178 citations · 382 across the 14 of their papers we have counts for
Showing 2021Show all
2 papers · 1 filter
cs.LG2021★ 11 cited
MixNN: Protection of Federated Learning Against Inference Attacks by Mixing Neural Network Layers
Antoine Boutet, Thomas Lebrun, Jan Aalmoes +1
Machine Learning (ML) has emerged as a core technology to provide learning models to perform complex tasks. Boosted by Machine Learning as a Service (MLaaS), the number of applicat…
cs.CR2021★ 5 cited
Privacy Assessment of Federated Learning using Private Personalized Layers
Théo Jourdan, Antoine Boutet, Carole Frindel
Federated Learning (FL) is a collaborative scheme to train a learning model across multiple participants without sharing data. While FL is a clear step forward towards enforcing us…