O Cloud Data Loss Prevention (Cloud DLP) faz agora parte da Proteção de dados confidenciais. O nome da API permanece o mesmo: Cloud Data Loss Prevention API (API DLP). Para informações sobre os serviços que compõem a proteção de dados confidenciais, consulte o artigo Vista geral da proteção de dados confidenciais.

Esta página foi traduzida pela API Cloud Translation.

Personalizar a probabilidade de correspondência

Através das regras de palavras-chave de ativação, pode expandir ainda mais os detetores de infoType incorporados e personalizados com regras de contexto avançadas. Uma regra de palavra de ativação indica à proteção de dados confidenciais que ajuste a probabilidade de uma descoberta, consoante a ocorrência de uma palavra de ativação perto dessa descoberta. Uma regra de palavra-chave de ativação é um tipo de regra de inspeção, que é especificada em conjuntos de regras. Cada regra é aplicada a um conjunto de infoTypes incorporados ou personalizados.

Anatomia de uma regra de hotword

Um detetor infoType pode ter zero ou mais regras de palavra de ativação. Na configuração de inspeção, define cada objeto HotwordRule na matriz rules da seguinte forma:

"rules":[
  {
    "hotwordRule":{
      "hotwordRegex":{
        "pattern":"REGEX_PATTERN"
      },
      "proximity":{
        "windowAfter":"NUM_CHARS_TO_CONSIDER_AFTER_FINDING",
        "windowBefore":"NUM_CHARS_TO_CONSIDER_BEFORE_FINDING"
      }
      "likelihoodAdjustment":{
        "fixedLikelihood":"LIKELIHOOD_VALUE"
             -- OR --
        "relativeLikelihood":"LIKELIHOOD_ADJUSTMENT"
      },
    }
  },
  ...
]

Substitua o seguinte:

REGEX_PATTERN: uma expressão regular (objeto Regex) que define o que se qualifica como uma palavra de ativação.
NUM_CHARS_TO_CONSIDER_AFTER_FINDING: um intervalo de carateres após a descoberta. A proteção de dados confidenciais analisa este intervalo para determinar se ocorre uma palavra de ativação perto da descoberta.
NUM_CHARS_TO_CONSIDER_BEFORE_FINDING: um intervalo de carateres antes da descoberta. A proteção de dados confidenciais analisa este intervalo para determinar se ocorre uma palavra de ativação perto da descoberta.
LIKELIHOOD_VALUE: um nível Likelihood fixo para definir a deteção.
LIKELIHOOD_ADJUSTMENT: um número que indica em que medida a proteção de dados confidenciais tem de aumentar ou diminuir a probabilidade da descoberta. Um número inteiro positivo aumenta o nível de probabilidade e um número inteiro negativo diminui-o. Por exemplo, se uma descoberta for POSSIBLE sem a regra de deteção e relativeLikelihood for 1, a descoberta é atualizada para LIKELY. Se relativeLikelihood for -1, a descoberta é desclassificada para UNLIKELY. A probabilidade nunca pode ser inferior a VERY_UNLIKELY nem superior a VERY_LIKELY. Nestes casos, o nível de probabilidade permanece inalterado. Por exemplo, se a probabilidade base for VERY_LIKELY e o valor relativeLikelihood for 1, a probabilidade final continua a ser VERY_LIKELY.

Exemplo de palavra de ativação: fazer corresponder números de registos médicos

Suponhamos que quer detetar um infoType personalizado, como um número de registo médico (MRN), no formato "###-#-#####". Além disso, quer que a proteção de dados confidenciais aumente a probabilidade de correspondência de cada resultado que siga a palavra-chave "MRN".

Exemplos de valores:

123-4-56789 seria uma correspondência como POSSIBLE.
O MRN 123-4-56789 seria correspondente a VERY_LIKELY.

O exemplo JSON e os fragmentos de código seguintes mostram como configurar a regra de palavra-chave de ativação. Este exemplo usa um detetor de expressões regulares personalizado.

Neste exemplo, tenha em atenção o seguinte:

O pedido define o infoType personalizado C_MRN, que é um detetor para qualquer string que corresponda à expressão regular [0-9]{3}-[0-9]{1}-[0-9]{5}.
A expressão regular (?i)(mrn|medical)(?-i) define a palavra-chave. A proteção de dados confidenciais procura esta palavra de ativação dentro do intervalo de carateres definido no campo proximity.
Para cada descoberta C_MRN que tenha uma palavra-chave dentro do conjunto proximity, a proteção de dados confidenciais define o nível de probabilidade como VERY_LIKELY.

C#

Para saber como instalar e usar a biblioteca cliente para a Proteção de dados confidenciais, consulte o artigo Bibliotecas cliente da Proteção de dados confidenciais.

Para se autenticar na Proteção de dados confidenciais, configure as Credenciais padrão da aplicação. Para mais informações, consulte o artigo Configure a autenticação para um ambiente de desenvolvimento local.


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

public class InspectDataWithHotwordRule
{
    public static InspectContentResponse InspectDataHotwordRule(
        string projectId,
        string text,
        string customRegex,
        string hotwordRegex,
        InfoType infoType = null)
    {
        // Instantiate dlp client.
        var dlp = DlpServiceClient.Create();

        // Construct the content item.
        var contentItem = new ContentItem
        {
            ByteItem = new ByteContentItem
            {
                Type = ByteContentItem.Types.BytesType.TextUtf8,
                Data = Google.Protobuf.ByteString.CopyFromUtf8(text)
            }
        };

        // Construct the info type if null.
        var infotype = infoType ?? new InfoType { Name = "C_MRN" };

        // Construct the custom regex detector.
        var customInfoType = new CustomInfoType
        {
            InfoType = infotype,
            Regex = new Regex { Pattern = customRegex },
            Likelihood = Likelihood.Possible
        };

        // Construct hotword rule.
        var hotwordRule = new DetectionRule.Types.HotwordRule
        {
            HotwordRegex = new Regex { Pattern = hotwordRegex },
            LikelihoodAdjustment = new DetectionRule.Types.LikelihoodAdjustment
            {
                FixedLikelihood = Likelihood.VeryLikely
            },
            Proximity = new DetectionRule.Types.Proximity
            {
                WindowBefore = 10
            }
        };

        // Construct the rule set for the inspect config.
        var inspectionRuleSet = new InspectionRuleSet
        {
            InfoTypes = { infotype },
            Rules =
            {
                new InspectionRule
                {
                    HotwordRule = hotwordRule
                }
            }
        };

