CrowdBLPS: A Blockchain-Based Location-Privacy-Preserving Mobile Crowdsensing System

With the popularization of intelligent terminals, especially current trends, such as "Industrie 4.0" and the Internet of Things, mobile crowdsensing is becoming one of the promising applications built on smart devices in mobile networks. However, the existing mobile crowdsensing models are...

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Bibliographic Details
Published in:IEEE transactions on industrial informatics 2020-06, Vol.16 (6), p.4206-4218
Main Authors: Zou, Shihong, Xi, Jinwen, Wang, Honggang, Xu, Guoai
Format: Article
Language:English
Subjects:
Blockchain
Contracts
Cryptography
Data integrity
Electronic devices
Fraud
Industrie 4.0
Internet of Things
Internet of Things (IoT)
location privacy preserving
mobile crowdsensing (MCS)
Network reliability
Privacy
reliability
Sensors
Task analysis
Wireless networks
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Summary:With the popularization of intelligent terminals, especially current trends, such as "Industrie 4.0" and the Internet of Things, mobile crowdsensing is becoming one of the promising applications built on smart devices in mobile networks. However, the existing mobile crowdsensing models are mostly based on a centralized platform, which is not fully trusted in reality and results in the existence of fraud and other security problems. Furthermore, the data quality collected through crowdsensing is varied, and the location privacy is difficult to guarantee, especially at the worker selection stage. To solve these two problems, an effective blockchain-based location-privacy-preserving crowdsensing model, CrowdBLPS, is proposed in this article. First, the idea of a blockchain is introduced into this model. The decentralized structure and the consensus approach are applied to realize the nonrepudiation and nontampering of information. Second, to improve the data sensing quality and protect worker privacy, a two-stage approach, including the preregistration stage and the final selection stage, is proposed. Finally, we further implement a prototype on the Ethereum public testing network, and the experimental results show the feasibility, availability, and reliability of CrowdBLPS.
ISSN:1551-3203
1941-0050
DOI:10.1109/TII.2019.2957791