使用自訂啟動字詞檢查機密資料的字串

如果附近有啟動字詞「患者」，則增加 PERSON_NAME 相符項目的可能性。 說明如何使用 InspectConfig 屬性掃描醫療資料庫，找出患者姓名。您可以使用 Cloud DLP 內建的 PERSON_NAME infoType 偵測工具，不過這會造成 Cloud DLP 比對所有人的姓名，而不是只比對患者的姓名。為修正這種情況，您可以加入啟動字詞規則，在潛在相符項目第一個字元的特定字元鄰近範圍內尋找「患者」一詞。然後，您可以為符合這個模式的發現項目，指派「非常可能」的可能性，因為這對應到您的特殊條件。在 InspectConfig 中將最低可能性設為 VERY_LIKELY，可確保在發現項目中只會傳回與這項設定相符的項目。

深入探索

如需包含這個程式碼範例的詳細說明文件，請參閱下列內容：

• 修改 infoType 偵測工具以修正掃描結果

程式碼範例

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 Google.Api.Gax.ResourceNames;
using Google.Cloud.Dlp.V2;
using System;
using static Google.Cloud.Dlp.V2.CustomInfoType.Types;

public class InspectStringCustomHotword
{
    public static InspectContentResponse Inspect(string projectId, string textToInspect, string customHotword)
    {
        var dlp = DlpServiceClient.Create();

        var byteContentItem = new ByteContentItem
        {
            Type = ByteContentItem.Types.BytesType.TextUtf8,
            Data = Google.Protobuf.ByteString.CopyFromUtf8(textToInspect)
        };

        var contentItem = new ContentItem
        {
            ByteItem = byteContentItem
        };

        var hotwordRule = new DetectionRule.Types.HotwordRule
        {
            HotwordRegex = new Regex { Pattern = customHotword },
            Proximity = new DetectionRule.Types.Proximity { WindowBefore = 50 },
            LikelihoodAdjustment = new DetectionRule.Types.LikelihoodAdjustment { FixedLikelihood = Likelihood.VeryLikely }
        };

        var infoType = new InfoType { Name = "PERSON_NAME" };

        var inspectionRuleSet = new InspectionRuleSet
        {
            InfoTypes = { infoType },
            Rules = { new InspectionRule { HotwordRule = hotwordRule } }
        };

        var inspectConfig = new InspectConfig
        {
            InfoTypes = { infoType },
            IncludeQuote = true,
            RuleSet = { inspectionRuleSet },
            MinLikelihood = Likelihood.VeryLikely
        };

        var request = new InspectContentRequest
        {
            Parent = new LocationName(projectId, "global").ToString(),
            Item = contentItem,
            InspectConfig = inspectConfig
        };

        var response = dlp.InspectContent(request);

        Console.WriteLine($"Findings: {response.Result.Findings.Count}");
        foreach (var f in response.Result.Findings)
        {
            Console.WriteLine("\tQuote: " + f.Quote);
            Console.WriteLine("\tInfo type: " + f.InfoType.Name);
            Console.WriteLine("\tLikelihood: " + f.Likelihood);
        }

        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"
)

// inspectStringCustomHotWord inspects a string from sensitive data by using a custom hot word
func inspectStringCustomHotWord(w io.Writer, projectID, textToInspect, customHotWord, infoTypeName string) error {
	// projectID := "my-project-id"
	// textToInspect := "patient name: John Doe"
	// customHotWord := "patient"
	// infoTypeName := "PERSON_NAME"

	ctx := context.Background()

	// Initialize a client once and reuse it to send multiple requests. Clients
	// are safe to use across goroutines. When the client is no longer needed,
	// call the Close method to cleanup its resources.
	client, err := dlp.NewClient(ctx)
	if err != nil {
		return err
	}

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

	// Specify the type and content to be inspected.
	contentItem := &dlppb.ContentItem{
		DataItem: &dlppb.ContentItem_ByteItem{
			ByteItem: &dlppb.ByteContentItem{
				Type: dlppb.ByteContentItem_TEXT_UTF8,
				Data: []byte(textToInspect),
			},
		},
	}

	// Increase likelihood of matches that have customHotword nearby
	hotwordRule := &dlppb.InspectionRule_HotwordRule{

		HotwordRule: &dlppb.CustomInfoType_DetectionRule_HotwordRule{
			HotwordRegex: &dlppb.CustomInfoType_Regex{
				Pattern: customHotWord,
			},
			Proximity: &dlppb.CustomInfoType_DetectionRule_Proximity{
				WindowBefore: 50,
			},
			LikelihoodAdjustment: &dlppb.CustomInfoType_DetectionRule_LikelihoodAdjustment{
				Adjustment: &dlppb.CustomInfoType_DetectionRule_LikelihoodAdjustment_FixedLikelihood{
					FixedLikelihood: dlppb.Likelihood_VERY_LIKELY,
				},
			},
		},
	}

