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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, Head of the Subject (Networks and Cyber Security) and the Programme Leader of BSc (Computer Networks and Cyber Security) and BSc (Computer and Digital Forensics). He is the deputy leader of CyberNets (Cybersecurity and Networks) Research Group. 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 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.

His personal profile:
University research profile:

Campus Address:                             
Room ELB120, Ellison Building
Northumbria University
Newcastle upon Tyne
Tel: 0191 227 3365
Email Biju


Biju Issac

Campus Address

Room ELB120, Ellison Building
Northumbria University
Newcastle upon Tyne

0191 227 3365

His research interests are in networks (wired and wireless), cybersecurity, machine learning applications of text mining, image processing etc., cloud computing optimizations and technology enabled learning.

  • Please visit the Pure Research Information Portal for further information
  • 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
  • An Investigation on Fragility of Machine Learning Classifiers in Android Malware Detection, Rafiq, H., Aslam, N., Issac, B., Randhawa, R. 2 May 2022, IEEE INFOCOM 2022, Piscataway, US, IEEE
  • On Impact of Adversarial Evasion Attacks on ML-based Android Malware Classifier Trained on Hybrid Features, Rafiq, H., Aslam, N., Issac, B., Randhawa, R. 2 Dec 2022, 2022 14th International Conference on Software, Knowledge, Information Management and Applications (SKIMA), Piscataway, US, IEEE
  • Evaluation of Cyberbullying using Optimized Multi-Stage ML Framework and NLP, Ketsbaia, L., Issac, B., Chen, X. 11 Dec 2021, Defence and Security Doctoral Symposium 2021
  • Preface, Abraham, A., Ohsawa, Y., McLoone, S., Haqiq, A., Issac, B., Jesus, I., Jabbar, M., Gagneja, K., Herrero, Á. 2021, Proceedings of the 12th International Conference on Soft Computing and Pattern Recognition (SoCPaR 2020), Cham, Switzerland, Springer

  • 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

  • Henry Kabuye AI-Based Intelligent Multi-stage and User-centric Ransomware Attack Detection Start Date: 01/10/2023
  • Christopher Taylor IoT Botnet and Malware Detection in Smart buildings through Artificial Intelligence Start Date: 01/10/2023
  • Aaron Gabriel Mitigating Bias Towards Dialects in Hate Speech Detection with Artificial Intelligence Start Date: 20/10/2022
  • Rahul Yumlembam Malware Detection Framework using Optimized Adversary Resistant Deep Learning Networks Start Date: 18/01/2021
  • Yousuf Al Kindi Start Date: 01/10/2019 End Date: 01/04/2020
  • Lida Ketsbaia Hate Speech Detection through Fuzzy-based Optimized Machine Learning and Data Augmentation Start Date: 01/10/2019

  • PhD
  • Computer Science MEng
  • Electrical and Electronic Engineering BEng
  • CCNA Cisco Academy Instructor
  • Chartered Engineer
  • Member of IET
  • Senior Fellow of HEA
  • Senior Member of IEEE

  • 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

Philosophy PhD September 03 2018

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