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Unmasking Criminal Enterprises: An Analysis of Bitcoin Transactions

机译:揭露犯罪企业:对比特币交易的分析

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With the rise of cryptographic ransomware, Bitcoin has found a niche as the standard currency for ransoms. While Bitcoin is pseudonymous, it provides no guarantee of untraceability. As a result, another niche has arisen-Bitcoin money laundering. Hidden Markov Models (HMMs) have previously been used in a number of applications where traditional pattern recognition falls short. In this paper, HMMs are inferred from transactions in the public blockchain in an attempt to link users, events, and enterprises. We introduce a proof-of-concept algorithm to infer HMMs from the Bitcoin blockchain.
机译:随着加密勒索软件的兴起,比特币已经找到了利基市场,成为勒索软件的标准货币。虽然比特币是假名,但它不能保证不可追溯性。结果,另一个利基市场出现了-比特币洗钱。隐马尔可夫模型(HMM)先前已用于传统模式识别不足的许多应用中。在本文中,从公共区块链中的交易中推断出HMM,以试图链接用户,事件和企业。我们引入了概念验证算法来从比特币区块链中推断HMM。

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