Cloud Data Loss Prevention (Cloud DLP) 現已併入機密資料保護。API 名稱維持不變：Cloud Data Loss Prevention API (DLP API)。如要瞭解構成 Sensitive Data Protection 的服務，請參閱「Sensitive Data Protection 總覽」。

Google 會運用 AI 技術將內容翻譯成你偏好的語言，但可能會出錯。

將機密資料去識別化

Sensitive Data Protection 可以將文字內容中的機密資料去識別化，包括儲存在資料表等容器結構中的文字。去識別化是從資料移除個人識別資訊的程序。API 會偵測個人識別資訊 (PII) 等機密資料，然後使用去識別化轉換來遮蔽、刪除或隱藏資料。舉例來說，去識別化技術可包含以下任何一種：

將部分或所有字元替換為星號 (*) 或井字號 (#) 等符號，遮蓋機密資料。
將每個機密資料例項替換為權杖或代理字串。
使用隨機產生或預先決定的金鑰來加密和取代機密資料。

您可以透過 HTTPS 使用 JSON，以及使用 Sensitive Data Protection 用戶端程式庫，透過 CLI 和多種程式設計語言，將資訊提供給 API。如要設定 CLI，請參閱快速入門導覽課程。如要進一步瞭解如何以 JSON 格式提交資訊，請參閱 JSON 快速入門導覽課程。

API 總覽

如要將機密資料去識別化，請使用 Sensitive Data Protection 的 content.deidentify 方法。

去識別化 API 呼叫作業包含三個部分：

要檢查的資料：API 要檢查的字串或表格結構 (ContentItem 物件)。
檢查項目：偵測設定資訊 (InspectConfig)，例如要尋找的資料類型 (或 infoType)、是否要篩選高於特定可能性門檻的發現項目，以及是否要傳回不超過特定數量的結果。

請務必在 InspectConfig 物件中，加入要掃描的 infoType。否則，Sensitive Data Protection 會掃描一組預設的 infoType (ALL_BASIC)，其中可能包含您不需要的類型。掃描不需要的 infoType 可能會不必要地增加要求延遲時間。

要求中必須包含 InspectConfig 物件，但有一個例外狀況。詳情請參閱本頁的「記錄轉換」一節。
如何處理檢查結果：設定資訊 (DeidentifyConfig)，定義您希望如何將機密資料去識別化。下節將更詳細說明這個引數。

API 會以相同格式傳回您提供的相同項目，但根據您的條件識別為包含機密資訊的任何文字均已去識別化。

指定偵測條件

資訊類型 (或「infoType」) 偵測工具是 Sensitive Data Protection 用來尋找機密資料的機制。

Sensitive Data Protection 包含多種 infoType 偵測工具，以下是所有工具的摘要：

內建 infoType 偵測工具內建於 Sensitive Data Protection。包括國家/地區或區域專屬機密資料類型，以及全球適用的資料類型的偵測工具。
自訂 infoType 偵測工具是您自行建立的偵測工具。自訂 infoType 偵測工具分為三種：
- 一般自訂字典偵測工具是 Sensitive Data Protection 比對的簡單字詞清單。如果您的清單包含多達數萬個字詞或詞組，請使用一般自訂字典偵測工具。如果您的字詞清單不會大幅變動，建議採用一般自訂字典偵測工具。
- 儲存的自訂字典偵測工具是由 Sensitive Data Protection 產生，使用儲存在 Cloud Storage 或 BigQuery 中的大量字詞或詞組清單。字詞或詞組清單龐大 (即高達數千萬個) 時，宜使用儲存的自訂字典偵測工具。
- 規則運算式 (regex) 偵測工具可讓 Sensitive Data Protection 根據規則運算式模式偵測相符項目。

如要修正掃描結果，可以建立檢查規則。

去識別化轉換

設定去識別化設定 (DeidentifyConfig) 時，必須指定一或多項轉換。轉換分為兩類：

InfoTypeTransformations：僅套用至提交文字中特定 infoType 值的轉換。
RecordTransformations：這類轉換只會套用至提交的表格型資料中，經識別為特定 infoType 的值，或套用至整欄表格型資料。

