Mohamed I. Ibrahem
Orcid: 0000-0002-8000-4161
According to our database1,
Mohamed I. Ibrahem authored at least 67 papers
between 2020 and 2026.
Collaborative distances:
Collaborative distances:
Timeline
Legend:
Book In proceedings Article PhD thesis Dataset OtherLinks
Online presence:
-
on orcid.org
On csauthors.net:
Bibliography
2026
IEEE Trans. Netw. Sci. Eng., 2026
Quantum-Enhanced Massive MIMO Beamforming for 6G IoT Networks: A QAOA-Based Optimization Framework.
IEEE Open J. Commun. Soc., 2026
Clustered Federated Learning for Healthcare Analytics: A Dual Blockchain-Functional Encryption Method for Fortified Aggregation.
IEEE Internet Things J., 2026
Privacy-Preserving Federated Meta-Learning for Cell-Free Massive MIMO: Instant Adaptation With Distributed Intelligence.
IEEE Internet Things J., 2026
Paradigm Shift Toward Distributed Learning in IoT Intelligence: A Comprehensive Survey of Opportunities and Challenges.
IEEE Internet Things J., 2026
A Secure and Robust ML Framework for Sequence Classification and Adversarial Evaluation in a Bilateral Carpal Tunnel Syndrome Crossover Dataset.
Inf., 2026
PR-EML: Physics-Respecting and Explainable Machine Learning for Proactive Multi-Band Adaptation in UAV-V2X Networks.
Proceedings of the IEEE Wireless Communications and Networking Conference, 2026
2025
Leveraging Multihead Attention and Counterfactual Explanations for Precise and Efficient Activity Recognition and Heart Attack Detection.
IEEE Internet Things J., September, 2025
Bayesian Optimization-Aided Hybrid Deep Learning Model for Lightweight UAV-Based Smoke Detection.
IEEE Internet Things J., August, 2025
Privacy-Preserving Data-Driven Learning Models for Emerging Communication Networks: A Comprehensive Survey.
IEEE Commun. Surv. Tutorials, August, 2025
Hyperparameter optimization of XGBoost and hybrid CnnSVM for cyber threat detection using modified Harris hawks algorithm.
PeerJ Comput. Sci., 2025
BOL-LPP: A Bayesian-Optimized LSTM Model for Day-Ahead Load Price Forecasting in the ERCOT Market.
IEEE Open J. Comput. Soc., 2025
Revolutionizing User Authentication Exploiting Explainable AI and CTGAN-Based Keystroke Dynamics.
IEEE Open J. Comput. Soc., 2025
Joint Optimization of IRS and THz Resource Allocation in 6G IoT Networks: An Adaptive Online MADDPG Approach.
IEEE Internet Things J., 2025
Empowering AI-Driven Healthcare With Secure, Decentralized, and Privacy-Enhancing Adaptive Intelligence.
IEEE Internet Things J., 2025
Explainable Artificial Intelligence in Malignant Lymphoma Classification: Optimized DenseNet121 Deep Learning Approach With Particle Swarm Optimization and Genetic Algorithm.
IEEE Access, 2025
Proceedings of the 12th International Conference on Wireless Networks and Mobile Communications, 2025
Combating Neural Network Adversaries in Autonomous Vehicles: A 6G-Ready Defense Framework.
Proceedings of the 12th International Conference on Wireless Networks and Mobile Communications, 2025
Adaptive Resource Allocation for 6G Network Slicing via Hybrid CNN-LSTM Architecture.
Proceedings of the 102nd IEEE Vehicular Technology Conference, 2025
Proceedings of the IEEE Virtual Conference on Communications, 2025
Proceedings of the IEEE Virtual Conference on Communications, 2025
Adversary-Resilient Clustered Federated Learning for Secure AI-Driven Healthcare Data Analytics.
Proceedings of the International Wireless Communications and Mobile Computing, 2025
ZTP: A Scalable and Lightweight Privacy-Preserving Blockchain via Scale-Free Quorums and Geometric Fragmentation.
Proceedings of the 54th International Conference on Parallel Processing, 2025
REDUS: Adaptive Resampling for Efficient Deep Learning in Centralized and Federated IoT Networks.
Proceedings of the IEEE International Conference on Communications, 2025
Adaptive Resource Allocation in Emerging High-mobility Networks Using Hybrid Deep Learning Models.
Proceedings of the IEEE International Conference on Communications, 2025
Towards Decentralized, Secure, and Efficient Adaptive Learning for Robust Healthcare Monitoring.
Proceedings of the IEEE International Conference on Communications, 2025
A Novel Secure and Efficient Approach for Heart Attack Detection with Unlinkability and Anonymity.
Proceedings of the 2025 IEEE Global Communications Conference, 2025
ZT-RIC: A Zero Trust RIC Framework for Ensuring Data Privacy and Confidentiality in Open RAN.
Proceedings of the 22nd IEEE Consumer Communications & Networking Conference, 2025
2024
Advanced 3D Face Reconstruction from Single 2D Images Using Enhanced Adversarial Neural Networks and Graph Neural Networks.
