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Sensors 2017, 17(9), 2024; https://doi.org/10.3390/s17092024

Incentivizing Verifiable Privacy-Protection Mechanisms for Offline Crowdsensing Applications

College of Computer Science and Technology, Nanjing University of Aeronautics and Astronautics, Nanjing 211106, China
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Received: 29 July 2017 / Revised: 26 August 2017 / Accepted: 31 August 2017 / Published: 4 September 2017
(This article belongs to the Section Sensor Networks)
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Abstract

Incentive mechanisms of crowdsensing have recently been intensively explored. Most of these mechanisms mainly focus on the standard economical goals like truthfulness and utility maximization. However, enormous privacy and security challenges need to be faced directly in real-life environments, such as cost privacies. In this paper, we investigate offline verifiable privacy-protection crowdsensing issues. We firstly present a general verifiable privacy-protection incentive mechanism for the offline homogeneous and heterogeneous sensing job model. In addition, we also propose a more complex verifiable privacy-protection incentive mechanism for the offline submodular sensing job model. The two mechanisms not only explore the private protection issues of users and platform, but also ensure the verifiable correctness of payments between platform and users. Finally, we demonstrate that the two mechanisms satisfy privacy-protection, verifiable correctness of payments and the same revenue as the generic one without privacy protection. Our experiments also validate that the two mechanisms are both scalable and efficient, and applicable for mobile devices in crowdsensing applications based on auctions, where the main incentive for the user is the remuneration. View Full-Text
Keywords: mobile crowdsensing; privacy protection; verifiable correctness; incentive mechanisms mobile crowdsensing; privacy protection; verifiable correctness; incentive mechanisms
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).
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Sun, J.; Liu, N. Incentivizing Verifiable Privacy-Protection Mechanisms for Offline Crowdsensing Applications. Sensors 2017, 17, 2024.

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