열에서 확인된 발견 항목 변환 셀 내용의 일부 또는 전체를 구성하는 발견 항목을 변환할 수 있습니다. 이 예시에서 PERSON_NAME의 모든 인스턴스는 익명으로 처리됩니다.
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 System;
using System.Collections.Generic;
using Google.Api.Gax.ResourceNames;
using Google.Cloud.Dlp.V2;
public class DeidentifyTableWithInfoTypes
{
public static Table DeidentifyTable(
string projectId,
Table tableToInspect = null,
IEnumerable<InfoType> infoTypes = null)
{
// Instantiate a client.
var dlp = DlpServiceClient.Create();
// Construct the table if null.
if (tableToInspect == null)
{
var row1 = new Value[]
{
new Value { StringValue = "101" },
new Value { StringValue = "Charles Dickens" },
new Value { StringValue = "95" },
new Value { StringValue = "Charles Dickens name was a curse invented by Shakespeare." }
};
var row2 = new Value[]
{
new Value { StringValue = "22" },
new Value { StringValue = "Jane Austin" },
new Value { StringValue = "21" },
new Value { StringValue = "There are 14 kisses in Jane Austen's novels." }
};
var row3 = new Value[]
{
new Value { StringValue = "55" },
new Value { StringValue = "Mark Twain" },
new Value { StringValue = "75" },
new Value { StringValue = "Mark Twain loved cats." }
};
tableToInspect = new Table
{
Headers =
{
new FieldId { Name = "AGE" },
new FieldId { Name = "PATIENT" },
new FieldId { Name = "HAPPINESS SCORE" },
new FieldId { Name = "FACTOID" }
},
Rows =
{
new Table.Types.Row { Values = { row1 } },
new Table.Types.Row { Values = { row2 } },
new Table.Types.Row { Values = { row3 } }
}
};
}
// Construct the table content item.
var contentItem = new ContentItem { Table = tableToInspect };
// Construct Replace With InfoTypes config to replace the match.
var replaceInfoTypesConfig = new ReplaceWithInfoTypeConfig();
// Construct Fields to be de-identified.
var fieldIds = new FieldId[] { new FieldId { Name = "PATIENT" }, new FieldId { Name = "FACTOID" } };
// Construct InfoType Transformation.
var infoTypeTransformations = new InfoTypeTransformations
{
Transformations =
{
new InfoTypeTransformations.Types.InfoTypeTransformation
{
PrimitiveTransformation = new PrimitiveTransformation
{
ReplaceWithInfoTypeConfig = replaceInfoTypesConfig
},
InfoTypes = { infoTypes ?? new InfoType[] { new InfoType { Name = "PERSON_NAME" } } }
}
}
};
// Construct the de-identify config using replace config.
var deidentifyConfig = new DeidentifyConfig
{
RecordTransformations = new RecordTransformations
{
FieldTransformations =
{
new FieldTransformation
{
InfoTypeTransformations = infoTypeTransformations,
Fields = { fieldIds }
}
}
}
};
// Construct the request.
var request = new DeidentifyContentRequest
{
ParentAsLocationName = new LocationName(projectId, "global"),
DeidentifyConfig = deidentifyConfig,
Item = contentItem
};
// Call the API.
var response = dlp.DeidentifyContent(request);
// Inspect the response.
