1 citations · 1 across the 1 of their papers we have counts for
Showing cs.DCShow all
2 papers · 1 filter
cs.DC2023
Unveiling Backdoor Risks Brought by Foundation Models in Heterogeneous Federated Learning
Xi Li, Chen Wu, Jiaqi Wang
The foundation models (FMs) have been used to generate synthetic public datasets for the heterogeneous federated learning (HFL) problem where each client uses a unique model archit…
cs.DC2023★ 1 cited
Backdoor Threats from Compromised Foundation Models to Federated Learning
Xi Li, Songhe Wang, Chen Wu +2
Federated learning (FL) represents a novel paradigm to machine learning, addressing critical issues related to data privacy and security, yet suffering from data insufficiency and…