Associate Professor, School of Computing and Digital Media
Biography
Dr Shahram Salekzamankhani is Associate Teaching Professor in Cyber Security and Computer Networks. He is Director of the United Kingdom's only Regional Palo Alto Networks Cybersecurity Academy at London Metropolitan University and Co-founder of the Cybersecurity Research Centre. His work focuses on industry-integrated cybersecurity education, wireless network security, IoT and IoT security, and the integration of emerging technologies into undergraduate and postgraduate teaching. Dr Shahram Salekzamankhani graduated with a PhD in Wireless Network Security from London Metropolitan University. He has been a member of the academic staff at London Metropolitan University since October 2000, accumulating almost 26 years of continuous service.
Throughout his career he has shouldered a wide range of responsibilities at the University, including roles as Course Leader for BEng Computer Networking and Infrastructure Security and BEng Computer Networking and Cloud Security, Deputy Course Leader for MSc Cyber Security and related postgraduate programmes, module convenor for postgraduate cybersecurity modules, Director of the United Kingdom's only Regional Palo Alto Networks Cybersecurity Academy, Director of the Cisco Academy, ASC and ITC, Co-founder and Co-Director of the Cybersecurity Research Centre, Deputy Director of Communication Technology Research Centre and Founder and Director of the Short Courses Training Centre (SCTC) within School Computing and Digital Media (SCDM). In addition, he has actively contributed to the University community by serving on Subject Standards Boards, programme validation and revalidation panels, and quality assurance forums, and by mentoring colleagues from Associate Lecturer to Senior Lecturer level.
Professional Memberships
- Senior Fellow of the Higher Education Academy (SFHEA)
- Member of the Institution of Engineering and Technology (MIET)
- Member of the International Association of Engineers (IAENG)
- Cisco Certified Academy Instructor in CCNA, CCNP, Cybersecurity, IoT, IoT Security, Artificial Intelligence, Machine Learning, and Data Science
- Palo Alto Networks Certified Academy Instructor in Cybersecurity and Network Security
Teaching and Research Interests
Dr Salekzamankhani is module leader for several postgraduate cybersecurity related modules and contributes to teaching across the MSc and BSc Computer Networking and Cloud and Cyber Security portfolios. He has designed and co-designed seventeen industry-integrated modules embedding Cisco Networking Academy and Palo Alto Networks industry certifications into the academic curriculum. He is currently undertaking professional development with the Cisco Networking Academy in Artificial Intelligence, Machine Learning, Internet of Things (IoT), and IoT Security, extending his instructor qualifications in these emerging areas and supporting their integration into postgraduate provision.
Dr Salekzamankhani's research interest lies at the intersection of wireless network security, IoT security, and machine-learning-based intrusion detection systems. His pioneering work focuses on the application of hybrid deep-learning architectures to the detection and prevention of intrusions in IoT environments, addressing one of the most significant challenges facing the modern wireless communications landscape. Recent published work, conducted in collaboration with his doctoral researcher Humera Ghani and Professor Bal Virdee, has developed a BiLSTM and XGBoost hybrid model for IoT intrusion detection achieving 97.15% accuracy on the IoT-23 and UNSW-NB15 benchmark datasets, representing a significant step forward in applied IoT security research.
Publications
- H. Ghani, S. Salekzamankhani, B. Virdee (2025). Statistical and Multivariate Analysis of IoT-23 Dataset. Journal of Cybersecurity and Privacy, vol.5, no.4.
- Kuku, O., Chrysikos, A., Salekzamankhani, S. (2025). Real-Time Forensic Analysis in IoT Environments. BOHR BIJIAM (accepted).
Oyeyemi, K., Chrysikos, A., Salekzamankhani, S. (2025). Preparing IoT-enabled organisations for digital forensics. Int. J. Inf. Secur. 24, 170.
- Oyeyemi, K., Chrysikos, A., Salekzamankhani, S. (2025). Enhancing Forensic Readiness in IoT-Enabled Organisations. Springer LNNS vol.1288.
