De-identifying sensitive data

Cloud Data Loss Prevention (DLP) can de-identify sensitive data in text content, including text stored in container structures such as tables. De-identification is the process of removing identifying information from data. The API detects sensitive data such as personally identifiable information (PII), and then uses a de-identification transformation to mask, delete, or otherwise obscure the data. For example, de-identification techniques can include any of the following:

  • Masking sensitive data by partially or fully replacing characters with a symbol, such as an asterisk (*) or hash (#).
  • Replacing each instance of sensitive data with a token, or surrogate, string.
  • Encrypting and replacing sensitive data using a randomly generated or pre-determined key.

When you de-identify data using the CryptoReplaceFfxFpeConfig or CryptoDeterministicConfig infoType transformations, you can re-identify that data, as long as you have the CryptoKey used to originally de-identify the data.

You can feed information to the API using JSON over HTTPS, as well as the CLI and several programming languages using the DLP client libraries. To set up the CLI, refer to the quickstart. For more information about submitting information in JSON format, see the JSON quickstart.

API overview

To de-identify sensitive data, use Cloud DLP's content.deidentify method.

There are three parts to a de-identification API call:

  • The data to inspect: A string or table structure (ContentItem object) for the API to inspect.
  • What to inspect for: Detection configuration information (InspectConfig) such as what types of data (or infoTypes) to look for, whether to filter findings that are above a certain likelihood threshold, whether to return no more than a certain number of results, and so on. Not specifying at least one infoType in an InspectConfig argument is equivalent to specifying all built-in infoTypes. Doing so is not recommended, as it can cause decreased performance and increased cost.
  • What to do with the inspection findings: Configuration information (DeidentifyConfig) that defines how you want the sensitive data de-identified. This argument is covered in more detail in the following section.

The API returns the same items you gave it, in the same format, but any text identified as containing sensitive information according to your criteria has been de-identified.

Specifying detection criteria

Information type (or "infoType") detectors are the mechanisms that Cloud DLP uses to find sensitive data.

Cloud DLP includes several kinds of infoType detectors, all of which are summarized here:

  • Built-in infoType detectors are built into Cloud DLP. They include detectors for country- or region-specific sensitive data types as well as globally applicable data types.
  • Custom infoType detectors are detectors that you create yourself. There are three kinds of custom infoType detectors:
    • Regular custom dictionary detectors are simple word lists that Cloud DLP matches on. Use regular custom dictionary detectors when you have a list of up to several tens of thousands of words or phrases. Regular custom dictionary detectors are preferred if you don't anticipate your word list changing significantly.
    • Stored custom dictionary detectors are generated by Cloud DLP using large lists of words or phrases stored in either Cloud Storage or BigQuery. Use stored custom dictionary detectors when you have a large list of words or phrases—up to tens of millions.
    • Regular expressions (regex) detectors enable Cloud DLP to detect matches based on a regular expression pattern.

In addition, Cloud DLP includes the concept of inspection rules, which enable you to fine-tune scan results using the following:

  • Exclusion rules enable you to decrease the number of findings returned by adding rules to a built-in or custom infoType detector.
  • Hotword rules enable you to increase the quantity or change the likelihood value of findings returned by adding rules to a built-in or custom infoType detector.

De-identification transformations

You must specify one or more transformations when you set the de-identification configuration (DeidentifyConfig). There are two categories of transformations:

  • InfoTypeTransformations: Transformations that are only applied to values within submitted text that are identified as a specific infoType.
  • RecordTransformations: Transformations that are only applied to values within submitted tabular text data that are identified as a specific infoType, or on an entire column of tabular data.

InfoType transformations

You can specify one or more infoType transformations per request. Within each InfoTypeTransformation object, you specify both of the following:

  • One or more infoTypes to which a transformation should be applied (the infoTypes[] array object).
  • A primitive transformation (the PrimitiveTransformation object).

Note that specifying an infoType is optional, but not specifying at least one infoType in an InspectConfig argument causes the transformation to apply to all built-in infoTypes that don't have a transformation provided. Doing so is not recommended, as it can cause decreased performance and increased cost.

