【Author】
Framewala, Aman; Harale, Sarvesh; Khatal, Shreya; Patel, Dhiren; Busnel, Yann; Rajarajan, Muttukrishnan
【Source】2020 SEVENTH INTERNATIONAL CONFERENCE ON SOFTWARE DEFINED SYSTEMS (SDS)
【Abstract】While cryptocurrencies like Bitcoin have the potential to break traditional financial barriers, there are growing concerns about such currencies being used to fund illegal activities. Blockchain keeps the complete history of all transactions ever performed and each node replicates it. The humongous data it contains can be analyzed to gain useful insights about user transactions as well as the blockchain as a whole. In this paper, we propose an approach to parse and visualize the data of Bitcoin blockchain in a graph structure and carry out analysis that includes tracking and tracing, address clustering and entity tagging. We also try to find patterns in the data at a macro level to provide insights about the overall system. Thus, these efforts lead to foundation work for an analysis tool for getting insights on the coin flow of any financial system including cryptocurrencies.
【Keywords】Blockchain; bitcoin; tracking and tracing; address clustering; entity tagging
【摘要】虽然比特币等加密货币有可能打破传统的金融壁垒，但人们越来越担心这些货币被用于资助非法活动。区块链保存所有执行过的事务的完整历史，每个节点复制它。可以分析其中包含的大量数据，以获得关于用户事务和整个区块链的有用见解。在本文中，我们提出了一种以图结构解析和可视化比特币区块链数据的方法，并进行了跟踪跟踪、地址聚类和实体标记等分析。我们还试图在宏观级别上找到数据中的模式，以提供关于整个系统的见解。因此，这些努力导致了一种分析工具的基础工作，用于了解包括加密货币在内的任何金融系统的货币流。
【关键词】区块链;比特币;追踪和跟踪;解决聚类;实体标记
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