        // Construct the inspect config.
        var inspectConfig = new InspectConfig
        {
            CustomInfoTypes = { customInfoType },
            IncludeQuote = true,
            RuleSet = { inspectionRuleSet },
        };

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

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

        // Inspect the response.
        Console.WriteLine($"Findings: {response.Result.Findings.Count}");
        foreach (var f in response.Result.Findings)
        {
            Console.WriteLine("Quote: " + f.Quote);
            Console.WriteLine("Info type: " + f.InfoType.Name);
            Console.WriteLine("Likelihood: " + f.Likelihood);
        }
        return response;
    }
}

Go

Para saber como instalar e usar a biblioteca cliente para a Proteção de dados confidenciais, consulte o artigo Bibliotecas cliente da Proteção de dados confidenciais.

import (
	"context"
	"fmt"
	"io"

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

// inspectWithHotWordRules inspects data with hot word rule, it uses custom
// regex with a hot word rule to increase the likelihood match
func inspectWithHotWordRules(w io.Writer, projectID, textToInspect string) error {
	// projectID := "my-project-id"
	// textToInspect := "Patient's MRN 444-5-22222 and just a number 333-2-33333"

	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 type and content to be inspected.
	contentItem := &dlppb.ContentItem{
		DataItem: &dlppb.ContentItem_ByteItem{
			ByteItem: &dlppb.ByteContentItem{
				Type: dlppb.ByteContentItem_TEXT_UTF8,
				Data: []byte(textToInspect),
			},
		},
	}

	// Construct the custom regex detectors
	customInfoType := &dlppb.CustomInfoType{
		InfoType: &dlppb.InfoType{
			Name: "C_MRN",
		},
		Type: &dlppb.CustomInfoType_Regex_{
			Regex: &dlppb.CustomInfoType_Regex{
				Pattern: "[1-9]{3}-[1-9]{1}-[1-9]{5}",
			},
		},
		Likelihood: dlppb.Likelihood_POSSIBLE,
	}

	// Construct hotword rule.
	hotWordRule := &dlppb.CustomInfoType_DetectionRule_HotwordRule{
		HotwordRegex: &dlppb.CustomInfoType_Regex{
			Pattern: "(?i)(mrn|medical)(?-i)",
		},
		Proximity: &dlppb.CustomInfoType_DetectionRule_Proximity{
			WindowBefore: int32(10),
		},
		LikelihoodAdjustment: &dlppb.CustomInfoType_DetectionRule_LikelihoodAdjustment{
			Adjustment: &dlppb.CustomInfoType_DetectionRule_LikelihoodAdjustment_FixedLikelihood{
				FixedLikelihood: dlppb.Likelihood_VERY_LIKELY,
			},
		},
	}

	inspectionRuleSet := &dlppb.InspectionRuleSet{
		Rules: []*dlppb.InspectionRule{
			{
				Type: &dlppb.InspectionRule_HotwordRule{
					HotwordRule: hotWordRule,
				},
			},
		},
		InfoTypes: []*dlppb.InfoType{
			customInfoType.InfoType,
		},
	}

	// Construct the Inspect request to be sent by the client.
	req := &dlppb.InspectContentRequest{
		Parent: fmt.Sprintf("projects/%s/locations/global", projectID),
		Item:   contentItem,
		InspectConfig: &dlppb.InspectConfig{
			CustomInfoTypes: []*dlppb.CustomInfoType{
				customInfoType,
			},
			RuleSet: []*dlppb.InspectionRuleSet{
				inspectionRuleSet,
			},
			IncludeQuote: true,
		},
	}

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

	// Parse the response and process results
	fmt.Fprintf(w, "Findings: %v\n", len(resp.Result.Findings))
	for _, v := range resp.GetResult().Findings {
		fmt.Fprintf(w, "Quote: %v\n", v.GetQuote())
		fmt.Fprintf(w, "InfoType Name: %v\n", v.GetInfoType().GetName())
		fmt.Fprintf(w, "Likelihood: %v\n", v.GetLikelihood())
	}
	return nil
}

Java

Para saber como instalar e usar a biblioteca cliente para a Proteção de dados confidenciais, consulte o artigo Bibliotecas cliente da Proteção de dados confidenciais.


import com.google.cloud.dlp.v2.DlpServiceClient;
import com.google.privacy.dlp.v2.ByteContentItem;
import com.google.privacy.dlp.v2.ByteContentItem.BytesType;
import com.google.privacy.dlp.v2.ContentItem;
import com.google.privacy.dlp.v2.CustomInfoType;
import com.google.privacy.dlp.v2.CustomInfoType.DetectionRule.HotwordRule;
import com.google.privacy.dlp.v2.CustomInfoType.DetectionRule.LikelihoodAdjustment;
import com.google.privacy.dlp.v2.CustomInfoType.DetectionRule.Proximity;
import com.google.privacy.dlp.v2.CustomInfoType.Regex;
import com.google.privacy.dlp.v2.Finding;
import com.google.privacy.dlp.v2.InfoType;
import com.google.privacy.dlp.v2.InspectConfig;
import com.google.privacy.dlp.v2.InspectContentRequest;
import com.google.privacy.dlp.v2.InspectContentResponse;
import com.google.privacy.dlp.v2.InspectionRule;
import com.google.privacy.dlp.v2.InspectionRuleSet;
import com.google.privacy.dlp.v2.Likelihood;
import com.google.privacy.dlp.v2.LocationName;
import com.google.protobuf.ByteString;
import java.io.IOException;

public class InspectWithHotwordRules {

  public static void main(String[] args) throws Exception {
    // TODO(developer): Replace these variables before running the sample.
    String projectId = "your-project-id";
    String textToInspect = "Patient's MRN 444-5-22222 and just a number 333-2-33333";
    String customRegexPattern = "[1-9]{3}-[1-9]{1}-[1-9]{5}";
    String hotwordRegexPattern = "(?i)(mrn|medical)(?-i)";
    inspectWithHotwordRules(projectId, textToInspect, customRegexPattern, hotwordRegexPattern);
  }

  // Inspects a BigQuery Table
  public static void inspectWithHotwordRules(
      String projectId, String textToInspect, String customRegexPattern, String hotwordRegexPattern)
      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 the type and content to be inspected.
      ByteContentItem byteItem =
          ByteContentItem.newBuilder()
              .setType(BytesType.TEXT_UTF8)
              .setData(ByteString.copyFromUtf8(textToInspect))
              .build();
      ContentItem item = ContentItem.newBuilder().setByteItem(byteItem).build();

