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

SectionObjectives
Configure network security- Google Cloud network security controls
  • 1. Private Google Access and restricted services
    • 2. Cloud Armor and DDoS protection
      • 3. VPC firewall rules
        Ensure data protection- Encryption and key management
        • 1. Customer-managed encryption keys (CMEK)
          • 2. Cloud KMS and key lifecycle management
            • 3. Data loss prevention (DLP) concepts
              Manage operations within a cloud security environment- Security monitoring and operations
              • 1. Logging and monitoring with Cloud Logging
                • 2. Security Command Center usage
                  • 3. Incident response and alerting
                    Configure access within a cloud solution environment- Identity and Access Management (IAM)
                    • 1. Implement least privilege access
                      • 2. Manage IAM roles and permissions
                        • 3. Service accounts and workload identity

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                          Professional-Cloud-Security-Engineer試験の準備方法｜素敵なProfessional-Cloud-Security-Engineer最新試験試験｜素晴らしいGoogle Cloud Certified - Professional Cloud Security Engineer Exam資格参考書

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                          Google Cloud Certified - Professional Cloud Security Engineer Exam 認定 Professional-Cloud-Security-Engineer 試験問題 (Q233-Q238):

                          質問 # 233
                          An organization is starting to move its infrastructure from its on-premises environment to Google Cloud Platform (GCP). The first step the organization wants to take is to migrate its ongoing data backup and disaster recovery solutions to GCP. The organization's on-premises production environment is going to be the next phase for migration to GCP. Stable networking connectivity between the on-premises environment and GCP is also being implemented.
                          Which GCP solution should the organization use?

                          正解：B

                          解説：
                          Objective: Migrate ongoing data backup and disaster recovery solutions to GCP.
                          Solution: Use Cloud Storage with scheduled tasks and gsutil.
                          Steps:
                          Step 1: Set up a Cloud Interconnect to ensure stable networking connectivity between the on-premises environment and GCP.
                          Step 2: Create a Cloud Storage bucket to store backups.
                          Step 3: Use gsutil, a command-line tool for Cloud Storage, to create scripts for data transfer.
                          Step 4: Schedule these scripts using cron jobs or another scheduling tool to automate the backup process.
                          Using Cloud Storage with scheduled tasks and gsutil ensures efficient and reliable backup and disaster recovery while leveraging stable connectivity provided by Cloud Interconnect.
                          Reference:
                          Cloud Storage Documentation
                          gsutil Tool Documentation
                          Cloud Interconnect Documentation


                          質問 # 234
                          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?

                          正解：C

                          解説：
                          https://cloud.google.com/dlp/docs/inspecting-storage#sampling https://cloud.google.com/dlp/docs/best-practices-costs#limit_scans_of_files_in_to_only_relevant_files


                          質問 # 235
                          You are responsible for managing your company's identities in Google Cloud. Your company enforces 2-Step Verification (2SV) for all users. You need to reset a user's access, but the user lost their second factor for 2SV. You want to minimize risk. What should you do?

                          正解：C


                          質問 # 236
                          You will create a new Service Account that should be able to list the Compute Engine instances in the project.
                          You want to follow Google-recommended practices.
                          What should you do?

                          正解：C


                          質問 # 237
                          Your organization is developing a sophisticated machine learning (ML) model to predict customer behavior for targeted marketing campaigns. The BigQuery dataset used for training includes sensitive personal information. You must design the security controls around the AI/ML pipeline. Data privacy must be maintained throughout the model's lifecycle and you must ensure that personal data is not used in the training process Additionally, you must restrict access to the dataset to an authorized subset of people only. What should you do?

                          正解：B

                          解説：
                          Comprehensive and Detailed Explanation From Exact Extract:
                          The core security and privacy requirement is to prevent personal data from being used in the training process, which necessitates de-identification. Cloud Data Loss Prevention (DLP), also referred to as Sensitive Data Protection (SDP), is the specific Google Cloud tool for this purpose. The secondary requirement, restricting access, is handled by IAM.
                          Extracts:
                          "Sensitive Data Protection (SDP)... De-identification enables you to transform your data to reduce data risk while retaining data utility." (Source 1.4)
                          "De-identification techniques like encryption, obfuscate raw sensitive identifiers in your data. These techniques let you preserve the utility of your data for joining or analytics, while reducing the risk of handling the data." (Source 1.1)
                          "DLP provides tools to classify and de-identify sensitive elements or unwanted content within your data...
                          Find and remove sensitive elements from your data before model training." (Source 1.4) IAM policies are the standard mechanism to satisfy the requirement to "restrict access to the dataset to an authorized subset of people only." Option B combines the precise technical solution for privacy (DLP De- identification) with the necessary access control (IAM).


                          質問 # 238
                          ......

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