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| Certification Vendor: | Google Cloud |
|---|---|
| Exam Name: | Google Cloud Certified Professional Cloud Security Engineer Exam |
| Exam Number: | Professional-Cloud-Security-Engineer |
| Certificate Validity Period: | 2 years |
| Exam Format: | Multiple choice, Multiple select, Scenario-based questions |
| Passing Score: | Not publicly disclosed (approx. 70% as industry estimate) |
| Exam Price: | $200 USD (plus tax where applicable) |
| Related Certifications: | Google Cloud Certified - Associate Cloud Engineer Google Cloud Certified - Professional Cloud Architect |
| Exam Duration: | 120 minutes |
| Real Exam Qty: | 50-60 |
| Available Languages: | Japanese, English |
| Recommended Training: | Professional Cloud Security Engineer Learning Path Official Exam Guide |
| Exam Registration: | Google Cloud Certification Registration |
| Sample Questions: | Google Professional-Cloud-Security-Engineer Sample Questions |
| Exam Way: | Online proctored (remote) or onsite proctored at authorized test centers |
| Pre Condition: | No formal prerequisites; recommended: 3+ years industry experience, 1+ year designing/managing Google Cloud security solutions |
| Official Syllabus URL: | https://cloud.google.com/learn/certification/cloud-security-engineer |
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The Google Professional Cloud Security Engineer certification is designed to validate the skills of the candidates in designing and implementing a secure infrastructure on GCP. The applicants for this certificate have an understanding of the industry security requirements and security best practices. They also develop, design, and manage secure infrastructures by leveraging the Google security technologies. To obtain the certification, the individuals must pass one qualifying exam.
NEW QUESTION # 292
You define central security controls in your Google Cloud environment for one of the folders in your organization you set an organizational policy to deny the assignment of external IP addresses to VMs. Two days later you receive an alert about a new VM with an external IP address under that folder.
What could have caused this alert?
Answer: A
Explanation:
Understand Organization Policies:
Organization policies allow you to enforce restrictions on Google Cloud resources to adhere to your organization's security and compliance requirements.
Policies can be set at the organization, folder, or project level, with project-level policies able to override higher-level policies unless explicitly prevented.
Identify the Policy Constraint:
The specific constraint in question is likely constraints/compute.vmExternalIpAccess, which controls whether VMs can have external IP addresses.
Check Policy Overwrites:
Navigate to the Organization Policies page in the Google Cloud Console.
Check the policy settings at the project level under the affected folder to see if there is an override in place with an 'allow' value.
This override would permit the creation of VMs with external IP addresses despite the higher-level restriction.
Resolve the Policy Conflict:
If an override is found, remove or modify the project-level policy to align with the organizational policy denying external IP addresses.
Communicate with project administrators to ensure they understand and comply with the overarching security policies.
Reference:
Organization Policy Best Practices
Managing Policy Constraints
NEW QUESTION # 293
You are auditing all your Google Cloud resources in the production project. You want to identify all principals who can change firewall rules.
What should you do?
Answer: A
Explanation:
To identify all principals who can change firewall rules, you should use Policy Analyzer to query for the permissions related to creating, updating, or deleting firewall rules. These permissions are usually associated with compute.firewalls.create, compute.firewalls.update, and compute.firewalls.delete. By checking which principals have these permissions, you can determine who has the ability to change firewall rules in your Google Cloud project.
NEW QUESTION # 294
A large financial institution is moving its Big Data analytics to Google Cloud Platform. They want to have maximum control over the encryption process of data stored at rest in BigQuery.
What technique should the institution use?
Answer: C
Explanation:
If you want to manage the key encryption keys used for your data at rest, instead of having Google manage the keys, use Cloud Key Management Service to manage your keys. This scenario is known as customer-managed encryption keys (CMEK). https://cloud.google.com/bigquery/docs/encryption-at-rest
NEW QUESTION # 295
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?
Answer: D
Explanation:
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).
NEW QUESTION # 296
Your DevOps team uses Packer to build Compute Engine images by using this process:
1. Create an ephemeral Compute Engine VM.
2. Copy a binary from a Cloud Storage bucket to the VM's file system.
3. Update the VM's package manager.
4. Install external packages from the internet onto the VM.
Your security team just enabled the organizational policy, constraints/ compute.vmExternalIpAccess, to restrict the usage of public IP Addresses on VMs. In response, your DevOps team updated their scripts to remove public IP addresses on the Compute Engine VMs; however, the build pipeline is failing due to connectivity issues.
What should you do? (Choose two.)
Answer: C,E
Explanation:
Provision a Cloud NAT instance (Option B): Cloud NAT allows your Compute Engine instances without public IP addresses to access the internet while preserving the security restrictions imposed by your organizational policy. By provisioning a Cloud NAT instance in the same VPC and region as your Compute Engine VMs, you enable outbound connectivity for these VMs.
Enable Private Google Access (Option C): Enabling Private Google Access on the subnet where your Compute Engine VMs are deployed allows these instances to access Google Cloud services over the private IP address range. This can help with accessing external resources needed during the Packer image build process without exposing the VMs to the public internet.
NEW QUESTION # 297
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