContentItem contentItem = ContentItem.newBuilder().setTable(tableToDeIdentify).build();

      // Specify how the content should be de-identified.
      // Select type of info to be replaced.
      InfoType infoType = InfoType.newBuilder().setName("PERSON_NAME").build();
      // Specify that findings should be replaced with corresponding info type name.
      ReplaceWithInfoTypeConfig replaceWithInfoTypeConfig =
          ReplaceWithInfoTypeConfig.getDefaultInstance();
      PrimitiveTransformation primitiveTransformation =
          PrimitiveTransformation.newBuilder()
              .setReplaceWithInfoTypeConfig(replaceWithInfoTypeConfig)
              .build();
      // Associate info type with the replacement strategy
      InfoTypeTransformation infoTypeTransformation =
          InfoTypeTransformation.newBuilder()
              .addInfoTypes(infoType)
              .setPrimitiveTransformation(primitiveTransformation)
              .build();
      InfoTypeTransformations infoTypeTransformations =
          InfoTypeTransformations.newBuilder().addTransformations(infoTypeTransformation).build();

      // Specify fields to be de-identified.
      List<FieldId> fieldIds =
          Stream.of("PATIENT", "FACTOID")
              .map(id -> FieldId.newBuilder().setName(id).build())
              .collect(Collectors.toList());

      // Associate the de-identification and conditions with the specified field.
      FieldTransformation fieldTransformation =
          FieldTransformation.newBuilder()
              .setInfoTypeTransformations(infoTypeTransformations)
              .addAllFields(fieldIds)
              .build();
      RecordTransformations transformations =
          RecordTransformations.newBuilder().addFieldTransformations(fieldTransformation).build();

      DeidentifyConfig deidentifyConfig =
          DeidentifyConfig.newBuilder().setRecordTransformations(transformations).build();

      // Combine configurations into a request for the service.
      DeidentifyContentRequest request =
          DeidentifyContentRequest.newBuilder()
              .setParent(LocationName.of(projectId, "global").toString())
              .setItem(contentItem)
              .setDeidentifyConfig(deidentifyConfig)
              .build();

      // Send the request and receive response from the service.
      DeidentifyContentResponse response = dlp.deidentifyContent(request);

      // Print the results.
      System.out.println("Table after de-identification: " + response.getItem().getTable());

      return response.getItem().getTable();
    }
  }
}

Node.js

如要瞭解如何安裝及使用 Sensitive Data Protection 的用戶端程式庫，請參閱「Sensitive Data Protection 用戶端程式庫」。

如要向 Sensitive Data Protection 進行驗證，請設定應用程式預設憑證。詳情請參閱「為本機開發環境設定驗證機制」。

// Imports the Google Cloud Data Loss Prevention library
const DLP = require('@google-cloud/dlp');

// Initialize google DLP Client
const dlp = new DLP.DlpServiceClient();

// The project ID to run the API call under
// const projectId = 'my-project';

// Construct the tabular data
const tablularData = {
  headers: [
    {name: 'AGE'},
    {name: 'PATIENT'},
    {name: 'HAPPINESS SCORE'},
    {name: 'FACTOID'},
  ],
  rows: [
    {
      values: [
        {integerValue: 101},
        {stringValue: 'Charles Dickens'},
        {integerValue: 95},
        {
          stringValue:
            'Charles Dickens name was a curse invented by Shakespeare.',
        },
      ],
    },
    {
      values: [
        {integerValue: 22},
        {stringValue: 'Jane Austen'},
        {integerValue: 21},
        {stringValue: "There are 14 kisses in Jane Austen's novels."},
      ],
    },
    {
      values: [
        {integerValue: 55},
        {stringValue: 'Mark Twain'},
        {integerValue: 75},
        {stringValue: 'Mark Twain loved cats.'},
      ],
    },
  ],
};

async function deIdentifyTableWithInfoType() {
  // Column that needs to be transformed
  const fieldIds = [{name: 'PATIENT'}, {name: 'FACTOID'}];

  // Construct InfoTypeTransformations configurations
  const infoTypeTransformations = {
    transformations: [
      {
        infoTypes: [{name: 'PERSON_NAME'}],
        primitiveTransformation: {
          replaceWithInfoTypeConfig: {},
        },
      },
    ],
  };

  // Combine configurations into a request for the service.
  const request = {
    parent: `projects/${projectId}/locations/global`,
    item: {
      table: tablularData,
    },
    deidentifyConfig: {
      recordTransformations: {
        fieldTransformations: [
          {
            infoTypeTransformations,
            fields: fieldIds,
          },
        ],
      },
    },
  };
  // Send the request and receive response from the service
  const [response] = await dlp.deidentifyContent(request);

  // Print the results
  console.log(
    `Table after de-identification: ${JSON.stringify(response.item.table)}`
  );
}

deIdentifyTableWithInfoType();

PHP

如要瞭解如何安裝及使用 Sensitive Data Protection 的用戶端程式庫，請參閱「Sensitive Data Protection 用戶端程式庫」。

如要向 Sensitive Data Protection 進行驗證，請設定應用程式預設憑證。詳情請參閱「為本機開發環境設定驗證機制」。

use Google\Cloud\Dlp\V2\Client\DlpServiceClient;
use Google\Cloud\Dlp\V2\ContentItem;
use Google\Cloud\Dlp\V2\DeidentifyConfig;
use Google\Cloud\Dlp\V2\DeidentifyContentRequest;
use Google\Cloud\Dlp\V2\FieldId;
use Google\Cloud\Dlp\V2\FieldTransformation;
use Google\Cloud\Dlp\V2\InfoType;
use Google\Cloud\Dlp\V2\InfoTypeTransformations;
use Google\Cloud\Dlp\V2\InfoTypeTransformations\InfoTypeTransformation;
use Google\Cloud\Dlp\V2\PrimitiveTransformation;
use Google\Cloud\Dlp\V2\RecordTransformations;
use Google\Cloud\Dlp\V2\ReplaceWithInfoTypeConfig;
use Google\Cloud\Dlp\V2\Table;
use Google\Cloud\Dlp\V2\Table\Row;
use Google\Cloud\Dlp\V2\Value;

/**
 * De-identify table data with infoTypes
 *
 * @param string $callingProjectId      The Google Cloud project id to use as a parent resource.
 * @param string $inputCsvFile          The input file(csv) path  to deidentify
 * @param string $outputCsvFile         The oupt file path to save deidentify content
 */

function deidentify_table_infotypes(
    // TODO(developer): Replace sample parameters before running the code.
    string $callingProjectId,
    string $inputCsvFile = './test/data/table1.csv',
    string $outputCsvFile = './test/data/deidentify_table_infotypes_output.csv'
): void {
    // Instantiate a client.
    $dlp = new DlpServiceClient();

    $parent = "projects/$callingProjectId/locations/global";

    // Read a CSV file
    $csvLines = file($inputCsvFile, FILE_IGNORE_NEW_LINES);
    $csvHeaders = explode(',', $csvLines[0]);
    $csvRows = array_slice($csvLines, 1);

    // Convert CSV file into protobuf objects
    $tableHeaders = array_map(function ($csvHeader) {
        return (new FieldId)
            ->setName($csvHeader);
    }, $csvHeaders);

    $tableRows = array_map(function ($csvRow) {
        $rowValues = array_map(function ($csvValue) {
            return (new Value())
                ->setStringValue($csvValue);
        }, explode(',', $csvRow));
        return (new Row())
            ->setValues($rowValues);
    }, $csvRows);

    // Construct the table object
    $tableToDeIdentify = (new Table())
        ->setHeaders($tableHeaders)
        ->setRows($tableRows);

    // Specify the content to be inspected.
    $content = (new ContentItem())
        ->setTable($tableToDeIdentify);

    // Specify the type of info the inspection will look for.
    $personNameInfoType = (new InfoType())
        ->setName('PERSON_NAME');

    // Specify that findings should be replaced with corresponding info type name.
    $primitiveTransformation = (new PrimitiveTransformation())
        ->setReplaceWithInfoTypeConfig(new ReplaceWithInfoTypeConfig());

    // Associate info type with the replacement strategy
    $infoTypeTransformation = (new InfoTypeTransformation())
        ->setPrimitiveTransformation($primitiveTransformation)
        ->setInfoTypes([$personNameInfoType]);

    $infoTypeTransformations = (new InfoTypeTransformations())
        ->setTransformations([$infoTypeTransformation]);

    // Specify fields to be de-identified.
    $fieldIds = [
        (new FieldId())->setName('PATIENT'),
        (new FieldId())->setName('FACTOID'),
    ];

    // Associate the de-identification and transformation with the specified fields.
    $fieldTransformation = (new FieldTransformation())
        ->setInfoTypeTransformations($infoTypeTransformations)
        ->setFields($fieldIds);

    $recordtransformations = (new RecordTransformations())
        ->setFieldTransformations([$fieldTransformation]);

    $deidentifyConfig = (new DeidentifyConfig())
        ->setRecordTransformations($recordtransformations);

    // Run request
    $deidentifyContentRequest = (new DeidentifyContentRequest())
        ->setParent($parent)
        ->setDeidentifyConfig($deidentifyConfig)
        ->setItem($content);
    $response = $dlp->deidentifyContent($deidentifyContentRequest);

    // Print the results
    $csvRef = fopen($outputCsvFile, 'w');
    fputcsv($csvRef, $csvHeaders);
    foreach ($response->getItem()->getTable()->getRows() as $tableRow) {
        $values = array_map(function ($tableValue) {
            return $tableValue->getStringValue();
        }, iterator_to_array($tableRow->getValues()));
        fputcsv($csvRef, $values);
    };
    printf('After de-identify the table data (Output File Location): %s', $outputCsvFile);
}

Python

如要瞭解如何安裝及使用 Sensitive Data Protection 的用戶端程式庫，請參閱「Sensitive Data Protection 用戶端程式庫」。

如要向 Sensitive Data Protection 進行驗證，請設定應用程式預設憑證。詳情請參閱「為本機開發環境設定驗證機制」。

from typing import Dict, List, Union

import google.cloud.dlp


def deidentify_table_replace_with_info_types(
    project: str,
    table_data: Dict[str, Union[List[str], List[List[str]]]],
    info_types: List[str],
    deid_content_list: List[str],
) -> None:
    """ Uses the Data Loss Prevention API to de-identify sensitive data in a
      table by replacing them with info type.

    Args:
        project: The Google Cloud project id to use as a parent resource.
        table_data: Json string representing table data.
        info_types: A list of strings representing info types to look for.
            A full list of info type categories can be fetched from the API.
        deid_content_list: A list of fields in table to de-identify

    Returns:
        None; the response from the API is printed to the terminal.

    Example:
    >> $ python deidentify_table_infotypes.py \
    '{
        "header": ["name", "email", "phone number"],
        "rows": [
            ["Robert Frost", "robertfrost@example.com", "4232342345"],
            ["John Doe", "johndoe@example.com", "4253458383"]
        ]
    }' \
    ["PERSON_NAME"] ["name"]
    >> '{
            "header": ["name", "email", "phone number"],
            "rows": [
                ["[PERSON_NAME]", "robertfrost@example.com", "4232342345"],
                ["[PERSON_NAME]", "johndoe@example.com", "4253458383"]
            ]
        }'
    """

    # Instantiate a client.
    dlp = google.cloud.dlp_v2.DlpServiceClient()

    # Construct the `table`. For more details on the table schema, please see
    # https://cloud.google.com/dlp/docs/reference/rest/v2/ContentItem#Table
    headers = [{"name": val} for val in table_data["header"]]
    rows = []
    for row in table_data["rows"]:
        rows.append({"values": [{"string_value": cell_val} for cell_val in row]})

    table = {"headers": headers, "rows": rows}

    # Construct item
    item = {"table": table}

    # Specify fields to be de-identified
    deid_content_list = [{"name": _i} for _i in deid_content_list]

    # Construct inspect configuration dictionary
    inspect_config = {"info_types": [{"name": info_type} for info_type in info_types]}

    # Construct deidentify configuration dictionary
    deidentify_config = {
        "record_transformations": {
            "field_transformations": [
                {
                    "info_type_transformations": {
                        "transformations": [
                            {
                                "primitive_transformation": {
                                    "replace_with_info_type_config": {}
                                }
                            }
                        ]
                    },
                    "fields": deid_content_list,
                }
            ]
        }
    }

    # Convert the project id into a full resource id.
    parent = f"projects/{project}/locations/global"

    # Call the API.
    response = dlp.deidentify_content(
        request={
            "parent": parent,
            "deidentify_config": deidentify_config,
            "item": item,
            "inspect_config": inspect_config,
        }
    )

    # Print the result
    print(f"Table after de-identification: {response.item.table}")

APIs Explorer 範例

"deidentifyConfig":{
  "recordTransformations":{
    "fieldTransformations":[
      {
        "infoTypeTransformations":{
          "transformations":[
            {
              "infoTypes":[
                {
                  "name":"PERSON_NAME"
                }
              ],
              "primitiveTransformation":{
                "replaceWithInfoTypeConfig":{

                }
              }
            }
          ]
        },
        "fields":[
          {
            "name":"PATIENT"
          },
          {
            "name":"FACTOID"
          }
        ]
      }
    ]
  }
}

根據資料欄內容隱藏資料列

您可以根據任何資料欄中顯示的內容，完全移除資料列。這個範例會隱藏「Charles Dickens」的記錄，因為這位病患年滿 89 歲。

輸入

轉換後的表格

年齡	PATIENT	快樂指數
101	查爾斯．狄更斯	95
22	珍奧斯汀	21
55	馬克吐溫	75

年齡	PATIENT	快樂指數
22	珍奧斯汀	21
55	馬克吐溫	75

C#

如要瞭解如何安裝及使用 Sensitive Data Protection 的用戶端程式庫，請參閱「Sensitive Data Protection 用戶端程式庫」。

如要向 Sensitive Data Protection 進行驗證，請設定應用程式預設憑證。詳情請參閱「為本機開發環境設定驗證機制」。


using System;
using Google.Api.Gax.ResourceNames;
using Google.Cloud.Dlp.V2;

public class DeidentifyTableWithRowSuppress
{
    public static Table DeidentifyTable(
        string projectId,
        Table tableToInspect = null)
    {
        // Instantiate a client.
        var dlp = DlpServiceClient.Create();

        // Construct the table if null.
        if (tableToInspect == null)
        {
            var row1 = new Value[]
            {
                new Value { StringValue = "101" },
                new Value { StringValue = "Charles Dickens" },
                new Value { StringValue = "95" }
            };
            var row2 = new Value[]
            {
                new Value { StringValue = "22" },
                new Value { StringValue = "Jane Austin" },
                new Value { StringValue = "21" }
            };
            var row3 = new Value[]
            {
                new Value { StringValue = "55" },
                new Value { StringValue = "Mark Twain" },
                new Value { StringValue = "75" }
            };

            tableToInspect = new Table
            {
                Headers =
                {
                    new FieldId { Name = "AGE" },
                    new FieldId { Name = "PATIENT" },
                    new FieldId { Name = "HAPPINESS SCORE" }
                },
                Rows =
                {
                    new Table.Types.Row { Values = { row1 } },
                    new Table.Types.Row { Values = { row2 } },
                    new Table.Types.Row { Values = { row3 } }
                }
            };
        }

        // Construct the byte content item.
        var contentItem = new ContentItem { Table = tableToInspect };

        // Construct the conditions.
        var conditions = new RecordCondition.Types.Conditions
        {
            Conditions_ =
            {
                new RecordCondition.Types.Condition
                {
                    Field = new FieldId { Name = "AGE" },
                    Operator = RelationalOperator.GreaterThan,
                    Value = new Value { IntegerValue = 89 }
                }
            }
        };

        // Construct the deidentify config using the record suppression and conditions.
        var deidentifyConfig = new DeidentifyConfig
        {
            RecordTransformations = new RecordTransformations
            {
                RecordSuppressions =
                {
                    new RecordSuppression
                    {
                        Condition = new RecordCondition
                        {
                            Expressions = new RecordCondition.Types.Expressions
                            {
                                Conditions = conditions
                            }
                        }
                    }
                }
            }
        };

        // Construct the request.
        var request = new DeidentifyContentRequest
        {
            ParentAsLocationName = new LocationName(projectId, "global"),
            DeidentifyConfig = deidentifyConfig,
            Item = contentItem
        };

        // Call the API.
        var response = dlp.DeidentifyContent(request);

        // Inspect the response.
        Console.WriteLine(response.Item.Table);
        return response.Item.Table;
    }
}

Go

如要瞭解如何安裝及使用 Sensitive Data Protection 的用戶端程式庫，請參閱「Sensitive Data Protection 用戶端程式庫」。

如要向 Sensitive Data Protection 進行驗證，請設定應用程式預設憑證。詳情請參閱「為本機開發環境設定驗證機制」。

import (
	"context"
	"fmt"
	"io"

	dlp "cloud.google.com/go/dlp/apiv2"
	"cloud.google.com/go/dlp/apiv2/dlppb"
)

// deidentifyTableRowSuppress de-identifies table data and
// suppress a row based on the content of column
func deidentifyTableRowSuppress(w io.Writer, projectID string) error {
	// projectId := "your-project-id"

	row1 := &dlppb.Table_Row{
		Values: []*dlppb.Value{
			{Type: &dlppb.Value_StringValue{StringValue: "22"}},
			{Type: &dlppb.Value_StringValue{StringValue: "Jane Austen"}},
			{Type: &dlppb.Value_StringValue{StringValue: "21"}},
		},
	}

	row2 := &dlppb.Table_Row{
		Values: []*dlppb.Value{
			{Type: &dlppb.Value_StringValue{StringValue: "55"}},
			{Type: &dlppb.Value_StringValue{StringValue: "Mark Twain"}},
			{Type: &dlppb.Value_StringValue{StringValue: "75"}},
		},
	}

	row3 := &dlppb.Table_Row{
		Values: []*dlppb.Value{
			{Type: &dlppb.Value_StringValue{StringValue: "101"}},
			{Type: &dlppb.Value_StringValue{StringValue: "Charles Dickens"}},
			{Type: &dlppb.Value_StringValue{StringValue: "95"}},
		},
	}

	table := &dlppb.Table{
		Headers: []*dlppb.FieldId{
			{Name: "AGE"},
			{Name: "PATIENT"},
			{Name: "HAPPINESS SCORE"},
		},
		Rows: []*dlppb.Table_Row{
			{Values: row1.Values},
			{Values: row2.Values},
			{Values: row3.Values},
		},
	}

	ctx := context.Background()

	// Initialize a client once and reuse it to send multiple requests. Clients
	// are safe to use across goroutines. When the client is no longer needed,
	// call the Close method to cleanup its resources.
	client, err := dlp.NewClient(ctx)
	if err != nil {
		return err
	}

	// Closing the client safely cleans up background resources.
	defer client.Close()

	// Specify what content you want the service to de-identify.
	contentItem := &dlppb.ContentItem{
		DataItem: &dlppb.ContentItem_Table{
			Table: table,
		},
	}

	// Apply the condition to record suppression.
	condition := &dlppb.RecordCondition{
		Expressions: &dlppb.RecordCondition_Expressions{
			Type: &dlppb.RecordCondition_Expressions_Conditions{
				Conditions: &dlppb.RecordCondition_Conditions{
					Conditions: []*dlppb.RecordCondition_Condition{
						{
							Field:    &dlppb.FieldId{Name: "AGE"},
							Operator: dlppb.RelationalOperator_GREATER_THAN,
							Value: &dlppb.Value{
								Type: &dlppb.Value_IntegerValue{IntegerValue: 89},
							},
						},
					},
				},
			},
		},
	}
	recordSupression := &dlppb.RecordSuppression{
		Condition: condition,
	}

	// Use record suppression as the only transformation
	recordTransformations := &dlppb.RecordTransformations{
		RecordSuppressions: []*dlppb.RecordSuppression{
			recordSupression,
		},
	}

	// Construct the de-identification request to be sent by the client.
	req := &dlppb.DeidentifyContentRequest{
		Parent: fmt.Sprintf("projects/%s/locations/global", projectID),
		DeidentifyConfig: &dlppb.DeidentifyConfig{
			Transformation: &dlppb.DeidentifyConfig_RecordTransformations{
				RecordTransformations: recordTransformations,
			},
		},
		Item: contentItem,
	}

	// Send the request.
	resp, err := client.DeidentifyContent(ctx, req)
	if err != nil {
		return err
	}

	// Print the results.
	fmt.Fprintf(w, "Table after de-identification : %v", resp.GetItem().GetTable())
	return nil
}

Java

如要瞭解如何安裝及使用 Sensitive Data Protection 的用戶端程式庫，請參閱「Sensitive Data Protection 用戶端程式庫」。

如要向 Sensitive Data Protection 進行驗證，請設定應用程式預設憑證。詳情請參閱「為本機開發環境設定驗證機制」。


import com.google.cloud.dlp.v2.DlpServiceClient;
import com.google.privacy.dlp.v2.ContentItem;
import com.google.privacy.dlp.v2.DeidentifyConfig;
import com.google.privacy.dlp.v2.DeidentifyContentRequest;
import com.google.privacy.dlp.v2.DeidentifyContentResponse;
import com.google.privacy.dlp.v2.FieldId;
import com.google.privacy.dlp.v2.LocationName;
import com.google.privacy.dlp.v2.RecordCondition;
import com.google.privacy.dlp.v2.RecordCondition.Condition;
import com.google.privacy.dlp.v2.RecordCondition.Conditions;
import com.google.privacy.dlp.v2.RecordCondition.Expressions;
import com.google.privacy.dlp.v2.RecordSuppression;
import com.google.privacy.dlp.v2.RecordTransformations;
import com.google.privacy.dlp.v2.RelationalOperator;
import com.google.privacy.dlp.v2.Table;
import com.google.privacy.dlp.v2.Table.Row;
import com.google.privacy.dlp.v2.Value;
import java.io.IOException;

public class DeIdentifyTableRowSuppress {

  public static void main(String[] args) throws IOException {
    // TODO(developer): Replace these variables before running the sample.
    String projectId = "your-project-id";
    Table tableToDeIdentify =
        Table.newBuilder()
            .addHeaders(FieldId.newBuilder().setName("AGE").build())
            .addHeaders(FieldId.newBuilder().setName("PATIENT").build())
            .addHeaders(FieldId.newBuilder().setName("HAPPINESS SCORE").build())
            .addRows(
                Row.newBuilder()
                    .addValues(Value.newBuilder().setStringValue("101").build())
                    .addValues(Value.newBuilder().setStringValue("Charles Dickens").build())
                    .addValues(Value.newBuilder().setStringValue("95").build())
                    .build())
            .addRows(
                Row.newBuilder()
                    .addValues(Value.newBuilder().setStringValue("22").build())
                    .addValues(Value.newBuilder().setStringValue("Jane Austen").build())
                    .addValues(Value.newBuilder().setStringValue("21").build())
                    .build())
            .addRows(
                Row.newBuilder()
                    .addValues(Value.newBuilder().setStringValue("55").build())
                    .addValues(Value.newBuilder().setStringValue("Mark Twain").build())
                    .addValues(Value.newBuilder().setStringValue("75").build())
                    .build())
            .build();

    deIdentifyTableRowSuppress(projectId, tableToDeIdentify);
  }

  public static Table deIdentifyTableRowSuppress(String projectId, Table tableToDeIdentify)
      throws IOException {
    // Initialize client that will be used to send requests. This client only needs to be created
    // once, and can be reused for multiple requests. After completing all of your requests, call
    // the "close" method on the client to safely clean up any remaining background resources.
    try (DlpServiceClient dlp = DlpServiceClient.create()) {
      // Specify what content you want the service to de-identify.
      ContentItem contentItem = ContentItem.newBuilder().setTable(tableToDeIdentify).build();

