354 citations · 833 across the 13 of their papers we have counts for
3 papers · 1 filter
Secure Aggregation for Buffered Asynchronous Federated Learning
Jinhyun So, Ramy E. Ali, Başak Güler +1
Federated learning (FL) typically relies on synchronous training, which is slow due to stragglers. While asynchronous training handles stragglers efficiently, it does not ensure pr…
LightSecAgg: a Lightweight and Versatile Design for Secure Aggregation in Federated Learning
Jinhyun So, Chaoyang He, Chien-Sheng Yang +5
Secure model aggregation is a key component of federated learning (FL) that aims at protecting the privacy of each user's individual model while allowing for their global aggregati…
Securing Secure Aggregation: Mitigating Multi-Round Privacy Leakage in Federated Learning
Jinhyun So, Ramy E. Ali, Basak Guler +2
Secure aggregation is a critical component in federated learning (FL), which enables the server to learn the aggregate model of the users without observing their local models. Conv…