From time to time, we release papers, blog posts, and videos related to Cloud Data Loss Prevention (DLP). They are listed here.
Scan for sensitive data in just a few clicks
A deeper look at the Google Cloud Platform Console user interface for Cloud DLP to show how you can start to inspect your enterprise data with just a few clicks.
How tokenization makes data usable without sacrificing privacy
Tokenization, sometimes referred to as pseudonymization or surrogate replacement, is widely used in industries like finance and healthcare to help reduce the use of data in use, compliance scope, and minimize sensitive data being exposed to systems that do not need it. With Cloud DLP, customers can perform tokenization at scale with minimal setup.
Using Cloud DLP to de-identify and obfuscate sensitive information
The team discusses how to leverage Cloud DLP to protect data by automatically incorporating data obfuscation and minimization techniques into your workflows.
Using Cloud DLP to find and protect PII
Scott Ellis, Cloud DLP Product Manager, discusses how to leverage Cloud DLP to increase your privacy posture.
Scanning BigQuery with Cloud DLP
The team shares how to easily scan BigQuery from the GCP Console.
Automating the classification of data uploaded to Cloud Storage
This tutorial shows how to implement an automated data quarantine and classification system using Cloud Storage and other GCP products.
Data Tokenization Using Cloud Dataflow/Beam & DLP API
This proof of concept reads structured and unstructured data from Cloud Storage and stores the de-identified data to BigQuery and Cloud Storage.
Example Cloud Dataflow template to de-identify stored data
This example template builds a streaming pipeline to transform sensitive data.
Relational database import to BigQuery with Cloud Dataflow
This proof-of-concept uses Cloud Dataflow and Cloud DLP to securely tokenize and import data from a relational database to BigQuery. The example describes how to use this pipeline with a sample SQL Server database created in Google Kubernetes Engine and use of DLP template to tokenize PII data before it's persisted.
Cloud OnAir: Protecting sensitive datasets on Google Cloud Platform
Data is one of your company's most valuable assets. Analytics and machine learning can help unlock valuable services for your customers and your business. These datasets can also contain sensitive data that need protection. In this webinar, you'll learn how Cloud DLP can help you discover, classify, and de-identify sensitive data as part of an overall governance strategy.
Cloud Next 2019: Scotiabank shares their cloud-native approach to ingesting PII into GCP
As a major international bank, Scotiabank discusses its security journey and cloud-native approach to ingesting PII into GCP, constraining access, and carefully and selectively allowing re-identification by bank applications.
Cloud Next 2019: Identify and Protect Sensitive Data in the Cloud
The team shares the latest advancements made to Cloud DLP and demos several different techniques to protect your sensitive data.