Research outputs
Selected research outputs
- AI-Powered System for an Efficient and Effective Cyber Incidents Detection and Response in Cloud Environments (Journal article - 2025)
- Reinforcement learning for an efficient and effective malware investigation during cyber incident response (Journal article - 2025)
- Hierarchical reinforcement learning for efficient and effective automated penetration testing of large networks (Journal article - 2023)
- ESASCF: Expertise Extraction, Generalization and Reply Framework for Optimized Automation of Network Security Compliance (Journal article - 2023)
- Advancing Cyber Incident Timeline Analysis Through Retrieval-Augmented Generation and Large Language Models (Journal article - 2025)
- Revolutionizing intrusion detection in industrial IoT with distributed learning and deep generative techniques (Journal article - 2024)
- Generative AI and LLMs for Critical Infrastructure Protection: Evaluation Benchmarks, Agentic AI, Challenges, and Opportunities. (Journal article - 2025)
- Weaponized IoT: A Comprehensive Comparative Forensic Analysis of Hacker Raspberry Pi and PC Kali Linux Machine (Journal article - 2025)
- Reinforcement Learning for Efficient Network Penetration Testing (Journal article - 2020)
2025
TSA-GRU: A Novel Hybrid Deep Learning Module for Learner Behavior Analytics in MOOCs
Boufaida, S. O., Benmachiche, A., Derdour, M., Maatallah, M., Kahil, M. S., & Ghanem, M. C. (2025). TSA-GRU: A Novel Hybrid Deep Learning Module for Learner Behavior Analytics in MOOCs. Future Internet, 17(8), 355. doi:10.3390/fi17080355
Hierarchical Graph Neural Network for Compressed Speech Steganalysis
Self-Healing Network of Interconnected Edge Devices Empowered by Infrastructure-as-Code and LoRa Communication
MalVol-25: A Diverse, Labelled and Detailed Volatile Memory Dataset for Malware Detection and Response Testing and Validation
Deep Transfer Learning for Kidney Cancer Diagnosis
Brain Tumour Segmentation Using Choquet Integrals and Coalition Game
Derdour, M., Yahiaoui, M. E. B., Kahil, M. S., Gasmi, M., & Ghanem, M. C. (2025). Brain Tumour Segmentation Using Choquet Integrals and Coalition Game. Information, 16(7), 615. doi:10.3390/info16070615
Security Compliance of IoT Devices with the UK PSTI Act: A Comparative Analysis
Integrating AI-Driven Deep Learning for Energy-Efficient Smart Buildings in Internet of Thing-based Industry 4.0
Ghanem, M. C., & Salloum, S. (2025). Integrating AI-Driven Deep Learning for Energy-Efficient Smart Buildings in Internet of Thing-based Industry 4.0. Babylonian Journal of Internet of Things, 2025, 121-130. doi:10.58496/bjiot/2025/007
Advanced Persistent Threats (APT) Attribution Using Deep Reinforcement Learning
Basnet, A. S., Ghanem, M. C., Dunsin, D., Kheddar, H., & Sowinski-Mydlarz, W. (2025). Advanced Persistent Threats (APT) Attribution Using Deep Reinforcement Learning. Digital Threats: Research and Practice. doi:10.1145/3736654
A Systematic Analysis on the Use of AI Techniques in Industrial IoT DDoS Attacks Detection, Mitigation and Prevention
Generative AI and LLMs for Critical Infrastructure Protection: Evaluation Benchmarks, Agentic AI, Challenges, and Opportunities.