      // Specify when the content should be de-identified.
      Condition condition =
          Condition.newBuilder()
              .setField(FieldId.newBuilder().setName("AGE").build())
              .setOperator(RelationalOperator.GREATER_THAN)
              .setValue(Value.newBuilder().setIntegerValue(89).build())
              .build();
      // Apply the condition to record suppression.
      RecordSuppression recordSuppressions =
          RecordSuppression.newBuilder()
              .setCondition(
                  RecordCondition.newBuilder()
                      .setExpressions(
                          Expressions.newBuilder()
                              .setConditions(
                                  Conditions.newBuilder().addConditions(condition).build())
                              .build())
                      .build())
              .build();
      // Use record suppression as the only transformation
      RecordTransformations transformations =
          RecordTransformations.newBuilder().addRecordSuppressions(recordSuppressions).build();

      DeidentifyConfig deidentifyConfig =
          DeidentifyConfig.newBuilder().setRecordTransformations(transformations).build();

      // Combine configurations into a request for the service.
      DeidentifyContentRequest request =
          DeidentifyContentRequest.newBuilder()
              .setParent(LocationName.of(projectId, "global").toString())
              .setItem(contentItem)
              .setDeidentifyConfig(deidentifyConfig)
              .build();

      // Send the request and receive response from the service.
      DeidentifyContentResponse response = dlp.deidentifyContent(request);

      // Print the results.
      System.out.println("Table after de-identification: " + response.getItem().getTable());

      return response.getItem().getTable();
    }
  }
}

Node.js

如要瞭解如何安裝及使用 Sensitive Data Protection 的用戶端程式庫，請參閱「Sensitive Data Protection 用戶端程式庫」。

如要向 Sensitive Data Protection 進行驗證，請設定應用程式預設憑證。詳情請參閱「為本機開發環境設定驗證機制」。

// Imports the Google Cloud Data Loss Prevention library
const DLP = require('@google-cloud/dlp');

// Initialize google DLP Client
const dlp = new DLP.DlpServiceClient();

// The project ID to run the API call under
// const projectId = 'my-project';

// Construct the tabular data
const tablularData = {
  headers: [{name: 'AGE'}, {name: 'PATIENT'}, {name: 'HAPPINESS SCORE'}],
  rows: [
    {
      values: [
        {integerValue: 101},
        {stringValue: 'Charles Dickens'},
        {integerValue: 95},
      ],
    },
    {
      values: [
        {integerValue: 22},
        {stringValue: 'Jane Austen'},
        {integerValue: 21},
      ],
    },
    {
      values: [
        {integerValue: 55},
        {stringValue: 'Mark Twain'},
        {integerValue: 75},
      ],
    },
  ],
};
async function deIdentifyTableRowSuppress() {
  // Specify when the content should be de-identified.
  const condition = {
    expressions: {
      conditions: {
        conditions: [
          {
            field: {name: 'AGE'},
            operator: 'GREATER_THAN',
            value: {integerValue: 89},
          },
        ],
      },
    },
  };

  // Apply the condition to record suppression.
  const recordTransformations = {
    recordSuppressions: [
      {
        condition,
      },
    ],
  };

  // Combine configurations into a request for the service.
  const request = {
    parent: `projects/${projectId}/locations/global`,
    item: {
      table: tablularData,
    },
    deidentifyConfig: {
      recordTransformations,
    },
  };

  // Send the request and receive response from the service.
  const [response] = await dlp.deidentifyContent(request);

  // Print the results.
  console.log(
    `Table after de-identification: ${JSON.stringify(response.item.table)}`
  );
}

deIdentifyTableRowSuppress();

PHP

如要瞭解如何安裝及使用 Sensitive Data Protection 的用戶端程式庫，請參閱「Sensitive Data Protection 用戶端程式庫」。

如要向 Sensitive Data Protection 進行驗證，請設定應用程式預設憑證。詳情請參閱「為本機開發環境設定驗證機制」。

use Google\Cloud\Dlp\V2\Client\DlpServiceClient;
use Google\Cloud\Dlp\V2\ContentItem;
use Google\Cloud\Dlp\V2\DeidentifyConfig;
use Google\Cloud\Dlp\V2\DeidentifyContentRequest;
use Google\Cloud\Dlp\V2\FieldId;
use Google\Cloud\Dlp\V2\RecordCondition;
use Google\Cloud\Dlp\V2\RecordCondition\Condition;
use Google\Cloud\Dlp\V2\RecordCondition\Conditions;
use Google\Cloud\Dlp\V2\RecordCondition\Expressions;
use Google\Cloud\Dlp\V2\RecordSuppression;
use Google\Cloud\Dlp\V2\RecordTransformations;
use Google\Cloud\Dlp\V2\RelationalOperator;
use Google\Cloud\Dlp\V2\Table;
use Google\Cloud\Dlp\V2\Table\Row;
use Google\Cloud\Dlp\V2\Value;

/**
 * De-identify table data: Suppress a row based on the content of a column
 * Suppress a row based on the content of a column. You can remove a row entirely based on the content that appears in any column. This example suppresses the record for "Charles Dickens," as this patient is over 89 years old.
 *
 * @param string $callingProjectId      The Google Cloud project id to use as a parent resource.
 * @param string $inputCsvFile          The input file(csv) path  to deidentify
 * @param string $outputCsvFile         The oupt file path to save deidentify content */

function deidentify_table_row_suppress(
    // TODO(developer): Replace sample parameters before running the code.
    string $callingProjectId,
    string $inputCsvFile = './test/data/table2.csv',
    string $outputCsvFile = './test/data/deidentify_table_row_suppress_output.csv'
): void {
    // Instantiate a client.
    $dlp = new DlpServiceClient();

    $parent = "projects/$callingProjectId/locations/global";

    // Read a CSV file
    $csvLines = file($inputCsvFile, FILE_IGNORE_NEW_LINES);
    $csvHeaders = explode(',', $csvLines[0]);
    $csvRows = array_slice($csvLines, 1);

    // Convert CSV file into protobuf objects
    $tableHeaders = array_map(function ($csvHeader) {
        return (new FieldId)
            ->setName($csvHeader);
    }, $csvHeaders);

    $tableRows = array_map(function ($csvRow) {
        $rowValues = array_map(function ($csvValue) {
            return (new Value())
                ->setStringValue($csvValue);
        }, explode(',', $csvRow));
        return (new Row())
            ->setValues($rowValues);
    }, $csvRows);

    // Construct the table object
    $tableToDeIdentify = (new Table())
        ->setHeaders($tableHeaders)
        ->setRows($tableRows);

    // Specify what content you want the service to de-identify.
    $content = (new ContentItem())
        ->setTable($tableToDeIdentify);

    // Specify when the content should be de-identified.
    $condition = (new Condition())
        ->setField((new FieldId())
            ->setName('AGE'))
        ->setOperator(RelationalOperator::GREATER_THAN)
        ->setValue((new Value())
            ->setIntegerValue(89));

    // Apply the condition to record suppression.
    $recordSuppressions = (new RecordSuppression())
        ->setCondition((new RecordCondition())
                ->setExpressions((new Expressions())
                        ->setConditions((new Conditions())
                                ->setConditions([$condition])
                        )
                )
        );

    // Use record suppression as the only transformation
    $recordtransformations = (new RecordTransformations())
        ->setRecordSuppressions([$recordSuppressions]);

    // Create the deidentification configuration object
    $deidentifyConfig = (new DeidentifyConfig())
        ->setRecordTransformations($recordtransformations);

    // Run request
    $deidentifyContentRequest = (new DeidentifyContentRequest())
        ->setParent($parent)
        ->setDeidentifyConfig($deidentifyConfig)
        ->setItem($content);
    $response = $dlp->deidentifyContent($deidentifyContentRequest);

    // Print the results
    $csvRef = fopen($outputCsvFile, 'w');
    fputcsv($csvRef, $csvHeaders);
    foreach ($response->getItem()->getTable()->getRows() as $tableRow) {
        $values = array_map(function ($tableValue) {
            return $tableValue->getStringValue();
        }, iterator_to_array($tableRow->getValues()));
        fputcsv($csvRef, $values);
    };
    printf($outputCsvFile);
}

Python

如要瞭解如何安裝及使用 Sensitive Data Protection 的用戶端程式庫，請參閱「Sensitive Data Protection 用戶端程式庫」。

如要向 Sensitive Data Protection 進行驗證，請設定應用程式預設憑證。詳情請參閱「為本機開發環境設定驗證機制」。

from typing import Dict, List, Union

import google.cloud.dlp


def deidentify_table_suppress_row(
    project: str,
    table_data: Dict[str, Union[List[str], List[List[str]]]],
    condition_field: str,
    condition_operator: str,
    condition_value: int,
) -> None:
    """ Uses the Data Loss Prevention API to de-identify sensitive data in a
      table by suppressing entire row/s based on a condition.

    Args:
        project: The Google Cloud project id to use as a parent resource.
        table_data: Dictionary representing table data.
        condition_field: A table field within the record this condition is evaluated against.
        condition_operator: Operator used to compare the field or infoType to the value. One of:
            RELATIONAL_OPERATOR_UNSPECIFIED, EQUAL_TO, NOT_EQUAL_TO, GREATER_THAN, LESS_THAN, GREATER_THAN_OR_EQUALS,
            LESS_THAN_OR_EQUALS, EXISTS.
        condition_value: Value to compare against. [Mandatory, except for ``EXISTS`` tests.].

    Example:

    >> $ python deidentify_table_row_suppress.py \
    '{"header": ["email", "phone number", "age"],
    "rows": [["robertfrost@example.com", "4232342345", "35"],
    ["johndoe@example.com", "4253458383", "64"]]}' \
    "age" "GREATER_THAN" 50
    >> '{"header": ["email", "phone number", "age"],
        "rows": [["robertfrost@example.com", "4232342345", "35", "21"]]}'
    """

    # Instantiate a client.
    dlp = google.cloud.dlp_v2.DlpServiceClient()

    # Construct the `table`. For more details on the table schema, please see
    # https://cloud.google.com/dlp/docs/reference/rest/v2/ContentItem#Table
    headers = [{"name": val} for val in table_data["header"]]
    rows = []
    for row in table_data["rows"]:
        rows.append({"values": [{"string_value": cell_val} for cell_val in row]})

    table = {"headers": headers, "rows": rows}

    # Construct the `item` containing the table data.
    item = {"table": table}

    # Construct condition list.
    condition = [
        {
            "field": {"name": condition_field},
            "operator": condition_operator,
            "value": {"integer_value": condition_value},
        }
    ]

    # Construct deidentify configuration dictionary
    deidentify_config = {
        "record_transformations": {
            "record_suppressions": [
                {
                    "condition": {
                        "expressions": {"conditions": {"conditions": condition}}
                    }
                }
            ]
        }
    }

    # Convert the project id into a full resource id.
    parent = f"projects/{project}/locations/global"

    # Call the API.
    response = dlp.deidentify_content(
        request={"parent": parent, "deidentify_config": deidentify_config, "item": item}
    )

    # Print the result.
    print(f"Table after de-identification: {response.item.table}")

APIs Explorer 範例

"deidentifyConfig":{
  "recordTransformations":{
    "recordSuppressions":[
      {
        "condition":{
          "expressions":{
            "conditions":{
              "conditions":[
                {
                  "field":{
                    "name":"AGE"
                  },
                  "operator":"GREATER_THAN",
                  "value":{
                    "integerValue":"89"
                  }
                }
              ]
            }
          }
        }
      }
    ]
  }
}

只有在另一個欄位符合特定條件時，才轉換發現項目

在本例中，只有在「AGE」欄指出病患年齡超過 89 歲時，PERSON_NAME 發現才會遭到編輯。

輸入

轉換後的表格

年齡	PATIENT	快樂指數	FACTOID
101	查爾斯．狄更斯	95	查爾斯．狄更斯的名字是詛咒，可能是莎士比亞發明的。
22	珍奧斯汀	21	珍奧斯汀的小說中共有 14 個吻。
55	馬克吐溫	75	馬克吐溫很喜歡貓。

年齡	PATIENT	快樂指數	FACTOID
101	[PERSON_NAME]	95	[PERSON_NAME] 這個名字是詛咒，可能是 [PERSON_NAME] 發明的。
22	珍奧斯汀	21	珍奧斯汀的小說中共有 14 個吻。
55	馬克吐溫	75	馬克吐溫很喜歡貓。

C#

如要瞭解如何安裝及使用 Sensitive Data Protection 的用戶端程式庫，請參閱「Sensitive Data Protection 用戶端程式庫」。

如要向 Sensitive Data Protection 進行驗證，請設定應用程式預設憑證。詳情請參閱「為本機開發環境設定驗證機制」。


using System;
using System.Collections.Generic;
using Google.Api.Gax.ResourceNames;
using Google.Cloud.Dlp.V2;

public class DeidentifyTableUsingLogicInfoTypes
{
    public static Table Deidentify(
        string projectId,
        Table tableToInspect = null,
        IEnumerable<InfoType> infoTypes = null)
    {
        // Instantiate the dlp client.
        var dlp = DlpServiceClient.Create();

        // Construct the table if null.
        if (tableToInspect == null)
        {
            var row1 = new Value[]
            {
                new Value { StringValue = "101" },
                new Value { StringValue = "Charles Dickens" },
                new Value { StringValue = "95" },
                new Value { StringValue = "Charles Dickens name was a curse invented by Shakespeare." }
            };
            var row2 = new Value[]
            {
                new Value { StringValue = "22" },
                new Value { StringValue = "Jane Austin" },
                new Value { StringValue = "21" },
                new Value { StringValue = "There are 14 kisses in Jane Austen's novels." }
            };
            var row3 = new Value[]
            {
                new Value { StringValue = "55" },
                new Value { StringValue = "Mark Twain" },
                new Value { StringValue = "75" },
                new Value { StringValue = "Mark Twain loved cats." }
            };

            tableToInspect = new Table
            {
                Headers =
                {
                    new FieldId { Name = "AGE" },
                    new FieldId { Name = "PATIENT" },
                    new FieldId { Name = "HAPPINESS SCORE" },
                    new FieldId { Name = "FACTOID" }
                },
                Rows =
                {
                    new Table.Types.Row { Values = { row1 } },
                    new Table.Types.Row { Values = { row2 } },
                    new Table.Types.Row { Values = { row3 } }
                }
            };
        }

        // Construct the table content item.
        var contentItem = new ContentItem { Table = tableToInspect };

        // Specify that findings should be replaced with corresponding info type name.
        var infoTypeTransformation = new InfoTypeTransformations
        {
            Transformations =
            {
                new InfoTypeTransformations.Types.InfoTypeTransformation
                {
                    InfoTypes = { infoTypes ?? new InfoType[] { new InfoType { Name = "PERSON_NAME" } } },
                    PrimitiveTransformation = new PrimitiveTransformation
                    {
                        ReplaceWithInfoTypeConfig = new ReplaceWithInfoTypeConfig()
                    }
                }
            }
        };

        // Specify the fields to be de-identified.
        var fields = new FieldId[] { new FieldId { Name = "PATIENT" }, new FieldId { Name = "FACTOID" } };

        // Specify when the above fields should be de-identified using condition.
        var condition = new RecordCondition.Types.Conditions
        {
            Conditions_ =
            {
                new RecordCondition.Types.Condition
                {
                    Field = new FieldId { Name = "AGE" },
                    Operator = RelationalOperator.GreaterThan,
                    Value = new Value { IntegerValue = 89 }
                }
            }
        };

        // Apply the condition to records.
        var recordCondition = new RecordCondition
        {
            Expressions = new RecordCondition.Types.Expressions
            {
                Conditions = condition
            }
        };

        // Associate the de-identification and conditions with the specified fields.
        var deidentifiedConfig = new DeidentifyConfig
        {
            RecordTransformations = new RecordTransformations
            {
                FieldTransformations =
                {
                    new FieldTransformation
                    {
                        InfoTypeTransformations = infoTypeTransformation,
                        Fields = { fields },
                        Condition = recordCondition
                    }
                }
            }
        };

        // Construct the request.
        var request = new DeidentifyContentRequest
        {
            ParentAsLocationName = new LocationName(projectId, "global"),
            DeidentifyConfig = deidentifiedConfig,
            Item = contentItem
        };

        // Call the API.
        var response = dlp.DeidentifyContent(request);

        // Inspect the response.
        Console.WriteLine(response.Item.Table);
        return response.Item.Table;
    }
}

Go

如要瞭解如何安裝及使用 Sensitive Data Protection 的用戶端程式庫，請參閱「Sensitive Data Protection 用戶端程式庫」。

如要向 Sensitive Data Protection 進行驗證，請設定應用程式預設憑證。詳情請參閱「為本機開發環境設定驗證機制」。

import (
	"context"
	"fmt"
	"io"

	dlp "cloud.google.com/go/dlp/apiv2"
	"cloud.google.com/go/dlp/apiv2/dlppb"
)

// deidentifyTableConditionInfoTypes de-identifies table data
// using conditional logic and replace with infoTypes
func deidentifyTableConditionInfoTypes(w io.Writer, projectID string, columnNames []string) error {
	// projectId := "your-project-id"
	// columnNames := []string{"PATIENT", "FACTOID"}

	row1 := &dlppb.Table_Row{
		Values: []*dlppb.Value{
			{Type: &dlppb.Value_StringValue{StringValue: "22"}},
			{Type: &dlppb.Value_StringValue{StringValue: "Jane Austen"}},
			{Type: &dlppb.Value_StringValue{StringValue: "21"}},
			{Type: &dlppb.Value_StringValue{StringValue: "There are 14 kisses in Jane Austen's novels."}},
		},
	}

	row2 := &dlppb.Table_Row{
		Values: []*dlppb.Value{
			{Type: &dlppb.Value_StringValue{StringValue: "55"}},
			{Type: &dlppb.Value_StringValue{StringValue: "Mark Twain"}},
			{Type: &dlppb.Value_StringValue{StringValue: "75"}},
			{Type: &dlppb.Value_StringValue{StringValue: "Mark Twain loved cats."}},
		},
	}

	row3 := &dlppb.Table_Row{
		Values: []*dlppb.Value{
			{Type: &dlppb.Value_StringValue{StringValue: "101"}},
			{Type: &dlppb.Value_StringValue{StringValue: "Charles Dickens"}},
			{Type: &dlppb.Value_StringValue{StringValue: "95"}},
			{Type: &dlppb.Value_StringValue{StringValue: "Charles Dickens name was a curse invented by Shakespeare."}},
		},
	}

	table := &dlppb.Table{
		Headers: []*dlppb.FieldId{
			{Name: "AGE"},
			{Name: "PATIENT"},
			{Name: "HAPPINESS SCORE"},
			{Name: "FACTOID"},
		},
		Rows: []*dlppb.Table_Row{
			{Values: row1.Values},
			{Values: row2.Values},
			{Values: row3.Values},
		},
	}

	ctx := context.Background()

	// Initialize a client once and reuse it to send multiple requests. Clients
	// are safe to use across goroutines. When the client is no longer needed,
	// call the Close method to cleanup its resources.
	client, err := dlp.NewClient(ctx)
	if err != nil {
		return err
	}

	// Closing the client safely cleans up background resources.
	defer client.Close()

	// Specify what content you want the service to de-identify.
	contentItem := &dlppb.ContentItem{
		DataItem: &dlppb.ContentItem_Table{
			Table: table,
		},
	}

	// Specify how the content should be de-identified.
	// Select type of info to be replaced.
	infoTypes := []*dlppb.InfoType{
		{Name: "PERSON_NAME"},
	}

	// Specify that findings should be replaced with corresponding info type name.
	primitiveTransformation := &dlppb.PrimitiveTransformation{
		Transformation: &dlppb.PrimitiveTransformation_ReplaceWithInfoTypeConfig{},
	}

	// Associate info type with the replacement strategy
	infoTypeTransformation := &dlppb.InfoTypeTransformations_InfoTypeTransformation{
		InfoTypes:               infoTypes,
		PrimitiveTransformation: primitiveTransformation,
	}

	infoTypeTransformations := &dlppb.InfoTypeTransformations{
		Transformations: []*dlppb.InfoTypeTransformations_InfoTypeTransformation{
			infoTypeTransformation,
		},
	}

	// Specify fields to be de-identified.
	var f []*dlppb.FieldId
	for _, c := range columnNames {
		f = append(f, &dlppb.FieldId{Name: c})
	}

	// Specify when the above fields should be de-identified.
	condition := &dlppb.RecordCondition{
		Expressions: &dlppb.RecordCondition_Expressions{
			Type: &dlppb.RecordCondition_Expressions_Conditions{
				Conditions: &dlppb.RecordCondition_Conditions{
					Conditions: []*dlppb.RecordCondition_Condition{
						{
							Field: &dlppb.FieldId{
								Name: "AGE",
							},
							Operator: dlppb.RelationalOperator_GREATER_THAN,
							Value: &dlppb.Value{
								Type: &dlppb.Value_IntegerValue{
									IntegerValue: 89,
								},
							},
						},
					},
				},
			},
		},
	}

	// Associate the de-identification and conditions with the specified fields.
	fieldTransformation := &dlppb.FieldTransformation{
		Fields:    f,
		Condition: condition,
		Transformation: &dlppb.FieldTransformation_InfoTypeTransformations{
			InfoTypeTransformations: infoTypeTransformations,
		},
	}

	recordTransformations := &dlppb.RecordTransformations{
		FieldTransformations: []*dlppb.FieldTransformation{
			fieldTransformation,
		},
	}

