对敏感数据进行去标识化

敏感数据保护功能可对文本内容（包括表等容器结构中存储的文本）中的敏感数据进行去标识化。去标识化是从数据中移除标识信息的过程。该 API 会检测敏感数据（例如个人身份信息 (PII)），然后通过去标识化转换进行遮盖、删除或以其它方式模糊数据。例如，去标识化技术可能包括以下任何一种：

• 使用星号 (*) 或井号 (＃) 等符号部分或完全替换字符，从而遮盖敏感数据。
• 使用令牌（即代理）字符串替换敏感数据的每个实例。
• 使用随机生成或预先确定的密钥加密并替换敏感数据。

您可使用 JSON 来通过 HTTPS 向 API 提供信息，也可采用 敏感数据保护客户端库通过 CLI 和多种编程语言提供信息。如需设置 CLI，请参阅快速入门。如需详细了解如何以 JSON 格式提交信息，请参阅 JSON 快速入门。

API 概览

如需对敏感数据进行去标识化，请使用 Sensitive Data Protection 的 content.deidentify 方法。

去标识化 API 调用分为 3 个部分：

• 需要检查的数据：API 要检查的字符串或表结构（ContentItem 对象）。

• 需要在数据中检查的内容：检测配置信息 (InspectConfig)，例如要查找的数据类型（或 infoType）、是否过滤超过特定可能性阈值的结果，以及返回的结果是否不得超过一定数量。

  在 InspectConfig 对象中，请务必添加要扫描的 infoType。否则，敏感数据保护功能会扫描一组默认的 infoType (ALL_BASIC)，其中有些 infoType 您可能不需要。扫描不需要的 infoType 可能会不必要地增加请求的延迟时间。

  您的请求中必须包含 InspectConfig 对象，但有一个例外情况。如需了解详情，请参阅本页上的记录转换。

• 检查结果的处置方式：配置信息 (DeidentifyConfig)，用于定义如何对敏感数据进行去标识化。此参数将在下一部分详细介绍。

API 会按相同格式返回您提供的相同内容，但会将根据您的标准识别为包含敏感信息的所有文本进行去标识化。

指定检测标准

信息类型（或“infoType”）检测器是敏感数据保护功能查找敏感数据所用的机制。

敏感数据保护包括多种 infoType 检测器，下方汇总了所有这些检测器：

• 内置 infoType 检测器内置于敏感数据保护中。其中包括适用于某个国家/区域特有的敏感数据类型的检测器以及适用于全球通用数据类型的检测器。
• 自定义 infoType 检测器 - 您自行创建的检测器。自定义 infoType 检测器有三种：
  • 常规自定义字典检测器 - 敏感数据保护功能匹配的简单字词列表。当您拥有一个包含多达数万个字词或短语的列表时，请使用常规自定义字典检测器。如果您预计字词列表不会发生显著变化，也建议首选常规自定义字典检测器。
  • 存储的自定义字典检测器 - 由敏感数据保护功能使用 Cloud Storage 或 BigQuery 中存储的大量字词或短语生成。当您拥有一个包含高达数千万个字词或短语的庞大列表时，请使用存储的自定义字典检测器。
  • 正则表达式 (regex) 检测器 - 使敏感数据保护功能能够基于正则表达式模式检测匹配项。

此外，敏感数据保护还包含检查规则的概念，因此您可使用以下规则微调扫描结果：

• 排除规则 - 让您可以通过向内置或自定义 infoType 检测器添加规则来减少返回的结果数量。
• 热词规则 - 让您可以通过向内置或自定义 infoType 检测器添加规则来增加返回的结果数量或更改其可能性值。

去标识化转换

设置去标识化配置 (DeidentifyConfig) 时，必须指定一个或多个转换。存在下面两类转换：

• InfoTypeTransformations：此类转换仅应用于已提交的文本中被识别为特定 infoType 的值。
• RecordTransformations：此类转换仅应用于已提交的列表文本数据中被识别为特定 infoType 的值，或者整个表格数据列中的值。

InfoType 转换

您可以为每个请求指定一个或多个 infoType 转换。在每个 InfoTypeTransformation 对象中，都要指定以下两项：

• 应该对其应用转换的一个或多个 infoType（infoTypes[] 数组对象）。
• 初始转换（PrimitiveTransformation 对象）。

请注意，您可根据需要指定 infoType，但如果未在 InspectConfig 参数中指定至少一个 infoType，系统就会将转换应用到未提供转换的所有内置 infoType。不建议此操作，因为这可能导致性能下降且费用增加。

初始转换

无论是仅应用于部分 infoType 还是应用于整个文本字符串，都必须指定至少一个要应用到输入项的初始转换。以下部分介绍了可供您使用的转换方法示例。如需查看 Sensitive Data Protection 提供的所有转换方法的列表，请参阅转换参考文档。

replaceConfig

如果将 replaceConfig 设置为 ReplaceValueConfig 对象，会将匹配的输入值替换为您指定的值。

例如，假设您已为所有 EMAIL_ADDRESS infoType 将 replaceConfig 设置为“[email-address]”，且已将下列字符串发送到敏感数据保护：

My name is Alicia Abernathy, and my email address is [e-mail].

返回的字符串如下：

My name is Alicia Abernathy, and my email address is [email-address].

多种语言的以下 JSON 示例和代码演示了如何构建 API 请求以及 DLP API 会返回哪些内容：

重要提示： 此页面上的代码要求您首先设置 Sensitive Data Protection 客户端。如需详细了解如何安装和创建敏感数据保护客户端，请参阅 敏感数据保护客户端库。（无需客户端库即可将 JSON 发送到敏感数据保护 REST 端点。）

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 deidentify_with_replace(
    project: str,
    input_str: str,
    info_types: List[str],
    replacement_str: str = "REPLACEMENT_STR",
) -> None:
    """Uses the Data Loss Prevention API to deidentify sensitive data in a
    string by replacing matched input values with a value you specify.
    Args:
        project: The Google Cloud project id to use as a parent resource.
        input_str: The string to deidentify (will be treated as text).
        info_types: A list of strings representing info types to look for.
        replacement_str: The string to replace all values that match given
            info types.
    Returns:
        None; the response from the API is printed to the terminal.
    """

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

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

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

    # Construct deidentify configuration dictionary
    deidentify_config = {
        "info_type_transformations": {
            "transformations": [
                {
                    "primitive_transformation": {
                        "replace_config": {
                            "new_value": {"string_value": replacement_str}
                        }
                    }
                }
            ]
        }
    }

    # Construct item
    item = {"value": input_str}

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

    # Print out the results.
    print(response.item.value)

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.DeidentifyConfig;
import com.google.privacy.dlp.v2.DeidentifyContentRequest;
import com.google.privacy.dlp.v2.DeidentifyContentResponse;
import com.google.privacy.dlp.v2.InfoType;
import com.google.privacy.dlp.v2.InfoTypeTransformations;
import com.google.privacy.dlp.v2.InfoTypeTransformations.InfoTypeTransformation;
import com.google.privacy.dlp.v2.InspectConfig;
import com.google.privacy.dlp.v2.LocationName;
import com.google.privacy.dlp.v2.PrimitiveTransformation;
import com.google.privacy.dlp.v2.ReplaceValueConfig;
import com.google.privacy.dlp.v2.Value;

public class DeIdentifyWithReplacement {

  public static void main(String[] args) throws Exception {
    // TODO(developer): Replace these variables before running the sample.
    String projectId = "your-project-id";
    String textToInspect =
        "My name is Alicia Abernathy, and my email address is [e-mail].";
    deIdentifyWithReplacement(projectId, textToInspect);
  }

  // Inspects the provided text.
  public static void deIdentifyWithReplacement(String projectId, String textToRedact) {
    // 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 content to be inspected.
      ContentItem item = ContentItem.newBuilder().setValue(textToRedact).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
      InfoType infoType = InfoType.newBuilder().setName("EMAIL_ADDRESS").build();
      InspectConfig inspectConfig = InspectConfig.newBuilder().addInfoTypes(infoType).build();
      // Specify replacement string to be used for the finding.
      ReplaceValueConfig replaceValueConfig =
          ReplaceValueConfig.newBuilder()
              .setNewValue(Value.newBuilder().setStringValue("[email-address]").build())
              .build();
      // Define type of deidentification as replacement.
      PrimitiveTransformation primitiveTransformation =
          PrimitiveTransformation.newBuilder().setReplaceConfig(replaceValueConfig).build();
      // Associate deidentification type with info type.
      InfoTypeTransformation transformation =
          InfoTypeTransformation.newBuilder()
              .addInfoTypes(infoType)
              .setPrimitiveTransformation(primitiveTransformation)
              .build();
      // Construct the configuration for the Redact request and list all desired transformations.
      DeidentifyConfig redactConfig =
          DeidentifyConfig.newBuilder()
              .setInfoTypeTransformations(
                  InfoTypeTransformations.newBuilder().addTransformations(transformation))
              .build();

      // Construct the Redact request to be sent by the client.
      DeidentifyContentRequest request =
          DeidentifyContentRequest.newBuilder()
              .setParent(LocationName.of(projectId, "global").toString())
              .setItem(item)
              .setDeidentifyConfig(redactConfig)
              .setInspectConfig(inspectConfig)
              .build();

      // Use the client to send the API request.
      DeidentifyContentResponse response = dlp.deidentifyContent(request);

      // Parse the response and process results
      System.out.println("Text after redaction: " + response.getItem().getValue());
    } catch (Exception e) {
      System.out.println("Error during inspectString: \n" + e.toString());
    }
  }
}

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:deidentify?key={YOUR_API_KEY}

{
  "item":{
    "value":"My name is Alicia Abernathy, and my email address is [e-mail]."
  },
  "deidentifyConfig":{
    "infoTypeTransformations":{
      "transformations":[
        {
          "infoTypes":[
            {
              "name":"EMAIL_ADDRESS"
            }
          ],
          "primitiveTransformation":{
            "replaceConfig":{
              "newValue":{
                "stringValue":"[email-address]"
              }
            }
          }
        }
      ]
    }
  },
  "inspectConfig":{
    "infoTypes":[
      {
        "name":"EMAIL_ADDRESS"
      }
    ]
  }
}

JSON 输出：

{
  "item":{
    "value":"My name is Alicia Abernathy, and my email address is [email-address]."
  },
  "overview":{
    "transformedBytes":"22",
    "transformationSummaries":[
      {
        "infoType":{
          "name":"EMAIL_ADDRESS"
        },
        "transformation":{
          "replaceConfig":{
            "newValue":{
              "stringValue":"[email-address]"
            }
          }
        },
        "results":[
          {
            "count":"1",
            "code":"SUCCESS"
          }
        ],
        "transformedBytes":"22"
      }
    ]
  }
}

redactConfig

如果指定 redactConfig，将会彻底移除给定的值来达到隐去该值的目的。redactConfig 消息不带参数，指定它就会启用该转换。

例如，假设您已为所有 EMAIL_ADDRESS infoType 指定 redactConfig，且已将下列字符串发送到敏感数据保护：

My name is Alicia Abernathy, and my email address is [e-mail].

返回的字符串如下：

My name is Alicia Abernathy, and my email address is .