      // Specify the regex pattern the inspection will look for.
      Regex regex = Regex.newBuilder().setPattern(customRegexPattern).build();

      // Construct the custom regex detector.
      InfoType infoType = InfoType.newBuilder().setName("C_MRN").build();
      CustomInfoType customInfoType =
          CustomInfoType.newBuilder().setInfoType(infoType).setRegex(regex).build();

      // Specify hotword likelihood adjustment.
      LikelihoodAdjustment likelihoodAdjustment =
          LikelihoodAdjustment.newBuilder().setFixedLikelihood(Likelihood.VERY_LIKELY).build();

      // Specify a window around a finding to apply a detection rule.
      Proximity proximity = Proximity.newBuilder().setWindowBefore(10).build();

      // Construct hotword rule.
      HotwordRule hotwordRule =
          HotwordRule.newBuilder()
              .setHotwordRegex(Regex.newBuilder().setPattern(hotwordRegexPattern).build())
              .setLikelihoodAdjustment(likelihoodAdjustment)
              .setProximity(proximity)
              .build();

      // Construct rule set for the inspect config.
      InspectionRuleSet inspectionRuleSet =
          InspectionRuleSet.newBuilder()
              .addInfoTypes(infoType)
              .addRules(InspectionRule.newBuilder().setHotwordRule(hotwordRule))
              .build();

      // Construct the configuration for the Inspect request.
      InspectConfig config =
          InspectConfig.newBuilder()
              .addCustomInfoTypes(customInfoType)
              .setIncludeQuote(true)
              .setMinLikelihood(Likelihood.POSSIBLE)
              .addRuleSet(inspectionRuleSet)
              .build();

      // Construct the Inspect request to be sent by the client.
      InspectContentRequest request =
          InspectContentRequest.newBuilder()
              .setParent(LocationName.of(projectId, "global").toString())
              .setItem(item)
              .setInspectConfig(config)
              .build();

      // Use the client to send the API request.
      InspectContentResponse response = dlp.inspectContent(request);

      // Parse the response and process results
      System.out.println("Findings: " + response.getResult().getFindingsCount());
      for (Finding f : response.getResult().getFindingsList()) {
        System.out.println("\tQuote: " + f.getQuote());
        System.out.println("\tInfo type: " + f.getInfoType().getName());
        System.out.println("\tLikelihood: " + f.getLikelihood());
      }
    }
  }
}

Node.js

Para saber como instalar e usar a biblioteca cliente para a Proteção de dados confidenciais, consulte o artigo Bibliotecas cliente da Proteção de dados confidenciais.

// 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 string to inspect
// const string = 'Patients MRN 444-5-22222';

// The minimum likelihood required before returning a match
// const minLikelihood = DLP.protos.google.privacy.dlp.v2.Likelihood.POSSIBLE;

// The maximum number of findings to report per request (0 = server maximum)
// const maxFindings = 0;

// The infoTypes of information to match
// See https://cloud.google.com/dlp/docs/concepts-infotypes for more information
// about supported infoTypes.
// const infoTypes = [{ name: 'EMAIL_ADDRESS' }];

// The customInfoTypes of information to match
// const customInfoTypes = [{ infoType: { name: 'DICT_TYPE' }, dictionary: { wordList: { words: ['foo', 'bar', 'baz']}}},
//   { infoType: { name: 'REGEX_TYPE' }, regex: {pattern: '\\(\\d{3}\\) \\d{3}-\\d{4}'}}];

// Whether to include the matching string
// const includeQuote = true;

// Custom hotword regex patten
// const hotwordRegexPattern = '(?i)(mrn|medical)(?-i)';

async function inspectWithHotwordRule() {
  // Construct item to inspect
  const item = {
    byteItem: {
      type: DLP.protos.google.privacy.dlp.v2.ByteContentItem.BytesType
        .TEXT_UTF8,
      data: Buffer.from(string, 'utf-8'),
    },
  };

  // Construct a hot word rule
  const hotwordRule = {
    hotwordRegex: {
      pattern: hotwordRegexPattern,
    },
    proximity: {
      windowBefore: 10,
    },
    likelihoodAdjustment: {
      fixedLikelihood:
        DLP.protos.google.privacy.dlp.v2.Likelihood.VERY_LIKELY,
    },
  };

  // Construct a hotword inspection rule
  const inpectionRuleSet = [
    {
      infoTypes: customInfoTypes.map(
        customInfoType => customInfoType.infoType
      ),
      rules: [{hotwordRule: hotwordRule}],
    },
  ];

  // Assigns likelihood to each match
  customInfoTypes = customInfoTypes.map(customInfoType => {
    customInfoType.likelihood =
      DLP.protos.google.privacy.dlp.v2.Likelihood.POSSIBLE;
    return customInfoType;
  });

  // Construct request
  const request = {
    parent: `projects/${projectId}/locations/global`,
    inspectConfig: {
      infoTypes: infoTypes,
      customInfoTypes: customInfoTypes,
      minLikelihood: minLikelihood,
      includeQuote: includeQuote,
      limits: {
        maxFindingsPerRequest: maxFindings,
      },
      ruleSet: inpectionRuleSet,
    },
    item: item,
  };

  // Run request
  const [response] = await dlp.inspectContent(request);
  const findings = response.result.findings;
  if (findings.length > 0) {
    console.log('Findings:');
    findings.forEach(finding => {
      if (includeQuote) {
        console.log(`\tQuote: ${finding.quote}`);
      }
      console.log(`\tInfo type: ${finding.infoType.name}`);
      console.log(`\tLikelihood: ${finding.likelihood}`);
    });
  } else {
    console.log('No findings.');
  }
}
inspectWithHotwordRule();

PHP

Para saber como instalar e usar a biblioteca cliente para a Proteção de dados confidenciais, consulte o artigo Bibliotecas cliente da Proteção de dados confidenciais.

