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Paper 2020/528

Privacy-Preserving COVID-19 Contact Tracing App: A Zero-Knowledge Proof Approach

Joseph K. Liu and Man Ho Au and Tsz Hon Yuen and Cong Zuo and Jiawei Wang and Amin Sakzad and Xiapu Luo and Li Li

Abstract

In this paper, we propose a privacy-preserving contact tracing app for COVID-19. The app allows users to be notified, if they have been a close contact with a confirmed patient. Our protocol is the most comprehensive and balanced privacy-preserving contact tracing solution to date. Our protocol strikes a balance between security, privacy and scalability. In terms of privacy, it allows all users to hide his past location and contact history with respect to the Government. Yet, all users can check whether he had a close contact with a confirmed patient without learning the identity of the patient. We use a zero-knowledge protocol to ensure that user privacy is protected. In terms of security, no user can send fake message to the system to launch a false positive attack. We give a formal security model and give a security proof for our protocol. In terms of scalability, we have implemented our protocol into Android smartphone and our evaluation result shows its practicality.

Metadata
Available format(s)
PDF
Category
Applications
Publication info
Preprint. MINOR revision.
Keywords
COVID-19Zero-knowledge proof
Contact author(s)
joseph liu @ monash edu
History
2021-10-17: last of 4 revisions
2020-05-06: received
See all versions
Short URL
https://ia.cr/2020/528
License
Creative Commons Attribution
CC BY
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