cyber-security-resources/ai_security/AI Security Best Practices/secure-deployment.md
2023-07-29 21:23:00 -04:00

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AI Secure Deployment

High-level list of AI Secure Deployment best practices:

Best Practice Description
Use Secure APIs All communication with the AI model should be done using secure APIs that use encryption and other security protocols.
Implement Authentication and Access Controls Ensure only authorized individuals can access the deployed AI models and associated data.
Use Secure Communication Channels All data exchanged with the AI model should be done over secure, encrypted communication channels.
Regular Updates and Patching Ensure the software, libraries, and dependencies used by your AI model are up to date and patched for known vulnerabilities.
Monitor System Usage and Performance Monitor for any anomalies that could indicate a security breach, such as unexpected spikes in system usage or a sudden decline in model performance.
Test for Robustness Regularly test your AI model's robustness to adversarial attacks and other types of unexpected inputs.
Implement Secure Data Storage Ensure that data used by your AI model, both for training and inference, is stored securely.
Privacy-preserving Techniques If your AI model handles sensitive data, consider using privacy-preserving techniques such as differential privacy or federated learning.
Plan for Incident Response Have a plan for how to respond if a security incident does occur, including steps for identifying the breach, containing it, investigating it, and recovering from it.
Regular Audits Regularly audit your AI system for potential security vulnerabilities.