BRAHMIA Amine

Research team

Engineering and Numerical Tools

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Educational activities

Research interests

• IoT
• WSN
• Securiy
• Federated Learning
• Distributed Architectures
• Smart Cities

Research supervisions

PhD Theses in Progress

• Fouad AL TFAILY, Intrusion Detection Mechanism for Cyber-Physical Systems Based on Federated Graph Neural Networks (GNNs), 2024–2027.

• Aimen KHIAR, Hybrid Metaheuristics and Federated Learning Techniques for Optimizing Electric Vehicle Battery Charging, 2024–2027.

• Ahmed BAAHMED, Computational Efficiency of Federated Learning Techniques on Edge-Cloud Infrastructure, 2023–2026.

• Meriem ARBAOUI, Federated Learning for IoMT Networks: Resource Optimization and Privacy Mechanisms, 2023–2026.

PhD Theses Defended

• Mortada TERMOS, Intrusion Detection in IoT Networks Using Complex Networks and AI Techniques, 2025.
• Bouchra FAKHER, Enhanced Federated Learning for Intelligent Energy Management in IoT-Enabled Smart Buildings, 2025.
• Kenza RIAHI, Towards a Robust and Lightweight Consensus Protocol for Permissioned Blockchains, 2024.
• Khoula ZAIMEN, Optimization of WSN Deployment in Smart Buildings, 2024.

Selected publications

Articles in journals with reviewing committee (2022- 2026)

• Mortada Termos, Zakariya Ghalmane, Mohamed-el-Amine Brahmia, Ahmad Fadlallah, Ali Jaber, Mourad ZGHAL. ADAP-GNN: Adaptive property-aware graph neural network for intrusion detection in IoT networks, Computers and Electrical Engineering, Volume 133, 2026, 111051.
• Ahmed-Rafik Baahmed, Jean-François Dollinger, Mohamed El Amine Brahmia, Mourad Zghal. HiFEL-OCKT: Hierarchical federated edge learning with objective congruence and multi-level knowledge transfer for IoT ecosystems, Internet of Things, Volume 36, 2026, 101868.
• Aimen Khiar, Mohamed el Amine Brahmia, Ammar Oulamara, Lhassane Idoumghar. Multi-objective electric vehicle charging scheduling under stochastic duration uncertainty, Omega, Volume 141, 2026, 103506.
• Bouchra Fakher, Mohamed El Amine Brahmia, Ismail Bennis, Abdelhafid Abouaissa. FedWKD: Federated learning weighted aggregation with knowledge distillation for IoT forecasting, Internet of Things, Volume 36, 2026, 101849.
• Al Tfaily, Fouad, Zakariya Ghalmane, Mohamed el Amine Brahmia, Hussein Hazimeh, Ali Jaber et Mourad Zghal. Graph-based federated learning approach for intrusion detection in IoT networks. Scientific Reports, vol. 15, no. 1, p. 41264, 2025.
• Fakher, B., Brahmia, M., Bennis, I. et al. Combining client-based anomaly detection and federated learning for energy forecasting in smart buildings. Cluster Comput 28, 1058 (2025).
• Meriem Arbaoui, Mohamed-el-Amine Brahmia, Abdellatif Rahmoun, and Mourad Zghal. 2024. Federated Learning Survey: A Multi-Level Taxonomy of Aggregation Techniques, Experimental Insights, and Future Frontiers. ACM Trans. Intell. Syst. Technol. 15, 6, Article 113 (December 2024), 69 pages.
• Harb, H., Hijazi, M., Brahmia, MEA. et al. An intelligent mechanism for energy consumption scheduling in smart buildings. Cluster Comput 27, 11149–11165 (2024).
• Kenza Riahi, Mohamed-el-Amine Brahmia, Abdelhafid Abouaissa, Lhassane Idoumghar. Multi-task learning for PBFT optimisation in permissioned blockchains, Blockchain: Research and Applications, Volume 5, Issue 3, 2024, 100206.
• Mortada Termos, Zakariya Ghalmane, Mohamed-el-Amine Brahmia, Ahmad Fadlallah, Ali Jaber, Mourad ZGHAL. GDLC: A new Graph Deep Learning framework based on centrality measures for intrusion detection in IoT networks, Internet of Things, Volume 26, 2024, 101214.
• K. Zaimen, MA. Brahmia, L. Moalic, A.  Abouaissa and L.  Idoumghar, “A  Survey of Artificial Intelligence Based WSNs Deployment Techniques and Related Objectives Modeling,” in IEEE Access, vol. 10, pp. 113294-113329, 2022.

 

International conferences with reviewing committee (2022- 2025)

