AI Security Best Practices: Protecting Your AI Systems
Essential security practices for AI systems including data protection, access control, and threat mitigation.
TL;DR
AI security requires protecting training data, securing model endpoints, implementing access controls, monitoring for adversarial inputs, and maintaining audit trails. Apply defense in depth with multiple layers of protection.
Data Security
Protect training data and knowledge bases with encryption, access controls, and monitoring. Implement data classification and handling procedures. Anonymize or mask sensitive data where possible.
Model Security
Secure model endpoints with authentication and rate limiting. Implement input validation to prevent injection attacks. Monitor for adversarial inputs and unusual patterns.
Access Control
Implement role-based access for AI system administration, model training, and user interactions. Apply principle of least privilege. Maintain comprehensive audit logs.
Monitoring and Response
Monitor AI systems for security anomalies, performance degradation, and unexpected behaviors. Establish incident response procedures specific to AI systems.