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Google Professional-Cloud-Security-Engineer Exam Overview:

Certification Vendor:	Google Cloud
Exam Name:	Professional Cloud Security Engineer Exam
Exam Number:	Professional-Cloud-Security-Engineer
Certificate Validity Period:	2 years
Related Certifications:	Google Cloud Certified - Professional Cloud Architect Google Cloud Certified - Associate Cloud Engineer
Real Exam Qty:	50-60
Available Languages:	Portuguese, English, Japanese, Spanish
Exam Price:	200 USD
Exam Duration:	120 minutes
Exam Format:	Multiple select, Case studies, Multiple choice
Recommended Training:	Google Cloud Security Engineer Training Resources Google Cloud Skills Boost - Security Engineer Learning Path
Exam Registration:	Kryterion Webassessor Registration Official Google Cloud Certification
Sample Questions:	Google Professional-Cloud-Security-Engineer Sample Questions
Exam Way:	Online proctored or test center (Kryterion Webassessor)
Pre Condition:	No formal prerequisites required. Recommended: 3+ years of industry experience including at least 1 year designing and managing solutions using Google Cloud.
Official Syllabus URL:	https://cloud.google.com/certification/cloud-security-engineer

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구글 프로페셔널-클라우드-보안-엔지니어 시험은 GCP(Google Cloud Platform) 솔루션의 보안을 담당하는 클라우드 보안 전문가들을 위한 자격증 프로그램입니다. 이 시험은 안전한 GCP 인프라와 애플리케이션을 설계하고 구현하기 위해 필요한 기술과 지식을 검증합니다. 이 시험을 통과함으로써 GCP 자원과 데이터를 보호하고, GCP 자원에 대한 액세스를 제어하며, GCP에서 규정 준수와 위험을 관리할 수 있는 기술을 보유하고 있음을 증명할 수 있습니다.

Google Professional-Cloud-Security-Engineer 인증은 Google Cloud Certified Program의 일부로 Google Cloud Technologies 사용에서 전문가의 기술과 지식을 검증하기위한 다양한 인증을 제공합니다. 이 프로그램은 클라우드 아키텍트, 데이터 엔지니어, 머신 러닝 엔지니어 등 다양한 역할을 담당하는 전문가를 위해 설계되었습니다. Google 클라우드 인증을 얻으면 전문가가 구직 시장에서 눈에 띄고 Google Cloud Technologies 사용에 대한 전문 지식을 보여줄 수 있습니다.

Google Professional-Cloud-Security-Engineer Certification 시험은 Google Cloud 환경에서 응용 프로그램 및 인프라의 보안을 담당하는 전문가의 지식과 기술을 테스트하도록 설계되었습니다. 이 시험은 클라우드 기반 애플리케이션 및 데이터 보안에 대한 전문 지식과 역량을 검증하기 때문에 클라우드 보안 전문가를위한 가장 인기있는 인증 중 하나입니다.

최신 Google Cloud Certified Professional-Cloud-Security-Engineer 무료샘플문제 (Q127-Q132):

질문 # 127
Last week, a company deployed a new App Engine application that writes logs to BigQuery. No other workloads are running in the project. You need to validate that all data written to BigQuery was done using the App Engine Default Service Account.
What should you do?

A. 1. In BigQuery, select the related dataset.
2. Make sure the App Engine Default Service Account is the only account that can write to the dataset.
B. 1. Go to the IAM section on the project.
2. Validate that the App Engine Default Service Account is the only account that has a role that can write to BigQuery.
C. 1. Use StackDriver Logging and filter on BigQuery Insert Jobs.
2. Click on the email address in line with the App Engine Default Service Account in the authentication field.
3. Click Show Matching Entries.
4. Make sure the resulting list is empty.
D. 1. Use StackDriver Logging and filter on BigQuery Insert Jobs.
2. Click on the email address in line with the App Engine Default Service Account in the authentication field.
3. Click Hide Matching Entries.
4. Make sure the resulting list is empty.

