Google Cloud AI Security Best Practices
Secure your AI workloads on Google Cloud Platform with comprehensive security controls for Vertex AI and other GCP AI services.
Vertex AI Security
- • VPC Service Controls
- • Private Google Access
- • Workload Identity
- • Model versioning and governance
Identity & Access
- • IAM policies and roles
- • Service accounts
- • Organization policies
- • Access transparency
Data Protection
- • Cloud KMS encryption
- • Customer-managed keys
- • Data Loss Prevention API
- • VPC-SC perimeters
Security Architecture
Network Security
- • Deploy in VPC with firewall rules
- • Use Private Service Connect
- • Implement Cloud Armor for DDoS protection
- • VPC Service Controls for data exfiltration prevention
Encryption & Key Management
- • Default encryption at rest for all data
- • Customer-managed encryption keys (CMEK)
- • Cloud External Key Manager (EKM)
- • TLS 1.3 for data in transit
Monitoring & Compliance
- • Cloud Logging for audit trails
- • Cloud Monitoring for metrics
- • Security Command Center
- • Compliance reports and certifications