	// Construct the de-identification request to be sent by the client.
	req := &dlppb.DeidentifyContentRequest{
		Parent: fmt.Sprintf("projects/%s/locations/global", projectID),
		DeidentifyConfig: &dlppb.DeidentifyConfig{
			Transformation: &dlppb.DeidentifyConfig_RecordTransformations{
				RecordTransformations: recordTransformations,
			},
		},
		Item: contentItem,
	}

	// Send the request.
	resp, err := client.DeidentifyContent(ctx, req)
	if err != nil {
		return err
	}

	// Print the results.
	fmt.Fprintf(w, "Table after de-identification : %v", resp.GetItem().GetTable())
	return nil

}

Java

如要瞭解如何安裝及使用 Sensitive Data Protection 的用戶端程式庫，請參閱「Sensitive Data Protection 用戶端程式庫」。

如要向 Sensitive Data Protection 進行驗證，請設定應用程式預設憑證。詳情請參閱「為本機開發環境設定驗證機制」。


import com.google.cloud.dlp.v2.DlpServiceClient;
import com.google.privacy.dlp.v2.ContentItem;
import com.google.privacy.dlp.v2.DeidentifyConfig;
import com.google.privacy.dlp.v2.DeidentifyContentRequest;
import com.google.privacy.dlp.v2.DeidentifyContentResponse;
import com.google.privacy.dlp.v2.FieldId;
import com.google.privacy.dlp.v2.FieldTransformation;
import com.google.privacy.dlp.v2.InfoType;
import com.google.privacy.dlp.v2.InfoTypeTransformations;
import com.google.privacy.dlp.v2.InfoTypeTransformations.InfoTypeTransformation;
import com.google.privacy.dlp.v2.LocationName;
import com.google.privacy.dlp.v2.PrimitiveTransformation;
import com.google.privacy.dlp.v2.RecordCondition;
import com.google.privacy.dlp.v2.RecordCondition.Condition;
import com.google.privacy.dlp.v2.RecordCondition.Conditions;
import com.google.privacy.dlp.v2.RecordCondition.Expressions;
import com.google.privacy.dlp.v2.RecordTransformations;
import com.google.privacy.dlp.v2.RelationalOperator;
import com.google.privacy.dlp.v2.ReplaceWithInfoTypeConfig;
import com.google.privacy.dlp.v2.Table;
import com.google.privacy.dlp.v2.Table.Row;
import com.google.privacy.dlp.v2.Value;
import java.io.IOException;
import java.util.List;
import java.util.stream.Collectors;
import java.util.stream.Stream;

public class DeIdentifyTableConditionInfoTypes {

  public static void main(String[] args) throws IOException {
    // TODO(developer): Replace these variables before running the sample.
    String projectId = "your-project-id";
    Table tableToDeIdentify =
        Table.newBuilder()
            .addHeaders(FieldId.newBuilder().setName("AGE").build())
            .addHeaders(FieldId.newBuilder().setName("PATIENT").build())
            .addHeaders(FieldId.newBuilder().setName("HAPPINESS SCORE").build())
            .addHeaders(FieldId.newBuilder().setName("FACTOID").build())
            .addRows(
                Row.newBuilder()
                    .addValues(Value.newBuilder().setStringValue("101").build())
                    .addValues(Value.newBuilder().setStringValue("Charles Dickens").build())
                    .addValues(Value.newBuilder().setStringValue("95").build())
                    .addValues(
                        Value.newBuilder()
                            .setStringValue(
                                "Charles Dickens name was a curse invented by Shakespeare.")
                            .build())
                    .build())
            .addRows(
                Row.newBuilder()
                    .addValues(Value.newBuilder().setStringValue("22").build())
                    .addValues(Value.newBuilder().setStringValue("Jane Austen").build())
                    .addValues(Value.newBuilder().setStringValue("21").build())
                    .addValues(
                        Value.newBuilder()
                            .setStringValue("There are 14 kisses in Jane Austen's novels.")
                            .build())
                    .build())
            .addRows(
                Row.newBuilder()
                    .addValues(Value.newBuilder().setStringValue("55").build())
                    .addValues(Value.newBuilder().setStringValue("Mark Twain").build())
                    .addValues(Value.newBuilder().setStringValue("75").build())
                    .addValues(Value.newBuilder().setStringValue("Mark Twain loved cats.").build())
                    .build())
            .build();

    deIdentifyTableConditionInfoTypes(projectId, tableToDeIdentify);
  }

  public static Table deIdentifyTableConditionInfoTypes(String projectId, Table tableToDeIdentify)
      throws IOException {
    // Initialize client that will be used to send requests. This client only needs to be created
    // once, and can be reused for multiple requests. After completing all of your requests, call
    // the "close" method on the client to safely clean up any remaining background resources.
    try (DlpServiceClient dlp = DlpServiceClient.create()) {
      // Specify what content you want the service to de-identify.
      ContentItem contentItem = ContentItem.newBuilder().setTable(tableToDeIdentify).build();

      // Specify how the content should be de-identified.
      // Select type of info to be replaced.
      InfoType infoType = InfoType.newBuilder().setName("PERSON_NAME").build();
      // Specify that findings should be replaced with corresponding info type name.
      ReplaceWithInfoTypeConfig replaceWithInfoTypeConfig =
          ReplaceWithInfoTypeConfig.getDefaultInstance();
      PrimitiveTransformation primitiveTransformation =
          PrimitiveTransformation.newBuilder()
              .setReplaceWithInfoTypeConfig(replaceWithInfoTypeConfig)
              .build();
      // Associate info type with the replacement strategy
      InfoTypeTransformation infoTypeTransformation =
          InfoTypeTransformation.newBuilder()
              .addInfoTypes(infoType)
              .setPrimitiveTransformation(primitiveTransformation)
              .build();
      InfoTypeTransformations infoTypeTransformations =
          InfoTypeTransformations.newBuilder().addTransformations(infoTypeTransformation).build();

      // Specify fields to be de-identified.
      List<FieldId> fieldIds =
          Stream.of("PATIENT", "FACTOID")
              .map(id -> FieldId.newBuilder().setName(id).build())
              .collect(Collectors.toList());

      // Specify when the above fields should be de-identified.
      Condition condition =
          Condition.newBuilder()
              .setField(FieldId.newBuilder().setName("AGE").build())
              .setOperator(RelationalOperator.GREATER_THAN)
              .setValue(Value.newBuilder().setIntegerValue(89).build())
              .build();
      // Apply the condition to records
      RecordCondition recordCondition =
          RecordCondition.newBuilder()
              .setExpressions(
                  Expressions.newBuilder()
                      .setConditions(Conditions.newBuilder().addConditions(condition).build())
                      .build())
              .build();

      // Associate the de-identification and conditions with the specified fields.
      FieldTransformation fieldTransformation =
          FieldTransformation.newBuilder()
              .setInfoTypeTransformations(infoTypeTransformations)
              .addAllFields(fieldIds)
              .setCondition(recordCondition)
              .build();
      RecordTransformations transformations =
          RecordTransformations.newBuilder().addFieldTransformations(fieldTransformation).build();

      DeidentifyConfig deidentifyConfig =
          DeidentifyConfig.newBuilder().setRecordTransformations(transformations).build();

      // Combine configurations into a request for the service.
      DeidentifyContentRequest request =
          DeidentifyContentRequest.newBuilder()
              .setParent(LocationName.of(projectId, "global").toString())
              .setItem(contentItem)
              .setDeidentifyConfig(deidentifyConfig)
              .build();

      // Send the request and receive response from the service.
      DeidentifyContentResponse response = dlp.deidentifyContent(request);

      // Print the results.
      System.out.println("Table after de-identification: " + response.getItem().getTable());

      return response.getItem().getTable();
    }
  }
}

Node.js

如要瞭解如何安裝及使用 Sensitive Data Protection 的用戶端程式庫，請參閱「Sensitive Data Protection 用戶端程式庫」。

如要向 Sensitive Data Protection 進行驗證，請設定應用程式預設憑證。詳情請參閱「為本機開發環境設定驗證機制」。

// Imports the Google Cloud Data Loss Prevention library
const DLP = require('@google-cloud/dlp');

// Initialize google DLP Client
const dlp = new DLP.DlpServiceClient();

// The project ID to run the API call under
// const projectId = 'my-project';

// Construct the tabular data
const tablularData = {
  headers: [
    {name: 'AGE'},
    {name: 'PATIENT'},
    {name: 'HAPPINESS SCORE'},
    {name: 'FACTOID'},
  ],
  rows: [
    {
      values: [
        {integerValue: 101},
        {stringValue: 'Charles Dickens'},
        {integerValue: 95},
        {
          stringValue:
            'Charles Dickens name was a curse invented by Shakespeare.',
        },
      ],
    },
    {
      values: [
        {integerValue: 22},
        {stringValue: 'Jane Austen'},
        {integerValue: 21},
        {stringValue: "There are 14 kisses in Jane Austen's novels."},
      ],
    },
    {
      values: [
        {integerValue: 55},
        {stringValue: 'Mark Twain'},
        {integerValue: 75},
        {stringValue: 'Mark Twain loved cats.'},
      ],
    },
  ],
};

async function deIdentifyTableConditionalInfoType() {
  // Specify fields to be de-identified.
  const fieldIds = [{name: 'PATIENT'}, {name: 'FACTOID'}];

  // Associate info type with the replacement strategy
  const infoTypeTransformations = {
    transformations: [
      {
        infoTypes: [{name: 'PERSON_NAME'}],
        primitiveTransformation: {
          replaceWithInfoTypeConfig: {},
        },
      },
    ],
  };

  // Specify when the above fields should be de-identified.
  const condition = {
    expressions: {
      conditions: {
        conditions: [
          {
            field: {name: 'AGE'},
            operator: 'GREATER_THAN',
            value: {integerValue: 89},
          },
        ],
      },
    },
  };

  // Apply the condition to records.
  const recordTransformations = {
    fieldTransformations: [
      {
        infoTypeTransformations,
        fields: fieldIds,
        condition: condition,
      },
    ],
  };

  // Combine configurations into a request for the service.
  const request = {
    parent: `projects/${projectId}/locations/global`,
    item: {
      table: tablularData,
    },
    deidentifyConfig: {
      recordTransformations,
    },
  };
  // Send the request and receive response from the service.
  const [response] = await dlp.deidentifyContent(request);

  // Print the results.
  console.log(
    `Table after de-identification: ${JSON.stringify(response.item.table)}`
  );
}

deIdentifyTableConditionalInfoType();

PHP

如要瞭解如何安裝及使用 Sensitive Data Protection 的用戶端程式庫，請參閱「Sensitive Data Protection 用戶端程式庫」。

如要向 Sensitive Data Protection 進行驗證，請設定應用程式預設憑證。詳情請參閱「為本機開發環境設定驗證機制」。

use Google\Cloud\Dlp\V2\Client\DlpServiceClient;
use Google\Cloud\Dlp\V2\ContentItem;
use Google\Cloud\Dlp\V2\DeidentifyConfig;
use Google\Cloud\Dlp\V2\DeidentifyContentRequest;
use Google\Cloud\Dlp\V2\FieldId;
use Google\Cloud\Dlp\V2\FieldTransformation;
use Google\Cloud\Dlp\V2\InfoType;
use Google\Cloud\Dlp\V2\InfoTypeTransformations;
use Google\Cloud\Dlp\V2\InfoTypeTransformations\InfoTypeTransformation;
use Google\Cloud\Dlp\V2\PrimitiveTransformation;
use Google\Cloud\Dlp\V2\RecordCondition;
use Google\Cloud\Dlp\V2\RecordCondition\Condition;
use Google\Cloud\Dlp\V2\RecordCondition\Conditions;
use Google\Cloud\Dlp\V2\RecordCondition\Expressions;
use Google\Cloud\Dlp\V2\RecordTransformations;
use Google\Cloud\Dlp\V2\RelationalOperator;
use Google\Cloud\Dlp\V2\ReplaceWithInfoTypeConfig;
use Google\Cloud\Dlp\V2\Table;
use Google\Cloud\Dlp\V2\Table\Row;
use Google\Cloud\Dlp\V2\Value;

/**
 * De-identify table data using conditional logic and replace with infoTypes.
 * Transform findings only when specific conditions are met on another field.
 *
 * @param string $callingProjectId      The Google Cloud project id to use as a parent resource.
 * @param string $inputCsvFile          The input file(csv) path  to deidentify
 * @param string $outputCsvFile         The oupt file path to save deidentify content
 */

function deidentify_table_condition_infotypes(
    // TODO(developer): Replace sample parameters before running the code.
    string $callingProjectId,
    string $inputCsvFile = './test/data/table1.csv',
    string $outputCsvFile = './test/data/deidentify_table_condition_infotypes_output.csv'
): void {
    // Instantiate a client.
    $dlp = new DlpServiceClient();

    $parent = "projects/$callingProjectId/locations/global";

    // Read a CSV file
    $csvLines = file($inputCsvFile, FILE_IGNORE_NEW_LINES);
    $csvHeaders = explode(',', $csvLines[0]);
    $csvRows = array_slice($csvLines, 1);

    // Convert CSV file into protobuf objects
    $tableHeaders = array_map(function ($csvHeader) {
        return (new FieldId)
            ->setName($csvHeader);
    }, $csvHeaders);

    $tableRows = array_map(function ($csvRow) {
        $rowValues = array_map(function ($csvValue) {
            return (new Value())
                ->setStringValue($csvValue);
        }, explode(',', $csvRow));
        return (new Row())
            ->setValues($rowValues);
    }, $csvRows);

    // Construct the table object
    $tableToDeIdentify = (new Table())
        ->setHeaders($tableHeaders)
        ->setRows($tableRows);

    // Specify what content you want the service to de-identify.
    $content = (new ContentItem())
        ->setTable($tableToDeIdentify);

    // Specify the type of info the inspection will look for.
    $personNameInfoType = (new InfoType())
        ->setName('PERSON_NAME');

    // Specify that findings should be replaced with corresponding info type name.
    $primitiveTransformation = (new PrimitiveTransformation())
        ->setReplaceWithInfoTypeConfig(new ReplaceWithInfoTypeConfig());

    // Associate info type with the replacement strategy
    $infoTypeTransformation = (new InfoTypeTransformation())
        ->setPrimitiveTransformation($primitiveTransformation)
        ->setInfoTypes([$personNameInfoType]);

    $infoTypeTransformations = (new InfoTypeTransformations())
        ->setTransformations([$infoTypeTransformation]);

    // Specify fields to be de-identified.
    $fieldIds = [
        (new FieldId())->setName('PATIENT'),
        (new FieldId())->setName('FACTOID'),
    ];

    // Specify when the above fields should be de-identified.
    $condition = (new Condition())
        ->setField((new FieldId())
            ->setName('AGE'))
        ->setOperator(RelationalOperator::GREATER_THAN)
        ->setValue((new Value())
            ->setIntegerValue(89));

    // Apply the condition to records
    $recordCondition = (new RecordCondition())
        ->setExpressions((new Expressions())
                ->setConditions((new Conditions())
                        ->setConditions([$condition])
                )
        );

    // Associate the de-identification and conditions with the specified fields.
    $fieldTransformation = (new FieldTransformation())
        ->setInfoTypeTransformations($infoTypeTransformations)
        ->setFields($fieldIds)
        ->setCondition($recordCondition);

    $recordtransformations = (new RecordTransformations())
        ->setFieldTransformations([$fieldTransformation]);

    $deidentifyConfig = (new DeidentifyConfig())
        ->setRecordTransformations($recordtransformations);

    // Run request
    $deidentifyContentRequest = (new DeidentifyContentRequest())
        ->setParent($parent)
        ->setDeidentifyConfig($deidentifyConfig)
        ->setItem($content);
    $response = $dlp->deidentifyContent($deidentifyContentRequest);

    // Print results
    $csvRef = fopen($outputCsvFile, 'w');
    fputcsv($csvRef, $csvHeaders);
    foreach ($response->getItem()->getTable()->getRows() as $tableRow) {
        $values = array_map(function ($tableValue) {
            return $tableValue->getStringValue();
        }, iterator_to_array($tableRow->getValues()));
        fputcsv($csvRef, $values);
    };
    printf($outputCsvFile);
}

Python

如要瞭解如何安裝及使用 Sensitive Data Protection 的用戶端程式庫，請參閱「Sensitive Data Protection 用戶端程式庫」。

如要向 Sensitive Data Protection 進行驗證，請設定應用程式預設憑證。詳情請參閱「為本機開發環境設定驗證機制」。

from typing import Dict, List, Union

import google.cloud.dlp
from google.cloud.dlp_v2 import types


def deidentify_table_condition_replace_with_info_types(
    project: str,
    table_data: Dict[str, Union[List[str], List[List[str]]]],
    deid_content_list: List[str],
    info_types: List[str],
    condition_field: str = None,
    condition_operator: str = None,
    condition_value: int = None,
) -> types.dlp.Table:
    """Uses the Data Loss Prevention API to de-identify sensitive data in a
    table by replacing them with info-types based on a condition.
    Args:
       project: The Google Cloud project id to use as a parent resource.
       table_data: Json string representing table data.
       deid_content_list: A list of fields in table to de-identify.
       info_types: A list of strings representing info types to look for.
           A full list of info categories and types is available from the API.
           Examples include "FIRST_NAME", "LAST_NAME", "EMAIL_ADDRESS". '
       condition_field: A table field within the record this condition is evaluated against.
       condition_operator: Operator used to compare the field or infoType to the value. One of:
           RELATIONAL_OPERATOR_UNSPECIFIED, EQUAL_TO, NOT_EQUAL_TO, GREATER_THAN, LESS_THAN, GREATER_THAN_OR_EQUALS,
           LESS_THAN_OR_EQUALS, EXISTS.
       condition_value: Value to compare against. [Mandatory, except for ``EXISTS`` tests.].

    Returns:
       De-identified table is returned;
       the response from the API is also printed to the terminal.

    Example:
    >> $ python deidentify_table_condition_infotypes.py \
    '{"header": ["email", "phone number", "age"],
    "rows": [["robertfrost@example.com", "4232342345", "45"],
    ["johndoe@example.com", "4253458383", "63"]]}' ["email"] \
    ["EMAIL_ADDRESS"] "age" "GREATER_THAN" 50
    >> '{"header": ["email", "phone number", "age"],
        "rows": [["robertfrost@example.com", "4232342345", "45"],
        ["[EMAIL_ADDRESS]", "4253458383", "63"]]}'
    """

    # Instantiate a client.
    dlp = google.cloud.dlp_v2.DlpServiceClient()

    # Construct the `table`. For more details on the table schema, please see
    # https://cloud.google.com/dlp/docs/reference/rest/v2/ContentItem#Table
    headers = [{"name": val} for val in table_data["header"]]
    rows = []
    for row in table_data["rows"]:
        rows.append({"values": [{"string_value": cell_val} for cell_val in row]})

    table = {"headers": headers, "rows": rows}

    # Construct the item
    item = {"table": table}

    # Specify fields to be de-identified
    deid_field_list = [{"name": _i} for _i in deid_content_list]

    # Construct inspect configuration dictionary
    inspect_config = {"info_types": [{"name": info_type} for info_type in info_types]}

    # Construct condition list
    condition = [
        {
            "field": {"name": condition_field},
            "operator": condition_operator,
            "value": {"integer_value": condition_value},
        }
    ]

    # Construct deidentify configuration dictionary
    deidentify_config = {
        "record_transformations": {
            "field_transformations": [
                {
                    "info_type_transformations": {
                        "transformations": [
                            {
                                "primitive_transformation": {
                                    "replace_with_info_type_config": {}
                                }
                            }
                        ]
                    },
                    "fields": deid_field_list,
                    "condition": {
                        "expressions": {"conditions": {"conditions": condition}}
                    },
                }
            ]
        }
    }

    # Convert the project id into a full resource id.
    parent = f"projects/{project}/locations/global"

    # Call the API.
    response = dlp.deidentify_content(
        request={
            "parent": parent,
            "deidentify_config": deidentify_config,
            "item": item,
            "inspect_config": inspect_config,
        }
    )

    print(f"Table after de-identification: {response.item.table}")

    return response.item.table

APIs Explorer 範例

"deidentifyConfig":{
  "recordTransformations":{
    "fieldTransformations":[
      {
        "infoTypeTransformations":{
          "transformations":[
            {
              "infoTypes":[
                {
                  "name":"PERSON_NAME"
                }
              ],
              "primitiveTransformation":{
                "replaceWithInfoTypeConfig":{

                }
              }
            }
          ]
        },
        "fields":[
          {
            "name":"PATIENT"
          },
          {
            "name":"FACTOID"
          }
        ],
        "condition":{
          "expressions":{
            "conditions":{
              "conditions":[
                {
                  "field":{
                    "name":"AGE"
                  },
                  "operator":"GREATER_THAN",
                  "value":{
                    "integerValue":"89"
                  }
                }
              ]
            }
          }
        }
      }
    ]
  }
}

使用加密編譯雜湊轉換功能轉換調查結果

下列 JSON 範例使用 infoType 轉換，指示 DLP API 檢查整個表格結構是否含有特定 infoTypes，然後使用暫時性CryptoKey加密相符值。

以下範例說明如何使用密碼編譯雜湊轉換，對兩種 infoType 進行去識別化。

輸入：

userid	留言
user1@example.org	我的電子郵件地址是 user1@example.org，電話號碼是 858-555-0222
user2@example.org	我的電子郵件地址是 user2@example.org，電話號碼是 858-555-0223
user3@example.org	我的電子郵件地址是 user3@example.org，電話號碼是 858-555-0224

轉換後的表格：

userid	留言
1kSfj3Op64MH1BiznupEpX0BdQrHMm62X6abgsPH5zM=	我的電子郵件地址是 1kSfj3Op64MH1BiznupEpX0BdQrHMm62X6abgsPH5zM=，電話號碼是 hYXPcsJNBCe1rr51sHiVw2KhtoyMe4HEFKNHWFcDVm0=
4ESy7+rEN8NVaUJ6J7kwvcgW8wcm0cm5gbBAcu6SfdM=	我的電子郵件地址是 4ESy7+rEN8NVaUJ6J7kwvcgW8wcm0cm5gbBAcu6SfdM=，電話號碼是 KKqW1tQwgvGiC6iWJHhLiz2enNSEFRzhmLOf9fSTxRw=
bu1blyd/mbjLmpF2Rdi6zpgsLatSwpJLVki2fMeudM0=	我的電子郵件地址是 bu1blyd/mbjLmpF2Rdi6zpgsLatSwpJLVki2fMeudM0=，電話號碼是 eNt7qtZVLmxRb8z8NBR/+z00In07CI3hEMStbwofWoc=

