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User experience-driven secure task assignment in spatial crowdsourcing

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Abstract

With the ubiquity of mobile devices and wireless networks, Spatial Crowdsourcing (SC) has earned considerable importance and attention as a new strategy of problem-solving. Tasks in SC have location constraints and workers need to move to certain locations to perform them. Current studies mainly focus on maximizing the benefits of the SC platform. However, user average waiting time, which is an important indicator of user experience, has been overlooked. To enhance user experience, the SC platform needs to collect lots of data from both workers and users. During this process, the private information may be compromised if the platform is not trustworthy. In this paper, we first define user experience-driven secure task assignment problem and propose two privacy-preserving online task assignment strategies to minimize the average waiting time. We securely construct an encrypted bipartite graph to protect private data. Based on this encrypted graph, we propose a secure Kuhn-Munkres algorithm to realize task assignment without privacy disclosure. Theoretical analysis shows the security of our approach and experimental results demonstrates its efficiency and effectiveness.

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Acknowledgements

This paper is partially supported by Natural Science Foundation of China (Grant No. 61572336, No. 61572335, No. 61632016, No. 61772356, No. 61802344, No. 61602400, No. 61702227), and Natural Science Research Project of Jiangsu Higher Education Institution (No. 18KJA520010, No. 17KJA520003), and a Hong Kong Polytechnic University start-up fund (project no. 1.9B0V), and a Project Funded by the Priority Academic Program Development of Jiangsu Higher Education Institutions.

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Authors and Affiliations

  1. Institute of Artificial Intelligence, School of Computer Science and Technology, Soochow University, Suzhou, China

    Wei Peng, An Liu & Zhixu Li

  2. Department of Computing, Macquarie University, Sydney, Australia

    Guanfeng Liu

  3. Department of Computing, The Hong Kong Polytechnic University, Hong Kong, China

    Qing Li

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  1. Wei Peng
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  2. An Liu
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  3. Zhixu Li
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  4. Guanfeng Liu
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  5. Qing Li
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Correspondence to An Liu.

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This article belongs to the Topical Collection: Special Issue on Web Information Management and Applications

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Peng, W., Liu, A., Li, Z. et al. User experience-driven secure task assignment in spatial crowdsourcing. World Wide Web 23, 2131–2151 (2020). https://doi.org/10.1007/s11280-019-00728-3

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