Bitcoin is the first and highest valued cryptocurrency that stores transactions in a publicly distributed ledger called the blockchain. Understanding the activity and behavior of Bitcoin actors is a crucial research topic as they are pseudonymous in the transaction network. In this article, we propose a method based on taint analysis to extract taint flows --dynamic networks representing the sequence of Bitcoins transferred from an initial source to other actors until dissolution. Then, we apply graph embedding methods to characterize taint flows. We evaluate our embedding method with taint flows from top mining pools and show that it can classify mining pools with high accuracy. We also found that taint flows from the same period show high similarity. Our work proves that tracing the money flows can be a promising approach to classifying source actors and characterizing different money flow patterns

翻译：比特币是第一个和最高价值的加密货币,它把交易储存在一个公开发行的分类账中,称为“链链”。了解比特币行为者的活动和行为是一个至关重要的研究课题,因为它们在交易网络中是假名的。在本篇文章中,我们提议了一种基于污物分析的方法,以提取污物流 -- -- 代表从原始来源转移到其他行为者直至解体的比特币序列的动态网络。然后,我们运用图层嵌入方法来说明污物流的特点。我们用从顶层采矿池中渗入的污物流来评估我们嵌入的方法,并表明它能够对采矿池进行高度精确的分类。我们还发现,同一时期的污物流显示出高度相似性。我们的工作证明,追踪资金流可以是一种很有希望的方法,对来源行为者进行分类,并描述不同的资金流动模式。