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International Conference on Information Security

ISC 2022: Information Security pp 473–490Cite as

Bilateral Privacy-Preserving Task Assignment with Personalized Participant Selection for Mobile Crowdsensing

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Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 13640))

Abstract

Mobile crowdsensing (MCS) as an emerging data collection paradigm allows people to collect data for more effective decision-making. Task assignment as an integral part of MCS plays an important role in the working of the system. However, the balance between system efficiency and result accuracy is still a challenge to be solved, while the privacy of requesters and task participants are needed to be considered during assigning tasks. This paper proposes a bilateral privacy-preserving task assignment scheme with personalized participant selection for MCS. With the design of a privacy-preserving top-k selection sub-protocol, the proposed scheme supports the task requester to personalize the selection of participants for task assignment. The balance between efficiency and accuracy is entirely determined by the preference of the task requester. The proposed scheme provides the protections of the privacy of both the task content and personalized parameters of the requester and the status and identity of the participants. Simulation experiments are performed on smart devices with a real-world dataset, and the results demonstrate the effectiveness of the proposed task assignment scheme compared to the previous work.

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Acknowledgements

This work is supported by the National Natural Science Foundation of China under grants 62072134 and U2001205, and the Key projects of Guangxi Natural Science Foundation under grant 2019JJD170020, and the Key Research and Development Program of Hubei Province under Grant 2021BEA163.

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Authors and Affiliations

  1. School of Computer Science, Hubei University of Technology, Wuhan, China

    Shijin Chen & Mingwu Zhang

  2. School of Computer Science, Shaanxi Normal University, Xi’an, China

    Bo Yang

Authors
  1. Shijin Chen
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  2. Mingwu Zhang
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  3. Bo Yang
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Corresponding author

Correspondence to Mingwu Zhang .

Editor information

Editors and Affiliations

  1. University of Wollongong, Wollongong, NSW, Australia

    Willy Susilo

  2. Xidian University, Xian, China

    Xiaofeng Chen

  3. University of Wollongong, Wollongong, NSW, Australia

    Fuchun Guo

  4. University of Wollongong, Wollongong, NSW, Australia

    Yudi Zhang

  5. Petra Christian University, Surabaya, Indonesia

    Rolly Intan

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Chen, S., Zhang, M., Yang, B. (2022). Bilateral Privacy-Preserving Task Assignment with Personalized Participant Selection for Mobile Crowdsensing. In: Susilo, W., Chen, X., Guo, F., Zhang, Y., Intan, R. (eds) Information Security. ISC 2022. Lecture Notes in Computer Science, vol 13640. Springer, Cham. https://doi.org/10.1007/978-3-031-22390-7_28

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  • DOI: https://doi.org/10.1007/978-3-031-22390-7_28

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-031-22389-1

  • Online ISBN: 978-3-031-22390-7

  • eBook Packages: Computer ScienceComputer Science (R0)

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