POSEIDON: Privacy-Preserving Federated Neural Network Learning

Abstract

Furthermore, the trusted party becomes a single point of failure, thus both data and model privacy could be compromised by data breaches, hacking, leaks, etc. Hence, solutions originating from the cryptographic community replace and emulate the trusted party with a group of computing servers. In particular, to enable privacy-preserving training of NNs, several studies employ multiparty computation (MPC) techniques and operate on the two [83], [28], three [82], [110],