InfoType 轉換

每項要求可以指定一或多項 infoType 轉換。在每個 InfoTypeTransformation 物件中，您必須指定下列兩項：

應套用轉換的一或多個 infoTypes (infoTypes[] 陣列物件)。
原始轉換 (PrimitiveTransformation 物件)。

請注意，指定 infoType 是選用步驟，但如果未在 InspectConfig 引數中指定至少一個 infoType，轉換作業會套用至所有未提供轉換的內建 infoType。我們不建議這麼做，因為這會導致效能下降且成本提高。

原始轉換

無論是僅套用至特定 infoType 或整個文字字串，您都必須指定至少一項要套用至輸入內容的基本轉換。以下各節說明可用的轉換方法範例。如需 Sensitive Data Protection 提供的所有轉換方法清單，請參閱「轉換參考資料」。

replaceConfig

將 replaceConfig 設為 ReplaceValueConfig 物件，即可將相符的輸入值替換為指定值。

舉例來說，假設您已將所有 EMAIL_ADDRESS infoType 的 replaceConfig 設為「[email-address]」，並將下列字串傳送至 Sensitive Data Protection：

My name is Alicia Abernathy, and my email address is aabernathy@example.com.

傳回的字串將顯示以下內容：

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

下列 JSON 範例和多種語言的程式碼，說明如何建立 API 要求，以及 DLP API 傳回的內容：

Python

如要瞭解如何安裝及使用 Sensitive Data Protection 的用戶端程式庫，請參閱「Sensitive Data Protection 用戶端程式庫」。

如要向 Sensitive Data Protection 進行驗證，請設定應用程式預設憑證。詳情請參閱「為本機開發環境設定驗證機制」。

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

如要瞭解如何安裝及使用 Sensitive Data Protection 的用戶端程式庫，請參閱「Sensitive Data Protection 用戶端程式庫」。

如要向 Sensitive Data Protection 進行驗證，請設定應用程式預設憑證。詳情請參閱「為本機開發環境設定驗證機制」。


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 aabernathy@example.com.";
    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

如要進一步瞭解如何透過 JSON 使用 DLP API，請參閱 JSON 快速入門導覽課程。

JSON 輸入：

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 aabernathy@example.com."
  },
  "deidentifyConfig":{
    "infoTypeTransformations":{
      "transformations":[
        {
          "infoTypes":[
            {
              "name":"EMAIL_ADDRESS"
            }
          ],
          "primitiveTransformation":{
            "replaceConfig":{
              "newValue":{
                "stringValue":"[email-address]"
              }
            }
          }
        }
      ]
    }
  },
  "inspectConfig":{
    "infoTypes":[
      {
        "name":"EMAIL_ADDRESS"
      }
    ]
  }
}

JSON 輸出內容：

{
  "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

指定 redactConfig 會完全移除指定的值，藉此遮蓋該值。redactConfig 訊息沒有引數，指定該訊息即可啟用轉換。

舉例來說，假設您為所有 EMAIL_ADDRESS infoType 指定 redactConfig，並將下列字串傳送至 Sensitive Data Protection：

My name is Alicia Abernathy, and my email address is aabernathy@example.com.

傳回的字串將顯示以下內容：

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

以下範例說明如何建立 API 要求，以及 DLP API 傳回的內容：

C#

如要瞭解如何安裝及使用 Sensitive Data Protection 的用戶端程式庫，請參閱「Sensitive Data Protection 用戶端程式庫」。

如要向 Sensitive Data Protection 進行驗證，請設定應用程式預設憑證。詳情請參閱「為本機開發環境設定驗證機制」。


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

如要瞭解如何安裝及使用 Sensitive Data Protection 的用戶端程式庫，請參閱「Sensitive Data Protection 用戶端程式庫」。

如要向 Sensitive Data Protection 進行驗證，請設定應用程式預設憑證。詳情請參閱「為本機開發環境設定驗證機制」。

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 aabernathy@example.com."
	// 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

如要瞭解如何安裝及使用 Sensitive Data Protection 的用戶端程式庫，請參閱「Sensitive Data Protection 用戶端程式庫」。

