创建自定义正则表达式检测器

借助正则表达式 (regex) 自定义 infoType 检测器，您可以创建自己的检测器，使敏感数据保护能够基于正则表达式模式检测匹配项。例如，假设您的医疗记录编号采用 ###-#-##### 形式。您可以定义一个正则表达式模式，如下所示：

[0-9]{3}-[0-9]{1}-[0-9]{5}

然后，敏感数据保护会匹配如下内容：

012-4-56789

正则表达式自定义 infoType 检测器详解

如 API 概览中所述，如需创建自定义正则表达式 infoType 检测器，需要定义一个包含以下内容的 CustomInfoType 对象：

• 您希望在 InfoType 对象中为自定义 infoType 检测器指定的名称。
• （可选）Likelihood 值。如果省略此字段，正则表达式匹配项将返回默认可能性 VERY_LIKELY。如果您发现正则表达式自定义 infoType 检测器返回太多误报，请尝试减小基本可能性，并通过检测规则和上下文信息来提高可能性。如需了解详情，请参阅对发现结果的可能性进行自定义。
• （可选）DetectionRule 或热词规则。这些规则可在指定热词的一定接近范围内调整结果的可能性。详细了解对发现结果的可能性进行自定义中的热词规则。

• （可选）SensitivityScore 值。如果省略此字段，则正则表达式的匹配项将返回默认敏感度级别 HIGH。

  敏感度得分用于数据分析文件。剖析数据时，敏感数据保护使用 infoType 的敏感度分数计算敏感度级别。

• 一个 Regex 对象，由定义正则表达式的单个模式构成。

作为一个 JSON 对象，包含所有可选组件的正则表达式自定义 infoType 检测器如下所示：

{
  "customInfoTypes":[
    {
      "infoType":{
        "name":"CUSTOM_INFOTYPE_NAME"
      },
      "likelihood":"LIKELIHOOD_LEVEL",
      "detectionRules":[
        {
          "hotwordRule":{
            HOTWORD_RULE
          }
        },
      "sensitivityScore":{
          "score": "SENSITIVITY_SCORE"
        },
      ],
      "regex":{
        "pattern":"REGULAR_EXPRESSION_PATTERN"
      }
    }
  ],
  ...
}

注意 ：您还可以通过引用 CustomInfoType 对象的 storedType 字段中现有的 StoredInfoType（而不是定义 regex 字段）来创建自定义正则表达式检测器。不过，此方法要求您先创建一个类型为 Regex 的 StoredInfoType。在大多数情况下，直接在 CustomInfoType 对象的 regex 字段中定义 Regex 对象会更简单。

正则表达式示例：匹配医疗记录编号

以下多种语言的 JSON 代码段和代码展示了一个正则表达式自定义 infoType 检测器，该检测器指示敏感数据保护匹配输入文本“Patient's MRN 444-5-22222”中的医疗记录编号 (MRN)，并为每个匹配项分配可能性 POSSIBLE。

C#

如需了解如何安装和使用用于敏感数据保护的客户端库，请参阅敏感数据保护客户端库。

如需向敏感数据保护服务进行身份验证，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。

在 GitHub 上查看 反馈

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

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

        // Construct content item by setting the text.
        var contentItem = new ContentItem { Value = text };

        // Construct the custom regex detector.
        var customInfoType = new CustomInfoType
        {
            InfoType = infoType ?? new InfoType { Name = "C_MRN" },
            Regex = new CustomInfoType.Types.Regex { Pattern = customRegex }
        };

        // Construct Inspect Config.
        var inspectConfig = new InspectConfig
        {
            CustomInfoTypes = { customInfoType },
            IncludeQuote = true,
            MinLikelihood = Likelihood.Possible
        };

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

        Console.WriteLine($"Findings: {resultFindings.Count}");
        foreach (var f in resultFindings)
        {
            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用于敏感数据保护的客户端库，请参阅敏感数据保护客户端库。

如需向敏感数据保护服务进行身份验证，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。

在 GitHub 上查看 反馈

import (
	"context"
	"fmt"
	"io"

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

// inspectWithCustomRegex inspect a data with custom regex pattern
func inspectWithCustomRegex(w io.Writer, projectID, textToInspect, customRegexPattern, infoTypeName string) error {
	//projectID := "my-project-id"
	//textToInspect := "Patients MRN 444-5-22222"
	//customRegexPattern := "[1-9]{3}-[1-9]{1}-[1-9]{5}"
	//infoTypeName := "C_MRN"

	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: infoTypeName,
		},
		// Specify the regex pattern the inspection will look for.
		Type: &dlppb.CustomInfoType_Regex_{
			Regex: &dlppb.CustomInfoType_Regex{
				Pattern: customRegexPattern,
			},
		},
		Likelihood: dlppb.Likelihood_POSSIBLE,
	}

	// Construct the Inspect request to be sent by the client.
	req := &dlppb.InspectContentRequest{
		Parent: fmt.Sprintf("projects/%s/locations/global", projectID),
		Item:   contentItem,
		// Construct the configuration for the Inspect request.
		InspectConfig: &dlppb.InspectConfig{
			CustomInfoTypes: []*dlppb.CustomInfoType{
				customInfoType,
			},
			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用于敏感数据保护的客户端库，请参阅敏感数据保护客户端库。

