Cross Hashing: Anonymizing encounters in Decentralised Contact Tracing Protocols

Abstract

During the COVID-19 (SARS-CoV-2) epidemic, Contact Tracing emerged as an essential tool for managing the epidemic. App-based solutions have emerged for Contact Tracing, including a protocol designed by Apple and Google (influenced by an open-source protocol known as DP3T). This protocol contains two well-documented de-anonymisation attacks. Firstly that when someone is marked as having tested positive and their keys are made public, they can be tracked over a large geographic area for 24 hours at a time. Secondly, whilst the app requires a minimum exposure duration to register a contact, there is no cryptographic guarantee for this property. This means an adversary can scan Bluetooth networks and retrospectively find who is infected. We propose a novel "cross hashing" approach to cryptographically guarantee minimum exposure durations. We further mitigate the 24-hour data exposure of infected individuals and reduce computational time for identifying if a user has been exposed using k-Anonymous buckets of hashes and Private Set Intersection. We empirically demonstrate that this modified protocol can offer like-for-like efficacy to the existing protocol.

Privacy-preserving Identity Broadcast for Contact Tracing Applications

“…However, by doing so, the users will also be able to reconstruct the entire daily trajectory of the infected user. The problem has been addressed in our recent work [4], where we proposed a cross-hashing approach, in which the daily temporal key is kept secret at all times. Instead, in case of infection, a user reveals cross-contact identifiers (CCI), which are obtained by hashing sequential randomised identifiers.…”

“…This configuration assumes beaconing at 1 Hz frequency combined with continuous scanning. The second, third and (5,6) 806,185 4,030,925 t=10, (3,6) 662,295 6,622,950 t=10, (4,6) 612,878 6,128,780 t=10, (5,6) 537,860 5,378,600 t=20, (3,6) 379,854 7,597,080 t=20, (4,6) 355,480 7,109,600 t=20, (5,6) 323, 788 6,475,760 fourth sections in the table show the effect of a more practical configuration, where a scanner needs to receive k out of n shares, when each share is transmitted for t seconds (i.e. t times).…”

“…Firstly, revealing the daily key allows other users to reconstruct all daily identifiers for that day, and therefore exposes the infected user to tracking throughout an entire day. This could potentially lead to revealing infected users' daily trajectory, a location of his or her home or office [4]. Secondly, the identity of an infected user becomes known not only to people who have been in direct continuous contact with the infected person, but also to Bluetooth devices that only had a fleeting encounter with the person.…”

“…In our recent work, [4] we proposed a cross-hashing method, where infected users share a hash computed from a chain of sequential randomised beacons, rather than their daily keys. This effectively enforces the minimum contact duration as nearby users need to stay around for long enough to receive and compute a hash chain from subsequent beacons.…”

CoAvoid: Secure, Privacy-Preserved Tracing of Contacts for Infectious Diseases

“…From tracking through questionnaires [2] in the 20th century, it has gradually evolved into tracking using digital mobile devices after 2010 [3]- [5]. From 2020, to reduce COVID-19-associated mortality, a variety of tracing approaches have emerged [6]- [8]. These solutions rely on Bluetooth Low Energy (BLE) to broadcast and record frequently changing anonymous identifiers.…”