Yigit, Y., Ferrag, M. A., Ghanem, M. C., Sarker, I. H., Maglaras, L. A., Chrysoulas, C., . . . Janicke, H. (2025). Generative AI and LLMs for Critical Infrastructure Protection: Evaluation Benchmarks, Agentic AI, Challenges, and Opportunities.. Sensors (Basel, Switzerland), 25(6), 1666. doi:10.3390/s25061666
Weaponized IoT: A Comprehensive Comparative Forensic Analysis of Hacker Raspberry Pi and PC Kali Linux Machine
Ghanem, M. C., Almeida Palmieri, E., Sowinski-Mydlarz, W., Al-Sudani, S., & Dunsin, D. (2025). Weaponized IoT: A Comprehensive Comparative Forensic Analysis of Hacker Raspberry Pi and PC Kali Linux Machine. IoT, 6(1), 18. doi:10.3390/iot6010018
Beyond Detection: Large Language Models and Next-Generation Cybersecurity
Ali, A., & Ghanem, M. C. (2025). Beyond Detection: Large Language Models and Next-Generation Cybersecurity. SHIFRA, 2025, 81-97. doi:10.70470/shifra/2025/005
Synchronization, Optimization, and Adaptation of Machine Learning Techniques for Computer Vision in Cyber-Physical Systems: A Comprehensive Analysis
Advancing Cyber Incident Timeline Analysis Through Retrieval-Augmented Generation and Large Language Models
Loumachi, F. Y., Ghanem, M. C., & Ferrag, M. A. (2025). Advancing Cyber Incident Timeline Analysis Through Retrieval-Augmented Generation and Large Language Models. Computers, 14(2), 67. doi:10.3390/computers14020067
Reinforcement learning for an efficient and effective malware investigation during cyber incident response
Dunsin, D., Ghanem, M. C., Ouazzane, K., & Vassilev, V. (2025). Reinforcement learning for an efficient and effective malware investigation during cyber incident response. High-Confidence Computing, 100299. doi:10.1016/j.hcc.2025.100299
Leveraging Reinforcement Learning for an Efficient Automation of Windows Registry Analysis during Cyber Incident Response
AI-Powered System for an Efficient and Effective Cyber Incidents Detection and Response in Cloud Environments
Farzaan, M. A. M., Ghanem, M. C., El-Hajjar, A., & Ratnayake, D. N. (2025). AI-Powered System for an Efficient and Effective Cyber Incidents Detection and Response in Cloud Environments. IEEE Transactions on Machine Learning in Communications and Networking, 3, 623-643. doi:10.1109/tmlcn.2025.3564912
Unsupervised text feature selection approach based on improved Prairie dog algorithm for the text clustering
Alshinwan, M., Memon, A. G., Ghanem, M. C., & Almaayah, M. (2025). Unsupervised text feature selection approach based on improved Prairie dog algorithm for the text clustering. Jordanian Journal of Informatics and Computing, 2025(1), 27-36. doi:10.63180/jjic.thestap.2025.1.4
2024
A Novel Reinforcement Learning Model for Post-Incident Malware Investigations
Dunsin, D., Ghanem, M. C., Ouazzane, K., & Vassilev, V. (2024). A Novel Reinforcement Learning Model for Post-Incident Malware Investigations. In 2024 11th International Conference on Social Networks Analysis, Management and Security (SNAMS) (pp. 33-40). IEEE. doi:10.1109/snams64316.2024.10883810
Optimal Portfolio and Trading Strategy Using Machine Learning
Ouazzane, K., Tang, K., & Ghanem, M. C. (2024). Optimal Portfolio and Trading Strategy Using Machine Learning. In Global Congress on Emerging Technologies (GCET-2024) (pp. 89-96). IEEE. doi:10.1109/gcet64327.2024.10934318
Revolutionizing intrusion detection in industrial IoT with distributed learning and deep generative techniques
Hamouda, D., Ferrag, M. A., Benhamida, N., Seridi, H., & Ghanem, M. C. (2024). Revolutionizing intrusion detection in industrial IoT with distributed learning and deep generative techniques. Internet of Things, 26, 101149. doi:10.1016/j.iot.2024.101149
A Hierarchical Security Event Correlation Model for Real-Time Threat Detection and Response
Maosa, H., Ouazzane, K., & Ghanem, M. C. (2024). A Hierarchical Security Event Correlation Model for Real-Time Threat Detection and Response. Network, 4(1), 68-90. doi:10.3390/network4010004
A Comprehensive Analysis of the Role of Artificial Intelligence and Machine Learning in Modern Digital Forensics and Incident Response
Dunsin, D., Ghanem, M. C., Ouazzane, K., & Vassilev, V. (2024). A Comprehensive Analysis of the Role of Artificial Intelligence and Machine Learning in Modern Digital Forensics and Incident Response. FSI Digital Investigation. doi:10.1016/j.fsidi.2023.301675
2023
A Novel Hybrid Method for Effective Identification and Extraction of Digital Evidence Masked by Steganographic Techniques in WAV and MP3 Files
