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Dr Biju Issac is an Associate Professor (Networks and Cyber Security) at Northumbria University and Director of the Academic Centre of Excellence in Cyber Security Research (ACE-CSR). His research focuses on AI security, LLM security, insider threat detection, malware and botnet detection, uncertainty estimation, ethical hacking, and resilient networked systems. He leads and contributes to projects funded by the Alan Turing Institute, NATO, Innovate UK, and industry partners. He is also the deputy leader of CyberNets (Cybersecurity and Networks) Research Group. He joined Northumbria as an academic staff member in September 2018.
He holds funded projects with the Alan Turing Institute (Laboratory for AI Security Research (LASR)), working on "AI Security" as follows: (1) 'Synthetic Data detection' (or specifically, Model-Agnostic Detection of Synthetic Data Using Uncertainty-Enhanced Non-Conformity Measures: A Mixture-of-Experts Approach) for UK Defence and Security, and (2) 'Closed-Box Inference of Large Language Models: Dual-Channel Probing, Traffic Analysis, and Quantization-Aware Fingerprinting' for UK Defence and National Security and US Defence and National Security. He has completed a funded project led by Kent - 'LLM-Facilitated and Graph-Based Analysis of Relationships Between Organisations' with the Alan Turing Institute, working for NCSC, and completed a funded project for Lockheed Martin Space (USA) to create an 'Intelligent Vulnerability Detection and Reporting Automation' tool. He has also completed funded projects, such as the NATO Advanced Training Course in 'Cyber Defence and Ethical Hacking' for Ukrainians from Lviv Polytechnic National University, Innovate UK-funded 'Ethical Hacking for Girls in the North East of England', etc. He is the Chair of the AI-Cybersecurity SIG (AI-Cyber SIG) under CRANE, an EPSRC-funded network to strengthen the UK’s cybersecurity research ecosystem, led by Oxford University.
He was the Head of the Subject (Networks and Cyber Security) from 2022 to 2025 and the Programme Leader of BSc (Computer Networks and Cyber Security) and BSc (Computer and Digital Forensics) from 2018 to 2023. He has done PhD in Networking and Mobile Communication (focusing on 802.11 Mobility and Security), having finished Bachelor of Engineering (BE) in Electronics and Communication Engineering and Master of Computer Applications (MCA) with a first. He is a Chartered Engineer (CEng), Senior IEEE member, Senior Fellow of HEA and EPSRC Associate Peer Review College member.
He founded Northumbria Cyber Clinic in 2018 that works with NEBRC (led by the police), to secure businesses against cyber attacks, where students are appointed to work as part-time ethical hackers. He currently teaches Cisco CCNA modules covering Networking, Switching, Routing and Security. He has won the ‘Innovator of the Year’ award in Dynamites 2020, organised by Dynamo North East and was shortlisted as a finalist in ‘Excellence in Cybersecurity’ for E&T Innovation Awards 2020, organised by IET, UK.
He has worked as a Computer Science academic staff at Teesside University since July 2012 where he was part of the Machine Intelligence research group and taught Network and System Administration modules. Prior to that, he worked as a Computer Science academic staff at an Australian University (Swinburne University of Technology) in Malaysia and at Madras Christian College under Madras University in India. He started his job as a project assistant at the Indian Institute of Science (IISc), Bangalore in India, where he worked on a funded Tomography project. He has authored 100+ publications such as conference papers, journal papers, book chapters and edited books. He is one of the Editors of Scientific Reports (Springer Nature) and IET Wireless Sensor Systems (Wiley) and the Editor in Chief (EiC) of the International Journal of Information and Computer Security.
Links to check:
(1) Personal Website
(2) University Research Profile
(3) Northumbria ACE-CSR
(4) AI-Cyber SIG
Campus Address
Room ELB120, Ellison BuildingNorthumbria University
Newcastle upon Tyne
NE1 8ST
0191 227 3365
His research interests are AI Security, Cyber Security (Malware/Botnets), Networks (wired and wireless), IoT Security (smart buildings), Satellite/drone/UAV communication networks and security, Secure routing protocols, AI/ML applications, Android security, Robotics automation/security and Cloud computing optimisations.
- Please visit the Pure Research Information Portal for further information
- Bayesian-Optimized Deep Learning for Adaptive Real-Time FDIA Detection in Smart Grid Demand Response Systems, Tirulo, A., Chauhan, S., Issac, B., Gebremariam, L., Vasilakos, A., Shafie-khah, M. 27 Feb 2026, In: IEEE Transactions on Smart Grid
- Insider Threat Detection Using GCN and Bi-LSTM with Explicit and Implicit Graph Representations, Yumlembam, R., Issac, B., Jacob, S., Yang, L., Krishnan, D. 22 Dec 2025, In: IEEE Transactions on Artificial Intelligence
- Enhancing Decision-Making in Windows PE Malware Classification During Dataset Shifts with Uncertainty Estimation, Yumlembam, R., Issac, B., Jacob, S. 3 Dec 2025, In: Knowledge-Based Systems
- Detection of AI generated images using combined uncertainty measures and particle swarm optimised rejection mechanism, Yumlembam, R., Issac, B., Aslam, N., Kollonoor Babu, E., Collyer, J., Kennedy, F. 17 Dec 2025, In: Scientific Reports
- Comprehensive Botnet Detection by Mitigating Adversarial Attacks, Navigating the Subtleties of Perturbation Distances and Fortifying Predictions with Conformal Layers, Yumlembam, R., Issac, B., Jacob, S., Yang, L. 1 Nov 2024, In: Information Fusion
- Please visit the Pure Research Information Portal for further information
- Publication Peer-review: Scientific Reports (Journal) 2025
- Editorial work: International Journal of Information and Computer Security (Journal) 2020
- Publication Peer-review: IET Wireless Sensor Systems (Journal) 2017
- Publication Peer-review: IEEE Access (Journal) 2017
- Henry Kabuye AI-Based Intelligent Multi-stage and User-centric Ransomware Attack Detection Start Date: 01/10/2023
- Adrian Brissett Threat Detection Using AI and Behavioral Analysis Start Date: 01/03/2026
- Christopher Taylor How can Federated Learning (FL) and Explainable AI (XAI) be integrated to detect and prevent botnet attacks in BIM-based IoT systems, while addressing challenges of model complexity, data privacy, scalability, and real-time operation? Start Date: 01/10/2023
- Aaron Gabriel A Mixture-of-Experts System for Fairer Hate Speech Detection using Synthetic Training Data Start Date: 20/10/2022
- Saqib Hussain Forensically Informed Multi-model Machine Learning Framework for Fake News Detection Start Date: 01/10/2024
PhD
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