use Google\Cloud\Dlp\V2\Client\DlpServiceClient;
use Google\Cloud\Dlp\V2\ContentItem;
use Google\Cloud\Dlp\V2\CustomInfoType;
use Google\Cloud\Dlp\V2\CustomInfoType\DetectionRule\HotwordRule;
use Google\Cloud\Dlp\V2\CustomInfoType\DetectionRule\LikelihoodAdjustment;
use Google\Cloud\Dlp\V2\CustomInfoType\DetectionRule\Proximity;
use Google\Cloud\Dlp\V2\CustomInfoType\Regex;
use Google\Cloud\Dlp\V2\InfoType;
use Google\Cloud\Dlp\V2\InspectConfig;
use Google\Cloud\Dlp\V2\InspectContentRequest;
use Google\Cloud\Dlp\V2\InspectionRule;
use Google\Cloud\Dlp\V2\InspectionRuleSet;
use Google\Cloud\Dlp\V2\Likelihood;

/**
 * Inspect data with a hotword rule
 * This sample uses a custom regex with a hotword rule to increase the likelihood of match.
 *
 * @param string $projectId         The Google Cloud project id to use as a parent resource.
 * @param string $textToInspect     The string to inspect.
 */
function inspect_hotword_rule(
    // TODO(developer): Replace sample parameters before running the code.
    string $projectId,
    string $textToInspect = "Patient's MRN 444-5-22222 and just a number 333-2-33333"
): void {
    // Instantiate a client.
    $dlp = new DlpServiceClient();

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

    // Specify what content you want the service to Inspect.
    $item = (new ContentItem())
        ->setValue($textToInspect);

    // Specify the regex pattern the inspection will look for.
    $customRegexPattern = '[1-9]{3}-[1-9]{1}-[1-9]{5}';
    $hotwordRegexPattern = '(?i)(mrn|medical)(?-i)';

    // Construct the custom regex detector.
    $cMrnDetector = (new InfoType())
        ->setName('C_MRN');
    $customInfoType = (new CustomInfoType())
        ->setInfoType($cMrnDetector)
        ->setLikelihood(Likelihood::POSSIBLE)
        ->setRegex((new Regex())
            ->setPattern($customRegexPattern));

    // Specify hotword likelihood adjustment.
    $likelihoodAdjustment = (new LikelihoodAdjustment())
        ->setFixedLikelihood(Likelihood::VERY_LIKELY);

    // Specify a window around a finding to apply a detection rule.
    $proximity = (new Proximity())
        ->setWindowBefore(10);

    $hotwordRule = (new HotwordRule())
        ->setHotwordRegex((new Regex())
            ->setPattern($hotwordRegexPattern))
        ->setLikelihoodAdjustment($likelihoodAdjustment)
        ->setProximity($proximity);

    // Construct rule set for the inspect config.
    $inspectionRuleSet = (new InspectionRuleSet())
        ->setInfoTypes([$cMrnDetector])
        ->setRules([
            (new InspectionRule())
                ->setHotwordRule($hotwordRule)
        ]);

    // Construct the configuration for the Inspect request.
    $inspectConfig = (new InspectConfig())
        ->setCustomInfoTypes([$customInfoType])
        ->setIncludeQuote(true)
        ->setRuleSet([$inspectionRuleSet]);

    // Run request
    $inspectContentRequest = (new InspectContentRequest())
        ->setParent($parent)
        ->setInspectConfig($inspectConfig)
        ->setItem($item);
    $response = $dlp->inspectContent($inspectContentRequest);

    // Print the results
    $findings = $response->getResult()->getFindings();
    if (count($findings) == 0) {
        printf('No findings.' . PHP_EOL);
    } else {
        printf('Findings:' . PHP_EOL);
        foreach ($findings as $finding) {
            printf('  Quote: %s' . PHP_EOL, $finding->getQuote());
            printf('  Info type: %s' . PHP_EOL, $finding->getInfoType()->getName());
            printf('  Likelihood: %s' . PHP_EOL, Likelihood::name($finding->getLikelihood()));
        }
    }
}

Python

Para saber como instalar e usar a biblioteca cliente para a Proteção de dados confidenciais, consulte o artigo Bibliotecas cliente da Proteção de dados confidenciais.

import google.cloud.dlp


def inspect_data_w_custom_hotwords(
    project: str,
    content_string: str,
) -> None:
    """Uses the Data Loss Prevention API to analyze string with medical record
       number custom regex detector, with custom hotwords rules to boost finding
       certainty under some circumstances.

    Args:
        project: The Google Cloud project id to use as a parent resource.
        content_string: The string to inspect.

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

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

    # Construct a custom regex detector info type called "C_MRN",
    # with ###-#-##### pattern, where each # represents a digit from 1 to 9.
    # The detector has a detection likelihood of POSSIBLE.
    custom_info_types = [
        {
            "info_type": {"name": "C_MRN"},
            "regex": {"pattern": "[1-9]{3}-[1-9]{1}-[1-9]{5}"},
            "likelihood": google.cloud.dlp_v2.Likelihood.POSSIBLE,
        }
    ]

    # Construct a rule set with hotwords "mrn" and "medical", with a likelohood
    # boost to VERY_LIKELY when hotwords are present within the 10 character-
    # window preceding the PII finding.
    hotword_rule = {
        "hotword_regex": {"pattern": "(?i)(mrn|medical)(?-i)"},
        "likelihood_adjustment": {
            "fixed_likelihood": google.cloud.dlp_v2.Likelihood.VERY_LIKELY
        },
        "proximity": {"window_before": 10},
    }

    rule_set = [
        {"info_types": [{"name": "C_MRN"}], "rules": [{"hotword_rule": hotword_rule}]}
    ]

    # Construct the configuration dictionary with the custom regex info type.
    inspect_config = {
        "custom_info_types": custom_info_types,
        "rule_set": rule_set,
        "include_quote": True,
    }

    # Construct the `item`.
    item = {"value": content_string}

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

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

    # Print out the results.
    if response.result.findings:
        for finding in response.result.findings:
            print(f"Quote: {finding.quote}")
            print(f"Info type: {finding.info_type.name}")
            print(f"Likelihood: {finding.likelihood}")
    else:
        print("No findings.")

REST

Consulte o início rápido de JSON para mais informações sobre a utilização da API DLP com JSON.

Método HTTP e URL:

POST https://dlp.googleapis.com/v2/projects/PROJECT_ID/content:inspect

Substitua PROJECT_ID pelo ID do projeto.

