Using Cloud DLP with Cloud Storage

This page contains references to pages that provide information on how to use Cloud Data Loss Prevention (DLP) with Cloud Storage.

Quickstart guides

Quickstart: Scheduling a Cloud DLP inspection scan
Schedule periodic inspection of a Cloud Storage bucket, a BigQuery table, or a Datastore kind. For detailed instructions, see Creating and scheduling Cloud DLP inspection jobs.

How-to guides

This section provides a categorized list of task-based guides that demonstrate how to use Cloud DLP with Cloud Storage.

Inspection

Inspecting storage and databases for sensitive data
Create a one-time job that searches for sensitive data in a Cloud Storage bucket, a BigQuery table, or a Datastore kind.
Creating and scheduling Cloud DLP inspection jobs
Create and schedule a job trigger that searches for sensitive data in a Cloud Storage bucket, a BigQuery table, or a Datastore kind. A job trigger automates the creation of Cloud DLP jobs on a periodic basis.

Working with scan results

Sending Cloud DLP scan results to Security Command Center
Scan a Cloud Storage bucket, a BigQuery table, or a Datastore kind, and then send the findings to Security Command Center.
Analyzing and reporting on DLP findings
Use Cloud Storage to run analytics on Cloud DLP findings.

Tutorials

De-identification and re-identification of PII using Cloud DLP

Create an automated data transformation pipeline to de-identify sensitive data like personally identifiable information (PII). This is a four-part series containing the following topics:

Building a secure anomaly detection solution using Dataflow, BigQuery ML, and Cloud Data Loss Prevention (DLP)

Build a secure network anomaly detection solution for telecommunication networks.

Automating the classification of data uploaded to Cloud Storage

Implement an automated data quarantine and classification system using Cloud DLP, Cloud Storage, and Cloud Functions.

Community contributions

The following are owned and managed by community members, and not by the Cloud DLP team. For questions on these items, contact their respective owners.

GitHub: Speech Redaction Framework
Redact sensitive information from audio files in Cloud Storage.
GitHub: Speech Analysis Framework
Transcribe audio, create a data pipeline for analytics of transcribed audio files, and redact sensitive information from audio transcripts.
GitHub: Real-time anomaly detection using Google Cloud stream analytics and AI services
Walk through a real-time artificial intelligence (AI) pattern for detecting anomalies in log files.

Pricing

When you inspect a Cloud Storage bucket, you incur Cloud DLP costs, according to the storage inspection job pricing.