Toward Incentivizing Fog-Based Privacy-Preserving Mobile Crowdsensing in the Internet of Vehicles
Author | Sun, Gang |
Author | Sun, Siyu |
Author | Yu, Hongfang |
Author | Guizani, Mohsen |
Available date | 2022-12-12T14:57:19Z |
Publication Date | 2020-05-01 |
Publication Name | IEEE Internet of Things Journal |
Identifier | http://dx.doi.org/10.1109/JIOT.2019.2951410 |
Citation | Sun, G., Sun, S., Yu, H., & Guizani, M. (2019). Toward incentivizing fog-based privacy-preserving mobile crowdsensing in the Internet of Vehicles. IEEE Internet of Things Journal, 7(5), 4128-4142. |
Abstract | In the face of a massive number of vehicular users, a data collection paradigm based on vehicular crowdsensing requires an effective means of attracting participants. Thus, the incentive mechanisms play a key role in crowdsensing procedure design, inevitably leading to problems related to user privacy leakage. In this article, to reduce the risk of privacy leakage in the implementation of incentive mechanisms, we propose a fog computing-based crowdsensing architecture specialized for vehicular crowdsensing and corresponding privacy-preserving solutions for the processes of data reporting, reward issuing, and trust management. Authentication and encryption technologies, such as zero-knowledge verification, one-way hashing, partially blind signature authentication, and homomorphic encryption, are utilized to achieve our goals. Finally, efficiency improvements in both privacy preservation and network response are proven through analysis and simulations. |
Sponsor | This work was supported in part by the National Natural Science Foundation of China under Grant 61571098, in part by the Sichuan Science and Technology Program under Grant 2019YGF0206, and in part by the 111 Project under Grant B14039. |
Language | en |
Publisher | Institute of Electrical and Electronics Engineers Inc. |
Subject | Crowdsensing data aggregation fog computing Internet of Vehicles (IoV) privacy preservation |
Type | Article |
Pagination | 4128-4142 |
Issue Number | 5 |
Volume Number | 7 |
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