APIs Explorer 範例

C#

如要瞭解如何安裝及使用 Sensitive Data Protection 的用戶端程式庫，請參閱「Sensitive Data Protection 用戶端程式庫」。

如要向 Sensitive Data Protection 進行驗證，請設定應用程式預設憑證。詳情請參閱「為本機開發環境設定驗證機制」。


using System;
using System.Collections.Generic;
using Google.Api.Gax.ResourceNames;
using Google.Cloud.Dlp.V2;

public class DeidentifyTableWithCryptoHash
{
    public static Table Deidentify(
        string projectId,
        Table tableToDeidentify = null,
        IEnumerable<InfoType> infoTypes = null,
        string transientKeyName = null)
    {
        // Instantiate the client.
        var dlp = DlpServiceClient.Create();

        // Construct the table if null.
        if (tableToDeidentify == null)
        {
            var row1 = new Value[]
            {
                new Value { StringValue = "user1@example.org" },
                new Value { StringValue = "my email is user1@example.org and phone is 858-555-0222" }
            };
            var row2 = new Value[]
            {
                new Value { StringValue = "user2@example.org" },
                new Value { StringValue = "my email is user2@example.org and phone is 858-555-0223" }
            };
            var row3 = new Value[]
            {
                new Value { StringValue = "user3@example.org" },
                new Value { StringValue = "my email is user3@example.org and phone is 858-555-0224" }
            };

            tableToDeidentify = new Table
            {
                Headers =
                {
                    new FieldId { Name = "User ID" },
                    new FieldId { Name = "comments" }
                },
                Rows =
                {
                    new Table.Types.Row { Values = { row1 } },
                    new Table.Types.Row { Values = { row2 } },
                    new Table.Types.Row { Values = { row3 } }
                }
            };
        }

        // Specify the table and construct the content item.
        var contentItem = new ContentItem { Table = tableToDeidentify };

        // Construct the infoTypes by specifying the type of info to be inspected if null.
        var infotypes = infoTypes ?? new InfoType[]
        {
            new InfoType { Name = "EMAIL_ADDRESS" },
            new InfoType { Name = "PHONE_NUMBER" }
        };

        // Construct the crypto hash config using transient crypto key name.
        var cryptoHashConfig = new CryptoHashConfig
        {
            CryptoKey = new CryptoKey
            {
                Transient = new TransientCryptoKey
                {
                    Name = transientKeyName ?? "[TRANSIENT-CRYPTO-KEY]"
                }
            }
        };

        // Construct the de-identify config using crypto hash config.
        var deidentifyConfig = new DeidentifyConfig
        {
            InfoTypeTransformations = new InfoTypeTransformations
            {
                Transformations =
                {
                    new InfoTypeTransformations.Types.InfoTypeTransformation
                    {
                        PrimitiveTransformation = new PrimitiveTransformation
                        {
                            CryptoHashConfig = cryptoHashConfig
                        },
                        InfoTypes = { infotypes }
                    }
                }
            }
        };

        // Construct the inspect config.
        var inspectConfig = new InspectConfig
        {
            InfoTypes = { infotypes },
            IncludeQuote = true
        };

        // Construct the request.
        var request = new DeidentifyContentRequest
        {
            ParentAsLocationName = new LocationName(projectId, "global"),
            DeidentifyConfig = deidentifyConfig,
            Item = contentItem,
            InspectConfig = inspectConfig
        };

        // Call the API.
        DeidentifyContentResponse response = dlp.DeidentifyContent(request);

        // Print the table.
        Console.WriteLine(response.Item.Table);

        return response.Item.Table;
    }
}

Go

如要瞭解如何安裝及使用 Sensitive Data Protection 的用戶端程式庫，請參閱「Sensitive Data Protection 用戶端程式庫」。

如要向 Sensitive Data Protection 進行驗證，請設定應用程式預設憑證。詳情請參閱「為本機開發環境設定驗證機制」。

import (
	"context"
	"fmt"
	"io"

	dlp "cloud.google.com/go/dlp/apiv2"
	"cloud.google.com/go/dlp/apiv2/dlppb"
)

// deIdentifyTableWithCryptoHash transforms findings using a cryptographic hash transformation.
func deIdentifyTableWithCryptoHash(w io.Writer, projectID, transientKeyName string) error {
	// projectId := "your-project-id"
	// transientKeyName := "YOUR_TRANSIENT_CRYPTO_KEY_NAME"

	row1 := &dlppb.Table_Row{
		Values: []*dlppb.Value{
			{Type: &dlppb.Value_StringValue{StringValue: "user1@example.org"}},
			{Type: &dlppb.Value_StringValue{StringValue: "my email is user1@example.org and phone is 858-555-0222"}},
		},
	}

	row2 := &dlppb.Table_Row{
		Values: []*dlppb.Value{
			{Type: &dlppb.Value_StringValue{StringValue: "user2@example.org"}},
			{Type: &dlppb.Value_StringValue{StringValue: "my email is user2@example.org and phone is 858-555-0232"}},
		},
	}

	row3 := &dlppb.Table_Row{
		Values: []*dlppb.Value{
			{Type: &dlppb.Value_StringValue{StringValue: "user3@example.org"}},
			{Type: &dlppb.Value_StringValue{StringValue: "my email is user3@example.org and phone is 858-555-0224"}},
		},
	}

	tableToDeidentify := &dlppb.Table{
		Headers: []*dlppb.FieldId{
			{Name: "userid"},
			{Name: "comments"},
		},
		Rows: []*dlppb.Table_Row{
			{Values: row1.Values},
			{Values: row2.Values},
			{Values: row3.Values},
		},
	}

	ctx := context.Background()

	// Initialize a client once and reuse it to send multiple requests. Clients
	// are safe to use across goroutines. When the client is no longer needed,
	// call the Close method to cleanup its resources.
	client, err := dlp.NewClient(ctx)
	if err != nil {
		return err
	}

	// Closing the client safely cleans up background resources.
	defer client.Close()

	// Specify what content you want the service to de-identify.
	contentItem := &dlppb.ContentItem{
		DataItem: &dlppb.ContentItem_Table{
			Table: tableToDeidentify,
		},
	}

	// Specify the type of info the inspection will look for.
	// See https://cloud.google.com/dlp/docs/infotypes-reference for complete list of info types
	infoTypes := []*dlppb.InfoType{
		{Name: "PHONE_NUMBER"},
		{Name: "EMAIL_ADDRESS"},
	}

	inspectConfig := &dlppb.InspectConfig{
		InfoTypes: infoTypes,
	}

	// Specify the transient key which will encrypt the data.
	if transientKeyName == "" {
		transientKeyName = "YOUR_TRANSIENT_CRYPTO_KEY_NAME"
	}

	// Specify the transient key which will encrypt the data.
	cryptoKey := &dlppb.CryptoKey{
		Source: &dlppb.CryptoKey_Transient{
			Transient: &dlppb.TransientCryptoKey{
				Name: transientKeyName,
			},
		},
	}

	// Specify how the info from the inspection should be encrypted.
	cryptoHashConfig := &dlppb.CryptoHashConfig{
		CryptoKey: cryptoKey,
	}

	// Define type of de-identification as cryptographic hash transformation.
	primitiveTransformation := &dlppb.PrimitiveTransformation_CryptoHashConfig{
		CryptoHashConfig: cryptoHashConfig,
	}

	infoTypeTransformation := &dlppb.InfoTypeTransformations_InfoTypeTransformation{
		InfoTypes: infoTypes,
		PrimitiveTransformation: &dlppb.PrimitiveTransformation{
			Transformation: primitiveTransformation,
		},
	}

	transformations := &dlppb.InfoTypeTransformations{
		Transformations: []*dlppb.InfoTypeTransformations_InfoTypeTransformation{
			infoTypeTransformation,
		},
	}

	// Specify the config for the de-identify request.
	deidentifyConfig := &dlppb.DeidentifyConfig{
		Transformation: &dlppb.DeidentifyConfig_InfoTypeTransformations{
			InfoTypeTransformations: transformations,
		},
	}

	// Construct the de-identification request to be sent by the client.
	req := &dlppb.DeidentifyContentRequest{
		Parent:           fmt.Sprintf("projects/%s/locations/global", projectID),
		DeidentifyConfig: deidentifyConfig,
		InspectConfig:    inspectConfig,
		Item:             contentItem,
	}

	// Send the request.
	resp, err := client.DeidentifyContent(ctx, req)
	if err != nil {
		return err
	}

	// Print the results.
	fmt.Fprintf(w, "Table after de-identification : %v", resp.GetItem().GetTable())
	return nil
}

Java

如要瞭解如何安裝及使用 Sensitive Data Protection 的用戶端程式庫，請參閱「Sensitive Data Protection 用戶端程式庫」。

如要向 Sensitive Data Protection 進行驗證，請設定應用程式預設憑證。詳情請參閱「為本機開發環境設定驗證機制」。


import com.google.cloud.dlp.v2.DlpServiceClient;
import com.google.privacy.dlp.v2.ContentItem;
import com.google.privacy.dlp.v2.CryptoHashConfig;
import com.google.privacy.dlp.v2.CryptoKey;
import com.google.privacy.dlp.v2.DeidentifyConfig;
import com.google.privacy.dlp.v2.DeidentifyContentRequest;
import com.google.privacy.dlp.v2.DeidentifyContentResponse;
import com.google.privacy.dlp.v2.FieldId;
import com.google.privacy.dlp.v2.InfoType;
import com.google.privacy.dlp.v2.InfoTypeTransformations;
import com.google.privacy.dlp.v2.InspectConfig;
import com.google.privacy.dlp.v2.LocationName;
import com.google.privacy.dlp.v2.PrimitiveTransformation;
import com.google.privacy.dlp.v2.Table;
import com.google.privacy.dlp.v2.TransientCryptoKey;
import com.google.privacy.dlp.v2.Value;
import java.io.IOException;
import java.util.List;
import java.util.stream.Collectors;
import java.util.stream.Stream;

public class DeIdentifyTableWithCryptoHash {

  public static void main(String[] args) throws Exception {
    // TODO(developer): Replace these variables before running the sample.

    // The Google Cloud project id to use as a parent resource.
    String projectId = "your-project-id";

    // The table to de-identify.
    Table tableToDeIdentify =
        Table.newBuilder()
            .addHeaders(FieldId.newBuilder().setName("userid").build())
            .addHeaders(FieldId.newBuilder().setName("comments").build())
            .addRows(
                Table.Row.newBuilder()
                    .addValues(Value.newBuilder().setStringValue("user1@example.org").build())
                    .addValues(
                        Value.newBuilder()
                            .setStringValue(
                                "my email is user1@example.org and phone is 858-555-0222")
                            .build())
                    .build())
            .addRows(
                Table.Row.newBuilder()
                    .addValues(Value.newBuilder().setStringValue("user2@example.org").build())
                    .addValues(
                        Value.newBuilder()
                            .setStringValue(
                                "my email is user2@example.org and phone is 858-555-0223")
                            .build())
                    .build())
            .addRows(
                Table.Row.newBuilder()
                    .addValues(Value.newBuilder().setStringValue("user3@example.org").build())
                    .addValues(
                        Value.newBuilder()
                            .setStringValue(
                                "my email is user3@example.org and phone is 858-555-0224")
                            .build())
                    .build())
            .build();

    // The randomly generated crypto key to encrypt the data.
    String transientKeyName = "YOUR_TRANSIENT_CRYPTO_KEY";
    deIdentifyWithCryptHashTransformation(projectId, tableToDeIdentify, transientKeyName);
  }

  // Transforms findings using a cryptographic hash transformation.
  public static void deIdentifyWithCryptHashTransformation(
      String projectId, Table tableToDeIdentify, String transientKeyName) throws IOException {
    // Initialize client that will be used to send requests. This client only needs to be created
    // once, and can be reused for multiple requests. After completing all of your requests, call
    // the "close" method on the client to safely clean up any remaining background resources.
    try (DlpServiceClient dlp = DlpServiceClient.create()) {
      // Specify what content you want the service to DeIdentify
      ContentItem contentItem = ContentItem.newBuilder().setTable(tableToDeIdentify).build();

      // Specify the type of info the inspection will look for.
      // See https://cloud.google.com/dlp/docs/infotypes-reference for complete list of info types
      List<InfoType> infoTypes =
          Stream.of("PHONE_NUMBER", "EMAIL_ADDRESS")
              .map(it -> InfoType.newBuilder().setName(it).build())
              .collect(Collectors.toList());

      InspectConfig inspectConfig = InspectConfig.newBuilder()
              .addAllInfoTypes(infoTypes)
              .build();

      // Specify the transient key which will encrypt the data.
      TransientCryptoKey transientCryptoKey = TransientCryptoKey.newBuilder()
              .setName(transientKeyName)
              .build();

      CryptoKey cryptoKey = CryptoKey.newBuilder()
              .setTransient(transientCryptoKey)
              .build();

      // Specify how the info from the inspection should be encrypted.
      CryptoHashConfig cryptoHashConfig = CryptoHashConfig.newBuilder()
              .setCryptoKey(cryptoKey)
              .build();

      // Define type of de-identification as cryptographic hash transformation.
      PrimitiveTransformation primitiveTransformation = PrimitiveTransformation.newBuilder()
              .setCryptoHashConfig(cryptoHashConfig)
              .build();

      InfoTypeTransformations.InfoTypeTransformation infoTypeTransformation =
          InfoTypeTransformations.InfoTypeTransformation.newBuilder()
              .setPrimitiveTransformation(primitiveTransformation)
              .addAllInfoTypes(infoTypes)
              .build();

      InfoTypeTransformations transformations = InfoTypeTransformations.newBuilder()
              .addTransformations(infoTypeTransformation)
              .build();

      // Specify the config for the de-identify request
      DeidentifyConfig deidentifyConfig = DeidentifyConfig.newBuilder()
              .setInfoTypeTransformations(transformations)
              .build();

      // Combine configurations into a request for the service.
      DeidentifyContentRequest request =
          DeidentifyContentRequest.newBuilder()
              .setParent(LocationName.of(projectId, "global").toString())
              .setItem(contentItem)
              .setInspectConfig(inspectConfig)
              .setDeidentifyConfig(deidentifyConfig)
              .build();

      // Send the request and receive response from the service
      DeidentifyContentResponse response = dlp.deidentifyContent(request);

      // Print the results
      System.out.println("Table after de-identification: " + response.getItem().getTable());
    }
  }
}

Node.js

如要瞭解如何安裝及使用 Sensitive Data Protection 的用戶端程式庫，請參閱「Sensitive Data Protection 用戶端程式庫」。

如要向 Sensitive Data Protection 進行驗證，請設定應用程式預設憑證。詳情請參閱「為本機開發環境設定驗證機制」。

// Imports the Google Cloud Data Loss Prevention library
const DLP = require('@google-cloud/dlp');

// Instantiates a client
const dlp = new DLP.DlpServiceClient();

// The project ID to run the API call under
// const projectId = 'my-project';

// Crypto key
// const transientKeyName = 'YOUR_TRANSIENT_CRYPTO_KEY';

// The table to de-identify.
const tableToDeIdentify = {
  headers: [{name: 'userid'}, {name: 'comments'}],
  rows: [
    {
      values: [
        {stringValue: 'user1@example.org'},
        {
          stringValue:
            'my email is user1@example.org and phone is 858-555-0222',
        },
      ],
    },
    {
      values: [
        {stringValue: 'user2@example.org'},
        {
          stringValue:
            'my email is user2@example.org and phone is 858-555-0223',
        },
      ],
    },
    {
      values: [
        {stringValue: 'user3@example.org'},
        {
          stringValue:
            'my email is user3@example.org and phone is 858-555-0224',
        },
      ],
    },
  ],
};
async function deIdentifyTableWithCryptoHash() {
  // Specify crypto hash configuration that uses transient key.
  const cryptoHashConfig = {
    cryptoKey: {
      transient: {
        name: transientKeyName,
      },
    },
  };

  // Construct de-identify request that uses crypto hash configuration.
  const request = {
    parent: `projects/${projectId}/locations/global`,
    deidentifyConfig: {
      infoTypeTransformations: {
        transformations: [
          {
            primitiveTransformation: {
              cryptoHashConfig: cryptoHashConfig,
            },
            infoTypes: [{name: 'PHONE_NUMBER'}, {name: 'EMAIL_ADDRESS'}],
          },
        ],
      },
    },
    item: {table: tableToDeIdentify},
  };

  // Send the request and receive response from the service.
  const [response] = await dlp.deidentifyContent(request);
  const deidentifiedTable = response.item.table;

  // Print the results.
  console.log(
    `Table after de-identification:\n${JSON.stringify(
      deidentifiedTable,
      null,
      2
    )}`
  );
}

deIdentifyTableWithCryptoHash();

PHP

如要瞭解如何安裝及使用 Sensitive Data Protection 的用戶端程式庫，請參閱「Sensitive Data Protection 用戶端程式庫」。

如要向 Sensitive Data Protection 進行驗證，請設定應用程式預設憑證。詳情請參閱「為本機開發環境設定驗證機制」。

use Google\Cloud\Dlp\V2\Client\DlpServiceClient;
use Google\Cloud\Dlp\V2\ContentItem;
use Google\Cloud\Dlp\V2\CryptoHashConfig;
use Google\Cloud\Dlp\V2\CryptoKey;
use Google\Cloud\Dlp\V2\DeidentifyConfig;
use Google\Cloud\Dlp\V2\DeidentifyContentRequest;
use Google\Cloud\Dlp\V2\FieldId;
use Google\Cloud\Dlp\V2\InfoType;
use Google\Cloud\Dlp\V2\InfoTypeTransformations;
use Google\Cloud\Dlp\V2\InfoTypeTransformations\InfoTypeTransformation;
use Google\Cloud\Dlp\V2\InspectConfig;
use Google\Cloud\Dlp\V2\PrimitiveTransformation;
use Google\Cloud\Dlp\V2\Table;
use Google\Cloud\Dlp\V2\Table\Row;
use Google\Cloud\Dlp\V2\TransientCryptoKey;
use Google\Cloud\Dlp\V2\Value;

/**
 * De-identify table data with crypto hash.
 * Transform findings using a cryptographic hash transformation.
 *
 * @param string $callingProjectId          The Google Cloud project id to use as a parent resource.
 * @param string $inputCsvFile              The input file(csv) path  to deidentify.
 * @param string $outputCsvFile             The oupt file path to save deidentify content.
 * @param string $transientCryptoKeyName    Specify the random string.
 */

function deidentify_table_with_crypto_hash(
    // TODO(developer): Replace sample parameters before running the code.
    string $callingProjectId,
    string $inputCsvFile = './test/data/table5.csv',
    string $outputCsvFile = './test/data/deidentify_table_with_crypto_hash_output.csv',
    string $transientCryptoKeyName = 'YOUR-TRANSIENT-CRYPTO-KEY'
): void {
    // Instantiate a client.
    $dlp = new DlpServiceClient();

    $parent = "projects/$callingProjectId/locations/global";

    // Read a CSV file.
    $csvLines = file($inputCsvFile, FILE_IGNORE_NEW_LINES);
    $csvHeaders = explode(',', $csvLines[0]);
    $csvRows = array_slice($csvLines, 1);

    // Convert CSV file into protobuf objects.
    $tableHeaders = array_map(function ($csvHeader) {
        return (new FieldId)
            ->setName($csvHeader);
    }, $csvHeaders);

    $tableRows = array_map(function ($csvRow) {
        $rowValues = array_map(function ($csvValue) {
            return (new Value())
                ->setStringValue($csvValue);
        }, explode(',', $csvRow));
        return (new Row())
            ->setValues($rowValues);
    }, $csvRows);

    // Construct the table object.
    $tableToDeIdentify = (new Table())
        ->setHeaders($tableHeaders)
        ->setRows($tableRows);

    // Specify what content you want the service to de-identify.
    $content = (new ContentItem())
        ->setTable($tableToDeIdentify);

    // Specify the type of info the inspection will look for.
    // See https://cloud.google.com/dlp/docs/infotypes-reference for complete list of info types
    $infoTypes = [
        (new InfoType())->setName('EMAIL_ADDRESS'),
        (new InfoType())->setName('PHONE_NUMBER')
    ];

    $inspectConfig = (new InspectConfig())
        ->setInfoTypes($infoTypes);

    // Specify the transient key which will encrypt the data.
    $cryptoKey = (new CryptoKey())
        ->setTransient((new TransientCryptoKey())
            ->setName($transientCryptoKeyName));

    // Specify how the info from the inspection should be encrypted.
    $cryptoHashConfig = (new CryptoHashConfig())
        ->setCryptoKey($cryptoKey);

    // Define type of de-identification as cryptographic hash transformation.
    $primitiveTransformation = (new PrimitiveTransformation())
        ->setCryptoHashConfig($cryptoHashConfig);

    $infoTypeTransformation = (new InfoTypeTransformation())
        ->setPrimitiveTransformation($primitiveTransformation)
        ->setInfoTypes($infoTypes);

    $infoTypeTransformations = (new InfoTypeTransformations())
        ->setTransformations([$infoTypeTransformation]);

    // Specify the config for the de-identify request
    $deidentifyConfig = (new DeidentifyConfig())
        ->setInfoTypeTransformations($infoTypeTransformations);

    // Send the request and receive response from the service.
    $deidentifyContentRequest = (new DeidentifyContentRequest())
        ->setParent($parent)
        ->setInspectConfig($inspectConfig)
        ->setDeidentifyConfig($deidentifyConfig)
        ->setItem($content);
    $response = $dlp->deidentifyContent($deidentifyContentRequest);

    // Print the results.
    $csvRef = fopen($outputCsvFile, 'w');
    fputcsv($csvRef, $csvHeaders);
    foreach ($response->getItem()->getTable()->getRows() as $tableRow) {
        $values = array_map(function ($tableValue) {
            return $tableValue->getStringValue();
        }, iterator_to_array($tableRow->getValues()));
        fputcsv($csvRef, $values);
    };
    printf('Table after deidentify (File Location): %s', $outputCsvFile);
}

Python

如要瞭解如何安裝及使用 Sensitive Data Protection 的用戶端程式庫，請參閱「Sensitive Data Protection 用戶端程式庫」。

