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Organizations often have to detect, redact, and sometimes encrypt Personally Identifiable Information (PII) or other sensitive data, such as credit card numbers, which would protect them against data exposure. If any part of the network is compromised, it will act as another safeguard which will keep the data redacted or encrypted. Google Cloud Platform’s Cloud Data Loss Prevention (DLP) API gives its clients an option to detect the presence of PII and other privacy-sensitive data in user-supplied, unstructured data streams, such as a paragraph, images, or audio recordings (which needs to be converted into text via Speech-to-Text API).
Features of DLP API
DLP Proxy Architecture
Cloud DLP methods for tokenization and date shifting use cryptography to generate replacement values. These cryptographic methods use a key to encrypt those values consistently to maintain referential integrity or, for reversible processes, to detokenize. You can directly provide this key to Cloud DLP when the call is made, or you can wrap it by using Cloud KMS. Wrapping your key in Cloud KMS provides another layer of access control and auditing, and is therefore the preferred method for production deployments.
- Infrastructure admin
Installs and configures the proxy to access the Cloud DLP proxy’s compute environment.
- Data analyst
Accesses the client that connects to the DLP proxy.
- Security admin
Classifies the data, creates the Cloud DLP templates, and configures Cloud KMS.
Google Cloud Platform’s Data Loss Protection API provides a service that can make organizations manage sensitive data, including detecting and redaction, masking, and tokenizing such data. This can help organizations comply with regulations such as GDPR, and reduce the risk of data exposure and data breaches.
To get hands-on experience on Google Cloud’s DLP API, try the website located here.