以下示例展示了如何创建 API 请求以及 DLP API 会返回哪些内容：

重要提示： 此页面上的代码要求您首先设置 Sensitive Data Protection 客户端。如需详细了解如何安装和创建敏感数据保护客户端，请参阅 敏感数据保护客户端库。（无需客户端库即可将 JSON 发送到敏感数据保护 REST 端点。）

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

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

        // Construct inspect config.
        var inspectConfig = new InspectConfig
        {
            InfoTypes = { infoTypes ?? new InfoType[] { new InfoType { Name = "EMAIL_ADDRESS" } } },
        };

        // Construct redact config.
        var redactConfig = new RedactConfig();

        // Construct deidentify config using redact config.
        var deidentifyConfig = new DeidentifyConfig
        {
            InfoTypeTransformations = new InfoTypeTransformations
            {
                Transformations =
                {
                    new InfoTypeTransformations.Types.InfoTypeTransformation
                    {
                        PrimitiveTransformation = new PrimitiveTransformation
                        {
                            RedactConfig = redactConfig
                        }
                    }
                }
            }
        };

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

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

        // Check the deidentified content.
        Console.WriteLine($"Deidentified content: {response.Item.Value}");
        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"
)

// deidentifyWithRedact de-identify the data by redacting with matched input values
func deidentifyWithRedact(w io.Writer, projectID, inputStr string, infoTypeNames []string) error {
	// projectID := "my-project-id"
	// inputStr := "My name is Alicia Abernathy, and my email address is [e-mail]."
	// infoTypeNames := []string{"EMAIL_ADDRESS"}

	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 fmt.Errorf("dlp.NewClient: %w", err)
	}

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

	// Specify the content to be inspected.
	contentItem := &dlppb.ContentItem{
		DataItem: &dlppb.ContentItem_Value{
			Value: inputStr,
		},
	}

	// 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
	var infoTypes []*dlppb.InfoType
	for _, it := range infoTypeNames {
		infoTypes = append(infoTypes, &dlppb.InfoType{Name: it})
	}
	inspectConfig := &dlppb.InspectConfig{
		InfoTypes: infoTypes,
	}

	// Define type of de-identification.
	primitiveTransformation := &dlppb.PrimitiveTransformation{
		Transformation: &dlppb.PrimitiveTransformation_RedactConfig{
			RedactConfig: &dlppb.RedactConfig{},
		},
	}

	// Associate de-identification type with info type.
	transformation := &dlppb.InfoTypeTransformations_InfoTypeTransformation{
		InfoTypes:               infoTypes,
		PrimitiveTransformation: primitiveTransformation,
	}

	// Construct the configuration for the Redact request and list all desired transformations.
	redactConfig := &dlppb.DeidentifyConfig{
		Transformation: &dlppb.DeidentifyConfig_InfoTypeTransformations{
			InfoTypeTransformations: &dlppb.InfoTypeTransformations{
				Transformations: []*dlppb.InfoTypeTransformations_InfoTypeTransformation{
					transformation,
				},
			},
		},
	}

	// Create a configured request.
	req := &dlppb.DeidentifyContentRequest{
		Parent:           fmt.Sprintf("projects/%s/locations/global", projectID),
		DeidentifyConfig: redactConfig,
		InspectConfig:    inspectConfig,
		Item:             contentItem,
	}

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

	// Print the result.
	fmt.Fprintf(w, "output: %v", resp.GetItem().GetValue())
	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.DeidentifyConfig;
import com.google.privacy.dlp.v2.DeidentifyContentRequest;
import com.google.privacy.dlp.v2.DeidentifyContentResponse;
import com.google.privacy.dlp.v2.InfoType;
import com.google.privacy.dlp.v2.InfoTypeTransformations;
import com.google.privacy.dlp.v2.InfoTypeTransformations.InfoTypeTransformation;
import com.google.privacy.dlp.v2.InspectConfig;
import com.google.privacy.dlp.v2.LocationName;
import com.google.privacy.dlp.v2.PrimitiveTransformation;
import com.google.privacy.dlp.v2.RedactConfig;

public class DeIdentifyWithRedaction {

  public static void main(String[] args) throws Exception {
    // TODO(developer): Replace these variables before running the sample.
    String projectId = "your-project-id";
    String textToInspect =
        "My name is Alicia Abernathy, and my email address is [e-mail].";
    deIdentifyWithRedaction(projectId, textToInspect);
  }

  // Inspects the provided text.
  public static void deIdentifyWithRedaction(String projectId, String textToRedact) {
    // 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 content to be inspected.
      ContentItem item = ContentItem.newBuilder().setValue(textToRedact).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
      InfoType infoType = InfoType.newBuilder().setName("EMAIL_ADDRESS").build();
      InspectConfig inspectConfig = InspectConfig.newBuilder().addInfoTypes(infoType).build();
      // Define type of deidentification.
      PrimitiveTransformation primitiveTransformation =
          PrimitiveTransformation.newBuilder()
              .setRedactConfig(RedactConfig.getDefaultInstance())
              .build();
      // Associate deidentification type with info type.
      InfoTypeTransformation transformation =
          InfoTypeTransformation.newBuilder()
              .addInfoTypes(infoType)
              .setPrimitiveTransformation(primitiveTransformation)
              .build();
      // Construct the configuration for the Redact request and list all desired transformations.
      DeidentifyConfig redactConfig =
          DeidentifyConfig.newBuilder()
              .setInfoTypeTransformations(
                  InfoTypeTransformations.newBuilder().addTransformations(transformation))
              .build();

      // Construct the Redact request to be sent by the client.
      DeidentifyContentRequest request =
          DeidentifyContentRequest.newBuilder()
              .setParent(LocationName.of(projectId, "global").toString())
              .setItem(item)
              .setDeidentifyConfig(redactConfig)
              .setInspectConfig(inspectConfig)
              .build();

      // Use the client to send the API request.
      DeidentifyContentResponse response = dlp.deidentifyContent(request);

      // Parse the response and process results
      System.out.println("Text after redaction: " + response.getItem().getValue());
    } catch (Exception e) {
      System.out.println("Error during inspectString: \n" + e.toString());
    }
  }
}

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();

// TODO(developer): Replace these variables before running the sample.
// const projectId = "your-project-id";

// The string to deidentify
// const string =
//   'My name is Alicia Abernathy, and my email address is [e-mail].';

// 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'}];

async function deIdentifyRedaction() {
  // Construct deidentify configuration
  const deidentifyConfig = {
    infoTypeTransformations: {
      transformations: [
        {
          infoTypes: infoTypes,
          primitiveTransformation: {
            redactConfig: {},
          },
        },
      ],
    },
  };

  // Construct inspect configuration
  const inspectConfig = {
    infoTypes: infoTypes,
  };

  // Construct Item
  const item = {
    value: string,
  };

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

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

  // Print the results
  console.log(`Text after redaction: ${response.item.value}`);
}

deIdentifyRedaction();

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\DeidentifyConfig;
use Google\Cloud\Dlp\V2\DeidentifyContentRequest;
use Google\Cloud\Dlp\V2\InfoType;
use Google\Cloud\Dlp\V2\InfoTypeTransformations;
use Google\Cloud\Dlp\V2\InfoTypeTransformations\InfoTypeTransformation;
use Google\Cloud\Dlp\V2\InspectConfig;
use Google\Cloud\Dlp\V2\PrimitiveTransformation;
use Google\Cloud\Dlp\V2\RedactConfig;

/**
 * De-identify data: Redacting with matched input values
 * Uses the Data Loss Prevention API to de-identify sensitive data in a string by redacting matched input values.
 *
 * @param string $callingProjectId      The Google Cloud project id to use as a parent resource.
 * @param string $textToInspect         The string to deidentify (will be treated as text).
 */
function deidentify_redact(
    // TODO(developer): Replace sample parameters before running the code.
    string $callingProjectId,
    string $textToInspect = 'My name is Alicia Abernathy, and my email address is [e-mail].'

): void {
    // Instantiate a client.
    $dlp = new DlpServiceClient();

    // Specify the content to be de-identify.
    $contentItem = (new ContentItem())
        ->setValue($textToInspect);

    // Specify the type of info the inspection will look for.
    $infoType = (new InfoType())
        ->setName('EMAIL_ADDRESS');
    $inspectConfig = (new InspectConfig())
        ->setInfoTypes([$infoType]);

    // Define type of de-identification.
    $primitiveTransformation = (new PrimitiveTransformation())
        ->setRedactConfig(new RedactConfig());

    // Associate de-identification type with info type.
    $transformation = (new InfoTypeTransformation())
        ->setInfoTypes([$infoType])
        ->setPrimitiveTransformation($primitiveTransformation);

    // Construct the configuration for the Redact request and list all desired transformations.
    $deidentifyConfig = (new DeidentifyConfig())
        ->setInfoTypeTransformations((new InfoTypeTransformations())
            ->setTransformations([$transformation]));

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

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

    // Print results
    printf('Text after redaction: %s', $response->getItem()->getValue());
}

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 deidentify_with_redact(
    project: str,
    input_str: str,
    info_types: List[str],
) -> None:
    """Uses the Data Loss Prevention API to deidentify sensitive data in a
    string by redacting matched input values.
    Args:
        project: The Google Cloud project id to use as a parent resource.
        input_str: The string to deidentify (will be treated as text).
        info_types: A list of strings representing info types to look for.
    Returns:
        None; the response from the API is printed to the terminal.
    """

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

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

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

    # Construct deidentify configuration dictionary
    deidentify_config = {
        "info_type_transformations": {
            "transformations": [{"primitive_transformation": {"redact_config": {}}}]
        }
    }

    # Construct item
    item = {"value": input_str}

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

    # Print out the results.
    print(response.item.value)

REST

JSON 输入：

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

{
  "item":{
    "value":"My name is Alicia Abernathy, and my email address is [e-mail]."
  },
  "deidentifyConfig":{
    "infoTypeTransformations":{
      "transformations":[
        {
          "infoTypes":[
            {
              "name":"EMAIL_ADDRESS"
            }
          ],
          "primitiveTransformation":{
            "redactConfig":{

            }
          }
        }
      ]
    }
  },
  "inspectConfig":{
    "infoTypes":[
      {
        "name":"EMAIL_ADDRESS"
      }
    ]
  }
}

JSON 输出：

{
  "item":{
    "value":"My name is Alicia Abernathy, and my email address is ."
  },
  "overview":{
    "transformedBytes":"22",
    "transformationSummaries":[
      {
        "infoType":{
          "name":"EMAIL_ADDRESS"
        },
        "transformation":{
          "redactConfig":{

          }
        },
        "results":[
          {
            "count":"1",
            "code":"SUCCESS"
          }
        ],
        "transformedBytes":"22"
      }
    ]
  }
}

characterMaskConfig

如果将 characterMaskConfig 设置为 CharacterMaskConfig 对象，就可以通过把给定数量的字符替换为固定字符来部分遮盖字符串。可以从字符串的开头或结尾开始遮盖。此转换也适用于数字类型，例如长整型。

CharacterMaskConfig 对象自带多个参数：

• maskingCharacter：用于遮盖敏感值中每个字符的字符。例如，您可以指定用星号 (*) 或井号 (#) 来遮盖信用卡号等信息中的一连串数字。
• numberToMask：要遮盖的字符数。如果未设置此值，则将遮盖所有匹配的字符。
• reverseOrder：是否按反向顺序遮盖字符。如果将 reverseOrder 设置为 true，将从值的末尾朝着值的开头遮盖匹配值中的字符。如果设置为 false，则从值的开头开始遮盖。
• charactersToIgnore[]：遮盖值时要跳过的一个或多个字符。例如，如果在此处指定连字符，就会在遮盖电话号码时保留连字符。您还可以指定一组要在遮盖时忽略的常见字符 (CharsToIgnore)。

例如，假设您已设置 characterMaskConfig 来使用“#”遮盖 EMAIL_ADDRESS infotype（“.”和“@”字符除外）。如果将以下字符串发送到敏感数据保护功能：

My name is Alicia Abernathy, and my email address is [e-mail].

返回的字符串如下：

My name is Alicia Abernathy, and my email address is ##########@#######.###.

