Cloud Data Loss Prevention (Cloud DLP) 现已成为敏感数据保护功能的一部分。API 名称保持不变：Cloud Data Loss Prevention API (DLP API)。如需了解构成敏感数据保护的服务，请参阅敏感数据保护概览。

此页面由 Cloud Translation API 翻译。

自定义匹配可能性

利用热词规则，您可以通过强大的上下文规则进一步扩展内置和自定义 infoType 检测器。热词规则会指示 Sensitive Data Protection 根据发现结果附近是否出现热词来调整发现结果的可能性。热词规则是一种在规则集中指定的检查规则。每个规则都会应用于一组内置或自定义 infoType。

热词规则详解

infoType 检测器可以具有零项或多项热词规则。在检查配置中，您可以在 rules 数组内定义每个 HotwordRule 对象，如下所示：

"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"
      },
    }
  },
  ...
]

替换以下内容：

REGEX_PATTERN：定义热词条件的正则表达式（Regex 对象）。
NUM_CHARS_TO_CONSIDER_AFTER_FINDING：发现结果后面的字符范围。Sensitive Data Protection 会分析此范围，以确定发现结果附近是否存在热词。
NUM_CHARS_TO_CONSIDER_BEFORE_FINDING：发现结果前面的字符范围。Sensitive Data Protection 会分析此范围，以确定发现结果附近是否存在热词。
LIKELIHOOD_VALUE：要将发现结果设为的固定 Likelihood 级别。
LIKELIHOOD_ADJUSTMENT：一个数字，表示 Sensitive Data Protection 必须提高或降低发现结果可能性的程度。正整数提高可能性级别，负整数降低可能性级别。例如，如果在未应用检测规则时发现结果是 POSSIBLE，且 relativeLikelihood 为 1，则发现结果将升级为 LIKELY。如果 relativeLikelihood 为 -1，则发现结果将降级为 UNLIKELY。可能性永远不会低于 VERY_UNLIKELY 或超过 VERY_LIKELY。在这些情况下，可能性级别保持不变。例如，如果基础可能性为 VERY_LIKELY 并且 relativeLikelihood 为 1，则最终可能性仍然为 VERY_LIKELY。

热词示例：匹配医疗记录编号

假设您想要检测一个自定义 infoType，例如格式为“###-#-#####”的医疗记录编号 (MRN)。同时，您希望敏感数据保护功能提高跟在热词“MRN”之后的每个发现结果的匹配可能性。

示例值：

123-4-56789 将匹配为 POSSIBLE。
MRN 123-4-56789 将匹配为 VERY_LIKELY。

以下 JSON 示例和代码段展示了如何配置热词规则。此示例使用自定义正则表达式检测器。

在此示例中，请注意以下事项：

请求定义了 C_MRN 自定义 infoType，这是与正则表达式 [0-9]{3}-[0-9]{1}-[0-9]{5} 匹配的任何字符串的检测器。
正则表达式 (?i)(mrn|medical)(?-i) 定义热词。敏感数据保护功能会在 proximity 字段定义的字符范围内搜索此热词。
对于在设置的 proximity 内包含热词的每个 C_MRN 发现结果，敏感数据保护会将可能性级别设置为 VERY_LIKELY。

C#

如需了解如何安装和使用敏感数据保护客户端库，请参阅敏感数据保护客户端库。

如需向 Sensitive Data Protection 进行身份验证，请设置应用默认凭据。如需了解详情，请参阅为本地开发环境设置身份验证。


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

如需了解如何安装和使用敏感数据保护客户端库，请参阅敏感数据保护客户端库。

如需向 Sensitive Data Protection 进行身份验证，请设置应用默认凭据。如需了解详情，请参阅为本地开发环境设置身份验证。

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

如需了解如何安装和使用敏感数据保护客户端库，请参阅敏感数据保护客户端库。

如需向 Sensitive Data Protection 进行身份验证，请设置应用默认凭据。如需了解详情，请参阅为本地开发环境设置身份验证。


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

如需了解如何安装和使用敏感数据保护客户端库，请参阅敏感数据保护客户端库。

如需向 Sensitive Data Protection 进行身份验证，请设置应用默认凭据。如需了解详情，请参阅为本地开发环境设置身份验证。

// 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

如需了解如何安装和使用敏感数据保护客户端库，请参阅敏感数据保护客户端库。

如需向 Sensitive Data Protection 进行身份验证，请设置应用默认凭据。如需了解详情，请参阅为本地开发环境设置身份验证。

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

如需了解如何安装和使用敏感数据保护客户端库，请参阅敏感数据保护客户端库。

如需向 Sensitive Data Protection 进行身份验证，请设置应用默认凭据。如需了解详情，请参阅为本地开发环境设置身份验证。

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

要详细了解如何将 DLP API 与 JSON 结合使用，请参阅 JSON 快速入门。

HTTP 方法和网址：

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

将 PROJECT_ID 替换为项目 ID。

JSON 输入：

{
  "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
              }
            }
          }
        ]
      }
    ]
  }
}

