Cloud Data Loss Prevention (Cloud DLP) ahora forma parte de la protección de datos sensibles. El nombre de la API sigue siendo el mismo: API de Cloud Data Loss Prevention (API de DLP). Para obtener información sobre los servicios que conforman la protección de datos sensibles, consulta la Descripción general de la protección de datos sensibles.

Personalizar probabilidad de coincidencia

Mediante las reglas de palabra clave, puedes extender aún más los detectores de Infotipo integrados y personalizados con reglas de contexto potentes. Una regla de palabra clave le indica a la Protección de datos sensibles que ajuste la probabilidad de un resultado, dependiendo de si una palabra clave se produce cerca de ese resultado. Una regla de palabra clave es un tipo de regla de inspección que se especifica en conjuntos de reglas. Cada regla se aplica a un conjunto de Infotipos integrados o personalizados.

Anatomía de una regla de palabra clave

Un detector de Infotipo puede tener cero o más reglas de palabra clave. En la configuración de inspección, debes definir cada objeto HotwordRule dentro del array rules de la siguiente manera:

"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"
      },
    }
  },
  ...
]

Reemplaza lo siguiente:

REGEX_PATTERN: Es una expresión regular (objeto Regex) que define lo que se califica como palabra clave.
NUM_CHARS_TO_CONSIDER_AFTER_FINDING: Un rango de caracteres después del resultado La protección de datos sensibles analiza este rango para determinar si una palabra clave aparece cerca del resultado.
NUM_CHARS_TO_CONSIDER_BEFORE_FINDING: Un rango de caracteres antes del resultado. La protección de datos sensibles analiza este rango para determinar si una palabra clave aparece cerca del resultado.
LIKELIHOOD_VALUE: un nivel Likelihood fijo para configurar el resultado.
LIKELIHOOD_ADJUSTMENT: Es un número que indica cuánto debe aumentar o disminuir la probabilidad de un resultado con la protección de datos sensibles. Un número entero positivo aumenta el nivel de probabilidad y un número entero negativo lo disminuye. Por ejemplo, si un resultado sería POSSIBLE sin la regla de detección y relativeLikelihood es 1, el resultado se actualiza a LIKELY. Si relativeLikelihood es -1, el resultado se cambia a UNLIKELY. La probabilidad nunca puede disminuir por debajo de VERY_UNLIKELY ni superar VERY_LIKELY. En estos casos, el nivel de probabilidad permanecen igual. Por ejemplo, si la probabilidad base es VERY_LIKELY y la relativeLikelihood es 1, la probabilidad final sigue siendo VERY_LIKELY.

Ejemplo de palabra clave: coincidencia de los números de historias clínicas

Supongamos que deseas detectar un Infotipo personalizado, como un número de historia clínica (MRN) en el formato "###-#-#####". Además, quieres que la protección de datos sensibles aumente la probabilidad de coincidencia de cada resultado que siga a la palabra clave "MRN".

Valores de ejemplo:

123-4-56789 coincidiría con POSSIBLE.
MRN 123-4-56789 coincidiría con VERY_LIKELY.

En los siguientes fragmentos de código y ejemplo de JSON, se muestra cómo configurar la regla de palabra clave. En este ejemplo, se usa un detector de expresiones regulares personalizado.

En este ejemplo, ten en cuenta lo siguiente:

La solicitud define el Infotipo personalizado C_MRN, que es un detector de cualquier string que coincida con la expresión regular [0-9]{3}-[0-9]{1}-[0-9]{5}.
La expresión regular (?i)(mrn|medical)(?-i) define la palabra clave. La protección de datos sensibles busca esta palabra clave dentro del rango de caracteres definidos en el campo proximity.
Para cada resultado de C_MRN que tenga una palabra clave dentro del conjunto proximity, la protección de datos sensibles establece el nivel de probabilidad en VERY_LIKELY.

C#

Para obtener información sobre cómo instalar y usar la biblioteca cliente de la protección de datos sensibles, consulta Bibliotecas cliente de la protección de datos sensibles.

Para autenticarte en la protección de datos sensibles, configura las credenciales predeterminadas de la aplicación. Si deseas obtener más información, consulta Configura la autenticación para un entorno de desarrollo local.

Ver en GitHub Comentarios


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 obtener información sobre cómo instalar y usar la biblioteca cliente de la protección de datos sensibles, consulta Bibliotecas cliente de la protección de datos sensibles.

Ver en GitHub Comentarios

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 obtener información sobre cómo instalar y usar la biblioteca cliente de la protección de datos sensibles, consulta Bibliotecas cliente de la protección de datos sensibles.

Ver en GitHub Comentarios


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 obtener información sobre cómo instalar y usar la biblioteca cliente de la protección de datos sensibles, consulta Bibliotecas cliente de la protección de datos sensibles.

