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| Section | Objectives |
|---|---|
| Topic 1: Configure access within a cloud solution environment | - Identity and Access Management (IAM)
|
| Topic 2: Configure network security | - Google Cloud network security controls
|
| Topic 3: Ensure data protection | - Encryption and key management
|
| Topic 4: Manage operations within a cloud security environment | - Security monitoring and operations
|
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NEW QUESTION # 58
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?
Answer: C
Explanation:
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
NEW QUESTION # 59
Your organization is building a real-time recommendation engine using ML models that process live user activity data stored in BigQuery and Cloud Storage. Each new model developed is saved to Artifact Registry.
This new system deploys models to Google Kubernetes Engine and uses Pub/Sub for message queues. Recent industry news has been reporting attacks exploiting ML model supply chains. You need to enhance the security in this serverless architecture, specifically against risks to the development and deployment pipeline.
What should you do?
Answer: B
Explanation:
To enhance the security of your machine learning (ML) model supply chain within a serverless architecture, it's crucial to implement measures that protect both the development and deployment pipelines.
* Option A: While limiting external dependencies and rotating encryption keys are good security practices, they do not directly address the risks associated with the ML model supply chain.
* Option B: Implementing container image vulnerability scanning during development and pre- deployment helps identify and mitigate known vulnerabilities in your container images. Enforcing Binary Authorization ensures that only trusted and verified images are deployed in your environment. This combination directly strengthens the security of the ML model supply chain by validating the integrity of container images before deployment.
* Option C: Sanitizing training data and applying role-based access controls are important security practices but do not specifically safeguard the deployment pipeline against compromised container images.
* Option D: While strict firewall rules and intrusion detection systems enhance network security, they do not specifically address vulnerabilities within the container images or the deployment process.
Therefore, Option B is the most effective approach, as it directly addresses the security of the development and deployment pipeline by ensuring that only vetted and secure container images are used in your environment.
References:
* Container Scanning Overview
* Binary Authorization Overview
NEW QUESTION # 60
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:
https://cloud.google.com/bigquery/docs/encryption-at-rest
NEW QUESTION # 61
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?
Answer: A
NEW QUESTION # 62
Your team sets up a Shared VPC Network where project co-vpc-prod is the host project. Your team has configured the firewall rules, subnets, and VPN gateway on the host project. They need to enable Engineering Group A to attach a Compute Engine instance to only the 10.1.1.0/24 subnet.
What should your team grant to Engineering Group A to meet this requirement?
Answer: C
Explanation:
https://cloud.google.com/vpc/docs/shared-vpc#svc_proj_admins
https://cloud.google.com/vpc/docs/shared-vpc#svc_proj_admins
NEW QUESTION # 63
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