JSON 输出（简化版本）：

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

输出显示，敏感数据保护功能使用 C_MRN 自定义 infoType 检测器正确识别了医疗记录编号。此外，由于热词规则中的上下文匹配，敏感数据保护功能根据配置为第一个结果（在设置的 proximity 内包含 MRN）分配了可能性 VERY_LIKELY。第二个发现结果缺少上下文，因此 likelihood 为 POSSIBLE。

热词示例：设置表列的匹配可能性

此示例演示了如何设置整个数据列的匹配可能性。例如，如果您想要从检查结果中排除一列数据，此方法非常有用。

请参考下表：一列包含占位符社会保障号 (SSN)，另一列包含真实的社会保障号。

虚构的社会保障号	真实的社会保障号
111-11-1111	222-22-2222

为了最大限度地减少检查结果中的噪声，您可以排除 Fake Social Security Number 列中的任何发现结果。为此列分配较低的可能性级别。然后，配置请求，以便从结果中排除该可能性级别的匹配项。

在此示例中，请注意以下事项：

热词规则应用于 US_SOCIAL_SECURITY_NUMBER infoType。
热词正则表达式 (Fake Social Security Number) 包含具有占位符值的列名称。
windowBefore 属性设置为 1，表示热词位于列标题中，并且发现结果必须位于该列中。
对于此列中的每个 US_SOCIAL_SECURITY_NUMBER 发现结果，敏感数据保护将可能性级别设置为 VERY_UNLIKELY。
minLikelihood 属性设置为 POSSIBLE，这意味着可能性级别低于 POSSIBLE 的任何发现结果都会从检查结果中排除。

要详细了解如何将 DLP API 与 JSON 结合使用，请参阅 JSON 快速入门。

HTTP 方法和网址：

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

将 PROJECT_ID 替换为项目 ID。

C#

如需了解如何安装和使用敏感数据保护客户端库，请参阅敏感数据保护客户端库。

如需向 Sensitive Data Protection 进行身份验证，请设置应用默认凭据。如需了解详情，请参阅为本地开发环境设置身份验证。



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

如需了解如何安装和使用敏感数据保护客户端库，请参阅敏感数据保护客户端库。

如需向 Sensitive Data Protection 进行身份验证，请设置应用默认凭据。如需了解详情，请参阅为本地开发环境设置身份验证。


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

如需了解如何安装和使用敏感数据保护客户端库，请参阅敏感数据保护客户端库。

如需向 Sensitive Data Protection 进行身份验证，请设置应用默认凭据。如需了解详情，请参阅为本地开发环境设置身份验证。


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

如需了解如何安装和使用敏感数据保护客户端库，请参阅敏感数据保护客户端库。

如需向 Sensitive Data Protection 进行身份验证，请设置应用默认凭据。如需了解详情，请参阅为本地开发环境设置身份验证。

// 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

如需了解如何安装和使用敏感数据保护客户端库，请参阅敏感数据保护客户端库。

如需向 Sensitive Data Protection 进行身份验证，请设置应用默认凭据。如需了解详情，请参阅为本地开发环境设置身份验证。

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

如需了解如何安装和使用敏感数据保护客户端库，请参阅敏感数据保护客户端库。

如需向 Sensitive Data Protection 进行身份验证，请设置应用默认凭据。如需了解详情，请参阅为本地开发环境设置身份验证。

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

JSON 输入：

{
  "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"
  }
}

JSON 输出：

{
  "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"
      }
    ]
  }
}

Fake Social Security Number 列中的值 111-11-1111 匹配热词规则，因此敏感数据保护为其分配 VERY_UNLIKELY 可能性级别。此级别低于检查配置中设置的最低可能性级别 (POSSIBLE)，因此该发现结果从检查结果中排除。

您可以通过移除设置的规则来对此示例进行实验。请注意，敏感数据保护在结果中包含 111-11-1111。