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Decentralized Privacy-Preserving Proximity Tracing
This repository contains a proposal for a secure and privacy-preserving decentralized privacy-preserving proximity tracing system. Its goal is to simplify and accelerate the process of identifying people who have been in contact with an infected person, thus providing a technological foundation to help slow the spread of the SARS-CoV-2 virus. The system aims to minimise privacy and security risks for individuals and communities and guarantee the highest level of data protection.
By publishing this document we seek feedback from a broad audience on the high-level design, its security and privacy properties, and the functionality it offers; so that further protection mechanisms can be added if weaknesses are identified. The white paper document is accompanied by an overview of the data protection aspects of the design, and a three page simplified introduction to the protocol.
If you have a similar project and you believe it would be beneficial to collaborate or exchange ideas drop an email here: dp3t@groupes.epfl.ch.
The following people are behind this design:
EPFL: Prof. Carmela Troncoso, Prof. Mathias Payer, Prof. Jean-Pierre Hubaux, Prof. Marcel Salathé, Prof. James Larus, Prof. Edouard Bugnion, Dr. Wouter Lueks, Theresa Stadler, Dr. Apostolos Pyrgelis, Dr. Daniele Antonioli, Ludovic Barman, Sylvain Chatel
ETHZ: Prof. Kenneth Paterson, Prof. Srdjan Capkun, Prof. David Basin, Dennis Jackson
KU Leuven: Prof. Bart Preneel, Prof. Nigel Smart, Dr. Dave Singelee, Dr. Aysajan Abidin
TU Delft: Prof. Seda Gürses
University College London: Dr. Michael Veale
CISPA: Prof. Cas Cremers
University of Oxford: Dr. Reuben Binns
TU Berlin / Fraunhofer HHI: Prof. Thomas Wiegand
Contact email: dp3t@groupes.epfl.ch.