AI Security Threats against Pervasive Robotic Systems (Academic / specialized course)

Robotics, automation, and AI systems are increasingly omnipresent in homes, industries, hospitals, public infrastructure, agriculture, and the military. As these systems become more deeply embedded, there are growing concerns around security, safety, accuracy, and trust. Failures or attacks on robotic systems can lead to severe consequences, including invasion of privacy, sabotage of critical operations, and physical harm.

Despite this, there is currently a lack of professionals trained specifically to understand and defend robotic systems that integrate AI. This gap motivates creating a curriculum that equips students with both theoretical understanding and hands-on experience with threats, attacks, and defensive strategies.

Target Audience & Prerequisites

• Senior undergraduate and graduate students in computer science, robotics, AI, cybersecurity, or related fields.

  Students should ideally have completed an introductory course in machine learning / artificial intelligence.

  Having some background or familiarity with robotics (sensors, actuators, planning, control) is recommended, though not strictly mandatory.

  Basic cybersecurity fundamentals are also helpful, though again not strictly required.