Ransomware

This paper proposed a three-stage feature selection method that effectively reduces the dimensionality of the data and considers the varying importance of the different feature groups in the classification of ransomware families.

This PhD research project focuses on developing an adaptive intrusion detection system that leverages advanced machine learning algorithms to detect and mitigate emerging ransomware threats. By designing novel ML techniques capable of analysing large-scale datasets of ransomware samples and benign files, the project aims to create a highly accurate and responsive defence against rapidly evolving ransomware attacks.