Cybersecurity Research at Robert Gordon University, UK

Research Areas and Recent Publications

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.

IoT and Cyber Physical Systems Security

CAN-MIRGU: A Comprehensive CAN Bus Attack Dataset from Moving Vehicles for Intrusion Detection System Evaluation in Symposium on Vehicles Security and Privacy (VehicleSec) in NDSS - 2024 - Watch Video
Beyond vanilla: Improved autoencoder-based ensemble in-vehicle intrusion detection system in Journal of Information Security and Applications - 2023
Towards a Robust, Effective and Resource Efficient Machine Learning Technique for IoT Security Monitoring in Computers & Security - 2023
Bayesian Optimized Autoencoder for Predictive Maintenance of Smart Packaging Machines in 6th International Conference on Industrial Cyber-Physical Systems (ICPS) - 2023
Ensemble Common Features Technique for Lightweight Intrusion Detection in Industrial Control System in 6th International Conference on Industrial Cyber-Physical Systems (ICPS) - 2023
Advanced Persistent Threats Detection based on Deep Learning Approach in 6th International Conference on Industrial Cyber-Physical Systems (ICPS) - 2023
Improving In-vehicle Networks Intrusion Detection Using On-Device Transfer Learning in Symposium on Vehicles Security and Privacy (VehicleSec) in NDSS - 2023
AI-Based Intrusion Detection Systems for In-Vehicle Networks: A Survey in ACM Computing Surveys - 2023
Keep the Moving Vehicle Secure: Context-Aware Intrusion Detection System for In-Vehicle CAN Bus Security in 14th International Conference on Cyber Conflict: Keep Moving!(CyCon) - 2022
Robust, effective and resource efficient deep neural network for intrusion detection in IoT networks in 8th ACM on Cyber-Physical System Security Workshop in ACM Asia CCS - 2022
Resource Efficient Federated Deep Learning for IoT Security Monitoring in Attacks and Defenses for the Internet-of-Things: 5th International Workshop in ESORICS - 2022
Topology for Preserving Feature Correlation in Tabular Synthetic Data in 15th International Conference on Security of Information and Networks (SIN) - 2022
Framework for Detecting APTs Based on Steps Analysis and Correlation in Springer Security and Resilience in Cyber-Physical Systems: Detection, Estimation and Control - 2022
Automated microsegmentation for lateral movement prevention in industrial internet of things (IIoT) in 14th International Conference on Security of Information and Networks (SIN) - 2021
Improving intrusion detection through training data augmentation in 14th International Conference on Security of Information and Networks (SIN) - 2021
Comparative Study of Malware Detection Techniques for Industrial Control Systems in 14th International Conference on Security of Information and Networks (SIN) - 2021
Effective detection of cyber attack in a cyber-physical power grid system in Future of information and communication conference (FICC) - 2021
Resource efficient boosting method for IoT security monitoring in IEEE 18th Annual Consumer Communications & Networking Conference (CCNC) - 2021
Memory efficient federated deep learning for intrusion detection in IoT networks in AI-CyberSec: Workshop on Artificial Intelligence and Cyber Security - 2021
Detecting malicious signal manipulation in smart grids using intelligent analysis of contextual data in 13th International Conference on Security of Information and Networks (SIN) - 2020
Detection of false command and response injection attacks for cyber physical systems security and resilience in 13th International Conference on Security of Information and Networks (SIN) - 2020
Handling minority class problem in threats detection based on heterogeneous ensemble learning approach in International Journal of Systems and Software Security and Protection (IJSSSP) - 2020
The use of machine learning algorithms for detecting advanced persistent threats in 12th International Conference on Security of Information and Networks (SIN) - 2019
Reducing computational cost in IoT cyber security: case study of artificial immune system algorithm in 16th International security and cryptography conference (SECRYPT) - 2019
Context-aware anomaly detector for monitoring cyber attacks on automotive CAN bus in 3rd ACM Computer Science in Cars Symposium - 2019

