Quantifying and Defending against the Privacy Risk in Logit-based Federated Learning

Sheng Wan, Dashan Gao, Hanlin Gu +3

Federated learning aims to protect data privacy by collaboratively learning a model without sharing private data among clients. Unlike traditional parameter-based FL methods that e…