P2B-Trace: Privacy-Preserving Blockchain-based Contact Tracing to Combat Pandemics

Zhe Peng, Cheng Xu, Haixin Wang, Jinbin Huang, Jianliang Xu, Xiaowen Chu

Research output: Chapter in book/report/conference proceedingConference proceedingpeer-review

52 Citations (Scopus)

Abstract

The eruption of a pandemic, such as COVID-19, can cause an unprecedented global crisis. Contact tracing, as a pillar of communicable disease control in public health for decades, has shown its effectiveness on pandemic control. Despite intensive research on contact tracing, existing schemes are vulnerable to attacks and can hardly simultaneously meet the requirements of data integrity and user privacy. The design of a privacy-preserving contact tracing framework to ensure the integrity of the tracing procedure has not been sufficiently studied and remains a challenge. In this paper, we propose P2B-Trace, a privacy-preserving contact tracing initiative based on blockchain. First, we design a decentralized architecture with blockchain to record an authenticated data structure of the user's contact records, which prevents the user from intentionally modifying his local records afterward. Second, we develop a zero-knowledge proximity verification scheme to further verify the user's proximity claim while protecting user privacy. We implement P2B-Trace and conduct experiments to evaluate the cost of privacy-preserving tracing integrity verification. The evaluation results demonstrate the effectiveness of our proposed system.

Original languageEnglish
Title of host publicationSIGMOD '21: Proceedings of the 2021 International Conference on Management of Data
PublisherAssociation for Computing Machinery (ACM)
Pages2389-2393
Number of pages5
ISBN (Print)9781450383431
DOIs
Publication statusPublished - Jun 2021
EventACM SIGMOD International Conference on Management of Data, SIGMOD 2021 - Virtual, Online, China
Duration: 20 Jun 202125 Jun 2021
https://dl.acm.org/doi/proceedings/10.1145/3448016

Publication series

NameProceedings of the ACM SIGMOD International Conference on Management of Data
ISSN (Print)0730-8078

Conference

ConferenceACM SIGMOD International Conference on Management of Data, SIGMOD 2021
Country/TerritoryChina
Period20/06/2125/06/21
Internet address

Scopus Subject Areas

  • Software
  • Information Systems

User-Defined Keywords

  • blockchain
  • contact tracing
  • integrity
  • privacy-preserving

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