Books (2)
[B2]
, Digital Forensics in Next-Generation Internet for Medical Things , CRC Press, 2025, ISBN: 10.1201/9781003640325 

[B1]
Journals (25)
[J25]
, Split Federated Learning-Driven Resource-Efficient MEC Framework for UAV-based Networks , IEEE Transactions on Network Science and Engineering, 2025, DOI: 10.1109/TNSE.2025.3622688
[J24]
, Advancing Privacy and Fairness in Healthcare Using Federated Edge Learning and Blockchain , IEEE Internet of Things Journal, 2025, DOI: 10.1109/JIOT.2025.3589179
[J23]
, Advancing Robustness and Privacy in Federated Learning for Secure Autonomous Vehicle Systems , IEEE Transactions on Consumer Electronics, 2025, DOI: 10.1109/TCE.2025.3558999
[J22]
, MetaPower: Empowering Peer-to-Peer Energy Trading in the Metaverse With Digital Twins and Blockchain , IEEE Systems, Man, and Cybernetics Magazine, 2025, DOI: 10.1109/MSMC.2024.3486666
[J21]
, A Blockchain-Based Cross-Domain DDoS Mitigation in Consumer Networks , IEEE Transactions on Consumer Electronics, 2025, DOI: 10.1109/TCE.2025.3559451
[J20]
, LLMs to Secure Consumer Networks: Open Problems and Future Directions , IEEE Consumer Electronics Magazine, 2025, DOI: 10.1109/MCE.2025.3542247
[J19]
, When Federated Learning Meets Knowledge Distillation to Secure Consumer Edge Network , IEEE Transactions on Consumer Electronics, 2025, DOI: 10.1109/TCE.2025.3559004
[J18]
, An In-Depth Comparative Study of Quantum-Classical Encoding Methods for Network Intrusion Detection , Accepted in IEEE Open Journal of the Communications Society, 2025,
[J17]
, Zero Trust Security Architecture for 6G Open Radio Access Networks (ORAN) , IEEE Networking Letters, 2024, DOI: 10.1109/LNET.2024.3514357
[J16]
, A Privacy-Preserving Framework for Efficient Network Intrusion Detection in Consumer Network Using Quantum Federated Learning , IEEE Transactions on Consumer Electronics, 2024, DOI: 10.1109/TCE.2024.3458985
[J15]
, Advancing Security and Trust in WSNs: A Federated Multi-Agent Deep Reinforcement Learning Approach , IEEE Transactions on Consumer Electronics, 2024, DOI: 10.1109/TCE.2024.10630602
[J14]
, Securing IIoT applications in 6G and beyond using adaptive ensemble learning and zero-touch multi-resource provisioning , Computer Communications, 2024, DOI: 10.1016/j.comcom.2024.01.018
[J13]
, A Privacy-Preserving Collaborative Jamming Attacks Detection Framework Using Federated Learning , IEEE Internet of Things Journal, 2024, DOI: 10.1109/JIOT.2023.3333870
[J12]
, Blockchain-Enabled Federated Learning for Enhanced Collaborative Intrusion Detection in Vehicular Edge Computing , IEEE Transactions on Intelligent Transportation Systems, 2024, DOI: 10.1109/TITS.2024.3351699
[J11]
, Federated Deep Reinforcement Learning for Efficient Jamming Attack Mitigation in O-RAN , IEEE Transactions on Vehicular Technology, 2024, DOI: 10.1109/TVT.2024.3359998
[J10]
, Trust Management in Vehicular Ad-Hoc Networks: Extensive Survey , IEEE Access, 2023, DOI: 10.1109/ACCESS.2023.3268991
[J9]
, Next-power: Next-generation framework for secure and sustainable energy trading in the metaverse , Ad Hoc Networks, 2023, DOI: 10.1016/j.adhoc.2023.103243
[J8]
, A MEC-Based Architecture to Secure IoT Applications using Federated Deep Learning , IEEE Internet Things Mag., 2023, DOI: 10.1109/IOTM.001.2100238
