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Google Professional-Cloud-Security-Engineer Certification is ideal for security professionals who are responsible for designing, implementing, and managing security solutions for cloud environments. Google Cloud Certified - Professional Cloud Security Engineer Exam certification is also beneficial for individuals who want to enhance their knowledge and skills in cloud security and advance their career in this field. Google Cloud Certified - Professional Cloud Security Engineer Exam certification demonstrates the candidate's ability to design and implement secure cloud environments using GCP technologies and validates their expertise in handling security challenges in cloud environments.

Google Cloud Certified - Professional Cloud Security Engineer Exam Sample Questions (Q159-Q164):

NEW QUESTION # 159
Your organization's Google Cloud VMs are deployed via an instance template that configures them with a public IP address in order to host web services for external users. The VMs reside in a service project that is attached to a host (VPC) project containing one custom Shared VPC for the VMs. You have been asked to reduce the exposure of the VMs to the internet while continuing to service external users. You have already recreated the instance template without a public IP address configuration to launch the managed instance group (MIG). What should you do?

A. Deploy a Cloud NAT Gateway in the service project for the MIG.
B. Deploy a Cloud NAT Gateway in the host (VPC) project for the MIG.
C. Deploy an external HTTP(S) load balancer in the service project with the MIG as a backend.
D. Deploy an external HTTP(S) load balancer in the host (VPC) project with the MIG as a backend.

Answer: C

Explanation:
This is the Two-tier web service model, below the example from google cloud documentation
https://cloud.google.com/vpc/docs/shared-vpc#two-tier_web_service

NEW QUESTION # 160
You are part of a security team investigating a compromised service account key. You need to audit which new resources were created by the service account.
What should you do?

A. Query Admin Activity logs.
B. Query Stackdriver Monitoring Workspace.
C. Query Data Access logs.
D. Query Access Transparency logs.

Answer: A

Explanation:
Admin activity logs are always created to log entries for API calls or other actions that modify the configuration or metadata of resources. For example, these logs record when users create VM instances or change Identity and Access Management permissions.

NEW QUESTION # 161
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?

A. Cloud VPN Gateway between all engineering projects using a hub and spoke model
B. Grant Compute Admin role to the networking team for each engineering project
C. VPC peering between all engineering projects using a hub and spoke model
D. Shared VPC Network with a host project and service projects

Answer: D

NEW QUESTION # 162
Your organization s customers must scan and upload the contract and their driver license into a web portal in Cloud Storage. You must remove all personally identifiable information (Pll) from files that are older than 12 months. Also you must archive the anonymized files for retention purposes.
What should you do?

A. Schedule a Cloud Key Management Service (KMS) rotation period of 12 months for the encryption keys of the Cloud Storage files containing Pll to de-identify them Delete the original keys.
B. Configure the Autoclass feature of the Cloud Storage bucket to de-identify Pll Archive the files that are older than 12 months Delete the original files.
C. Create a Cloud Data Loss Prevention (DLP) inspection job that de-identifies Pll in files created more than 12 months ago and archives them to another Cloud Storage bucket. Delete the original files.
D. Set a time to live (TTL) of 12 months for the files in the Cloud Storage bucket that removes PH and moves the files to the archive storage class.

Answer: C

Explanation:
To remove personally identifiable information (PII) from files older than 12 months and archive the anonymized files for retention purposes, you can use Google Cloud Data Loss Prevention (DLP).
* Create a Cloud DLP Inspection Job:
* Go to the Cloud DLP section in the Google Cloud Console.
* Create an inspection job that scans files in your Cloud Storage bucket for PII.
* Configure the job to only target files that are older than 12 months.
* Configure De-identification:
* In the inspection job settings, configure de-identification actions to remove or obfuscate PII in the files.
* Specify the transformation techniques appropriate for your data, such as masking or tokenization.
* Archive Anonymized Files:
* Set up the job to move the de-identified files to another Cloud Storage bucket designated for archival.
* Ensure this bucket has the appropriate retention policies and access controls in place.
* Delete Original Files:
* After de-identification and archiving, configure the job to delete the original files from the source bucket.
This approach ensures that PII is effectively removed from old files and that the anonymized data is securely archived, maintaining compliance with data retention and privacy policies.
Cloud Data Loss Prevention Documentation
Setting Up DLP Jobs
Cloud Storage Documentation

NEW QUESTION # 163
Your team maintains 1PB of sensitive data within BigOuery that contains personally identifiable information (PII). You need to provide access to this dataset to another team within your organization for analysis purposes. You must share the BigQuery dataset with the other team while protecting the PII. What should you do?

A. Export the BigQuery dataset to Cloud Storage. Create a VPC Service Control perimeter and allow only their team's project access to the bucket.
B. Implement data pseudonymization techniques to replace the PII fields with non-identifiable values.
Grant the other team access to the pseudonymized dataset.
C. Create a filtered copy of the dataset and replace the sensitive data with hash values in a separate project. Grant the other team access to this new project.
D. Utilize BigQuery's row-level access policies to mask PII columns based on the other team's user identities.

Answer: D

Explanation:
https://cloud.google.com/bigquery/docs/row-level-security-intro?hl=es-
419#filter_row_data_based_on_region

NEW QUESTION # 164
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