將機密資料去識別化

「機密資料保護」服務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。去識別化是移除資料中識別資訊的程序。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:

  • 將局部或全部字元替換為星號 (*) 或井號 (#) 等符號以「遮蔽」機密資料。
  • 將機密資料的每個例項替換為代碼或代理值字串。
  • 使用隨機產生或預先決定的金鑰來加密和取代機密資料。

您可以在 HTTPS 使用 JSON、CLI,以及透過 Sensitive Data Protection 用戶端程式庫使用多種程式設計語言,提供資訊給 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提交 JSON 格式的資訊,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」:要讓 API 檢查的字串或資料表結構 (ContentItem 物件)。
  • 要檢查的內容:偵測設定資訊 (InspectConfig),例如要尋找的資料類型 (或 infoType)、是否要篩選高於某個可能性門檻的發現項目,以及是否要傳回不超過某個數目的結果。

    InspectConfig 物件中,請務必加入要掃描的 infoType。否則,Sensitive Data Protection 會掃描預設的 infoType 集 (ALL_BASIC),其中可能包含您不需要的項目。掃描不需要的 infoType 可能會導致要求延遲。

    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」。

  • 「如何處理檢查發現項目」:定義您要如何將機密資料去識別化的設定資訊 (DeidentifyConfig)。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 包括數種 infoType 偵測工具,分別摘要如下:

  • 內建 infoType 偵測工具內建於 Sensitive Data Protection。包括用於掃描特定國家/地區機密資料類型及全球適用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 用於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 使用儲存在 Cloud Storage 或 BigQuery 中的龐大字詞或詞組清單所產生。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)」可讓敏感性資料保護功能根據規則運算式模式偵測相符項目。

此外,Sensitive Data Protection 引進檢查規則的概念,可讓您使用以下項目微調掃描結果:

  • 「排除規則」可讓您將規則新增到內建或自訂 infoType 偵測工具中,藉此減少傳回的發現項目數。
  • 「啟動字詞規則」可讓您將規則新增到內建或自訂 infoType 偵測工具中,藉此提高傳回的發現項目數量,或變更傳回發現項目的可能性值

去識別化轉換

進行去識別化設定 (DeidentifyConfig) 時,您必須指定一或多個轉換。轉換分為兩類:

  • InfoTypeTransformations:這種轉換只會套用到識別為特定 infoType 的所提交文字中的值。
  • RecordTransformations:這種轉換只會套用到識別為特定 infoType 的所提交表格文字資料中的值,或是整欄表格資料中的值。

InfoType 轉換

您可以在每個要求指定一或多個 infoType 轉換。在每個 InfoTypeTransformation 物件中,您需要指定以下兩者:

請注意,您可以自行選擇是否要指定 infoType,但如果沒有在 InspectConfig 引數中指定至少一個 infoType,則會導致系統將轉換套用到未提供轉換的所有內建 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

您必須指定至少一個要套用到輸入的原始轉換,無論是只將其套用到某些 infoType 或套用到整個文字字串皆是如此。以下各節將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

replaceConfig 設為 ReplaceValueConfig 物件會將相符的輸入值替換為您指定的值。

舉例來說,假設您已將所有 EMAIL_ADDRESS infoType 的 replaceConfig 設定為「[email-address]」,且系統已將以下字串傳送至 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].

以下 JSON 範例和幾種程式語言的程式碼,說明如何形成 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,請參閱這篇文章

如要驗證 Sensitive Data Protection,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」。

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,請參閱這篇文章

如要驗證 Sensitive Data Protection,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」。


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:

{
  "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 會透過將值徹底移除的方式遮蓋指定值。redactConfig 訊息沒有引數;指定這個物件會啟用其轉換。

舉例來說,假設您已為所有 EMAIL_ADDRESS infoType 指定 redactConfig,且系統已將以下字串傳送至 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 .

以下範例說明如何形成 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,請參閱這篇文章

如要驗證 Sensitive Data Protection,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」。


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,請參閱這篇文章

如要驗證 Sensitive Data Protection,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」。

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,請參閱這篇文章

如要驗證 Sensitive Data Protection,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」。


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,請參閱這篇文章

如要驗證 Sensitive Data Protection,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」。

// 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,請參閱這篇文章

如要驗證 Sensitive Data Protection,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」。

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,請參閱這篇文章

如要驗證 Sensitive Data Protection,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」。

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:

{
  "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

characterMaskConfig 設定為 CharacterMaskConfig 物件會將指定的字元數替換為某個固定字元,藉此局部遮蔽字串。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 物件有一些自己的引數:

  • maskingCharacter:用來遮蔽機密值每個字元的字元。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:要遮蔽的字元數。如果您沒有設定這個值,系統將遮蔽所有相符的字元。
  • reverseOrder:是否要以反向的順序遮蔽字元。如果將 reverseOrder 設定為 True,會使得相符值中的字元從值的結尾朝著開頭進行遮蔽。如果將該引數設定為 False,會從值的開頭開始進行遮蔽。
  • charactersToIgnore[]:遮蔽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。您也可以指定遮蔽時要忽略的一組常見字元 (CharsToIgnore)。

