Professional-Cloud-Security-Engineer題庫資訊 - Professional-Cloud-Security-Engineer證照指南

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

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

>> Professional-Cloud-Security-Engineer題庫資訊 <<

Professional-Cloud-Security-Engineer證照指南 - Professional-Cloud-Security-Engineer考試證照

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最新的 Google Cloud Certified Professional-Cloud-Security-Engineer 免費考試真題 (Q245-Q250):

問題 #245
You have noticed an increased number of phishing attacks across your enterprise user accounts. You want to implement the Google 2-Step Verification (2SV) option that uses a cryptographic signature to authenticate a user and verify the URL of the login page. Which Google 2SV option should you use?

答案：B

解題說明：
Explanation
https://cloud.google.com/titan-security-key
Security keys use public key cryptography to verify a user's identity and URL of the login page ensuring attackers can't access your account even if you are tricked into providing your username and password.


問題 #246
You want to make sure that your organization's Cloud Storage buckets cannot have data publicly available to the internet. You want to enforce this across all Cloud Storage buckets. What should you do?

答案：B


問題 #247
A customer has an analytics workload running on Compute Engine that should have limited internet access.
Your team created an egress firewall rule to deny (priority 1000) all traffic to the internet.
The Compute Engine instances now need to reach out to the public repository to get security updates. What should your team do?

答案：D


問題 #248
Your company has deployed an artificial intelligence model in a central project. As this model has a lot of sensitive intellectual property and must be kept strictly isolated from the internet, you must expose the model endpoint only to a defined list of projects in your organization. What should you do?

答案：C

解題說明：
The problem requires exposing a sensitive AI model endpoint internally (strictly isolated from the internet) to a defined list of projects within the organization.
Internal Exposure and Isolation: An "internal Application Load Balancer" is suitable for exposing services within your VPC network, ensuring they are not accessible from the internet.
Private Service Connect (PSC): This is the key technology for securely and privately exposing services from one VPC network (the service producer, where the model is) to other VPC networks (the service consumers, the defined list of projects) within the same or different organizations. PSC allows consumers to access services using internal IP addresses, with traffic remaining on Google's private network. You can configure a service attachment that points to the internal load balancer, and then permit specific consumer projects to connect to this service attachment.Extract Reference: "Private Service Connect is a capability of Google Cloud networking that allows consumers to access managed services privately from inside their VPC network. Similarly, it allows managed service producers to host these services in their own separate VPC networks and offer a private connection to their consumers." (Google Cloud Documentation: "Private Service Connect | VPC" - https://cloud.google.com/vpc/docs/private-service-connect) Extract Reference: "Private Service Connect endpoints are internal IP addresses in a consumer VPC network that can be directly accessed by clients in that network. Endpoints are created by deploying a forwarding rule that references a service attachment or a bundle of Google APIs." (Google Cloud Documentation: "About Private Service Connect | VPC" - https://cloud.google.com/vpc/docs/private-service-connect) Extract Reference: "Private Service Connect can be used to access managed services that are owned by Google, third-party software as a service (SaaS) companies, or other teams within the consumer's own company. Both published services and Google APIs can be targets of Private Service Connect." (Google Cloud Documentation: "About Private Service Connect | VPC" - https://cloud.google.com/vpc/docs/private- service-connect) Let's evaluate the other options:
A). Shared VPC and central firewall rules: While Shared VPC centralizes network management, it does not provide a direct managed service exposure mechanism like PSC for a model endpoint to specific projects. It's more about sharing subnets and network resources. Administering all firewall rules centrally would also not meet the need for exposing only this specific model to a defined list of projects in a managed, private service pattern.
B). Activate Private Google Access (PGA): Private Google Access allows VMs without external IP addresses to access Google APIs and services (like Cloud Storage, BigQuery, etc.) privately from within their VPC network. It's for consuming Google services, not for exposing custom services hosted in a Google Cloud project to other projects.
D). External Application Load Balancer + Cloud Armor: An "external Application Load Balancer" exposes the service to the internet. While Cloud Armor can restrict access based on IP addresses, it still involves internet exposure, which contradicts the "strictly isolated from the internet" requirement. Restricting to "Google Cloud IP addresses" doesn't guarantee access only to a defined list of projects and still exposes the service externally.
Therefore, creating an internal Application Load Balancer and exposing it via Private Service Connect is the most suitable and secure solution for this scenario.


問題 #249
Your company has deployed an artificial intelligence model in a central project. This model has a lot of sensitive intellectual property and must be kept strictly isolated from the internet. You must expose the model endpoint only to a defined list of projects in your organization. What should you do?

答案：A

解題說明：
Comprehensive and Detailed Explanation From Exact Extract:
The requirements necessitate a private, cross-project service-to-service connection with explicit authorization-a capability perfectly addressed by Private Service Connect (PSC).
Internal Load Balancer: Ensures the service is isolated from the internet (Layer 7 Load Balancer for HTTP/S ML endpoint).
Private Service Connect (PSC): Allows a service (the model endpoint, exposed via the internal load balancer) in one VPC/project (producer) to be securely consumed by other VPCs/projects (consumers) using an internal IP address.
Defined List of Projects: PSC enables Explicit authorization, allowing the producer to define the allowed list of consumers that can establish a connection, directly meeting the granular restriction requirement.
Extracts:
"Private Service Connect provides... Explicit authorization. Private Service Connect provides an authorization model that gives consumers and producers granular control." (Source 2.4)
"Private Service Connect backends let Google Cloud load balancers send traffic through Private Service Connect to reach published services... Placing a load balancer in front of a managed service provides the consumer with more visibility and control..." (Source 2.4)
"Publish services by using Private Service Connect... Select the internal load balancer that hosts the service that you want to publish." (Source 2.3)


問題 #250
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