Our research focuses on the intersection of cybersecurity and artificial intelligence (AI), which covers a wide range of topics. We explore the application of AI technologies for defensive and offensive security, and also examine the potential for AI technologies to be used for malicious and unethical purposes. Furthermore, we investigate ways to enhance the security and robustness of AI technologies. In addition to these technical aspects, we also consider the Human Factors in Security. This includes the ways in which individuals interact with technology and the social and organizational factors that can affect security.
To make our research more accessible, we have organized our publications into categories based on their application domains. You can navigate to each of these categories using the floating menus provided, and access recent publications to stay informed on the latest developments in our research areas.
If you wish to view a complete list of our publications, we recommend visiting the individual profiles of our team members. You can find more information about their research interests and expertise, as well as a list of their publications.
Currently, we are actively seeking PhD students (self-funded) to work on research projects related to cybersecurity. If you have a Bachelor’s degree in a Computer Science-related field (with a UK equivalent of 1st or 2nd upper), and have a strong interest in any of the above areas, please don’t hesitate to get in touch with us. We welcome enthusiastic and motivated individuals who are passionate about advancing the field of cybersecurity through cutting-edge research. Please contact us for more information on how to apply for our PhD program.
AI-Powered Automated vulnerability anti-patterns system for software security (TRL 5-7 prototype development) - CyberShell Solutions
AI-Powered Automated vulnerability anti-patterns system for software security (feasibility study extension) - CyberShell Solutions
AI-Powered Automated vulnerability anti-patterns system for software security (feasibility study) - CyberShell Solutions
Protecting Vehicles from Cyber Attacks - Horiba Mira
Anomaly Detection in Controller Area Networks (CAN bus) - Horiba Mira
Towards a Robust, Effective and Resource Efficient Machine Learning Technique for IoT Security Monitoring (Link)
Effective Detection of Cyber-attacks against IoTs in Critical Infrastructures (Link)
Protecting vehicles from cyber attacks : Context aware AI-based intrusion detection system to detect cyber attacks on the automotive CAN bus (Link)
|Hatem Ahriz||Dipto Arifeen||Shadi Hajar||Ian Haris|
|Harsha Kalutarage||Chris McDermott||MS Mekala||Chris Middleton|
|Lankesh Munasinghe||U. Otokwala||Nadeeka Pathirana||Andrei Petrovski|
|Sampath Rajapaksha||Janaka Senanayake|