如要向 Sensitive Data Protection 進行驗證，請設定應用程式預設憑證。詳情請參閱「為本機開發環境設定驗證機制」。


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 aabernathy@example.com.";
    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

如要瞭解如何安裝及使用 Sensitive Data Protection 的用戶端程式庫，請參閱「Sensitive Data Protection 用戶端程式庫」。

如要向 Sensitive Data Protection 進行驗證，請設定應用程式預設憑證。詳情請參閱「為本機開發環境設定驗證機制」。

// 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 aabernathy@example.com.';

// 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

如要瞭解如何安裝及使用 Sensitive Data Protection 的用戶端程式庫，請參閱「Sensitive Data Protection 用戶端程式庫」。

如要向 Sensitive Data Protection 進行驗證，請設定應用程式預設憑證。詳情請參閱「為本機開發環境設定驗證機制」。

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 aabernathy@example.com.'

): 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

如要瞭解如何安裝及使用 Sensitive Data Protection 的用戶端程式庫，請參閱「Sensitive Data Protection 用戶端程式庫」。

如要向 Sensitive Data Protection 進行驗證，請設定應用程式預設憑證。詳情請參閱「為本機開發環境設定驗證機制」。

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 輸入：

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 aabernathy@example.com."
  },
  "deidentifyConfig":{
    "infoTypeTransformations":{
      "transformations":[
        {
          "infoTypes":[
            {
              "name":"EMAIL_ADDRESS"
            }
          ],
          "primitiveTransformation":{
            "redactConfig":{

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

JSON 輸出內容：

{
  "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

將 characterMaskConfig 設為 CharacterMaskConfig 物件，即可將指定數量的字元替換為固定字元，部分遮蓋字串。遮蔽可以從字串的開頭或結尾開始。這種轉換也適用於長整數等數字類型。

CharacterMaskConfig 物件有幾個專屬引數：

maskingCharacter：用於遮蓋機密值中每個字元的字元。舉例來說，您可以指定星號 (*) 或井號 (#) 來遮蔽一系列數字，例如信用卡號碼的數字。
numberToMask：要遮蓋的字元數。如未設定這個值，系統會遮蓋所有相符的字元。
reverseOrder：是否以反向順序遮蓋字元。如果將 reverseOrder 設為 true，系統會從結尾開始遮蓋相符值中的字元，直到開頭為止。如果將該引數設定為 False，會從值的開頭開始進行遮蔽。
charactersToIgnore[]：遮蓋值時要略過的一或多個字元。舉例來說，您可以在這裡指定連字號，在遮蔽電話號碼時，將連字號保留在現有的位置。您也可以指定一組常見字元 (CharsToIgnore)，在遮蓋時忽略這些字元。

舉例來說，假設您已設定 characterMaskConfig，使用「#」遮蓋 EMAIL_ADDRESS 資訊類型，但「.」和「@」字元除外。如果將下列字串傳送至 Sensitive Data Protection：

My name is Alicia Abernathy, and my email address is aabernathy@example.com.

傳回的字串將顯示以下內容：

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

以下範例說明如何使用 DLP API，透過遮蓋技術將機密資料去識別化。

Java

如要瞭解如何安裝及使用 Sensitive Data Protection 的用戶端程式庫，請參閱「Sensitive Data Protection 用戶端程式庫」。

如要向 Sensitive Data Protection 進行驗證，請設定應用程式預設憑證。詳情請參閱「為本機開發環境設定驗證機制」。


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

如要瞭解如何安裝及使用 Sensitive Data Protection 的用戶端程式庫，請參閱「Sensitive Data Protection 用戶端程式庫」。

如要向 Sensitive Data Protection 進行驗證，請設定應用程式預設憑證。詳情請參閱「為本機開發環境設定驗證機制」。

// 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

如要瞭解如何安裝及使用 Sensitive Data Protection 的用戶端程式庫，請參閱「Sensitive Data Protection 用戶端程式庫」。