Primitive transformations

You must specify at least one primitive transformation to apply to input, regardless of whether you're applying it only to certain infoTypes or to the entire text string. You have several transformation options, which are summarized in the following table. Click the object name for more information.

The full list of possible transformations.

replaceConfig

Setting replaceConfig to a ReplaceValueConfig object replaces matched input values with a value you specify.

For example, suppose you’ve set replaceConfig to "[email-address]" for all EMAIL_ADDRESS infoTypes, and the following string is sent to Cloud DLP:

My name is Alicia Abernathy, and my email address is aabernathy@example.com.

The returned string will be the following:

My name is Alicia Abernathy, and my email address is [email-address].

The following JSON example and code in several languages shows how to form the API request and what the Cloud DLP API returns:

Protocol

See the JSON quickstart for more information about using the Cloud DLP API with JSON.

JSON Input:

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 Output:

{
  "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"
      }
    ]
  }
}

Python

def deidentify_with_replace(
    project, input_str, info_types, replacement_str="REPLACEMENT_STR",
):
    """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.
    """
    import google.cloud.dlp

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

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

    # 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


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());
    }
  }
}
redactConfig

Specifying redactConfig redacts a given value by removing it completely. The redactConfig message has no arguments; specifying it enables its transformation.

For example, suppose you’ve specified redactConfig for all EMAIL_ADDRESS infoTypes, and the following string is sent to Cloud DLP:

My name is Alicia Abernathy, and my email address is aabernathy@example.com.

The returned string will be the following:

My name is Alicia Abernathy, and my email address is .

The following examples show how to form the API request and what the Cloud DLP API returns:

Protocol

JSON Input:

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 Output:

{
  "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"
      }
    ]
  }
}

Java


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());
    }
  }
}

Python

def deidentify_with_redact(
    project, input_str, info_types,
):
    """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.
    """
    import google.cloud.dlp

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

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

    # 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)

characterMaskConfig

Setting characterMaskConfig to a CharacterMaskConfig object partially masks a string by replacing a given number of characters with a fixed character. Masking can start from the beginning or end of the string. This transformation also works with number types such as long integers.

The CharacterMaskConfig object has several of its own arguments:

  • maskingCharacter: The character to use to mask each character of a sensitive value. For example, you could specify an asterisk (*) or hash (#) to mask a series of numbers such as those in a credit card number.
  • numberToMask: The number of characters to mask. If you don’t set this value, all matching characters will be masked.
  • reverseOrder: Whether to mask characters in reverse order. Setting reverseOrder to true causes characters in matched values to be masked from the end toward the beginning of the value. Setting it to false causes masking to begin at the start of the value.
  • charactersToIgnore[]: One or more characters to skip when masking values. For example, specify a hyphen here to leave the hyphens in place when masking a telephone number. You can also specify a group of common characters (CharsToIgnore) to ignore when masking.

For example, suppose you've set characterMaskConfig to mask with '#' for EMAIL_ADDRESS infotypes, except for the '.' and '@' characters. If the following string is sent to Cloud DLP:

My name is Alicia Abernathy, and my email address is aabernathy@example.com.

The returned string will be the following:

My name is Alicia Abernathy, and my email address is ##########@#######.###.

Following are examples that demonstrate how to use the Cloud DLP API to de-identify sensitive data using masking techniques.

