Advanced Systems Engineering for Cybersecurity. 3 credits

Catalog description

This doctoral course explores advanced systems engineering for AI-enabled and autonomous systems, focusing on design, validation, and assurance. Students model complex human-cyber systems, analyze AI-specific threats, and validate trustworthiness using model-based, probabilistic, and formal methods. Topics include adversarial ML, data poisoning, model inversion, prompt injection, data exfiltration, and hallucination risks, contrasted with traditional system threats. Using model-based systems engineering, Bayesian reasoning, digital twins, and runtime assurance, students design secure, resilient architectures. The final project develops and defends an assurance case for an AI system. Proficiency in a programming language, a modeling language, and systems engineering principles is required. Graduates gain expertise in: 1) advanced design and validation, 2) AI and autonomy threat analysis, and 3) integrated assurance and trust frameworks. Offered by Cyber Security Engineering . May not be repeated for credit.