Research Area: Blockchain Technology
With the rapid development of embedded smart devices, a new data collection paradigm, mobile crowd-sensing (MCS), has been proposed. MCS allows individuals from the crowd to act as sensors and contribute their observation data. However, existing MCS systems are mostly based on third-party platforms, and there is no guarantee that a center is completely credible. In addition, security and privacy issues should not be ignored. During MCS’ execution, the participants’ various information and truth value are usually exposed, and the computation related to data privacy cannot be verified. In this paper, we integrate the blockchain into the MCS scenario to design a blockchain based privacy-preserving quality control mechanism, which prevents data from being tampered with, and denied, ensuring that the reward is distributed fairly. In the new system, we propose a privacy preserving participant selection scheme and the result can be verified (i.e., security against malicious node) without any third-party arbiter. Finally, considering the issues with sensing data privacy and efficiency in the truth discovery process, we propose a new privacy-aware crowdsensing design with iterative truth discovery based on rational secure multi-party computation. The experimental results show that compared to the prior result, the proposed solutions are highly practical and facilitate quality control without violating the participant’s privacy.
Keywords:
Author(s) Name: Jian An; Zhenxing Wang; Xin He; Xiaolin Gui; Jindong Cheng; Ruowei Gui
Journal name: IEEE/ACM Transactions on Networking
Conferrence name:
Publisher name: IEEE
DOI: 10.1109/TNET.2022.3141582
Volume Information: Volume: 30, Issue: 3, June 2022, Page(s): 1352 - 136