Entrada JSON:

{
  "item":{
    "value":"Patient's MRN 444-5-22222 and just a number 333-2-33333"
  },
  "inspectConfig":{
    "customInfoTypes":[
      {
        "infoType":{
          "name":"C_MRN"
        },
        "regex":{
          "pattern":"[0-9]{3}-[0-9]{1}-[0-9]{5}"
        },
        "likelihood":"POSSIBLE",
      }
    ],
    "ruleSet":[
        {
        "infoTypes": [{"name" : "C_MRN"}],
        "rules":[
          {
            "hotwordRule":{
              "hotwordRegex":{
                "pattern":"(?i)(mrn|medical)(?-i)"
              },
              "likelihoodAdjustment":{
                "fixedLikelihood":"VERY_LIKELY"
              },
              "proximity":{
                "windowBefore":10
              }
            }
          }
        ]
      }
    ]
  }
}

Saída JSON (abreviada):

{
  "result": {
    "findings": [
      {
        "infoType": {
          "name": "C_MRN"
        },
        "likelihood": "VERY_LIKELY",
        "location": {
          "byteRange": {
            "start": "14",
            "end": "25"
          },
          "codepointRange": { ... }
        }
      },
      {
        "infoType": {
          "name": "C_MRN"
        },
        "likelihood": "POSSIBLE",
          "byteRange": {
            "start": "44",
            "end": "55"
          },
          "codepointRange": { ... }
        }
      }
    ]
  }
}

O resultado mostra que a proteção de dados confidenciais identificou corretamente o número do registo médico através do detetor de infoType personalizado C_MRN. Além disso, devido à correspondência de contexto na regra de palavra de ativação, a proteção de dados confidenciais atribuiu ao primeiro resultado, que tinha um MRN no conjunto proximity, uma probabilidade de VERY_LIKELY, conforme configurado. A segunda descoberta não tinha contexto, pelo que o likelihood permaneceu em POSSIBLE.

Exemplo de palavra-chave: defina a probabilidade de correspondência de uma coluna da tabela

Este exemplo demonstra como pode definir a probabilidade de correspondência de uma coluna inteira de dados. Esta abordagem é útil, por exemplo, se quiser excluir uma coluna de dados dos resultados da inspeção.

Considere a seguinte tabela. Uma coluna contém números da segurança social (SSNs) de marcadores de posição e outra contém SSNs reais.

Número de beneficiário da segurança social falso	Número de Identificação da Segurança Social real
111-11-1111	222-22-2222

Para minimizar o ruído nos resultados da inspeção, pode excluir quaisquer conclusões na coluna Fake Social Security Number. Atribua um nível de probabilidade baixo a esta coluna. Em seguida, configure o pedido de forma que as correspondências com esse nível de probabilidade sejam excluídas dos resultados.

Neste exemplo, tenha em atenção o seguinte:

A regra de palavra de ativação é aplicada ao US_SOCIAL_SECURITY_NUMBER infoType.
A expressão regular da palavra-chave de ativação (Fake Social Security Number) contém o nome da coluna que tem os valores dos marcadores de posição.
A propriedade windowBefore está definida como 1, o que significa que a palavra de ativação está num cabeçalho de coluna e as conclusões têm de estar na coluna.
Para cada resultado US_SOCIAL_SECURITY_NUMBER nesta coluna, o Sensitive Data Protection define o nível de probabilidade como VERY_UNLIKELY.
A propriedade minLikelihood está definida como POSSIBLE, o que significa que qualquer descoberta que tenha um nível de probabilidade inferior a POSSIBLE é excluída dos resultados da inspeção.

Consulte o início rápido de JSON para mais informações sobre a utilização da API DLP com JSON.

Método HTTP e URL:

POST https://dlp.googleapis.com/v2/projects/PROJECT_ID/content:inspect

Substitua PROJECT_ID pelo ID do projeto.

C#

Para saber como instalar e usar a biblioteca cliente para a Proteção de dados confidenciais, consulte o artigo Bibliotecas cliente da Proteção de dados confidenciais.



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

public class InspectTableWithCustomHotwords
{
    public static InspectResult InspectTable(
        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 = "111-11-1111" },
                new Value { StringValue = "222-22-2222" }
            };
            tableToInspect = new Table
            {
                Headers =
                {
                    new FieldId { Name = "Fake Social Security Number" },
                    new FieldId { Name = "Real Social Security Number" }
                },
                Rows =
                {
                    new Table.Types.Row { Values = { row1 } }
                }
            };
        }

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

        // Specify the type of info to be inspected.
        var infotypes = infoTypes ?? new InfoType[] { new InfoType { Name = "US_SOCIAL_SECURITY_NUMBER" } };

        // Construct the Inspection Rule Set by specifying the hotword rule as detection rule.
        var ruleSet = new InspectionRuleSet[]
        {
            new InspectionRuleSet
            {
                InfoTypes = { infotypes },
                Rules =
                {
                    new InspectionRule
                    {
                        HotwordRule = new DetectionRule.Types.HotwordRule
                        {
                            HotwordRegex = new Regex
                            {
                                Pattern = "(Fake Social Security Number)"
                            },
                            LikelihoodAdjustment = new DetectionRule.Types.LikelihoodAdjustment
                            {
                                FixedLikelihood = Likelihood.VeryUnlikely
                            },
                            Proximity = new DetectionRule.Types.Proximity
                            {
                                WindowBefore = 1
                            }
                        }
                    }
                }
            }
        };

        // Construct the request.
        var request = new InspectContentRequest
        {
            InspectConfig = new InspectConfig
            {
                InfoTypes = { infotypes },
                IncludeQuote = true,
                MinLikelihood = Likelihood.Possible,
                RuleSet = { ruleSet }
            },
            ParentAsLocationName = new LocationName(projectId, "global"),
            Item = contentItem
        };

        // Call the API.
        InspectContentResponse response = dlp.InspectContent(request);

        // Inspect the results.
        var resultFindings = response.Result.Findings;

        Console.WriteLine($"Findings: {resultFindings.Count}");

        foreach (var f in resultFindings)
        {
            Console.WriteLine("\tQuote: " + f.Quote);
            Console.WriteLine("\tInfo type: " + f.InfoType.Name);
            Console.WriteLine("\tLikelihood: " + f.Likelihood);
        }

        return response.Result;
    }
}

Go

Para saber como instalar e usar a biblioteca cliente para a Proteção de dados confidenciais, consulte o artigo Bibliotecas cliente da Proteção de dados confidenciais.


import (
	"context"
	"fmt"
	"io"

