POSEIDON: Privacy-Preserving Federated Neural Network Learning

Sinem Sav, Apostolos Pyrgelis, Juan R. Troncoso-Pastoriza +4

In this paper, we address the problem of privacy-preserving training and evaluation of neural networks in an $N$-party, federated learning setting. We propose a novel system, POSEI…