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Sensitive Data Encoding in Blockchain-Based P2P Trading System

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Pervasive Systems, Algorithms and Networks (I-SPAN 2019)

Abstract

With the rapid development and application of information technology, blockchain technology has become one of the important means to promote the integration of the real economy and the digital economy. However, for the application of blockchain technology in P2P transactions, existing technology provide no reasonable framework. This paper proposes a framework of P2P trading system based on blockchain technology. The proposed framework can ensure the security of data and establish trust among entities. It can also reduce business divergence and costs. In order to prevent the leak of sensitive data in the trading process, we also propose an encoding method of sensitive data. This guarantees the data from being stolen or tampered. The calculations on matrixes of this method can use the computing resources of all nodes in the blockchain to calculate in parallel, and then summarize the results. This makes full use of massive GPU resources in the blockchain, and makes the calculation valuable. The proposed framework and method realize transactions without the intervention of a centralized platform. It not only establishes the trust relationship among entities well, but also realizes safe and reliable P2P transactions.

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Acknowledgements

This work was supported in part by the National Key Research & Development Program 2018AAA0100800, the Key Research and Development Program of Jiangsu under grant BE2018004-04; it was also supported by the Fundamental Research Funds for the Central Universities under Grant 2019B22214, and by the State Key Laboratory of Integrated Management of Pest Insects and Rodents under grant IPM1914.

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Correspondence to Xin Su .

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Liu, Y., Su, X., Xu, N., Yao, X. (2019). Sensitive Data Encoding in Blockchain-Based P2P Trading System. In: Esposito, C., Hong, J., Choo, KK. (eds) Pervasive Systems, Algorithms and Networks. I-SPAN 2019. Communications in Computer and Information Science, vol 1080. Springer, Cham. https://doi.org/10.1007/978-3-030-30143-9_9

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  • DOI: https://doi.org/10.1007/978-3-030-30143-9_9

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-30142-2

  • Online ISBN: 978-3-030-30143-9

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