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

// inspectTableWithCustomHotword Sets the match likelihood of a table column to customize data inspection results.
// This example showcases how you can adjust the match likelihood for an entire column of data, enabling the
// exclusion of specific columns from inspection if needed.
func inspectTableWithCustomHotword(w io.Writer, projectID, hotwordRegexPattern string) error {
	// projectID := "your-project-id"
	// hotwordRegexPattern := "(Fake Social Security Number)"

	tableToInspect := &dlppb.Table{
		Headers: []*dlppb.FieldId{
			{Name: "Fake Social Security Number"},
			{Name: "Real Social Security Number"},
		},
		Rows: []*dlppb.Table_Row{
			{
				Values: []*dlppb.Value{
					{
						Type: &dlppb.Value_StringValue{StringValue: "111-11-1111"},
					},
					{
						Type: &dlppb.Value_StringValue{StringValue: "222-22-2222"},
					},
				},
			},
		},
	}

	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_Table{
		Table: tableToInspect,
	}

	// Specify the likelihood adjustment to adjust the match likelihood for your detection rule
	// based on your needs and desired level of sensitivity in data analysis.
	likelihoodAdjustment := &dlppb.CustomInfoType_DetectionRule_LikelihoodAdjustment{
		Adjustment: &dlppb.CustomInfoType_DetectionRule_LikelihoodAdjustment_FixedLikelihood{
			FixedLikelihood: dlppb.Likelihood_VERY_UNLIKELY,
		},
	}

	// 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: "US_SOCIAL_SECURITY_NUMBER"},
	}

	// Specify the proximity so that It helps identify sensitive information
	// occurring near other data points, enabling more context-aware analysis.
	proximity := &dlppb.CustomInfoType_DetectionRule_Proximity{
		WindowBefore: 5,
	}

	// Construct hotWord rule.
	hotwordRule := &dlppb.CustomInfoType_DetectionRule_HotwordRule{
		HotwordRegex: &dlppb.CustomInfoType_Regex{
			Pattern: hotwordRegexPattern,
		},
		Proximity:            proximity,
		LikelihoodAdjustment: likelihoodAdjustment,
	}

	// Construct rule set for the inspect config.
	inspectionRuleSet := &dlppb.InspectionRuleSet{
		InfoTypes: infoTypes,
		Rules: []*dlppb.InspectionRule{
			{
				Type: &dlppb.InspectionRule_HotwordRule{
					HotwordRule: hotwordRule,
				},
			},
		},
	}

	// Construct the configuration for the Inspect request.
	config := &dlppb.InspectConfig{
		IncludeQuote:  true,
		InfoTypes:     infoTypes,
		MinLikelihood: dlppb.Likelihood_POSSIBLE,
		RuleSet: []*dlppb.InspectionRuleSet{
			inspectionRuleSet,
		},
	}

	// Construct the Inspect request to be sent by the client.
	req := &dlppb.InspectContentRequest{
		Parent: fmt.Sprintf("projects/%s/locations/global", projectID),
		Item: &dlppb.ContentItem{
			DataItem: contentItem,
		},
		InspectConfig: config,
	}
	// Send the request.
	resp, err := client.InspectContent(ctx, req)
	if err != nil {
		return err
	}

	// Parse the response and process results.
	fmt.Fprintf(w, "Findings: %v\n", len(resp.Result.Findings))
	for _, v := range resp.GetResult().Findings {
		fmt.Fprintf(w, "Quote: %v\n", v.GetQuote())
		fmt.Fprintf(w, "Infotype Name: %v\n", v.GetInfoType().GetName())
		fmt.Fprintf(w, "Likelihood: %v\n", v.GetLikelihood())
	}
	return nil
}

Java

Para saber como instalar e usar a biblioteca cliente para a Proteção de dados confidenciais, consulte o artigo Bibliotecas cliente da Proteção de dados confidenciais.


import com.google.cloud.dlp.v2.DlpServiceClient;
import com.google.privacy.dlp.v2.ContentItem;
import com.google.privacy.dlp.v2.CustomInfoType;
import com.google.privacy.dlp.v2.FieldId;
import com.google.privacy.dlp.v2.Finding;
import com.google.privacy.dlp.v2.InfoType;
import com.google.privacy.dlp.v2.InspectConfig;
import com.google.privacy.dlp.v2.InspectContentRequest;
import com.google.privacy.dlp.v2.InspectContentResponse;
import com.google.privacy.dlp.v2.InspectionRule;
import com.google.privacy.dlp.v2.InspectionRuleSet;
import com.google.privacy.dlp.v2.Likelihood;
import com.google.privacy.dlp.v2.LocationName;
import com.google.privacy.dlp.v2.Table;
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 InspectTableWithCustomHotword {

  public static void main(String[] args) throws IOException {
    // 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";
    // Specify the table to be considered for de-identification.
    Table tableToDeIdentify =
        Table.newBuilder()
            .addHeaders(FieldId.newBuilder().setName("Some Social Security Number").build())
            .addHeaders(FieldId.newBuilder().setName("Real Social Security Number").build())
            .addRows(
                Table.Row.newBuilder()
                    .addValues(Value.newBuilder().setStringValue("111-11-1111").build())
                    .addValues(Value.newBuilder().setStringValue("222-22-2222").build())
                    .build())
            .build();
    // Specify the regex pattern to be detected.
    // Refer https://github.com/google/re2/wiki/Syntax for creating regular expression.
    String hotwordRegexPattern = "Some Social Security Number";
    inspectDemotingFindingsWithHotwords(projectId, tableToDeIdentify, hotwordRegexPattern);
  }

  //  Inspects the provided table, excluding the findings of entire column matching regular
  // expression.
  public static void inspectDemotingFindingsWithHotwords(
      String projectId, Table tableToDeIdentify, String hotwordRegexPattern) 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();

      CustomInfoType.DetectionRule.LikelihoodAdjustment likelihoodAdjustment =
          CustomInfoType.DetectionRule.LikelihoodAdjustment.newBuilder()
              .setFixedLikelihood(Likelihood.VERY_UNLIKELY)
              .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("US_SOCIAL_SECURITY_NUMBER")
              .map(it -> InfoType.newBuilder().setName(it).build())
              .collect(Collectors.toList());

      CustomInfoType.DetectionRule.Proximity proximity =
          CustomInfoType.DetectionRule.Proximity.newBuilder().setWindowBefore(1).build();

      // Construct hotword rule.
      CustomInfoType.DetectionRule.HotwordRule hotwordRule =
          CustomInfoType.DetectionRule.HotwordRule.newBuilder()
              .setHotwordRegex(
                  CustomInfoType.Regex.newBuilder().setPattern(hotwordRegexPattern).build())
              .setLikelihoodAdjustment(likelihoodAdjustment)
              .setProximity(proximity)
              .build();

