2 papers
cs.CR2020
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 -party, federated learning setting. We propose a novel system, POSEI…
cs.CR2019
Drynx: Decentralized, Secure, Verifiable System for Statistical Queries and Machine Learning on Distributed Datasets
David Froelicher, Juan R. Troncoso-Pastoriza, Joao Sa Sousa +1
Data sharing has become of primary importance in many domains such as big-data analytics, economics and medical research, but remains difficult to achieve when the data are sensiti…