	// Construct a ruleset that applies the hotword rule to the PERSON_NAME infotype.
	ruleSet := &dlppb.InspectionRuleSet{
		InfoTypes: []*dlppb.InfoType{
			{Name: infoTypeName}, //"PERSON_NAME"
		},
		Rules: []*dlppb.InspectionRule{
			{
				Type: &dlppb.InspectionRule_HotwordRule{
					HotwordRule: hotwordRule.HotwordRule,
				},
			},
		},
	}

	// Construct the Inspect request to be sent by the client.
	req := &dlppb.InspectContentRequest{
		Parent: fmt.Sprintf("projects/%s/locations/global", projectID),
		Item:   contentItem,
		InspectConfig: &dlppb.InspectConfig{
			InfoTypes: []*dlppb.InfoType{
				{Name: infoTypeName}, //"PERSON_NAME"
			},
			IncludeQuote:  true,
			MinLikelihood: dlppb.Likelihood_VERY_LIKELY,
			RuleSet: []*dlppb.InspectionRuleSet{
				ruleSet,
			},
		},
	}

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

	// Parse the response and process results
	fmt.Fprintf(w, "Findings: %v\n", len(resp.Result.Findings))
	for _, v := range resp.GetResult().Findings {
		fmt.Fprintf(w, "Quote: %v\n", v.GetQuote())
		fmt.Fprintf(w, "Infotype Name: %v\n", v.GetInfoType().GetName())
		fmt.Fprintf(w, "Likelihood: %v\n", v.GetLikelihood())
	}
	return nil

}

Java

如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.ByteContentItem;
import com.google.privacy.dlp.v2.ByteContentItem.BytesType;
import com.google.privacy.dlp.v2.ContentItem;
import com.google.privacy.dlp.v2.CustomInfoType.DetectionRule.HotwordRule;
import com.google.privacy.dlp.v2.CustomInfoType.DetectionRule.LikelihoodAdjustment;
import com.google.privacy.dlp.v2.CustomInfoType.DetectionRule.Proximity;
import com.google.privacy.dlp.v2.CustomInfoType.Regex;
import com.google.privacy.dlp.v2.Finding;
import com.google.privacy.dlp.v2.InfoType;
import com.google.privacy.dlp.v2.InspectConfig;
import com.google.privacy.dlp.v2.InspectContentRequest;
import com.google.privacy.dlp.v2.InspectContentResponse;
import com.google.privacy.dlp.v2.InspectionRule;
import com.google.privacy.dlp.v2.InspectionRuleSet;
import com.google.privacy.dlp.v2.Likelihood;
import com.google.privacy.dlp.v2.LocationName;
import com.google.protobuf.ByteString;
import java.io.IOException;

public class InspectStringCustomHotword {

  public static void main(String[] args) throws Exception {
    // TODO(developer): Replace these variables before running the sample.
    String projectId = "your-project-id";
    String textToInspect = "patient name: John Doe";
    String customHotword = "patient";
    inspectStringCustomHotword(projectId, textToInspect, customHotword);
  }

  // Inspects the provided text.
  public static void inspectStringCustomHotword(
      String projectId, String textToInspect, String customHotword) throws IOException {
    // Initialize client that will be used to send requests. This client only needs to be created
    // once, and can be reused for multiple requests. After completing all of your requests, call
    // the "close" method on the client to safely clean up any remaining background resources.
    try (DlpServiceClient dlp = DlpServiceClient.create()) {
      // Specify the type and content to be inspected.
      ByteContentItem byteItem =
          ByteContentItem.newBuilder()
              .setType(BytesType.TEXT_UTF8)
              .setData(ByteString.copyFromUtf8(textToInspect))
              .build();
      ContentItem item = ContentItem.newBuilder().setByteItem(byteItem).build();

      // Increase likelihood of matches that have customHotword nearby
      HotwordRule hotwordRule =
          HotwordRule.newBuilder()
              .setHotwordRegex(Regex.newBuilder().setPattern(customHotword))
              .setProximity(Proximity.newBuilder().setWindowBefore(50))
              .setLikelihoodAdjustment(
                  LikelihoodAdjustment.newBuilder().setFixedLikelihood(Likelihood.VERY_LIKELY))
              .build();

