This lecture provides a comprehensive introduction to the security, robustness, privacy, and safety of modern Artificial Intelligence (AI) systems, with a particular focus on deep learning. While AI systems are increasingly deployed in safety-critical and security-sensitive domains, they remain vulnerable to a broad spectrum of adversarial, privacy, and misuse-related threats. The course systematically studies these vulnerabilities and presents state-of-the-art defense mechanisms, risk management approaches, and protection techniques.
Students will learn how to analyze AI systems from a cybersecurity perspective across the entire AI lifecycle — from data collection and model training to deployment and post-deployment monitoring. The course integrates theoretical foundations with hands-on exercises, enabling students to implement attacks and defenses in practical machine learning settings.
- verantwortliche Lehrperson: Alexandra Dmitrienko
- verantwortliche Lehrperson: Mavulliahnagavenkata Sairaghavavarun Gadey
- verantwortliche Lehrperson: Venkata Maruti Sesha Giri Marella