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A Bitcoin Transaction Network Analytic Method for Future Blockchain Forensic Investigation 6.pdf (868.41 kB)

A Bitcoin Transaction Network Analytic Method for Future Blockchain Forensic Investigation

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journal contribution
posted on 2020-02-26, 14:46 authored by Yan Wu, Fang Tao, Lu Liu, Jiayan Gu, John Panneerselvam, Rongbo Zhu, Mohammad Nasir Shahzad
Popular Blockchain-based cryptocurrencies, like Bitcoin, are increasingly being used maliciously to launder money on the dark Web. In order to trace and analyze suspected Bitcoin transactions and addresses, address clustering methods and Bitcoin flow analysis methods are gaining attention recently. However, existing methods only focus on Bitcoin addresses and flow, and neglect other important information, such as transaction structure and behavior features. In order to exploit all useful features of transactions, this paper proposes a Bitcoin transaction network analytic method for facilitating Blockchain forensic investigation based on an extended safe Petri Net. The structural features and dynamic semantics of Petri net are used in our proposed model to define the static and dynamic features of Bitcoin transactions. Nineteen features have been identified to define Bitcoin transaction patterns for analyzing and finding suspected addresses. Bitcoin gene has been embedded into the Petri net transitions to trace and analyze Bitcoin flow accurately. Finally, marginal distribution analysis of Bitcoin transaction features and data visualization techniques are used to eliminate some false positive samples further and to improve the accuracy of identifying suspected addresses. The proposed Bitcoin transaction network analytic method provides a reliable forensic investigation model along with a prototype platform which is beneficial for financial security. The efficiency of our proposed method is empirically verified based on a real-life case study analysis.

Funding

UK-Jiangsu 20-20 Initiative Pump Priming; 10.13039/501100004608-Natural Science Foundation of Jiangsu Province; 10.13039/501100001809-National Natural Science Funds of China; 10.13039/501100013290-National Key Research and Development Program of China; Postdoc Funds of China and Jiangsu Province; UK-Jiangsu 20-20 World Class University Initiative programme

History

Citation

IEEE Transactions on Network Science and Engineering,DOI: 10.1109/TNSE.2020.2970113

Author affiliation

Department of Informatics

Version

  • AM (Accepted Manuscript)

Published in

IEEE Transactions on Network Science and Engineering

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

issn

2327-4697

Copyright date

2020

Available date

2020-01-28

Publisher version

https://ieeexplore.ieee.org/document/8972613

Language

en

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