如要向 Sensitive Data Protection 進行驗證，請設定應用程式預設憑證。詳情請參閱「為本機開發環境設定驗證機制」。

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

如要瞭解如何安裝及使用 Sensitive Data Protection 的用戶端程式庫，請參閱「Sensitive Data Protection 用戶端程式庫」。

如要向 Sensitive Data Protection 進行驗證，請設定應用程式預設憑證。詳情請參閱「為本機開發環境設定驗證機制」。

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

如要瞭解如何安裝及使用 Sensitive Data Protection 的用戶端程式庫，請參閱「Sensitive Data Protection 用戶端程式庫」。

如要向 Sensitive Data Protection 進行驗證，請設定應用程式預設憑證。詳情請參閱「為本機開發環境設定驗證機制」。

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#

如要瞭解如何安裝及使用 Sensitive Data Protection 的用戶端程式庫，請參閱「Sensitive Data Protection 用戶端程式庫」。

如要向 Sensitive Data Protection 進行驗證，請設定應用程式預設憑證。詳情請參閱「為本機開發環境設定驗證機制」。


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

以下 JSON 範例說明如何形成 API 要求，以及 DLP API 傳回的內容：

JSON 輸入：

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 aabernathy@example.com."
  },
  "deidentifyConfig":{
    "infoTypeTransformations":{
      "transformations":[
        {
          "infoTypes":[
            {
              "name":"EMAIL_ADDRESS"
            }
          ],
          "primitiveTransformation":{
            "characterMaskConfig":{
              "maskingCharacter":"#",
              "reverseOrder":false,
              "charactersToIgnore":[
                {
                  "charactersToSkip":".@"
                }
              ]
            }
          }
        }
      ]
    }
  },
  "inspectConfig":{
    "infoTypes":[
      {
        "name":"EMAIL_ADDRESS"
      }
    ]
  }
}

JSON 輸出內容：

{
  "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

將 cryptoHashConfig 設為 CryptoHashConfig 物件，會使用密碼編譯雜湊產生代理值，對輸入值執行假名化。

這個方法會將輸入值替換為加密的「摘要」或雜湊值。摘要是透過輸入值的 SHA-256 雜湊計算而得。用於建立雜湊的加密編譯金鑰是 CryptoKey 物件，大小必須為 32 或 64 個位元組。

這個方法會輸出雜湊輸出的 base64 編碼表示法。目前，您只能對字串與整數值進行雜湊處理。

舉例來說，假設您已為所有 EMAIL_ADDRESS infoType 指定 cryptoHashConfig，且 CryptoKey 物件包含隨機產生的金鑰 (TransientCryptoKey)。接著，系統會將下列字串傳送至 Sensitive Data Protection：

My name is Alicia Abernathy, and my email address is aabernathy@example.com.

以加密編譯形式產生的傳回字串會如下所示：

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

當然，系統會以加密編譯的形式產生十六進位字串，與這裡所示的內容不同。

dateShiftConfig

將 dateShiftConfig 設為 DateShiftConfig 物件，會對日期輸入值執行日期移位，將日期隨機移動幾天。

日期轉移的做法是隨機移動一組日期，但仍保留日期的順序和日期之間的時間長度。日期的轉移通常是依個人或實體來達成。也就是說，您會想要透過相同的轉移差異來轉移特定個人的所有日期，但會對不同個人之間使用的轉移差異加以區隔。

如需進一步瞭解日期轉移，請參閱日期轉移概念主題。

以下是多種語言的程式碼範例，示範如何使用 DLP API 透過日期移位功能對日期進行去識別化。

Java

如要瞭解如何安裝及使用 Sensitive Data Protection 的用戶端程式庫，請參閱「Sensitive Data Protection 用戶端程式庫」。

如要向 Sensitive Data Protection 進行驗證，請設定應用程式預設憑證。詳情請參閱「為本機開發環境設定驗證機制」。


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

如要瞭解如何安裝及使用 Sensitive Data Protection 的用戶端程式庫，請參閱「Sensitive Data Protection 用戶端程式庫」。

如要向 Sensitive Data Protection 進行驗證，請設定應用程式預設憑證。詳情請參閱「為本機開發環境設定驗證機制」。

// 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

如要瞭解如何安裝及使用 Sensitive Data Protection 的用戶端程式庫，請參閱「Sensitive Data Protection 用戶端程式庫」。

