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Google Professional-Cloud-Security-Engineer Exam Syllabus Topics:

SectionWeightObjectives
Managing operations19%- Automating infrastructure and application security
  • 1. Configuring Binary Authorization for GKE or Cloud Run
  • 2. Automating virtual machine and container image creation (hardening, maintenance, patch management)
  • 3. Managing policy and drift detection at scale (CSPM, custom org policies, Security Health Analytics)
  • 4. Automating security scanning for CVEs through CI/CD pipelines
Configuring access25%- Managing service accounts
  • 1. Securing, auditing, and mitigating usage of service account keys
  • 2. Identifying scenarios requiring service accounts
  • 3. Securing and protecting service accounts (including default service accounts)
  • 4. Creating, disabling, and authorizing service accounts
  • 5. Managing and creating short-lived credentials
- Managing Cloud Identity
  • 1. Configuring Workforce Identity Federation
  • 2. Automating user lifecycle management processes
  • 3. Managing super administrator accounts
  • 4. Administering user accounts and groups programmatically
  • 5. Configuring Google Cloud Directory Sync and implementing SSO with a third-party identity provider
Supporting compliance requirements14%- Determining security requirements
  • 1. Implementing security controls for Vertex AI and AI/ML workloads
  • 2. Identifying security requirements (e.g., regulatory, compliance)
  • 3. Configuring audit logging and monitoring (Cloud Audit Logs, Access Transparency)
Configuring network security19%- Designing network security
  • 1. Configuring load balancing for security (Cloud Armor, SSL policies)
  • 2. Establishing private connectivity between VPC and Google APIs (Private Google Access, Private Service Connect)
  • 3. Configuring network perimeter controls (firewall rules, hierarchical firewall policies, Cloud NGFW)
  • 4. Using Cloud NAT to enable outbound traffic
Ensuring data protection23%- Protecting sensitive data and preventing data loss
  • 1. Securing secrets with Secret Manager
  • 2. Configuring Sensitive Data Protection (discovering and redacting PII, pseudonymization)
  • 3. Restricting access to Google Cloud data services (BigQuery, Cloud Storage, Cloud SQL)
  • 4. Protecting and managing compute instance metadata

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Google Cloud Certified - Professional Cloud Security Engineer Exam Sample Questions (Q217-Q222):

NEW QUESTION # 217
Your team needs to configure their Google Cloud Platform (GCP) environment so they can centralize the control over networking resources like firewall rules, subnets, and routes. They also have an on-premises environment where resources need access back to the GCP resources through a private VPN connection. The networking resources will need to be controlled by the network security team.
Which type of networking design should your team use to meet these requirements?

Answer: C

Explanation:
https://cloud.google.com/docs/enterprise/best-practices-for-enterprise- organizations#centralize_network_control


NEW QUESTION # 218
As adoption of the Cloud Data Loss Prevention (DLP) API grows within the company, you need to optimize usage to reduce cost. DLP target data is stored in Cloud Storage and BigQuery. The location and region are identified as a suffix in the resource name.
Which cost reduction options should you recommend?

Answer: B

Explanation:
Explanation/Reference: https://cloud.google.com/dlp/docs/reference/rest/v2/InspectJobConfig


NEW QUESTION # 219
Your company wants to determine what products they can build to help customers improve their credit scores depending on their age range. To achieve this, you need to join user information in the company's banking app with customers' credit score data received from a third party. While using this raw data will allow you to complete this task, it exposes sensitive data, which could be propagated into new systems.
This risk needs to be addressed using de-identification and tokenization with Cloud Data Loss Prevention while maintaining the referential integrity across the database. Which cryptographic token format should you use to meet these requirements?

Answer: D

Explanation:
Explanation
"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
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.


NEW QUESTION # 220
An administrative application is running on a virtual machine (VM) in a managed group at port 5601 inside a Virtual Private Cloud (VPC) instance without access to the internet currently. You want to expose the web interface at port 5601 to users and enforce authentication and authorization Google credentials What should you do?

Answer: C

Explanation:
Explanation
This approach allows you to expose the web interface securely by using Identity-Aware Proxy (IAP), which provides authentication and authorization with Google credentials. The HTTP Load Balancer can distribute traffic to the VMs in the managed group, and the VPC firewall rule ensures that access is allowed from the IAP network range.


NEW QUESTION # 221
How should a customer reliably deliver Stackdriver logs from GCP to their on-premises SIEM system?

Answer: C

Explanation:
Explanation
Scenarios for exporting Cloud Logging data: Splunk This scenario shows how to export selected logs from Cloud Logging to Pub/Sub for ingestion into Splunk. Splunk is a security information and event management (SIEM) solution that supports several ways of ingesting data, such as receiving streaming data out of Google Cloud through Splunk HTTP Event Collector (HEC) or by fetching data from Google Cloud APIs through Splunk Add-on for Google Cloud. Using the Pub/Sub to Splunk Dataflow template, you can natively forward logs and events from a Pub/Sub topic into Splunk HEC. If Splunk HEC is not available in your Splunk deployment, you can use the Add-on to collect the logs and events from the Pub/Sub topic.
https://cloud.google.com/solutions/exporting-stackdriver-logging-for-splunk


NEW QUESTION # 222
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