如需向敏感数据保护服务进行身份验证，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。

在 GitHub 上查看 反馈

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.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.Likelihood;
import com.google.privacy.dlp.v2.LocationName;
import com.google.protobuf.ByteString;
import java.io.IOException;

public class InspectWithCustomRegex {

  public static void main(String[] args) throws Exception {
    // TODO(developer): Replace these variables before running the sample.
    String projectId = "your-project-id";
    String textToInspect = "Patients MRN 444-5-22222";
    String customRegexPattern = "[1-9]{3}-[1-9]{1}-[1-9]{5}";
    inspectWithCustomRegex(projectId, textToInspect, customRegexPattern);
  }

  // Inspects a BigQuery Table
  public static void inspectWithCustomRegex(
      String projectId, String textToInspect, String customRegexPattern) 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();

      // Construct the configuration for the Inspect request.
      InspectConfig config =
          InspectConfig.newBuilder()
              .addCustomInfoTypes(customInfoType)
              .setIncludeQuote(true)
              .setMinLikelihood(Likelihood.POSSIBLE)
              .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用于敏感数据保护的客户端库，请参阅敏感数据保护客户端库。

如需向敏感数据保护服务进行身份验证，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。

在 GitHub 上查看 反馈

// 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 regex pattern to match for
// const customRegex = '[1-9]{3}-[1-9]{1}-[1-9]{5}';

async function inspectWithCustomRegex() {
  // 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 the custom regex detector.
  const customInfoTypes = [
    {
      infoType: {
        name: 'C_MRN',
      },
      likelihood: DLP.protos.google.privacy.dlp.v2.Likelihood.POSSIBLE,
      regex: {
        pattern: customRegex,
      },
    },
  ];

  // Construct request
  const request = {
    parent: `projects/${projectId}/locations/global`,
    inspectConfig: {
      customInfoTypes: customInfoTypes,
      includeQuote: true,
    },
    item: item,
  };

  // Run request
  const [response] = await dlp.inspectContent(request);
  const findings = response.result.findings;
  if (findings.length > 0) {
    console.log('Findings: \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.');
  }
}
inspectWithCustomRegex();

PHP

如需了解如何安装和使用用于敏感数据保护的客户端库，请参阅敏感数据保护客户端库。

如需向敏感数据保护服务进行身份验证，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。

在 GitHub 上查看 反馈

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\Regex;
use Google\Cloud\Dlp\V2\InfoType;
use Google\Cloud\Dlp\V2\InspectConfig;
use Google\Cloud\Dlp\V2\InspectContentRequest;
use Google\Cloud\Dlp\V2\Likelihood;

/**
 * Inspect data with a custom regex
 * Regex example: Matching medical record numbers. The following sample uses a regular expression custom infoType detector that instructs Cloud DLP to match a medical record number (MRN) in the input text "Patient's MRN 444-5-22222," and then assigns each match a likelihood of POSSIBLE.
 *
 * @param string $projectId         The Google Cloud project id to use as a parent resource.
 * @param string $textToInspect     The string to inspect.
 */
function inspect_custom_regex(
    // TODO(developer): Replace sample parameters before running the code.
    string $projectId,
    string $textToInspect = 'Patients MRN 444-5-22222'
): 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}';

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

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

    // 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用于敏感数据保护的客户端库，请参阅敏感数据保护客户端库。

如需向敏感数据保护服务进行身份验证，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。

在 GitHub 上查看 反馈

import google.cloud.dlp

def inspect_data_with_custom_regex_detector(
    project: str,
    content_string: str,
) -> None:
    """Uses the Data Loss Prevention API to analyze string with medical record
       number custom regex detector

    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 the configuration dictionary with the custom regex info type.
    inspect_config = {
        "custom_info_types": custom_info_types,
        "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。

JSON 输入：

POST https://dlp.googleapis.com/v2/projects/[PROJECT_ID]/content:inspect?key={YOUR_API_KEY}

{
  "item":{
    "value":"Patients MRN 444-5-22222"
  },
  "inspectConfig":{
    "customInfoTypes":[
      {
        "infoType":{
          "name":"C_MRN"
        },
        "regex":{
          "pattern":"[1-9]{3}-[1-9]{1}-[1-9]{5}"
        },
        "likelihood":"POSSIBLE"
      }
    ]
  }
}

JSON 输出：

{
  "result":{
    "findings":[
      {
        "infoType":{
          "name":"C_MRN"
        },
        "likelihood":"POSSIBLE",
        "location":{
          "byteRange":{
            "start":"13",
            "end":"24"
          },
          "codepointRange":{
            "start":"13",
            "end":"24"
          }
        },
        "createTime":"2018-11-30T01:29:37.799Z"
      }
    ]
  }
}

输出显示，借助我们命名为 C_MRN 的自定义 infoType 检测器及其自定义正则表达式，敏感数据保护正确识别了医疗记录编号并按照指示为其分配了确定性 POSSIBLE。

基于此示例构建自定义匹配可能性，使其包含上下文字词。