Dr Biju Issac

Associate Professor

Department: Computer and Information Sciences

Dr Biju Issac joined Northumbria as an academic staff in September 2018. He is an Associate Professor and Head of the Subject (Networks and Cyber Security). He is the Director of the Academic Centre of Excellence in Cyber Security Research (ACE-CSR). He is the deputy leader of CyberNets (Cybersecurity and Networks) Research Group.

He was the Programme Leader of BSc (Computer Networks and Cyber Security) and BSc (Computer and Digital Forensics) from 2018-2023. He has done PhD in Networking and Mobile Communication, 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 the Editor in Chief (EiC) of the International Journal of Information and Computer Security.

His personal profile: https://www.bijuissac.com/
University research profile: https://researchportal.northumbria.ac.uk/en/persons/biju-issac

Campus Address

Room ELB120, Ellison Building
Northumbria University
Newcastle upon Tyne
NE1 8ST

0191 227 3365

Email Biju

Research Themes and Scholarly Interests

His research interests are Networks (wired and wireless), Cyber Security (Malware/Botnets), Robotics automation and security, IoT device communication (smart buildings) and security, Satellite/drone/UAV communication networks and security, Secure routing protocols, Artificial Intelligence or machine learning applications, Android security and Cloud computing optimizations.

Key Publications

Please visit the Pure Research Information Portal for further information
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
Ensemble LOF-based detection of false data injection in smart grid demand response system, Tirulo, A., Chauhan, S., Issac, B. 1 May 2024, In: Computers and Electrical Engineering
Malware and botnet prevention in smart building IoT devices using blockchain-enabled federated learning, Taylor, C., Issac, B., Aslam, N., Rogage, K., Kelly, G. 24 Jun 2024, International Conference on AI and the Digital Economy (CADE 2024), Stevenage, IET
Ok-NB: An Enhanced OPTICS and k-Naive Bayes Classifier for Imbalance Classification with Overlapping , Ahmed, Z., Issac, B., Das, S. 22 Apr 2024, In: IEEE Access
A Multi-Stage Machine Learning and Fuzzy Approach to Cyber-Hate Detection, Ketsbaia, L., Issac, B., Chen, X., Jacob, S. 2023, In: IEEE Access
Android Malware Classification and Optimisation Based on BM25 Score of Android API, Yumlembam, R., Issac, B., Yang, L., Jacob, S. 20 May 2023, IEEE INFOCOM 2023 - IEEE Conference on Computer Communications Workshops (INFOCOM WKSHPS), Hoboken, NJ, USA, IEEE
IoT-based Android Malware Detection Using Graph Neural Network With Adversarial Defense, Yumlembam, R., Issac, B., Jacob, S., Yang, L. 15 May 2023, In: IEEE Internet of Things Journal
Plant and Salamander Inspired Network Attack Detection and Data Recovery Model, Sharma, R., Issac, B., Xin, Q., Gadekallu, T., Nath, K. 14 Jun 2023, In: Sensors
A Local Differential Privacy based Hybrid Recommendation Model with BERT and Matrix Factorization, Neera, J., Chen, X., Aslam, N., Issac, B., O'Brien, E. 11 Jul 2022, Proceedings of the 19th International Conference on Security and Cryptography (SECRYPT 2022), Setúbal, Portugal, Scitepress
AndroMalPack: Enhancing the ML-based Malware Classification by Detection and Removal of Repacked Apps for Android Systems, Rafiq, H., Aslam, N., Aleem, M., Issac, B., Randhawa, R. 14 Nov 2022, In: Scientific Reports

Professional Activity

Please visit the Pure Research Information Portal for further information
Editorial work: International Journal of Information and Computer Security (Journal) 2020
Publication Peer-review: Journal of Systems and Information Technology (Journal) 2018
Publication Peer-review: IET Wireless Sensor Systems (Journal) 2017
Publication Peer-review: IEEE Access (Journal) 2017

PGR Supervision

Lida Ketsbaia Detection of online hate through fuzzy-based optimised machine learning models and data augmentation Start Date: 01/10/2019 End Date: 25/06/2024
Yousuf Al Kindi Start Date: 01/10/2019 End Date: 01/04/2020
Rahul Yumlembam ???Enhancing Cybersecurity Defences using Graph-Based Deep Learning, Uncertainty Estimation, and Anomaly Detection in Malware Threat Identification and Mitigation Start Date: 18/01/2021
Aaron Gabriel Mitigating Bias Towards Dialects in Hate Speech Detection with Artificial Intelligence Start Date: 20/10/2022
Henry Kabuye AI-Based Intelligent Multi-stage and User-centric Ransomware Attack Detection Start Date: 01/10/2023
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
Saqib Hussain Forensically Informed Multi-model Machine Learning Framework for Fake News Detection Start Date: 01/10/2024

Key Publications

Please visit the Pure Research Information Portal for further information
Multi-Population Differential Evolution for Retinal Blood Vessel Segmentation. Publication Status: Published 2018
Performance Comparison of Intrusion Detection Machine Learning Classifiers on Benchmark and New Datasets. Publication Status: Published 2018
Are machine learning based intrusion detection system always secure? An insight into tampered learning. Publication Status: Published 2018
Extended LBP based Facial Expression Recognition System for Adaptive AI Agent Behaviour. Publication Status: Published 2018
Intelligent Intrusion Detection System Through Combined and Optimized Machine Learning. Publication Status: Published 2018
Performance comparison of intrusion detection systems and application of machine learning to Snort system. Publication Status: Published 2018
Enhanced cuckoo search algorithm for virtual machine placement in cloud data centres. Publication Status: E-pub ahead of print 2018
A Survey on Biometrics and Cancelable Biometrics Systems. Publication Status: Published 2018
Online voting system based on image steganography and visual cryptography. Publication Status: Published 2017

Qualifications

Philosophy PhD September 03 2018

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