Protocol

The following JSON example shows how to form the API request and what the Cloud DLP API returns:

JSON Input:

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 Output:

{
  "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"
      }
    ]
  }
}

Java


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 com.google.privacy.dlp.v2.ReplaceWithInfoTypeConfig;
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()
              .setReplaceWithInfoTypeConfig(ReplaceWithInfoTypeConfig.getDefaultInstance())
              .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

// 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

def deidentify_with_mask(
    project, input_str, info_types, masking_character=None, number_to_mask=0
):
    """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).
        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.
    """

    # Import the client library
    import google.cloud.dlp

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

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

    # 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

import (
	"context"
	"fmt"
	"io"

	dlp "cloud.google.com/go/dlp/apiv2"
	dlppb "google.golang.org/genproto/googleapis/privacy/dlp/v2"
)

// 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: %v", err)
	}
	// 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: %v", err)
	}
	// Print the result.
	fmt.Fprint(w, r.GetItem().GetValue())
	return nil
}

PHP

/**
 * Deidentify sensitive data in a string by masking it with a character.
 */
use Google\Cloud\Dlp\V2\CharacterMaskConfig;
use Google\Cloud\Dlp\V2\DlpServiceClient;
use Google\Cloud\Dlp\V2\InfoType;
use Google\Cloud\Dlp\V2\PrimitiveTransformation;
use Google\Cloud\Dlp\V2\DeidentifyConfig;
use Google\Cloud\Dlp\V2\InfoTypeTransformations\InfoTypeTransformation;
use Google\Cloud\Dlp\V2\InfoTypeTransformations;
use Google\Cloud\Dlp\V2\ContentItem;

/** Uncomment and populate these variables in your code */
// $callingProjectId = 'The GCP Project ID to run the API call under';
// $string = 'The string to deidentify';
// $numberToMask = 0; // (Optional) The maximum number of sensitive characters to mask in a match
// $maskingCharacter = 'x'; // (Optional) The character to mask matching sensitive data with

// 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
$response = $dlp->deidentifyContent([
    'parent' => $parent,
    'deidentifyConfig' => $deidentifyConfig,
    'item' => $item
]);

// Print the results
$deidentifiedValue = $response->getItem()->getValue();
print($deidentifiedValue);

C#


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;
    }
}

cryptoHashConfig

Setting cryptoHashConfig to a CryptoHashConfig object performs pseudonymization on an input value by generating a surrogate value using cryptographic hashing.

This method replaces the input value with an encrypted "digest," or hash value. The digest is computed by taking the SHA-256 hash of the input value. The cryptographic key used to make the hash is a CryptoKey object, and must be either 32 or 64 bytes in size.

The method outputs a base64-encoded representation of the hashed output. Currently, only string and integer values can be hashed.

For example, suppose you’ve specified cryptoHashConfig for all EMAIL_ADDRESS infoTypes, and the CryptoKey object consists of a randomly-generated key (a TransientCryptoKey). Then, the following string is sent to Cloud DLP:

My name is Alicia Abernathy, and my email address is aabernathy@example.com.

The cryptographically generated returned string will look like the following:

My name is Alicia Abernathy, and my email address is 41D1567F7F99F1DC2A5FAB886DEE5BEE.

Of course, the hex string will be cryptographically generated and different from the one shown here.

dateShiftConfig

Setting dateShiftConfig to a DateShiftConfig object performs date shifting on a date input value by shifting the dates by a random number of days.

Date shifting techniques randomly shift a set of dates but preserve the sequence and duration of a period of time. Shifting dates is usually done in context to an individual or an entity. That is, you want to shift all of the dates for a specific individual using the same shift differential, but use a separate shift differential for each other individual.

For more information about date shifting, see the date shifting concept topic.

Following is sample code in several languages that demonstrates how to use the Cloud DLP API to de-identify dates using date shifting.

Java


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

// 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

def deidentify_with_date_shift(
    project,
    input_csv_file=None,
    output_csv_file=None,
    date_fields=None,
    lower_bound_days=None,
    upper_bound_days=None,
    context_field_id=None,
    wrapped_key=None,
    key_name=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.
    """
    # Import the client library
    import google.cloud.dlp

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

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

    # Convert date field list to Protobuf type
    def map_fields(field):
        return {"name": field}

    if date_fields:
        date_fields = map(map_fields, date_fields)
    else:
        date_fields = []

    # Read and parse the CSV file
    import csv
    from datetime import datetime

    f = []
    with open(input_csv_file, "r") 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):
        return {"name": header}

    def map_data(value):
        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):
        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:
        import base64