      // Construct rule set for the inspect config.
      InspectionRuleSet inspectionRuleSet =
          InspectionRuleSet.newBuilder()
              .addAllInfoTypes(infoTypes)
              .addRules(InspectionRule.newBuilder().setHotwordRule(hotwordRule))
              .build();

      // Construct the configuration for the Inspect request.
      InspectConfig config =
          InspectConfig.newBuilder()
              .setIncludeQuote(true)
              .setMinLikelihood(Likelihood.POSSIBLE)
              .addRuleSet(inspectionRuleSet)
              .addAllInfoTypes(infoTypes)
              .build();

      // Construct the Inspect request to be sent by the client.
      InspectContentRequest request =
          InspectContentRequest.newBuilder()
              .setParent(LocationName.of(projectId, "global").toString())
              .setItem(contentItem)
              .setInspectConfig(config)
              .build();

      InspectContentResponse response = dlp.inspectContent(request);
      // Parse the response and process results.
      System.out.println("Findings: " + response.getResult().getFindingsCount());
      for (Finding f : response.getResult().getFindingsList()) {
        System.out.println("\tQuote: " + f.getQuote());
        System.out.println("\tInfo type: " + f.getInfoType().getName());
        System.out.println("\tLikelihood: " + f.getLikelihood());
      }
    }
  }
}

Node.js

Para saber como instalar e usar a biblioteca cliente para a Proteção de dados confidenciais, consulte o artigo Bibliotecas cliente da Proteção de dados confidenciais.

// 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 = "your-project-id";

// Table to inspect
const tableToInspect = {
  headers: [
    {name: 'Fake Social Security Number'},
    {name: 'Real Social Security Number'},
  ],
  rows: [
    {
      values: [{stringValue: '111-11-1111'}, {stringValue: '222-22-2222'}],
    },
  ],
};

async function inspectWithCustomHotwords() {
  // Specify the regex pattern to be detected.
  const hotwordRegexPattern = '(Fake Social Security Number)';

  // Specify what content you want the service to de-identify.
  const contentItem = {
    table: tableToInspect,
  };

  // Specify the type of info the inspection will look for.
  const infoTypes = [{name: 'US_SOCIAL_SECURITY_NUMBER'}];

  // Construct hotword rule.
  const hotwordRule = {
    hotwordRegex: {
      pattern: hotwordRegexPattern,
    },
    likelihoodAdjustment: {
      fixedLikelihood:
        DLP.protos.google.privacy.dlp.v2.Likelihood.VERY_UNLIKELY,
    },
    proximity: {
      windowBefore: 1,
    },
  };

  // Construct rule set for the inspect configuration.
  const inspectionRuleSet = {
    infoTypes: infoTypes,
    rules: [
      {
        hotwordRule: hotwordRule,
      },
    ],
  };

  // Construct the configuration for the Inspect request.
  const config = {
    infoTypes: infoTypes,
    ruleSet: [inspectionRuleSet],
    minLikelihood: DLP.protos.google.privacy.dlp.v2.Likelihood.POSSIBLE,
    includeQuote: true,
  };

  // Construct the Inspect request to be sent by the client.
  const request = {
    parent: `projects/${projectId}/locations/global`,
    item: contentItem,
    inspectConfig: config,
  };

  // Use the client to send the API request.
  const [response] = await dlp.inspectContent(request);

  // Print Findings.
  const findings = response.result.findings;
  if (findings.length > 0) {
    console.log(`Findings: ${findings.length}\n`);
    findings.forEach(finding => {
      console.log(`InfoType: ${finding.infoType.name}`);
      console.log(`\tQuote: ${finding.quote}`);
      console.log(`\tLikelihood: ${finding.likelihood} \n`);
    });
  } else {
    console.log('No findings.');
  }
}
inspectWithCustomHotwords();

PHP

Para saber como instalar e usar a biblioteca cliente para a Proteção de dados confidenciais, consulte o artigo Bibliotecas cliente da Proteção de dados confidenciais.

use Google\Cloud\Dlp\V2\Client\DlpServiceClient;
use Google\Cloud\Dlp\V2\ContentItem;
use Google\Cloud\Dlp\V2\CustomInfoType\DetectionRule\HotwordRule;
use Google\Cloud\Dlp\V2\CustomInfoType\DetectionRule\LikelihoodAdjustment;
use Google\Cloud\Dlp\V2\CustomInfoType\DetectionRule\Proximity;
use Google\Cloud\Dlp\V2\CustomInfoType\Regex;
use Google\Cloud\Dlp\V2\FieldId;
use Google\Cloud\Dlp\V2\InfoType;
use Google\Cloud\Dlp\V2\InspectConfig;
use Google\Cloud\Dlp\V2\InspectContentRequest;
use Google\Cloud\Dlp\V2\InspectionRule;
use Google\Cloud\Dlp\V2\InspectionRuleSet;
use Google\Cloud\Dlp\V2\Likelihood;
use Google\Cloud\Dlp\V2\Table;
use Google\Cloud\Dlp\V2\Table\Row;
use Google\Cloud\Dlp\V2\Value;

/**
 * Hotword example: Set the match likelihood of a table column.
 * This example demonstrates how you can set the match likelihood of an entire column of data.
 * This approach is helpful, for example, if you want to exclude a column of data from inspection
 * results.
 *
 * @param string $projectId         The Google Cloud project id to use as a parent resource.
 */
function inspect_column_values_w_custom_hotwords(string $projectId): void
{
    // Instantiate a client.
    $dlp = new DlpServiceClient();

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

    // Specify the table to be inspected.
    $tableToDeIdentify = (new Table())
        ->setHeaders([
            (new FieldId())
                ->setName('Fake Social Security Number'),
            (new FieldId())
                ->setName('Real Social Security Number'),
        ])
        ->setRows([
            (new Row())->setValues([
                (new Value())
                    ->setStringValue('111-11-1111'),
                (new Value())
                    ->setStringValue('222-22-2222')
            ])
        ]);

    $item = (new ContentItem())
        ->setTable($tableToDeIdentify);

    // Specify the regex pattern the inspection will look for.
    $hotwordRegexPattern = 'Fake Social Security Number';

    // Specify hotword likelihood adjustment.
    $likelihoodAdjustment = (new LikelihoodAdjustment())
        ->setFixedLikelihood(Likelihood::VERY_UNLIKELY);

