Abdullatif Albaseer

Orcid: 0000-0002-6886-6500

According to our database1, Abdullatif Albaseer authored at least 35 papers between 2016 and 2024.

Collaborative distances:
  • Dijkstra number2 of five.
  • Erdős number3 of four.

Timeline

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Links

On csauthors.net:

Bibliography

2024
Energy-Aware Service Offloading for Semantic Communications in Wireless Networks.
CoRR, 2024

Empowering HWNs with Efficient Data Labeling: A Clustered Federated Semi-Supervised Learning Approach.
CoRR, 2024

Tailoring Semantic Communication at Network Edge: A Novel Approach Using Dynamic Knowledge Distillation.
CoRR, 2024

The Role of Deep Learning in Advancing Proactive Cybersecurity Measures for Smart Grid Networks: A Survey.
CoRR, 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
Exploiting Unlabeled Data in Smart Cities using Federated Learning.
CoRR, 2020

Federated Learning for Localization: A Privacy-Preserving Crowdsourcing Method.
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

Exploiting Unlabeled Data in Smart Cities using Federated Edge Learning.
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

Cluster-Based Node Placement Approach for Linear Pipeline Monitoring.
IEEE Access, 2019

2017
Anomaly resilient node placement approach for pipelines monitoring.
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


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