Google Cloud Professional Cloud Security Engineer Practice Exam

To anonymize sensitive health information in a reversible way, which Google Cloud solution is appropriate?

1. Identity and Access Management

2. Cloud Data Loss Prevention with cryptographic hashing

3. Google BigQuery

4. Dataflow with ETL processes

The correct answer is: Cloud Data Loss Prevention with cryptographic hashing

Anonymizing sensitive health information while maintaining the ability to reverse that anonymization is a critical requirement in many health data management scenarios. The appropriate solution in this case is Cloud Data Loss Prevention (DLP) with cryptographic hashing. Cloud DLP is designed specifically to help organizations identify, manage, and protect sensitive data. One of its robust features is the ability to apply cryptographic hashing to data. This technique involves transforming sensitive data, like health information, into a hash—a fixed-size string of characters derived from the original data using a mathematical function. Importantly, when applied correctly, this allows for the information to be stored and processed without exposing the underlying sensitive data. The use of hashing can be reversible if the original data is securely stored and managed separately from its hashed value, enabling authorized users to retrieve the original data when necessary. In contrast, other options do not provide the reversible anonymization capability required for this scenario. Identity and Access Management primarily controls who can access resources rather than providing data anonymization. Google BigQuery is a powerful data analytics platform but lacks specific built-in features for data anonymization and reversible hashing. Dataflow is a tool for data processing, and while it can facilitate ETL (Extract, Transform, Load) processes,