Matt's PhD is in the Electronics and Electrical Engineering department of Wolfson School, his Research Theme is Communications. He began his PhD in January 2019. He is supervised by Dr. Kostas Kyriakopoulos and Prof. Sangarapillai Lambotharan, and being funded by the Doctoral College.
Matt obtained a BSc in Computer Science from De Montfort University (DMU) in 2016. He went on to study an MSc in Internet Computing and Network Security at Loughborough University and graduated in 2018. He has an interest in the Internet of Things, the interconnection micro and smart devices. He is a keen programmer and can program efficiently in Python, C and Java and also enjoys web development, leading him to also code in PHP.
PhD Project Title: Detecting multi-stage cyber-attacks using intrusion detection systems and machine learning
As Internet usage, Cloud Computing and Internet of Things (IoTs) continue to grow at a rapid pace, so does the need for more intelligent intrusion detection. IoT, as an example of edge computing is considered a vulnerable point of network security, which is seen as a major concern as by 2030 it is anticipated that there will be up to 30 billion IoT devices connected to the Internet. These interconnected micro and smart devices have left a gap in network security that is being exploited by malicious actors. Intrusion Detection Systems (IDS) are one way of detecting such attacks, although sometimes struggle as these attacks are increasingly pre-panned multi-stage attacks (MSA). These MSAs are difficult to detect as each stage may appear benign, but when all stages are combined become a malicious cyber attack. Further, these attacks may span over the course of days, weeks or even months.
Matt's research is aimed at detecting these network attacks by utilising anomaly-based IDS, with the assistance of classification machine learning algorithms such as artificial neural networks and logistic regression.