下面的示例演示了如何通过 DLP API 来使用遮盖技术对敏感数据进行去标识化。

重要提示： 此页面上的代码要求您首先设置 Sensitive Data Protection 客户端。如需详细了解如何安装和创建敏感数据保护客户端，请参阅 敏感数据保护客户端库。（无需客户端库即可将 JSON 发送到敏感数据保护 REST 端点。）

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.CharacterMaskConfig;
import com.google.privacy.dlp.v2.ContentItem;
import com.google.privacy.dlp.v2.DeidentifyConfig;
import com.google.privacy.dlp.v2.DeidentifyContentRequest;
import com.google.privacy.dlp.v2.DeidentifyContentResponse;
import com.google.privacy.dlp.v2.InfoType;
import com.google.privacy.dlp.v2.InfoTypeTransformations;
import com.google.privacy.dlp.v2.InfoTypeTransformations.InfoTypeTransformation;
import com.google.privacy.dlp.v2.InspectConfig;
import com.google.privacy.dlp.v2.LocationName;
import com.google.privacy.dlp.v2.PrimitiveTransformation;
import java.io.IOException;
import java.util.Arrays;

public class DeIdentifyWithMasking {

  public static void main(String[] args) throws Exception {
    // TODO(developer): Replace these variables before running the sample.
    String projectId = "your-project-id";
    String textToDeIdentify = "My SSN is 372819127";
    deIdentifyWithMasking(projectId, textToDeIdentify);
  }

  public static void deIdentifyWithMasking(String projectId, String textToDeIdentify)
      throws IOException {
    // Initialize client that will be used to send requests. This client only needs to be created
    // once, and can be reused for multiple requests. After completing all of your requests, call
    // the "close" method on the client to safely clean up any remaining background resources.
    try (DlpServiceClient dlp = DlpServiceClient.create()) {

      // Specify what content you want the service to DeIdentify
      ContentItem contentItem = ContentItem.newBuilder().setValue(textToDeIdentify).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
      InfoType infoType = InfoType.newBuilder().setName("US_SOCIAL_SECURITY_NUMBER").build();
      InspectConfig inspectConfig =
          InspectConfig.newBuilder().addAllInfoTypes(Arrays.asList(infoType)).build();

      // Specify how the info from the inspection should be masked.
      CharacterMaskConfig characterMaskConfig =
          CharacterMaskConfig.newBuilder()
              .setMaskingCharacter("X") // Character to replace the found info with
              .setNumberToMask(5) // How many characters should be masked
              .build();
      PrimitiveTransformation primitiveTransformation =
          PrimitiveTransformation.newBuilder()
              .setCharacterMaskConfig(characterMaskConfig)
              .build();
      InfoTypeTransformation infoTypeTransformation =
          InfoTypeTransformation.newBuilder()
              .setPrimitiveTransformation(primitiveTransformation)
              .build();
      InfoTypeTransformations transformations =
          InfoTypeTransformations.newBuilder().addTransformations(infoTypeTransformation).build();

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

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

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

      // Print the results
      System.out.println("Text after masking: " + response.getItem().getValue());
    }
  }
}

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-id';

// The string to deidentify
// const string = 'My SSN is 372819127';

// (Optional) The maximum number of sensitive characters to mask in a match
// If omitted from the request or set to 0, the API will mask any matching characters
// const numberToMask = 5;

// (Optional) The character to mask matching sensitive data with
// const maskingCharacter = 'x';

// Construct deidentification request
const item = {value: string};

async function deidentifyWithMask() {
  const request = {
    parent: `projects/${projectId}/locations/global`,
    deidentifyConfig: {
      infoTypeTransformations: {
        transformations: [
          {
            primitiveTransformation: {
              characterMaskConfig: {
                maskingCharacter: maskingCharacter,
                numberToMask: numberToMask,
              },
            },
          },
        ],
      },
    },
    item: item,
  };

  // Run deidentification request
  const [response] = await dlp.deidentifyContent(request);
  const deidentifiedItem = response.item;
  console.log(deidentifiedItem.value);
}

deidentifyWithMask();

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 deidentify_with_mask(
    project: str,
    input_str: str,
    info_types: List[str],
    masking_character: str = None,
    number_to_mask: int = 0,
) -> None:
    """Uses the Data Loss Prevention API to deidentify sensitive data in a
    string by masking it with a character.
    Args:
        project: The Google Cloud project id to use as a parent resource.
        input_str: The string to deidentify (will be treated as text).
        info_types: A list of strings representing info types to look for.
            A full list of info type categories can be fetched from the API.
        masking_character: The character to mask matching sensitive data with.
        number_to_mask: The maximum number of sensitive characters to mask in
            a match. If omitted or set to zero, the API will default to no
            maximum.
    Returns:
        None; the response from the API is printed to the terminal.
    """

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

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

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

    # Construct deidentify configuration dictionary
    deidentify_config = {
        "info_type_transformations": {
            "transformations": [
                {
                    "primitive_transformation": {
                        "character_mask_config": {
                            "masking_character": masking_character,
                            "number_to_mask": number_to_mask,
                        }
                    }
                }
            ]
        }
    }

    # Construct item
    item = {"value": input_str}

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

    # Print out the results.
    print(response.item.value)

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"
)

// mask deidentifies the input by masking all provided info types with maskingCharacter
// and prints the result to w.
func mask(w io.Writer, projectID, input string, infoTypeNames []string, maskingCharacter string, numberToMask int32) error {
	// projectID := "my-project-id"
	// input := "My SSN is 111222333"
	// infoTypeNames := []string{"US_SOCIAL_SECURITY_NUMBER"}
	// maskingCharacter := "+"
	// numberToMask := 6
	// Will print "My SSN is ++++++333"

	ctx := context.Background()
	client, err := dlp.NewClient(ctx)
	if err != nil {
		return fmt.Errorf("dlp.NewClient: %w", err)
	}
	defer client.Close()
	// Convert the info type strings to a list of InfoTypes.
	var infoTypes []*dlppb.InfoType
	for _, it := range infoTypeNames {
		infoTypes = append(infoTypes, &dlppb.InfoType{Name: it})
	}
	// Create a configured request.
	req := &dlppb.DeidentifyContentRequest{
		Parent: fmt.Sprintf("projects/%s/locations/global", projectID),
		InspectConfig: &dlppb.InspectConfig{
			InfoTypes: infoTypes,
		},
		DeidentifyConfig: &dlppb.DeidentifyConfig{
			Transformation: &dlppb.DeidentifyConfig_InfoTypeTransformations{
				InfoTypeTransformations: &dlppb.InfoTypeTransformations{
					Transformations: []*dlppb.InfoTypeTransformations_InfoTypeTransformation{
						{
							InfoTypes: []*dlppb.InfoType{}, // Match all info types.
							PrimitiveTransformation: &dlppb.PrimitiveTransformation{
								Transformation: &dlppb.PrimitiveTransformation_CharacterMaskConfig{
									CharacterMaskConfig: &dlppb.CharacterMaskConfig{
										MaskingCharacter: maskingCharacter,
										NumberToMask:     numberToMask,
									},
								},
							},
						},
					},
				},
			},
		},
		// The item to analyze.
		Item: &dlppb.ContentItem{
			DataItem: &dlppb.ContentItem_Value{
				Value: input,
			},
		},
	}
	// Send the request.
	r, err := client.DeidentifyContent(ctx, req)
	if err != nil {
		return fmt.Errorf("DeidentifyContent: %w", err)
	}
	// Print the result.
	fmt.Fprint(w, r.GetItem().GetValue())
	return nil
}

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\CharacterMaskConfig;
use Google\Cloud\Dlp\V2\Client\DlpServiceClient;
use Google\Cloud\Dlp\V2\ContentItem;
use Google\Cloud\Dlp\V2\DeidentifyConfig;
use Google\Cloud\Dlp\V2\DeidentifyContentRequest;
use Google\Cloud\Dlp\V2\InfoType;
use Google\Cloud\Dlp\V2\InfoTypeTransformations;
use Google\Cloud\Dlp\V2\InfoTypeTransformations\InfoTypeTransformation;
use Google\Cloud\Dlp\V2\PrimitiveTransformation;

/**
 * Deidentify sensitive data in a string by masking it with a character.
 *
 * @param string $callingProjectId The GCP Project ID to run the API call under
 * @param string $string           The string to deidentify
 * @param int    $numberToMask     (Optional) The maximum number of sensitive characters to mask in a match
 * @param string $maskingCharacter (Optional) The character to mask matching sensitive data with (defaults to "x")
 */
function deidentify_mask(
    string $callingProjectId,
    string $string,
    int $numberToMask = 0,
    string $maskingCharacter = 'x'
): void {
    // Instantiate a client.
    $dlp = new DlpServiceClient();

    // The infoTypes of information to mask
    $ssnInfoType = (new InfoType())
        ->setName('US_SOCIAL_SECURITY_NUMBER');
    $infoTypes = [$ssnInfoType];

    // Create the masking configuration object
    $maskConfig = (new CharacterMaskConfig())
        ->setMaskingCharacter($maskingCharacter)
        ->setNumberToMask($numberToMask);

    // Create the information transform configuration objects
    $primitiveTransformation = (new PrimitiveTransformation())
        ->setCharacterMaskConfig($maskConfig);

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

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

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

    $item = (new ContentItem())
        ->setValue($string);

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

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

    // Print the results
    $deidentifiedValue = $response->getItem()->getValue();
    print($deidentifiedValue);
}

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;

public class DeidentifyWithMasking
{
    public static DeidentifyContentResponse Deidentify(string projectId, string text)
    {
        // Instantiate a client.
        var dlp = DlpServiceClient.Create();

        // Construct a request.
        var transformation = new InfoTypeTransformations.Types.InfoTypeTransformation
        {
            PrimitiveTransformation = new PrimitiveTransformation
            {
                CharacterMaskConfig = new CharacterMaskConfig
                {
                    MaskingCharacter = "*",
                    NumberToMask = 5,
                    ReverseOrder = false,
                }
            }
        };
        var request = new DeidentifyContentRequest
        {
            Parent = new LocationName(projectId, "global").ToString(),
            InspectConfig = new InspectConfig
            {
                InfoTypes =
                {
                    new InfoType { Name = "US_SOCIAL_SECURITY_NUMBER" }
                }
            },
            DeidentifyConfig = new DeidentifyConfig
            {
                InfoTypeTransformations = new InfoTypeTransformations
                {
                    Transformations = { transformation }
                }
            },
            Item = new ContentItem { Value = text }
        };

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

        // Inspect the results.
        Console.WriteLine($"Deidentified content: {response.Item.Value}");
        return response;
    }
}

REST

下面的 JSON 示例演示了如何创建 API 请求且 DLP API 返回哪些内容：

JSON 输入：

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

{
  "item":{
    "value":"My name is Alicia Abernathy, and my email address is [e-mail]."
  },
  "deidentifyConfig":{
    "infoTypeTransformations":{
      "transformations":[
        {
          "infoTypes":[
            {
              "name":"EMAIL_ADDRESS"
            }
          ],
          "primitiveTransformation":{
            "characterMaskConfig":{
              "maskingCharacter":"#",
              "reverseOrder":false,
              "charactersToIgnore":[
                {
                  "charactersToSkip":".@"
                }
              ]
            }
          }
        }
      ]
    }
  },
  "inspectConfig":{
    "infoTypes":[
      {
        "name":"EMAIL_ADDRESS"
      }
    ]
  }
}

JSON 输出：

{
  "item":{
    "value":"My name is Alicia Abernathy, and my email address is ##########@#######.###."
  },
  "overview":{
    "transformedBytes":"22",
    "transformationSummaries":[
      {
        "infoType":{
          "name":"EMAIL_ADDRESS"
        },
        "transformation":{
          "characterMaskConfig":{
            "maskingCharacter":"#",
            "charactersToIgnore":[
              {
                "charactersToSkip":".@"
              }
            ]
          }
        },
        "results":[
          {
            "count":"1",
            "code":"SUCCESS"
          }
        ],
        "transformedBytes":"22"
      }
    ]
  }
}

cryptoHashConfig

如果把 cryptoHashConfig 设置为 CryptoHashConfig 对象，将使用加密哈希技术生成代理值来对输入值执行假名化。

此方法会使用加密的“摘要”或哈希值替换输入值。 摘要是通过获取输入值的 SHA-256 哈希计算得出的。 用于获取哈希的加密密钥为 CryptoKey 对象，且大小必须为 32 或 64 字节。

此方法会输出以 base64 编码表示的哈希输出值。目前，只能对字符串和整数值进行哈希处理。

例如，假设您已为所有 EMAIL_ADDRESS infoType 指定 cryptoHashConfig，且 CryptoKey 对象由随机生成的密钥（一种 TransientCryptoKey）组成。然后，您将下列字符串发送到敏感数据保护：

My name is Alicia Abernathy, and my email address is [e-mail].

返回的字符串以加密方式生成，显示如下：

My name is Alicia Abernathy, and my email address is 41D1567F7F99F1DC2A5FAB886DEE5BEE.

