Abstract
The prosperous development of Ethereum has bred many illegal activities by malefactors, such as Ponzi schemes, theft of funds from exchanges, and attacks on service providers. Aiming to expedite the realization of their gains, criminals will launder illicit money, making it as difficult as possible for security companies or agencies to recover those illicit funds. In this paper, we focus on a typical security event on Upbit exchange and explore the scale of the gang behind the security event. Specifically, We construct a rough suspicious money laundering transaction network by crawling downstream transactions of 815 accounts marked as Upbit hacks. Then, in order to refine a more accurate gang of Upbit hacks, we design a suspiciousness indicator for money laundering and modify an existing general risk assessment framework based on propagation models to assess the money laundering risk of accounts. Based on the risks, we acquire an accurate gang for Upbit hacks. In the end, we find that the size of the Upbit hack gang is much bigger than we thought. We also present several interesting analyses of the Upbit hack gang.
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Acknowledgements
The work described in this paper is supported by the National Natural Science Foundation of China (61973325).
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Fu, Q., Lin, D., Wu, J. (2023). Bigger Than We Thought: The Upbit Hack Gang. In: Pardalos, P., Kotsireas, I., Knottenbelt, W.J., Leonardos, S. (eds) Mathematical Research for Blockchain Economy. MARBLE 2023. Lecture Notes in Operations Research. Springer, Cham. https://doi.org/10.1007/978-3-031-48731-6_11
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DOI: https://doi.org/10.1007/978-3-031-48731-6_11
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