        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):
        return header.name

    def write_data(data):
        return data.string_value or "%s/%s/%s" % (
            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("Successfully saved date-shift output to {}".format(output_csv_file))

Go

import (
	"context"
	"fmt"
	"io"

	dlp "cloud.google.com/go/dlp/apiv2"
	dlppb "google.golang.org/genproto/googleapis/privacy/dlp/v2"
)

// 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: %v", err)
	}
	// 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: %v", err)
	}
	// Print the result.
	fmt.Fprint(w, r.GetItem().GetValue())
	return nil
}

PHP

/**
 * Deidentify dates in a CSV file by pseudorandomly shifting them.
 */
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\DlpServiceClient;
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;

/** Uncomment and populate these variables in your code */
// $callingProject = 'The GCP Project ID to run the API call under';
// $inputCsvFile = 'The path to the CSV file to deidentify';
// $outputCsvFile = 'The path to save the date-shifted CSV file to';
// $dateFieldNames = 'The comma-separated list of (date) fields in the CSV file to date shift';
// $lowerBoundDays = 'The maximum number of days to shift a date backward';
// $upperBoundDays = 'The maximum number of days to shift a date forward';
/**
 * 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
 */
// $contextFieldName = ''; (Optional) The column to determine date shift amount based on
// $keyName = ''; // Optional) The encrypted ('wrapped') AES-256 key to use when shifting dates
// $wrappedKey = ''; // (Optional) The name of the Cloud KMS key used to encrypt (wrap) the AES-256 key

// 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
$response = $dlp->deidentifyContent([
    'parent' => $parent,
    'deidentifyConfig' => $deidentifyConfig,
    'item' => $item
]);

// 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#


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

Setting cryptoReplaceFfxFpeConfig to a CryptoReplaceFfxFpeConfig object performs pseudonymization on an input value by replacing an input value with a token. This token is:

  • The encrypted input value.
  • The same length as the input value.
  • Computed using format-preserving encryption in FFX mode ("FPE-FFX") keyed on the cryptographic key specified by cryptoKey.
  • Comprised of the characters specified by alphabet. Valid options:
    • NUMERIC
    • HEXADECIMAL
    • UPPER_CASE_ALPHA_NUMERIC
    • ALPHA_NUMERIC

The input value:

  • Must be at least two characters long (or the empty string).
  • Must be comprised of the characters specified by an alphabet. The alphabet can be comprised of between 2 and 95 characters. (An alphabet with 95 characters includes all printable characters in the US-ASCII character set.)

Cloud DLP computes the replacement token using a cryptographic key. You provide this key in one of three ways:

  1. By requesting that the Cloud DLP generate it.
  2. By embedding it encrypted in the API request. For this option, the key is wrapped (encrypted) by a Cloud Key Management Service (Cloud KMS) key.
  3. By embedding it unencrypted in the API request. (Not recommended.)

To create a Cloud KMS wrapped key, you send a request containing a 16-, 24-, or 32-byte plaintext field value to the Cloud KMS projects.locations.keyRings.cryptoKeys.encrypt method. The wrapped key is the value in the ciphertext field of the method's response.

The value is a base64-encoded string by default. To set this value in Cloud DLP, it must be decoded into a byte string. The following code snippets highlight how to do this in several languages. End-to-end examples are provided following these snippets.

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)

For more information about encrypting and decrypting data using Cloud KMS, see Encrypting and Decrypting Data.

Following is sample code in several languages that demonstrates how to use Cloud DLP to de-identify sensitive data by replacing an input value with a token.