如要向 Sensitive Data Protection 進行驗證，請設定應用程式預設憑證。詳情請參閱「為本機開發環境設定驗證機制」。

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

如要瞭解如何安裝及使用 Sensitive Data Protection 的用戶端程式庫，請參閱「Sensitive Data Protection 用戶端程式庫」。

如要向 Sensitive Data Protection 進行驗證，請設定應用程式預設憑證。詳情請參閱「為本機開發環境設定驗證機制」。

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

如要瞭解如何安裝及使用 Sensitive Data Protection 的用戶端程式庫，請參閱「Sensitive Data Protection 用戶端程式庫」。

如要向 Sensitive Data Protection 進行驗證，請設定應用程式預設憑證。詳情請參閱「為本機開發環境設定驗證機制」。

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#

如要瞭解如何安裝及使用 Sensitive Data Protection 的用戶端程式庫，請參閱「Sensitive Data Protection 用戶端程式庫」。

如要向 Sensitive Data Protection 進行驗證，請設定應用程式預設憑證。詳情請參閱「為本機開發環境設定驗證機制」。


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

將 cryptoReplaceFfxFpeConfig 設為 CryptoReplaceFfxFpeConfig 物件，即可將輸入內容替換為權杖，對輸入內容執行匿名化。代碼具有下列特性：

加密的輸入值。
長度與輸入值相同。
使用 FFX 模式中的格式保留加密 (「FPE-FFX」) 計算，並以 cryptoKey 指定的加密編譯金鑰為索引鍵。
由 alphabet 指定的字元組成。有效選項：
- NUMERIC
- HEXADECIMAL
- UPPER_CASE_ALPHA_NUMERIC
- ALPHA_NUMERIC

輸入值具有以下特性：

至少必須要有兩個字元的長度 (或空字串)。
必須由 alphabet 指定的字元組成。alphabet 的長度可介於 2 到 95 個字元之間。(包含 95 個字元的 alphabet 包含 US-ASCII 字元集中的所有可列印字元)。

Sensitive Data Protection 會使用加密編譯金鑰計算替換權杖。您可透過以下三種方式的其中之一提供這個金鑰：

將未加密的金鑰嵌入 API 要求。我們不建議這麼做。
要求 Sensitive Data Protection 生成。
將加密金鑰嵌入 API 要求中。

如果選擇在 API 要求中嵌入金鑰，則必須建立金鑰並使用 Cloud Key Management Service (Cloud KMS) 金鑰包裝 (加密)。根據預設，傳回的值是以 Base64 編碼的字串。如要在 Sensitive Data Protection 中設定這個值，必須將其解碼為位元組字串。下列程式碼片段說明如何以多種語言執行這項操作。這些程式碼片段後方會提供端對端範例。

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)

如要進一步瞭解如何使用 Cloud KMS 加密及解密資料，請參閱加密及解密資料的說明。

FPE-FFX 的設計會保留輸入文字的長度和字元集。這表示它缺少驗證和初始化向量，會導致輸出權杖長度增加。AES-SIV 等其他方法可提供更強大的安全保障，建議用於權杖化用途，除非長度和字元集保留是嚴格要求，例如與舊版資料系統的回溯相容性。

以下是多種語言的程式碼範例，示範如何使用 Sensitive Data Protection，將輸入值替換為權杖，藉此去識別化機密資料。

Java

如要瞭解如何安裝及使用 Sensitive Data Protection 的用戶端程式庫，請參閱「Sensitive Data Protection 用戶端程式庫」。

如要向 Sensitive Data Protection 進行驗證，請設定應用程式預設憑證。詳情請參閱「為本機開發環境設定驗證機制」。


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

如要瞭解如何安裝及使用 Sensitive Data Protection 的用戶端程式庫，請參閱「Sensitive Data Protection 用戶端程式庫」。

如要向 Sensitive Data Protection 進行驗證，請設定應用程式預設憑證。詳情請參閱「為本機開發環境設定驗證機制」。

// 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

如要瞭解如何安裝及使用 Sensitive Data Protection 的用戶端程式庫，請參閱「Sensitive Data Protection 用戶端程式庫」。