当然，十六进制字符串将以加密方式生成且与此处所示不同。

dateShiftConfig

如果把 dateShiftConfig 设置为 DateShiftConfig 对象，将通过按随机天数偏移日期来对日期输入值执行日期偏移。

日期偏移技术会随机偏移一组日期，但保留一段时间内的顺序和持续时间。通常在个人或实体的上下文中完成偏移日期。也就是说，您要按同一偏移差分偏移特定个人的所有日期，但对每个人使用不同的偏移差分。

要详细了解日期偏移，请参阅日期偏移概念主题。

下面是多种语言的示例代码，演示了如何使用 DLP API 通过日期偏移对日期进行去标识化。

重要提示： 此页面上的代码要求您首先设置 Sensitive Data Protection 客户端。如需详细了解如何安装和创建敏感数据保护客户端，请参阅 敏感数据保护客户端库。（无需客户端库即可将 JSON 发送到敏感数据保护 REST 端点。）

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.common.base.Splitter;
import com.google.privacy.dlp.v2.ContentItem;
import com.google.privacy.dlp.v2.DateShiftConfig;
import com.google.privacy.dlp.v2.DeidentifyConfig;
import com.google.privacy.dlp.v2.DeidentifyContentRequest;
import com.google.privacy.dlp.v2.DeidentifyContentResponse;
import com.google.privacy.dlp.v2.FieldId;
import com.google.privacy.dlp.v2.FieldTransformation;
import com.google.privacy.dlp.v2.LocationName;
import com.google.privacy.dlp.v2.PrimitiveTransformation;
import com.google.privacy.dlp.v2.RecordTransformations;
import com.google.privacy.dlp.v2.Table;
import com.google.privacy.dlp.v2.Value;
import com.google.type.Date;
import java.io.BufferedReader;
import java.io.BufferedWriter;
import java.io.IOException;
import java.nio.file.Files;
import java.nio.file.Path;
import java.nio.file.Paths;
import java.time.LocalDate;
import java.time.format.DateTimeFormatter;
import java.util.Arrays;
import java.util.List;
import java.util.stream.Collectors;

public class DeIdentifyWithDateShift {

  public static void main(String[] args) throws Exception {
    // TODO(developer): Replace these variables before running the sample.
    String projectId = "your-project-id";
    Path inputCsvFile = Paths.get("path/to/your/input/file.csv");
    Path outputCsvFile = Paths.get("path/to/your/output/file.csv");
    deIdentifyWithDateShift(projectId, inputCsvFile, outputCsvFile);
  }

  public static void deIdentifyWithDateShift(
      String projectId, Path inputCsvFile, Path outputCsvFile) 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()) {
      // Read the contents of the CSV file into a Table
      List<FieldId> headers;
      List<Table.Row> rows;
      try (BufferedReader input = Files.newBufferedReader(inputCsvFile)) {
        // Parse and convert the first line into header names
        headers =
            Arrays.stream(input.readLine().split(","))
                .map(header -> FieldId.newBuilder().setName(header).build())
                .collect(Collectors.toList());
        // Parse the remainder of the file as Table.Rows
        rows =
            input.lines().map(DeIdentifyWithDateShift::parseLineAsRow).collect(Collectors.toList());
      }
      Table table = Table.newBuilder().addAllHeaders(headers).addAllRows(rows).build();
      ContentItem item = ContentItem.newBuilder().setTable(table).build();

      // Set the maximum days to shift dates backwards (lower bound) or forward (upper bound)
      DateShiftConfig dateShiftConfig =
          DateShiftConfig.newBuilder().setLowerBoundDays(5).setUpperBoundDays(5).build();
      PrimitiveTransformation transformation =
          PrimitiveTransformation.newBuilder().setDateShiftConfig(dateShiftConfig).build();
      // Specify which fields the DateShift should apply too
      List<FieldId> dateFields = Arrays.asList(headers.get(1), headers.get(3));
      FieldTransformation fieldTransformation =
          FieldTransformation.newBuilder()
              .addAllFields(dateFields)
              .setPrimitiveTransformation(transformation)
              .build();
      RecordTransformations recordTransformations =
          RecordTransformations.newBuilder().addFieldTransformations(fieldTransformation).build();
      // Specify the config for the de-identify request
      DeidentifyConfig deidentifyConfig =
          DeidentifyConfig.newBuilder().setRecordTransformations(recordTransformations).build();

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

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

      // Write the results to the target CSV file
      try (BufferedWriter writer = Files.newBufferedWriter(outputCsvFile)) {
        Table outTable = response.getItem().getTable();
        String headerOut =
            outTable.getHeadersList().stream()
                .map(FieldId::getName)
                .collect(Collectors.joining(","));
        writer.write(headerOut + "\n");

        List<String> rowOutput =
            outTable.getRowsList().stream()
                .map(row -> joinRow(row.getValuesList()))
                .collect(Collectors.toList());
        for (String line : rowOutput) {
          writer.write(line + "\n");
        }
        System.out.println("Content written to file: " + outputCsvFile.toString());
      }
    }
  }

  // Convert the string from the csv file into com.google.type.Date
  public static Date parseAsDate(String s) {
    LocalDate date = LocalDate.parse(s, DateTimeFormatter.ofPattern("MM/dd/yyyy"));
    return Date.newBuilder()
        .setDay(date.getDayOfMonth())
        .setMonth(date.getMonthValue())
        .setYear(date.getYear())
        .build();
  }

  // Each row is in the format: Name,BirthDate,CreditCardNumber,RegisterDate
  public static Table.Row parseLineAsRow(String line) {
    List<String> values = Splitter.on(",").splitToList(line);
    Value name = Value.newBuilder().setStringValue(values.get(0)).build();
    Value birthDate = Value.newBuilder().setDateValue(parseAsDate(values.get(1))).build();
    Value creditCardNumber = Value.newBuilder().setStringValue(values.get(2)).build();
    Value registerDate = Value.newBuilder().setDateValue(parseAsDate(values.get(3))).build();
    return Table.Row.newBuilder()
        .addValues(name)
        .addValues(birthDate)
        .addValues(creditCardNumber)
        .addValues(registerDate)
        .build();
  }

  public static String formatDate(Date d) {
    return String.format("%s/%s/%s", d.getMonth(), d.getDay(), d.getYear());
  }

  public static String joinRow(List<Value> values) {
    String name = values.get(0).getStringValue();
    String birthDate = formatDate(values.get(1).getDateValue());
    String creditCardNumber = values.get(2).getStringValue();
    String registerDate = formatDate(values.get(3).getDateValue());
    return String.join(",", name, birthDate, creditCardNumber, registerDate);
  }
}

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();

// Import other required libraries
const fs = require('fs');

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

// The path to the CSV file to deidentify
// The first row of the file must specify column names, and all other rows
// must contain valid values
// const inputCsvFile = '/path/to/input/file.csv';

// The path to save the date-shifted CSV file to
// const outputCsvFile = '/path/to/output/file.csv';

// The list of (date) fields in the CSV file to date shift
// const dateFields = [{ name: 'birth_date'}, { name: 'register_date' }];

// The maximum number of days to shift a date backward
// const lowerBoundDays = 1;

// The maximum number of days to shift a date forward
// const upperBoundDays = 1;

// (Optional) The column to determine date shift amount based on
// If this is not specified, a random shift amount will be used for every row
// If this is specified, then 'wrappedKey' and 'keyName' must also be set
// const contextFieldId = [{ name: 'user_id' }];

// (Optional) The name of the Cloud KMS key used to encrypt ('wrap') the AES-256 key
// If this is specified, then 'wrappedKey' and 'contextFieldId' must also be set
// const keyName = 'projects/YOUR_GCLOUD_PROJECT/locations/YOUR_LOCATION/keyRings/YOUR_KEYRING_NAME/cryptoKeys/YOUR_KEY_NAME';

// (Optional) The encrypted ('wrapped') AES-256 key to use when shifting dates
// This key should be encrypted using the Cloud KMS key specified above
// If this is specified, then 'keyName' and 'contextFieldId' must also be set
// const wrappedKey = 'YOUR_ENCRYPTED_AES_256_KEY'

// Helper function for converting CSV rows to Protobuf types
const rowToProto = row => {
  const values = row.split(',');
  const convertedValues = values.map(value => {
    if (Date.parse(value)) {
      const date = new Date(value);
      return {
        dateValue: {
          year: date.getFullYear(),
          month: date.getMonth() + 1,
          day: date.getDate(),
        },
      };
    } else {
      // Convert all non-date values to strings
      return {stringValue: value.toString()};
    }
  });
  return {values: convertedValues};
};

async function deidentifyWithDateShift() {
  // Read and parse a CSV file
  const csvLines = fs
    .readFileSync(inputCsvFile)
    .toString()
    .split('\n')
    .filter(line => line.includes(','));
  const csvHeaders = csvLines[0].split(',');
  const csvRows = csvLines.slice(1);

  // Construct the table object
  const tableItem = {
    table: {
      headers: csvHeaders.map(header => {
        return {name: header};
      }),
      rows: csvRows.map(row => rowToProto(row)),
    },
  };

  // Construct DateShiftConfig
  const dateShiftConfig = {
    lowerBoundDays: lowerBoundDays,
    upperBoundDays: upperBoundDays,
  };

  if (contextFieldId && keyName && wrappedKey) {
    dateShiftConfig.context = {name: contextFieldId};
    dateShiftConfig.cryptoKey = {
      kmsWrapped: {
        wrappedKey: wrappedKey,
        cryptoKeyName: keyName,
      },
    };
  } else if (contextFieldId || keyName || wrappedKey) {
    throw new Error(
      'You must set either ALL or NONE of {contextFieldId, keyName, wrappedKey}!'
    );
  }

  // Construct deidentification request
  const request = {
    parent: `projects/${projectId}/locations/global`,
    deidentifyConfig: {
      recordTransformations: {
        fieldTransformations: [
          {
            fields: dateFields,
            primitiveTransformation: {
              dateShiftConfig: dateShiftConfig,
            },
          },
        ],
      },
    },
    item: tableItem,
  };

  // Run deidentification request
  const [response] = await dlp.deidentifyContent(request);
  const tableRows = response.item.table.rows;

  // Write results to a CSV file
  tableRows.forEach((row, rowIndex) => {
    const rowValues = row.values.map(
      value =>
        value.stringValue ||
        `${value.dateValue.month}/${value.dateValue.day}/${value.dateValue.year}`
    );
    csvLines[rowIndex + 1] = rowValues.join(',');
  });
  csvLines.push('');
  fs.writeFileSync(outputCsvFile, csvLines.join('\n'));

  // Print status
  console.log(`Successfully saved date-shift output to ${outputCsvFile}`);
}

deidentifyWithDateShift();

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 base64
import csv
from datetime import datetime
from typing import List

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


def deidentify_with_date_shift(
    project: str,
    input_csv_file: str = None,
    output_csv_file: str = None,
    date_fields: List[str] = None,
    lower_bound_days: int = None,
    upper_bound_days: int = None,
    context_field_id: str = None,
    wrapped_key: str = None,
    key_name: str = None,
) -> None:
    """Uses the Data Loss Prevention API to deidentify dates in a CSV file by
        pseudorandomly shifting them.
    Args:
        project: The Google Cloud project id to use as a parent resource.
        input_csv_file: The path to the CSV file to deidentify. The first row
            of the file must specify column names, and all other rows must
            contain valid values.
        output_csv_file: The path to save the date-shifted CSV file.
        date_fields: The list of (date) fields in the CSV file to date shift.
            Example: ['birth_date', 'register_date']
        lower_bound_days: The maximum number of days to shift a date backward
        upper_bound_days: The maximum number of days to shift a date forward
        context_field_id: (Optional) The column to determine date shift amount
            based on. If this is not specified, a random shift amount will be
            used for every row. If this is specified, then 'wrappedKey' and
            'keyName' must also be set. Example:
            contextFieldId = [{ 'name': 'user_id' }]
        key_name: (Optional) The name of the Cloud KMS key used to encrypt
            ('wrap') the AES-256 key. Example:
            key_name = 'projects/YOUR_GCLOUD_PROJECT/locations/YOUR_LOCATION/
            keyRings/YOUR_KEYRING_NAME/cryptoKeys/YOUR_KEY_NAME'
        wrapped_key: (Optional) The encrypted ('wrapped') AES-256 key to use.
            This key should be encrypted using the Cloud KMS key specified by
            key_name.
    Returns:
        None; the response from the API is printed to the terminal.
    """