如要向 Sensitive Data Protection 進行驗證，請設定應用程式預設憑證。詳情請參閱「為本機開發環境設定驗證機制」。

from typing import Dict, List, Union

import google.cloud.dlp


def deidentify_table_with_crypto_hash(
    project: str,
    table_data: Dict[str, Union[List[str], List[List[str]]]],
    info_types: List[str],
    transient_key_name: str,
) -> None:
    """Uses the Data Loss Prevention API to de-identify sensitive data
    in a table using a cryptographic hash transformation.
    Args:
        project: The Google Cloud project id to use as a parent resource.
        table_data: Dictionary representing table data.
        info_types: A list of strings representing info types to look for.
            A full list of info type categories can be fetched from the API.
        transient_key_name: Name of the transient crypto key used for encryption.
            The scope of this key is a single API call. It is generated for
            the transformation and then discarded.
    """

    # Instantiate a client
    dlp = google.cloud.dlp_v2.DlpServiceClient()

    # Construct the `table`. For more details on the table schema, please see
    # https://cloud.google.com/dlp/docs/reference/rest/v2/ContentItem#Table
    headers = [{"name": val} for val in table_data["header"]]
    rows = []
    for row in table_data["rows"]:
        rows.append({"values": [{"string_value": cell_val} for cell_val in row]})

    table = {"headers": headers, "rows": rows}

    # Construct the `item` that service will de-identify.
    item = {"table": table}

    # Prepare info_types by converting the list of strings into a list of
    # dictionaries.
    info_types = [{"name": info_type} for info_type in info_types]

    # Construct cryptographic hash configuration using the transient key
    # which will encrypt the data.
    crypto_hash_config = {"crypto_key": {"transient": {"name": transient_key_name}}}

    # Specify the type of info the inspection will look for.
    inspect_config = {
        "info_types": info_types,
    }

    # Construct deidentify configuration dictionary.
    deidentify_config = {
        "info_type_transformations": {
            "transformations": [
                {
                    "info_types": info_types,
                    "primitive_transformation": {
                        "crypto_hash_config": crypto_hash_config
                    },
                }
            ]
        }
    }

    # Convert the project id into a full resource id.
    parent = f"projects/{project}/locations/global"

    # Call the API.
    response = dlp.deidentify_content(
        request={
            "parent": parent,
            "deidentify_config": deidentify_config,
            "inspect_config": inspect_config,
            "item": item,
        }
    )

    # Print the result.
    print(f"Table after de-identification: {response.item.table}")

REST

    {
      "inspectConfig":{
        "infoTypes":[
          {
            "name":"EMAIL_ADDRESS"
          },
          {
            "name":"PHONE_NUMBER"
          }
        ]
      },
      "deidentifyConfig":{
        "infoTypeTransformations":{
          "transformations":[
            {
              "infoTypes":[
                {
                  "name":"EMAIL_ADDRESS"
                },
                {
                  "name":"PHONE_NUMBER"
                }
              ],
              "primitiveTransformation":{
                "cryptoHashConfig":{
                  "cryptoKey":{
                    "transient":{
                      "name":"[TRANSIENT-CRYPTO-KEY]"
                    }
                  }
                }
              }
            }
          ]
        }
      },
      "item":{
        "table":{
          "headers":[
            {
              "name":"userid"
            },
            {
              "name":"comments"
            }
          ],
          "rows":[
            {
              "values":[
                {
                  "stringValue":"abby_abernathy@example.org"
                },
                {
                  "stringValue":"my email is abby_abernathy@example.org and phone is 858-555-0222"
                }
              ]
            },
            {
              "values":[
                {
                  "stringValue":"bert_beauregard@example.org"
                },
                {
                  "stringValue":"my email is bert_beauregard@example.org and phone is 858-555-0223"
                }
              ]
            },
            {
              "values":[
                {
                  "stringValue":"cathy_crenshaw@example.org"
                },
                {
                  "stringValue":"my email is cathy_crenshaw@example.org and phone is 858-555-0224"
                }
              ]
            }
          ]
        }
      }
    }

使用兩種不同的加密雜湊轉換方式轉換調查結果

這個範例示範如何在單一去識別化設定中，於不同轉換中使用不同的加密編譯金鑰。首先，系統會宣告「userid」欄位的欄位轉換。該轉換不包含任何 infoType 轉換，因此無論資料類型為何，每個資料列中的「userid」欄位都會轉換。接著，系統會宣告另一個欄位轉換，這次是針對「comments」欄位。

輸入：

userid	留言
user1@example.org	我的電子郵件地址是 user1@example.org，電話號碼是 858-555-0222
abbyabernathy1	我的使用者 ID 是 abbyabernathy1，電子郵件地址是 aabernathy@example.com

轉換後的表格：

userid	留言
5WvS4+aJtCCwWWG79cmRNamDgyvJ+CkuwNpA2gaR1VQ=	我的電子郵件地址是 vjqGLaA6+NUUnZAWXpI72lU1GfwQdOKu7XqWaJPcvQQ=，電話號碼是 BY+mSXXTu6mOoX5pr0Xbse60uelsSHmwRCq6HcscKtk=
t0dOmHvkT0VsM++SVmESVKHenLkmhBmFezH3hSDldDg=	我的使用者 ID 是 abbyabernathy1，電子郵件地址是 TQ3ancdUn9zgwO5qe6ahkmVrBuNhvlMknxjPjIt0N2w=

APIs Explorer 範例

C#

如要瞭解如何安裝及使用 Sensitive Data Protection 的用戶端程式庫，請參閱「Sensitive Data Protection 用戶端程式庫」。

如要向 Sensitive Data Protection 進行驗證，請設定應用程式預設憑證。詳情請參閱「為本機開發環境設定驗證機制」。


using System;
using System.Collections.Generic;
using Google.Api.Gax.ResourceNames;
using Google.Cloud.Dlp.V2;

public class DeidentifyTableWithMultipleCryptoHash
{
    public static Table Deidentify(
        string projectId,
        Table tableToDeidentify = null,
        IEnumerable<InfoType> infoTypes = null,
        string transientKeyName1 = null,
        string transientKeyName2 = null)
    {
        // Instantiate the client.
        var dlp = DlpServiceClient.Create();

        // Construct the table if null.
        if (tableToDeidentify == null)
        {
            var row1 = new Value[]
            {
                new Value { StringValue = "user1@example.org" },
                new Value { StringValue = "my email is user1@example.org and phone is 858-555-0222" }
            };
            var row2 = new Value[]
            {
                new Value { StringValue = "user2@example.org" },
                new Value { StringValue = "my email is user2@example.org and phone is 858-555-0223" }
            };
            var row3 = new Value[]
            {
                new Value { StringValue = "user3@example.org" },
                new Value { StringValue = "my email is user3@example.org and phone is 858-555-0224" }
            };

            tableToDeidentify = new Table
            {
                Headers =
                {
                    new FieldId { Name = "User ID" },
                    new FieldId { Name = "comments" }
                },
                Rows =
                {
                    new Table.Types.Row { Values = { row1 } },
                    new Table.Types.Row { Values = { row2 } },
                    new Table.Types.Row { Values = { row3 } }
                }
            };
        }

        // Specify the table and construct the content item.
        var contentItem = new ContentItem { Table = tableToDeidentify };

        // Construct the crypto hash config for primitive transformation using
        // transient crypto key name.
        var cryptoHashConfig1 = new CryptoHashConfig
        {
            CryptoKey = new CryptoKey
            {
                Transient = new TransientCryptoKey
                {
                    Name = transientKeyName1 ?? "[TRANSIENT-CRYPTO-KEY-1]"
                }
            }
        };

        // Construct the crypto hash config for infoType transformation using
        // transient crypto key name.
        var cryptoHashConfig2 = new CryptoHashConfig
        {
            CryptoKey = new CryptoKey
            {
                Transient = new TransientCryptoKey
                {
                    Name = transientKeyName2 ?? "[TRANSIENT-CRYPTO-KEY-2]"
                }
            }
        };

        // Construct the infoTypes by specifying the type of info to be inspected if null.
        var infotypes = infoTypes ?? new InfoType[]
        {
            new InfoType { Name = "EMAIL_ADDRESS" },
            new InfoType { Name = "PERSON_NAME" }
        };

        // Construct the deidentify config using crypto hash configs.
        var deidentifyConfig = new DeidentifyConfig
        {
            RecordTransformations = new RecordTransformations
            {
                FieldTransformations =
                {
                    new FieldTransformation
                    {
                        Fields = { new FieldId[] { new FieldId { Name = "User ID" } } },
                        PrimitiveTransformation = new PrimitiveTransformation
                        {
                            CryptoHashConfig = cryptoHashConfig1
                        }
                    },
                    new FieldTransformation
                    {
                        Fields = { new FieldId[] { new FieldId { Name = "comments" } } },
                        InfoTypeTransformations =  new InfoTypeTransformations
                        {
                            Transformations =
                            {
                                new InfoTypeTransformations.Types.InfoTypeTransformation
                                {
                                    PrimitiveTransformation = new PrimitiveTransformation
                                    {
                                        CryptoHashConfig = cryptoHashConfig2
                                    },
                                    InfoTypes = { infotypes }
                                }
                            }
                        }
                    }
                }
            }
        };

        // Construct the inspect config.
        var inspectConfig = new InspectConfig
        {
            InfoTypes = { infotypes },
            IncludeQuote = true
        };

        // Construct the request.
        var request = new DeidentifyContentRequest
        {
            ParentAsLocationName = new LocationName(projectId, "global"),
            DeidentifyConfig = deidentifyConfig,
            Item = contentItem,
            InspectConfig = inspectConfig
        };

        // Call the API.
        var response = dlp.DeidentifyContent(request);

        // Print the table.
        Console.WriteLine(response.Item.Table);

        return response.Item.Table;
    }
}

Go

如要瞭解如何安裝及使用 Sensitive Data Protection 的用戶端程式庫，請參閱「Sensitive Data Protection 用戶端程式庫」。

如要向 Sensitive Data Protection 進行驗證，請設定應用程式預設憑證。詳情請參閱「為本機開發環境設定驗證機制」。

import (
	"context"
	"fmt"
	"io"

	dlp "cloud.google.com/go/dlp/apiv2"
	"cloud.google.com/go/dlp/apiv2/dlppb"
)

// deIdentifyTableWithMultipleCryptoHash Transforms findings using two separate cryptographic hash transformations.
func deIdentifyTableWithMultipleCryptoHash(w io.Writer, projectID, transientKeyName1, transientKeyName2 string) error {
	// projectId := "your-project-id"
	// transientKeyName1 := "YOUR_TRANSIENT_CRYPTO_KEY_1"
	// transientKeyName2 := "YOUR_TRANSIENT_CRYPTO_KEY_2"

	// The table to de-identify.
	row1 := &dlppb.Table_Row{
		Values: []*dlppb.Value{
			{Type: &dlppb.Value_StringValue{StringValue: "user1@example.org"}},
			{Type: &dlppb.Value_StringValue{StringValue: "my email is user1@example.org and phone is 858-555-0222"}},
		},
	}

	row2 := &dlppb.Table_Row{
		Values: []*dlppb.Value{
			{Type: &dlppb.Value_StringValue{StringValue: "abbyabernathy1"}},
			{Type: &dlppb.Value_StringValue{StringValue: "my userid is abbyabernathy1 and my email is aabernathy@example.com"}},
		},
	}

	tableToDeidentify := &dlppb.Table{
		Headers: []*dlppb.FieldId{
			{Name: "userid"},
			{Name: "comments"},
		},
		Rows: []*dlppb.Table_Row{
			{Values: row1.Values},
			{Values: row2.Values},
		},
	}

	ctx := context.Background()

	// Initialize a client once and reuse it to send multiple requests. Clients
	// are safe to use across goroutines. When the client is no longer needed,
	// call the Close method to cleanup its resources.
	client, err := dlp.NewClient(ctx)
	if err != nil {
		return err
	}

	// Closing the client safely cleans up background resources.
	defer client.Close()

	// Specify what content you want the service to de-identify.
	contentItem := &dlppb.ContentItem{
		DataItem: &dlppb.ContentItem_Table{
			Table: tableToDeidentify,
		},
	}

	// Specify the type of info the inspection will look for.
	// See https://cloud.google.com/dlp/docs/infotypes-reference for complete list of info types
	infoTypes := []*dlppb.InfoType{
		{Name: "PHONE_NUMBER"},
		{Name: "EMAIL_ADDRESS"},
	}

	inspectConfig := &dlppb.InspectConfig{
		InfoTypes: infoTypes,
	}

	// Specify the transient key names.

	transientCryptoKey1 := &dlppb.TransientCryptoKey{
		Name: transientKeyName1,
	}

	transientCryptoKey2 := &dlppb.TransientCryptoKey{
		Name: transientKeyName2,
	}

	cryptoKey1 := &dlppb.CryptoKey_Transient{
		Transient: transientCryptoKey1,
	}

	cryptoKey2 := &dlppb.CryptoKey_Transient{
		Transient: transientCryptoKey2,
	}

	// Specify the CryptoHashConfig for transientKey1.
	cryptoHashConfig1 := &dlppb.CryptoHashConfig{
		CryptoKey: &dlppb.CryptoKey{
			Source: cryptoKey1,
		},
	}

	// Specify the CryptoHashConfig for transientKey1.
	cryptoHashConfig2 := &dlppb.CryptoHashConfig{
		CryptoKey: &dlppb.CryptoKey{
			Source: cryptoKey2,
		},
	}

	// Define type of de-identification as cryptographic hash transformation.

	// Specify the transformation for transientKey1
	primitiveTransformation1 := &dlppb.PrimitiveTransformation{
		Transformation: &dlppb.PrimitiveTransformation_CryptoHashConfig{
			CryptoHashConfig: cryptoHashConfig1,
		},
	}

	// Specify the transformation for transientKey2
	primitiveTransformation2 := &dlppb.PrimitiveTransformation{
		Transformation: &dlppb.PrimitiveTransformation_CryptoHashConfig{
			CryptoHashConfig: cryptoHashConfig2,
		},
	}

	infoTypeTransformation := &dlppb.InfoTypeTransformations_InfoTypeTransformation{
		PrimitiveTransformation: primitiveTransformation2,
	}

	transformations := &dlppb.InfoTypeTransformations{
		Transformations: []*dlppb.InfoTypeTransformations_InfoTypeTransformation{
			infoTypeTransformation,
		},
	}

	// Specify fields to be de-identified.
	fieldIds := []*dlppb.FieldId{
		{Name: "userid"},
		{Name: "comments"},
	}

	fieldTransformations := []*dlppb.FieldTransformation{
		{
			Fields: []*dlppb.FieldId{
				fieldIds[0],
			},
			Transformation: &dlppb.FieldTransformation_PrimitiveTransformation{
				PrimitiveTransformation: primitiveTransformation1,
			},
		},
		{
			Fields: []*dlppb.FieldId{
				fieldIds[1],
			},
			Transformation: &dlppb.FieldTransformation_InfoTypeTransformations{
				InfoTypeTransformations: transformations,
			},
		},
	}

	recordTransformations := &dlppb.RecordTransformations{
		FieldTransformations: fieldTransformations,
	}

	// Specify the config for the de-identify request
	deidentifyConfig := &dlppb.DeidentifyConfig{
		Transformation: &dlppb.DeidentifyConfig_RecordTransformations{
			RecordTransformations: recordTransformations,
		},
	}

	// Construct the de-identification request to be sent by the client.
	req := &dlppb.DeidentifyContentRequest{
		Parent:           fmt.Sprintf("projects/%s/locations/global", projectID),
		DeidentifyConfig: deidentifyConfig,
		InspectConfig:    inspectConfig,
		Item:             contentItem,
	}

	// Send the request.
	resp, err := client.DeidentifyContent(ctx, req)
	if err != nil {
		return err
	}

	// Print the results.
	fmt.Fprintf(w, "Table after de-identification : %v", resp.GetItem().GetTable())
	return nil
}

Java

如要瞭解如何安裝及使用 Sensitive Data Protection 的用戶端程式庫，請參閱「Sensitive Data Protection 用戶端程式庫」。

如要向 Sensitive Data Protection 進行驗證，請設定應用程式預設憑證。詳情請參閱「為本機開發環境設定驗證機制」。


import com.google.cloud.dlp.v2.DlpServiceClient;
import com.google.privacy.dlp.v2.ContentItem;
import com.google.privacy.dlp.v2.CryptoHashConfig;
import com.google.privacy.dlp.v2.CryptoKey;
import com.google.privacy.dlp.v2.DeidentifyConfig;
import com.google.privacy.dlp.v2.DeidentifyContentRequest;
import com.google.privacy.dlp.v2.DeidentifyContentResponse;
import com.google.privacy.dlp.v2.FieldId;
import com.google.privacy.dlp.v2.FieldTransformation;
import com.google.privacy.dlp.v2.InfoType;
import com.google.privacy.dlp.v2.InfoTypeTransformations;
import com.google.privacy.dlp.v2.InspectConfig;
import com.google.privacy.dlp.v2.LocationName;
import com.google.privacy.dlp.v2.PrimitiveTransformation;
import com.google.privacy.dlp.v2.RecordTransformations;
import com.google.privacy.dlp.v2.Table;
import com.google.privacy.dlp.v2.TransientCryptoKey;
import com.google.privacy.dlp.v2.Value;
import java.io.IOException;
import java.util.ArrayList;
import java.util.List;
import java.util.stream.Collectors;
import java.util.stream.Stream;

public class DeIdentifyTableWithMultipleCryptoHash {

  public static void main(String[] args) throws Exception {
    // TODO(developer): Replace these variables before running the sample.

    // The Google Cloud project id to use as a parent resource.
    String projectId = "your-project-id";

    // The table to de-identify.
    Table tableToDeIdentify =
        Table.newBuilder()
            .addHeaders(FieldId.newBuilder().setName("userid").build())
            .addHeaders(FieldId.newBuilder().setName("comments").build())
            .addRows(
                Table.Row.newBuilder()
                    .addValues(Value.newBuilder().setStringValue("user1@example.org").build())
                    .addValues(
                        Value.newBuilder()
                            .setStringValue(
                                "my email is user1@example.org and phone is 858-555-0222")
                            .build())
                    .build())
            .addRows(
                Table.Row.newBuilder()
                    .addValues(Value.newBuilder().setStringValue("user2@example.org").build())
                    .addValues(
                        Value.newBuilder()
                            .setStringValue(
                                "my email is user2@example.org and phone is 858-555-0223")
                            .build())
                    .build())
            .addRows(
                Table.Row.newBuilder()
                    .addValues(Value.newBuilder().setStringValue("user3@example.org").build())
                    .addValues(
                        Value.newBuilder()
                            .setStringValue(
                                "my email is user3@example.org and phone is 858-555-0224")
                            .build())
                    .build())
            .build();

    // The names of the keys used to encrypt the data.
    String transientKeyName1 = "YOUR_TRANSIENT_CRYPTO_KEY";
    String transientKeyName2 = "YOUR_TRANSIENT_CRYPTO_KEY_2";

    deIdentifyWithCryptHashTransformation(
        projectId, tableToDeIdentify, transientKeyName1, transientKeyName2);
  }

  // Transforms findings using two separate cryptographic hash transformations.
  public static void deIdentifyWithCryptHashTransformation(
      String projectId, Table tableToDeIdentify, String transientKeyName1, String transientKeyName2)
      throws IOException {
    // Initialize client that will be used to send requests. This client only needs to be created
    // once, and can be reused for multiple requests. After completing all of your requests, call
    // the "close" method on the client to safely clean up any remaining background resources.
    try (DlpServiceClient dlp = DlpServiceClient.create()) {
      // Specify what content you want the service to DeIdentify
      ContentItem contentItem = ContentItem.newBuilder().setTable(tableToDeIdentify).build();

      // Specify the type of info the inspection will look for.
      // See https://cloud.google.com/dlp/docs/infotypes-reference for complete list of info types
      List<InfoType> infoTypes =
          Stream.of("PHONE_NUMBER", "EMAIL_ADDRESS")
              .map(it -> InfoType.newBuilder().setName(it).build())
              .collect(Collectors.toList());

      InspectConfig inspectConfig = InspectConfig.newBuilder()
              .addAllInfoTypes(infoTypes)
              .build();

      // Specify the transient key which will encrypt the data.
      TransientCryptoKey transientCryptoKey = TransientCryptoKey.newBuilder()
              .setName(transientKeyName1)
              .build();
      TransientCryptoKey transientCryptoKey2 = TransientCryptoKey.newBuilder()
              .setName(transientKeyName2)
              .build();

      CryptoKey cryptoKey = CryptoKey.newBuilder()
              .setTransient(transientCryptoKey)
              .build();

      CryptoKey cryptoKey2 = CryptoKey.newBuilder()
              .setTransient(transientCryptoKey2)
              .build();

      CryptoHashConfig cryptoHashConfig = CryptoHashConfig.newBuilder()
                  .setCryptoKey(cryptoKey)
                  .build();

      CryptoHashConfig cryptoHashConfig2 = CryptoHashConfig.newBuilder()
              .setCryptoKey(cryptoKey2)
              .build();

      // Define type of de-identification as cryptographic hash transformation.
      PrimitiveTransformation primitiveTransformation = PrimitiveTransformation.newBuilder()
              .setCryptoHashConfig(cryptoHashConfig)
              .build();

      PrimitiveTransformation primitiveTransformation2 = PrimitiveTransformation.newBuilder()
              .setCryptoHashConfig(cryptoHashConfig2)
              .build();

      InfoTypeTransformations.InfoTypeTransformation infoTypeTransformation =
          InfoTypeTransformations.InfoTypeTransformation.newBuilder()
              .setPrimitiveTransformation(primitiveTransformation2)
              .addAllInfoTypes(infoTypes)
              .build();

      InfoTypeTransformations transformations =
          InfoTypeTransformations.newBuilder().addTransformations(infoTypeTransformation).build();

      // Specify fields to be de-identified.
      List<FieldId> fieldIds =
          Stream.of("userid")
              .map(id -> FieldId.newBuilder().setName(id).build())
              .collect(Collectors.toList());

      List<FieldId> fieldIds1 =
          Stream.of("comments")
              .map(id -> FieldId.newBuilder().setName(id).build())
              .collect(Collectors.toList());

      List<FieldTransformation> fieldTransformations = new ArrayList<>();
      fieldTransformations.add(
          FieldTransformation.newBuilder()
              .addAllFields(fieldIds)
              .setPrimitiveTransformation(primitiveTransformation)
              .build());
      fieldTransformations.add(
          FieldTransformation.newBuilder()
              .addAllFields(fieldIds1)
              .setInfoTypeTransformations(transformations)
              .build());