如要向 Sensitive Data Protection 進行驗證，請設定應用程式預設憑證。詳情請參閱「為本機開發環境設定驗證機制」。

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

如要瞭解如何安裝及使用 Sensitive Data Protection 的用戶端程式庫，請參閱「Sensitive Data Protection 用戶端程式庫」。

如要向 Sensitive Data Protection 進行驗證，請設定應用程式預設憑證。詳情請參閱「為本機開發環境設定驗證機制」。

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

如要瞭解如何安裝及使用 Sensitive Data Protection 的用戶端程式庫，請參閱「Sensitive Data Protection 用戶端程式庫」。

如要向 Sensitive Data Protection 進行驗證，請設定應用程式預設憑證。詳情請參閱「為本機開發環境設定驗證機制」。

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#

如要瞭解如何安裝及使用 Sensitive Data Protection 的用戶端程式庫，請參閱「Sensitive Data Protection 用戶端程式庫」。

如要向 Sensitive Data Protection 進行驗證，請設定應用程式預設憑證。詳情請參閱「為本機開發環境設定驗證機制」。


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;
    }
}

如需程式碼範例，瞭解如何使用 Sensitive Data Protection 重新識別透過 CryptoReplaceFfxFpeConfig 轉換方法去識別化的機密資料，請參閱「格式保留加密：重新識別範例」。

fixedSizeBucketingConfig

分桶轉換 (包括這項和 bucketingConfig) 會將數值型資料「分桶」到不同範圍，藉此遮蓋資料。產生的數字範圍是以連字符連接的字串，包含下限、連字號和上限。

將 fixedSizeBucketingConfig 設為 FixedSizeBucketingConfig 物件，即可根據固定大小範圍，將輸入值分桶。FixedSizeBucketingConfig 物件包含下列項目：

lowerBound：所有值區的下限值。小於這個值的值會組成單一特徵分塊。
upperBound：所有值區的上限值。大於這個值的值會組成單一特徵分塊。
bucketSize：除了最小和最大值區以外，每個值區的大小。

舉例來說，如果 lowerBound 設為 10、upperBound 設為 89，且 bucketSize 設為 10，則會使用下列值區：-10、10-20、20-30、30-40、40-50、50-60、60-70、70-80、80-89、89+。

如要進一步瞭解特徵分塊的概念，請參閱一般化與特徵分塊一文。

bucketingConfig

bucketingConfig 轉換比其他分桶轉換 (fixedSizeBucketingConfig) 更有彈性。您不必指定上限、下限和間隔值來建立大小相同的值區，而是指定要建立的每個值區的最大值和最小值。每個最大與最小值組合必須具有相同的類型。

將 bucketingConfig 設為 BucketingConfig 物件，即可指定自訂值區。BucketingConfig 物件包含 Bucket 物件的 buckets[] 陣列。每個 Bucket 物件都包含下列項目：

min：值區範圍的下限。省略這個值可建立沒有下限的特徵分塊。
max：值區範圍的上限。省略這個值可建立沒有上限的特徵分塊。
replacementValue：用來取代下限和上限範圍內的值。如未提供 replacementValue，系統會改用以連字號分隔的 min-max 範圍。

如果值超出定義的範圍，傳回的 TransformationSummary 會包含錯誤訊息。

舉例來說，請考慮下列 bucketingConfig 轉換設定：

"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"
      }
    }
  ]
}

這會定義以下行為：

系統會將介於 1 到 30 之間的整數值替換為 LOW 以遮蔽這些值。
系統會將介於 31 到 65 之間的整數值替換為 MEDIUM 以遮蔽這些值。
系統會將介於 66 到 100 之間的整數值替換為 HIGH 以遮蔽這些值。

如要進一步瞭解特徵分塊的概念，請參閱一般化與特徵分塊一文。

replaceWithInfoTypeConfig

指定 replaceWithInfoTypeConfig 會將每個相符的值替換為 infoType 的名稱。replaceWithInfoTypeConfig 訊息沒有引數，指定該訊息即可啟用轉換。

舉例來說，假設您為所有 EMAIL_ADDRESS infoType 指定了 replaceWithInfoTypeConfig，並將下列字串傳送至 Sensitive Data Protection：

My name is Alicia Abernathy, and my email address is aabernathy@example.com.

