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

https://cloud.google.com/logging/docs/access-control#considerations roles/logging.privateLogViewer (Private Logs Viewer) includes all the permissions contained by roles/logging.viewer, plus the ability to read Data Access audit logs in the _Default bucket.

To handle PII data ingestion and ensure both redaction and re-identification for analytics purposes, you can use Cloud Data Loss Prevention (DLP) with appropriate techniques for masking and encryption.

Cloud Data Loss Prevention (DLP) with Cryptographic Hashing (C):

Use Cloud DLP to apply cryptographic hashing to PII data. Hashing transforms the data into a fixed-length string that is not directly readable, providing a layer of obfuscation. This helps in masking the PII while retaining the ability to verify data integrity.

Cloud Data Loss Prevention (DLP) with Deterministic Encryption using AES-SIV (E):

Apply deterministic encryption using AES-SIV through Cloud DLP. Deterministic encryption ensures that the same input will always produce the same encrypted output, allowing you to re-identify the PII when necessary. This method enables secure encryption while allowing data re-identification for analytics.

By combining these two approaches, you can effectively mask PII for privacy protection and later re-identify it when required for analysis.

References

Cloud Data Loss Prevention Documentation

Data Redaction and Masking Techniques

To configure the behavior where each department member automatically has read-only access to all new project resources created by any department member, you should use Google Cloud's folder structure and IAM roles effectively. Here are the steps:

Create Folders for Departments: Create a folder under your Organization for each department. Folders help organize resources and provide a hierarchy for applying policies and permissions.

Assign IAM Roles to Google Groups: Assign the Project Viewer role to the Google Group associated with each department at the folder level. This ensures that all members of the group have the necessary permissions.

Inherited Permissions: When a department member creates a new project under their department's folder, the permissions assigned to the folder are inherited by the new project. Thus, all department members will automatically have read-only access to the project's resources.

Navigate to IAM & Admin in the GCP Console.

Select "Folders" from the left-hand menu.

For each department, create a new folder under the organization.

Select the newly created folder, and then go to the "Permissions" tab.

Click on "Add" to assign a new role.

Enter the email address of the Google Group for the department.

Assign the "Project Viewer" role to the group.

Access Restrictions: Since the permissions are applied at the folder level, only the members of the specific department's Google Group will have read-only access to the projects created in that folder. Other departments will not have access unless explicitly granted.

By following these steps, you ensure that department members have the required access to their respective projects without manual configuration for each new project.

Google Cloud IAM Documentation

Google Cloud Resource Manager Documentation

To meet data residency requirements on Google Cloud, the recommended option is to use Organization Policy Service constraints. This service allows you to define and enforce specific constraints across your organization, including constraints related to the geographical location where data is stored.

Organization Policy Service constraints allow administrators to enforce policies that restrict resources to specific locations. For instance, you can set policies to ensure that all storage buckets, databases, and other data resources reside within specific geographic boundaries. This helps in complying with data residency requirements.

References

Organization Policy Service documentation

Google Cloud Data Residency

”This encryption method is reversible, which helps to maintain referential integrity across your database and has no character-set limitations.” https://cloud.google.com/blog/products/identity-security/take-charge-of-your-data-how-tokenization-makes-data-usable-without-sacrificing-privacy

https://cloud.google.com/dlp/docs/pseudonymization

FPE provides fewer security guarantees compared to other deterministic encryption methods such as AES-SIV. For these reasons, Google strongly recommends using deterministic encryption with AES-SIV instead of FPE for all security sensitive use cases. Other methods like deterministic encryption using AES-SIV provide these stronger security guarantees and are recommended for tokenization use cases unless length and character set preservation are strict requirements—for example, for backward compatibility with a legacy data system.

The Standard Tier network only provides regional load balancing, while the Premium Tier supports global load balancing with a single anycast IP address. To distribute requests across multiple regions, you need to use the Premium Tier and update the load balancer configuration accordingly.

Steps:

Upgrade to Premium Tier: Update the load balancer to use the Premium Tier network in the Google Cloud Console.

Add New Instance Group: Add the instance group in the new region (us-east-2) to the backend configuration of the existing load balancer.

Verify Configuration: Ensure that the frontend configuration of the load balancer uses a single external IP address for global distribution.

To provide on-premises hosts with access to Google APIs without using public IP addresses or the public internet, Google Cloud provides Private Google Access for on-premises hosts. This feature allows traffic to stay within the Google network via Cloud Interconnect or Cloud VPN.

According to the official Google Cloud Documentation (Configuring Private Google Access for on-premises hosts):

"Private Google Access for on-premises hosts provides a way for on-premises systems to connect to Google APIs and services by routing traffic through a Cloud VPN tunnel or Cloud Interconnect attachment (VLAN). On-premises hosts don't need public IP addresses; instead, they use internal IP addresses."

Key Implementation Steps:

Network Connectivity: Ensure your on-premises network is connected to your VPC via Cloud Interconnect or VPN.

DNS Configuration: You must configure your on-premises DNS to map API requests (like storage.googleapis.com) to special IP ranges. There are two primary options:

private.googleapis.com: Resolves to 199.36.153.8/30. This range supports most Google APIs but only those that are VPC-Service Control compatible.

restricted.googleapis.com: Resolves to 199.36.153.4/30. This is required specifically when using VPC Service Controls (VPC-SC) to ensure data cannot be exfiltrated to services outside the perimeter.

Routing: You must configure custom static routes in your VPC or use BGP to advertise the 199.36.153.8/30 (or 199.36.153.4/30) range back to your on-premises router.

Why other options are incorrect:

A is incorrect: Shared VPC is used to share a network across multiple Google Cloud projects, not to extend a VPC directly to on-premises hardware.

C is incorrect: While the IP range 199.36.153.8/30 is correct for private.googleapis.com, Cloud NAT is used for outbound internet access from VPC instances without external IPs; it does not facilitate private on-premises-to-API connectivity.

D is incorrect: VPC Peering connects two VPCs within Google Cloud. You cannot "peer" an on-premises data center directly via VPC Peering; you must use Interconnect or VPN.

VPC Peering is between organizations not between Projects in an organization. That is Shared VPC. In this case, both projects are in same organization so having VPC Service Controls around both projects with necessary rules should be fine.

https://cloud.google.com/vpc-service-controls/docs/overview