most citedEnhancing Privacy against Inversion Attacks in Federated Learning by using Mixing Gradients Strategies

3 citations · 3 across the 2 of their papers we have counts for

collaborators

2 papers

cs.LG2022★ 3 cited

Enhancing Privacy against Inversion Attacks in Federated Learning by using Mixing Gradients Strategies

Shaltiel Eloul, Fran Silavong, Sanket Kamthe +2

Federated learning reduces the risk of information leakage, but remains vulnerable to attacks. We investigate how several neural network design decisions can defend against gradien…

eess.IV2022

ST-FL: Style Transfer Preprocessing in Federated Learning for COVID-19 Segmentation

Antonios Georgiadis, Varun Babbar, Fran Silavong +2

Chest Computational Tomography (CT) scans present low cost, speed and objectivity for COVID-19 diagnosis and deep learning methods have shown great promise in assisting the analysi…