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

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

    # Convert date field list to Protobuf type
    def map_fields(field: str) -> dict:
        return {"name": field}

    if date_fields:
        date_fields = map(map_fields, date_fields)
    else:
        date_fields = []

    f = []
    with open(input_csv_file) as csvfile:
        reader = csv.reader(csvfile)
        for row in reader:
            f.append(row)

    #  Helper function for converting CSV rows to Protobuf types
    def map_headers(header: str) -> dict:
        return {"name": header}

    def map_data(value: str) -> dict:
        try:
            date = datetime.strptime(value, "%m/%d/%Y")
            return {
                "date_value": {"year": date.year, "month": date.month, "day": date.day}
            }
        except ValueError:
            return {"string_value": value}

    def map_rows(row: str) -> dict:
        return {"values": map(map_data, row)}

    # Using the helper functions, convert CSV rows to protobuf-compatible
    # dictionaries.
    csv_headers = map(map_headers, f[0])
    csv_rows = map(map_rows, f[1:])

    # Construct the table dict
    table_item = {"table": {"headers": csv_headers, "rows": csv_rows}}

    # Construct date shift config
    date_shift_config = {
        "lower_bound_days": lower_bound_days,
        "upper_bound_days": upper_bound_days,
    }

    # If using a Cloud KMS key, add it to the date_shift_config.
    # The wrapped key is base64-encoded, but the library expects a binary
    # string, so decode it here.
    if context_field_id and key_name and wrapped_key:
        date_shift_config["context"] = {"name": context_field_id}
        date_shift_config["crypto_key"] = {
            "kms_wrapped": {
                "wrapped_key": base64.b64decode(wrapped_key),
                "crypto_key_name": key_name,
            }
        }
    elif context_field_id or key_name or wrapped_key:
        raise ValueError(
            """You must set either ALL or NONE of
        [context_field_id, key_name, wrapped_key]!"""
        )

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

    # Write to CSV helper methods
    def write_header(header: types.storage.FieldId) -> str:
        return header.name

    def write_data(data: types.storage.Value) -> str:
        return data.string_value or "{}/{}/{}".format(
            data.date_value.month,
            data.date_value.day,
            data.date_value.year,
        )

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

    # Write results to CSV file
    with open(output_csv_file, "w") as csvfile:
        write_file = csv.writer(csvfile, delimiter=",")
        write_file.writerow(map(write_header, response.item.table.headers))
        for row in response.item.table.rows:
            write_file.writerow(map(write_data, row.values))
    # Print status
    print(f"Successfully saved date-shift output to {output_csv_file}")

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"
)

// deidentifyDateShift shifts dates found in the input between lowerBoundDays and
// upperBoundDays.
func deidentifyDateShift(w io.Writer, projectID string, lowerBoundDays, upperBoundDays int32, input string) error {
	// projectID := "my-project-id"
	// lowerBoundDays := -1
	// upperBound := -1
	// input := "2016-01-10"
	// Will print "2016-01-09"
	ctx := context.Background()
	client, err := dlp.NewClient(ctx)
	if err != nil {
		return fmt.Errorf("dlp.NewClient: %w", err)
	}
	defer client.Close()
	// Create a configured request.
	req := &dlppb.DeidentifyContentRequest{
		Parent: fmt.Sprintf("projects/%s/locations/global", projectID),
		DeidentifyConfig: &dlppb.DeidentifyConfig{
			Transformation: &dlppb.DeidentifyConfig_InfoTypeTransformations{
				InfoTypeTransformations: &dlppb.InfoTypeTransformations{
					Transformations: []*dlppb.InfoTypeTransformations_InfoTypeTransformation{
						{
							InfoTypes: []*dlppb.InfoType{}, // Match all info types.
							PrimitiveTransformation: &dlppb.PrimitiveTransformation{
								Transformation: &dlppb.PrimitiveTransformation_DateShiftConfig{
									DateShiftConfig: &dlppb.DateShiftConfig{
										LowerBoundDays: lowerBoundDays,
										UpperBoundDays: upperBoundDays,
									},
								},
							},
						},
					},
				},
			},
		},
		// The InspectConfig is used to identify the DATE fields.
		InspectConfig: &dlppb.InspectConfig{
			InfoTypes: []*dlppb.InfoType{
				{
					Name: "DATE",
				},
			},
		},
		// The item to analyze.
		Item: &dlppb.ContentItem{
			DataItem: &dlppb.ContentItem_Value{
				Value: input,
			},
		},
	}
	// Send the request.
	r, err := client.DeidentifyContent(ctx, req)
	if err != nil {
		return fmt.Errorf("DeidentifyContent: %w", err)
	}
	// Print the result.
	fmt.Fprint(w, r.GetItem().GetValue())
	return nil
}

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 DateTime;
use Exception;
use Google\Cloud\Dlp\V2\Client\DlpServiceClient;
use Google\Cloud\Dlp\V2\ContentItem;
use Google\Cloud\Dlp\V2\CryptoKey;
use Google\Cloud\Dlp\V2\DateShiftConfig;
use Google\Cloud\Dlp\V2\DeidentifyConfig;
use Google\Cloud\Dlp\V2\DeidentifyContentRequest;
use Google\Cloud\Dlp\V2\FieldId;
use Google\Cloud\Dlp\V2\FieldTransformation;
use Google\Cloud\Dlp\V2\KmsWrappedCryptoKey;
use Google\Cloud\Dlp\V2\PrimitiveTransformation;
use Google\Cloud\Dlp\V2\RecordTransformations;
use Google\Cloud\Dlp\V2\Table;
use Google\Cloud\Dlp\V2\Table\Row;
use Google\Cloud\Dlp\V2\Value;
use Google\Type\Date;

/**
 * Deidentify dates in a CSV file by pseudorandomly shifting them.
 * If contextFieldName is not specified, a random shift amount will be used for every row.
 * If contextFieldName is specified, then 'wrappedKey' and 'keyName' must also be set.
 *
 * @param string $callingProjectId  The GCP Project ID to run the API call under
 * @param string $inputCsvFile      The path to the CSV file to deidentify
 * @param string $outputCsvFile     The path to save the date-shifted CSV file to
 * @param string $dateFieldNames    The comma-separated list of (date) fields in the CSV file to date shift
 * @param int    $lowerBoundDays    The maximum number of days to shift a date backward
 * @param int    $upperBoundDays    The maximum number of days to shift a date forward
 * @param string $contextFieldName  (Optional) The column to determine date shift amount based on
 * @param string $keyName           (Optional) The encrypted ('wrapped') AES-256 key to use when shifting dates
 * @param string $wrappedKey        (Optional) The name of the Cloud KMS key used to encrypt (wrap) the AES-256 key
 */
function deidentify_dates(
    string $callingProjectId,
    string $inputCsvFile,
    string $outputCsvFile,
    string $dateFieldNames,
    int $lowerBoundDays,
    int $upperBoundDays,
    string $contextFieldName = '',
    string $keyName = '',
    string $wrappedKey = ''
): void {
    // Instantiate a client.
    $dlp = new DlpServiceClient();

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

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

    $tableRows = array_map(function ($csvRow) {
        $rowValues = array_map(function ($csvValue) {
            if ($csvDate = DateTime::createFromFormat('m/d/Y', $csvValue)) {
                $date = (new Date())
                    ->setYear((int) $csvDate->format('Y'))
                    ->setMonth((int) $csvDate->format('m'))
                    ->setDay((int) $csvDate->format('d'));
                return (new Value())
                    ->setDateValue($date);
            } else {
                return (new Value())
                    ->setStringValue($csvValue);
            }
        }, explode(',', $csvRow));

        return (new Row())
            ->setValues($rowValues);
    }, $csvRows);

    // Convert date fields into protobuf objects
    $dateFields = array_map(function ($dateFieldName) {
        return (new FieldId())->setName($dateFieldName);
    }, explode(',', $dateFieldNames));

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

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

    // Construct dateShiftConfig
    $dateShiftConfig = (new DateShiftConfig())
        ->setLowerBoundDays($lowerBoundDays)
        ->setUpperBoundDays($upperBoundDays);

    if ($contextFieldName && $keyName && $wrappedKey) {
        $contextField = (new FieldId())
            ->setName($contextFieldName);

        // Create the wrapped crypto key configuration object
        $kmsWrappedCryptoKey = (new KmsWrappedCryptoKey())
            ->setWrappedKey(base64_decode($wrappedKey))
            ->setCryptoKeyName($keyName);

        $cryptoKey = (new CryptoKey())
            ->setKmsWrapped($kmsWrappedCryptoKey);

        $dateShiftConfig
            ->setContext($contextField)
            ->setCryptoKey($cryptoKey);
    } elseif ($contextFieldName || $keyName || $wrappedKey) {
        throw new Exception('You must set either ALL or NONE of {$contextFieldName, $keyName, $wrappedKey}!');
    }

    // Create the information transform configuration objects
    $primitiveTransformation = (new PrimitiveTransformation())
        ->setDateShiftConfig($dateShiftConfig);

    $fieldTransformation = (new FieldTransformation())
        ->setPrimitiveTransformation($primitiveTransformation)
        ->setFields($dateFields);

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

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

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

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

    // Check for errors
    foreach ($response->getOverview()->getTransformationSummaries() as $summary) {
        foreach ($summary->getResults() as $result) {
            if ($details = $result->getDetails()) {
                printf('Error: %s' . PHP_EOL, $details);
                return;
            }
        }
    }

    // Save the results to a file
    $csvRef = fopen($outputCsvFile, 'w');
    fputcsv($csvRef, $csvHeaders);
    foreach ($response->getItem()->getTable()->getRows() as $tableRow) {
        $values = array_map(function ($tableValue) {
            if ($tableValue->getStringValue()) {
                return $tableValue->getStringValue();
            }
            $protoDate = $tableValue->getDateValue();
            $date = mktime(0, 0, 0, $protoDate->getMonth(), $protoDate->getDay(), $protoDate->getYear());
            return strftime('%D', $date);
        }, iterator_to_array($tableRow->getValues()));
        fputcsv($csvRef, $values);
    };
    fclose($csvRef);
    printf('Deidentified dates written to %s' . PHP_EOL, $outputCsvFile);
}

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 System.IO;
using System.Linq;
using Google.Api.Gax.ResourceNames;
using Google.Cloud.Dlp.V2;
using Google.Protobuf;

public class DeidentifyWithDateShift
{
    public static DeidentifyContentResponse Deidentify(
        string projectId,
        string inputCsvFilePath,
        int lowerBoundDays,
        int upperBoundDays,
        string dateFields,
        string contextField,
        string keyName,
        string wrappedKey)
    {
        var hasKeyName = !string.IsNullOrEmpty(keyName);
        var hasWrappedKey = !string.IsNullOrEmpty(wrappedKey);
        var hasContext = !string.IsNullOrEmpty(contextField);
        bool allFieldsSet = hasKeyName && hasWrappedKey && hasContext;
        bool noFieldsSet = !hasKeyName && !hasWrappedKey && !hasContext;
        if (!(allFieldsSet || noFieldsSet))
        {
            throw new ArgumentException("Must specify ALL or NONE of: {contextFieldId, keyName, wrappedKey}!");
        }

        var dlp = DlpServiceClient.Create();

        // Read file
        var csvLines = File.ReadAllLines(inputCsvFilePath);
        var csvHeaders = csvLines[0].Split(',');
        var csvRows = csvLines.Skip(1).ToArray();

        // Convert dates to protobuf format, and everything else to a string
        var protoHeaders = csvHeaders.Select(header => new FieldId { Name = header });
        var protoRows = csvRows.Select(csvRow =>
        {
            var rowValues = csvRow.Split(',');
            var protoValues = rowValues.Select(rowValue =>
               System.DateTime.TryParse(rowValue, out var parsedDate)
               ? new Value { DateValue = Google.Type.Date.FromDateTime(parsedDate) }
               : new Value { StringValue = rowValue });

            var rowObject = new Table.Types.Row();
            rowObject.Values.Add(protoValues);
            return rowObject;
        });

        var dateFieldList = dateFields
            .Split(',')
            .Select(field => new FieldId { Name = field });

