Forensic Analysis of Bitcoin Transactions

Y. Wu, Anthony Luo, Dianxiang Xu
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引用次数: 9

Abstract

Bitcoin [1] as a popular digital currency has been a target of theft and other illegal activities. Key to the forensic investigation is to identify bitcoin addresses involved in bitcoin transfers. This paper presents a framework, FABT, for forensic analysis of bitcoin transactions by identifying suspicious bitcoin addresses. It formalizes the clues of a given case as transaction patterns defined over a comprehensive set of features. FABT converts the bitcoin transaction data into a formal model, called Bitcoin Transaction Net (BTN). The traverse of all bitcoin transactions in the order of their occurrences is captured by the firing sequence of all transitions in the BTN. We have applied FABT to identify suspicious addresses in the Mt.Gox case. A subgroup of the suspicious addresses has been found to share many characteristics about the received/transferred amount, number of transactions, and time intervals.
比特币交易的取证分析
比特币[1]作为一种流行的数字货币,一直是盗窃和其他非法活动的目标。法医调查的关键是识别涉及比特币转账的比特币地址。本文提出了一个框架,FABT,通过识别可疑的比特币地址来对比特币交易进行取证分析。它将给定情况的线索形式化为在一组全面的特性上定义的事务模式。FABT将比特币交易数据转换成一个正式的模型,称为比特币交易网(bitcoin transaction Net, BTN)。所有比特币交易按其发生顺序的遍历由BTN中所有转换的触发序列捕获。我们已经使用FABT来识别Mt.Gox案件中的可疑地址。发现可疑地址的子组在接收/转账金额、交易数量和时间间隔方面具有许多共同特征。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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