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Professional-Cloud-Security-Engineer Exam Materials: Google Cloud Certified - Professional Cloud Security Engineer Exam & Professional-Cloud-Security-Engineer Study Guide Files

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The Google Professional-Cloud-Security-Engineer exam consists of multiple-choice and multiple-select questions and has a duration of two hours. It is recommended that candidates have at least three years of industry experience in security and at least one year of experience in designing and managing solutions on the Google Cloud Platform before taking the exam. Professional-Cloud-Security-Engineer exam fee is $200, and it can be taken remotely or at a testing center.

Google Professional-Cloud-Security-Engineer exam is a certification that validates the expertise of individuals in securing applications, data, and infrastructure on the Google Cloud Platform. Professional-Cloud-Security-Engineer Exam is designed for professionals who want to demonstrate their knowledge of security controls and techniques used to protect cloud resources. Google Cloud Certified - Professional Cloud Security Engineer Exam certification is highly valued in the IT industry and is a testament to an individual's skills in cloud security.

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Google Cloud Certified - Professional Cloud Security Engineer Exam Sample Questions (Q46-Q51):

NEW QUESTION # 46
Which of the following actions ensures that access to specific models within Vertex AI is properly restricted across the organization?

A. Regularly audit user activity logs in Vertex AI to identify and revoke access to unapproved models.
B. Implement an organization policy that restricts the vertexai.allowedModels constraint.
C. Train custom models within your Vertex AI project and restrict user access to these models.
D. Configure IAM permissions on individual Model Garden to restrict access to specific models.

Answer: B

Explanation:
The problem states that the organization is using Model Garden and needs to ensure users can only access approved models. This implies a need for a central, enforceable control mechanism.
Organization Policies and Constraints: Google Cloud Organization Policy Service allows administrators to centrally control resources across an organization. Constraints are specific types of restrictions that can be applied. For AI Platform (which includes Vertex AI and Model Garden), there are specific constraints designed to control model usage.
vertexai.allowedModels Constraint: This specific organization policy constraint is designed precisely to restrict which models can be used within a given organization, folder, or project. It provides a centralized way to define a list of approved models that users are allowed to access.Extract Reference: "The vertexai.
allowedModels constraint allows you to specify a list of model URIs that are allowed to be used within the resource hierarchy." and "This constraint helps organizations enforce compliance and control which models are consumed by their users." (Google Cloud documentation, typically found under Organization Policy Service constraints for Vertex AI or AI Platform) Let's evaluate the other options:
A). Configure IAM permissions on individual Model Garden to restrict access to specific models: IAM (Identity and Access Management) typically grants permissions at a broader resource level (e.g., project, dataset, model resource). While you can control who can manage models, directly restricting access to specific models within Model Garden for consumption via IAM roles on individual models is not the primary mechanism for enforcing a list of approved models across an organization in a preventative way. Organization policies are designed for this kind of broad, preventative control.
B). Regularly audit user activity logs in Vertex AI to identify and revoke access to unapproved models:
Auditing logs is a reactive measure. While important for monitoring and detecting violations, it does not prevent users from accessing unapproved models in the first place. The requirement is to ensure they can only access approved models, implying a proactive control.
C). Train custom models within your Vertex AI project and restrict user access to these models: This is about managing access to custom-trained models, not about controlling access to the collection of models in Model Garden, which often includes pre-trained or publicly available models that need to be whitelisted. It doesn't address the requirement of ensuring users only access approved models from the broader Model Garden collection.
Therefore, implementing an organization policy with the vertexai.allowedModels constraint is the most effective and Google-recommended way to centrally ensure that users can only access approved models within an organization using Model Garden.

NEW QUESTION # 47
You are a security administrator at your company and are responsible for managing access controls (identification, authentication, and authorization) on Google Cloud. Which Google-recommended best practices should you follow when configuring authentication and authorization? (Choose two.)

A. Manually add users to Google Cloud.
B. Use SSO/SAML integration with Cloud Identity for user authentication and user lifecycle management.
C. Provide granular access with predefined roles.
D. Use Google default encryption.
E. Provision users with basic roles using Google's Identity and Access Management (1AM) service.

Answer: B,C

NEW QUESTION # 48
How should a customer reliably deliver Stackdriver logs from GCP to their on-premises SIEM system?

A. Build a connector for the SIEM to query for all logs in real time from the GCP RESTful JSON APIs.
B. Configure Organizational Log Sinks to export logs to a Cloud Pub/Sub Topic, which will be sent to the SIEM via Dataflow.
C. Configure every project to export all their logs to a common BigQuery DataSet, which will be queried by the SIEM system.
D. Send all logs to the SIEM system via an existing protocol such as syslog.

Answer: B

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 # 49
Your company is moving to Google Cloud. You plan to sync your users first by using Google Cloud Directory Sync (GCDS). Some employees have already created Google Cloud accounts by using their company email addresses that were created outside of GCDS. You must create your users on Cloud Identity.
What should you do?

A. Use the transfer tool to migrate unmanaged users.
B. Configure GCDS and use GCDS exclusion rules to ensure users are not suspended.
C. Configure GCDS and use GCDS search rules lo sync these users.
D. Write a custom script to identify existing Google Cloud users and call the Admin SDK Directory API to transfer their account.

Answer: B

NEW QUESTION # 50
A customer needs to prevent attackers from hijacking their domain/IP and redirecting users to a malicious site through a man-in-the-middle attack.
Which solution should this customer use?

A. DNS Security Extensions
B. Cloud Identity-Aware Proxy
C. Cloud Armor
D. VPC Flow Logs

Answer: A

Explanation:
DNSSEC - use a DNS registrar that supports DNSSEC, and enable it. DNSSEC digitally signs DNS communication, making it more difficult (but not impossible) for hackers to intercept and spoof. Domain Name System Security Extensions (DNSSEC) adds security to the Domain Name System (DNS) protocol by enabling DNS responses to be validated. Having a trustworthy Domain Name System (DNS) that translates a domain name like www.example.com into its associated IP address is an increasingly important building block of today's web-based applications. Attackers can hijack this process of domain/IP lookup and redirect users to a malicious site through DNS hijacking and man-in-the-middle attacks. DNSSEC helps mitigate the risk of such attacks by cryptographically signing DNS records. As a result, it prevents attackers from issuing fake DNS responses that may misdirect browsers to nefarious websites. https://cloud.google.com/blog/products/gcp/dnssec-now-available-in-cloud-dns

NEW QUESTION # 51
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Noah Scott Noah Scott

Biography

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