no code implementations • 6 Sep 2022 • Juan R. Trocoso-Pastoriza, Alain Mermoud, Romain Bouyé, Francesco Marino, Jean-Philippe Bossuat, Vincent Lenders, Jean-Pierre Hubaux
However, this activity presents challenges due to the tension between data sharing and confidentiality, that result in information retention often leading to a free-rider problem.
no code implementations • 16 Mar 2021 • Sylvain Chatel, Apostolos Pyrgelis, Juan Ramon Troncoso-Pastoriza, Jean-Pierre Hubaux
Tree-based models are among the most efficient machine learning techniques for data mining nowadays due to their accuracy, interpretability, and simplicity.
no code implementations • 1 Sep 2020 • Sinem Sav, Apostolos Pyrgelis, Juan R. Troncoso-Pastoriza, David Froelicher, Jean-Philippe Bossuat, Joao Sa Sousa, Jean-Pierre Hubaux
In this paper, we address the problem of privacy-preserving training and evaluation of neural networks in an $N$-party, federated learning setting.
1 code implementation • 8 Jul 2020 • Sylvain Chatel, Apostolos Pyrgelis, Juan R. Troncoso-Pastoriza, Jean-Pierre Hubaux
Service providers are interested in verifying the integrity of the users' data to improve their services and obtain useful knowledge for their business.
Cryptography and Security
3 code implementations • 25 May 2020 • Carmela Troncoso, Mathias Payer, Jean-Pierre Hubaux, Marcel Salathé, James Larus, Edouard Bugnion, Wouter Lueks, Theresa Stadler, Apostolos Pyrgelis, Daniele Antonioli, Ludovic Barman, Sylvain Chatel, Kenneth Paterson, Srdjan Čapkun, David Basin, Jan Beutel, Dennis Jackson, Marc Roeschlin, Patrick Leu, Bart Preneel, Nigel Smart, Aysajan Abidin, Seda Gürses, Michael Veale, Cas Cremers, Michael Backes, Nils Ole Tippenhauer, Reuben Binns, Ciro Cattuto, Alain Barrat, Dario Fiore, Manuel Barbosa, Rui Oliveira, José Pereira
This document describes and analyzes a system for secure and privacy-preserving proximity tracing at large scale.
Cryptography and Security Computers and Society