PRICE: Privacy and reliability-aware real-time incentive system for crowdsensing

Publication Type

Journal Article

Publication Date

12-2021

Abstract

Crowdsensing is regarded as a critical component of the Internet of Things (IoT) and has been widely applied in smart city services. Incentive mechanism design, data reliability evaluation, and privacy preservation are the research focuses of crowdsensing. However, most existing incentive mechanisms fail to protect data privacy and evaluate data credibility, simultaneously. Moreover, traditional privacy and reliability-aware incentive schemes are usually challenging to realize real-time reward distribution. To this end, we first point out a single-time slice of failure problem in real-time incentive mechanisms and propose a two-layer truth discovery model (TLTD) to resolve this problem. Then, a reliability-aware real-time incentive mechanism (RRIM) is designed based on the proposed TLTD. In order to evaluate data reliability in a privacy-preserving manner, we build a privacy-preserving truth discovery solution ( PriTD ) based on secure computation protocols. Finally, our proposed system [privacy and reliability-aware real-time incentive system for crowdsensing (PRICE)] integrating the aforementioned protocols realizes real-time reward distribution, data reliability evaluation, and privacy protection, simultaneously. Theoretical analysis and experimental evaluations on a synthetic and real-world data set demonstrate the feasibility and efficiency of the proposed PRICE.

Keywords

Crowdsensing, Incentive mechanism, Privacy preservation, Secure computation, Truth discovery

Discipline

Information Security

Research Areas

Cybersecurity

Publication

IEEE Internet of Things Journal

Volume

8

Issue

24

First Page

17584

Last Page

17595

ISSN

2327-4662

Identifier

10.1109/JIOT.2021.3081596

Publisher

Institute of Electrical and Electronics Engineers

Additional URL

https://doi.org/10.1109/JIOT.2021.3081596

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