  This document describes and analyzes a system for secure and
privacy-preserving proximity tracing at large scale. This system, referred to
as DP3T, provides a technological foundation to help slow the spread of
SARS-CoV-2 by simplifying and accelerating the process of notifying people who
might have been exposed to the virus so that they can take appropriate measures
to break its transmission chain. The system aims to minimise privacy and
security risks for individuals and communities and guarantee the highest level
of data protection. The goal of our proximity tracing system is to determine
who has been in close physical proximity to a COVID-19 positive person and thus
exposed to the virus, without revealing the contact's identity or where the
contact occurred. To achieve this goal, users run a smartphone app that
continually broadcasts an ephemeral, pseudo-random ID representing the user's
phone and also records the pseudo-random IDs observed from smartphones in close
proximity. When a patient is diagnosed with COVID-19, she can upload
pseudo-random IDs previously broadcast from her phone to a central server.
Prior to the upload, all data remains exclusively on the user's phone. Other
users' apps can use data from the server to locally estimate whether the
device's owner was exposed to the virus through close-range physical proximity
to a COVID-19 positive person who has uploaded their data. In case the app
detects a high risk, it will inform the user.
