Research Area: Blockchain Technology
Worker selection in crowdsensing plays an important role in the quality control of sensing services. The majority of existing studies on worker selection {color{red}were} largely dependent on a trusted centralized server, which might suffer from single point of failure, the lack of transparency and so on. Some works recently proposed blockchain-based crowdsensing, which {color{red}utilized} reputation values stored on blockchains to select trusted workers. However, the transparency of blockchains enables attackers to effectively infer private information about workers by the disclosure of their reputation values. In this paper, we {color{red}proposed} the TrustWorker, a trustworthy and privacy-preserving worker selection scheme for blockchain-based crowdsensing. By taking the advantages of blockchains such as decentralization, transparency and immutability, our TrustWorker {color{red}could} make the worker selection process trustworthy. To protect workers reputation privacy in our TrustWorker, we {color{red}adopted} a deterministic encryption algorithm to encrypt reputation values and then {color{red}selected} the top N workers in the light of secret minimum heapsort scheme. Finally, we theoretically {color{red}analyzed} the effectiveness and efficiency of our TrustWorker, and then {color{red}conducted} a series of experiments. The theoretical analysis and experiment results demonstrate that our TrustWorker can achieve trustworthy worker selection, while ensuring the workers privacy and the high quality of sensing services.
Keywords:
Author(s) Name: Sheng Gao; Xiuhua Chen; Jianming Zhu; Xuewen Dong; Jianfeng Ma
Journal name: IEEE Transactions on Services Computing ( Early Access )
Conferrence name:
Publisher name: IEEE
DOI: 10.1109/TSC.2021.3103938
Volume Information: Page(s): 1 - 1