Ver en GitHub Comentarios

// 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 obtener información sobre cómo instalar y usar la biblioteca cliente de la protección de datos sensibles, consulta Bibliotecas cliente de la protección de datos sensibles.

Ver en GitHub Comentarios

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 obtener información sobre cómo instalar y usar la biblioteca cliente de la protección de datos sensibles, consulta Bibliotecas cliente de la protección de datos sensibles.

Ver en GitHub Comentarios

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

Consulta la guía de inicio rápido de JSON para obtener más información sobre cómo usar la API de DLP con JSON.

Método HTTP y URL:

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

Reemplaza PROJECT_ID por el ID del proyecto.

Entrada de 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
              }
            }
          }
        ]
      }
    ]
  }
}

Resultado de JSON (abreviado):

{
  "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": { ... }
        }
      }
    ]
  }
}

El resultado muestra que la protección de datos sensibles identificó de forma correcta el número de historia clínica con el detector de Infotipo personalizado C_MRN. Además, debido a la coincidencia de contexto en la regla de palabra clave, la protección de datos sensibles asignó al primer resultado (que tenía un MRN dentro del conjunto proximity) una probabilidad de VERY_LIKELY, según la configuración. El segundo resultado no tenía el contexto, por lo que likelihood se quedó en POSSIBLE.

Ejemplo de palabra clave: Configura la probabilidad de coincidencia de una columna de tabla

En este ejemplo, se muestra cómo puedes configurar la probabilidad de coincidencia de una columna de datos completa. Este enfoque es útil, por ejemplo, si deseas excluir una columna de datos de los resultados de la inspección.

Considera la siguiente tabla. Una columna contiene números de seguridad social (NSS) con marcador de posición, y otra contiene NSS reales.

Número de seguridad social falso	Número de seguridad social real
111-11-1111	222-22-2222

Para minimizar el ruido en los resultados de la inspección, puedes excluir cualquier resultado de la columna Fake Social Security Number. Asigna un nivel de probabilidad bajo a esta columna. Luego, configura la solicitud de modo que coincida con ese nivel de probabilidad y se excluya de los resultados.

En este ejemplo, ten en cuenta lo siguiente:

La regla de palabra clave se aplica al Infotipo US_SOCIAL_SECURITY_NUMBER.
La expresión regular (Fake Social Security Number) de la palabra clave contiene el nombre de la columna que tiene los valores de marcador de posición.
La propiedad windowBefore se establece en 1, lo que significa que la palabra clave está en un encabezado de columna, y los resultados deben estar en la columna.
Para cada resultado de US_SOCIAL_SECURITY_NUMBER de esta columna, la protección de datos sensibles establece el nivel de probabilidad en VERY_UNLIKELY.
La propiedad minLikelihood se establece en POSSIBLE, lo que significa que cualquier resultado que tenga un nivel de probabilidad inferior a POSSIBLE se excluye de los resultados de la inspección.

Consulta la guía de inicio rápido de JSON para obtener más información sobre cómo usar la API de DLP con JSON.

Método HTTP y URL:

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

Reemplaza PROJECT_ID por el ID del proyecto.

C#

Para obtener información sobre cómo instalar y usar la biblioteca cliente de la protección de datos sensibles, consulta Bibliotecas cliente de la protección de datos sensibles.

Ver en GitHub Comentarios



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 obtener información sobre cómo instalar y usar la biblioteca cliente de la protección de datos sensibles, consulta Bibliotecas cliente de la protección de datos sensibles.

Ver en GitHub Comentarios


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 obtener información sobre cómo instalar y usar la biblioteca cliente de la protección de datos sensibles, consulta Bibliotecas cliente de la protección de datos sensibles.

Ver en GitHub Comentarios


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 obtener información sobre cómo instalar y usar la biblioteca cliente de la protección de datos sensibles, consulta Bibliotecas cliente de la protección de datos sensibles.

Ver en GitHub Comentarios

// 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 obtener información sobre cómo instalar y usar la biblioteca cliente de la protección de datos sensibles, consulta Bibliotecas cliente de la protección de datos sensibles.

Ver en GitHub Comentarios

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 obtener información sobre cómo instalar y usar la biblioteca cliente de la protección de datos sensibles, consulta Bibliotecas cliente de la protección de datos sensibles.

Ver en GitHub Comentarios

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 de 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"
  }
}

Salida de 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"
      }
    ]
  }
}

El valor 111-11-1111, que se encuentra en la columna Fake Social Security Number, coincidió con la regla de palabra clave, por lo que la protección de datos sensibles le asignó el nivel de probabilidad VERY_UNLIKELY . Este nivel es más bajo que la probabilidad mínima establecida en la configuración de inspección (POSSIBLE), por lo que este resultado se excluye del resultado de la inspección.

Puedes experimentar con este ejemplo si quitas el conjunto de reglas. Ten en cuenta que la protección de datos sensibles incluye el número 111-11-1111 en los resultados.