- Oyeyemi, K., Chrysikos, A., Salekzamankhani, S. (2024). Digital Forensic Readiness in IoT-Enabled Organisations. ICDAM-2024.
- Sharma, R., Salekzamankhani, S., Virdee, B., Awan, M.U. (2024). Development and Evaluation of Network Utilities using Python. ICICC-2024, Delhi.
- Oyeyemi, K., Chrysikos, A., Salekzamankhani, S. (2024). Digital forensic readiness in IoT-enabled organisations. IJEEDC, 12(9), pp.21-28.
- Ghani, H., Salekzamankhani, S., Virdee, B. (2023). A hybrid dimensionality reduction for network intrusion detection. Journal of Cybersecurity and Privacy, 3(4).
- Ghani, H., Virdee, B., Salekzamankhani, S. (2023). A deep learning approach for network intrusion detection. Journal of Cybersecurity and Privacy, 3(3).
- Ghani, H., Salekzamankhani, S., Virdee, B. (2023). ICDAM2023 Volume 1. DOI: 10.1007/978-981-99-6544-1
Alibakhshikenari, M. et al., Salekzamankhani, S. (2023). On-chip terahertz antenna array. International Journal of Electronics and Communications, 167.
- Riaz, M. et al., Salekzamankhani, S. (2022). Sharp roll-off triband microstrip bandpass filter. International Journal of RF and Microwave CAE.
- Alibakhshikenari, M. et al., Salekzamankhani, S. (2021). High-isolation antenna array using SIW for subterahertz wireless applications. Nature Scientific Reports, 11(10218).
- Alibakhshikenari, M. et al., Salekzamankhani, S. (2020). THz on-chip antenna based on metasurface concept. Nature Scientific Reports, 10(11034).
- Elmahi, E., Salekzamankhani, S., Sharma, M. (2019). In-Depth Analysis of Signal Jammers and Anti-Jamming Effect on 5G Signal. FiCloudW 2019.
- Riaz, M. et al., Salekzamankhani, S. (2019). Quasi-elliptic dual-band planar BPF for 5G communications. Microwave and Optical Technology Letters.
- Bajnaid, N., Benlamri, R., Pakstas, A., Salekzamankhani, S. (2016). Towards Ontology-Based SQA Recommender. IJKE.
- Bajnaid, N., Benlamri, R., Pakstas, A., Salekzamankhani, S. (2015). Towards Ontology-Based SQA Recommender. J Inform Tech Softw Eng.
- Bajnaid, N. et al. (2016). Ontological Approach to Software Quality Assurance Knowledge. ICKE 2016, Los Angeles.
- Bajnaid, N. et al. (2013). Ontology-Based Personalized SQA e-Learning System. CECIIS 2013, Croatia.
- Bajnaid, N. et al. (2013). Software Quality Assurance Ontology. SEKE 2013, Boston.
- Bajnaid, N., Pakstas, A., Salekzamankhani, S. (2012). Ontology-Based Modelling of Software QA Knowledge. GTSE 2012, KTH Stockholm.
- Salekzamankhani, S., Pakstas, A., Virdee, B. (2011). Ontology for Intrusion Handling Systems in Wireless LANs. BCFIC 2011, Riga.
- Salekzamankhani, S., Pakstas, A., Virdee, B. (2010). Ontology Approach, Identification Subsystem for IHS in Wireless LANs. WCE/ICWN'10, Imperial College London. Best Paper Award.
- Salekzamankhani, S., Pakstas, A., Virdee, B. (2010). Response and Management Console Subsystems for IHS in Wireless LANs. WCE/ICWN'10, Imperial College London.
- Salekzamankhani, S., Pakštas, A. (2007). Reference model for intrusion handling systems for Wireless LANs. SoftCOM2007.
- Pakštas, A., Salekzamankhani, S., Virdee, B. (2006). Fighting Intrusions in Wireless LANs. ICI 2006, Tashkent.
- Salekzamankhani, S., Pakštas, A., Virdee, B. (2005). Reference Model for IDS in Wireless LANs. IEEE Globecom 2005, AWIN Workshop.