      RecordTransformations recordTransformations = RecordTransformations.newBuilder()
              .addAllFieldTransformations(fieldTransformations)
              .build();

      // Specify the config for the de-identify request
      DeidentifyConfig deidentifyConfig = DeidentifyConfig.newBuilder()
              .setRecordTransformations(recordTransformations)
              .build();

      // Combine configurations into a request for the service.
      DeidentifyContentRequest request =
          DeidentifyContentRequest.newBuilder()
              .setParent(LocationName.of(projectId, "global").toString())
              .setItem(contentItem)
              .setInspectConfig(inspectConfig)
              .setDeidentifyConfig(deidentifyConfig)
              .build();

      // Send the request and receive response from the service.
      DeidentifyContentResponse response = dlp.deidentifyContent(request);

      // Print the results.
      System.out.println("Table after de-identification: " + response.getItem().getTable());
    }
  }
}

Node.js

如要瞭解如何安裝及使用 Sensitive Data Protection 的用戶端程式庫，請參閱「Sensitive Data Protection 用戶端程式庫」。

如要向 Sensitive Data Protection 進行驗證，請設定應用程式預設憑證。詳情請參閱「為本機開發環境設定驗證機制」。

// Imports the Google Cloud client library
const DLP = require('@google-cloud/dlp');
// Instantiates a client
const dlp = new DLP.DlpServiceClient();

// The project ID to run the API call under
// const projectId = 'my-project';

// Crypto key 1
// const transientKey1 = 'YOUR_TRANSIENT_CRYPTO_KEY';

// Crypto key 2
// const transientKey2 = 'YOUR_TRANSIENT_CRYPTO_KEY_2';

// The table to de-identify.
const tableToDeIdentify = {
  headers: [{name: 'userid'}, {name: 'comments'}],
  rows: [
    {
      values: [
        {stringValue: 'user1@example.org'},
        {
          stringValue:
            'my email is user1@example.org and phone is 858-555-0222',
        },
      ],
    },
    {
      values: [
        {stringValue: 'user2@example.org'},
        {
          stringValue:
            'my email is user2@example.org and phone is 858-555-0223',
        },
      ],
    },
    {
      values: [
        {
          stringValue: 'user3@example.org',
        },
        {
          stringValue:
            'my email is user3@example.org and phone is 858-555-0224',
        },
      ],
    },
  ],
};

async function deIdentifyTableWithMultipleCryptoHash() {
  // The type of info the inspection will look for.
  const infoTypes = [{name: 'PHONE_NUMBER'}, {name: 'EMAIL_ADDRESS'}];

  // The fields to be de-identified.
  const fieldIds1 = [{name: 'userid'}];

  const fieldIds2 = [{name: 'comments'}];

  // Construct two primitive transformations using two different keys.
  const primitiveTransformation1 = {
    cryptoHashConfig: {
      cryptoKey: {
        transient: {
          name: transientKey1,
        },
      },
    },
  };

  const primitiveTransformation2 = {
    cryptoHashConfig: {
      cryptoKey: {
        transient: {
          name: transientKey2,
        },
      },
    },
  };

  // Construct infoType transformation using transient key 2
  const infoTypeTransformation = {
    primitiveTransformation: primitiveTransformation2,
    infoTypes: infoTypes,
  };

  // Associate each field with transformation defined above.
  const fieldTransformations = [
    {
      fields: fieldIds1,
      primitiveTransformation: primitiveTransformation1,
    },
    {
      fields: fieldIds2,
      infoTypeTransformations: {
        transformations: [infoTypeTransformation],
      },
    },
  ];

  // Use transformation confiugrations and construct de-identify configuration.
  const deidentifyConfig = {
    recordTransformations: {
      fieldTransformations: fieldTransformations,
    },
  };

  // Combine configurations into a request for the service.
  const request = {
    parent: `projects/${projectId}/locations/global`,
    deidentifyConfig: deidentifyConfig,
    inspectConfig: {
      infoTypes: infoTypes,
    },
    item: {
      table: tableToDeIdentify,
    },
  };

  // Send the request and receive response from the service.
  const [response] = await dlp.deidentifyContent(request);

  const deidentifiedTable = response.item.table;

  // Print the results.
  console.log(
    `Deidentified table: ${JSON.stringify(deidentifiedTable, null, 2)}`
  );
}
deIdentifyTableWithMultipleCryptoHash();

PHP

如要瞭解如何安裝及使用 Sensitive Data Protection 的用戶端程式庫，請參閱「Sensitive Data Protection 用戶端程式庫」。

如要向 Sensitive Data Protection 進行驗證，請設定應用程式預設憑證。詳情請參閱「為本機開發環境設定驗證機制」。

use Google\Cloud\Dlp\V2\Client\DlpServiceClient;
use Google\Cloud\Dlp\V2\ContentItem;
use Google\Cloud\Dlp\V2\CryptoHashConfig;
use Google\Cloud\Dlp\V2\CryptoKey;
use Google\Cloud\Dlp\V2\DeidentifyConfig;
use Google\Cloud\Dlp\V2\DeidentifyContentRequest;
use Google\Cloud\Dlp\V2\FieldId;
use Google\Cloud\Dlp\V2\FieldTransformation;
use Google\Cloud\Dlp\V2\InfoType;
use Google\Cloud\Dlp\V2\InfoTypeTransformations;
use Google\Cloud\Dlp\V2\InfoTypeTransformations\InfoTypeTransformation;
use Google\Cloud\Dlp\V2\InspectConfig;
use Google\Cloud\Dlp\V2\PrimitiveTransformation;
use Google\Cloud\Dlp\V2\RecordTransformations;
use Google\Cloud\Dlp\V2\Table;
use Google\Cloud\Dlp\V2\Table\Row;
use Google\Cloud\Dlp\V2\TransientCryptoKey;
use Google\Cloud\Dlp\V2\Value;

/**
 * De-identify table data with multiple crypto hash.
 * Transform findings using two separate cryptographic hash transformations.
 *
 * @param string $callingProjectId          The Google Cloud project id to use as a parent resource.
 * @param string $inputCsvFile              The input file(csv) path  to deidentify.
 * @param string $outputCsvFile             The oupt file path to save deidentify content.
 * @param string $transientCryptoKeyName1   Specify the random string.
 * @param string $transientCryptoKeyName2   Specify the random string.
 */

function deidentify_table_with_multiple_crypto_hash(
    // TODO(developer): Replace sample parameters before running the code.
    string $callingProjectId,
    string $inputCsvFile = './test/data/table6.csv',
    string $outputCsvFile = './test/data/deidentify_table_with_multiple_crypto_hash_output.csv',
    string $transientCryptoKeyName1 = 'YOUR-TRANSIENT-CRYPTO-KEY-1',
    string $transientCryptoKeyName2 = 'YOUR-TRANSIENT-CRYPTO-KEY-2'
): void {
    // Instantiate a client.
    $dlp = new DlpServiceClient();

    $parent = "projects/$callingProjectId/locations/global";

    // Read a CSV file.
    $csvLines = file($inputCsvFile, FILE_IGNORE_NEW_LINES);
    $csvHeaders = explode(',', $csvLines[0]);
    $csvRows = array_slice($csvLines, 1);

    // Convert CSV file into protobuf objects.
    $tableHeaders = array_map(function ($csvHeader) {
        return (new FieldId)
            ->setName($csvHeader);
    }, $csvHeaders);

    $tableRows = array_map(function ($csvRow) {
        $rowValues = array_map(function ($csvValue) {
            return (new Value())
                ->setStringValue($csvValue);
        }, explode(',', $csvRow));
        return (new Row())
            ->setValues($rowValues);
    }, $csvRows);

    // Construct the table object.
    $tableToDeIdentify = (new Table())
        ->setHeaders($tableHeaders)
        ->setRows($tableRows);

    // Specify what content you want the service to de-identify.
    $content = (new ContentItem())
        ->setTable($tableToDeIdentify);

    // Specify the type of info the inspection will look for.
    // See https://cloud.google.com/dlp/docs/infotypes-reference for complete list of info types
    $infoTypes = [
        (new InfoType())->setName('EMAIL_ADDRESS'),
        (new InfoType())->setName('PHONE_NUMBER')
    ];

    $inspectConfig = (new InspectConfig())
        ->setInfoTypes($infoTypes);

    // ---- First Crypto Hash Rule ----

    // Specify the transient key which will encrypt the data.
    $cryptoHashConfig1 = (new CryptoHashConfig())
        ->setCryptoKey((new CryptoKey())
            ->setTransient((new TransientCryptoKey())
                ->setName($transientCryptoKeyName1)));

    // Define type of de-identification as cryptographic hash transformation.
    $primitiveTransformation1 = (new PrimitiveTransformation())
        ->setCryptoHashConfig($cryptoHashConfig1);

    $fieldTransformation1 = (new FieldTransformation())
        ->setPrimitiveTransformation($primitiveTransformation1)
        // Specify fields to be de-identified.
        ->setFields([
            (new FieldId())->setName('userid')
        ]);

    // ---- Second Crypto Hash Rule ----

    // Specify the transient key which will encrypt the data.
    $cryptoHashConfig2 = (new CryptoHashConfig())
        ->setCryptoKey((new CryptoKey())
            ->setTransient((new TransientCryptoKey())
                ->setName($transientCryptoKeyName2)));

    // Define type of de-identification as cryptographic hash transformation.
    $primitiveTransformation2 = (new PrimitiveTransformation())
        ->setCryptoHashConfig($cryptoHashConfig2);

    $infoTypeTransformation = (new InfoTypeTransformation())
        ->setPrimitiveTransformation($primitiveTransformation2)
        ->setInfoTypes($infoTypes);

    $infoTypeTransformations = (new InfoTypeTransformations())
        ->setTransformations([$infoTypeTransformation]);

    $fieldTransformation2 = (new FieldTransformation())
        ->setInfoTypeTransformations($infoTypeTransformations)
        // Specify fields to be de-identified.
        ->setFields([
            (new FieldId())->setName('comments')
        ]);

    $recordtransformations = (new RecordTransformations())
        ->setFieldTransformations([$fieldTransformation1, $fieldTransformation2]);

    // Specify the config for the de-identify request
    $deidentifyConfig = (new DeidentifyConfig())
        ->setRecordTransformations($recordtransformations);

    // Send the request and receive response from the service.
    $deidentifyContentRequest = (new DeidentifyContentRequest())
        ->setParent($parent)
        ->setInspectConfig($inspectConfig)
        ->setDeidentifyConfig($deidentifyConfig)
        ->setItem($content);
    $response = $dlp->deidentifyContent($deidentifyContentRequest);

    // Print the results.
    $csvRef = fopen($outputCsvFile, 'w');
    fputcsv($csvRef, $csvHeaders);
    foreach ($response->getItem()->getTable()->getRows() as $tableRow) {
        $values = array_map(function ($tableValue) {
            return $tableValue->getStringValue();
        }, iterator_to_array($tableRow->getValues()));
        fputcsv($csvRef, $values);
    };
    printf('Table after deidentify (File Location): %s', $outputCsvFile);
}

Python

如要瞭解如何安裝及使用 Sensitive Data Protection 的用戶端程式庫，請參閱「Sensitive Data Protection 用戶端程式庫」。

如要向 Sensitive Data Protection 進行驗證，請設定應用程式預設憑證。詳情請參閱「為本機開發環境設定驗證機制」。

from typing import Dict, List, Union

import google.cloud.dlp


def deidentify_table_with_multiple_crypto_hash(
    project: str,
    table_data: Dict[str, Union[List[str], List[List[str]]]],
    info_types: List[str],
    transient_key_name_1: str,
    transient_key_name_2: str,
    deid_fields_1: List[str],
    deid_fields_2: List[str],
) -> None:
    """Uses the Data Loss Prevention API to de-identify sensitive data
    in table using multiple transient cryptographic hash keys.
    Args:
        project: The Google Cloud project id to use as a parent resource.
        table_data: Dictionary representing table data.
        info_types: A list of strings representing info types to look for.
            A full list of info type categories can be fetched from the API.
        transient_key_name_1: Name of the first transient crypto key used
            for encryption. The scope of this key is a single API call.
            It is generated for the transformation and then discarded.
        transient_key_name_2: Name of the second transient crypto key used
            for encryption. The scope of this key is a single API call.
            It is generated for the transformation and then discarded.
        deid_fields_1: List of column names in table to de-identify using
            transient_key_name_1.
        deid_fields_2: List of column names in table to de-identify using
            transient_key_name_2.

    """

    # Instantiate a client
    dlp = google.cloud.dlp_v2.DlpServiceClient()

    # Construct the `table`. For more details on the table schema, please see
    # https://cloud.google.com/dlp/docs/reference/rest/v2/ContentItem#Table
    headers = [{"name": val} for val in table_data["header"]]
    rows = []
    for row in table_data["rows"]:
        rows.append({"values": [{"string_value": cell_val} for cell_val in row]})

    table = {"headers": headers, "rows": rows}

    # Construct the `item`
    item = {"table": table}

    # Prepare info_types by converting the list of strings into a list of
    # dictionaries.
    info_types = [{"name": info_type} for info_type in info_types]

    # Construct cryptographic hash configurations using two transient keys
    # which will encrypt the data.
    crypto_hash_config_1 = {"crypto_key": {"transient": {"name": transient_key_name_1}}}
    crypto_hash_config_2 = {"crypto_key": {"transient": {"name": transient_key_name_2}}}

    # Prepare fields to be de-identified by converting list of strings
    # into list of dictionaries.
    deid_fields_1 = [{"name": field} for field in deid_fields_1]
    deid_fields_2 = [{"name": field} for field in deid_fields_2]

    # Specify the type of info the inspection will look for.
    inspect_config = {
        "info_types": info_types,
    }

    # Construct deidentify configuration dictionary.
    deidentify_config = {
        "record_transformations": {
            "field_transformations": [
                {
                    "fields": deid_fields_1,
                    "primitive_transformation": {
                        "crypto_hash_config": crypto_hash_config_1
                    },
                },
                {
                    "fields": deid_fields_2,
                    "info_type_transformations": {
                        "transformations": [
                            {
                                "info_types": info_types,
                                "primitive_transformation": {
                                    "crypto_hash_config": crypto_hash_config_2
                                },
                            }
                        ]
                    },
                },
            ]
        }
    }

    # Convert the project id into a full resource id.
    parent = f"projects/{project}/locations/global"

    # Call the API.
    response = dlp.deidentify_content(
        request={
            "parent": parent,
            "deidentify_config": deidentify_config,
            "inspect_config": inspect_config,
            "item": item,
        }
    )

    # Print the result.
    print(f"Table after de-identification: {response.item.table}")

REST

{ "inspectConfig":{ "infoTypes":[ { "name":"EMAIL_ADDRESS" }, { "name":"PHONE_NUMBER" } ] }, "deidentifyConfig":{ "recordTransformations":{ "fieldTransformations":[ { "fields":[ { "name":"userid" } ], "primitiveTransformation":{ "cryptoHashConfig":{ "cryptoKey":{ "transient":{ "name":"[TRANSIENT-CRYPTO-KEY-1]" } } } } }, { "fields":[ { "name":"comments" } ], "infoTypeTransformations":{ "transformations":[ { "infoTypes":[ { "name":"PHONE_NUMBER" }, { "name":"EMAIL_ADDRESS" } ], "primitiveTransformation":{ "cryptoHashConfig":{ "cryptoKey":{ "transient":{ "name":"[TRANSIENT-CRYPTO-KEY-2]" } } } } } ] } } ] } }, "item":{ "table":{ "headers":[ { "name":"userid" }, { "name":"comments" } ], "rows":[ { "values":[ { "stringValue":"user1@example.org" }, { "stringValue":"my email is user1@example.org and phone is 858-333-2222" } ] }, { "values":[ { "stringValue":"abbyabernathy1" }, { "stringValue":"my userid is abbyabernathy1 and my email is aabernathy@example.com" } ] } ] } } }

使用格式保留加密轉換結果

這個範例示範如何使用 Sensitive Data Protection，將機密字串替換為長度和字母與原始字串相同的權杖。本範例使用 CryptoReplaceFfxFpeConfig 轉換方法。詳情請參閱「格式保留加密」。

C#

如要瞭解如何安裝及使用 Sensitive Data Protection 的用戶端程式庫，請參閱「Sensitive Data Protection 用戶端程式庫」。

如要向 Sensitive Data Protection 進行驗證，請設定應用程式預設憑證。詳情請參閱「為本機開發環境設定驗證機制」。


using System;
using Google.Api.Gax.ResourceNames;
using Google.Cloud.Dlp.V2;
using Google.Protobuf;
using static Google.Cloud.Dlp.V2.CryptoReplaceFfxFpeConfig.Types;

public class DeidentifyTableWithFpe
{
    public static Table DeidentifyTable(
        string projectId,
        string keyName,
        string wrappedKey,
        FfxCommonNativeAlphabet alphabet = FfxCommonNativeAlphabet.Numeric,
        Table tableToInspect = null)
    {
        // Instantiate a client.
        var dlp = DlpServiceClient.Create();

        // Construct the table if null.
        if (tableToInspect == null)
        {
            var row1 = new Value[]
            {
                new Value { StringValue = "11111" },
                new Value { StringValue = "2015" },
                new Value { StringValue = "$10" }
            };
            var row2 = new Value[]
            {
                new Value { StringValue = "33333" },
                new Value { StringValue = "2016" },
                new Value { StringValue = "$20" }
            };
            var row3 = new Value[]
            {
                new Value { StringValue = "22222" },
                new Value { StringValue = "2016" },
                new Value { StringValue = "$15" }
            };

            tableToInspect = new Table
            {
                Headers =
                {
                    new FieldId { Name = "Employee ID" },
                    new FieldId { Name = "Date" },
                    new FieldId { Name = "Compensation" }
                },
                Rows =
                {
                    new Table.Types.Row { Values = { row1 } },
                    new Table.Types.Row { Values = { row2 } },
                    new Table.Types.Row { Values = { row3 } }
                }
            };
        }

        // Provide the table and construct the content item.
        var contentItem = new ContentItem { Table = tableToInspect };

        // Specify an encrypted AES-256 key and the name of the Cloud KMS Key that
        // encrypted it and specify how it should be encrypted.
        var cryptoReplaceFfxFpeConfig = new CryptoReplaceFfxFpeConfig
        {
            CryptoKey = new CryptoKey
            {
                KmsWrapped = new KmsWrappedCryptoKey
                {
                    CryptoKeyName = keyName,
                    WrappedKey = ByteString.FromBase64(wrappedKey)
                }
            },
            CommonAlphabet = alphabet
        };

        // Specify fields to be encrypted.
        var fields = new FieldId[] { new FieldId { Name = "Employee ID" } };

        // Construct the deidentify config using crypto replace config created above.
        var deidentifyConfig = new DeidentifyConfig
        {
            RecordTransformations = new RecordTransformations
            {
                FieldTransformations =
                {
                    new FieldTransformation
                    {
                        PrimitiveTransformation = new PrimitiveTransformation
                        {
                            CryptoReplaceFfxFpeConfig = cryptoReplaceFfxFpeConfig
                        },
                        Fields = { fields }
                    }
                }
            }
        };

        // Construct the request.
        var request = new DeidentifyContentRequest
        {
            ParentAsLocationName = new LocationName(projectId, "global"),
            DeidentifyConfig = deidentifyConfig,
            Item = contentItem,
        };

        // Call the API.
        DeidentifyContentResponse response = dlp.DeidentifyContent(request);

        // Inspect the response.
        Console.WriteLine(response.Item.Table);

        return response.Item.Table;
    }
}

Go

如要瞭解如何安裝及使用 Sensitive Data Protection 的用戶端程式庫，請參閱「Sensitive Data Protection 用戶端程式庫」。

如要向 Sensitive Data Protection 進行驗證，請設定應用程式預設憑證。詳情請參閱「為本機開發環境設定驗證機制」。

import (
	"context"
	"encoding/base64"
	"fmt"
	"io"

	dlp "cloud.google.com/go/dlp/apiv2"
	"cloud.google.com/go/dlp/apiv2/dlppb"
)

// deidentifyTableFPE de-identifies table data with format preserving encryption.
func deidentifyTableFPE(w io.Writer, projectID string, kmsKeyName, wrappedAESKey string) error {
	// projectId := "your-project-id"
	/* keyFileName :=  "projects/YOUR_PROJECT/"
	   + "locations/YOUR_KEYRING_REGION/"
	   + "keyRings/YOUR_KEYRING_NAME/"
	   + "cryptoKeys/YOUR_KEY_NAME"
	*/
	// wrappedAESKey := "YOUR_ENCRYPTED_AES_256_KEY"

	// define your table.
	row1 := &dlppb.Table_Row{
		Values: []*dlppb.Value{
			{Type: &dlppb.Value_StringValue{StringValue: "11111"}},
			{Type: &dlppb.Value_StringValue{StringValue: "2015"}},
			{Type: &dlppb.Value_StringValue{StringValue: "$10"}},
		},
	}

	row2 := &dlppb.Table_Row{
		Values: []*dlppb.Value{
			{Type: &dlppb.Value_StringValue{StringValue: "22222"}},
			{Type: &dlppb.Value_StringValue{StringValue: "2016"}},
			{Type: &dlppb.Value_StringValue{StringValue: "$20"}},
		},
	}

	row3 := &dlppb.Table_Row{
		Values: []*dlppb.Value{
			{Type: &dlppb.Value_StringValue{StringValue: "33333"}},
			{Type: &dlppb.Value_StringValue{StringValue: "2016"}},
			{Type: &dlppb.Value_StringValue{StringValue: "$15"}},
		},
	}

	table := &dlppb.Table{
		Headers: []*dlppb.FieldId{
			{Name: "Employee ID"},
			{Name: "Date"},
			{Name: "Compensation"},
		},
		Rows: []*dlppb.Table_Row{
			{Values: row1.Values},
			{Values: row2.Values},
			{Values: row3.Values},
		},
	}

	ctx := context.Background()

	// Initialize a client once and reuse it to send multiple requests. Clients
	// are safe to use across goroutines. When the client is no longer needed,
	// call the Close method to cleanup its resources.
	client, err := dlp.NewClient(ctx)
	if err != nil {
		return err
	}

	// Closing the client safely cleans up background resources.
	defer client.Close()

	// Specify what content you want the service to de-identify.
	contentItem := &dlppb.ContentItem{
		DataItem: &dlppb.ContentItem_Table{
			Table: table,
		},
	}