      // Construct a ruleset that applies the hotword rule to the PERSON_NAME infotype.
      InspectionRuleSet ruleSet =
          InspectionRuleSet.newBuilder()
              .addInfoTypes(InfoType.newBuilder().setName("PERSON_NAME").build())
              .addRules(InspectionRule.newBuilder().setHotwordRule(hotwordRule))
              .build();

      // Construct the configuration for the Inspect request.
      InspectConfig config =
          InspectConfig.newBuilder()
              .addInfoTypes(InfoType.newBuilder().setName("PERSON_NAME").build())
              .setIncludeQuote(true)
              .addRuleSet(ruleSet)
              .setMinLikelihood(Likelihood.VERY_LIKELY)
              .build();

      // Construct the Inspect request to be sent by the client.
      InspectContentRequest request =
          InspectContentRequest.newBuilder()
              .setParent(LocationName.of(projectId, "global").toString())
              .setItem(item)
              .setInspectConfig(config)
              .build();

      // Use the client to send the API request.
      InspectContentResponse response = dlp.inspectContent(request);

      // Parse the response and process results
      System.out.println("Findings: " + response.getResult().getFindingsCount());
      for (Finding f : response.getResult().getFindingsList()) {
        System.out.println("\tQuote: " + f.getQuote());
        System.out.println("\tInfo type: " + f.getInfoType().getName());
        System.out.println("\tLikelihood: " + f.getLikelihood());
      }
    }
  }
}

Node.js

如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 inspect
// const string = 'patient name: John Doe';

// Custom hotward
// const customHotword = 'patient';

async function inspectStringCustomHotword() {
  // Specify the type and content to be inspected.
  const item = {
    byteItem: {
      type: DLP.protos.google.privacy.dlp.v2.ByteContentItem.BytesType
        .TEXT_UTF8,
      data: Buffer.from(string, 'utf-8'),
    },
  };

  // Increase likelihood of matches that have customHotword nearby.
  const hotwordRule = {
    hotwordRegex: {
      pattern: customHotword,
    },
    proximity: {
      windowBefore: 50,
    },
    likelihoodAdjustment: {
      fixedLikelihood:
        DLP.protos.google.privacy.dlp.v2.Likelihood.VERY_LIKELY,
    },
  };

  // Construct a ruleset that applies the hotword rule to the PERSON_NAME infotype.
  const ruleSet = [
    {
      infoTypes: [{name: 'PERSON_NAME'}],
      rules: [
        {
          hotwordRule: hotwordRule,
        },
      ],
    },
  ];

  // Construct the configuration for the Inspect request.
  const inspectConfig = {
    infoTypes: [{name: 'PERSON_NAME'}],
    ruleSet: ruleSet,
    includeQuote: true,
  };

  // Construct the Inspect request to be sent by the client.
  const request = {
    parent: `projects/${projectId}/locations/global`,
    inspectConfig: inspectConfig,
    item: item,
  };

  // Use the client to send the API request.
  const [response] = await dlp.inspectContent(request);

  // Print findings.
  const findings = response.result.findings;
  if (findings.length > 0) {
    console.log(`Findings: ${findings.length}\n`);
    findings.forEach(finding => {
      console.log(`InfoType: ${finding.infoType.name}`);
      console.log(`\tQuote: ${finding.quote}`);
      console.log(`\tLikelihood: ${finding.likelihood} \n`);
    });
  } else {
    console.log('No findings.');
  }
}
inspectStringCustomHotword();

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\CustomInfoType\DetectionRule\HotwordRule;
use Google\Cloud\Dlp\V2\CustomInfoType\DetectionRule\LikelihoodAdjustment;
use Google\Cloud\Dlp\V2\CustomInfoType\DetectionRule\Proximity;
use Google\Cloud\Dlp\V2\CustomInfoType\Regex;
use Google\Cloud\Dlp\V2\InfoType;
use Google\Cloud\Dlp\V2\InspectConfig;
use Google\Cloud\Dlp\V2\InspectContentRequest;
use Google\Cloud\Dlp\V2\InspectionRule;
use Google\Cloud\Dlp\V2\InspectionRuleSet;
use Google\Cloud\Dlp\V2\Likelihood;

