TY - GEN
T1 - Privacy-Preserving Contact Tracing Protocol for Mobile Devices
T2 - 16th International Conference on Information Security Practice and Experience, ISPEC 2021
AU - Liu, Joseph K.
AU - Au, Man Ho
AU - Yuen, Tsz Hon
AU - Zuo, Cong
AU - Wang, Jiawei
AU - Sakzad, Amin
AU - Luo, Xiapu
AU - Li, Li
AU - Choo, Kim Kwang Raymond
N1 - Publisher Copyright:
© 2021, Springer Nature Switzerland AG.
PY - 2021
Y1 - 2021
N2 - In this paper, we propose a privacy-preserving contact tracing protocol for smart phones, and more specifically Android and iOS phones. The protocol allows users to be notified, if they have been a close contact of a confirmed patient. The protocol is designed to strike a balance between privacy, security, and scalability. Specifically, the app allows all users to hide their past location(s) and contact history from the Government, without affecting their ability to determine whether they have close contact with a confirmed patient whose identity will not be revealed. A zero-knowledge protocol is used to achieve such a user privacy functionality. In terms of security, no user can send fake messages to the system to launch a false positive attack. We present a security model and formally prove the security of the protocol. To demonstrate scalability, we evaluate an Android and an iOS implementation of our protocol. A comparative summary shows that our protocol is the most comprehensive and balanced privacy-preserving contact tracing solution to-date.
AB - In this paper, we propose a privacy-preserving contact tracing protocol for smart phones, and more specifically Android and iOS phones. The protocol allows users to be notified, if they have been a close contact of a confirmed patient. The protocol is designed to strike a balance between privacy, security, and scalability. Specifically, the app allows all users to hide their past location(s) and contact history from the Government, without affecting their ability to determine whether they have close contact with a confirmed patient whose identity will not be revealed. A zero-knowledge protocol is used to achieve such a user privacy functionality. In terms of security, no user can send fake messages to the system to launch a false positive attack. We present a security model and formally prove the security of the protocol. To demonstrate scalability, we evaluate an Android and an iOS implementation of our protocol. A comparative summary shows that our protocol is the most comprehensive and balanced privacy-preserving contact tracing solution to-date.
UR - http://www.scopus.com/inward/record.url?scp=85122031809&partnerID=8YFLogxK
U2 - 10.1007/978-3-030-93206-0_20
DO - 10.1007/978-3-030-93206-0_20
M3 - Conference contribution
AN - SCOPUS:85122031809
SN - 9783030932053
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 327
EP - 344
BT - Information Security Practice and Experience - 16th International Conference, ISPEC 2021, Proceedings
A2 - Deng, Robert
A2 - Bao, Feng
A2 - Wang, Guilin
A2 - Shen, Jian
A2 - Ryan, Mark
A2 - Meng, Weizhi
A2 - Wang, Ding
PB - Springer Science and Business Media Deutschland GmbH
Y2 - 17 December 2021 through 19 December 2021
ER -