Decentralized Privacy-Preserving Proximity Tracing

This repository contains a proposal for a secure and 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.

Who we are

We are a international consortium of technologists, legal experts, engineers and epidemiologists with a wide range of experience who are interested in ensuring that any proximity tracing technology does not result in governments obtaining surveillance capabilities which will endanger civil society.

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, Dr. Jan Beutel, 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 Helmholtz Center for Information Security: Prof. Cas Cremers
University of Oxford: Dr. Reuben Binns
University of Torino / ISI Foundation: Prof. Ciro Cattuto
University of Salerno: Prof. Giuseppe Persiano
IMDEA Software: Prof. Dario Fiore
INESC TEC: Prof. Manuel Barbosa
Stanford Univerity: Prof. Dan Boneh

In this repository you will find various documents defining our specification. 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.

By publishing these documents 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. We feel it is vital that designs are made public so the wider community can verify their claimed privacy gaurantees before they are deployed across a whole population.

Open source implementations for iOS, Android, and the back-end server are available on the other DP-3T repositories. DP-3T alphas are public for testing and feedback: Android and iOS.

An explanatory comic is also available in many languages.

We also publish privacy and security analysis of specific and general proximity tracing systems. We have published a guidebook to privacy and security risks of the entire spectrum of digital proximity tracing tools, and analysis of the PEPP-PT-NTK and PEPP-PT-ROBERT protocols.

Contact email: dp3t@groupes.epfl.ch.

Joint Statement

DP-3T is listed as one of several privacy-preserving decentralized approaches to contact tracing in a joint statement from over 300 scientists from over 25 countries. The open letter is available here.

Apple and Google Proposal

Apple and Google have released a joint specification describing their system support for privacy-preserving proximity tracing on iOS and Android . Their proposal is very similar to our early proposal named "Low-cost decentralized proximity tracing".

DP-3T appreciates the endorsement of these two companies for our solution and is happy to work with both of them to implement our app on both platforms.

But, we also strongly believe that Apple and Google should adopt our subsequent enhancements, detailed in later versions of our white paper, which increase user privacy. We also strongly encourage both companies to allow an external audit of their code to ensure its functionality corresponds to its specification.

April 8th, 2020: The relationship between DP-3T and PEPP-PT

Please note that since this announcement, DP-3T partners have resigned from the PEPP-PT initiative.

The Decentralised Privacy-Preserving Proximity Tracing (DP-3T) project is an open protocol for COVID-19 proximity tracing using Bluetooth Low Energy functionality on mobile devices that ensures personal data and computation stays entirely on an individual's phone. It was produced by a core team of over 25 scientists and academic researchers from across Europe. It has also been scrutinized and improved by the wider community.

DP-3T is a free-standing effort, originally started at EPFL and ETHZ, that has now broadened out to include stakeholders from across Europe and beyond. We develop the protocol and implement it in an open-sourced app and server on this repository.

DP-3T members have been participating in the loose umbrella of the 'Pan-European Privacy-Preserving Proximity Tracing' (PEPP-PT) project. DP-3T is not the only protocol under this umbrella. PEPP-PT also endorses centralized approaches with very different privacy properties. Pandemics do not respect borders, so there is substantial value in PEPP-PT's role of encouraging dialogue, knowledge-sharing, and interoperability.

Nevertheless, as the systems endorsed by PEPP-PT have technical differences that yield very different privacy properties, it is a mistake to use the term 'PEPP-PT' to describe a specific solution or to refer to PEPP-PT as if it embodies a single approach rather than several very different ones.