AI Product Security: Foundations and Proactive Security for AI

Introduction

• Securing AI products
• Why does AI security matter?

1. Fundamentals of AI Security

• Essentials of AI security
• Common threats and vulnerabilities in AI systems
• Ethical concerns, privacy, fairness, and user rights
• Security across the AI life cycle

2. Building Resilient AI: Securing AI Models, Data, and Deployment

• Overview of adversarial AI attacks
• Attacks on AI algorithms with real-world examples
• Attacks on filters
• Subversion of AI artifacts in supply chain attacks
• Defending against adversarial attacks
• Data security in AI systems
• Model security: Protecting AI models
• Securing AI deployment pipelines
• Secure deployment strategies for AI systems

3. AI Security Governance, Risk Management, and Compliance

• Governance in AI product security
• AI risk management
• AI audit and compliance

4. System Design Principles

• Foundational principles of AI system design
• Advanced principles of AI system design

Conclusion

• Next steps