	// Specify an encrypted AES-256 key and the name of the Cloud KMS key that encrypted it.
	kmsKeyDecode, err := base64.StdEncoding.DecodeString(wrappedAESKey)
	if err != nil {
		return fmt.Errorf("error in decoding key: %w", err)
	}

	kmsWrappedCryptoKey := &dlppb.KmsWrappedCryptoKey{
		WrappedKey:    kmsKeyDecode,
		CryptoKeyName: kmsKeyName,
	}

	cryptoKey := &dlppb.CryptoKey_KmsWrapped{
		KmsWrapped: kmsWrappedCryptoKey,
	}

	// Specify how the content should be encrypted.
	cryptoReplaceFfxFpeConfig := &dlppb.CryptoReplaceFfxFpeConfig{
		CryptoKey: &dlppb.CryptoKey{
			Source: cryptoKey,
		},
		Alphabet: &dlppb.CryptoReplaceFfxFpeConfig_CommonAlphabet{
			CommonAlphabet: dlppb.CryptoReplaceFfxFpeConfig_NUMERIC,
		},
	}

	primitiveTransformation := &dlppb.PrimitiveTransformation{
		Transformation: &dlppb.PrimitiveTransformation_CryptoReplaceFfxFpeConfig{
			CryptoReplaceFfxFpeConfig: cryptoReplaceFfxFpeConfig,
		},
	}

	// Specify field to be encrypted.
	fieldId := &dlppb.FieldId{
		Name: "Employee ID",
	}

	// Associate the encryption with the specified field.
	fieldTransformation := &dlppb.FieldTransformation{
		Fields: []*dlppb.FieldId{
			fieldId,
		},
		Transformation: &dlppb.FieldTransformation_PrimitiveTransformation{
			PrimitiveTransformation: primitiveTransformation,
		},
	}

	transformations := &dlppb.RecordTransformations{
		FieldTransformations: []*dlppb.FieldTransformation{
			fieldTransformation,
		},
	}

	// Construct the de-identification request to be sent by the client.
	req := &dlppb.DeidentifyContentRequest{
		Parent: fmt.Sprintf("projects/%s/locations/global", projectID),
		DeidentifyConfig: &dlppb.DeidentifyConfig{
			Transformation: &dlppb.DeidentifyConfig_RecordTransformations{
				RecordTransformations: transformations,
			},
		},
		Item: contentItem,
	}

	// Send the request.
	resp, err := client.DeidentifyContent(ctx, req)
	if err != nil {
		return err
	}

	// Print the results.
	fmt.Fprintf(w, "De-identify Table after format-preserving encryption : %+v", resp.GetItem().GetTable())
	return nil
}

Java

如要瞭解如何安裝及使用 Sensitive Data Protection 的用戶端程式庫，請參閱「Sensitive Data Protection 用戶端程式庫」。

如要向 Sensitive Data Protection 進行驗證，請設定應用程式預設憑證。詳情請參閱「為本機開發環境設定驗證機制」。


import com.google.cloud.dlp.v2.DlpServiceClient;
import com.google.common.io.BaseEncoding;
import com.google.privacy.dlp.v2.ContentItem;
import com.google.privacy.dlp.v2.CryptoKey;
import com.google.privacy.dlp.v2.CryptoReplaceFfxFpeConfig;
import com.google.privacy.dlp.v2.CryptoReplaceFfxFpeConfig.FfxCommonNativeAlphabet;
import com.google.privacy.dlp.v2.DeidentifyConfig;
import com.google.privacy.dlp.v2.DeidentifyContentRequest;
import com.google.privacy.dlp.v2.DeidentifyContentResponse;
import com.google.privacy.dlp.v2.FieldId;
import com.google.privacy.dlp.v2.FieldTransformation;
import com.google.privacy.dlp.v2.KmsWrappedCryptoKey;
import com.google.privacy.dlp.v2.LocationName;
import com.google.privacy.dlp.v2.PrimitiveTransformation;
import com.google.privacy.dlp.v2.RecordTransformations;
import com.google.privacy.dlp.v2.Table;
import com.google.privacy.dlp.v2.Table.Row;
import com.google.privacy.dlp.v2.Value;
import com.google.protobuf.ByteString;
import java.io.IOException;

public class DeIdentifyTableWithFpe {

  public static void main(String[] args) throws Exception {
    // TODO(developer): Replace these variables before running the sample.
    String projectId = "your-project-id";
    String kmsKeyName =
        "projects/YOUR_PROJECT/"
            + "locations/YOUR_KEYRING_REGION/"
            + "keyRings/YOUR_KEYRING_NAME/"
            + "cryptoKeys/YOUR_KEY_NAME";
    String wrappedAesKey = "YOUR_ENCRYPTED_AES_256_KEY";
    Table tableToDeIdentify =
        Table.newBuilder()
            .addHeaders(FieldId.newBuilder().setName("Employee ID").build())
            .addHeaders(FieldId.newBuilder().setName("Date").build())
            .addHeaders(FieldId.newBuilder().setName("Compensation").build())
            .addRows(
                Row.newBuilder()
                    .addValues(Value.newBuilder().setStringValue("11111").build())
                    .addValues(Value.newBuilder().setStringValue("2015").build())
                    .addValues(Value.newBuilder().setStringValue("$10").build())
                    .build())
            .addRows(
                Row.newBuilder()
                    .addValues(Value.newBuilder().setStringValue("22222").build())
                    .addValues(Value.newBuilder().setStringValue("2016").build())
                    .addValues(Value.newBuilder().setStringValue("$20").build())
                    .build())
            .addRows(
                Row.newBuilder()
                    .addValues(Value.newBuilder().setStringValue("33333").build())
                    .addValues(Value.newBuilder().setStringValue("2016").build())
                    .addValues(Value.newBuilder().setStringValue("$15").build())
                    .build())
            .build();
    deIdentifyTableWithFpe(projectId, tableToDeIdentify, kmsKeyName, wrappedAesKey);
  }

  public static void deIdentifyTableWithFpe(
      String projectId, Table tableToDeIdentify, String kmsKeyName, String wrappedAesKey)
      throws IOException {
    // Initialize client that will be used to send requests. This client only needs to be created
    // once, and can be reused for multiple requests. After completing all of your requests, call
    // the "close" method on the client to safely clean up any remaining background resources.
    try (DlpServiceClient dlp = DlpServiceClient.create()) {
      // Specify what content you want the service to de-identify.
      ContentItem contentItem = ContentItem.newBuilder().setTable(tableToDeIdentify).build();

      // Specify an encrypted AES-256 key and the name of the Cloud KMS key that encrypted it
      KmsWrappedCryptoKey kmsWrappedCryptoKey =
          KmsWrappedCryptoKey.newBuilder()
              .setWrappedKey(ByteString.copyFrom(BaseEncoding.base64().decode(wrappedAesKey)))
              .setCryptoKeyName(kmsKeyName)
              .build();
      CryptoKey cryptoKey = CryptoKey.newBuilder().setKmsWrapped(kmsWrappedCryptoKey).build();

      // Specify how the content should be encrypted.
      CryptoReplaceFfxFpeConfig cryptoReplaceFfxFpeConfig =
          CryptoReplaceFfxFpeConfig.newBuilder()
              .setCryptoKey(cryptoKey)
              // Set of characters in the input text. For more info, see
              // https://cloud.google.com/dlp/docs/reference/rest/v2/organizations.deidentifyTemplates#DeidentifyTemplate.FfxCommonNativeAlphabet
              .setCommonAlphabet(FfxCommonNativeAlphabet.NUMERIC)
              .build();
      PrimitiveTransformation primitiveTransformation =
          PrimitiveTransformation.newBuilder()
              .setCryptoReplaceFfxFpeConfig(cryptoReplaceFfxFpeConfig)
              .build();

      // Specify field to be encrypted.
      FieldId fieldId = FieldId.newBuilder().setName("Employee ID").build();

      // Associate the encryption with the specified field.
      FieldTransformation fieldTransformation =
          FieldTransformation.newBuilder()
              .setPrimitiveTransformation(primitiveTransformation)
              .addFields(fieldId)
              .build();
      RecordTransformations transformations =
          RecordTransformations.newBuilder().addFieldTransformations(fieldTransformation).build();

      DeidentifyConfig deidentifyConfig =
          DeidentifyConfig.newBuilder().setRecordTransformations(transformations).build();

      // Combine configurations into a request for the service.
      DeidentifyContentRequest request =
          DeidentifyContentRequest.newBuilder()
              .setParent(LocationName.of(projectId, "global").toString())
              .setItem(contentItem)
              .setDeidentifyConfig(deidentifyConfig)
              .build();

      // Send the request and receive response from the service.
      DeidentifyContentResponse response = dlp.deidentifyContent(request);

      // Print the results.
      System.out.println(
          "Table after format-preserving encryption: " + response.getItem().getTable());
    }
  }
}

Node.js

如要瞭解如何安裝及使用 Sensitive Data Protection 的用戶端程式庫，請參閱「Sensitive Data Protection 用戶端程式庫」。

如要向 Sensitive Data Protection 進行驗證，請設定應用程式預設憑證。詳情請參閱「為本機開發環境設定驗證機制」。

// Imports the Google Cloud Data Loss Prevention library
const DLP = require('@google-cloud/dlp');

// Instantiates a client
const dlp = new DLP.DlpServiceClient();

// The project ID to run the API call under
// const projectId = 'my-project';

// The set of characters to replace sensitive ones with
// For more information, see https://cloud.google.com/dlp/docs/reference/rest/v2/organizations.deidentifyTemplates#ffxcommonnativealphabet
// const alphabet = 'NUMERIC';

// The name of the Cloud KMS key used to encrypt ('wrap') the AES-256 key
// const keyName = 'projects/YOUR_GCLOUD_PROJECT/locations/YOUR_LOCATION/keyRings/YOUR_KEYRING_NAME/cryptoKeys/YOUR_KEY_NAME';

// The encrypted ('wrapped') AES-256 key to use
// This key should be encrypted using the Cloud KMS key specified above
// const wrappedKey = 'YOUR_ENCRYPTED_AES_256_KEY'

// Table to de-identify
const tablularData = {
  headers: [{name: 'Employee ID'}, {name: 'Date'}, {name: 'Compensation'}],
  rows: [
    {
      values: [
        {stringValue: '11111'},
        {stringValue: '2015'},
        {stringValue: '$10'},
      ],
    },
    {
      values: [
        {stringValue: '22222'},
        {stringValue: '2016'},
        {stringValue: '$20'},
      ],
    },
    {
      values: [
        {stringValue: '33333'},
        {stringValue: '2016'},
        {stringValue: '$15'},
      ],
    },
  ],
};

async function deidentifyTableWithFpe() {
  // Specify field to be encrypted.
  const fieldIds = [{name: 'Employee ID'}];

  // Specify an encrypted AES-256 key and the name of the Cloud KMS key that encrypted it
  const cryptoKeyConfig = {
    kmsWrapped: {
      wrappedKey: wrappedKey,
      cryptoKeyName: keyName,
    },
  };

  // Specify how the content should be encrypted.
  const cryptoReplaceFfxFpeConfig = {
    cryptoKey: cryptoKeyConfig,
    commonAlphabet: alphabet,
  };

  // Associate the encryption with the specified field.
  const fieldTransformations = [
    {
      fields: fieldIds,
      primitiveTransformation: {
        cryptoReplaceFfxFpeConfig,
      },
    },
  ];

  // Combine configurations into a request for the service.
  const request = {
    parent: `projects/${projectId}/locations/global`,
    deidentifyConfig: {
      recordTransformations: {
        fieldTransformations,
      },
    },
    item: {
      table: tablularData,
    },
  };

  // Send the request and receive response from the service.
  const [response] = await dlp.deidentifyContent(request);

  // Print the results.
  console.log(
    `Table after de-identification: ${JSON.stringify(response.item.table)}`
  );
}
await deidentifyTableWithFpe();

PHP

如要瞭解如何安裝及使用 Sensitive Data Protection 的用戶端程式庫，請參閱「Sensitive Data Protection 用戶端程式庫」。

如要向 Sensitive Data Protection 進行驗證，請設定應用程式預設憑證。詳情請參閱「為本機開發環境設定驗證機制」。


use Google\Cloud\Dlp\V2\Client\DlpServiceClient;
use Google\Cloud\Dlp\V2\ContentItem;
use Google\Cloud\Dlp\V2\CryptoKey;
use Google\Cloud\Dlp\V2\CryptoReplaceFfxFpeConfig;
use Google\Cloud\Dlp\V2\CryptoReplaceFfxFpeConfig\FfxCommonNativeAlphabet;
use Google\Cloud\Dlp\V2\DeidentifyConfig;
use Google\Cloud\Dlp\V2\DeidentifyContentRequest;
use Google\Cloud\Dlp\V2\FieldId;
use Google\Cloud\Dlp\V2\FieldTransformation;
use Google\Cloud\Dlp\V2\KmsWrappedCryptoKey;
use Google\Cloud\Dlp\V2\PrimitiveTransformation;
use Google\Cloud\Dlp\V2\RecordTransformations;
use Google\Cloud\Dlp\V2\Table;
use Google\Cloud\Dlp\V2\Table\Row;
use Google\Cloud\Dlp\V2\Value;

/**
 * De-identify table data with format-preserving encryption.
 * Demonstrates encrypting sensitive data in a table while maintaining format.
 *

 * @param string $callingProjectId      The Google Cloud project id to use as a parent resource.
 * @param string $inputCsvFile          The input file(csv) path  to deidentify.
 * @param string $outputCsvFile         The oupt file path to save deidentify content.
 * @param string $encryptedFieldNames   The field to be encrypted.
 * @param string $kmsKeyName            The name of the Cloud KMS key used to encrypt ('wrap') the AES-256 key.
 * Example: key_name = 'projects/YOUR_GCLOUD_PROJECT/locations/YOUR_LOCATION/keyRings/YOUR_KEYRING_NAME/cryptoKeys/YOUR_KEY_NAME'
 * @param string $wrappedAesKey         The encrypted ('wrapped') AES-256 key to use.

 * */

function deidentify_table_fpe(
    string $callingProjectId,
    string $inputCsvFile,
    string $outputCsvFile,
    string $encryptedFieldNames,
    string $kmsKeyName,
    string $wrappedAesKey
): void {
    // Instantiate a client.
    $dlp = new DlpServiceClient();

    $parent = "projects/$callingProjectId/locations/global";

    // Read a CSV file.
    $csvLines = file($inputCsvFile, FILE_IGNORE_NEW_LINES);
    $csvHeaders = explode(',', $csvLines[0]);
    $csvRows = array_slice($csvLines, 1);

    // Convert CSV file into protobuf objects.
    $tableHeaders = array_map(function ($csvHeader) {
        return (new FieldId)
            ->setName($csvHeader);
    }, $csvHeaders);

    $tableRows = array_map(function ($csvRow) {
        $rowValues = array_map(function ($csvValue) {
            return (new Value())
                ->setStringValue($csvValue);
        }, explode(',', $csvRow));
        return (new Row())
            ->setValues($rowValues);
    }, $csvRows);

    // Construct the table object.
    $tableToDeIdentify = (new Table())
        ->setHeaders($tableHeaders)
        ->setRows($tableRows);

    // Specify the content to be de-identify.
    $content = (new ContentItem())
        ->setTable($tableToDeIdentify);

    // Specify an encrypted AES-256 key and the name of the Cloud KMS key that encrypted it.
    $kmsWrappedCryptoKey = (new KmsWrappedCryptoKey())
        ->setWrappedKey(base64_decode($wrappedAesKey))
        ->setCryptoKeyName($kmsKeyName);

    $cryptoKey = (new CryptoKey())
        ->setKmsWrapped($kmsWrappedCryptoKey);

    // Specify how the content should be encrypted.
    $cryptoReplaceFfxFpeConfig = (new CryptoReplaceFfxFpeConfig())
        ->setCryptoKey($cryptoKey)
        ->setCommonAlphabet(FfxCommonNativeAlphabet::NUMERIC);

    $primitiveTransformation = (new PrimitiveTransformation())
        ->setCryptoReplaceFfxFpeConfig($cryptoReplaceFfxFpeConfig);

    // Specify field to be encrypted.
    $encryptedFields = array_map(function ($encryptedFieldName) {
        return (new FieldId())
            ->setName($encryptedFieldName);
    }, explode(',', $encryptedFieldNames));

    // Associate the encryption with the specified field.
    $fieldTransformation = (new FieldTransformation())
        ->setPrimitiveTransformation($primitiveTransformation)
        ->setFields($encryptedFields);

    $recordtransformations = (new RecordTransformations())
        ->setFieldTransformations([$fieldTransformation]);

    $deidentifyConfig = (new DeidentifyConfig())
        ->setRecordTransformations($recordtransformations);

    // Run request.
    $deidentifyContentRequest = (new DeidentifyContentRequest())
        ->setParent($parent)
        ->setDeidentifyConfig($deidentifyConfig)
        ->setItem($content);
    $response = $dlp->deidentifyContent($deidentifyContentRequest);

    // Print the results.
    $csvRef = fopen($outputCsvFile, 'w');
    fputcsv($csvRef, $csvHeaders);
    foreach ($response->getItem()->getTable()->getRows() as $tableRow) {
        $values = array_map(function ($tableValue) {
            return $tableValue->getStringValue();
        }, iterator_to_array($tableRow->getValues()));
        fputcsv($csvRef, $values);
    };
    printf('Table after format-preserving encryption (File Location): %s', $outputCsvFile);
}

Python

如要瞭解如何安裝及使用 Sensitive Data Protection 的用戶端程式庫，請參閱「Sensitive Data Protection 用戶端程式庫」。

如要向 Sensitive Data Protection 進行驗證，請設定應用程式預設憑證。詳情請參閱「為本機開發環境設定驗證機制」。

from typing import List

import google.cloud.dlp


def deidentify_table_with_fpe(
    project: str,
    table_header: List[str],
    table_rows: List[List[str]],
    deid_field_names: List[str],
    key_name: str = None,
    wrapped_key: bytes = None,
    alphabet: str = None,
) -> None:
    """Uses the Data Loss Prevention API to de-identify sensitive data in a
      table while maintaining format.

    Args:
        project: The Google Cloud project id to use as a parent resource.
        table_header: List of strings representing table field names.
        table_rows: List of rows representing table data.
        deid_field_names: A list of fields in table to de-identify.
        key_name: The name of the Cloud KMS key used to encrypt ('wrap') the
            AES-256 key. Example:
            key_name = 'projects/YOUR_GCLOUD_PROJECT/locations/YOUR_LOCATION/
            keyRings/YOUR_KEYRING_NAME/cryptoKeys/YOUR_KEY_NAME'
        wrapped_key: The decrypted ('wrapped', in bytes) AES-256 key to use. This key
            should be encrypted using the Cloud KMS key specified by key_name.
        alphabet: The set of characters to replace sensitive ones with. For
            more information, see https://cloud.google.com/dlp/docs/reference/
            rest/v2/projects.deidentifyTemplates#ffxcommonnativealphabet
    """

    # Instantiate a client.
    dlp = google.cloud.dlp_v2.DlpServiceClient()

    # Construct the `table`. For more details on the table schema, please see
    # https://cloud.google.com/dlp/docs/reference/rest/v2/ContentItem#Table
    headers = [{"name": val} for val in table_header]
    rows = []
    for row in table_rows:
        rows.append({"values": [{"string_value": cell_val} for cell_val in row]})

    table = {"headers": headers, "rows": rows}

    # Construct the `item` for table.
    item = {"table": table}

    # Specify fields to be de-identified.
    deid_field_names = [{"name": _i} for _i in deid_field_names]

    # Construct FPE configuration dictionary
    crypto_replace_ffx_fpe_config = {
        "crypto_key": {
            "kms_wrapped": {"wrapped_key": wrapped_key, "crypto_key_name": key_name},
        },
        "common_alphabet": alphabet,
    }

    # Construct deidentify configuration dictionary
    deidentify_config = {
        "record_transformations": {
            "field_transformations": [
                {
                    "primitive_transformation": {
                        "crypto_replace_ffx_fpe_config": crypto_replace_ffx_fpe_config
                    },
                    "fields": deid_field_names,
                }
            ]
        }
    }

    # Convert the project id into a full resource id.
    parent = f"projects/{project}/locations/global"

    # Call the API.
    response = dlp.deidentify_content(
        request={"parent": parent, "deidentify_config": deidentify_config, "item": item}
    )

    # Print out results.
    print(f"Table after de-identification: {response.item.table}")

重新識別使用格式保留加密去識別化的發現項目

這個範例說明如何使用 Sensitive Data Protection，重新識別透過 CryptoReplaceFfxFpeConfig 轉換方法去識別化的表格中的機密資料。詳情請參閱「格式保留加密」。

C#

如要瞭解如何安裝及使用 Sensitive Data Protection 的用戶端程式庫，請參閱「Sensitive Data Protection 用戶端程式庫」。

如要向 Sensitive Data Protection 進行驗證，請設定應用程式預設憑證。詳情請參閱「為本機開發環境設定驗證機制」。


using System;
using Google.Api.Gax.ResourceNames;
using Google.Cloud.Dlp.V2;
using Google.Protobuf;
using static Google.Cloud.Dlp.V2.CryptoReplaceFfxFpeConfig.Types;

public class ReidentifyTableDataWithFpe
{
    public static Table ReidentifyTableData(
        string projectId,
        string keyName,
        string wrappedKey,
        FfxCommonNativeAlphabet alphabet = FfxCommonNativeAlphabet.Numeric,
        Table tableToInspect = null)
    {
        // Instantiate a client.
        var dlp = DlpServiceClient.Create();

        // Construct the table if null.
        var table = tableToInspect;

        if (table == null)
        {
            var row1 = new Value[]
            {
                new Value { StringValue = "28777" },
                new Value { StringValue = "Justin" }
            };
            var row2 = new Value[]
            {
                new Value { StringValue = "28778" },
                new Value { StringValue = "Gary" }
            };

            table = new Table
            {
                Headers =
                {
                    new FieldId { Name = "Employee ID" },
                    new FieldId { Name = "Employee Name" }
                },
                Rows =
                {
                    new Table.Types.Row { Values = { row1 } },
                    new Table.Types.Row { Values = { row2 } }
                }
            };
        }

        // Construct the content item by providing the table.
        var contentItem = new ContentItem { Table = table };

        // Specify how to decrypt the previously de-identified information.
        var cryptoReplaceFfxFpeConfig = new CryptoReplaceFfxFpeConfig
        {
            CryptoKey = new CryptoKey
            {
                KmsWrapped = new KmsWrappedCryptoKey
                {
                    CryptoKeyName = keyName,
                    WrappedKey = ByteString.FromBase64(wrappedKey)
                }
            },
            CommonAlphabet = alphabet
        };

