most citedTrustworthy Federated Learning: A Survey

7 citations · 7 across the 1 of their papers we have counts for

collaborators

5 papers

cs.DC2025

Enhancing Communication Efficiency in FL with Adaptive Gradient Quantization and Communication Frequency Optimization

Asadullah Tariq, Tariq Qayyum, Mohamed Adel Serhani +3

Federated Learning (FL) enables participant devices to collaboratively train deep learning models without sharing their data with the server or other devices, effectively addressin…

cs.LG2025

Intelligent Task Offloading in VANETs: A Hybrid AI-Driven Approach for Low-Latency and Energy Efficiency

Tariq Qayyum, Asadullah Tariq, Muhammad Ali +3

Vehicular Ad-hoc Networks (VANETs) are integral to intelligent transportation systems, enabling vehicles to offload computational tasks to nearby roadside units (RSUs) and mobile e…

cs.CR2025

Blockchain and Distributed Ledger Technologies for Cyberthreat Intelligence Sharing

Asadullah Tariq, Tariq Qayyum, Saed Alrabaee +1

Cyberthreat intelligence sharing is a critical aspect of cybersecurity, and it is essential to understand its definition, objectives, benefits, and impact on society. Blockchain an…

cs.CY2024

Inevitable-Metaverse: A Novel Twitter Dataset for Public Sentiments on Metaverse

Kadhim Hayawi, Sakib Shahriar, Mohamed Adel Serhani +1

Metaverse has emerged as a novel technology with the objective to merge the physical world into the virtual world. This technology has seen a lot of interest and investment in rece…

cs.AI20237 cited

Trustworthy Federated Learning: A Survey

Asadullah Tariq, Mohamed Adel Serhani, Farag Sallabi +3

Federated Learning (FL) has emerged as a significant advancement in the field of Artificial Intelligence (AI), enabling collaborative model training across distributed devices whil…