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Cybersecurity for Artificial Intelligence & Machine Learning

95-767

Units: 6

Description

Advancements in Artificial Intelligence (AI) and Machine Learning (ML) have allowed for a surge in adoption of AI & ML solutions to address problems across numerous domains. With this rising reliance on AI & ML in many organizations, it is critical that such systems are protected from malicious activities. This course will discuss AI & ML cybersecurity issues, explore case studies of AI & ML cyber incidents, present AI & ML adversarial techniques, and demonstrate secure design approaches to protect AI & ML systems. With an emphasis on machine learning, the course will focus on secure machine learning systems development approaches and secure machine learning operations (MLOps). Students are expected to have knowledge of fundamental statistics and the ability to program in Python.

Learning Outcomes

The goals of the course are for students to understand the security issues relevant to artificial intelligence (AI) & machine learning (ML) systems and be able to produce secure AI/ML engineering guidance to mitigate security risks in AI/ML systems. Students will be able to express AI/ML security concerns, convey AI/ML security risks including cases studies of know incidents, and demonstrate ways to address AI/ML security issues.

Prerequisites Description

(90812 or 90819 or 95888 or 95898 or 95895 or 95896) and (90707 or 90711 or 90777 or 95796)