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Transaction Deanonymization in Large-Scale Bitcoin Systems via Propagation Pattern Analysis

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Security and Privacy in Digital Economy (SPDE 2020)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 1268))

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Abstract

Bitcoin is a digital currency payment system, which bases on the property of decentralization and anonymization of Blockchain. Researches on transaction deanonymization for the Bitcoin system may not associate anonymous transactions with the IP addresses (physical identity) of the originator accurately and may consume network resources excessively. In this paper, we propose an approach to obtain the originating transactions through analyzing the propagation information. We calculate a pattern matching score by combining the propagation pattern extraction and the node weight assignment. Through carrying out the experiments in the real Bitcoin system, we effectively match the originating transactions with the target node, which reaches a precision of 81.3% and is 30% higher than the state-of-the-art method.

This work is partially supported by Key-Area Research and Development Program of Guangdong Province (No. 2019B010137003), Zhejiang Lab Open Fund with No. 2020AA3AB04, National Natural Science Foundation of China under Grants 61972039 and 61872041, and Beijing Natural Science Foundation under Grant 4192050.

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Author information

Authors and Affiliations

  1. School of Computer Science, Beijing Institute of Technology, Beijing, 100081, China

    Meng Shen, Junxian Duan, Ning Shang & Liehuang Zhu

  2. Cyberspace Security Research Center, Peng Cheng Laboratory, Shenzhen, 518000, China

    Meng Shen

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  1. Meng Shen
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  2. Junxian Duan
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  3. Ning Shang
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  4. Liehuang Zhu
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Corresponding author

Correspondence to Meng Shen .

Editor information

Editors and Affiliations

  1. University of Technology Sydney, Sydney, NSW, Australia

    Shui Yu

  2. IBM Zurich Research Laboratory, Zurich, Switzerland

    Peter Mueller

  3. Ningbo University, Ningbo, China

    Jiangbo Qian

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Shen, M., Duan, J., Shang, N., Zhu, L. (2020). Transaction Deanonymization in Large-Scale Bitcoin Systems via Propagation Pattern Analysis. In: Yu, S., Mueller, P., Qian, J. (eds) Security and Privacy in Digital Economy. SPDE 2020. Communications in Computer and Information Science, vol 1268. Springer, Singapore. https://doi.org/10.1007/978-981-15-9129-7_45

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  • DOI: https://doi.org/10.1007/978-981-15-9129-7_45

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-15-9128-0

  • Online ISBN: 978-981-15-9129-7

  • eBook Packages: Computer ScienceComputer Science (R0)

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