77 citations · 203 across the 10 of their papers we have counts for
Showing 2025Show all
2 papers · 1 filter
cs.CR2025★ 2 cited
Dual Defense: Enhancing Privacy and Mitigating Poisoning Attacks in Federated Learning
Runhua Xu, Shiqi Gao, Chao Li +2
Federated learning (FL) is inherently susceptible to privacy breaches and poisoning attacks. To tackle these challenges, researchers have separately devised secure aggregation mech…
cs.CR2025★ 60 cited
TAPFed: Threshold Secure Aggregation for Privacy-Preserving Federated Learning
Runhua Xu, Bo Li, Chao Li +3
Federated learning is a computing paradigm that enhances privacy by enabling multiple parties to collaboratively train a machine learning model without revealing personal data. How…