BU-Trace : A Permissionless Mobile System for Privacy-Preserving Intelligent Contact Tracing

Research output: Chapters, Conference Papers, Creative and Literary WorksRGC 32 - Refereed conference paper (with host publication)peer-review

12 Scopus Citations
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Author(s)

  • Zhe Peng
  • Jinbin Huang
  • Haixin Wang
  • Shihao Wang
  • Xiaowen Chu
  • Li Chen
  • Xin Huang
  • Xiaoyi Fu
  • Yike Guo
  • Jianliang Xu

Detail(s)

Original languageEnglish
Title of host publicationDatabase Systems for Advanced Applications. DASFAA 2021 International Workshops
Subtitle of host publicationBDQM, GDMA, MLDLDSA, MobiSocial, and MUST, Taipei, Taiwan, April 11–14, 2021, Proceedings
EditorsChristian S. Jensen, Ee-Peng Lim, De-Nian Yang
Place of PublicationCham
PublisherSpringer 
Pages381-397
ISBN (electronic)978-3-030-73216-5
ISBN (print)9783030732158
Publication statusPublished - 2021
Externally publishedYes

Publication series

NameLecture Notes in Computer Science
Volume12680
ISSN (Print)0302-9743
ISSN (electronic)1611-3349

Conference

Title26th International Conference on Database Systems for Advanced Applications (DASFAA 2021)
LocationOnline
PlaceTaiwan
CityTaipei
Period11 - 14 April 2021

Abstract

The coronavirus disease 2019 (COVID-19) pandemic has caused an unprecedented health crisis for the global. Digital contact tracing, as a transmission intervention measure, has shown its effectiveness on pandemic control. Despite intensive research on digital contact tracing, existing solutions can hardly meet users’ requirements on privacy and convenience. In this paper, we propose BU - Trace, a novel permissionless mobile system for privacy-preserving intelligent contact tracing based on QR code and NFC technologies. First, a user study is conducted to investigate and quantify the user acceptance of a mobile contact tracing system. Second, a decentralized system is proposed to enable contact tracing while protecting user privacy. Third, an intelligent behavior detection algorithm is designed to ease the use of our system. We implement BU - Trace and conduct extensive experiments in several real-world scenarios. The experimental results show that BU - Trace achieves a privacy-preserving and intelligent mobile system for contact tracing without requesting location or other privacy-related permissions. © 2021, Springer Nature Switzerland AG.

Research Area(s)

  • Contact tracing, Intelligent, Permissionless, Privacy-preserving

Citation Format(s)

BU-Trace: A Permissionless Mobile System for Privacy-Preserving Intelligent Contact Tracing. / Peng, Zhe; Huang, Jinbin; Wang, Haixin et al.
Database Systems for Advanced Applications. DASFAA 2021 International Workshops: BDQM, GDMA, MLDLDSA, MobiSocial, and MUST, Taipei, Taiwan, April 11–14, 2021, Proceedings. ed. / Christian S. Jensen; Ee-Peng Lim; De-Nian Yang. Cham: Springer , 2021. p. 381-397 (Lecture Notes in Computer Science; Vol. 12680).

Research output: Chapters, Conference Papers, Creative and Literary WorksRGC 32 - Refereed conference paper (with host publication)peer-review