• Fakher, Bouchra, Mohamed-el-Amine Brahmia, Ismail Bennis et Abdelhafid Abouaissa. “FedCSA: A Novel Federated Learning Client Selection with Anomaly Detection Approach for IoT Systems.” In 2025 IEEE Wireless Communications and Networking Conference (WCNC), pp. 1–6. IEEE, 2025.
• Termos, Mortada, Zakariya Ghalmane, Mohamed-el-Amine Brahmia, Ahmad Fadlallah, Ali Jaber et Mourad Zghal. “Integrating Centrality Measures in Federated Learning-Based Intrusion Detection Systems.” In 2025 IEEE Wireless Communications and Networking Conference (WCNC), pp. 1–6. IEEE, 2025.
• Al Tfaily, Fouad, Zakariya Ghalmane, Mortada Termos, Mohamed-el-Amine Brahmia, Ali Jaber et Mourad Zghal. “Generating Realistic Cyber Security Datasets for IoT Networks with Diverse Complex Network Properties.” In 10th International Conference on Internet of Things, Big Data and Security, pp. 321–328. SCITEPRESS, 2025.
• Termos, Mortada, Zakariya Ghalmane, Mohamed-el-Amine Brahmia, Ahmad Fadlallah, Ali Jaber et Mourad Zghal. “Enhancing IoT Network Intrusion Detection with a New GraphSAGE Embedding Algorithm Using Centrality Measures.” In 10th International Conference on Internet of Things, Big Data and Security, pp. 329–336. SCITEPRESS, 2025.
• Khiar, Aimen, Mohamed-el-Amine Brahmia, Ammar Oulamara et Lhassane Idoumghar. “Optimized scheduling for electric vehicle charging: A multi-objective approach to grid stability and user satisfaction.” In 14th International Conference on Operations Research and Enterprise Systems, pp. 146–155. SCITEPRESS, 2025.
• Abboud, Aline, Mohamed-el-Amine Brahmia, Abdelhafid Abouaissa, Ahmad Shahin et Rocks Mazraani. “Empowering Energy Consumption Forecasting in Smart Buildings: Towards a Hybrid Loss Function.” In 2024 International Wireless Communications and Mobile Computing (IWCMC), pp. 1118–1123. IEEE, 2024.
• Baahmed, Ahmed, Jean-François Dollinger, Mohamed-el-Amine Brahmia et Mourad Zghal. “Hyperparameter Impact on Computational Efficiency in Federated Edge Learning.” In 2024 International Wireless Communications and Mobile Computing (IWCMC), pp. 849–854. IEEE, 2024.
• Fakher, Bouchra, Mohamed-el-Amine Brahmia, Mustafa Al Samara, Ismail Bennis et Abdelhafid Abouaissa. “Fedlbs: Federated learning loss-based swapping approach for energy building’s load forecasting.” In 2024 International Wireless Communications and Mobile Computing (IWCMC), pp. 949–954. IEEE, 2024.
• Arbaoui, Meriem, Mohamed-el-Amine Brahmia, Abdellatif Rahmoun et Mourad Zghal. “Optimizing shapley value for client valuation in federated learning through enhanced gtg-shapley.” In 2024 International Wireless Communications and Mobile Computing (IWCMC), pp. 1528–1533. IEEE, 2024.
• Zaimen, Khaoula, Laurent Moalic, Mohamed-elAmine Brahmia, Abdelhafid Abouaissa et Lhassane Idoumghar. “A Hybrid Binary Grey Wolf Optimiser for WSN Deployment in Indoor Environments Based on BIM Database.” In 2024 IEEE Wireless Communications and Networking Conference (WCNC), pp. 1–6. IEEE, 2024.
• Termos, Mortada, Zakariya Ghalmane, Mohamed-el-Amine Brahmia, Ahmad Fadlallah, Ali Jaber et Mourad Zghal. “Intrusion Detection System for IoT Based on Complex Networks and Machine Learning.” In 2023 IEEE Intl Conf on Dependable, Autonomic and Secure Computing, Intl Conf on Pervasive Intelligence and Computing, (DASC), pp. 471–477. IEEE, 2023.
• Abboud, Aline, Mohamed-el-Amine Brahmia, Abdelhafid Abouaissa, Ahmad Shahin et Rocks Mazraani. “A Hybrid Aggregation Approach for Federated Learning to Improve Energy Consumption in Smart Buildings.” In 2023 International Wireless Communications and Mobile Computing (IWCMC), pp. 854–859. IEEE, 2023.
• Zaimen, Khaoula, Mohamed-el-Amine Brahmia, Laurent Moalic, Abdelhafid Abouaissa et Lhassane Idoumghar. “A comparative study of meta-heuristic algorithms for WSN deployment problem in indoor environments.” In 2023 IEEE Congress on Evolutionary Computation (CEC), pp. 1–8. IEEE, 2023.
• Zaimen, Khaoula, Laurent Moalic, Mohamed-el-Amine Brahmia, Abdelhafid Abouaissa et Lhassane Idoumghar. “Connectivity Repair Heuristics for Stationary Wireless Sensor Networks.” In IEEE International Conference on Communications (ICC), 2023.
• Arbaoui, Meriem, Mohamed-el-Amine Brahmia et Abdellatif Rahmoun. “A review of IoT architectures in smart healthcare applications.” In 2022 Seventh International Conference on Fog and Mobile Edge Computing (FMEC), pp. 1–8. IEEE, 2022.
• Brahmia, Mohamed-el-Amine, Sami Babouche, Samir Ouchani et Mourad Zghal. “An Adaptive Attack Prediction Framework in Cyber-Physical Systems.” In 2022 Ninth International Conference on Software Defined Systems (SDS), pp. 1–7. IEEE, 2022.
• Riahi, Kenza, Mohamed-El-Amine Brahmia, Abdelhafid Abouaissa et Lhassane Idoumghar. “APBFT: An Adaptive PBFT Consensus for Private Blockchains.” In GLOBECOM 2022 – 2022 IEEE Global Communications Conference, pp. 1788–1793. IEEE, 2022.
• ARBAOUI, Meriem, Mohamed-el-Amine BRAHMIA et Abdellatif RAHMOUN. “Towards secure and reliable aggregation for Federated Learning protocols in healthcare applications.” In 2022 Ninth International Conference on Software Defined Systems (SDS). IEEE, 2022.
• Riahi, Kenza, Mohamed-El-Amine Brahmia, Abdelhafid Abouaissa et Lhassane Idoumghar. “FPBFT: A Fast PBFT Protocol for Private Blockchains.” In 2022 9th International Conference on Internet of Things: Systems, Management and Security (IOTSMS), pp. 1–8. IEEE, 2022.