Interoperable Digital Proximity Tracing protocol (IDPT)

Draft Version 2, 19/05/2020, 25/05/2020This document introduces the Interoperable Digital Proximity Tracing (IDPT) protocol, that can be run by applications that also run the DP3T digital proximity tracking protocol to enable interoperability with the ROBERT digital proximity tracking protocol . We believe that the same mechanism can be adapted to allow interoperability between other decentralized and centralized digital proximity tracing protocols, but analysis of this is kept out of the scope of the document. The IDPT protocol avoids the reidentification attack of positive-tested users of the centralised system that was claimed to be an inherent property of interoperability systems , as in IDPT the system does not publish the list of decentralised ephemeral identifier that were at risk of exposure of users of app R. Moreover, it avoids the possibility of creation of proximity graphs for users of IDPT who were in contact with users of ROBERT. As is well known, the current iOS and Android Exposure Notification API only supports protocols of the distributed class. Due to this lack of support for centralized approaches, the implementation of the IDPT protocol has the same known difficulties as ROBERT, which appear mainly when applications are running in the background. Additionally, since devices must transmit more BLE beacons per second, we expect that devices running IDPT will have higher power consumption compared to implementing a pure DP3T mechanism. We believe that, in practice, the use of IDPT in countries where majority of users of DP3T-type applications should be optional, mainly in areas where the presence of R nodes is likely (for example, large cities, tourist areas, airports, etc.). Another situation in which the use of IDPT could be adequate is when a user of the app I visits a country where the majority of the population uses R application. In addition, a country could introduce a DP3T application in a first phase, and only later incorporate IDPT.Preprin

Analysis of DP3T

To help fighting the COVID-19 pandemic, the Pan-European Privacy-Preserving Proximity Tracing (PEPP-PT) project proposed a Decentralized Privacy-Preserving Proximity Tracing (DP3T) system. This helps tracking the spread of SARS-CoV-2 virus while keeping the privacy of individuals safe. In this report, we analyze the security and the privacy protection of DP3T. Without questioning how effective it could be against the pandemic, we show that it may introduce severe risks to society. Furthermore, we argue that some privacy protection measurements by DP3T may have the opposite affect of what they were intended to. Specifically, sick and reported people may be deanonymized, private encounters may be revealed, and people may be coerced to reveal the private data they collect

A model for A=3 antinuclei production in proton-nucleus collisions

A simple coalescence model based on the same diagrammatic approach of antimatter production in hadronic collisions as used previously for antideuterons is used here for the hadroproduction of mass 3 antinuclei. It is shown that the model is able to reproduce the existing experimental data on Tbar and 3hebar production without any additional parameter.Comment: 7 figures. submitted to Eur. Phys. J.

Poster: Trace yourself-it could be easy

Contact tracing helps to predict and prevent the spread of viruses. This work proposes Tracey for decentralized, privacy-preserving tracing. Unlike automated tracing solutions that operate in the background, such as the widespread governmental Corona Tracing Apps, our system builds on manual contact exchanges to ensure reliable contact tracing even for groups and venues. The devices share secrets that allow anonymous notifications using the health authorities’ trusted database. This work illustrates the concept, provides initial security analysis, first results, and gives an outlook on possible extensions

The saga of the Covid-19 contact tracing apps: lessons for data governance

This note selectively unpacks the rapid evolution of the (Western) debate around the opportunity to deploy contact tracing apps, alongside other digital tools such as apps for symptoms sharing and immunity certificates to mitigate the Covid-19 pandemics. I do so from the perspective of a social scientist interested in the implications of the development of digital tools at times of emergency in terms of data governance. I argue that a more articulated reflection is needed towards the development of a healthy institutional structure that regulates the role of large tech platforms, such as Google and Apple (G&A), and public institutions, in governing data, particularly when health data and public value are involved. I unravel the saga of contact tracing apps in the UK and EU, looking at the technical, legal and ethical aspects and I attempt to draw more general lessons for data governance

Rapid Review of Contact Tracing Methods for COVID-19

This rapid review explores the question “How can we undertake ‘people-powered’ contact tracing activity at scale? What types of options are available?”. The main focus of the report will be on investigating any methods and evidence around digitally enhanced people-powered contact tracing. The spectrum of available methodologies for contact tracing range from paper-based methods to fully automated, anonymous digital contact tracing using mobile phone Apps and Bluetooth or geolocation services. Selected examples are provided

COVID-19 Tracking Applications: A Human-Centric Analysis

The year 2020 will always be remembered with the imprints left by COVID-19 on our lives. While the pandemic has had many undesirable effects for the whole world, one of its biggest side effects has been the fast digital transformation that has taken place, which was already in progress with the Industry 4.0 era. The readily available technology and wireless communications infrastructures paved the way for a myriad of digital technologies for the containment of the disease using mobile contact tracing applications developed by health authority organizations in many countries. The mounting privacy concerns especially with Bluetooth-enabled proximity tracing and centralized tracking technologies used by these applications have given rise to the development of new privacy-preserving contact tracing protocols. Although these new protocols have alleviated the privacy concerns of citizens to a certain extent, widespread adoption is still far from being the reality. In this paper, we analyze existing contact tracing technologies from a human-centric standpoint by focusing on their privacy implications. We present our comprehensive dataset consisting of the contact tracing application usage information in 94 countries and provide results of a multinational survey we have conducted on the sentiments of people regarding contact tracing applications. The survey results demonstrate that privacy concerns are still the leading deterrent for people when deciding whether to use these applications. Nevertheless, it is a globally accepted argument that the most effective and fastest method for contact tracking will be digital technologies free from human errors and manual procedures. Accordingly, it is concluded that a policy of developing decentralized tracking solutions based entirely on user privacy should be followed, in which independent trusted third parties assume the role of authority in the system architecture, if absolutely necessary, in order to effectively combat the pandemic worldwide. An important feature of the systems to be developed to pave the way for widespread use is to provide the users the right to be forgotten