Lecturer in Computer Science
- I am an Early Career researcher interested in cybersecurity, network anomaly detection AI, and Machine Learning. View my Orchid ID.
Teaching and supervision
Research interests for potential research students
- Cybersecurity
- Network Anomaly Detection
- Machine Learning
- AI
Research
My PhD is in AI and Cybersecurity entitled A Deep Learning-based Approach to Identifying and Mitigating Network Attacks Within SDN Environments Using Non-standard Data Sources Network Anomaly Detection.
I am interested in:
- Network Anomaly Detection
- Machine Learning
- Artificial Intelligence
- Cybersecurity
- A Trust-Based Cooperative System for Efficient Wi-Fi Radio Access Networks
- IEEE Access
- 2023 | Journal article
- DOI: 10.1109/ACCESS.2023.3338177
- Contributors: Alessandro Raschellà; Max Hashem Eiza; Michael Mackay; Qi Shi; Matthew Banton
- Model-Based Security Assessment on the Design of a Patient-Centric Data Sharing Platform
- 2022 | Book chapter
- DOI: 10.1007/978-3-031-16011-0_5
- Contributors: Matthew Banton; Thais Webber; Agastya Silvina; Juliana Bowles
- Conflict-Free Access Rules for Sharing Smart Patient Health Records
- 2021 | Book chapter
- DOI: 10.1007/978-3-030-91167-6_3
- Contributors: Matthew Banton; Juliana Bowles; Agastya Silvina; Thais Webber
- Design of a Trustworthy and Resilient Data Sharing Platform for Healthcare Provision
- 2021 | Book chapter
- DOI: 10.1007/978-3-030-86507-8_14
- Contributors: Matthew Banton; Juliana Bowles; Agastya Silvina; Thais Webber
- Intrusion Detection Using Extremely Limited Data Based on SDN
- Proceedings of 2020 IEEE 10th International Conference on Intelligent Systems Intrusion
- 2020-08-28 | Conference paper
- DOI: 10.1109/IS48319.2020.9199950
- Contributors Matthew Banton; Nathan Shone; William Hurst; Qi Shi
- 6th International Conference on Information and Communication Technologies for Disaster Management, ICT-DM 2019
- 2019-12-18 | Conference paper
- DOI: 10.1109/ICT-DM47966.2019.9032959
- Contributors Matthew Banton; Nathan Shone; William Hurst; Qi Shi:
- Visualising Network Anomalies in an Unsupervised Manner Using Deep Network Autoencoders
- The Fourth International Conference on Applications and Systems of Visual Paradigms VISUAL 2019
- 2019-06-30 | Conference paper
- Contributors Matthew Banton; Nathan Shone; William Hurst; Qi Shi