Gain visibility into the data you store and process
Create dashboards and audit reports. Automate tagging, remediation, or policy based on findings. Connect DLP results into Security Command Center, Data Catalog, or export to your own SIEM or governance tool.
Configure data inspection and monitoring with ease
Schedule inspection jobs directly in the console UI or stream data into our API to inspect or protect workloads on Google Cloud, on-premises, mobile applications, or other cloud service providers.
Reduce risk to unlock more data for your business
Protection of sensitive data, like personally identifiable information (PII), is critical to your business. Deploy de-identification in migrations, data workloads, and real-time data collection and processing.
Data discovery and classification
With over 150 built-in infoTypes, Cloud DLP gives you the power to scan, discover, classify, and report on data from virtually anywhere. Cloud DLP has native support for scanning and classifying sensitive data in Cloud Storage, BigQuery, and Datastore and a streaming content API to enable support for additional data sources, custom workloads, and applications.
Automatically mask your data to safely unlock more of the cloud
Cloud DLP provides tools to classify, mask, tokenize, and transform sensitive elements to help you better manage the data that you collect, store, or use for business or analytics. With support for structured and unstructured data, Cloud DLP can help you preserve the utility of your data for joining, analytics, and AI while protecting the raw sensitive identifiers.
Measure re-identification risk in structured data
Enhance your understanding of data privacy risk. Quasi-identifiers are partially-identifying elements or combinations of data that may link to a single person or a very small group. Cloud DLP allows you to measure statistical properties such as k-anonymity and l-diversity, expanding your ability to understand and protect data privacy.
See DLP in action
Sittercity uses uses Cloud DLP API to detect and redact personal data to keep its service secure.
Ambra health uses the Cloud DLP API for managing and redacting sensitive patient data at scale.
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De-identification of PII in large-scale data using Cloud DLP
Learn how to use Cloud DLP to create an automated transformation pipeline to de-identify sensitive data like personally identifiable information (PII).
Automating the classification of data in Cloud Storage
Learn how to implement an automated data quarantine and classification system using Cloud Storage and other Google Cloud products.
Relational database import to BigQuery with Dataflow
This proof-of-concept uses Dataflow and Cloud DLP to securely tokenize and import data from a relational database to BigQuery.
Using a Cloud DLP proxy to query a database
This concept architecture uses a proxy that parses, inspects, and then either logs the findings or de-identifies the results by using Cloud DLP.
Inspecting storage and databases for sensitive data
Instructions for setting up an inspection scan using Cloud DLP in the Cloud Console, and (optionally) for scheduling periodic repeating inspection scans.
Scheduling a Cloud DLP inspection scan
You can schedule inspection scans of storage repositories like Cloud Storage, BigQuery, and Datastore using Cloud DLP’s job trigger feature.
Cloud DLP Client Libraries
Learn how to get started with the Cloud Client Libraries for the Cloud Data Loss Prevention API.
Cloud DLP can help classify your data on or off cloud giving you the insights you need to ensure proper governance, control, and compliance. Save detailed findings to BigQuery for analysis or publish summary findings to other services like Data Catalog, Security Command Center, Cloud Monitoring, and Pub/Sub. Audit and monitor your data in Cloud Console or build custom reports and dashboards using Google Data Studio or your tool of choice.
Scan for sensitive data in just a few clicks
Automating the classification of data in Cloud Storage
Unblock more workloads as you migrate to the cloud. Cloud DLP enables you to inspect and classify your sensitive data in structured and unstructured workloads. De-identification techniques like tokenization (pseudonymization) let you preserve the utility of your data for joining or analytics while reducing the risk of handling the data by obfuscating the raw sensitive identifiers.
De-identification of PII in large-scale datasets
|Flexible classification||150+ pre-defined detectors with a focus on quality, speed, and scale. Detectors are improving and expanding all the time.|
|Simple and powerful redaction||De-identify your data: redact, mask, tokenize, and transform text and images to help ensure data privacy.|
|Serverless||Cloud DLP is ready to go, no need to manage hardware, VMs, or scale. Just send a little or a lot of data and Cloud DLP scales for you.|
|Detailed findings||Classification results can be sent directly into BigQuery for detailed analysis or export into other systems. Custom reports can easily be generated in Data Studio.|
|Secure data handling||Cloud DLP handles your data securely and undergoes several independent third-party audits to test for data safety, privacy, and security.|
|Pay-as-you-go pricing||Cloud DLP is charged based on the amount of data processed, not based on a subscription service or device. This customer-friendly pricing allows you to pay as you go and not in advance of demand.|
|Easy workload integration||Efficiently deploy Cloud DLP with reusable templates, monitor your data with periodic scans, and integrate into serverless architecture with Pub/Sub notifications.|
|Custom rules||Add your own custom types, adjust detection thresholds, and create detection rules to fit your needs and reduce noise.|