Desidentificar dados usando o agrupamento por classes de tabela

Transformar uma coluna sem inspeção. Para transformar uma coluna com um conteúdo já conhecido, pule a inspeção e especifique uma transformação diretamente.

Mais informações

Para ver a documentação detalhada que inclui este exemplo de código, consulte:

Exemplo de código

C#

Para saber como instalar e usar a biblioteca de cliente para proteção de dados sensíveis, consulte Bibliotecas de cliente de proteção de dados sensíveis.

Para usar a proteção de dados sensíveis, configure o Application Default Credentials. Para mais informações, consulte Configurar a autenticação para um ambiente de desenvolvimento local.


using System;
using Google.Api.Gax.ResourceNames;
using Google.Cloud.Dlp.V2;

public class DeidentifyUsingTableBucketing
{
    public static Table DeidentifyData(
        string projectId,
        Table tableToInspect = null)
    {
        // Instantiate dlp 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" }
            };
            var row2 = new Value[]
            {
                new Value { StringValue = "22" },
                new Value { StringValue = "Jane Austin" },
                new Value { StringValue = "21" }
            };
            var row3 = new Value[]
            {
                new Value { StringValue = "55" },
                new Value { StringValue = "Mark Twain" },
                new Value { StringValue = "75" }
            };

            tableToInspect = new Table
            {
                Headers =
                {
                    new FieldId { Name = "AGE" },
                    new FieldId { Name = "PATIENT" },
                    new FieldId { Name = "HAPPINESS SCORE" }
                },
                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 };

        // Specify how the content should be de-identified.
        var fixedSizeBucketingConfig = new FixedSizeBucketingConfig
        {
            BucketSize = 10,
            LowerBound = new Value { IntegerValue = 0 },
            UpperBound = new Value { IntegerValue = 100 },
        };

        // Specify the fields to be encrypted.
        var fields = new FieldId[] { new FieldId { Name = "HAPPINESS SCORE" } };

        // Associate the encryption with the specified field.
        var fieldTransformation = new FieldTransformation
        {
            PrimitiveTransformation = new PrimitiveTransformation
            {
                FixedSizeBucketingConfig = fixedSizeBucketingConfig
            },
            Fields = { fields }
        };

        // Construct the deidentify config.
        var deidentifyConfig = new DeidentifyConfig
        {
            RecordTransformations = new RecordTransformations
            {
                FieldTransformations = { fieldTransformation }
            }
        };

        // 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

Para saber como instalar e usar a biblioteca de cliente para proteção de dados sensíveis, consulte Bibliotecas de cliente de proteção de dados sensíveis.

Para usar a proteção de dados sensíveis, configure o Application Default Credentials. Para mais informações, consulte Configurar a autenticação para um ambiente de desenvolvimento local.

import (
	"context"
	"fmt"
	"io"

	dlp "cloud.google.com/go/dlp/apiv2"
	"cloud.google.com/go/dlp/apiv2/dlppb"
)

// deIdentifyTableBucketing de-identifies data using table bucketing
func deIdentifyTableBucketing(w io.Writer, projectID string) error {
	// projectId := "your-project-id"
	// table := "your-table-value"

	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"}},
		},
	}

	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"}},
		},
	}

	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"}},
		},
	}

	table := &dlppb.Table{
		Headers: []*dlppb.FieldId{
			{Name: "AGE"},
			{Name: "PATIENT"},
			{Name: "HAPPINESS SCORE"},
		},
		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.NewClient(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.
	fixedSizeBucketingConfig := &dlppb.FixedSizeBucketingConfig{
		BucketSize: 10,
		LowerBound: &dlppb.Value{
			Type: &dlppb.Value_IntegerValue{
				IntegerValue: 0,
			},
		},
		UpperBound: &dlppb.Value{
			Type: &dlppb.Value_IntegerValue{
				IntegerValue: 100,
			},
		},
	}
	primitiveTransformation := &dlppb.PrimitiveTransformation_FixedSizeBucketingConfig{
		FixedSizeBucketingConfig: fixedSizeBucketingConfig,
	}

	// Specify field to be encrypted.
	fieldId := &dlppb.FieldId{
		Name: "HAPPINESS SCORE",
	}

	// Associate the encryption with the specified field.
	fieldTransformation := &dlppb.FieldTransformation{
		Transformation: &dlppb.FieldTransformation_PrimitiveTransformation{
			PrimitiveTransformation: &dlppb.PrimitiveTransformation{
				Transformation: primitiveTransformation,
			},
		},
		Fields: []*dlppb.FieldId{
			fieldId,
		},
	}

	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

Para saber como instalar e usar a biblioteca de cliente para proteção de dados sensíveis, consulte Bibliotecas de cliente de proteção de dados sensíveis.

