1 citations · 2 across the 9 of their papers we have counts for
9 papers
Efficient Data Labeling and Optimal Device Scheduling in HWNs Using Clustered Federated Semi-Supervised Learning
Moqbel Hamood, Abdullatif Albaseer, Mohamed Abdallah +1
Clustered Federated Multi-task Learning (CFL) has emerged as a promising technique to address statistical challenges, particularly with non-independent and identically distributed…
Optimized Federated Multitask Learning in Mobile Edge Networks: A Hybrid Client Selection and Model Aggregation Approach
Moqbel Hamood, Abdullatif Albaseer, Mohamed Abdallah +2
We propose clustered federated multitask learning to address statistical challenges in non-independent and identically distributed data across clients. Our approach tackles complex…
Charging Ahead: A Hierarchical Adversarial Framework for Counteracting Advanced Cyber Threats in EV Charging Stations
Mohammed Al-Mehdhar, Abdullatif Albaseer, Mohamed Abdallah +1
The increasing popularity of electric vehicles (EVs) necessitates robust defenses against sophisticated cyber threats. A significant challenge arises when EVs intentionally provide…
FedPot: A Quality-Aware Collaborative and Incentivized Honeypot-Based Detector for Smart Grid Networks
Abdullatif Albaseer, Nima Abdi, Mohamed Abdallah +2
Honeypot technologies provide an effective defense strategy for the Industrial Internet of Things (IIoT), particularly in enhancing the Advanced Metering Infrastructure's (AMI) sec…
Energy-Aware Service Offloading for Semantic Communications in Wireless Networks
Hassan Saadat, Abdullatif Albaseer, Mohamed Abdallah +2
Today, wireless networks are becoming responsible for serving intelligent applications, such as extended reality and metaverse, holographic telepresence, autonomous transportation,…
Empowering HWNs with Efficient Data Labeling: A Clustered Federated Semi-Supervised Learning Approach
Moqbel Hamood, Abdullatif Albaseer, Mohamed Abdallah +1
Clustered Federated Multitask Learning (CFL) has gained considerable attention as an effective strategy for overcoming statistical challenges, particularly when dealing with non in…