/**
 * Inspect a string from sensitive data by using a custom hotword
 * Increase the likelihood of a PERSON_NAME match if there is the hotword "patient" nearby. Illustrates using the InspectConfig property for the purpose of scanning a medical database for patient names. You can use Cloud DLP's built-in PERSON_NAME infoType detector, but that causes Cloud DLP to match on all names of people, not just names of patients. To fix this, you can include a hotword rule that looks for the word "patient" within a certain character proximity from the first character of potential matches. You can then assign findings that match this pattern a likelihood of "very likely," since they correspond to your special criteria. Setting the minimum likelihood to VERY_LIKELY within InspectConfig ensures that only matches to this configuration are returned in findings.
 *
 * @param string $projectId         The Google Cloud project id to use as a parent resource.
 * @param string $textToInspect     The string to inspect.
 */
function inspect_string_custom_hotword(
    // TODO(developer): Replace sample parameters before running the code.
    string $projectId,
    string $textToInspect = 'patient name: John Doe'
): void {
    // Instantiate a client.
    $dlp = new DlpServiceClient();

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

    // Specify what content you want the service to Inspect.
    $item = (new ContentItem())
        ->setValue($textToInspect);

    // Construct hotword rules
    $hotwordRule = (new HotwordRule())
        ->setHotwordRegex(
            (new Regex())
                ->setPattern('patient')
        )
        ->setProximity(
            (new Proximity())
                ->setWindowBefore(50)
        )
        ->setLikelihoodAdjustment(
            (new LikelihoodAdjustment())
                ->setFixedLikelihood(Likelihood::VERY_LIKELY)
        );

    // Construct a ruleset that applies the hotword rule to the PERSON_NAME infotype.
    $personName = (new InfoType())
        ->setName('PERSON_NAME');
    $inspectionRuleSet = (new InspectionRuleSet())
        ->setInfoTypes([$personName])
        ->setRules([
            (new InspectionRule())
                ->setHotwordRule($hotwordRule),
        ]);

    // Construct the configuration for the Inspect request, including the ruleset.
    $inspectConfig = (new InspectConfig())
        ->setInfoTypes([$personName])
        ->setIncludeQuote(true)
        ->setRuleSet([$inspectionRuleSet])
        ->setMinLikelihood(Likelihood::VERY_LIKELY);

    // Run request
    $inspectContentRequest = (new InspectContentRequest())
        ->setParent($parent)
        ->setInspectConfig($inspectConfig)
        ->setItem($item);
    $response = $dlp->inspectContent($inspectContentRequest);

    // Print the results
    $findings = $response->getResult()->getFindings();
    if (count($findings) == 0) {
        printf('No findings.' . PHP_EOL);
    } else {
        printf('Findings:' . PHP_EOL);
        foreach ($findings as $finding) {
            printf('  Quote: %s' . PHP_EOL, $finding->getQuote());
            printf('  Info type: %s' . PHP_EOL, $finding->getInfoType()->getName());
            printf('  Likelihood: %s' . PHP_EOL, Likelihood::name($finding->getLikelihood()));
        }
    }
}

Python

如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 google.cloud.dlp


def inspect_string_w_custom_hotword(
    project: str, content_string: str, custom_hotword: str = "patient"
) -> None:
    """Uses the Data Loss Prevention API increase likelihood for matches on
       PERSON_NAME if the user specified custom hot-word is present. Only
       includes findings with the increased likelihood by setting a minimum
       likelihood threshold of VERY_LIKELY.

    Args:
        project: The Google Cloud project id to use as a parent resource.
        content_string: The string to inspect.
        custom_hotword: The custom hot-word used for likelihood boosting.
    """

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

    # Construct a rule set with caller provided hotword, with a likelihood
    # boost to VERY_LIKELY when the hotword are present within the 50 character-
    # window preceding the PII finding.
    hotword_rule = {
        "hotword_regex": {"pattern": custom_hotword},
        "likelihood_adjustment": {
            "fixed_likelihood": google.cloud.dlp_v2.Likelihood.VERY_LIKELY
        },
        "proximity": {"window_before": 50},
    }

    rule_set = [
        {
            "info_types": [{"name": "PERSON_NAME"}],
            "rules": [{"hotword_rule": hotword_rule}],
        }
    ]

    # Construct the configuration dictionary with the custom regex info type.
    inspect_config = {
        "rule_set": rule_set,
        "min_likelihood": google.cloud.dlp_v2.Likelihood.VERY_LIKELY,
        "include_quote": True,
    }

    # Construct the `item`.
    item = {"value": content_string}

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

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

    # Print out the results.
    if response.result.findings:
        for finding in response.result.findings:
            print(f"Quote: {finding.quote}")
            print(f"Info type: {finding.info_type.name}")
            print(f"Likelihood: {finding.likelihood}")
    else:
        print("No findings.")

後續步驟

如要搜尋及篩選其他 Google Cloud 產品的程式碼範例，請參閱Google Cloud 範例瀏覽器。