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Commodity-Tra: A Traceable Transaction Scheme Based on FISCO BCOS

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Security and Privacy in Social Networks and Big Data (SocialSec 2022)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 1663))

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Abstract

In recent years, because online shopping has the advantages of abundant products, easy selection, fast door-to-door delivery, and timely information feedback, people are more and more fond of online shopping compared to physical store shopping. With the wave of online shopping, the use of commodity transaction systems has become more and more widespread. However, the traditional commodity transaction system generally adopts centralized management and cannot be traced, which cannot guarantee the openness and transparency of commodity source information, and cannot well meet the commodity purchasing needs of consumers. In order to solve the above problems, we use blockchain technology to propose Commodity-Tra: a traceable transaction scheme based on FISCO BCOS platform. The system Commodity-Tra is suitable for the scene of commodity traceability, and can provide consumers with true and accurate commodity traceability information, which can better meet consumers’ purchasing needs. In addition, we analyze the impact of the traceability on page response time from the aspects of network bandwidth and virtual machine memory, respectively. The experimental results show that the page response time only increases by 2.8 s on average. Therefore, Commodity-Tra is capable of providing the traceability function without affecting users’ experience.

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Author information

Authors and Affiliations

  1. School of Computer Science, Qufu Normal University, Jining, China

    Chunmei Li, Zheng Wei, Jun Ge, Mingyue Zhang & Yun Fang

  2. School of Cyberspace Security, Shandong University of Political Science and Law, Jinan, China

    Lei Shang

Authors
  1. Chunmei Li
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  2. Lei Shang
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  3. Zheng Wei
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  4. Jun Ge
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  5. Mingyue Zhang
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  6. Yun Fang
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Corresponding author

Correspondence to Yun Fang .

Editor information

Editors and Affiliations

  1. Xidian University, Xi’an, China

    Xiaofeng Chen

  2. Fujian Normal University, Fuzhou, China

    Xinyi Huang

  3. Wrocław University of Science and Technology, Wrocław, Poland

    Mirosław Kutyłowski

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Li, C., Shang, L., Wei, Z., Ge, J., Zhang, M., Fang, Y. (2022). Commodity-Tra: A Traceable Transaction Scheme Based on FISCO BCOS. In: Chen, X., Huang, X., Kutyłowski, M. (eds) Security and Privacy in Social Networks and Big Data. SocialSec 2022. Communications in Computer and Information Science, vol 1663. Springer, Singapore. https://doi.org/10.1007/978-981-19-7242-3_17

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  • DOI: https://doi.org/10.1007/978-981-19-7242-3_17

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-19-7241-6

  • Online ISBN: 978-981-19-7242-3

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