Console.WriteLine(response.Item.Table);
return response.Item.Table;
}
}
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"
)
// deidentifyTableInfotypes de-identifies table data with info types
func deidentifyTableInfotypes(w io.Writer, projectID string) error {
// projectId := "your-project-id"
row1 := &dlppb.Table_Row{
Values: []*dlppb.Value{
{Type: &dlppb.Value_StringValue{StringValue: "22"}},
{Type: &dlppb.Value_StringValue{StringValue: "Jane Austen"}},
{Type: &dlppb.Value_StringValue{StringValue: "21"}},
{Type: &dlppb.Value_StringValue{StringValue: "There are 14 kisses in Jane Austen's novels."}},
},
}
row2 := &dlppb.Table_Row{
Values: []*dlppb.Value{
{Type: &dlppb.Value_StringValue{StringValue: "55"}},
{Type: &dlppb.Value_StringValue{StringValue: "Mark Twain"}},
{Type: &dlppb.Value_StringValue{StringValue: "75"}},
{Type: &dlppb.Value_StringValue{StringValue: "Mark Twain loved cats."}},
},
}
row3 := &dlppb.Table_Row{
Values: []*dlppb.Value{
{Type: &dlppb.Value_StringValue{StringValue: "101"}},
{Type: &dlppb.Value_StringValue{StringValue: "Charles Dickens"}},
{Type: &dlppb.Value_StringValue{StringValue: "95"}},
{Type: &dlppb.Value_StringValue{StringValue: "Charles Dickens name was a curse invented by Shakespeare."}},
},
}
table := &dlppb.Table{
Headers: []*dlppb.FieldId{
{Name: "AGE"},
{Name: "PATIENT"},
{Name: "HAPPINESS SCORE"},
{Name: "FACTOID"},
},
Rows: []*dlppb.Table_Row{
{Values: row1.Values},
{Values: row2.Values},
{Values: row3.Values},
},
}
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.NewRESTClient(ctx)
if err != nil {
return err
}
// Closing the client safely cleans up background resources.
defer client.Close()
// Specify what content you want the service to de-identify.
contentItem := &dlppb.ContentItem{
DataItem: &dlppb.ContentItem_Table{
Table: table,
},
}
// Specify how the content should be de-identified.
// Select type of info to be replaced.
infoTypes := []*dlppb.InfoType{
{Name: "PERSON_NAME"},
}
// Specify that findings should be replaced with corresponding info type name.
replaceWithInfoTypeConfig := &dlppb.ReplaceWithInfoTypeConfig{}
primitiveTransformation := &dlppb.PrimitiveTransformation{
Transformation: &dlppb.PrimitiveTransformation_ReplaceWithInfoTypeConfig{
ReplaceWithInfoTypeConfig: replaceWithInfoTypeConfig,
},
}
// Associate info type with the replacement strategy
infoTypeTransformations := &dlppb.InfoTypeTransformations{
Transformations: []*dlppb.InfoTypeTransformations_InfoTypeTransformation{
{
InfoTypes: infoTypes,
PrimitiveTransformation: primitiveTransformation,
},
},
}
// Specify fields to be de-identified.
fields := []*dlppb.FieldId{
{Name: "PATIENT"},
{Name: "FACTOID"},
}
// Associate the de-identification and conditions with the specified field.
fieldTransformation := &dlppb.FieldTransformation{
Fields: fields,
Transformation: &dlppb.FieldTransformation_InfoTypeTransformations{
InfoTypeTransformations: infoTypeTransformations,
},
}
recordTransformations := &dlppb.RecordTransformations{
FieldTransformations: []*dlppb.FieldTransformation{
fieldTransformation,
},
}
// Construct the de-identification request to be sent by the client.
req := &dlppb.DeidentifyContentRequest{
Parent: fmt.Sprintf("projects/%s/locations/global", projectID),
DeidentifyConfig: &dlppb.DeidentifyConfig{
Transformation: &dlppb.DeidentifyConfig_RecordTransformations{
RecordTransformations: recordTransformations,
},
},
Item: contentItem,
}
// Send the request.
resp, err := client.DeidentifyContent(ctx, req)
if err != nil {
return err
}
// Print the results.
fmt.Fprintf(w, "Table after de-identification : %v", resp.GetItem().GetTable())
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.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.FieldId;
import com.google.privacy.dlp.v2.FieldTransformation;
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.LocationName;
import com.google.privacy.dlp.v2.PrimitiveTransformation;
import com.google.privacy.dlp.v2.RecordTransformations;
import com.google.privacy.dlp.v2.ReplaceWithInfoTypeConfig;
import com.google.privacy.dlp.v2.Table;
import com.google.privacy.dlp.v2.Table.Row;
import com.google.privacy.dlp.v2.Value;
import java.io.IOException;
import java.util.List;
import java.util.stream.Collectors;
import java.util.stream.Stream;
public class DeIdentifyTableInfoTypes {
public static void main(String[] args) throws IOException {
// TODO(developer): Replace these variables before running the sample.
