Google Cloud Professional Cloud Security Engineer Practice Exam

How can user access in BigQuery be limited effectively during specified hours?

1. IAM policies without conditions

2. Scheduling data access requests

3. Custom IAM conditions based on time

4. Restricting API access

The correct answer is: Custom IAM conditions based on time

The most effective method for limiting user access in BigQuery during specified hours is to utilize custom IAM conditions based on time. This approach allows you to define specific conditions under which certain permissions are granted or denied, based on the current time when a user attempts to access the data. By applying custom conditions, you can create rules that explicitly allow or deny access during designated hours. For example, you might set it up so that users can only run queries or access datasets between 9 AM and 5 PM on weekdays. This granular control over permissions enhances security and ensures that sensitive data is not accessed when it should be restricted. In contrast, IAM policies without conditions provide blanket permissions that do not take time into account, making them unsuitable for time-specific access control. Scheduling data access requests is not a built-in feature of BigQuery and does not inherently manage user access based on time. Restricting API access is more general and does not specify user-level access controls based on the time of day. Therefore, custom IAM conditions offer the most precise and effective way to manage access in alignment with specific timeframes.