Para usar a proteção de dados sensíveis, configure o Application Default Credentials. Para mais informações, consulte Configurar a autenticação para um ambiente de desenvolvimento local.


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.FixedSizeBucketingConfig;
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.Table.Row;
import com.google.privacy.dlp.v2.Value;
import java.io.IOException;

public class DeIdentifyTableBucketing {

  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())
            .addRows(
                Row.newBuilder()
                    .addValues(Value.newBuilder().setStringValue("101").build())
                    .addValues(Value.newBuilder().setStringValue("Charles Dickens").build())
                    .addValues(Value.newBuilder().setStringValue("95").build())
                    .build())
            .addRows(
                Row.newBuilder()
                    .addValues(Value.newBuilder().setStringValue("22").build())
                    .addValues(Value.newBuilder().setStringValue("Jane Austen").build())
                    .addValues(Value.newBuilder().setStringValue("21").build())
                    .build())
            .addRows(
                Row.newBuilder()
                    .addValues(Value.newBuilder().setStringValue("55").build())
                    .addValues(Value.newBuilder().setStringValue("Mark Twain").build())
                    .addValues(Value.newBuilder().setStringValue("75").build())
                    .build())
            .build();

    deIdentifyTableBucketing(projectId, tableToDeIdentify);
  }

  public static Table deIdentifyTableBucketing(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.
      FixedSizeBucketingConfig fixedSizeBucketingConfig =
          FixedSizeBucketingConfig.newBuilder()
              .setBucketSize(10)
              .setLowerBound(Value.newBuilder().setIntegerValue(0).build())
              .setUpperBound(Value.newBuilder().setIntegerValue(100).build())
              .build();
      PrimitiveTransformation primitiveTransformation =
          PrimitiveTransformation.newBuilder()
              .setFixedSizeBucketingConfig(fixedSizeBucketingConfig)
              .build();

      // Specify field to be encrypted.
      FieldId fieldId = FieldId.newBuilder().setName("HAPPINESS SCORE").build();

      // Associate the encryption with the specified field.
      FieldTransformation fieldTransformation =
          FieldTransformation.newBuilder()
              .setPrimitiveTransformation(primitiveTransformation)
              .addFields(fieldId)
              .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

Para saber como instalar e usar a biblioteca de cliente para proteção de dados sensíveis, consulte Bibliotecas de cliente de proteção de dados sensíveis.

Para usar a proteção de dados sensíveis, configure o Application Default Credentials. Para mais informações, consulte Configurar a autenticação para um ambiente de desenvolvimento local.

// 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'}],
  rows: [
    {
      values: [
        {integerValue: 101},
        {stringValue: 'Charles Dickens'},
        {integerValue: 95},
      ],
    },
    {
      values: [
        {integerValue: 22},
        {stringValue: 'Jane Austen'},
        {integerValue: 21},
      ],
    },
    {
      values: [
        {integerValue: 55},
        {stringValue: 'Mark Twain'},
        {integerValue: 75},
      ],
    },
  ],
};
async function deIdentifyTableBucketing() {
  // Specify field to be de-identified.
  const targetColumn = {name: 'HAPPINESS SCORE'};

  // Specify how the content should be de-identified.
  const bucketingConfig = {
    bucketSize: 10,
    lowerBound: {
      integerValue: 0,
    },
    upperBound: {
      integerValue: 100,
    },
  };

  const primitiveTransformation = {
    fixedSizeBucketingConfig: bucketingConfig,
  };

  // Combine configurations into a request for the service.
  const request = {
    parent: `projects/${projectId}/locations/global`,
    item: {
      table: tablularData,
    },
    deidentifyConfig: {
      recordTransformations: {
        fieldTransformations: [
          {
            fields: [targetColumn],
            primitiveTransformation,
          },
        ],
      },
    },
  };
  // 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)}`
  );
}

deIdentifyTableBucketing();

PHP

Para saber como instalar e usar a biblioteca de cliente para proteção de dados sensíveis, consulte Bibliotecas de cliente de proteção de dados sensíveis.

Para usar a proteção de dados sensíveis, configure o Application Default Credentials. Para mais informações, consulte Configurar a autenticação para um ambiente de desenvolvimento local.

