COURSE SYLLABUS

On completion of the course the student shall:

• demonstrate comprehension of fundamental AI concepts relevant to cybersecurity
• display knowledge of how Artificial Intelligence (AI) and Machine Learning (ML) methods can be exploited by adversaries for offensive purposes
• display knowledge of how AI and ML can be employed defensively to detect and mitigate cybersecurity threats

• demonstrate skills in identifying and analysing AI/ML-driven cybersecurity threats such as phishing, deepfakes, and automated attacks
• demonstrate the ability to apply AI/ML methods for log analysis, anomaly detection, and intrusion detection

• demonstrate the ability to critically assess the ethical implications of using AI in cybersecurity
• demonstrate an understanding of the strengths and limitations of AI/ML methods in cybersecurity contexts

The course provides a comprehensive overview of the intersection of cybersecurity and AI. It introduces core AI and ML concepts and their applications within the cybersecurity domain. It covers how adversaries exploit AI technologies to conduct sophisticated cyber-attacks such as personalised phishing, deepfake generation, and automated hacking techniques. Concurrently, the course explores defensive strategies utilizing AI/ML, including anomaly detection, behavioral analytics, and automated log analysis for threat detection and incident response.

The course includes the following elements:

• Fundamentals of AI and ML
• AI/ML-driven offensive cybersecurity techniques (e.g. personalized phishing and social engineering, deepfakes and misinformation, automated attack strategies,
• AI/ML-driven defensive cybersecurity techniques (e.g. intrusion detection systems, behavioral and anomaly detection, automated analysis and response, and ethical and societal impacts of AI in cybersecurity

Lectures, seminars, and project work.

Language of instruction is English.