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Protecting Location Privacy in Spatial Crowdsourcing

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Web Technologies and Applications (APWeb 2015)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 9461))

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Abstract

Recently, spatial crowdsourcing has attracted wide attention in both the research community and industry, one of which is the eMarket platform. It enables requesters to release spatial tasks (i.e., tasks related to a location) and expect them to be performed by workers (i.e., users with smart mobile devices). One of the key functions of such platform is spatial tasks assignment. The traditional solutions to the tasks assignment problem require workers to disclose their locations to the spatial crowdsourcing server (SC-server), which are untrustworthy entities. In this paper, we employ the peer-to-peer spatial K-anonymity to protect the workers’ location privacy. However, it will result in the consequence that various spatial tasks can’t be performed. To improve the spatial task assignment, we propose an optimized scheme for spatial task assignment without compromising the workers’ location privacy, and verify the effect through our experiments.

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Author information

Authors and Affiliations

  1. School of Computer Science and Technology, University of Science and Technology of China, Hefei, Anhui, People’s Republic of China

    Jie Hu, Liusheng Huang, Lu Li & Wei Yang

  2. Suzhou Institute for Advanced Study, University of Science and Technology of China, Suzhou, Jiangsu, People’s Republic of China

    Jie Hu, Liusheng Huang, Lu Li, Mingyu Qi & Wei Yang

Authors
  1. Jie Hu
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  2. Liusheng Huang
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  3. Lu Li
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  4. Mingyu Qi
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  5. Wei Yang
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Corresponding author

Correspondence to Jie Hu .

Editor information

Editors and Affiliations

  1. Guangdong University of Technology, Guangzhou, Guangdong, China

    Ruichu Cai

  2. Research Institute of China Telecom Co., Guangzhou, China

    Kang Chen

  3. Wuhan University, Wuhan, China

    Liang Hong

  4. Advanced Digital Sciences Center, Singapore, Singapore

    Xiaoyan Yang

  5. East China Normal University, Shanghai, China

    Rong Zhang

  6. Peking University, Beijing, China

    Lei Zou

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© 2015 Springer International Publishing Switzerland

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Hu, J., Huang, L., Li, L., Qi, M., Yang, W. (2015). Protecting Location Privacy in Spatial Crowdsourcing. In: Cai, R., Chen, K., Hong, L., Yang, X., Zhang, R., Zou, L. (eds) Web Technologies and Applications. APWeb 2015. Lecture Notes in Computer Science(), vol 9461. Springer, Cham. https://doi.org/10.1007/978-3-319-28121-6_11

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  • DOI: https://doi.org/10.1007/978-3-319-28121-6_11

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-28120-9

  • Online ISBN: 978-3-319-28121-6

  • eBook Packages: Computer ScienceComputer Science (R0)

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