舉例來說,假設您已將 characterMaskConfig 設為使用「#」遮蓋 EMAIL_ADDRESS infoType,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,透過遮蔽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,請參閱這篇文章

如要驗證 Sensitive Data Protection,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」。


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,請參閱這篇文章

如要驗證 Sensitive Data Protection,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」。

// 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,請參閱這篇文章

如要驗證 Sensitive Data Protection,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」。

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,請參閱這篇文章

如要驗證 Sensitive Data Protection,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」。

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,請參閱這篇文章

如要驗證 Sensitive Data Protection,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」。

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,請參閱這篇文章

如要驗證 Sensitive Data Protection,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」。


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:

{
  "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

cryptoHashConfig 設為 CryptoHashConfig 物件,會使用加密編譯雜湊產生替代值,對輸入值執行匿名化

這個方法會將輸入值替換為加密的「摘要」或雜湊值。系統會進行輸入值的 SHA-256 雜湊來計算摘要。用來進行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。

這個方法的輸出為以 Base64 編碼的雜湊內容。 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 cryptoHashConfig infoType 指定 EMAIL_ADDRESS,且 CryptoKey 物件包含一個隨機產生的金鑰 (TransientCryptoKey)。接著,系統會將以下字串傳送至 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

dateShiftConfig 設為 DateShiftConfig 物件,即可對日期輸入值執行日期轉移,也就是將日期轉移隨機天數。

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

以下是幾種不同程式語言的範例程式碼,示範如何透過日期轉移使用 DLP API 將日期去識別化。

Java

如要瞭解如何安裝及使用 Sensitive Data Protection 的用戶端程式庫,請參閱這篇文章

如要驗證 Sensitive Data Protection,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」。


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,請參閱這篇文章

如要驗證 Sensitive Data Protection,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」。

// 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,請參閱這篇文章

如要驗證 Sensitive Data Protection,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」。

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,請參閱這篇文章

如要驗證 Sensitive Data Protection,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」。

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,請參閱這篇文章

如要驗證 Sensitive Data Protection,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」。

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,請參閱這篇文章

如要驗證 Sensitive Data Protection,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」。


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

cryptoReplaceFfxFpeConfig 設為 CryptoReplaceFfxFpeConfig 物件,即可對輸入值執行匿名化,也就是將輸入值替換為權杖。代碼具有下列特性:

  • 加密的輸入值。
  • 長度與輸入值相同。
  • 在金鑰使用 cryptoKey 指定的加密編譯金鑰的 FFX 模式中,使用格式保留加密 (「FPE-FFX」) 進行計算。
  • alphabet 指定的字元構成。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 指定的字元構成。alphabet 長度可介於 2 至 95 個字元之間,(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代碼。您可透過以下三種方式的其中之一提供這個金鑰:

  • 將金鑰以未加密的方式嵌入 API 請求中。我們不建議這麼做。
  • 要求 Sensitive Data Protection 產生這個金鑰。
  • 將金鑰以加密的方式嵌入 API 請求中。

如果選擇將金鑰嵌入 API 請求中,您需要建立金鑰並使用 Cloud Key Management Service (Cloud KMS) 金鑰包裝 (加密) 金鑰。根據預設,傳回的值為 Base64 編碼的字串。如要在 Sensitive Data Protection 中設定這個值,必須將它解碼為位元組字串。以下程式碼片段將示範如何以各種不同的程式語言執行這項操作。這些程式碼片段的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。

根據設計,FPE-FFX 會保留輸入文字的長度和字元集。這表示該權杖缺少驗證和初始化向量,因此輸出權杖的長度會擴增。其他方法 (例如 AES-SIV) 可提供更強大的安全保障,因此建議用於權杖化用途,除非長度和字元集保留是嚴格的必要條件,例如為了與舊版資料系統向後相容。

以下是幾種不同程式語言的範例程式碼,示範如何使用 Sensitive Data Protection 將輸入值替換為代碼,藉此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,請參閱這篇文章

如要驗證 Sensitive Data Protection,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」。


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,請參閱這篇文章

如要驗證 Sensitive Data Protection,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」。

// 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,請參閱這篇文章

如要驗證 Sensitive Data Protection,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」。

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,請參閱這篇文章

如要驗證 Sensitive Data Protection,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」。

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,請參閱這篇文章

如要驗證 Sensitive Data Protection,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」。

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,請參閱這篇文章

如要驗證 Sensitive Data Protection,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」。


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

特徵分塊轉換 (此設定以及 bucketingConfig) 的作用在於將數值型資料「特徵分塊」為範圍,藉此遮蔽數值型資料。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。

fixedSizeBucketingConfig 設定為 FixedSizeBucketingConfig 物件會根據固定的大小範圍對輸入值進行特徵分塊。FixedSizeBucketingConfig 物件包含下列項目:

