Muntadher Sallal

Dr Muntadher Sallal

  • Senior Lecturer in Computer Science (Cyber Security)
  • Poole House P416, Talbot Campus, Fern Barrow, Poole, BH12 5BB
Back to top

Biography

Dr. Muntadher Sallal is a Senior lecturer in Cyber Security and researcher in Bournemouth University Cyber Security Research group (BUCSR).

Prior to joining Bournemouth University I have served as a Lecturer in Cyber Security in Nottingham Trent University/UK , Research Fellow in Surrey Centre for Cyber Security (SCCS) /UK, and prior to that working as a Part time Lecturer at School of Computing at the University of Portsmouth /UK.

Dr. Muntadher’s expertise is in security, privacy, and trust of distributed system such as Distributed ledger technologies (DLT) , IoT, e-voting, darknet, and SDN. In addition, his research also focuses on security of cryptocurrencies and their implications on gambling, cybercrimes, and darknet. Furthermore, Muntadher has worked on variety of successful funded projects which uses DLTs and machine learning techniques to preserve security in smart cities and e-voting systems. Dr. Muntadher has a strong research profile with multiple publications in prestigious and high impact conferences and journals.

Journal Articles

  • Sallal, M., de Fréin, R. and Malik, A., 2023. PVPBC: Privacy and Verifiability Preserving E-Voting Based on Permissioned Blockchain. Future Internet, 15 (4).
  • Alsadi, M., Casey, M., Dragan, C.C., Dupressoir, F., Riley, L., Sallal, M., Schneider, S., Treharne, H., Wadsworth, J. and Wright, P., 2023. Towards End-to-End Verifiable Online Voting: Adding Verifiability to Established Voting Systems. IEEE Transactions on Dependable and Secure Computing.
  • Sallal, M., de Fréin, R., Malik, A. and Aziz, B., 2022. An empirical comparison of the security and performance characteristics of topology formation algorithms for Bitcoin networks. Array, 15.
  • Sallal, M., Owenson, G., Salman, D. and Adda, M., 2022. Security and performance evaluation of master node protocol based reputation blockchain in the bitcoin network. Blockchain: Research and Applications, 3 (1).
  • Sallal, M., Schneider, S., Casey, M., Dragan, C., Dupressoir, F., Riley, L., Treharne, H., Wadsworth, J. and Wright, P., 2020. VMV: Augmenting an Internet Voting System with Selene Verifiability. arXiv.org.

Conferences

  • Fletcher-Smith, C. and Sallal, M., 2023. Security Analysis of Blockchain Layer-One Sharding Based Extended-UTxO Model. Communications in Computer and Information Science, 1839 CCIS, 95-123.
  • Udo, J.E. and Sallal, M., 2023. RDSF: Risk Driven Security Framework for Industrial Autonomous Robots. Proceedings - International Conference on Distributed Computing Systems, 2023-July, 1075-1076.
  • Sabeur, Z., Bruno, A., Johnstone, L., Ferjani, M., Benaouda, D., Cetinkaya, D., Arbab-Zavar, B., Sallal, M. and Hardiman, B., 2022. Digital Twins for the Intelligent Detection of Malicious Activities in Urban Spaces. In: 13th International Conference on Applied Human Factors and Ergonomics (AHFE 2022) 24-28 July 2022 New York, USA. Cognitive Computing and Internet of Things, vol. 67 published by AHFE Open Access.
  • Sabeur, Z., Bruno, A., Johnstone, L., Ferjani, M., Benaouda, D., Arbab-Zavar, B., Cetinkaya, D. and Sallal, M., 2022. Cyber-Physical Behaviour Detection and Understanding using Artificial Intelligence. In: 13th International Conference on Applied Human Factors and Ergonomics (AHFE 2022) 24-28 July 2022 New York, USA. Cognitive Computing and Internet of Things, vol. 67 published by AHFE Open Access.
  • Bruno, A., Ferjani, M., Sabeur, Z., Arbab-Zavar, B., Cetinkaya, D., Johnstone, L., Sallal, M. and Benaouda, D., 2022. High-Level Feature Extraction for Crowd Behaviour Analysis: A Computer Vision Approach. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 13374 LNCS, 59-70.
  • Bruno, A., Ferjani, M., Sabeur, Z.A., Arbab-Zavar, B., Cetinkaya, D., Johnstone, L., Sallal, M. and Benaouda, D., 2022. High-Level Feature Extraction for Crowd Behaviour Analysis: A Computer Vision Approach. ICIAP Workshops, 13374, 59-70 Springer.
  • Banno, S., Murad, H. and Sallal, M., 2020. Automated Cognitive Analyses for Intelligent Tutoring Systems. Proceedings - 2020 IEEE/ACM International Conference on Big Data Computing, Applications and Technologies, BDCAT 2020, 171-178.
  • Sallal, M., Schneider, S., Casey, M., Dupressoir, F., Treharne, H., Dragan, C., Riley, L. and Wright, P., 2020. Augmenting an Internet Voting System with Selene Verifiability using Permissioned Distributed Ledger. Proceedings - International Conference on Distributed Computing Systems, 2020-November, 1167-1168.
  • Sallal, M., Owenson, G. and Adda, M., 2020. Security and Performance Evaluation of Master Node Protocol in the Bitcoin Peer-to-Peer Network. Proceedings - IEEE Symposium on Computers and Communications, 2020-July.
  • Sallal, M., Owenson, G. and Adda, M., 2020. Evaluation of Security and Performance of Master Node Protocol in the Bitcoin Peer-to-Peer Network. IEEE International Conference on Blockchain and Cryptocurrency, ICBC 2020.
  • Sallal, M.F., Owenson, G. and Adda, M., 2017. Proximity Awareness Approach to Enhance Propagation Delay on the Bitcoin Peer-to-Peer Network. Proceedings - International Conference on Distributed Computing Systems, 2411-2416.
  • Sallal, M., Owenson, G. and Add, M., 2017. Locality based approach to improve propagation delay on the Bitcoin peer-to-peer network. In: 2017 IFIP/IEEE Symposium on Integrated Network and Service Management (IM) 8-12 May 2017 Lisbon, Portugal.
  • Sallal, M., Owenson, G. and Adda, M., 2016. A Bitcoin Model for Evaluation of Clustering to Improve Propagation Delay in Bitcoin Network. In: 19th CSE / 14th EUC / 15th DCABES 2016 24-26 January 2016 Paris/France.
  • Sallal, M., Owenson, G. and Adda, M., 2016. Bitcoin Network Measurements for Simulation Validation and Parameterisation. In: 11th International Network Conference (pp. 109-114). 11-15 July 2016 Frankfort University.

Theses

  • Sallal, M., 2018. Evaluation of security and performance of clustering in the Bitcoin network, with the aim of improving the consistency of the Blockchain. PhD Thesis. School of Computing, University of Portsmouth.

Grants

  • S4AllCities: Smart Spaces Safety and Security for All Cities (European Commission (H2020), 11 Feb 2023). Completed