Java


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 email is gary@example.com";
    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

// 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



def deidentify_with_fpe(
    project,
    input_str,
    info_types,
    alphabet=None,
    surrogate_type=None,
    key_name=None,
    wrapped_key=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).
        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.
    """
    # Import the client library
    import google.cloud.dlp

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

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

    # 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)

    # 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

import (
	"context"
	"fmt"
	"io"
	"io/ioutil"

	dlp "cloud.google.com/go/dlp/apiv2"
	dlppb "google.golang.org/genproto/googleapis/privacy/dlp/v2"
)

// 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, keyFileName, cryptoKeyName, surrogateInfoType string) error {
	// projectID := "my-project-id"
	// input := "My SSN is 123456789"
	// infoTypeNames := []string{"US_SOCIAL_SECURITY_NUMBER"}
	// keyFileName := "projects/YOUR_GCLOUD_PROJECT/locations/YOUR_LOCATION/keyRings/YOUR_KEYRING_NAME/cryptoKeys/YOUR_KEY_NAME"
	// cryptoKeyName := "YOUR_ENCRYPTED_AES_256_KEY"
	// surrogateInfoType := "AGE"
	ctx := context.Background()
	client, err := dlp.NewClient(ctx)
	if err != nil {
		return fmt.Errorf("dlp.NewClient: %v", err)
	}
	// 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})
	}
	// Read the key file.
	keyBytes, err := ioutil.ReadFile(keyFileName)
	if err != nil {
		return fmt.Errorf("ReadFile: %v", 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:    keyBytes,
													CryptoKeyName: cryptoKeyName,
												},
											},
										},
										// 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: %v", err)
	}
	// Print the result.
	fmt.Fprint(w, r.GetItem().GetValue())
	return nil
}

PHP

/**
 * Deidentify a string using Format-Preserving Encryption (FPE).
 */
use Google\Cloud\Dlp\V2\CryptoReplaceFfxFpeConfig;
use Google\Cloud\Dlp\V2\CryptoReplaceFfxFpeConfig\FfxCommonNativeAlphabet;
use Google\Cloud\Dlp\V2\CryptoKey;
use Google\Cloud\Dlp\V2\DlpServiceClient;
use Google\Cloud\Dlp\V2\PrimitiveTransformation;
use Google\Cloud\Dlp\V2\KmsWrappedCryptoKey;
use Google\Cloud\Dlp\V2\InfoType;
use Google\Cloud\Dlp\V2\DeidentifyConfig;
use Google\Cloud\Dlp\V2\InfoTypeTransformations\InfoTypeTransformation;
use Google\Cloud\Dlp\V2\InfoTypeTransformations;
use Google\Cloud\Dlp\V2\ContentItem;

/** Uncomment and populate these variables in your code */
// $callingProjectId = 'The GCP Project ID to run the API call under';
// $string = 'The string to deidentify';
// $keyName = 'The name of the Cloud KMS key used to encrypt (wrap) the AES-256 key';
// $wrappedKey = 'The name of the Cloud KMS key use, encrypted with the KMS key in $keyName';
// $surrogateTypeName = ''; // (Optional) surrogate custom info type to enable reidentification

// 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
$response = $dlp->deidentifyContent([
    'parent' => $parent,
    'deidentifyConfig' => $deidentifyConfig,
    'item' => $content
]);

// Print the results
$deidentifiedValue = $response->getItem()->getValue();
print($deidentifiedValue);

C#


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;
    }
}

fixedSizeBucketingConfig

The bucketing transformations—this one and bucketingConfig—serve to mask numerical data by “bucketing” it into ranges. The resulting number range is a hyphenated string consisting of a lower bound, a hyphen, and an upper bound.

Setting fixedSizeBucketingConfig to a FixedSizeBucketingConfig object buckets input values based on fixed size ranges. The FixedSizeBucketingConfig object consists of the following:

  • lowerBound: The lower bound value of all of the buckets. Values less than this one are grouped together in a single bucket.
  • upperBound: The upper bound value of all of the buckets. Values greater than this one are grouped together in a single bucket.
  • bucketSize: The size of each bucket other than the minimum and maximum buckets.

For example, if lowerBound is set to 10, upperBound is set to 89, and bucketSize is set to 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+.

For more information about the concept of bucketing, see Generalization and Bucketing.

bucketingConfig

The bucketingConfig transformation offers more flexibility than the other bucketing transformation, fixedSizeBucketingConfig. Instead of specifying upper and lower bounds and an interval value with which to create equal-sized buckets, you specify the maximum and minimum values for each bucket you want created. Each maximum and minimum value pair must have the same type.