  • lowerBound:所有特徵分塊的下限值。小於這個值的值會組成單一特徵分塊。
  • upperBound:所有特徵分塊的上限值。大於這個值的值會組成單一特徵分塊。
  • bucketSize:最小與最大特徵分塊以外的每個特徵分塊的大小。

舉例來說,如果將 lowerBound 設為 10、將 upperBound 設為 89,並將 bucketSize 設為 10,則會使用以下特徵分塊:-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 轉換比另一種特徵分塊轉換 fixedSizeBucketingConfig 更有彈性。您需要為所要建立的每個特徵分塊指定最大與最小值,而不是指定上限與下限以及用來建立相等大小特徵分塊的間隔值。每個最大與最小值組合必須具有相同的類型。

bucketingConfig 設定為 BucketingConfig 物件會指定自訂特徵分塊。BucketingConfig 物件包含 buckets[] 陣列的 Bucket 物件。每個 Bucket 物件都包含下列項目:

  • min:特徵分塊範圍的下限。省略這個值可建立沒有下限的特徵分塊。
  • max:特徵分塊範圍的上限。省略這個值可建立沒有上限的特徵分塊。
  • replacementValue:可使用這個值來替換介於下限與上限之間的值。如未提供 replacementValue,將會改用以連字符連接的 min-max 範圍。

如果值落在定義的範圍之外,傳回的 TransformationSummary 將包含錯誤訊息。

舉例來說,假設有以下的 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;指定這個物件會啟用其轉換。

舉例來說,假設您已為所有 EMAIL_ADDRESS infoType 指定 replaceWithInfoTypeConfig,且系統已將以下字串傳送至 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

timePartConfig 設為 TimePartConfig 物件,可保留一部分相符的值,包括 DateTimestampTimeOfDay 值。TimePartConfig 物件包含 partToExtract 引數,您可將其設定為任何 TimePart 列舉值,包括年、月、日等等。

舉例來說,假設您已將 partToExtract 設為 YEAR,藉此設定 timePartConfig 轉換。將下方第一欄中的資料傳送至 Sensitive Data Protection 後,會在第二欄產生轉換值:

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) 只會套用到識別為特定 infoType 的表格資料中的值。在 RecordTransformations 中,還有兩種轉換的子類別:

  • fieldTransformations[]:會套用多種欄位轉換的轉換。
  • recordSuppressions[]: 定義要完全抑制哪些記錄的規則。輸出中會省略符合 recordSuppressions[] 內任何抑制規則的記錄。

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:得出的值必須為 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,您必須指定一種:

    • infoTypeTransformations:將欄位內容視為任意文字,並僅將 PrimitiveTransformation 套用至符合 InfoType 的內容。本主題前面已探討這些轉換。
    • primitiveTransformation:將指定的原始轉換 (PrimitiveTransformation 物件) 套用到整個欄位。本主題前面已探討這些轉換。

      如果 RecordTransformations 物件只包含 primitiveTransformation,且沒有 infoTypeTransformations,則不需要在要求中加入 InspectConfig 物件。如果這麼做,Sensitive Data Protection 會忽略該資料集。

欄位轉換範例

以下範例會傳送 projects.content.deidentify 要求,並進行兩項欄位轉換:

  • 第一個欄位轉換會套用至前兩個資料欄 (column1column2)。由於轉換類型為 primitiveTransformation 物件 (具體來說是 CryptoDeterministicConfig),Sensitive Data Protection 會轉換整個欄位。

  • 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,因此 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,請先替換以下項目:

  • PROJECT_ID:您的 Google Cloud 專案 ID。專案 ID 為英數字串,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"
      }
    ]
  }
}

如要傳送要求,請展開以下其中一個選項:

您應該會收到如下的 JSON 回應:

{
  "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

除了將轉換套用到欄位資料以外,您也可以指示 Sensitive Data Protection 只在某些抑制條件得出的值為 True 時才抑制記錄,藉此將資料去識別化。您可以在同一個要求中同時套用欄位轉換和記錄抑制。

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

每個 RecordSuppression 物件都包含單一 RecordCondition 物件,而該物件又包含單一 Expressions 物件。

Expressions 物件包含:

  • logicalOperator:其中一個 LogicalOperator 列舉類型。
  • conditionsConditions 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,兩個值都必須是 stringbooleanintegerdoubleTimestampTimeofDay 類型。

如果比較得出的值為 True,則會抑制記錄,反之亦然。 如果比較的值不是相同的類型,則會出現警告,且條件得出的值為 False。

可復原的轉換

使用 CryptoReplaceFfxFpeConfigCryptoDeterministicConfig infoType 轉換作業去識別化資料後,只要有當初用來去識別化資料的 CryptoKey,就能重新識別該資料。詳情請參閱「以加密技術為基礎的權杖化轉換」。

發現項目數量上限

如果要求包含超過 3,000 項發現項目,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