        // Construct + execute the request
        var dateShiftConfig = new DateShiftConfig
        {
            LowerBoundDays = lowerBoundDays,
            UpperBoundDays = upperBoundDays
        };

        dateShiftConfig.Context = new FieldId { Name = contextField };
        dateShiftConfig.CryptoKey = new CryptoKey
        {
            KmsWrapped = new KmsWrappedCryptoKey
            {
                WrappedKey = ByteString.FromBase64(wrappedKey),
                CryptoKeyName = keyName
            }
        };

        var deidConfig = new DeidentifyConfig
        {
            RecordTransformations = new RecordTransformations
            {
                FieldTransformations =
                {
                    new FieldTransformation
                    {
                        PrimitiveTransformation = new PrimitiveTransformation
                        {
                            DateShiftConfig = dateShiftConfig
                        },
                        Fields = { dateFieldList }
                    }
                }
            }
        };

        var response = dlp.DeidentifyContent(
            new DeidentifyContentRequest
            {
                Parent = new LocationName(projectId, "global").ToString(),
                DeidentifyConfig = deidConfig,
                Item = new ContentItem
                {
                    Table = new Table
                    {
                        Headers = { protoHeaders },
                        Rows = { protoRows }
                    }
                }
            });

        return response;
    }
}

cryptoReplaceFfxFpeConfig

如果把 cryptoReplaceFfxFpeConfig 设置为 CryptoReplaceFfxFpeConfig 对象，可通过将输入值替换为令牌来对输入值执行假名化。此令牌具有如下特点：

• 已加密输入值。
• 与输入值长度相同。
• 在 FFX 模式（“FPE-FFX”）下通过保留格式加密计算得出，该模式按 cryptoKey 指定的加密密钥进行加密。
• 由 alphabet 指定的字符组成。有效选项包括：
  • NUMERIC
  • HEXADECIMAL
  • UPPER_CASE_ALPHA_NUMERIC
  • ALPHA_NUMERIC

输入值需满足以下条件：

• 必须至少具有两个字符（或为空字符串）。
• 必须由 alphabet 指定的字符组成。alphabet 可以包含 2 到 95 个字符。（有 95 个字符的 alphabet 包含 US-ASCII 字符集中的所有可打印字符。）

敏感数据保护功能使用加密密钥计算替换令牌。您可通过下述三种方式之一提供此密钥：

• 将其嵌入 API 请求但不加密。不过，我们不建议您这样做。
• 请求 Sensitive Data Protection 生成该密钥。
• 将其嵌入 API 请求并加密。

如果您选择将密钥嵌入 API 请求中，则需要使用 Cloud Key Management Service (Cloud KMS) 密钥创建密钥并对其进行封装（加密）。返回的值默认为一个 base64 编码的字符串。如需在敏感数据保护中设置此值，必须将其解码为字节字符串。以下代码段重点介绍了如何使用多种语言执行此操作。 在这些代码段之后，还提供了端到端示例。

Java

KmsWrappedCryptoKey.newBuilder()
    .setWrappedKey(ByteString.copyFrom(BaseEncoding.base64().decode(wrappedKey)))

Python

# The wrapped key is base64-encoded, but the library expects a binary
# string, so decode it here.
import base64
wrapped_key = base64.b64decode(wrapped_key)

PHP

// Create the wrapped crypto key configuration object
$kmsWrappedCryptoKey = (new KmsWrappedCryptoKey())
    ->setWrappedKey(base64_decode($wrappedKey))
    ->setCryptoKeyName($keyName);

C#

WrappedKey = ByteString.FromBase64(wrappedKey)

如需详细了解如何使用 Cloud KMS 加密和解密数据，请参阅加密和解密数据。

注意：使用 Cloud KMS 执行加密操作时，您需要支付费用。此外，使用 Cloud HSM 密钥或 Cloud EKM 密钥时，您会使用包含相应密钥的项目的 Cloud KMS 配额。相反，如果您将软件 Cloud KMS 密钥与敏感数据保护功能搭配使用，则不会应用任何配额值。如需了解详情，请参阅 Cloud KMS 文档中的配额。

根据设计，FPE-FFX 会保留输入文本的长度和字符集。这意味着它缺少身份验证和初始化矢量，这会导致输出令牌的长度扩展。其他方法（例如 AES-SIV）可以提供更强大的安全保证，建议用于令牌化用例，除非严格要求保留长度和字符集（例如，用于与旧版数据系统的向后兼容性）。

下面是多种语言的示例代码，演示了如何使用敏感数据保护功能将输入值替换为令牌，对敏感数据进行去标识化。

重要提示： 此页面上的代码要求您首先设置 Sensitive Data Protection 客户端。如需详细了解如何安装和创建敏感数据保护客户端，请参阅 敏感数据保护客户端库。（无需客户端库即可将 JSON 发送到敏感数据保护 REST 端点。）

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.common.io.BaseEncoding;
import com.google.privacy.dlp.v2.ContentItem;
import com.google.privacy.dlp.v2.CryptoKey;
import com.google.privacy.dlp.v2.CryptoReplaceFfxFpeConfig;
import com.google.privacy.dlp.v2.CryptoReplaceFfxFpeConfig.FfxCommonNativeAlphabet;
import com.google.privacy.dlp.v2.DeidentifyConfig;
import com.google.privacy.dlp.v2.DeidentifyContentRequest;
import com.google.privacy.dlp.v2.DeidentifyContentResponse;
import com.google.privacy.dlp.v2.InfoType;
import com.google.privacy.dlp.v2.InfoTypeTransformations;
import com.google.privacy.dlp.v2.InfoTypeTransformations.InfoTypeTransformation;
import com.google.privacy.dlp.v2.InspectConfig;
import com.google.privacy.dlp.v2.KmsWrappedCryptoKey;
import com.google.privacy.dlp.v2.LocationName;
import com.google.privacy.dlp.v2.PrimitiveTransformation;
import com.google.protobuf.ByteString;
import java.io.IOException;
import java.util.Arrays;

public class DeIdentifyWithFpe {

  public static void main(String[] args) throws Exception {
    // TODO(developer): Replace these variables before running the sample.
    String projectId = "your-project-id";
    String textToDeIdentify = "I'm Gary and my SSN is 552096781";
    String kmsKeyName =
        "projects/YOUR_PROJECT/"
            + "locations/YOUR_KEYRING_REGION/"
            + "keyRings/YOUR_KEYRING_NAME/"
            + "cryptoKeys/YOUR_KEY_NAME";
    String wrappedAesKey = "YOUR_ENCRYPTED_AES_256_KEY";
    deIdentifyWithFpe(projectId, textToDeIdentify, kmsKeyName, wrappedAesKey);
  }

  public static void deIdentifyWithFpe(
      String projectId, String textToDeIdentify, String kmsKeyName, String wrappedAesKey)
      throws IOException {
    // Initialize client that will be used to send requests. This client only needs to be created
    // once, and can be reused for multiple requests. After completing all of your requests, call
    // the "close" method on the client to safely clean up any remaining background resources.
    try (DlpServiceClient dlp = DlpServiceClient.create()) {
      // Specify what content you want the service to DeIdentify
      ContentItem contentItem = ContentItem.newBuilder().setValue(textToDeIdentify).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
      InfoType infoType = InfoType.newBuilder().setName("US_SOCIAL_SECURITY_NUMBER").build();
      InspectConfig inspectConfig =
          InspectConfig.newBuilder().addAllInfoTypes(Arrays.asList(infoType)).build();

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

      // Specify how the info from the inspection should be encrypted.
      InfoType surrogateInfoType = InfoType.newBuilder().setName("SSN_TOKEN").build();
      CryptoReplaceFfxFpeConfig cryptoReplaceFfxFpeConfig =
          CryptoReplaceFfxFpeConfig.newBuilder()
              .setCryptoKey(cryptoKey)
              // Set of characters in the input text. For more info, see
              // https://cloud.google.com/dlp/docs/reference/rest/v2/organizations.deidentifyTemplates#DeidentifyTemplate.FfxCommonNativeAlphabet
              .setCommonAlphabet(FfxCommonNativeAlphabet.NUMERIC)
              .setSurrogateInfoType(surrogateInfoType)
              .build();
      PrimitiveTransformation primitiveTransformation =
          PrimitiveTransformation.newBuilder()
              .setCryptoReplaceFfxFpeConfig(cryptoReplaceFfxFpeConfig)
              .build();
      InfoTypeTransformation infoTypeTransformation =
          InfoTypeTransformation.newBuilder()
              .setPrimitiveTransformation(primitiveTransformation)
              .build();
      InfoTypeTransformations transformations =
          InfoTypeTransformations.newBuilder().addTransformations(infoTypeTransformation).build();

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

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

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

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

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 deidentify
// const string = 'My SSN is 372819127';

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

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

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

// (Optional) The name of the surrogate custom info type to use
// Only necessary if you want to reverse the deidentification process
// Can be essentially any arbitrary string, as long as it doesn't appear
// in your dataset otherwise.
// const surrogateType = 'SOME_INFO_TYPE_DEID';

async function deidentifyWithFpe() {
  // Construct FPE config
  const cryptoReplaceFfxFpeConfig = {
    cryptoKey: {
      kmsWrapped: {
        wrappedKey: wrappedKey,
        cryptoKeyName: keyName,
      },
    },
    commonAlphabet: alphabet,
  };
  if (surrogateType) {
    cryptoReplaceFfxFpeConfig.surrogateInfoType = {
      name: surrogateType,
    };
  }

  // Construct deidentification request
  const item = {value: string};
  const request = {
    parent: `projects/${projectId}/locations/global`,
    deidentifyConfig: {
      infoTypeTransformations: {
        transformations: [
          {
            primitiveTransformation: {
              cryptoReplaceFfxFpeConfig: cryptoReplaceFfxFpeConfig,
            },
          },
        ],
      },
    },
    item: item,
  };

  // Run deidentification request
  const [response] = await dlp.deidentifyContent(request);
  const deidentifiedItem = response.item;
  console.log(deidentifiedItem.value);
}
deidentifyWithFpe();

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 base64
from typing import List

import google.cloud.dlp


def deidentify_with_fpe(
    project: str,
    input_str: str,
    info_types: List[str],
    alphabet: str = None,
    surrogate_type: str = None,
    key_name: str = None,
    wrapped_key: str = None,
) -> None:
    """Uses the Data Loss Prevention API to deidentify sensitive data in a
    string using Format Preserving Encryption (FPE).
    Args:
        project: The Google Cloud project id to use as a parent resource.
        input_str: The string to deidentify (will be treated as text).
        info_types: A list of strings representing info types to look for.
        alphabet: The set of characters to replace sensitive ones with. For
            more information, see https://cloud.google.com/dlp/docs/reference/
            rest/v2beta2/organizations.deidentifyTemplates#ffxcommonnativealphabet
        surrogate_type: The name of the surrogate custom info type to use. Only
            necessary if you want to reverse the deidentification process. Can
            be essentially any arbitrary string, as long as it doesn't appear
            in your dataset otherwise.
        key_name: The name of the Cloud KMS key used to encrypt ('wrap') the
            AES-256 key. Example:
            key_name = 'projects/YOUR_GCLOUD_PROJECT/locations/YOUR_LOCATION/
            keyRings/YOUR_KEYRING_NAME/cryptoKeys/YOUR_KEY_NAME'
        wrapped_key: The encrypted ('wrapped') AES-256 key to use. This key
            should be encrypted using the Cloud KMS key specified by key_name.
    Returns:
        None; the response from the API is printed to the terminal.
    """

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

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

    # The wrapped key is base64-encoded, but the library expects a binary
    # string, so decode it here.
    wrapped_key = base64.b64decode(wrapped_key)

    # Construct FPE configuration dictionary
    crypto_replace_ffx_fpe_config = {
        "crypto_key": {
            "kms_wrapped": {"wrapped_key": wrapped_key, "crypto_key_name": key_name}
        },
        "common_alphabet": alphabet,
    }