Setting bucketingConfig to a BucketingConfig object specifies custom buckets. The BucketingConfig object consists of a buckets[] array of Bucket objects. Each Bucket object consists of the following:

  • min: The lower bound of the bucket’s range. Omit this value to create a bucket that has no lower bound.
  • max: The upper bound of the bucket’s range. Omit this value to create a bucket that has no upper bound.
  • replacementValue: The value with which to replace values that fall within the lower and upper bounds. If you don’t provide a replacementValue, a hyphenated min-max range will be used instead.

If a value falls outside of the defined ranges, the TransformationSummary returned will contain an error message.

For example, consider the following configuration for the bucketingConfig transformation:

"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"
      }
    }
  ]
}

This defines the following behavior:

  • Integer values falling between 1 and 30 are masked by being replaced with LOW.
  • Integer values falling between 31-65 are masked by being replaced with MEDIUM.
  • Integer values falling between 66-100 are masked by being replaced with HIGH.

For more information about the concept of bucketing, see Generalization and Bucketing.

replaceWithInfoTypeConfig

Specifying replaceWithInfoTypeConfig replaces each matched value with the name of the infoType. The replaceWithInfoTypeConfig message has no arguments; specifying it enables its transformation.

For example, suppose you’ve specified replaceWithInfoTypeConfig for all EMAIL_ADDRESS infoTypes, and the following string is sent to Cloud DLP:

My name is Alicia Abernathy, and my email address is aabernathy@example.com.

The returned string will be the following:

My name is Alicia Abernathy, and my email address is EMAIL_ADDRESS.
timePartConfig

Setting timePartConfig to a TimePartConfig object preserves a portion of a matched value that includes Date, Timestamp, and TimeOfDay values. The TimePartConfig object consists of a partToExtract argument, which can be set to any of the TimePart enumerated values, including year, month, day of the month, and so on.

For example, suppose you’ve configured a timePartConfig transformation by setting partToExtract to YEAR. After sending the data in the first column below to Cloud DLP, you'd end up with the transformed values in the second column:

Original values Transformed values
9/21/1976 1976
6/7/1945 1945
1/20/2009 2009
7/4/1776 1776
8/1/1984 1984
4/21/1982 1982

Record transformations

Record transformations (the RecordTransformations object) are only applied to values within tabular data that are identified as a specific infoType. Within RecordTransformations, there are two further subcategories of transformations:

  • fieldTransformations[]: Transformations that apply various field transformations.
  • recordSuppressions[]: Rules defining which records get suppressed completely. Records that match any suppression rule within recordSuppressions[] are omitted from the output.

Field transformations

Each FieldTransformation object includes three arguments:

  • fields: One or more input fields (FieldID objects) to apply the transformation to.
  • condition: A condition (a RecordCondition object) that must evaluate to true for the transformation to be applied. For example, apply a bucket transformation to an age column of a record only if the ZIP code column for the same record is within a specific range. Or, redact a field only if the birthdate field puts a person's age at 85 or above.
  • One of the following two transformation type arguments. Specifying one is required:

Record suppressions

In addition to applying transformations to field data, you can also instruct Cloud DLP to de-identify data by simply suppressing records when certain suppression conditions evaluate to true. You can apply both field transformations and record suppressions in the same request.

You set the recordSuppressions message of the RecordTransformations object to an array of one or more RecordSuppression objects.

Each RecordSuppression object contains a single RecordCondition object, which in turn contains a single Expressions object.

An Expressions object contains:

  • logicalOperator: One of the LogicalOperator enumerated types.
  • conditions: A Conditions object, containing an array of one or more Condition objects. A Condition is a comparison of a field value and another value, both of which be of type string, boolean, integer, double, Timestamp, or TimeofDay.

If the comparison evaluates to true, the record is suppressed, and vice-versa. If the compared values are not the same type, a warning is given and the condition evaluates to false.