This page contains references to pages that provide information on how to use Cloud Data Loss Prevention (DLP) with Cloud Storage.
- 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.
This section provides a categorized list of task-based guides that demonstrate how to use Cloud DLP with Cloud Storage.
- 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.
- 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.
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.
When you inspect a Cloud Storage bucket, you incur Cloud DLP costs, according to the storage inspection job pricing.