핫워드 '환자'가 근접한 위치에 있는 경우 PERSON_NAME 일치의 가능성을 높임 의료 데이터베이스에서 환자 이름을 스캔하기 위한 InspectConfig 속성 사용을 보여줍니다. Cloud DLP의 기본 제공 PERSON_NAME infoType 감지기를 사용할 수 있지만, 이 경우 Cloud DLP가 환자 이름뿐만 아니라 모든 사람의 이름에서 일치하는 항목을 찾습니다. 이 문제를 해결하려면 잠재적인 일치 항목의 첫 글자로부터 특정 문자 수 만큼의 근접도 내에서 '환자'라는 단어를 찾는 핫워드 규칙을 포함할 수 있습니다. 이는 특수한 기준에 해당하므로 이 패턴과 일치하는 결과에 'very likely' 가능성을 할당할 수 있습니다. InspectConfig 내에서 최소 가능성을 VERY_LIKELY로 설정하면 이 구성과 일치하는 항목만 검색 결과에 반환되도록 보장할 수 있습니다.
더 살펴보기
이 코드 샘플이 포함된 자세한 문서는 다음을 참조하세요.
코드 샘플
C#
민감한 정보 보호의 클라이언트 라이브러리를 설치하고 사용하는 방법은 민감한 정보 보호 클라이언트 라이브러리를 참조하세요.
Sensitive Data Protection에 인증하려면 애플리케이션 기본 사용자 인증 정보를 설정합니다. 자세한 내용은 로컬 개발 환경의 인증 설정을 참조하세요.
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
Sensitive Data Protection의 클라이언트 라이브러리를 설치하고 사용하는 방법은 Sensitive Data Protection 클라이언트 라이브러리를 참조하세요.
Sensitive Data Protection에 인증하려면 애플리케이션 기본 사용자 인증 정보를 설정합니다. 자세한 내용은 로컬 개발 환경의 인증 설정을 참조하세요.
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
Sensitive Data Protection의 클라이언트 라이브러리를 설치하고 사용하는 방법은 Sensitive Data Protection 클라이언트 라이브러리를 참조하세요.
Sensitive Data Protection에 인증하려면 애플리케이션 기본 사용자 인증 정보를 설정합니다. 자세한 내용은 로컬 개발 환경의 인증 설정을 참조하세요.
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
Sensitive Data Protection의 클라이언트 라이브러리를 설치하고 사용하는 방법은 Sensitive Data Protection 클라이언트 라이브러리를 참조하세요.
Sensitive Data Protection에 인증하려면 애플리케이션 기본 사용자 인증 정보를 설정합니다. 자세한 내용은 로컬 개발 환경의 인증 설정을 참조하세요.
// 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
Sensitive Data Protection의 클라이언트 라이브러리를 설치하고 사용하는 방법은 Sensitive Data Protection 클라이언트 라이브러리를 참조하세요.
Sensitive Data Protection에 인증하려면 애플리케이션 기본 사용자 인증 정보를 설정합니다. 자세한 내용은 로컬 개발 환경의 인증 설정을 참조하세요.
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
Sensitive Data Protection의 클라이언트 라이브러리를 설치하고 사용하는 방법은 Sensitive Data Protection 클라이언트 라이브러리를 참조하세요.
Sensitive Data Protection에 인증하려면 애플리케이션 기본 사용자 인증 정보를 설정합니다. 자세한 내용은 로컬 개발 환경의 인증 설정을 참조하세요.
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.")
다음 단계
다른 Google Cloud 제품의 코드 샘플을 검색하고 필터링하려면 Google Cloud 샘플 브라우저를 참조하세요.