A Geo-Obfuscation Approach to Protect Worker Location Privacy in Spatial Crowdsourcing Systems

Ce Pang, Chenxi Qiu, Ning Wang

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

4 Scopus citations

Abstract

In Spatial Crowdsourcing (SC), workers are required to move to the task location to perform the tasks. To promote cost-effective crowdsourcing work, tasks need to be assigned to workers with low traveling costs. As such, workers are required to disclose their location information to SC servers, which may lead to serious privacy concerns. In this paper, we propose a geo-obfuscation approach to help workers protect their location information while ensuring the accuracy of traveling cost estimation in task assignment. We implemented our approach with a real-world experiment and the experimental results demonstrate the effectiveness of our approach in terms of both privacy and information accuracy.

Original languageEnglish (US)
Title of host publicationProceedings - 2019 IEEE 16th International Conference on Mobile Ad Hoc and Smart Systems Workshops, MASSW 2019
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages166-167
Number of pages2
ISBN (Electronic)9781728141213
DOIs
StatePublished - Nov 2019
Event16th IEEE International Conference on Mobile Ad Hoc and Smart Systems Workshops, MASSW 2019 - Monterey, United States
Duration: Nov 4 2019Nov 7 2019

Publication series

NameProceedings - 2019 IEEE 16th International Conference on Mobile Ad Hoc and Smart Systems Workshops, MASSW 2019

Conference

Conference16th IEEE International Conference on Mobile Ad Hoc and Smart Systems Workshops, MASSW 2019
Country/TerritoryUnited States
CityMonterey
Period11/4/1911/7/19

All Science Journal Classification (ASJC) codes

  • Artificial Intelligence
  • Computer Networks and Communications
  • Hardware and Architecture
  • Safety, Risk, Reliability and Quality
  • Control and Optimization

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