    // Specify a window around a finding to apply a detection rule.
    $proximity = (new Proximity())
        ->setWindowBefore(1);

    // Construct the hotword rule.
    $hotwordRule = (new HotwordRule())
        ->setHotwordRegex((new Regex())
            ->setPattern($hotwordRegexPattern))
        ->setLikelihoodAdjustment($likelihoodAdjustment)
        ->setProximity($proximity);

    // Construct rule set for the inspect config.
    $infotype = (new InfoType())
        ->setName('US_SOCIAL_SECURITY_NUMBER');
    $inspectionRuleSet = (new InspectionRuleSet())
        ->setInfoTypes([$infotype])
        ->setRules([
            (new InspectionRule())
                ->setHotwordRule($hotwordRule)
        ]);

    // Construct the configuration for the Inspect request.
    $inspectConfig = (new InspectConfig())
        ->setInfoTypes([$infotype])
        ->setIncludeQuote(true)
        ->setRuleSet([$inspectionRuleSet])
        ->setMinLikelihood(Likelihood::POSSIBLE);

    // Run request.
    $inspectContentRequest = (new InspectContentRequest())
        ->setParent($parent)
        ->setInspectConfig($inspectConfig)
        ->setItem($item);
    $response = $dlp->inspectContent($inspectContentRequest);

    // Print the results.
    $findings = $response->getResult()->getFindings();
    if (count($findings) == 0) {
        printf('No findings.' . PHP_EOL);
    } else {
        printf('Findings:' . PHP_EOL);
        foreach ($findings as $finding) {
            printf('  Quote: %s' . PHP_EOL, $finding->getQuote());
            printf('  Info type: %s' . PHP_EOL, $finding->getInfoType()->getName());
            printf('  Likelihood: %s' . PHP_EOL, Likelihood::name($finding->getLikelihood()));
        }
    }
}

Python

Para saber como instalar e usar a biblioteca cliente para a Proteção de dados confidenciais, consulte o artigo Bibliotecas cliente da Proteção de dados confidenciais.

from typing import List

import google.cloud.dlp


def inspect_column_values_w_custom_hotwords(
    project: str,
    table_header: List[str],
    table_rows: List[List[str]],
    info_types: List[str],
    custom_hotword: str,
) -> None:
    """Uses the Data Loss Prevention API to inspect table data using built-in
    infoType detectors, excluding columns that match a custom hot-word.
    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 values.
        info_types: The infoType for which hot-word rule is applied.
        custom_hotword: The custom regular expression used for likelihood boosting.
    """

    # 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 to be inspected.
    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 a rule set with caller provided hot-word, with a likelihood
    # boost to VERY_UNLIKELY when the hot-word are present
    hotword_rule = {
        "hotword_regex": {"pattern": custom_hotword},
        "likelihood_adjustment": {
            "fixed_likelihood": google.cloud.dlp_v2.Likelihood.VERY_UNLIKELY
        },
        "proximity": {"window_before": 1},
    }

    rule_set = [
        {
            "info_types": info_types,
            "rules": [{"hotword_rule": hotword_rule}],
        }
    ]

    # Construct the configuration dictionary, which defines the entire inspect content task.
    inspect_config = {
        "info_types": info_types,
        "rule_set": rule_set,
        "min_likelihood": google.cloud.dlp_v2.Likelihood.POSSIBLE,
        "include_quote": True,
    }

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

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

    # Print out the results.
    if response.result.findings:
        for finding in response.result.findings:
            try:
                if finding.quote:
                    print(f"Quote: {finding.quote}")
            except AttributeError:
                pass
            print(f"Info type: {finding.info_type.name}")
            print(f"Likelihood: {finding.likelihood}")
    else:
        print("No findings.")

REST

Entrada JSON:

{
  "item": {
    "table": {
      "headers": [
        {
          "name": "Fake Social Security Number"
        },
        {
          "name": "Real Social Security Number"
        }
      ],
      "rows": [
        {
          "values": [
            {
              "stringValue": "111-11-1111"
            },
            {
              "stringValue": "222-22-2222"
            }
          ]
        }
      ]
    }
  },
  "inspectConfig": {
    "infoTypes": [
      {
        "name": "US_SOCIAL_SECURITY_NUMBER"
      }
    ],
    "includeQuote": true,
    "ruleSet": [
      {
        "infoTypes": [
          {
            "name": "US_SOCIAL_SECURITY_NUMBER"
          }
        ],
        "rules": [
          {
            "hotwordRule": {
              "hotwordRegex": {
                "pattern": "(Fake Social Security Number)"
              },
              "likelihoodAdjustment": {
                "fixedLikelihood": "VERY_UNLIKELY"
              },
              "proximity": {
                "windowBefore": 1
              }
            }
          }
        ]
      }
    ],
    "minLikelihood": "POSSIBLE"
  }
}

Saída JSON:

{
  "result": {
    "findings": [
      {
        "quote": "222-22-2222",
        "infoType": {
          "name": "US_SOCIAL_SECURITY_NUMBER"
        },
        "likelihood": "VERY_LIKELY",
        "location": {
          "byteRange": {
            "end": "11"
          },
          "codepointRange": {
            "end": "11"
          },
          "contentLocations": [
            {
              "recordLocation": {
                "fieldId": {
                  "name": "Real Social Security Number"
                },
                "tableLocation": {}
              }
            }
          ]
        },
        "createTime": "TIMESTAMP",
        "findingId": "TIMESTAMP"
      }
    ]
  }
}

O valor 111-11-1111, que se encontra na coluna Fake Social Security Number, correspondeu à regra de palavra-chave, pelo que a proteção de dados confidenciais lhe atribuiu o nível de probabilidade VERY_UNLIKELY . Este nível é inferior à probabilidade mínima definida na configuração da inspeção (POSSIBLE), pelo que esta descoberta é excluída do resultado da inspeção.

Pode experimentar este exemplo removendo o conjunto de regras. Repare que a proteção de dados confidenciais inclui 111-11-1111 nos resultados.

Personalizar a probabilidade de correspondência Mantenha tudo organizado com as coleções Salve e categorize o conteúdo com base nas suas preferências.

Anatomia de uma regra de hotword

Exemplo de palavra de ativação: fazer corresponder números de registos médicos

C#

Go

Java

Node.js

PHP

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REST

Exemplo de palavra-chave: defina a probabilidade de correspondência de uma coluna da tabela

C#

Go

Java

Node.js

PHP

Python

REST

Personalizar a probabilidade de correspondência