Zakaria Abou El Houda
Orcid: 0000-0002-2893-1101
According to our database1,
Zakaria Abou El Houda
authored at least 31 papers
between 2018 and 2024.
Collaborative distances:
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Bibliography
2024
Federated Deep Reinforcement Learning for Efficient Jamming Attack Mitigation in O-RAN.
IEEE Trans. Veh. Technol., July, 2024
Blockchain-Enabled Federated Learning for Enhanced Collaborative Intrusion Detection in Vehicular Edge Computing.
IEEE Trans. Intell. Transp. Syst., July, 2024
A Privacy-Preserving Collaborative Jamming Attacks Detection Framework Using Federated Learning.
IEEE Internet Things J., April, 2024
Securing IIoT applications in 6G and beyond using adaptive ensemble learning and zero-touch multi-resource provisioning.
Comput. Commun., 2024
Reputation-Aware Scheduling for Secure Internet of Drones: A Federated Multi-Agent Deep Reinforcement Learning Approach.
Proceedings of the IEEE INFOCOM 2024, 2024
Blockchain Meets O-RAN: A Decentralized Zero-Trust Framework for Secure and Resilient O-RAN in 6G and Beyond.
Proceedings of the IEEE INFOCOM 2024, 2024
2023
Next-power: Next-generation framework for secure and sustainable energy trading in the metaverse.
Ad Hoc Networks, October, 2023
IEEE Internet Things Mag., March, 2023
When Collaborative Federated Learning Meets Blockchain to Preserve Privacy in Healthcare.
IEEE Trans. Netw. Sci. Eng., 2023
MiTFed: A Privacy Preserving Collaborative Network Attack Mitigation Framework Based on Federated Learning Using SDN and Blockchain.
IEEE Trans. Netw. Sci. Eng., 2023
Advancing Security and Efficiency in Federated Learning Service Aggregation for Wireless Networks.
Proceedings of the 34th IEEE Annual International Symposium on Personal, 2023
Securing Federated Learning through Blockchain and Explainable AI for Robust Intrusion Detection in IoT Networks.
Proceedings of the IEEE INFOCOM 2023, 2023
Proceedings of the IEEE International Conference on Blockchain and Cryptocurrency, 2023
Secure and Efficient Federated Learning for Robust Intrusion Detection in IoT Networks.
Proceedings of the IEEE Global Communications Conference, 2023
2022
When Federated Learning Meets Game Theory: A Cooperative Framework to Secure IIoT Applications on Edge Computing.
IEEE Trans. Ind. Informatics, 2022
"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
A Novel IoT-Based Explainable Deep Learning Framework for Intrusion Detection Systems.
IEEE Internet Things Mag., 2022
A Low-Latency Fog-based Framework to secure IoT Applications using Collaborative Federated Learning.
Proceedings of the 47th IEEE Conference on Local Computer Networks, 2022
Ensemble Learning for Intrusion Detection in SDN-Based Zero Touch Smart Grid Systems.
Proceedings of the 47th IEEE Conference on Local Computer Networks, 2022
Proceedings of the IEEE International Conference on Communications, 2022
Cost-efficient Federated Reinforcement Learning- Based Network Routing for Wireless Networks.
Proceedings of the 2022 IEEE Future Networks World Forum, 2022
2021
Security Enforcement through Software Defined Networks (SDN). (Renforcement de la sécurité à travers les réseaux programmables).
PhD thesis, 2021
Proceedings of the ICC 2021, 2021
Proceedings of the IEEE Global Communications Conference, 2021
2020
IEEE Trans. Netw. Serv. Manag., 2020
Proceedings of the 2020 IEEE International Conference on Communications, 2020
BrainChain - A Machine learning Approach for protecting Blockchain applications using SDN.
Proceedings of the 2020 IEEE International Conference on Communications, 2020
2019
Cochain-SC: An Intra- and Inter-Domain Ddos Mitigation Scheme Based on Blockchain Using SDN and Smart Contract.
IEEE Access, 2019
Co-IoT: A Collaborative DDoS Mitigation Scheme in IoT Environment Based on Blockchain Using SDN.
Proceedings of the 2019 IEEE Global Communications Conference, 2019
2018
ChainSecure - A Scalable and Proactive Solution for Protecting Blockchain Applications Using SDN.
Proceedings of the IEEE Global Communications Conference, 2018