String projectId = "your-project-id";
Table tableToDeIdentify =
Table.newBuilder()
.addHeaders(FieldId.newBuilder().setName("AGE").build())
.addHeaders(FieldId.newBuilder().setName("PATIENT").build())
.addHeaders(FieldId.newBuilder().setName("HAPPINESS SCORE").build())
.addHeaders(FieldId.newBuilder().setName("FACTOID").build())
.addRows(
Row.newBuilder()
.addValues(Value.newBuilder().setStringValue("101").build())
.addValues(Value.newBuilder().setStringValue("Charles Dickens").build())
.addValues(Value.newBuilder().setStringValue("95").build())
.addValues(
Value.newBuilder()
.setStringValue(
"Charles Dickens name was a curse invented by Shakespeare.")
.build())
.build())
.addRows(
Row.newBuilder()
.addValues(Value.newBuilder().setStringValue("22").build())
.addValues(Value.newBuilder().setStringValue("Jane Austen").build())
.addValues(Value.newBuilder().setStringValue("21").build())
.addValues(
Value.newBuilder()
.setStringValue("There are 14 kisses in Jane Austen's novels.")
.build())
.build())
.addRows(
Row.newBuilder()
.addValues(Value.newBuilder().setStringValue("55").build())
.addValues(Value.newBuilder().setStringValue("Mark Twain").build())
.addValues(Value.newBuilder().setStringValue("75").build())
.addValues(Value.newBuilder().setStringValue("Mark Twain loved cats.").build())
.build())
.build();
deIdentifyTableInfoTypes(projectId, tableToDeIdentify);
}
public static Table deIdentifyTableInfoTypes(String projectId, Table tableToDeIdentify)
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 de-identify.
ContentItem contentItem = ContentItem.newBuilder().setTable(tableToDeIdentify).build();
// Specify how the content should be de-identified.
// Select type of info to be replaced.
InfoType infoType = InfoType.newBuilder().setName("PERSON_NAME").build();
// Specify that findings should be replaced with corresponding info type name.
ReplaceWithInfoTypeConfig replaceWithInfoTypeConfig =
ReplaceWithInfoTypeConfig.getDefaultInstance();
PrimitiveTransformation primitiveTransformation =
PrimitiveTransformation.newBuilder()
.setReplaceWithInfoTypeConfig(replaceWithInfoTypeConfig)
.build();
// Associate info type with the replacement strategy
InfoTypeTransformation infoTypeTransformation =
InfoTypeTransformation.newBuilder()
.addInfoTypes(infoType)
.setPrimitiveTransformation(primitiveTransformation)
.build();
InfoTypeTransformations infoTypeTransformations =
InfoTypeTransformations.newBuilder().addTransformations(infoTypeTransformation).build();
// Specify fields to be de-identified.
List<FieldId> fieldIds =
Stream.of("PATIENT", "FACTOID")
.map(id -> FieldId.newBuilder().setName(id).build())
.collect(Collectors.toList());
// Associate the de-identification and conditions with the specified field.
FieldTransformation fieldTransformation =
FieldTransformation.newBuilder()
.setInfoTypeTransformations(infoTypeTransformations)
.addAllFields(fieldIds)
.build();
RecordTransformations transformations =
RecordTransformations.newBuilder().addFieldTransformations(fieldTransformation).build();
DeidentifyConfig deidentifyConfig =
DeidentifyConfig.newBuilder().setRecordTransformations(transformations).build();
// Combine configurations into a request for the service.
DeidentifyContentRequest request =
DeidentifyContentRequest.newBuilder()
.setParent(LocationName.of(projectId, "global").toString())
.setItem(contentItem)
.setDeidentifyConfig(deidentifyConfig)
.build();
// Send the request and receive response from the service.
DeidentifyContentResponse response = dlp.deidentifyContent(request);
// Print the results.
