1 citations · 2 across the 12 of their papers we have counts for
4 papers · 1 filter
SCRUB-FL: Sanitizing and Cleansing Representations via Unlearning of Backdoors
Osama Wehbi, Sarhad Arisdakessian, Omar Abdel Wahab +2
Federated Learning (FL) enables collaborative model training without sharing raw data, making it a promising paradigm for privacy-sensitive applications. However, its decentralized…
FL-PBM: Pre-Training Backdoor Mitigation for Federated Learning
Osama Wehbi, Sarhad Arisdakessian, Omar Abdel Wahab +3
Backdoor attacks pose a significant threat to the integrity and reliability of Artificial Intelligence (AI) models, enabling adversaries to manipulate model behavior by injecting p…
Mitigating Backdoor Attacks in Federated Learning Using PPA and MiniMax Game Theory
Osama Wehbi, Sarhad Arisdakessian, Omar Abdel Wahab +3
Federated Learning (FL) is witnessing wider adoption due to its ability to benefit from large amounts of scattered data while preserving privacy. However, despite its advantages, f…
From Connectivity to Multi-Orbit Intelligence: Space-Based Data Center Architectures for 6G and Beyond
Shimaa Naser, Maryam Tariq, Raneem Abdel-Rahim +6
Direct handset-to-satellite (DHTS) communication is emerging as a core capability of 6G non-terrestrial networks, enabling standard devices to directly access low Earth orbit (LEO)…