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Long Live Randomization: On Privacy-Preserving Contact Tracing in Pandemic

Nguyen, Thien Duc and Miettinen, Markus and Sadeghi, Ahmad-Reza (2020):
Long Live Randomization: On Privacy-Preserving Contact Tracing in Pandemic.
In: MTD'20: Proceedings of the 7th ACM Workshop on Moving Target Defense,
ACM, CCS '20: 2020 ACM SIGSAC Conference on Computer and Communications Security, virtual Conference, 09.-13.11.2020, ISBN 978-1-4503-8085-0,
DOI: 10.1145/3411496.3421229,
[Conference or Workshop Item]

Abstract

Caused by coronavirus SARS-CoV-2, the COVID-19 disease spreads particularly through direct contact between people. Health authorities face the challenge of identifying and isolating infection chains to prevent the pandemic from spreading further. To improve the efficiency and effectiveness of manual contact tracing, many countries have recently introduced digital contact tracing apps running on smartphones of users for helping to identify contacts between individual users. These apps are usually based on beaconing pseudonymous identifiers over a proximity communication protocol like Bluetooth LE. The identification of potentially critical contacts is then performed by comparing the identifiers emitted by persons reported as infected and the identifiers observed by other users of the system and issuing appropriate warnings to them in case a matching identifier is found. However, by beaconing identifiers into their proximity, individual users potentially become traceable by entities that systematically collect observations in various places. To preserve privacy of users and be compliant to various privacy regulations many proposed systems use ephemeral, pseudo-random identifiers that are more difficult to link together.In this paper, we briefly analyze and discuss privacy properties of a selected number of proposed contact tracing solutions and the impact of the applied randomization approaches. We also discuss the pros and cons of these tracing schemes.

Item Type: Conference or Workshop Item
Erschienen: 2020
Creators: Nguyen, Thien Duc and Miettinen, Markus and Sadeghi, Ahmad-Reza
Title: Long Live Randomization: On Privacy-Preserving Contact Tracing in Pandemic
Language: English
Abstract:

Caused by coronavirus SARS-CoV-2, the COVID-19 disease spreads particularly through direct contact between people. Health authorities face the challenge of identifying and isolating infection chains to prevent the pandemic from spreading further. To improve the efficiency and effectiveness of manual contact tracing, many countries have recently introduced digital contact tracing apps running on smartphones of users for helping to identify contacts between individual users. These apps are usually based on beaconing pseudonymous identifiers over a proximity communication protocol like Bluetooth LE. The identification of potentially critical contacts is then performed by comparing the identifiers emitted by persons reported as infected and the identifiers observed by other users of the system and issuing appropriate warnings to them in case a matching identifier is found. However, by beaconing identifiers into their proximity, individual users potentially become traceable by entities that systematically collect observations in various places. To preserve privacy of users and be compliant to various privacy regulations many proposed systems use ephemeral, pseudo-random identifiers that are more difficult to link together.In this paper, we briefly analyze and discuss privacy properties of a selected number of proposed contact tracing solutions and the impact of the applied randomization approaches. We also discuss the pros and cons of these tracing schemes.

Title of Book: MTD'20: Proceedings of the 7th ACM Workshop on Moving Target Defense
Publisher: ACM
ISBN: 978-1-4503-8085-0
Divisions: 20 Department of Computer Science
20 Department of Computer Science > System Security Lab
DFG-Collaborative Research Centres (incl. Transregio)
DFG-Collaborative Research Centres (incl. Transregio) > Collaborative Research Centres
Profile Areas
Profile Areas > Cybersecurity (CYSEC)
DFG-Collaborative Research Centres (incl. Transregio) > Collaborative Research Centres > CRC 1119: CROSSING – Cryptography-Based Security Solutions: Enabling Trust in New and Next Generation Computing Environments
Event Title: CCS '20: 2020 ACM SIGSAC Conference on Computer and Communications Security
Event Location: virtual Conference
Event Dates: 09.-13.11.2020
Date Deposited: 03 Feb 2021 15:00
DOI: 10.1145/3411496.3421229
Corresponding Links:
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Alternative keywordsLanguage
contact tracingEnglish
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