[J7]
, MiTFed: A Privacy-Preserving Collaborative Network Attack Mitigation Framework Based on Federated Learning Using SDN and Blockchain , IEEE Trans. Netw. Sci. Eng., 2023, DOI: 10.1109/TNSE.2023.3237367
[J6]
, When Collaborative Federated Learning Meets Blockchain to Preserve Privacy in Healthcare , IEEE Trans. Netw. Sci. Eng., 2023, DOI: 10.1109/TNSE.2022.3211192
[J5]
, A Novel IoT-Based Explainable Deep Learning Framework for Intrusion Detection Systems , IEEE Internet Things Mag., 2022, DOI: 10.1109/IOTM.005.2200028
[J4]
, “Why Should I Trust Your IDS?”: An Explainable Deep Learning Framework for Intrusion Detection Systems in Internet of Things Networks , IEEE Open J. Commun. Soc., 2022, DOI: 10.1109/OJCOMS.2022.3188750
[J3]
, When Federated Learning Meets Game Theory: A Cooperative Framework to Secure IIoT Applications on Edge Computing , IEEE Trans. Ind. Informatics, 2022, DOI: 10.1109/TII.2022.3170347
[J2]
, Bringing Intelligence to Software Defined Networks: Mitigating DDoS Attacks , IEEE Transactions on Network and Service Management, 2020, DOI: 10.1109/TNSM.2020.3014870
[J1]
, Cochain-SC: An Intra- and Inter-Domain DDoS Mitigation Scheme Based on Blockchain Using SDN and Smart Contract , IEEE Access, 2019, DOI: 10.1109/ACCESS.2019.2930715
Book Chapters (4)
[BC4]
, Federated learning in healthcare , Digital Forensics in Next-Generation Internet for Medical Things: Balancing Security and Sustainability, 2025,
[BC3]
, Cyber Threat Actors Review: Examining the Tactics and Motivations of Adversaries in the Cyber Landscape , 2024, ISBN: 9781003404361
[BC2]
, Foundations models in cybersecurity: A comprehensive review and future direction , 2024, ISBN: 9781003497585
[BC1]
, A Novel Unsupervised Learning Method for Intrusion Detection in Software-Defined Networks , Computational Intelligence in Recent Communication Networks, 2021, ISBN: 10.1007/978-3-030-77185-0_7
Conference proceedings (26)
[C26]
, Domain Adversarial Neural Networks with Adversarial Robustness Evaluation for Intrusion Detection Systems , 20th International Conference on Risks and Security of Internet and Systems (CRiSIS), to appear, 2025,
[C25]
, Blockchain-Based Federated Learning for Enhanced Cyber-Threats Detection in Connected Vehicles , 2025, DOI: 10.1109/ICC52391.2025.11161266
[C24]
, An SDN-based Adaptive Ensemble Learning Framework for Intrusion Mitigation in Wireless Networks , 2025, DOI: 10.1109/ICC52391.2025.11161745
[C23]
, Enhanced Adversarial Domain Adaptation for Intrusion Detection Systems , IEEE International Conference on Wireless and Mobile Computing, Networking and Communications (WiMob), to appear, 2025,
[C22]
, Securing O-RAN Equipment Using Blockchain-Based Supply Chain Verification , 2025, DOI: 10.1109/IWCMC65282.2025.11059692
[C21]
, A Blockchain-Enabled Multi-Layered Zero-Trust Security Framework for O-RAN , 2025, DOI: 10.1109/IWCMC65282.2025.11059720
[C20]
, Vehicular Edge Computing: An Enhanced Vehicle Participant Selection System for Federated Learning , 2025, DOI: 10.1109/IWCMC65282.2025.11059723
[C19]
, Enhancing IIoT Security with Deep Reinforcement Learning for Intrusion Detection , 2025, DOI: 10.1109/NTMS65597.2025.11076670
[C18]
