Blockchain-based Fair and Decentralized Data Trading Model

Author:

Li Taotao123,Li Dequan3,Wang Mingsheng12

Affiliation:

1. State Key Laboratory of Information Security, Institute of Information Engineering, Chinese Academy of Sciences, Beijing, 100093 China

2. School of Cyber Security, University of Chinese Academy of Sciences, Beijing, 100049 China

3. Beijing Engineering Research Center of Space-ground Integration Information Security, Spacestar co. Limited, Beijing, 100080 China

Abstract

Abstract Data is a kind of important asset in the digital economy and is driving the rise of data markets. Meanwhile, data markets promote data trading efficiently and improve the utilization of data. However, several challenges about data trading need to be addressed. Here, we resolve these challenges via our blockchain-based fair and decentralized data trading model. Disputes about data correctness is settled by the decentralized arbitration mechanism in our model. To ensure the fairness of data trading, we integrate a sale contract and a deterministic public-key encryption algorithm. The decentralization feature of blockchain cuts off the single-point failure for the data trading platform. In addition, we prove that the proposed protocol achieves the desirable security properties that a secure data trading protocol should have. Moreover, utilizing the smart contract in Solidity and program in Java, we implement our model and then evaluate its performance.

Publisher

Oxford University Press (OUP)

Subject

General Computer Science

Reference44 articles.

1. A survey on internet of things: architecture, enabling technologies, security and privacy, and applications;Lin;IEEE Internet Things J,2017

2. Internet of things and big data analytics for smart and connected communities;Sun;IEEE Access,2016

3. Research directions for the internet of things;Stankovic;IEEE Internet Things J,2014

4. Design and realization of winternet: from net of things to internet of things;Wu;TCPS,2016

5. On binary decomposition based privacy-preserving aggregation schemes in real-time monitoring systems;Yang;IEEE Trans. Parallel Distrib. Syst.,2016

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