Security of Machine Learning Systems

Catalog description

Explores cutting-edge research at the intersection of machine learning and cybersecurity. Topics may include ML for cybersecurity, adversarial attacks and defenses, privacy-preserving and federated learning, and security of large language models (LLMs). Students engage with current research through paper presentations, discussions, and a project, preparing them for competitive research in emerging cybersecurity areas. Prerequisite: CSS 576 or CSS 581.