Location Privacy-Preserving Mobile Crowd Sensing with Anonymous Reputation

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Abstract

In this paper, we give a location privacy-preserving solution for the mobile crowd sensing (MCS) system. The solution makes use of the blind signature technique for anonymous authentication and allows a mobile user to participate in the MCS for certain times set in the registration. Furthermore, we introduce a concept of anonymous reputation for mobile users on the basis of the blind signature technique as well. An anonymous reputation can be referred by the MCS platform when assigning tasks to a mobile user and can be upgraded or downgraded by the MCS platform, depending on the quality of reports submitted by the mobile user. For the security analysis, we provide security proofs for our solution on the basis of our formal definitions for anonymity, unlinkability and unforgeability for MCS. The performance analysis and experiments have shown that our solution is more efficient than existing solutions for MCS based on the blind signature technique.

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Yi, X., Lam, K. Y., Bertino, E., & Rao, F. Y. (2019). Location Privacy-Preserving Mobile Crowd Sensing with Anonymous Reputation. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 11736 LNCS, pp. 387–411). Springer. https://doi.org/10.1007/978-3-030-29962-0_19

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