정답：D

설명：
To validate that all data written to BigQuery was done using the App Engine Default Service Account, you can use StackDriver Logging (now known as Cloud Logging) to filter and inspect the logs for BigQuery insert jobs. By hiding the entries matching the App Engine Default Service Account, you can ensure that no other service account has written to BigQuery if the resulting list is empty.
Steps:
Open Cloud Logging: Navigate to Cloud Logging in the Google Cloud Console.
Filter Logs: Apply a filter to display logs for BigQuery insert jobs.
Inspect Entries: Click on the email address that corresponds to the App Engine Default Service Account in the authentication field.
Hide Matching Entries: Select the option to hide matching entries.
Validate: Check if the resulting list is empty, confirming that no other service account has performed write operations to BigQuery.
Reference:
Google Cloud Logging
Monitoring BigQuery logs

질문 # 128
Your organization uses the top-tier folder to separate application environments (prod and dev).
The developers need to see all application development audit logs, but they are not permitted to review production logs. Your security team can review all logs in production and development environments. You must grant Identity and Access Management (IAM) roles at the right resource level for the developers and security team while you ensure least privilege.
What should you do?

A. 1. Grant logging.viewer role to the security team at the organization resource level.
2. Grant logging.viewer role to the developer team at the folder resource level that contains all the dev projects.
B. 1. Grant logging.admin role to the security team at the organization resource level.
2. Grant logging.viewer role to the developer team at the folder resource level that contains all the dev projects.
C. 1. Grant logging.admin role to the security team at the organization resource level.
2. Grant logging.admin role to the developer team at the organization resource level.
D. 1. Grant logging.viewer role to the security team at the organization resource level.
2. Grant logging.admin role to the developer team at the organization resource level.

정답：A

설명：
Grant logging.viewer role to the security team at the organization resource level. This allows the security team to view all logs in both production and development environments.
Grant logging.viewer role to the developer team at the folder resource level that contains all the dev projects. This allows the developers to view all application development audit logs, but not the production logs, ensuring least privilege.

질문 # 129
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?

A. Within the model project, create an internal Application Load Balancer that points to the model endpoint. Expose this load balancer with Private Service Connect to a configured list of projects.
B. Activate Private Google Access in both the model project and in each project that needs to connect to the model. Create a firewall policy to allow connectivity to Private Google Access addresses.
C. Within the model project, create an external Application Load Balancer that points to the model endpoint. Create a Cloud Armor policy to restrict IP addresses to Google Cloud.
D. Create a central project to host Shared VPC networks that are provided to all other projects. Centrally administer all firewall rules in this project to grant access to the model.

정답：A

설명：
To share a service (like an AI model) across project boundaries privately and securely-without complex VPC peering or exposing it to the internet-Private Service Connect (PSC) is the recommended solution.14 According to Google Cloud Documentation (Private Service Connect for Vertex AI/Custom Services):
"Private Service Connect allows a service producer to expose a service (via an Internal Load Balancer) to service consumers in other VPC networks or projects.15 The producer creates a Service Attachment that points to the load balancer.16 The consumer creates a PSC Endpoint in their own VPC. Traffic stays entirely within the Google backbone, and the producer can maintain an 'Allowlist' of Project IDs that are permitted to connect." Why this fits the requirements:
* Isolation: The model remains in its own project and is not reachable via the internet (Option C is out).
* Granular Control: PSC allows you to explicitly list which Project IDs can access the service attachment (Option A).17
* Scalability: It avoids the "transitive peering" and "IP overlap" limitations often found in Shared VPC or Peering architectures (Option B).
Reference:
Google Cloud Documentation: "Private Service Connect overview" (https://cloud.google.com/vpc/docs
/private-service-connect).
Vertex AI Documentation: "Using Private Service Connect for online inference" (https://cloud.google.com
/vertex-ai/docs/predictions/private-service-connect).

질문 # 130
Your company recently published a security policy to minimize the usage of service account keys. On- premises Windows-based applications are interacting with Google Cloud APIs. You need to implement Workload Identity Federation (WIF) with your identity provider on-premises.
What should you do?

