Preserving location privacy in ride-hailing service

Youssef Khazbak, Jingyao Fan, Sencun Zhu, Guohong Cao

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Citation (Scopus)

Abstract

Ride-hailing service has become part of our daily life due to its convenience and low cost. However, it also raises location privacy concerns for riders, because the service provider can observe the full mobility traces of riders while they hail rides. To address this problem, we first present a baseline privacy preserving solution. Although the baseline solution can provide personalized rider location privacy, we identify potential location inference attacks against it. To overcome these attacks, we propose an enhanced privacy preserving solution that exploits novel obfuscation techniques to enable matching ride requests to drivers without breaching riders' location privacy and with limited loss of matching accuracy. We use real dataset of taxicabs to show that our solution, compared to previous work, provides much better ride matching, i.e., ride matching closer to the optimal solution, while preserving personalized riders' location privacy.

Original languageEnglish (US)
Title of host publication2018 IEEE Conference on Communications and Network Security, CNS 2018
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Print)9781538645864
DOIs
StatePublished - Aug 10 2018
Event6th IEEE Conference on Communications and Network Security, CNS 2018 - Beijing, China
Duration: May 30 2018Jun 1 2018

Publication series

Name2018 IEEE Conference on Communications and Network Security, CNS 2018

Other

Other6th IEEE Conference on Communications and Network Security, CNS 2018
CountryChina
CityBeijing
Period5/30/186/1/18

Fingerprint

Taxicabs
Precipitation (meteorology)
Costs

All Science Journal Classification (ASJC) codes

  • Computer Networks and Communications
  • Safety, Risk, Reliability and Quality

Cite this

Khazbak, Y., Fan, J., Zhu, S., & Cao, G. (2018). Preserving location privacy in ride-hailing service. In 2018 IEEE Conference on Communications and Network Security, CNS 2018 [8433221] (2018 IEEE Conference on Communications and Network Security, CNS 2018). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/CNS.2018.8433221
Khazbak, Youssef ; Fan, Jingyao ; Zhu, Sencun ; Cao, Guohong. / Preserving location privacy in ride-hailing service. 2018 IEEE Conference on Communications and Network Security, CNS 2018. Institute of Electrical and Electronics Engineers Inc., 2018. (2018 IEEE Conference on Communications and Network Security, CNS 2018).
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title = "Preserving location privacy in ride-hailing service",
abstract = "Ride-hailing service has become part of our daily life due to its convenience and low cost. However, it also raises location privacy concerns for riders, because the service provider can observe the full mobility traces of riders while they hail rides. To address this problem, we first present a baseline privacy preserving solution. Although the baseline solution can provide personalized rider location privacy, we identify potential location inference attacks against it. To overcome these attacks, we propose an enhanced privacy preserving solution that exploits novel obfuscation techniques to enable matching ride requests to drivers without breaching riders' location privacy and with limited loss of matching accuracy. We use real dataset of taxicabs to show that our solution, compared to previous work, provides much better ride matching, i.e., ride matching closer to the optimal solution, while preserving personalized riders' location privacy.",
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Khazbak, Y, Fan, J, Zhu, S & Cao, G 2018, Preserving location privacy in ride-hailing service. in 2018 IEEE Conference on Communications and Network Security, CNS 2018., 8433221, 2018 IEEE Conference on Communications and Network Security, CNS 2018, Institute of Electrical and Electronics Engineers Inc., 6th IEEE Conference on Communications and Network Security, CNS 2018, Beijing, China, 5/30/18. https://doi.org/10.1109/CNS.2018.8433221

Preserving location privacy in ride-hailing service. / Khazbak, Youssef; Fan, Jingyao; Zhu, Sencun; Cao, Guohong.

2018 IEEE Conference on Communications and Network Security, CNS 2018. Institute of Electrical and Electronics Engineers Inc., 2018. 8433221 (2018 IEEE Conference on Communications and Network Security, CNS 2018).

Research output: Chapter in Book/Report/Conference proceedingConference contribution

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AB - Ride-hailing service has become part of our daily life due to its convenience and low cost. However, it also raises location privacy concerns for riders, because the service provider can observe the full mobility traces of riders while they hail rides. To address this problem, we first present a baseline privacy preserving solution. Although the baseline solution can provide personalized rider location privacy, we identify potential location inference attacks against it. To overcome these attacks, we propose an enhanced privacy preserving solution that exploits novel obfuscation techniques to enable matching ride requests to drivers without breaching riders' location privacy and with limited loss of matching accuracy. We use real dataset of taxicabs to show that our solution, compared to previous work, provides much better ride matching, i.e., ride matching closer to the optimal solution, while preserving personalized riders' location privacy.

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Khazbak Y, Fan J, Zhu S, Cao G. Preserving location privacy in ride-hailing service. In 2018 IEEE Conference on Communications and Network Security, CNS 2018. Institute of Electrical and Electronics Engineers Inc. 2018. 8433221. (2018 IEEE Conference on Communications and Network Security, CNS 2018). https://doi.org/10.1109/CNS.2018.8433221