System.out.println("Table after de-identification: " + response.getItem().getTable());
return response.getItem().getTable();
}
}
}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');
// Initialize google DLP Client
const dlp = new DLP.DlpServiceClient();
// The project ID to run the API call under
// const projectId = 'my-project';
// Construct the tabular data
const tablularData = {
headers: [
{name: 'AGE'},
{name: 'PATIENT'},
{name: 'HAPPINESS SCORE'},
{name: 'FACTOID'},
],
rows: [
{
values: [
{integerValue: 101},
{stringValue: 'Charles Dickens'},
{integerValue: 95},
{
stringValue:
'Charles Dickens name was a curse invented by Shakespeare.',
},
],
},
{
values: [
{integerValue: 22},
{stringValue: 'Jane Austen'},
{integerValue: 21},
{stringValue: "There are 14 kisses in Jane Austen's novels."},
],
},
{
values: [
{integerValue: 55},
{stringValue: 'Mark Twain'},
{integerValue: 75},
{stringValue: 'Mark Twain loved cats.'},
],
},
],
};
async function deIdentifyTableWithInfoType() {
// Column that needs to be transformed
const fieldIds = [{name: 'PATIENT'}, {name: 'FACTOID'}];
// Construct InfoTypeTransformations configurations
const infoTypeTransformations = {
transformations: [
{
infoTypes: [{name: 'PERSON_NAME'}],
primitiveTransformation: {
replaceWithInfoTypeConfig: {},
},
},
],
};
// Combine configurations into a request for the service.
const request = {
parent: `projects/${projectId}/locations/global`,
item: {
table: tablularData,
},
deidentifyConfig: {
recordTransformations: {
fieldTransformations: [
{
infoTypeTransformations,
fields: fieldIds,
},
],
},
},
};
// Send the request and receive response from the service
const [response] = await dlp.deidentifyContent(request);
// Print the results
console.log(
`Table after de-identification: ${JSON.stringify(response.item.table)}`
);
}
deIdentifyTableWithInfoType();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\DeidentifyConfig;
use Google\Cloud\Dlp\V2\DeidentifyContentRequest;
use Google\Cloud\Dlp\V2\FieldId;
use Google\Cloud\Dlp\V2\FieldTransformation;
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;
use Google\Cloud\Dlp\V2\RecordTransformations;
use Google\Cloud\Dlp\V2\ReplaceWithInfoTypeConfig;
use Google\Cloud\Dlp\V2\Table;
use Google\Cloud\Dlp\V2\Table\Row;
use Google\Cloud\Dlp\V2\Value;
/**
* De-identify table data with infoTypes
*
* @param string $callingProjectId The Google Cloud project id to use as a parent resource.
* @param string $inputCsvFile The input file(csv) path to deidentify
* @param string $outputCsvFile The oupt file path to save deidentify content
*/
function deidentify_table_infotypes(
// TODO(developer): Replace sample parameters before running the code.
string $callingProjectId,
string $inputCsvFile = './test/data/table1.csv',
string $outputCsvFile = './test/data/deidentify_table_infotypes_output.csv'
): void {
// Instantiate a client.
$dlp = new DlpServiceClient();
$parent = "projects/$callingProjectId/locations/global";
// 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) {
return (new Value())
->setStringValue($csvValue);
}, explode(',', $csvRow));
return (new Row())
->setValues($rowValues);
}, $csvRows);
// Construct the table object
$tableToDeIdentify = (new Table())
->setHeaders($tableHeaders)
->setRows($tableRows);
// Specify the content to be inspected.
$content = (new ContentItem())
->setTable($tableToDeIdentify);
// Specify the type of info the inspection will look for.
$personNameInfoType = (new InfoType())
->setName('PERSON_NAME');
// Specify that findings should be replaced with corresponding info type name.
$primitiveTransformation = (new PrimitiveTransformation())
->setReplaceWithInfoTypeConfig(new ReplaceWithInfoTypeConfig());
// Associate info type with the replacement strategy
$infoTypeTransformation = (new InfoTypeTransformation())
->setPrimitiveTransformation($primitiveTransformation)
->setInfoTypes([$personNameInfoType]);
$infoTypeTransformations = (new InfoTypeTransformations())
->setTransformations([$infoTypeTransformation]);
// Specify fields to be de-identified.
