Abdullatif Albaseer
Orcid: 0000-0002-6886-6500
According to our database1,
Abdullatif Albaseer
authored at least 41 papers
between 2016 and 2024.
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Bibliography
2024
Optimized Federated Multitask Learning in Mobile Edge Networks: A Hybrid Client Selection and Model Aggregation Approach.
IEEE Trans. Veh. Technol., November, 2024
FedPot: A Quality-Aware Collaborative and Incentivized Honeypot-Based Detector for Smart Grid Networks.
IEEE Trans. Netw. Serv. Manag., August, 2024
Novel Approach for Curbing Unfair Energy Consumption and Biased Model in Federated Edge Learning.
IEEE Trans. Green Commun. Netw., June, 2024
The Role of Deep Learning in Advancing Proactive Cybersecurity Measures for Smart Grid Networks: A Survey.
IEEE Internet Things J., May, 2024
IEEE Open J. Commun. Soc., 2024
Empowering HWNs with Efficient Data Labeling: A Clustered Federated Semi-Supervised Learning Approach.
Proceedings of the IEEE Wireless Communications and Networking Conference, 2024
Charging Ahead: A Hierarchical Adversarial Framework for Counteracting Advanced Cyber Threats in EV Charging Stations.
Proceedings of the 99th IEEE Vehicular Technology Conference, 2024
Adaptive Honeypot Defense Deployment: A Stackelberg Game Approach with Decentralized DRL for AMI Protection.
Proceedings of the International Conference on Computing, Networking and Communications, 2024
Proceedings of the IEEE International Conference on Communications, 2024
Tailoring Semantic Communication at Network Edge: A Novel Approach Using Dynamic Knowledge Distillation.
Proceedings of the IEEE International Conference on Communications, 2024
2023
Data-Driven Participant Selection and Bandwidth Allocation for Heterogeneous Federated Edge Learning.
IEEE Trans. Syst. Man Cybern. Syst., September, 2023
Blockchain-Empowered Resource Allocation in Multi-UAV-Enabled 5G-RAN: A Multi-Agent Deep Reinforcement Learning Approach.
IEEE Trans. Cogn. Commun. Netw., August, 2023
Fair Selection of Edge Nodes to Participate in Clustered Federated Multitask Learning.
IEEE Trans. Netw. Serv. Manag., June, 2023
Clustered and Multi-Tasked Federated Distillation for Heterogeneous and Resource Constrained Industrial IoT Applications.
IEEE Internet Things Mag., June, 2023
Federated Learning Resource Optimization and Client Selection for Total Energy Minimization Under Outage, Latency, and Bandwidth Constraints With Partial or No CSI.
IEEE Open J. Commun. Soc., 2023
Multiagent Federated Reinforcement Learning for Resource Allocation in UAV-Enabled Internet of Medical Things Networks.
IEEE Internet Things J., 2023
Mitigating IEC-60870-5-104 Vulnerabilities: Anomaly Detection in Smart Grid based on LSTM Autoencoder.
Proceedings of the International Symposium on Networks, Computers and Communications, 2023
OpenPLC and lib61850 Smart Grid Testbed: Performance Evaluation and Analysis of GOOSE Communication.
Proceedings of the International Symposium on Networks, Computers and Communications, 2023
Exploiting the Divergence Between Output of ML Models to Detect Adversarial Attacks in Streaming IoT Applications.
Proceedings of the IEEE International Conference on Communications, 2023
Intelligent Model Aggregation in Hierarchical Clustered Federated Multitask Learning.
Proceedings of the IEEE Global Communications Conference, 2023
DRL-based Federated Uncertainty-guided Semi-Supervised Learning for Network Traffic Selection and Threshold Determination in ZSM.
Proceedings of the IEEE Global Communications Conference, 2023
Privacy-Preserving Honeypot-Based Detector in Smart Grid Networks: A New Design for Quality-Assurance and Fair Incentives Federated Learning Framework.
Proceedings of the 20th IEEE Consumer Communications & Networking Conference, 2023
2022
Fine-Grained Data Selection for Improved Energy Efficiency of Federated Edge Learning.
IEEE Trans. Netw. Sci. Eng., 2022
Semi-Supervised Federated Learning Over Heterogeneous Wireless IoT Edge Networks: Framework and Algorithms.
IEEE Internet Things J., 2022
Exploration and Exploitation in Federated Learning to Exclude Clients with Poisoned Data.
Proceedings of the 2022 International Wireless Communications and Mobile Computing, 2022
Balanced Energy Consumption Based on Historical Participation of Resource-Constrained Devices in Federated Edge Learning.
Proceedings of the 2022 International Wireless Communications and Mobile Computing, 2022
Fine-tuned LSTM-Based Model for Efficient Honeypot-Based Network Intrusion Detection System in Smart Grid Networks.
Proceedings of the 5th International Conference on Communications, 2022
FDRL Approach for Association and Resource Allocation in Multi-UAV Air-To-Ground IoMT Network.
Proceedings of the IEEE Global Communications Conference, 2022
2021
Emotion Recognition for Healthcare Surveillance Systems Using Neural Networks: A Survey.
Proceedings of the 17th International Wireless Communications and Mobile Computing, 2021
Threshold-Based Data Exclusion Approach for Energy-Efficient Federated Edge Learning.
Proceedings of the IEEE International Conference on Communications Workshops, 2021
Client Selection Approach in Support of Clustered Federated Learning over Wireless Edge Networks.
Proceedings of the IEEE Global Communications Conference, 2021
AI-Based Radio Resource Allocation in Support of the Massive Heterogeneity of 6G Networks.
Proceedings of the 4th IEEE 5G World Forum, 2021
2020
CoRR, 2020
Federated Learning for RSS Fingerprint-based Localization: A Privacy-Preserving Crowdsourcing Method.
Proceedings of the 16th International Wireless Communications and Mobile Computing Conference, 2020
Proceedings of the 16th International Wireless Communications and Mobile Computing Conference, 2020
Performance Evaluation of Physical Attacks against E2E Autoencoder over Rayleigh Fading Channel.
Proceedings of the IEEE International Conference on Informatics, 2020
2019
Node placement approaches for pipelines monitoring: simulation and experimental analysis.
Int. J. Sens. Networks, 2019
IEEE Access, 2019
2017
Proceedings of the 13th International Wireless Communications and Mobile Computing Conference, 2017
2016
Multi-Hop Wireless Network: A Comparative Study for Routing Protocols using OMNET++ Simulator.
J. Ubiquitous Syst. Pervasive Networks, 2016