Course Overview
This course introduces the security risks and defenses associated with artificial intelligence and machine learning systems. Students examine AI/ML threat models, data integrity and provenance, secure model pipelines, adversarial attacks, privacy risks, and governance frameworks such as the NIST AI Risk Management Framework. Through hands-on labs, students design, test, and defend ML systems against adversarial manipulation while assessing residual risk and compliance considerations.
Prerequisites: CYBR 501 and CYBR 502