, Securing O-RAN with Zero Trust Architectureand Large Language Models , Proceedings of the 4th International Conference on Advances in Communication Technology and Computer Engineering (ICACTCE'24), 2025, Best Paper Award
[C17]
, Securing the Metaverse: The Intersection of ML-Based Oracles and Blockchain Technology , 2024, DOI: 10.1109/iMETA62882.2024.10807869Best Paper Award
[C16]
, Blockchain Meets O-RAN: A Decentralized Zero-Trust Framework for Secure and Resilient O-RAN in 6G and Beyond , IEEE INFOCOM 2024 - IEEE Conference on Computer Communications Workshops (INFOCOM WKSHPS), 2024, DOI: 10.1109/INFOCOM.2024.10620803
[C15]
, Reputation-Aware Scheduling for Secure Internet of Drones: A Federated Multi-Agent Deep Reinforcement Learning Approach , IEEE INFOCOM 2024 - IEEE Conference on Computer Communications Workshops (INFOCOM WKSHPS), 2024, DOI: 10.1109/GLOCOM.2018.8647279
[C14]
, Secure and Efficient Federated Learning for Robust Intrusion Detection in IoT Networks , 2023, DOI: 10.1109/GLOBECOM54140.2023.10436768
[C13]
, Towards a Secure and Scalable Access Control System Using Blockchain , 2023, DOI: 10.1109/ICBC56567.2023.10174880Nominated for Best Paper Award
[C12]
, Securing Federated Learning through Blockchain and Explainable AI for Robust Intrusion Detection in IoT Networks , 2023, DOI: 10.1109/INFOCOMWKSHPS57453.2023.10225769
[C11]
, Advancing Security and Efficiency in Federated Learning Service Aggregation for Wireless Networks , 2023, DOI: 10.1109/PIMRC56721.2023.10293790
[C10]
, Cost-efficient Federated Reinforcement Learning-Based Network Routing for Wireless Networks , 2022, DOI: 10.1109/FNWF55208.2022.00050
[C9]
, A Hierarchical Fog Computing Framework for Network Attack Detection in SDN , 2022, DOI: 10.1109/ICC45855.2022.9838560
[C8]
, Ensemble Learning for Intrusion Detection in SDN-Based Zero Touch Smart Grid Systems , 2022, DOI: 10.1109/LCN53696.2022.9843645
[C7]
, A Low-Latency Fog-based Framework to Secure IoT Applications using Collaborative Federated Learning , 2022, DOI: 10.1109/LCN53696.2022.9843315
[C6]
, A Novel Machine Learning Framework for Advanced Attack Detection using SDN , 2021, DOI: 10.1109/GLOBECOM46510.2021.9685643
[C5]
, Blockchain-based Reverse Auction for V2V charging in smart grid environment , 2021, DOI: 10.1109/ICC42927.2021.9500366
[C4]
, BrainChain – A Machine learning Approach for protecting Blockchain applications using SDN , 2020, DOI: 10.1109/ICC40277.2020.9148808
[C3]
, Blockchain Meets AMI: Towards Secure Advanced Metering Infrastructures , 2020, DOI: 10.1109/ICC40277.2020.9148963
[C2]
, Co-IoT: A Collaborative DDoS Mitigation Scheme in IoT Environment Based on Blockchain Using SDN , 2019, DOI: 10.1109/GLOBECOM38437.2019.9013542
[C1]
, ChainSecure – A Scalable and Proactive Solution for Protecting Blockchain Applications Using SDN , 2018, DOI: 10.1109/GLOCOM.2018.8647279
MSc Theses (2)
[Msc2]
[Msc1]
Patent (1)
[P1]
, Method for Processing a Data Packet and Associated Device, Switching Equipment and Computer Program , 2020, ID: WO2020020911A1
PhD Thesis (1)
[PhD1]
, Security Enforcement through Software Defined Networks (SDN). (Renforcement de la sécurité à travers les réseaux programmables) , University of Montreal, Quebec, Canada, 2021, DOI: https://tel.archives-ouvertes.fr/tel-03810672
