This course explores the intersection of artificial intelligence (AI) and cybersecurity, focusing on vulnerabilities, defense mechanisms, and ethical implications of AI systems. Students will explore adversarial attacks, data poisoning, privacy breaches, and model vulnerabilities while learning to design robust countermeasures like adversarial training, anomaly detection, and privacy-preserving techniques (e.g., federated learning). The course bridges technical challenges with ethical considerations, addressing bias, regulatory policies, and societal impacts.

Continuous Assessment: 50%

Examination: 50%

Examination Duration: 2 hours

Min. Examination Passing Requirement: 30%

For a student to pass the course, at least 30% of the maximum mark for the examination must be obtained.