    # Add surrogate type
    if surrogate_type:
        crypto_replace_ffx_fpe_config["surrogate_info_type"] = {"name": surrogate_type}

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

    # Construct deidentify configuration dictionary
    deidentify_config = {
        "info_type_transformations": {
            "transformations": [
                {
                    "primitive_transformation": {
                        "crypto_replace_ffx_fpe_config": crypto_replace_ffx_fpe_config
                    }
                }
            ]
        }
    }

    # Convert string to item
    item = {"value": input_str}

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

    # Print results
    print(response.item.value)

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"
	"encoding/base64"
	"fmt"
	"io"

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

// deidentifyFPE deidentifies the input with FPE (Format Preserving Encryption).
// keyFileName is the file name with the KMS wrapped key and cryptoKeyName is the
// full KMS key resource name used to wrap the key. surrogateInfoType is an
// optional identifier needed for reidentification. surrogateInfoType can be any
// value not found in your input.
// Info types can be found with the infoTypes.list method or on https://cloud.google.com/dlp/docs/infotypes-reference
func deidentifyFPE(w io.Writer, projectID, input string, infoTypeNames []string, kmsKeyName, wrappedAESKey, surrogateInfoType string) error {
	// projectID := "my-project-id"
	// input := "My SSN is 123456789"
	// infoTypeNames := []string{"US_SOCIAL_SECURITY_NUMBER"}
	// kmsKeyName := "projects/YOUR_GCLOUD_PROJECT/locations/YOUR_LOCATION/keyRings/YOUR_KEYRING_NAME/cryptoKeys/YOUR_KEY_NAME"
	// wrappedAESKey := "YOUR_ENCRYPTED_AES_256_KEY"
	// surrogateInfoType := "AGE"
	ctx := context.Background()
	client, err := dlp.NewClient(ctx)
	if err != nil {
		return fmt.Errorf("dlp.NewClient: %w", err)
	}
	defer client.Close()
	// Convert the info type strings to a list of InfoTypes.
	var infoTypes []*dlppb.InfoType
	for _, it := range infoTypeNames {
		infoTypes = append(infoTypes, &dlppb.InfoType{Name: it})
	}

	// Specify an encrypted AES-256 key and the name of the Cloud KMS key that encrypted it.
	kmsWrappedCryptoKey, err := base64.StdEncoding.DecodeString(wrappedAESKey)
	if err != nil {
		return err
	}

	// Create a configured request.
	req := &dlppb.DeidentifyContentRequest{
		Parent: fmt.Sprintf("projects/%s/locations/global", projectID),
		InspectConfig: &dlppb.InspectConfig{
			InfoTypes: infoTypes,
		},
		DeidentifyConfig: &dlppb.DeidentifyConfig{
			Transformation: &dlppb.DeidentifyConfig_InfoTypeTransformations{
				InfoTypeTransformations: &dlppb.InfoTypeTransformations{
					Transformations: []*dlppb.InfoTypeTransformations_InfoTypeTransformation{
						{
							InfoTypes: []*dlppb.InfoType{}, // Match all info types.
							PrimitiveTransformation: &dlppb.PrimitiveTransformation{
								Transformation: &dlppb.PrimitiveTransformation_CryptoReplaceFfxFpeConfig{
									CryptoReplaceFfxFpeConfig: &dlppb.CryptoReplaceFfxFpeConfig{
										CryptoKey: &dlppb.CryptoKey{
											Source: &dlppb.CryptoKey_KmsWrapped{
												KmsWrapped: &dlppb.KmsWrappedCryptoKey{
													WrappedKey:    kmsWrappedCryptoKey,
													CryptoKeyName: kmsKeyName,
												},
											},
										},
										// Set the alphabet used for the output.
										Alphabet: &dlppb.CryptoReplaceFfxFpeConfig_CommonAlphabet{
											CommonAlphabet: dlppb.CryptoReplaceFfxFpeConfig_ALPHA_NUMERIC,
										},
										// Set the surrogate info type, used for reidentification.
										SurrogateInfoType: &dlppb.InfoType{
											Name: surrogateInfoType,
										},
									},
								},
							},
						},
					},
				},
			},
		},
		// The item to analyze.
		Item: &dlppb.ContentItem{
			DataItem: &dlppb.ContentItem_Value{
				Value: input,
			},
		},
	}
	// Send the request.
	r, err := client.DeidentifyContent(ctx, req)
	if err != nil {
		return fmt.Errorf("DeidentifyContent: %w", err)
	}
	// Print the result.
	fmt.Fprint(w, r.GetItem().GetValue())
	return nil
}

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\CryptoKey;
use Google\Cloud\Dlp\V2\CryptoReplaceFfxFpeConfig;
use Google\Cloud\Dlp\V2\CryptoReplaceFfxFpeConfig\FfxCommonNativeAlphabet;
use Google\Cloud\Dlp\V2\DeidentifyConfig;
use Google\Cloud\Dlp\V2\DeidentifyContentRequest;
use Google\Cloud\Dlp\V2\InfoType;
use Google\Cloud\Dlp\V2\InfoTypeTransformations;
use Google\Cloud\Dlp\V2\InfoTypeTransformations\InfoTypeTransformation;
use Google\Cloud\Dlp\V2\KmsWrappedCryptoKey;
use Google\Cloud\Dlp\V2\PrimitiveTransformation;

/**
 * Deidentify a string using Format-Preserving Encryption (FPE).
 *
 * @param string $callingProjectId  The GCP Project ID to run the API call under
 * @param string $string            The string to deidentify
 * @param string $keyName           The name of the Cloud KMS key used to encrypt (wrap) the AES-256 key
 * @param string $wrappedKey        The name of the Cloud KMS key use, encrypted with the KMS key in $keyName
 * @param string $surrogateTypeName (Optional) surrogate custom info type to enable reidentification
 */
function deidentify_fpe(
    string $callingProjectId,
    string $string,
    string $keyName,
    string $wrappedKey,
    string $surrogateTypeName = ''
): void {
    // Instantiate a client.
    $dlp = new DlpServiceClient();

    // The infoTypes of information to mask
    $ssnInfoType = (new InfoType())
        ->setName('US_SOCIAL_SECURITY_NUMBER');
    $infoTypes = [$ssnInfoType];

    // Create the wrapped crypto key configuration object
    $kmsWrappedCryptoKey = (new KmsWrappedCryptoKey())
        ->setWrappedKey(base64_decode($wrappedKey))
        ->setCryptoKeyName($keyName);

    // The set of characters to replace sensitive ones with
    // For more information, see https://cloud.google.com/dlp/docs/reference/rest/V2/organizations.deidentifyTemplates#ffxcommonnativealphabet
    $commonAlphabet = FfxCommonNativeAlphabet::NUMERIC;

    // Create the crypto key configuration object
    $cryptoKey = (new CryptoKey())
        ->setKmsWrapped($kmsWrappedCryptoKey);

    // Create the crypto FFX FPE configuration object
    $cryptoReplaceFfxFpeConfig = (new CryptoReplaceFfxFpeConfig())
        ->setCryptoKey($cryptoKey)
        ->setCommonAlphabet($commonAlphabet);

    if ($surrogateTypeName) {
        $surrogateType = (new InfoType())
            ->setName($surrogateTypeName);
        $cryptoReplaceFfxFpeConfig->setSurrogateInfoType($surrogateType);
    }

    // Create the information transform configuration objects
    $primitiveTransformation = (new PrimitiveTransformation())
        ->setCryptoReplaceFfxFpeConfig($cryptoReplaceFfxFpeConfig);

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

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

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

    $content = (new ContentItem())
        ->setValue($string);

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

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

    // Print the results
    $deidentifiedValue = $response->getItem()->getValue();
    print($deidentifiedValue);
}

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

public class DeidentifyWithFpe
{
    public static DeidentifyContentResponse Deidentify(
        string projectId,
        string dataValue,
        IEnumerable<InfoType> infoTypes,
        string keyName,
        string wrappedKey,
        FfxCommonNativeAlphabet alphabet)
    {
        var deidentifyConfig = new DeidentifyConfig
        {
            InfoTypeTransformations = new InfoTypeTransformations
            {
                Transformations =
                {
                    new InfoTypeTransformations.Types.InfoTypeTransformation
                    {
                        PrimitiveTransformation = new PrimitiveTransformation
                        {
                            CryptoReplaceFfxFpeConfig = new CryptoReplaceFfxFpeConfig
                            {
                                CommonAlphabet = alphabet,
                                CryptoKey = new CryptoKey
                                {
                                    KmsWrapped = new KmsWrappedCryptoKey
                                    {
                                        CryptoKeyName = keyName,
                                        WrappedKey = ByteString.FromBase64 (wrappedKey)
                                    }
                                },
                                SurrogateInfoType = new InfoType
                                {
                                    Name = "TOKEN"
                                }
                            }
                        }
                    }
                }
            }
        };

        var dlp = DlpServiceClient.Create();
        var response = dlp.DeidentifyContent(
            new DeidentifyContentRequest
            {
                Parent = new LocationName(projectId, "global").ToString(),
                InspectConfig = new InspectConfig
                {
                    InfoTypes = { infoTypes }
                },
                DeidentifyConfig = deidentifyConfig,
                Item = new ContentItem { Value = dataValue }
            });

        Console.WriteLine($"Deidentified content: {response.Item.Value}");
        return response;
    }
}

如需查看演示如何使用 Sensitive Data Protection 重新识别通过 CryptoReplaceFfxFpeConfig 转换方法去标识化的敏感数据的代码示例，请参阅保留格式加密：重新识别示例。

fixedSizeBucketingConfig

分桶转换（即此转换和 bucketingConfig）通过将数值数据“分桶”到不同范围，对其进行遮盖。生成的数字范围是一个带连字符的字符串，由下限、连字符和上限组成。

如果把 fixedSizeBucketingConfig 设置为 FixedSizeBucketingConfig 对象，将根据固定大小范围对输入值进行分桶。FixedSizeBucketingConfig 对象包含以下内容：

• lowerBound：所有分桶的下限值。小于此下限的值都将全部分组到一个分桶中。
• upperBound：所有分桶的上限值。大于此上限的值都将全部分组到一个分桶中。
• bucketSize：每个分桶的大小（最小和最大分桶除外）。

例如，如果 lowerBound 设置为 10，upperBound 设置为 89，bucketSize 设置为 10，则将使用以下分桶：-10、10-20、20-30、30-40、40-50、50-60、60-70、70-80、80-89、89+。

要详细了解分桶的概念，请参阅泛化和分桶。

bucketingConfig

bucketingConfig 转换比另一种分桶转换（即 fixedSizeBucketingConfig）更为灵活。取代指定上限值、下限值和用于创建等大分桶的间隔值，您为此转换要创建的每个分桶指定最大值和最小值。每个最大值和最小值对必须具有相同类型。

将 bucketingConfig 设置为 BucketingConfig 对象即可指定自定义分桶。BucketingConfig 对象由 Bucket 对象的buckets[] 数组构成。每个 Bucket 对象都包含以下内容：

• min：分桶范围的下限。省略此值可创建没有下限的分桶。
• max：分桶范围的上限。省略此值可创建没有上限的分桶。
• replacementValue：该值用于替换介于下限与上限之间的值。如果您未提供 replacementValue，则系统会改用带连字符的 min-max 范围。

如果某个值不在所定义的范围内，返回的 TransformationSummary 将包含错误消息。

例如，请考虑在 bucketingConfig 转换中使用以下配置：

"bucketingConfig":{
  "buckets":[
    {
      "min":{
        "integerValue":"1"
      },
      "max":{
        "integerValue":"30"
      },
      "replacementValue":{
        "stringValue":"LOW"
      }
    },
    {
      "min":{
        "integerValue":"31"
      },
      "max":{
        "integerValue":"65"
      },
      "replacementValue":{
        "stringValue":"MEDIUM"
      }
    },
    {
      "min":{
        "integerValue":"66"
      },
      "max":{
        "integerValue":"100"
      },
      "replacementValue":{
        "stringValue":"HIGH"
      }
    }
  ]
}

这会定义以下行为：

• 遮盖 1 至 30 的整数值的方式是将它们替换为 LOW。
• 遮盖 31 至 65 的整数值的方式是将它们替换为 MEDIUM。
• 66 至 100 之间的整数值替换为 HIGH，从而进行遮罩。

要详细了解分桶的概念，请参阅泛化和分桶。

replaceWithInfoTypeConfig

如果指定 replaceWithInfoTypeConfig，就会将每个匹配的值都替换为 infoType 的名称。replaceWithInfoTypeConfig 消息不带参数，指定它就会启用该转换。

例如，假设您已为所有 EMAIL_ADDRESS infoType 指定 replaceWithInfoTypeConfig，且已将下列字符串发送到敏感数据保护：

My name is Alicia Abernathy, and my email address is [e-mail].