傳回的字串將顯示以下內容：

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

timePartConfig

將 timePartConfig 設為 TimePartConfig 物件，可保留部分相符值，包括 Date、Timestamp 和 TimeOfDay 值。TimePartConfig 物件包含 partToExtract 引數，可設為任何 TimePart 列舉值，包括年、月、日等。

舉例來說，假設您將 partToExtract 設為 YEAR，設定了 timePartConfig 轉換。將下表第一欄的資料傳送至 Sensitive Data Protection 後，第二欄會顯示轉換後的值：

原始值	轉換值
`9/21/1976`	`1976`
`6/7/1945`	`1945`
`1/20/2009`	`2009`
`7/4/1776`	`1776`
`8/1/1984`	`1984`
`4/21/1982`	`1982`

記錄轉換

記錄轉換 (RecordTransformations 物件) 只會套用至表格型資料中，識別為特定 infoType 的值。RecordTransformations 包含兩個轉換子類別：

fieldTransformations[]：套用各種欄位轉換的轉換。
recordSuppressions[]：定義要完全隱藏哪些記錄的規則。符合 recordSuppressions[] 內任何抑制規則的記錄，都會從輸出內容中省略。

欄位轉換

每個 FieldTransformation 物件都包含三個引數：

fields：要套用轉換的一或多個輸入欄位 (FieldID 物件)。
condition：必須評估為 true 才能套用轉換的條件 (RecordCondition 物件)。舉例來說，只有當相同記錄的郵遞區號欄在某個特定範圍內時，才會將特徵分塊轉換套用到記錄的年齡欄。或者，只有當出生日期欄位中某個人的年齡為 85 歲或以上時，才會遮蓋欄位。
以下兩種轉換類型引數的其中之一，必須指定其中一項：
- infoTypeTransformations：將欄位內容視為自由文字，並僅對符合 InfoType 的內容套用 PrimitiveTransformation。本主題稍早已討論過這些轉換。
- primitiveTransformation：將指定的原始轉換 (PrimitiveTransformation 物件) 套用至整個欄位。本主題稍早已討論過這些轉換。
  
  如果 RecordTransformations 物件只包含 primitiveTransformation，不含 infoTypeTransformations，則要求中不需要包含 InspectConfig 物件。如果這麼做，Sensitive Data Protection 會忽略該欄。

欄位轉換範例

下列範例會傳送包含兩項欄位轉換的 projects.content.deidentify 要求：

第一個欄位轉換會套用至前兩個資料欄 (column1 和 column2)。由於轉換類型是 primitiveTransformation 物件 (具體來說是 CryptoDeterministicConfig)，Sensitive Data Protection 會轉換整個欄位。

警告：為示範用途，這個範例使用未包裝的金鑰。請勿將這組金鑰用於實際的機密工作負載。Google 建議您改用包裝金鑰。如要進一步瞭解如何建立包裝金鑰，並在去識別化和重新識別要求中使用，請參閱「將機密資料去識別化及重新識別」。
第二個欄位轉換會套用至第三欄 (column3)。由於轉換類型是 infoTypeTransformations 物件，Sensitive Data Protection 只會將原始轉換 (具體來說是 ReplaceWithInfoTypeConfig) 套用至符合檢查設定中 infoType 的內容。

使用任何要求資料之前，請先修改下列項目的值：

PROJECT_ID：您的 Google Cloud 專案 ID。專案 ID 是英數字串，例如 my-project。

HTTP 方法和網址：

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

JSON 要求主體：

{
  "item": {
    "table": {
      "headers": [
        {
          "name": "column1"
        },
        {
          "name": "column2"
        },
        {
          "name": "column3"
        }
      ],
      "rows": [
        {
          "values": [
            {
              "stringValue": "Example string 1"
            },
            {
              "stringValue": "Example string 2"
            },
            {
              "stringValue": "My email address is dani@example.org"
            }
          ]
        },
        {
          "values": [
            {
              "stringValue": "Example string 1"
            },
            {
              "stringValue": "Example string 3"
            },
            {
              "stringValue": "My email address is cruz@example.org"
            }
          ]
        }
      ]
    }
  },
  "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"
      }
    ]
  }
}

