CrowdHB: A Decentralized Location Privacy-Preserving Crowdsensing System Based on a Hybrid Blockchain Network

【Author】 Zou, Shihong; Xi, Jinwen; Xu, Guoai; Zhang, Miao; Lu, Yueming

【Source】IEEE INTERNET OF THINGS JOURNAL

【影响因子】10.238

【Abstract】With the advent of the Internet of Things (IoT), crowdsensing, as a new emerging application of the IoT that employs ubiquitous mobile users with smartphones for data collection and processing, has further deepened our knowledge. However, the problems of the current crowdsensing systems regarding system security, user privacy, and user payment (UP) raise serious privacy and security concerns, which affect participants' adoption of the system. The Blockchain technology allows for nondeterministic multiple parties to interact with each other anonymously in a network that is not fully trusted. In this article, we propose a new decentralized crowdsensing system, called CrowdHB. Unlike other blockchain-based crowdsensing systems, CrowdHB adopts a hybrid blockchain architecture and uses smart contracts to achieve location privacy preservation and ensure data quality while improving the system performance. Furthermore, to optimize task assignments to mobile users, we propose a location privacy-preserving optimization mechanism (LPPOM) and the approach of consistency optimization (ACO) to achieve a tradeoff between user privacy and system performance. The extensive experimental results show that the proposed CrowdHB outperforms the other crowdsensing systems in terms of task success rate and performance for a large number of mobile users and tasks.

【Keywords】Crowdsensing; Privacy; Blockchain; Task analysis; Security; Internet of Things; Optimization; Consistency; crowdsensing; hybrid blockchain; Internet of Things (IoT); location privacy preservation

【发表时间】2022 AUG 15

【收录时间】2022-08-28

【文献类型】理论模型

【主题类别】

区块链技术-协同技术-隐私计算