Intelligent Malware Profiling for Automated Campaign Detection

The project aim is to investigate the question whether it is possible to develop algorithms to profile the characteristics of malware and link these to targeted distribution campaigns. The novel element will be research into large-scale, near real-time automatic malware fingerprinting. The student's objective is to look at linking analyses to threat vectors including, but not limited to, certain types of malware, organised criminal gangs, infection mechanisms and device/software type. The PhD will require a blend of creative thought around infection pathways, artificial intelligence methods for representation of behavioural profiles, and scalable analysis using the distributed Cloud services.
The outcomes of the project will lead to novel computer science articles and potentially a novel service for the Airbus Security Operations Centre (SOC). Airbus Group Innovations has an established international reputation for innovative research with impactful application in the areas of Risk & Security, among others.
The student will be given full access to Airbus facilities in Newport and be integrated into the Cyber Operations team as a member of the research unit, providing first-hand industry R&T experience. The research will develop skills in malware reverse engineering, artificial intelligence methods for representing malware behaviour, and Cloud deployment of machine learning models on massive datasets.