Ghane, M. C., Uribarri, M. D., Djemai, R., Dunsin, D., & Araujo, I. I. (2023). A Novel Hybrid Method for Effective Identification and Extraction of Digital Evidence Masked by Steganographic Techniques in WAV and MP3 Files. Journal of Information Security and Cybercrimes Research, 6(2), 89-104. doi:10.26735/izbk9372
D2WFP: A Novel Protocol for Forensically Identifying, Extracting, and Analysing Deep and Dark Web Browsing Activities
Ghanem, M. C., Mulvihill, P., Ouazzane, K., Djemai, R., & Dunsin, D. (2023). D2WFP: A Novel Protocol for Forensically Identifying, Extracting, and Analysing Deep and Dark Web Browsing Activities. Journal of Cybersecurity and Privacy, 3(4), 808-829. doi:10.3390/jcp3040036
Hierarchical reinforcement learning for efficient and effective automated penetration testing of large networks
Ghanem, M. C., Chen, T. M., & Nepomuceno, E. G. (2023). Hierarchical reinforcement learning for efficient and effective automated penetration testing of large networks. Journal of Intelligent Information Systems, 60(2), 281-303. doi:10.1007/s10844-022-00738-0
ESASCF: Expertise Extraction, Generalization and Reply Framework for Optimized Automation of Network Security Compliance
Ghanem, M. C., Chen, T. M., Ferrag, M. A., & Kettouche, M. E. (2023). ESASCF: Expertise Extraction, Generalization and Reply Framework for Optimized Automation of Network Security Compliance. IEEE Access, 11, 129840-129853. doi:10.1109/access.2023.3332834
2020
Reinforcement Learning for Efficient Network Penetration Testing
Ghanem, M. C., & Chen, T. M. (2019). Reinforcement Learning for Efficient Network Penetration Testing. Information, 11(1), 6. doi:10.3390/info11010006
2018
Reinforcement Learning for Intelligent Penetration Testing
Ghanem, M. C., & Chen, T. M. (2018). Reinforcement Learning for Intelligent Penetration Testing. In 2018 Second World Conference on Smart Trends in Systems, Security and Sustainability (WorldS4) (pp. 185-192). IEEE. doi:10.1109/worlds4.2018.8611595
2016
Enhancing WPA2-PSK four-way handshaking after re-authentication to deal with de-authentication followed by brute-force attack a novel re-authentication protocol
Ghanem, M. C., & Ratnayake, D. N. (2016). Enhancing WPA2-PSK four-way handshaking after re-authentication to deal with de-authentication followed by brute-force attack a novel re-authentication protocol. In 2016 International Conference On Cyber Situational Awareness, Data Analytics And Assessment (CyberSA) (pp. 1-7). IEEE. doi:10.1109/cybersa.2016.7503286
1996
A new control strategy to achieve sinusoidal line current in a cascade buck-boost converter
Ghanem, M. C., Al-Haddad, K., & Roy, G. (1996). A new control strategy to achieve sinusoidal line current in a cascade buck-boost converter. IEEE Transactions on Industrial Electronics, 43(3), 441-449. doi:10.1109/41.499817
1995
Comparative study of AC/DC convertors with unity power factor
Ghanem, M. C., Al-Haddad, K., & Roy, G. (n.d.). Comparative study of AC/DC convertors with unity power factor. In Proceedings 1995 Canadian Conference on Electrical and Computer Engineering Vol. 2 (pp. 858-861). IEEE. doi:10.1109/ccece.1995.526562
Study of a modified parallel resonance AC-DC convertor with unity power factor and high efficiency
Ghanem, M. C., Morry, S. E., Al-Haddad, K., & Roy, G. (n.d.). Study of a modified parallel resonance AC-DC convertor with unity power factor and high efficiency. In Proceedings 1995 Canadian Conference on Electrical and Computer Engineering Vol. 2 (pp. 975-978). IEEE. doi:10.1109/ccece.1995.526591
1994
Unity power factor parallel resonant converter UPFPRC
Ghanem., Madama., Al-Haddad., & Roy. (1994). Unity power factor parallel resonant converter UPFPRC. In Proceedings of Canadian Conference on Electrical and Computer Engineering CCECE-94 (pp. 97-100 vol.1). IEEE. doi:10.1109/ccece.1994.405652
1993
A new single phase buck-boost converter with unity power factor
Ghanem, M. C., Al-Haddad, K., & Roy, G. (n.d.). A new single phase buck-boost converter with unity power factor. In Conference Record of the 1993 IEEE Industry Applications Conference Twenty-Eighth IAS Annual Meeting (pp. 785-792). IEEE. doi:10.1109/ias.1993.298988
Unity power factor scheme using cascade converters
Ghanem, M. C., Al-Haddad, K., & Roy, G. (n.d.). Unity power factor scheme using cascade converters. In Proceedings of IECON '93 - 19th Annual Conference of IEEE Industrial Electronics (pp. 936-941). IEEE. doi:10.1109/iecon.1993.339149