Welcome to Security Foundation - Discuss all things Google Cloud platform security!

[anilnandigam]

Hi everyone,

A big welcome to all new members joining the Google Cloud Security Foundation forum!

This space is dedicated to discussing the core principles, best practices, and essential services for building a secure foundation on Google Cloud Platform. We focus specifically on understanding and utilizing the cloud-first security controls that are integral parts of the Google Cloud platform itself.

Topics we often cover here include these core platform controls:

• Identity and Access Management (IAM) fundamentals
• Network security basics (VPCs, Firewall Rules, Cloud Armor basics)
• Data security concepts (Encryption at rest/in transit)
• Logging and Monitoring essentials (Cloud Logging, Cloud Monitoring)
• Understanding the Shared Fate Model on Google Cloud
• Cloud Security Posture Management & more
• Regulations and compliance standards

Please feel free to:

• Introduce yourself! Let us know a bit about your background and what you hope to learn or discuss.
• Ask questions. No question is too basic when building a strong foundation with these controls.
• Share your knowledge and experiences. Help others learn from your journey.

We're excited to have you here and look forward to building a secure cloud together!

Best regards,

Anil

[manishgaur · Accepted solution]

Establishing a secure foundation for Generative AI (Gen AI) workloads on Google Cloud requires a multi-layered approach. Here's what you should consider:

• Data Privacy: Protect training data and user input, control output, and meet compliance requirements. Use Cloud Storage, BigQuery (with KMS CMEK and VPC-SC), Data Loss Prevention API, and IAM.
• Model Integrity: Prevent model theft and tampering. Use Vertex AI Model Registry, Artifact Registry, IAM, Binary Authorization, and Vertex AI Pipelines.
• Access Management: Use least privilege and secure APIs. Use IAM, service accounts, Identity-Aware Proxy, and API Gateway.
• Infrastructure Protection: Secure networks and compute resources. Use VPC, GKE security features, Shielded VMs, Cloud Armor, and Security Command Center.

Also, implement robust logging and monitoring, have an incident response plan and more!!!
For more!! Check out us at the Security Foundation Booth in Security Hub.

[CloudSecNinja]

What are the critical security considerations and recommended Google Cloud controls when establishing a secure foundation for Generative AI workloads?

[manishgaur · Accepted solution]

Establishing a secure foundation for Generative AI (Gen AI) workloads on Google Cloud requires a multi-layered approach. Here's what you should consider:

• Data Privacy: Protect training data and user input, control output, and meet compliance requirements. Use Cloud Storage, BigQuery (with KMS CMEK and VPC-SC), Data Loss Prevention API, and IAM.
• Model Integrity: Prevent model theft and tampering. Use Vertex AI Model Registry, Artifact Registry, IAM, Binary Authorization, and Vertex AI Pipelines.
• Access Management: Use least privilege and secure APIs. Use IAM, service accounts, Identity-Aware Proxy, and API Gateway.
• Infrastructure Protection: Secure networks and compute resources. Use VPC, GKE security features, Shielded VMs, Cloud Armor, and Security Command Center.

Also, implement robust logging and monitoring, have an incident response plan and more!!!
For more!! Check out us at the Security Foundation Booth in Security Hub.

[anilnandigam · Accepted solution]

We have recently launched AI Protection Platform in Google Cloud that helps secure your Gen AI workloads. You can check out this blog for more info. 

@manishgaur has been helping our customers, so can share more on security considerations and recos.