Mihui Kim, Younghee Park, Pankaj Balasaheb Dighe, Journal of Information Processing Systems Vol. 15, No. 5, pp. 1036-1054, Oct. 2019  

10.3745/JIPS.01.0045
Keywords: Incentive Method, Internet of Things (IoT) Model, Mobile Crowd Sensing (MCS), Privacy-Preserving, Using Group Signature
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Abstract

Recently, concomitant with a surge in numbers of Internet of Things (IoT) devices with various sensors, mobile crowdsensing (MCS) has provided a new business model for IoT. For example, a person can share road traffic pictures taken with their smartphone via a cloud computing system and the MCS data can provide benefits to other consumers. In this service model, to encourage people to actively engage in sensing activities and to voluntarily share their sensing data, providing appropriate incentives is very important. However, the sensing data from personal devices can be sensitive to privacy, and thus the privacy issue can suppress data sharing. Therefore, the development of an appropriate privacy protection system is essential for successful MCS. In this study, we address this problem due to the conflicting objectives of privacy preservation and incentive payment. We propose a privacy-preserving mechanism that protects identity and location privacy of sensing users through an on-demand incentive payment and group signatures methods. Subsequently, we apply the proposed mechanism to one example of MCS—an intelligent parking system—and demonstrate the feasibility and efficiency of our mechanism through emulation.

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