返回的字符串如下：

My name is Alicia Abernathy, and my email address is EMAIL_ADDRESS.

timePartConfig

如果把 timePartConfig 设置为 TimePartConfig 对象，将保留包含 Date、Timestamp 和 TimeOfDay 值的匹配值的一部分。TimePartConfig 对象包含一个 partToExtract 参数，后者可设置为年、月、日等任意 TimePart 枚举值。

例如，假设您已通过将 partToExtract 设置为 YEAR 来配置 timePartConfig 转换。在将下述第一列中的数据发送到敏感数据保护之后，最终将获得第二列中显示的转换后的值：

原始值	转换后的值
9/21/1976	1976
6/7/1945	1945
1/20/2009	2009
7/4/1776	1776
8/1/1984	1984
4/21/1982	1982

记录转换

记录转换（RecordTransformations 对象）仅应用于表格数据中被识别为特定 infoType 的值。在 RecordTransformations 中，还可将转换细分成两个子类别：

• fieldTransformations[]：应用各种字段转换的转换。
• recordSuppressions[]：用于定义完全隐藏哪些记录的规则。输出中不显示与 recordSuppressions[] 中任何隐藏规则相匹配的记录。

注意 ：如果您想在 content.deidentify 调用中使用 RecordTransformations 配置，请确保 item 字段的值为 Table 类型。

字段转换

每个 FieldTransformation 对象都包含三个参数：

• fields：需要应用转换的一个或多个输入字段（FieldID 对象）。
• condition：计算结果必须为 true 才能应用转换的条件（RecordCondition 对象）。例如，仅当记录的邮编列是在特定范围内时，才向该记录的年龄列应用分桶转换。或者，仅当出生日期字段表明某人的年龄为 85 岁或以上时，才隐去字段。

• 下列两个转换类型参数之一。需要指定任一项：

  • infoTypeTransformations：将字段内容视为自由文本，且仅将 PrimitiveTransformation 应用于与 InfoType 匹配的内容。如需了解这些转换，请参见本主题前面的内容。

  • primitiveTransformation：将指定的初始转换（PrimitiveTransformation 对象）应用于整个字段。如需了解这些转换，请参见本主题前面的内容。

    如果您的 RecordTransformations 对象仅包含 primitiveTransformation 而没有 infoTypeTransformations，则您无需在请求中添加 InspectConfig 对象。如果您这样做，Sensitive Data Protection 会忽略它。

字段转换示例

以下示例会发送一个包含两个字段转换的 projects.content.deidentify 请求：

• 第一个字段转换应用于前两个列（column1 和 column2）。由于其转换类型为 primitiveTransformation 对象（具体为 CryptoDeterministicConfig），因此 Sensitive Data Protection 会转换整个字段。

  警告 ：为演示目的，此示例使用了未封装的密钥。请勿将此密钥用于实际的敏感工作负载。Google 建议您改用封装的密钥。如需详细了解如何创建封装密钥并在去标识化和重标识请求中使用它，请参阅对敏感数据进行去标识化和重标识。

• 第二个字段转换应用于第三列 (column3)。由于其转换类型为 infoTypeTransformations 对象，因此敏感数据保护功能仅会将基元转换（具体而言，是 ReplaceWithInfoTypeConfig）应用于与检查配置中设置的 infoType 匹配的内容。

在使用任何请求数据之前，请先进行以下替换：

• PROJECT_ID：您的 Google Cloud 项目 ID。 项目 ID 是字母数字字符串，例如 my-project。

HTTP 方法和网址：

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

请求 JSON 正文：

{
  "item": {
    "table": {
      "headers": [
        {
          "name": "column1"
        },
        {
          "name": "column2"
        },
        {
          "name": "column3"
        }
      ],
      "rows": [
        {
          "values": [
            {
              "stringValue": "Example string 1"
            },
            {
              "stringValue": "Example string 2"
            },
            {
              "stringValue": "My email address is [e-mail]"
            }
          ]
        },
        {
          "values": [
            {
              "stringValue": "Example string 1"
            },
            {
              "stringValue": "Example string 3"
            },
            {
              "stringValue": "My email address is [e-mail]"
            }
          ]
        }
      ]
    }
  },
  "deidentifyConfig": {
    "recordTransformations": {
      "fieldTransformations": [
        {
          "fields": [
            {
              "name": "column1"
            },
            {
              "name": "column2"
            }
          ],
          "primitiveTransformation": {
            "cryptoDeterministicConfig": {
              "cryptoKey": {
                "unwrapped": {
                  "key": "YWJjZGVmZ2hpamtsbW5vcA=="
                }
              }
            }
          }
        },
        {
          "fields": [
            {
              "name": "column3"
            }
          ],
          "infoTypeTransformations": {
            "transformations": [
              {
                "primitiveTransformation": {
                  "replaceWithInfoTypeConfig": {}
                }
              }
            ]
          }
        }
      ]
    }
  },
  "inspectConfig": {
    "infoTypes": [
      {
        "name": "EMAIL_ADDRESS"
      }
    ]
  }
}

如需发送您的请求，请展开以下选项之一：

curl（Linux、macOS 或 Cloud Shell）

注意：以下命令假定您已使用您的用户账号通过运行 gcloud init 或 gcloud auth login 登录 gcloud CLI，或者使用了 Cloud Shell，这会使您自动登录 gcloud CLI。您可以运行 gcloud auth list 来检查当前活跃的账号。

将请求正文保存在名为 deidentify-tabular-content-request.json 的文件中，然后执行以下命令：

curl -X POST \
     -H "Authorization: Bearer $(gcloud auth print-access-token)" \
     -H "x-goog-user-project: PROJECT_ID" \
     -H "Content-Type: application/json; charset=utf-8" \
     -d @deidentify-tabular-content-request.json \
     "https://dlp.googleapis.com/v2/projects/PROJECT_ID/content:deidentify"

PowerShell (Windows)

注意：以下命令假定您已使用您的用户账号通过运行 gcloud init 或 gcloud auth login 登录 gcloud CLI。您可以运行 gcloud auth list 来检查当前活跃的账号。

将请求正文保存在名为 deidentify-tabular-content-request.json 的文件中，然后执行以下命令：

$cred = gcloud auth print-access-token
$headers = @{ "Authorization" = "Bearer $cred"; "x-goog-user-project" = "PROJECT_ID" }

Invoke-WebRequest `
    -Method POST `
    -Headers $headers `
    -ContentType: "application/json; charset=utf-8" `
    -InFile deidentify-tabular-content-request.json `
    -Uri "https://dlp.googleapis.com/v2/projects/PROJECT_ID/content:deidentify" | Select-Object -Expand Content

您应该收到类似以下内容的 JSON 响应：

{
  "item": {
    "table": {
      "headers": [
        {
          "name": "column1"
        },
        {
          "name": "column2"
        },
        {
          "name": "column3"
        }
      ],
      "rows": [
        {
          "values": [
            {
              "stringValue": "AWttmGlln6Z2MFOMqcOzDdNJS52XFxOOZsg0ckDeZzfc"
            },
            {
              "stringValue": "AUBTE+sQB6eKZ5iD3Y0Ss682zANXbijuFl9KL9ExVOTF"
            },
            {
              "stringValue": "My email address is [EMAIL_ADDRESS]"
            }
          ]
        },
        {
          "values": [
            {
              "stringValue": "AWttmGlln6Z2MFOMqcOzDdNJS52XFxOOZsg0ckDeZzfc"
            },
            {
              "stringValue": "AU+oD2pnqUDTLNItE8RplY3E0fTHeO4rZkX4GeFHN2CI"
            },
            {
              "stringValue": "My email address is [EMAIL_ADDRESS]"
            }
          ]
        }
      ]
    }
  },
  "overview": {
    "transformedBytes": "96",
    "transformationSummaries": [
      {
        "field": {
          "name": "column1"
        },
        "results": [
          {
            "count": "2",
            "code": "SUCCESS"
          }
        ],
        "fieldTransformations": [
          {
            "fields": [
              {
                "name": "column1"
              },
              {
                "name": "column2"
              }
            ],
            "primitiveTransformation": {
              "cryptoDeterministicConfig": {
                "cryptoKey": {
                  "unwrapped": {
                    "key": "YWJjZGVmZ2hpamtsbW5vcA=="
                  }
                }
              }
            }
          }
        ],
        "transformedBytes": "32"
      },
      {
        "field": {
          "name": "column2"
        },
        "results": [
          {
            "count": "2",
            "code": "SUCCESS"
          }
        ],
        "fieldTransformations": [
          {
            "fields": [
              {
                "name": "column1"
              },
              {
                "name": "column2"
              }
            ],
            "primitiveTransformation": {
              "cryptoDeterministicConfig": {
                "cryptoKey": {
                  "unwrapped": {
                    "key": "YWJjZGVmZ2hpamtsbW5vcA=="
                  }
                }
              }
            }
          }
        ],
        "transformedBytes": "32"
      },
      {
        "infoType": {
          "name": "EMAIL_ADDRESS",
          "sensitivityScore": {
            "score": "SENSITIVITY_MODERATE"
          }
        },
        "field": {
          "name": "column3"
        },
        "results": [
          {
            "count": "2",
            "code": "SUCCESS"
          }
        ],
        "fieldTransformations": [
          {
            "fields": [
              {
                "name": "column3"
              }
            ],
            "infoTypeTransformations": {
              "transformations": [
                {
                  "primitiveTransformation": {
                    "replaceWithInfoTypeConfig": {}
                  }
                }
              ]
            }
          }
        ],
        "transformedBytes": "32"
      }
    ]
  }
}

记录隐藏

除了向字段数据应用转换，您还能指示 Sensitive Data Protection 在数据的特定禁止条件评估结果为 true 时禁止记录，从而实现去标识化。您可在同一请求中同时应用字段转换和记录隐藏。

您需要将 RecordTransformations 对象的 recordSuppressions 消息设置为一个或多个 RecordSuppression 对象的数组。

每个 RecordSuppression 对象都包含一个 RecordCondition 对象，后者又包含一个 Expressions 对象。

Expressions 对象包含以下内容：

• logicalOperator：LogicalOperator 枚举类型之一。
• conditions：一个 Conditions 对象，其中有一个包含一个或多个 Condition 对象的数组。Condition 是一个字段值和另一个值的比较，两者类型为 string、boolean、integer、double、Timestamp 或 TimeofDay。

如果比较结果为 true，将隐藏记录；反之则不隐藏。 如果比较的值类型不同，将发出警告，同时条件计算结果为 false。

可逆转的转换

使用 CryptoReplaceFfxFpeConfig 或 CryptoDeterministicConfig infoType 转换对数据进行去标识化后，只要您拥有最初对数据进行去标识化所用的 CryptoKey，就可以重新标识数据。如需了解详情，请参阅基于加密的令牌化转换。

发现结果数量限制

如果您的请求有超过 3,000 项发现结果，敏感数据保护功能会返回以下消息：

Too many findings to de-identify. Retry with a smaller request.

敏感数据保护功能返回的发现结果列表是请求中所有发现结果的任意子集。如需获取所有发现，请将请求拆分为更小的批次。

后续步骤

• 详细了解去标识化工作流如何在实际部署中发挥作用。

• 完成 Redacting Sensitive Data with Sensitive Data Protection Codelab。

• 完成演示如何创建封装的密钥、对内容进行令牌化和重标识令牌化内容的示例。

• 详细了解如何在存储空间中创建去标识化的数据副本。