A. Set up a workload identity pool with your corporate Active Directory Federation Service (ADFS) Let all principals in the pool impersonate the Google Cloud service account.
B. Set up a workload identity pool with your corporate Active Directory Federation Service (ADFS) Configure a rule to let principals in the pool impersonate the Google Cloud service account.
C. Set up a workload identity pool with an OpenID Connect (OIDC) service on the name machine Configure a rule to let principals in the pool impersonate the Google Cloud service account.
D. Set up a workload identity pool with an OpenID Connect (OIDC) service on the same machine Let all principals in the pool impersonate the Google Cloud service account.

정답：B

설명：
To minimize the usage of service account keys and implement Workload Identity Federation (WIF) with your on-premises identity provider, you can use a workload identity pool integrated with your corporate Active Directory Federation Service (ADFS). This setup allows your on-premises Windows-based applications to authenticate to Google Cloud APIs without using long-lived service account keys.
* Set Up a Workload Identity Pool:
* In the Google Cloud Console, go to IAM & Admin > Workload Identity Federation.
* Create a new workload identity pool.
* Configure the pool to trust your corporate ADFS by specifying the federation provider details.
* Create a Workload Identity Provider:
* Within the created pool, set up a new provider for ADFS.
* Configure the provider with the necessary details such as the issuer URL and credentials.
* Configure Impersonation Rules:
* Set up rules to allow principals in the workload identity pool to impersonate specific Google Cloud service accounts.
* This is done by specifying the identity provider and the conditions under which the service accounts can be impersonated.
* Update Applications:
* Modify your on-premises applications to use the configured ADFS authentication to obtain tokens.
* These tokens can then be exchanged for Google Cloud access tokens to interact with Google Cloud APIs securely.
By setting up the workload identity pool and configuring impersonation rules, you achieve secure authentication without needing to distribute and manage service account keys.
References:
* Workload Identity Federation Documentation
* Federating On-Premises Identities to Workload Identity Federation

질문 # 131
Your company recently published a security policy to minimize the usage of service account keys. On- premises Windows-based applications are interacting with Google Cloud APIs. You need to implement Workload Identity Federation (WIF) with your identity provider on-premises.
What should you do?

A. Set up a workload identity pool with your corporate Active Directory Federation Service (ADFS) Let all principals in the pool impersonate the Google Cloud service account.
B. Set up a workload identity pool with your corporate Active Directory Federation Service (ADFS) Configure a rule to let principals in the pool impersonate the Google Cloud service account.
C. Set up a workload identity pool with an OpenID Connect (OIDC) service on the name machine Configure a rule to let principals in the pool impersonate the Google Cloud service account.
D. Set up a workload identity pool with an OpenID Connect (OIDC) service on the same machine Let all principals in the pool impersonate the Google Cloud service account.

정답：B

설명：
To minimize the usage of service account keys and implement Workload Identity Federation (WIF) with your on-premises identity provider, you can use a workload identity pool integrated with your corporate Active Directory Federation Service (ADFS). This setup allows your on-premises Windows-based applications to authenticate to Google Cloud APIs without using long-lived service account keys.
* Set Up a Workload Identity Pool:
* In the Google Cloud Console, go to IAM & Admin > Workload Identity Federation.
* Create a new workload identity pool.
* Configure the pool to trust your corporate ADFS by specifying the federation provider details.
* Create a Workload Identity Provider:
* Within the created pool, set up a new provider for ADFS.
* Configure the provider with the necessary details such as the issuer URL and credentials.
* Configure Impersonation Rules:
* Set up rules to allow principals in the workload identity pool to impersonate specific Google Cloud service accounts.
* This is done by specifying the identity provider and the conditions under which the service accounts can be impersonated.
* Update Applications:
* Modify your on-premises applications to use the configured ADFS authentication to obtain tokens.
* These tokens can then be exchanged for Google Cloud access tokens to interact with Google Cloud APIs securely.
By setting up the workload identity pool and configuring impersonation rules, you achieve secure authentication without needing to distribute and manage service account keys.
Workload Identity Federation Documentation
Federating On-Premises Identities to Workload Identity Federation

질문 # 132
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