Publications

Drynx: Decentralized, Secure, Verifiable System for Statistical Queries and Machine Learning on Distributed Datasets

D. Froelicher, J. R. Troncoso-Pastoriza, J. S. Sousa and J. P. Hubaux, “Drynx: Decentralized, Secure, Verifiable System for Statistical Queries and Machine Learning on Distributed Datasets,” in IEEE Transactions on Information Forensics and Security, vol. 15, pp. 3035-3050, 2020, doi: 10.1109/TIFS.2020.2976612.

Scalable Privacy-Preserving Distributed Learning

David Froelicher, Juan R. Troncoso-Pastoriza, Apostolos Pyrgelis, Sinem Sav, João Sá Sousa, Jean-Philippe Bossuat and Jean-Pierre Hubaux: Scalable Privacy-Preserving Distributed Learning. Under submission. 2020

MedCo: Enabling Secure and Privacy-Preserving Exploration of Distributed Clinical and Genomic Data

J. L. Raisaro, J. R. Troncoso-Pastoriza, M. Misbach, J. A. Gomes de Sá E Sousa, S. Pradervand et al. : MedCo: Enabling Secure and Privacy-Preserving Exploration of Distributed Clinical and Genomic DataIEEE/ACM Transactions on computational biology and bioinformatics, vol. 16, no. 4, pp. 1328-1341, 1 July-Aug. 2019. DOI: 10.1109/TCBB.2018.2854776.

MedChain: Accountable and Auditable Data Sharing in Distributed Clinical Research Networks

Juan R. Troncoso-Pastoriza, Jean-Louis Raisaro, Linus Gasser, Bryan Ford and Jean-Pierre Hubaux: MedChain: Accountable and Auditable Data Sharing in Distributed Clincial Research Networks. AMIA 2019 Informatics Summit, March 25-28, 2019, San Francisco, USA.

MedCo2: Privacy-Preserving Cohort Exploration and Analysis

David Froelicher, Mickaël Misbach, Juan R. Troncoso-Pastoriza, Jean-Louis Raisaro and Jean-Pierre Hubaux: MedCo2: Privacy-Preserving Cohort Exploration and Analysis. 6th International Workshop on Genome Privacy and Security (GenoPri’19), October 21-22, 2019, Boston, USA

Multiparty Homomorphic Encryption: From Theory to Practice

Christian Mouchet, Juan R. Troncoso-Pastoriza and Jean-Pierre Hubaux: Multiparty Homomorphic Encryption: From Theory to PracticeCryptology ePrint Archive, Report 2020/304, 2020

UnLynx: A Decentralized System for Privacy-Conscious Data Sharing
David Froelicher, Patricia Egger, João Sá Sousa, Jean Louis Raisaro, Zhicong Huang, Christian Mouchet, Bryan Ford, and Jean-Pierre Hubaux: UnLynx: A Decentralized System for Privacy-Conscious Data SharingPrivacy Enhancing Technologies Symposium (PETS), volume 4, pages 152–170, Minneapolis, USA, 2017.
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