Handbook

Existing cyber security solutions, such as firewalls, access controls, cyber threat intelligence and hunting, penetration testing, intrusion detection and prevention, and cryptography-based applications require automation and orchestration for achieving Intelligent Security in critical infrastructure systems and networks. Intelligent Security is a new trend in contemporary cyber security theories and practicals that develop artificial intelligence and machine learning for cyber security systems. This aims at devising intelligent methods for offensive and defensive applications, and the automation of the security processes to enhance efficiency and reduce human errors.

This course covers the fundamentals of machine learning theories, their practical implementation, and their utilisation in cyber security applications. Students learn data acquisition, exploration and visualisation techniques for cyber security industry challenges. Students also learn descriptive statistics and probabilistic models as the fundamentals of developing machine learning algorithms. Moreover, students practically learn supervised and unsupervised machine learning algorithms to solve red-blue teaming problems, along with industry standards and best practices.