Network Security

MADONNA: Browser-Based MAlicious Domain Detection Through Optimized Neural Network with Feature Analysis in 38th IFIP TC 11 International Conference on Information Security and Privacy Protection (IFIPSec) - 2023
3R: A reliable multi agent reinforcement learning based routing protocol for wireless medical sensor networks in Computer Networks - 2023
Security Challenges in Wireless Body Area Networks for Smart Healthcare in Artificial Intelligence for Disease Diagnosis and Prognosis in Smart Healthcare - 2023
DQR: a double Q learning multi agent routing protocol for wireless medical sensor network in Security and Privacy in Communication Networks: 18th EAI International Conference, SecureComm - 2022
A Robust Exploration Strategy in Reinforcement Learning Based on Temporal Difference Error in AI 2022: Advances in Artificial Intelligence: 35th Australasian Joint Conference, AI - 2022
A survey on wireless body area networks: Architecture, security challenges and research opportunities in Computers & Security - 2021
TrustMod: A Trust Management Module For NS-3 Simulator in IEEE 20th International Conference on Trust, Security and Privacy in Computing and Communications (TrustCom) - 2021
Ltms: A lightweight trust management system for wireless medical sensor networks in IEEE 19th International Conference on Trust, Security and Privacy in Computing and Communications (TrustCom) - 2020
Etaree: An effective trend-aware reputation evaluation engine for wireless medical sensor networks in IEEE Conference on Communications and Network Security (CNS) - 2020
Anomaly Detection in Network Traffic Using Dynamic Graph Mining with a Sparse Autoencoder in IEEE 18th International Conference on Trust, Security and Privacy in Computing and Communications (TrustCom) - 2019

Software Security

Defendroid: Real-time Android code vulnerability detection via blockchain federated neural network with XAI in Journal of Information Security and Applications - 2024
FedREVAN: Real-time Detection of Vulnerable Android Source Code through Federated Neural Network with XAI in WASP at 28th European Symposium on Research in Computer Security (ESORICS 2023)
Enhancing Security Assurance in Software Development: AI-based Vulnerable Code Detection with Static Analysis in SecAssure at 28th European Symposium on Research in Computer Security (ESORICS 2023)
Android Code Vulnerabilities Early Detection Using AI-Powered ACVED Plugin in 37th Annual IFIP WG 11.3 Conference on Data and Applications Security and Privacy (DBSec'23)
Labelled Vulnerability Dataset on Android Source Code (LVDAndro) to Develop AI-Based Code Vulnerability Detection Models in 20th International security and cryptography conference (SECRYPT) - 2023
Android source code vulnerability detection: a systematic literature review in ACM Computing Surveys - 2023
Developing secured Android applications by mitigating code vulnerabilities with machine learning in ACM on Asia Conference on Computer and Communications Security (AsiaCCS) - 2022
AI-Powered Vulnerability Detection for Secure Source Code Development in 15th International Conference on Security for Information Technology and Communications (SECITC) - 2022
Android Mobile Malware Detection Using Machine Learning: A Systematic Review in MDPI Electronics Special Issue in High Accuracy Detection of Mobile Malware Using Machine Learning - 2021
Naive Bayes: applications, variations and vulnerabilities: a review of literature with code snippets for implementation in Soft Computing - A Fusion of Foundations, Methodologies and Applications - 2021

Human-centred Security

Replacing Human Input in Spam Email Detection Using Deep Learning in Artificial Intelligence in HCI: 3rd International Conference, AI-HCI - 2022
Dimensions of ‘socio’vulnerabilities of advanced persistent threats in International Conference on Software, Telecommunications and Computer Networks (SoftCOM) - 2019
Evaluating awareness and perception of botnet activity within consumer internet-of-things (IoT) networks in MDPI Informatics Special Issue on Human Factors in Security and Privacy in IoT (HFSP-IoT) - 2019

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.

Completed/ Ongoing Research Projects

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)
A Reliable Trust-Aware Reinforcement Learning Based Routing Protocol for Wireless Medical Sensor Networks (Link-1, Link-2)
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-1, Link-2)
Identifying enhanced mechanisms to develop secure mobile applications (Link-1, Link-2)
IoT based Inferential Measurement System for Asset Integrity and Security (Link-1, Link-2)