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; Yike Guo; Jianliang Xu

doi:10.1007/978-3-030-73216-5_26

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, Yike Guo, Jianliang Xu^*

^*Corresponding author for this work

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

14 Citations (Scopus)

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.

Original language	English
Title of host publication	Database Systems for Advanced Applications. DASFAA 2021 International Workshops
Subtitle of host publication	BDQM, GDMA, MLDLDSA, MobiSocial, and MUST, Taipei, Taiwan, April 11–14, 2021, Proceedings
Editors	Christian S. Jensen, Ee-Peng Lim, De-Nian Yang
Place of Publication	Cham
Publisher	Springer
Pages	381-397
ISBN (Electronic)	978-3-030-73216-5
ISBN (Print)	9783030732158
DOIs	https://doi.org/10.1007/978-3-030-73216-5_26
Publication status	Published - 2021
Externally published	Yes
Event	26th International Conference on Database Systems for Advanced Applications (DASFAA 2021) - Online, Taipei, Taiwan Duration: 11 Apr 2021 → 14 Apr 2021 https://dm.iis.sinica.edu.tw/DASFAA2021/call_for_research_paper.html

Publication series

Name	Lecture Notes in Computer Science
Volume	12680
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Conference

Conference	26th International Conference on Database Systems for Advanced Applications (DASFAA 2021)
Country/Territory	Taiwan
City	Taipei
Period	11/04/21 → 14/04/21
Internet address	https://dm.iis.sinica.edu.tw/DASFAA2021/call_for_research_paper.html

Research Keywords

Contact tracing
Intelligent
Permissionless
Privacy-preserving

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

Access Output

10.1007/978-3-030-73216-5_26

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Cite this

Peng, Z., Huang, J., Wang, H., Wang, S., Chu, X., Zhang, X., Chen, L., Huang, X., Fu, X., Guo, Y., & Xu, J. (2021). BU-Trace: A Permissionless Mobile System for Privacy-Preserving Intelligent Contact Tracing. In C. S. Jensen, E.-P. Lim, & D.-N. Yang (Eds.), Database Systems for Advanced Applications. DASFAA 2021 International Workshops: BDQM, GDMA, MLDLDSA, MobiSocial, and MUST, Taipei, Taiwan, April 11–14, 2021, Proceedings (pp. 381-397). (Lecture Notes in Computer Science; Vol. 12680). Springer . https://doi.org/10.1007/978-3-030-73216-5_26

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

@inproceedings{c0833aee51e0439498166d6a89cdc632,

title = "BU-Trace: A Permissionless Mobile System for Privacy-Preserving Intelligent Contact Tracing",

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{\textquoteright} 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. {\textcopyright} 2021, Springer Nature Switzerland AG.",

keywords = "Contact tracing, Intelligent, Permissionless, Privacy-preserving",

author = "Zhe Peng and Jinbin Huang and Haixin Wang and Shihao Wang and Xiaowen Chu and Xinzhi Zhang and Li Chen and Xin Huang and Xiaoyi Fu and Yike Guo and Jianliang Xu",

year = "2021",

doi = "10.1007/978-3-030-73216-5_26",

language = "English",

isbn = "9783030732158",

series = "Lecture Notes in Computer Science",

publisher = "Springer ",

pages = "381--397",

editor = "Jensen, {Christian S.} and Ee-Peng Lim and De-Nian Yang",

booktitle = "Database Systems for Advanced Applications. DASFAA 2021 International Workshops",

note = "26th International Conference on Database Systems for Advanced Applications (DASFAA 2021) ; Conference date: 11-04-2021 Through 14-04-2021",

url = "https://dm.iis.sinica.edu.tw/DASFAA2021/call_for_research_paper.html",

}

Peng, Z, Huang, J, Wang, H, Wang, S, Chu, X, Zhang, X, Chen, L, Huang, X, Fu, X, Guo, Y & Xu, J 2021, BU-Trace: A Permissionless Mobile System for Privacy-Preserving Intelligent Contact Tracing. in CS Jensen, E-P Lim & D-N Yang (eds), Database Systems for Advanced Applications. DASFAA 2021 International Workshops: BDQM, GDMA, MLDLDSA, MobiSocial, and MUST, Taipei, Taiwan, April 11–14, 2021, Proceedings. Lecture Notes in Computer Science, vol. 12680, Springer , Cham, pp. 381-397, 26th International Conference on Database Systems for Advanced Applications (DASFAA 2021), Taipei, Taiwan, 11/04/21. https://doi.org/10.1007/978-3-030-73216-5_26

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 Works › RGC 32 - Refereed conference paper (with host publication) › peer-review

TY - GEN

T1 - BU-Trace

T2 - 26th International Conference on Database Systems for Advanced Applications (DASFAA 2021)

AU - Peng, Zhe

AU - Huang, Jinbin

AU - Wang, Haixin

AU - Wang, Shihao

AU - Chu, Xiaowen

AU - Zhang, Xinzhi

AU - Chen, Li

AU - Huang, Xin

AU - Fu, Xiaoyi

AU - Guo, Yike

AU - Xu, Jianliang

PY - 2021

Y1 - 2021

N2 - 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.

AB - 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.

KW - Contact tracing

KW - Intelligent

KW - Permissionless

KW - Privacy-preserving

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UR - https://www.scopus.com/record/pubmetrics.uri?eid=2-s2.0-85104752779&origin=recordpage

U2 - 10.1007/978-3-030-73216-5_26

DO - 10.1007/978-3-030-73216-5_26

M3 - RGC 32 - Refereed conference paper (with host publication)

SN - 9783030732158

T3 - Lecture Notes in Computer Science

SP - 381

EP - 397

BT - Database Systems for Advanced Applications. DASFAA 2021 International Workshops

A2 - Jensen, Christian S.

A2 - Lim, Ee-Peng

A2 - Yang, De-Nian

PB - Springer

CY - Cham

Y2 - 11 April 2021 through 14 April 2021

ER -

Peng Z, Huang J, Wang H, Wang S, Chu X, Zhang X et al. BU-Trace: A Permissionless Mobile System for Privacy-Preserving Intelligent Contact Tracing. In Jensen CS, Lim EP, Yang DN, editors, Database Systems for Advanced Applications. DASFAA 2021 International Workshops: BDQM, GDMA, MLDLDSA, MobiSocial, and MUST, Taipei, Taiwan, April 11–14, 2021, Proceedings. Cham: Springer . 2021. p. 381-397. (Lecture Notes in Computer Science). Epub 2021 Apr 6. doi: 10.1007/978-3-030-73216-5_26

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

Abstract

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Conference

Research Keywords

UN SDGs

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