請展開以下其中一個選項，以傳送要求：

curl (Linux、macOS 或 Cloud Shell)

注意：下列指令假設您已執行 gcloud init 或 gcloud auth login，透過使用者帳戶登入 gcloud CLI，或已使用 Cloud Shell 自動登入 gcloud CLI。您可以執行 gcloud auth list，查看目前使用的帳戶。

將要求主體儲存在名為 deidentify-tabular-content-request.json 的檔案中，然後執行下列指令：

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：下列指令假設您已執行 gcloud init 或 gcloud auth login，透過使用者帳戶登入 gcloud CLI。您可以執行 gcloud auth list，查看目前使用的帳戶。

將要求主體儲存在名為 deidentify-tabular-content-request.json 的檔案中，然後執行下列指令：

$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

您應該會收到如下的 JSON 回覆：

{
  "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"
      }
    ]
  }
}

記錄抑制

除了對欄位資料套用轉換，您也可以指示 Sensitive Data Protection，在特定抑制條件評估為 true 時，直接抑制記錄，將資料去識別化。您可以在同一個要求中同時套用欄位轉換和記錄抑制。

您需要將 RecordTransformations 物件的 recordSuppressions 訊息設為一或多個 RecordSuppression 物件的陣列。

每個 RecordSuppression 物件都包含一個 RecordCondition 物件，而該物件又包含一個 Expressions 物件。

Expressions 物件包含：

logicalOperator：其中一個 LogicalOperator 列舉類型。
conditions：Conditions 物件，包含一或多個 Condition 物件的陣列。Condition 是欄位值與另一個值的比較，兩者都必須是 string、boolean、integer、double、Timestamp 或 TimeofDay 類型。

如果比較結果為 true，系統會隱藏記錄，反之亦然。如果比較的值類型不同，系統會顯示警告，且條件會評估為 false。

可復原的轉換

使用 CryptoReplaceFfxFpeConfig 或 CryptoDeterministicConfig infoType 轉換作業將資料去識別化時，只要您有原本用於將資料去識別化的 CryptoKey，就能重新識別該資料。詳情請參閱「加密型權杖化轉換」。

發現項目數量限制

如果要求超過 3,000 個發現項目，Sensitive Data Protection 會傳回下列訊息：

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

Sensitive Data Protection 傳回的發現項目清單，是要求中所有發現項目的任意子集。如要取得所有發現項目，請將要求拆分為較小的批次。

後續步驟

進一步瞭解去識別化工作流程如何融入實際部署作業。
完成「使用 Sensitive Data Protection 遮蓋機密資料」程式碼實驗室。
透過範例瞭解如何建立包裝金鑰、將內容權杖化，以及重新識別權杖化內容。
進一步瞭解如何建立去識別化的儲存空間資料副本。

將機密資料去識別化 透過集合功能整理內容 你可以依據偏好儲存及分類內容。

API 總覽

指定偵測條件

去識別化轉換

InfoType 轉換

原始轉換

replaceConfig

Python

Java

REST

redactConfig

C#

Go

Java

Node.js

PHP

Python

REST

characterMaskConfig

Java

Node.js

Python

Go

PHP

C#

REST

cryptoHashConfig

dateShiftConfig

Java

Node.js

Python

Go

PHP

C#

cryptoReplaceFfxFpeConfig

Java

Python

PHP

C#

Java

Node.js

Python

Go

PHP

C#

fixedSizeBucketingConfig

bucketingConfig

replaceWithInfoTypeConfig

timePartConfig

記錄轉換

欄位轉換

欄位轉換範例

curl (Linux、macOS 或 Cloud Shell)

PowerShell (Windows)

記錄抑制

可復原的轉換

發現項目數量限制

後續步驟

將機密資料去識別化