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
Citation
ZHAO, Bowen; LIU, Ximeng; CHEN, Wei-Neng; LIANG, Wei; ZHANG, Xinglin; and DENG, Robert H..
PRICE: Privacy and reliability-aware real-time incentive system for crowdsensing. (2021). IEEE Internet of Things Journal. 8, (24), 17584-17595.
Available at: https://ink.library.smu.edu.sg/sis_research/6932
Additional URL
https://doi.org/10.1109/JIOT.2021.3081596