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

Zhe PENG, Jinbin Huang, Haixin Wang, Shihao Wang, Xiaowen CHU, Xinzhi ZHANG, Li CHEN, Xin HUANG, Xiaoyi Fu, Yi-Ke GUO, Jianliang XU*

*Corresponding author for this work

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

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.

Original languageEnglish
Title of host publicationDatabase Systems for Advanced Applications
Subtitle of host publicationDASFAA 2021 International Workshops - BDQM, GDMA, MLDLDSA, MobiSocial and MUST, Proceedings
EditorsChristian S. Jensen, Ee-Peng Lim, De-Nian Yang, Wang-Chien Lee, Vincent S. Tseng, Vana Kalogeraki, Jen-Wei Huang, Chih-Ya Shen
PublisherSpringer Science and Business Media Deutschland GmbH
Pages381-397
Number of pages17
ISBN (Print)9783030732158
DOIs
Publication statusPublished - 2021
EventInternational Conference on Database Systems for Advanced Applications, DASFAA 2021 held in conjunction with BDQM 2021, GDMA 2021, MLDLDSA 2021, MobiSocial 2021 and MUST 2021 - Taipei, Taiwan, Province of China
Duration: 11 Apr 202114 Apr 2021

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume12680 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

ConferenceInternational Conference on Database Systems for Advanced Applications, DASFAA 2021 held in conjunction with BDQM 2021, GDMA 2021, MLDLDSA 2021, MobiSocial 2021 and MUST 2021
Country/TerritoryTaiwan, Province of China
CityTaipei
Period11/04/2114/04/21

Scopus Subject Areas

  • Theoretical Computer Science
  • Computer Science(all)

User-Defined Keywords

  • Contact tracing
  • Intelligent
  • Permissionless
  • Privacy-preserving

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