most citedEnhancing Security and Privacy in Federated Learning using Low-Dimensional Update Representation and Proximity-Based Defense

6 citations · 6 across the 1 of their papers we have counts for

collaborators

1 paper

cs.CR2024★ 6 cited

Enhancing Security and Privacy in Federated Learning using Low-Dimensional Update Representation and Proximity-Based Defense

Wenjie Li, Kai Fan, Jingyuan Zhang +3

Federated Learning (FL) is a promising privacy-preserving machine learning paradigm that allows data owners to collaboratively train models while keeping their data localized. Desp…