$fieldIds = [
(new FieldId())->setName('PATIENT'),
(new FieldId())->setName('FACTOID'),
];
// Associate the de-identification and transformation with the specified fields.
$fieldTransformation = (new FieldTransformation())
->setInfoTypeTransformations($infoTypeTransformations)
->setFields($fieldIds);
$recordtransformations = (new RecordTransformations())
->setFieldTransformations([$fieldTransformation]);
$deidentifyConfig = (new DeidentifyConfig())
->setRecordTransformations($recordtransformations);
// Run request
$deidentifyContentRequest = (new DeidentifyContentRequest())
->setParent($parent)
->setDeidentifyConfig($deidentifyConfig)
->setItem($content);
$response = $dlp->deidentifyContent($deidentifyContentRequest);
// Print the results
$csvRef = fopen($outputCsvFile, 'w');
fputcsv($csvRef, $csvHeaders);
foreach ($response->getItem()->getTable()->getRows() as $tableRow) {
$values = array_map(function ($tableValue) {
return $tableValue->getStringValue();
}, iterator_to_array($tableRow->getValues()));
fputcsv($csvRef, $values);
};
printf('After de-identify the table data (Output File Location): %s', $outputCsvFile);
}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.
from typing import Dict, List, Union
import google.cloud.dlp
def deidentify_table_replace_with_info_types(
project: str,
table_data: Dict[str, Union[List[str], List[List[str]]]],
info_types: List[str],
deid_content_list: List[str],
) -> None:
""" Uses the Data Loss Prevention API to de-identify sensitive data in a
table by replacing them with info type.
Args:
project: The Google Cloud project id to use as a parent resource.
table_data: Json string representing table data.
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.
deid_content_list: A list of fields in table to de-identify
Returns:
None; the response from the API is printed to the terminal.
Example:
>> $ python deidentify_table_infotypes.py \
'{
"header": ["name", "email", "phone number"],
"rows": [
["Robert Frost", "robertfrost@example.com", "4232342345"],
["John Doe", "johndoe@example.com", "4253458383"]
]
}' \
["PERSON_NAME"] ["name"]
>> '{
"header": ["name", "email", "phone number"],
"rows": [
["[PERSON_NAME]", "robertfrost@example.com", "4232342345"],
["[PERSON_NAME]", "johndoe@example.com", "4253458383"]
]
}'
"""
# Instantiate a client.
dlp = google.cloud.dlp_v2.DlpServiceClient()
# Construct the `table`. For more details on the table schema, please see
# https://cloud.google.com/dlp/docs/reference/rest/v2/ContentItem#Table
headers = [{"name": val} for val in table_data["header"]]
rows = []
for row in table_data["rows"]:
rows.append({"values": [{"string_value": cell_val} for cell_val in row]})
table = {"headers": headers, "rows": rows}
# Construct item
item = {"table": table}
# Specify fields to be de-identified
deid_content_list = [{"name": _i} for _i in deid_content_list]
# Construct inspect configuration dictionary
inspect_config = {"info_types": [{"name": info_type} for info_type in info_types]}
# Construct deidentify configuration dictionary
deidentify_config = {
"record_transformations": {
"field_transformations": [
{
"info_type_transformations": {
"transformations": [
{
"primitive_transformation": {
"replace_with_info_type_config": {}
}
}
]
},
"fields": deid_content_list,
}
]
}
}
# Convert the project id into a full resource id.
parent = f"projects/{project}/locations/global"
# Call the API.
response = dlp.deidentify_content(
request={
"parent": parent,
"deidentify_config": deidentify_config,
"item": item,
"inspect_config": inspect_config,
}
)
# Print the result
print(f"Table after de-identification: {response.item.table}")
다음 단계
다른 Google Cloud 제품의 코드 샘플을 검색하고 필터링하려면 Google Cloud 샘플 브라우저를 참조하세요.