        // Specify the field to be decrypted.
        var fields = new FieldId[] { new FieldId { Name = "Employee ID" } };

        // Construct the re-identify config and specify the transformation.
        var reidentifyConfig = new DeidentifyConfig
        {
            RecordTransformations = new RecordTransformations
            {
                FieldTransformations =
                {
                    new FieldTransformation
                    {
                        PrimitiveTransformation = new PrimitiveTransformation
                        {
                            CryptoReplaceFfxFpeConfig = cryptoReplaceFfxFpeConfig,
                        },
                        Fields = { fields }
                    }
                }
            }
        };

        // Construct the request.
        var request = new ReidentifyContentRequest
        {
            Parent = new LocationName(projectId, "global").ToString(),
            Item = contentItem,
            ReidentifyConfig = reidentifyConfig
        };

        // Call the API.
        ReidentifyContentResponse response = dlp.ReidentifyContent(request);

        // Inspect the response.
        Console.WriteLine($"Table after re-identification: {response.Item.Table}");

        return response.Item.Table;
    }
}

Go

如要瞭解如何安裝及使用 Sensitive Data Protection 的用戶端程式庫，請參閱「Sensitive Data Protection 用戶端程式庫」。

如要向 Sensitive Data Protection 進行驗證，請設定應用程式預設憑證。詳情請參閱「為本機開發環境設定驗證機制」。

import (
	"context"
	"encoding/base64"
	"fmt"
	"io"

	dlp "cloud.google.com/go/dlp/apiv2"
	"cloud.google.com/go/dlp/apiv2/dlppb"
)

// reidTableDataWithFPE re-identifies table data with FPE
func reidTableDataWithFPE(w io.Writer, projectID, kmsKeyName, wrappedAesKey string) error {
	// projectId := "my-project-id"
	/* kmsKeyName :=  "projects/YOUR_PROJECT/"
	   + "locations/YOUR_KEYRING_REGION/"
	   + "keyRings/YOUR_KEYRING_NAME/"
	   + "cryptoKeys/YOUR_KEY_NAME"
	*/
	// wrappedAesKey := "YOUR_ENCRYPTED_AES_256_KEY"

	ctx := context.Background()

	// Initialize a client once and reuse it to send multiple requests. Clients
	// are safe to use across goroutines. When the client is no longer needed,
	// call the Close method to cleanup its resources.
	client, err := dlp.NewClient(ctx)
	if err != nil {
		return err
	}

	// Closing the client safely cleans up background resources.
	defer client.Close()

	// Specify the table data that needs to be re-identified.
	tableToReIdentify := &dlppb.Table{
		Headers: []*dlppb.FieldId{
			{Name: "Employee ID"},
		},
		Rows: []*dlppb.Table_Row{
			{
				Values: []*dlppb.Value{
					{
						Type: &dlppb.Value_StringValue{
							StringValue: "90511",
						},
					},
				},
			},
		},
	}

	// Specify the content you want to re-identify.
	contentItem := &dlppb.ContentItem{
		DataItem: &dlppb.ContentItem_Table{
			Table: tableToReIdentify,
		},
	}

	// Specify an encrypted AES-256 key and the name of the Cloud KMS key that encrypted it.
	kmsWrappedCryptoKey, err := base64.StdEncoding.DecodeString(wrappedAesKey)
	if err != nil {
		return err
	}

	cryptoKey := &dlppb.CryptoKey{
		Source: &dlppb.CryptoKey_KmsWrapped{
			KmsWrapped: &dlppb.KmsWrappedCryptoKey{
				WrappedKey:    kmsWrappedCryptoKey,
				CryptoKeyName: kmsKeyName,
			},
		},
	}

	// Specify how to un-encrypt the previously de-identified information.
	cryptoReplaceFfxFpeConfig := &dlppb.CryptoReplaceFfxFpeConfig{
		CryptoKey: cryptoKey,
		Alphabet: &dlppb.CryptoReplaceFfxFpeConfig_CommonAlphabet{
			CommonAlphabet: dlppb.CryptoReplaceFfxFpeConfig_NUMERIC,
		},
	}

	primitiveTransformation := &dlppb.PrimitiveTransformation{
		Transformation: &dlppb.PrimitiveTransformation_CryptoReplaceFfxFpeConfig{
			CryptoReplaceFfxFpeConfig: cryptoReplaceFfxFpeConfig,
		},
	}

	// Specify field to be decrypted.
	fieldId := &dlppb.FieldId{
		Name: "Employee ID",
	}

	// Associate the decryption with the specified field.
	fieldTransformation := &dlppb.FieldTransformation{
		Transformation: &dlppb.FieldTransformation_PrimitiveTransformation{
			PrimitiveTransformation: primitiveTransformation,
		},
		Fields: []*dlppb.FieldId{
			fieldId,
		},
	}

	recordTransformations := &dlppb.RecordTransformations{
		FieldTransformations: []*dlppb.FieldTransformation{
			fieldTransformation,
		},
	}

	deidentifyConfig := &dlppb.DeidentifyConfig{
		Transformation: &dlppb.DeidentifyConfig_RecordTransformations{
			RecordTransformations: recordTransformations,
		},
	}

	// Combine configurations into a request for the service.
	req := &dlppb.ReidentifyContentRequest{
		Parent:           fmt.Sprintf("projects/%s/locations/global", projectID),
		ReidentifyConfig: deidentifyConfig,
		Item:             contentItem,
	}

	// Send the request and receive response from the service.
	resp, err := client.ReidentifyContent(ctx, req)
	if err != nil {
		return err
	}

	// Print the result.
	fmt.Fprintf(w, "Table after re-identification : %v", resp.GetItem().GetTable())
	return nil
}

Java

如要瞭解如何安裝及使用 Sensitive Data Protection 的用戶端程式庫，請參閱「Sensitive Data Protection 用戶端程式庫」。

如要向 Sensitive Data Protection 進行驗證，請設定應用程式預設憑證。詳情請參閱「為本機開發環境設定驗證機制」。


import com.google.cloud.dlp.v2.DlpServiceClient;
import com.google.common.io.BaseEncoding;
import com.google.privacy.dlp.v2.ContentItem;
import com.google.privacy.dlp.v2.CryptoKey;
import com.google.privacy.dlp.v2.CryptoReplaceFfxFpeConfig;
import com.google.privacy.dlp.v2.CryptoReplaceFfxFpeConfig.FfxCommonNativeAlphabet;
import com.google.privacy.dlp.v2.DeidentifyConfig;
import com.google.privacy.dlp.v2.FieldId;
import com.google.privacy.dlp.v2.FieldTransformation;
import com.google.privacy.dlp.v2.KmsWrappedCryptoKey;
import com.google.privacy.dlp.v2.LocationName;
import com.google.privacy.dlp.v2.PrimitiveTransformation;
import com.google.privacy.dlp.v2.RecordTransformations;
import com.google.privacy.dlp.v2.ReidentifyContentRequest;
import com.google.privacy.dlp.v2.ReidentifyContentResponse;
import com.google.privacy.dlp.v2.Table;
import com.google.privacy.dlp.v2.Table.Row;
import com.google.privacy.dlp.v2.Value;
import com.google.protobuf.ByteString;
import java.io.IOException;

public class ReIdentifyTableWithFpe {

  public static void main(String[] args) throws Exception {
    // TODO(developer): Replace these variables before running the sample.
    String projectId = "your-project-id";
    String kmsKeyName =
        "projects/YOUR_PROJECT/"
            + "locations/YOUR_KEYRING_REGION/"
            + "keyRings/YOUR_KEYRING_NAME/"
            + "cryptoKeys/YOUR_KEY_NAME";
    String wrappedAesKey = "YOUR_ENCRYPTED_AES_256_KEY";
    Table tableToReIdentify =
        Table.newBuilder()
            .addHeaders(FieldId.newBuilder().setName("Employee ID").build())
            .addRows(
                Row.newBuilder()
                    .addValues(Value.newBuilder().setStringValue("28777").build())
                    .build())
            .build();
    reIdentifyTableWithFpe(projectId, tableToReIdentify, kmsKeyName, wrappedAesKey);
  }

  public static void reIdentifyTableWithFpe(
      String projectId, Table tableToReIdentify, String kmsKeyName, String wrappedAesKey)
      throws IOException {
    // Initialize client that will be used to send requests. This client only needs to be created
    // once, and can be reused for multiple requests. After completing all of your requests, call
    // the "close" method on the client to safely clean up any remaining background resources.
    try (DlpServiceClient dlp = DlpServiceClient.create()) {
      // Specify what content you want the service to re-identify.
      ContentItem contentItem = ContentItem.newBuilder().setTable(tableToReIdentify).build();

      // Specify an encrypted AES-256 key and the name of the Cloud KMS key that encrypted it.
      KmsWrappedCryptoKey kmsWrappedCryptoKey =
          KmsWrappedCryptoKey.newBuilder()
              .setWrappedKey(ByteString.copyFrom(BaseEncoding.base64().decode(wrappedAesKey)))
              .setCryptoKeyName(kmsKeyName)
              .build();
      CryptoKey cryptoKey = CryptoKey.newBuilder().setKmsWrapped(kmsWrappedCryptoKey).build();

      // Specify how to un-encrypt the previously de-identified information.
      CryptoReplaceFfxFpeConfig cryptoReplaceFfxFpeConfig =
          CryptoReplaceFfxFpeConfig.newBuilder()
              .setCryptoKey(cryptoKey)
              // Set of characters in the input text. For more info, see
              // https://cloud.google.com/dlp/docs/reference/rest/v2/organizations.deidentifyTemplates#DeidentifyTemplate.FfxCommonNativeAlphabet
              .setCommonAlphabet(FfxCommonNativeAlphabet.NUMERIC)
              .build();
      PrimitiveTransformation primitiveTransformation =
          PrimitiveTransformation.newBuilder()
              .setCryptoReplaceFfxFpeConfig(cryptoReplaceFfxFpeConfig)
              .build();

      // Specify field to be decrypted.
      FieldId fieldId = FieldId.newBuilder().setName("Employee ID").build();

      // Associate the decryption with the specified field.
      FieldTransformation fieldTransformation =
          FieldTransformation.newBuilder()
              .setPrimitiveTransformation(primitiveTransformation)
              .addFields(fieldId)
              .build();
      RecordTransformations transformations =
          RecordTransformations.newBuilder().addFieldTransformations(fieldTransformation).build();

      DeidentifyConfig reidentifyConfig =
          DeidentifyConfig.newBuilder().setRecordTransformations(transformations).build();

      // Combine configurations into a request for the service.
      ReidentifyContentRequest request =
          ReidentifyContentRequest.newBuilder()
              .setParent(LocationName.of(projectId, "global").toString())
              .setItem(contentItem)
              .setReidentifyConfig(reidentifyConfig)
              .build();

      // Send the request and receive response from the service
      ReidentifyContentResponse response = dlp.reidentifyContent(request);

      // Print the results
      System.out.println("Table after re-identification: " + response.getItem().getValue());
    }
  }
}

Node.js

如要瞭解如何安裝及使用 Sensitive Data Protection 的用戶端程式庫，請參閱「Sensitive Data Protection 用戶端程式庫」。

如要向 Sensitive Data Protection 進行驗證，請設定應用程式預設憑證。詳情請參閱「為本機開發環境設定驗證機制」。

// Imports the Google Cloud Data Loss Prevention library
const DLP = require('@google-cloud/dlp');

// Instantiates a client
const dlp = new DLP.DlpServiceClient();

// The project ID to run the API call under
// const projectId = 'my-project';

// The set of characters to replace sensitive ones with
// For more information, see https://cloud.google.com/dlp/docs/reference/rest/v2/organizations.deidentifyTemplates#ffxcommonnativealphabet
// const alphabet = 'ALPHA_NUMERIC';

// The name of the Cloud KMS key used to encrypt ('wrap') the AES-256 key
// const keyName = 'projects/YOUR_GCLOUD_PROJECT/locations/YOUR_LOCATION/keyRings/YOUR_KEYRING_NAME/cryptoKeys/YOUR_KEY_NAME';

// The encrypted ('wrapped') AES-256 key to use
// This key should be encrypted using the Cloud KMS key specified above
// const wrappedKey = 'YOUR_ENCRYPTED_AES_256_KEY'

// The name of the surrogate custom info type to use when reidentifying data
// const surrogateType = 'SOME_INFO_TYPE_DEID';

// Table to re-identify
const tablularData = {
  headers: [{name: 'Employee ID'}],
  rows: [{values: [{stringValue: '90511'}]}],
};

async function reidentifyTableWithFpe() {
  // Specify field to be re-identified.
  const fieldIds = [{name: 'Employee ID'}];

  // Specify an encrypted AES-256 key and the name of the Cloud KMS key that encrypted it
  const cryptoKeyConfig = {
    kmsWrapped: {
      wrappedKey: wrappedKey,
      cryptoKeyName: keyName,
    },
  };

  // Associate transformation with crypto key congurations.
  const primitiveTransformation = {
    cryptoReplaceFfxFpeConfig: {
      cryptoKey: cryptoKeyConfig,
      commonAlphabet: alphabet,
    },
  };

  // Combine configurations into a request for the service.
  const request = {
    parent: `projects/${projectId}/locations/global`,
    reidentifyConfig: {
      recordTransformations: {
        fieldTransformations: [
          {
            fields: fieldIds,
            primitiveTransformation: primitiveTransformation,
          },
        ],
      },
    },
    item: {
      table: tablularData,
    },
  };

  // Send the request and receive response from the service.
  const [response] = await dlp.reidentifyContent(request);

  // Print the results.
  console.log(
    `Table after re-identification: ${JSON.stringify(response.item.table)}`
  );
}
await reidentifyTableWithFpe();

PHP

如要瞭解如何安裝及使用 Sensitive Data Protection 的用戶端程式庫，請參閱「Sensitive Data Protection 用戶端程式庫」。

如要向 Sensitive Data Protection 進行驗證，請設定應用程式預設憑證。詳情請參閱「為本機開發環境設定驗證機制」。


use Google\Cloud\Dlp\V2\Client\DlpServiceClient;
use Google\Cloud\Dlp\V2\ContentItem;
use Google\Cloud\Dlp\V2\CryptoKey;
use Google\Cloud\Dlp\V2\CryptoReplaceFfxFpeConfig;
use Google\Cloud\Dlp\V2\CryptoReplaceFfxFpeConfig\FfxCommonNativeAlphabet;
use Google\Cloud\Dlp\V2\DeidentifyConfig;
use Google\Cloud\Dlp\V2\FieldId;
use Google\Cloud\Dlp\V2\FieldTransformation;
use Google\Cloud\Dlp\V2\KmsWrappedCryptoKey;
use Google\Cloud\Dlp\V2\PrimitiveTransformation;
use Google\Cloud\Dlp\V2\RecordTransformations;
use Google\Cloud\Dlp\V2\ReidentifyContentRequest;
use Google\Cloud\Dlp\V2\Table;
use Google\Cloud\Dlp\V2\Table\Row;
use Google\Cloud\Dlp\V2\Value;

/**
 * Re-identify table data with FPE.
 *
 * @param string $callingProjectId      The Google Cloud project id to use as a parent resource.
 * @param string $inputCsvFile          The input file(csv) path  to reidentify.
 * @param string $outputCsvFile         The oupt file path to save reidentify content.
 * @param string $encryptedFieldNames   The field to be encrypted.
 * @param string $kmsKeyName            The name of the Cloud KMS key used to encrypt ('wrap') the AES-256 key.
 * Example: key_name = 'projects/YOUR_GCLOUD_PROJECT/locations/YOUR_LOCATION/keyRings/YOUR_KEYRING_NAME/cryptoKeys/YOUR_KEY_NAME'
 * @param string $wrappedAesKey         The encrypted ('wrapped') AES-256 key to use.
 *
 * */

function reidentify_table_fpe(
    string $callingProjectId,
    string $inputCsvFile,
    string $outputCsvFile,
    string $encryptedFieldNames,
    string $kmsKeyName,
    string $wrappedAesKey
): void {
    // Instantiate a client.
    $dlp = new DlpServiceClient();

    $parent = "projects/$callingProjectId/locations/global";

    // Read a CSV file.
    $csvLines = file($inputCsvFile, FILE_IGNORE_NEW_LINES);
    $csvHeaders = explode(',', $csvLines[0]);
    $csvRows = array_slice($csvLines, 1);

    // Convert CSV file into protobuf objects.
    $tableHeaders = array_map(function ($csvHeader) {
        return (new FieldId)
            ->setName($csvHeader);
    }, $csvHeaders);

    $tableRows = array_map(function ($csvRow) {
        $rowValues = array_map(function ($csvValue) {
            return (new Value())
                ->setStringValue($csvValue);
        }, explode(',', $csvRow));
        return (new Row())
            ->setValues($rowValues);
    }, $csvRows);

    // Construct the table object.
    $tableToDeIdentify = (new Table())
        ->setHeaders($tableHeaders)
        ->setRows($tableRows);

    // Specify the content to be reidentify.
    $content = (new ContentItem())
        ->setTable($tableToDeIdentify);

    // Specify an encrypted AES-256 key and the name of the Cloud KMS key that encrypted it.
    $kmsWrappedCryptoKey = (new KmsWrappedCryptoKey())
        ->setWrappedKey(base64_decode($wrappedAesKey))
        ->setCryptoKeyName($kmsKeyName);

    $cryptoKey = (new CryptoKey())
        ->setKmsWrapped($kmsWrappedCryptoKey);

    // Specify how to un-encrypt the previously de-identified information.
    $cryptoReplaceFfxFpeConfig = (new CryptoReplaceFfxFpeConfig())
        ->setCryptoKey($cryptoKey)
        ->setCommonAlphabet(FfxCommonNativeAlphabet::NUMERIC);

    $primitiveTransformation = (new PrimitiveTransformation())
        ->setCryptoReplaceFfxFpeConfig($cryptoReplaceFfxFpeConfig);

    // Specify field to be decrypted.
    $encryptedFields = array_map(function ($encryptedFieldName) {
        return (new FieldId())
            ->setName($encryptedFieldName);
    }, explode(',', $encryptedFieldNames));

    // Associate the decryption with the specified field.
    $fieldTransformation = (new FieldTransformation())
        ->setPrimitiveTransformation($primitiveTransformation)
        ->setFields($encryptedFields);

    $recordtransformations = (new RecordTransformations())
        ->setFieldTransformations([$fieldTransformation]);

    $reidentifyConfig = (new DeidentifyConfig())
        ->setRecordTransformations($recordtransformations);

    // Run request.
    $reidentifyContentRequest = (new ReidentifyContentRequest())
        ->setParent($parent)
        ->setReidentifyConfig($reidentifyConfig)
        ->setItem($content);
    $response = $dlp->reidentifyContent($reidentifyContentRequest);

    // Print the results.
    $csvRef = fopen($outputCsvFile, 'w');
    fputcsv($csvRef, $csvHeaders);
    foreach ($response->getItem()->getTable()->getRows() as $tableRow) {
        $values = array_map(function ($tableValue) {
            return $tableValue->getStringValue();
        }, iterator_to_array($tableRow->getValues()));
        fputcsv($csvRef, $values);
    };
    printf('Table after re-identification (File Location): %s', $outputCsvFile);
}

Python

如要瞭解如何安裝及使用 Sensitive Data Protection 的用戶端程式庫，請參閱「Sensitive Data Protection 用戶端程式庫」。

如要向 Sensitive Data Protection 進行驗證，請設定應用程式預設憑證。詳情請參閱「為本機開發環境設定驗證機制」。

import base64

from typing import List

import google.cloud.dlp


def reidentify_table_with_fpe(
    project: str,
    table_header: List[str],
    table_rows: List[List[str]],
    reid_field_names: List[str],
    key_name: str = None,
    wrapped_key: bytes = None,
    alphabet: str = None,
) -> None:
    """Uses the Data Loss Prevention API to re-identify sensitive data in a
    table that was encrypted by Format Preserving Encryption (FPE).

    Args:
        project: The Google Cloud project id to use as a parent resource.
        table_header: List of strings representing table field names.
        table_rows: List of rows representing table data.
        reid_field_names: A list of fields in table to re-identify.
        key_name: The name of the Cloud KMS key used to encrypt ('wrap') the
            AES-256 key. Example:
            key_name = 'projects/YOUR_GCLOUD_PROJECT/locations/YOUR_LOCATION/
            keyRings/YOUR_KEYRING_NAME/cryptoKeys/YOUR_KEY_NAME'
        wrapped_key: The decrypted ('wrapped', in bytes) AES-256 key to use. This key
            should be encrypted using the Cloud KMS key specified by key_name.
        alphabet: The set of characters to replace sensitive ones with. For
            more information, see https://cloud.google.com/dlp/docs/reference/
            rest/v2/projects.deidentifyTemplates#ffxcommonnativealphabet
    """

    # Instantiate a client.
    dlp = google.cloud.dlp_v2.DlpServiceClient()

    # Construct the `table`. For more details on the table schema, please see
    # https://cloud.google.com/dlp/docs/reference/rest/v2/ContentItem#Table
    headers = [{"name": val} for val in table_header]
    rows = []
    for row in table_rows:
        rows.append({"values": [{"string_value": cell_val} for cell_val in row]})
    table = {"headers": headers, "rows": rows}

    # Convert table to `item`
    item = {"table": table}

    # Specify fields to be re-identified/decrypted.
    reid_field_names = [{"name": _i} for _i in reid_field_names]

    # Construct FPE configuration dictionary
    crypto_replace_ffx_fpe_config = {
        "crypto_key": {
            "kms_wrapped": {"wrapped_key": wrapped_key, "crypto_key_name": key_name}
        },
        "common_alphabet": alphabet,
    }

    # Construct reidentify configuration dictionary
    reidentify_config = {
        "record_transformations": {
            "field_transformations": [
                {
                    "primitive_transformation": {
                        "crypto_replace_ffx_fpe_config": crypto_replace_ffx_fpe_config,
                    },
                    "fields": reid_field_names,
                }
            ]
        }
    }

    # Convert the project id into a full resource id.
    parent = f"projects/{project}/locations/global"

    # Call the API.
    response = dlp.reidentify_content(
        request={
            "parent": parent,
            "reidentify_config": reidentify_config,
            "item": item,
        }
    )

    # Print out results.
    print(f"Table after re-identification: {response.item.table}")

將表格資料去識別化示例 透過集合功能整理內容 你可以依據偏好儲存及分類內容。

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使用加密編譯雜湊轉換功能轉換調查結果

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