Sensors, October, 2024
A Lightweight Privacy-Preserving Load Forecasting and Monitoring Scheme Supporting Dynamic Billing for Smart Grids: No KDC Required.
IEEE Internet Things J., October, 2024
Securing Smart Grid False Data Detectors Against White-Box Evasion Attacks Without Sacrificing Accuracy.
IEEE Internet Things J., October, 2024
The Potential of Deep Learning in Underwater Wireless Sensor Networks and Noise Canceling for the Effective Monitoring of Aquatic Life.
Sensors, September, 2024
Sensors, September, 2024
ZT-RIC:A Zero Trust RIC Framework for ensuring data Privacy and Confidentiality in Open RAN.
CoRR, 2024
IEEE Access, 2024
Securing Smart Grids: Deep Reinforcement Learning Approach for Detecting Cyber-Attacks.
Proceedings of the International Conference on Smart Applications, 2024
Proceedings of the International Conference on Smart Applications, 2024
An Innovative Approach for Human Activity Recognition Based on a Multi-Head Attention Mechanism.
Proceedings of the International Conference on Machine Learning and Applications, 2024
Poisoning Attack Mitigation for Privacy-Preserving Federated Learning-Based Energy Theft Detection.
Proceedings of the IEEE International Conference on Communications, 2024
Privacy-preserving, Lightweight, and Decentralized Load Forecasting in Smart Grid AMI Networks.
Proceedings of the IEEE International Conference on Communications, 2024
Federated Learning With Selective Knowledge Distillation Over Bandwidth-constrained Wireless Networks.
Proceedings of the IEEE International Conference on Communications, 2024
FedSafe-No KDC Needed: Decentralized Federated Learning with Enhanced Security and Efficiency.
Proceedings of the 21st IEEE Consumer Communications & Networking Conference, 2024
Proceedings of the 2nd International Conference on Artificial Intelligence, 2024
A Survey on the Landscape of Machine Learning Solutions for Detecting Phishing Attacks.
Proceedings of the 2nd International Conference on Artificial Intelligence, 2024
Privacy Preservation Techniques in Smart Grids: Balancing Security and Utility in IoT-Driven Environments.
Proceedings of the 2nd International Conference on Artificial Intelligence, 2024
Exploring Advanced Techniques for Identifying Electricity Theft in Smart Grid Systems.
Proceedings of the 2nd International Conference on Artificial Intelligence, 2024
Proceedings of the 2nd International Conference on Artificial Intelligence, 2024
2023
Real-Time Anomaly Detection for Water Quality Sensor Monitoring Based on Multivariate Deep Learning Technique.
Sensors, October, 2023
Enhancing Security in ZigBee Wireless Sensor Networks: A New Approach and Mutual Authentication Scheme for D2D Communication.
Sensors, 2023
Privacy-Preserving and Communication-Efficient Energy Prediction Scheme Based on Federated Learning for Smart Grids.
IEEE Internet Things J., 2023
Detection of Distributed Denial of Charge (DDoC) Attacks Using Deep Neural Networks With Vector Embedding.
IEEE Access, 2023
Privacy-Preserving Detection of Power Theft in Smart Grid Change and Transmit (CAT) Advanced Metering Infrastructure.
IEEE Access, 2023
Joint Knowledge Distillation and Local Differential Privacy for Communication-Efficient Federated Learning in Heterogeneous Systems.
Proceedings of the IEEE Global Communications Conference, 2023
Secure and Efficient Federated Learning in LEO Constellations Using Decentralized Key Generation and On-Orbit Model Aggregation.
Proceedings of the IEEE Global Communications Conference, 2023
Moreau Envelopes-Based Personalized Asynchronous Federated Learning: Improving Practicality in Network Edge Intelligence.
Proceedings of the IEEE Global Communications Conference, 2023
2022
Electricity-Theft Detection for Change-and-Transmit Advanced Metering Infrastructure.
IEEE Internet Things J., 2022
IEEE Internet Things J., 2022
Real-Time Detection of False Readings in Smart Grid AMI Using Deep and Ensemble Learning.
IEEE Access, 2022
Privacy-preserving and Efficient Decentralized Federated Learning-based Energy Theft Detector.
Proceedings of the IEEE Global Communications Conference, 2022
2021
Efficient Privacy-Preserving Electricity Theft Detection With Dynamic Billing and Load Monitoring for AMI Networks.
IEEE Internet Things J., 2021
Privacy Preserving and Efficient Data Collection Scheme for AMI Networks Using Deep Learning.
IEEE Internet Things J., 2021
Countering Presence Privacy Attack in Efficient AMI Networks Using Interactive Deep-Learning.
Proceedings of the International Symposium on Networks, Computers and Communications, 2021
Proceedings of the International Symposium on Networks, Computers and Communications, 2021
Proceedings of the International Symposium on Networks, Computers and Communications, 2021
Proceedings of the IEEE International Conference on Communications Workshops, 2021
2020
PMBFE: Efficient and Privacy-Preserving Monitoring and Billing Using Functional Encryption for AMI Networks.
Proceedings of the 2020 International Symposium on Networks, Computers and Communications, 2020