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\FixedSizeBucketingConfig;
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;

/**
 * De-identify data using table bucketing
 * Transform a column without inspection. To transform a column in which the content is
 * already known, you can skip inspection and specify a transformation directly.
 *
 * @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_bucketing(
    // TODO(developer): Replace sample parameters before running the code.
    string $callingProjectId,
    string $inputCsvFile = './test/data/table2.csv',
    string $outputCsvFile = './test/data/deidentify_table_bucketing_output.csv'
): 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) {
            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 what content you want the service to de-identify.
    $contentItem = (new ContentItem())
        ->setTable($tableToDeIdentify);

    // Specify how the content should be de-identified.
    $fixedSizeBucketingConfig = (new FixedSizeBucketingConfig())
        ->setBucketSize(10)
        ->setLowerBound((new Value())
            ->setIntegerValue(10))
        ->setUpperBound((new Value())
            ->setIntegerValue(100));

    $primitiveTransformation = (new PrimitiveTransformation())
        ->setFixedSizeBucketingConfig($fixedSizeBucketingConfig);

    // Specify the field to to apply bucketing transform on
    $fieldId = (new FieldId())
        ->setName('HAPPINESS_SCORE');

    // Associate the encryption with the specified field.
    $fieldTransformation = (new FieldTransformation())
        ->setPrimitiveTransformation($primitiveTransformation)
        ->setFields([$fieldId]);

    $recordTransformations = (new RecordTransformations())
        ->setFieldTransformations([$fieldTransformation]);

    // Create the deidentification configuration object
    $deidentifyConfig = (new DeidentifyConfig())
        ->setRecordTransformations($recordTransformations);

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

    // Run request
    $deidentifyContentRequest = (new DeidentifyContentRequest())
        ->setParent($parent)
        ->setDeidentifyConfig($deidentifyConfig)
        ->setItem($contentItem);
    $response = $dlp->deidentifyContent($deidentifyContentRequest);

    // Print 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, $values);
    };
    printf($outputCsvFile);
}

Python

Para saber como instalar e usar a biblioteca de cliente para proteção de dados sensíveis, consulte Bibliotecas de cliente de proteção de dados sensíveis.

Para usar a proteção de dados sensíveis, configure o Application Default Credentials. Para mais informações, consulte Configurar a autenticação para um ambiente de desenvolvimento local.

from typing import Dict, List, Union

import google.cloud.dlp
from google.cloud.dlp_v2 import types

def deidentify_table_bucketing(
    project: str,
    table_data: Dict[str, Union[List[str], List[List[str]]]],
    deid_content_list: List[str],
    bucket_size: int,
    bucketing_lower_bound: int,
    bucketing_upper_bound: int,
) -> types.dlp.Table:
    """Uses the Data Loss Prevention API to de-identify sensitive data in a
    table by replacing them with fixed size bucket ranges.
    Args:
        project: The Google Cloud project id to use as a parent resource.
        table_data: Dictionary representing table data.
        deid_content_list: A list of fields in table to de-identify.
        bucket_size: Size of each bucket for fixed sized bucketing
            (except for minimum and maximum buckets). So if ``bucketing_lower_bound`` = 10,
            ``bucketing_upper_bound`` = 89, and ``bucket_size`` = 10, then the
            following buckets would be used: -10, 10-20, 20-30, 30-40,
            40-50, 50-60, 60-70, 70-80, 80-89, 89+.
       bucketing_lower_bound: Lower bound value of buckets.
       bucketing_upper_bound:  Upper bound value of buckets.

    Returns:
       De-identified table is returned;
       the response from the API is also printed to the terminal.

    Example:
    >> $ python deidentify_table_bucketing.py \
        '{"header": ["email", "phone number", "age"],
        "rows": [["robertfrost@example.com", "4232342345", "35"],
        ["johndoe@example.com", "4253458383", "68"]]}' \
        ["age"] 10 0 100
        >>  '{"header": ["email", "phone number", "age"],
            "rows": [["robertfrost@example.com", "4232342345", "30:40"],
            ["johndoe@example.com", "4253458383", "60:70"]]}'
    """

    # 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 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 the `item`.
    item = {"table": table}

    # Construct fixed sized bucketing configuration
    fixed_size_bucketing_config = {
        "bucket_size": bucket_size,
        "lower_bound": {"integer_value": bucketing_lower_bound},
        "upper_bound": {"integer_value": bucketing_upper_bound},
    }

    # Specify fields to be de-identified
    deid_content_list = [{"name": _i} for _i in deid_content_list]

    # Construct Deidentify Config
    deidentify_config = {
        "record_transformations": {
            "field_transformations": [
                {
                    "fields": deid_content_list,
                    "primitive_transformation": {
                        "fixed_size_bucketing_config": fixed_size_bucketing_config
                    },
                }
            ]
        }
    }

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

    # Print the results.
    print(f"Table after de-identification: {response.item.table}")

    # Return the response.
    return response.item.table

A seguir

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