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](DP3T%20White%20Paper.pdf) is accompanied by an [overview of the data protection aspects of the design](DP3T%20-%20Data%20Protection%20and%20Security.pdf), and a [three page simplified introduction to the protocol](DP3T%20-%20Simplified%20Three%20Page%20Brief.pdf).
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](mailto:dp3t@groupes.epfl.ch).
**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
