Professional-Cloud-Security-Engineer Exam Dumps - Google Cloud Certified - Professional Cloud Security Engineer

https://gsuite.google.com/learn-more/security/security-whitepaper/page-1.html

Shared responsibility “Security of the Cloud” - GCP is responsible for protecting the infrastructure that runs all of the services offered in the GCP Cloud. This infrastructure is composed of the hardware, software, networking, and facilities that run GCP Cloud services.

https://cloud.google.com/bigquery/docs/scan-with-dlp

Cloud Data Loss Prevention API allows to detect and redact or remove sensitive data before the comments or reviews are published. Cloud DLP will read information from BigQuery, Cloud Storage or Datastore and scan it for sensitive data.

Use Google Shielded VM including secure boot Virtual Trusted Platform Module (vTPM) and integrity monitoring: Shielded VMs provide verifiable integrity of the VM by ensuring that it was not tampered with or compromised at the boot level. They use features like Secure Boot, vTPM, and integrity monitoring to detect and prevent malicious changes to the VM's operating system and firmware.

Activate Confidential Computing: Confidential Computing provides a secure environment for processing sensitive data. It uses hardware-based enclaves to protect data in use by ensuring it cannot be accessed by the underlying host or any other unauthorized entity. By leveraging Intel SGX or AMD SEV, it ensures that data remains encrypted even when it is being processed.

Enforce these actions by using organization policies: Organization policies can enforce the use of Shielded VMs and Confidential Computing across your organization. This ensures that all VMs comply with these security measures without requiring manual configuration for each VM.

References

Shielded VMs documentation

Confidential Computing documentation

Organization Policies documentation

To ensure that the developers can view audit logs for the development environment and the security team can review all logs, you should grant IAM roles at the appropriate resource levels:

Grant logging.admin Role to the Security Team:

Assign the logging.admin role to the security team at the organization resource level.

This grants the security team full access to all logging data across the organization, including both production and development environments.

Grant logging.viewer Role to the Developer Team:

Assign the logging.viewer role to the developer team at the folder resource level that contains all the development projects.

This restricts the developers' access to only view logs in the development environment, ensuring they do not have access to production logs.

By using these roles and assigning them at the appropriate levels, you ensure that each team has the access they need while adhering to the principle of least privilege.

To mitigate the risk posed by long-running Google Cloud CLI sessions, it is essential to enforce a reauthentication frequency. This ensures that users must periodically reauthenticate, reducing the window of opportunity for an attacker to exploit an open session. Setting the reauthentication frequency to one hour forces users to reauthenticate after this period, thereby limiting the duration an attacker can use a compromised session.

Access Google Cloud Console: Log in to your Google Cloud Console using your admin credentials.

Navigate to Security Settings: Go to the "Security" section of the Cloud Console.

Set Session Control: Under the session management settings, locate the "Reauthentication frequency" setting. This controls how often users must reauthenticate.

Configure Reauthentication Frequency: Set the reauthentication frequency to "1 hour". This configuration will force users to reauthenticate every hour, thus limiting the duration of each session.

Save Changes: Confirm and save your changes. This setting will now apply to all users, ensuring that open sessions are minimized to a duration of one hour.

https://cloud.google.com/confidential-computing/confidential-vm/docs/creating-cvm-instance#considerations

Confidential VM does not support live migration. You can only enable Confidential Computing on a VM when you first create the instance. https://cloud.google.com/confidential-computing/confidential-vm/docs/creating-cvm-instance

To maintain proper security policies across numerous Google Cloud environments, especially with a large developer base and a small security team, it's crucial to implement automated and scalable security measures.​

Option A: While applying AI-recommended security posture templates can be beneficial, as of now, there isn't a specific predefined template for Gemini in Vertex AI within the Security Command Center.​

Option B: Publishing internal policies and guidelines is essential for promoting secure development practices but may not be sufficient alone to enforce or detect security policies.​

Option C: Implementing the principle of least privilege through Identity and Access Management (IAM) roles minimizes the risk of misconfigurations and unauthorized access by ensuring users have only the permissions necessary for their tasks.​

Option D: Applying organization policy constraints enforces specific configurations and restrictions across projects. Utilizing Security Health Analytics helps in detecting and monitoring deviations from these policies, providing automated insights into potential security issues.​

Option E: Using Cloud Logging to detect misconfigurations and triggering Cloud Run functions for remediation introduces complexity and may require significant maintenance, making it less practical for a small security team.​

Therefore, Options C and D are the most effective strategies. They provide automated enforcement and monitoring of security policies, aligning with the need for scalable solutions given the organization's size and resources.​