Paper 2020/375

Privacy-Preserving Contact Tracing of COVID-19 Patients

Leonie Reichert, Samuel Brack, and Björn Scheuermann

Abstract

The current Covid-19 pandemic shows that our modern globalized world can be heavily affected by a quickly spreading, highly infectious, deadly virus in a matter of weeks. It became apparent that manual contact tracing and quarantining of suspects can only be effective in the first days of the spread before the exponential growth overwhelms the health authorities. By automating tracing processes and quarantining everyone who came in contact with infected people, as well as arriving travelers, it should be possible to quickly loosen lockdown measures. Countries like China, Singapore and Israel hastily developed privacy-endangering schemes to computationally trace contacts using user-generated location histories or mass surveillance data . There have been reports of deanonymizations of South Korean citizens from the public “anonymized” data set of infected people. To approach this conflict of interests first identify and formulate of privacy risks of contact tracing. On this basis we propose a privacy-preserving approach to contact tracing using secure multi party computation and binary search. Our preliminary evaluation shows the idea is feasible in different scenarios derived from real-world case studies.

Metadata
Available format(s)
PDF
Category
Applications
Publication info
Published elsewhere. https://www.ieee-security.org/TC/SP2020/poster-abstracts/hotcrp_sp20posters-final10.pdf
Keywords
Secure Multiparty ComputationContact TracingPrivacy Enhancing TechnologiesHealth Data
Contact author(s)
reicleon @ hu-berlin de
samuel brack @ informatik hu-berlin de
History
2020-11-02: last of 3 revisions
2020-04-02: received
See all versions
Short URL
https://ia.cr/2020/375
License
Creative Commons Attribution
CC BY

BibTeX

@misc{cryptoeprint:2020/375,
      author = {Leonie Reichert and Samuel Brack and Björn Scheuermann},
      title = {Privacy-Preserving Contact Tracing of COVID-19 Patients},
      howpublished = {Cryptology ePrint Archive, Paper 2020/375},
      year = {2020},
      note = {\url{https://eprint.iacr.org/2020/375}},
      url = {https://eprint.iacr.org/2020/375}
}
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