Privacy-Enhanced Crowdsourcing Data Trading based on Blockchain and Stackelberg Game

被引:5
|
作者
Huang, Zhiyuan [1 ]
Zheng, Jun [2 ]
Xiao, Mingjun [1 ]
机构
[1] Univ Sci & Technol China, Sch Comp Sci & Technol, Suzhou Inst Adv Study, Hefei, Peoples R China
[2] Univ Sci & Technol China, Sch Software Engn, Suzhou Inst Adv Study, Hefei, Anhui, Peoples R China
来源
2021 IEEE 18TH INTERNATIONAL CONFERENCE ON MOBILE AD HOC AND SMART SYSTEMS (MASS 2021) | 2021年
基金
中国国家自然科学基金;
关键词
Blockchain; Dynamic Game with Complete Information; Stackelberg Game; Homomorphic Watermarking;
D O I
10.1109/MASS52906.2021.00089
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Crowdsourcing Data Trading is a novel paradigm, where a platform can aggregate data collected by a group of mobile users. Traditional crowdsourcing data trading systems rely on trusted data trading brokers, which increase costs and cannot prevent collusion. What's more, they don't take of data quality and truthfulness into consideration concurrently. The emergence of blockchain and smart contracts brings in a decentralized scheme. However, the selection of the most effective providers remains challenging. To tackle these problems, we propose a dynamic-game-with-complete-information-and-Blockchain-based Crowdsourcing data Trading system (CBCT), which mainly includes a smart contracts called CBCToken. Firstly, we replace the data trading broker and adopt the Stackelberg Game, a Dynamic Game with complete information (DGC), to manage the selection of providers.Moreover, homomorphic watermarking technology is applied to protect the data copyright. Lastly, we deploy BCDToken on an Ethereum test network to demonstrate its practicability and significant performances.
引用
收藏
页码:621 / 626
页数:6
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