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Tendrils of Crime: Visualizing the Diffusion of Stolen Bitcoins
arXiv - CS - Computers and Society Pub Date : 2019-01-07 , DOI: arxiv-1901.01769
Mansoor Ahmed-Rengers, Ilia Shumailov, Ross Anderson

The first six months of 2018 saw cryptocurrency thefts of $761 million, and the technology is also the latest and greatest tool for money laundering. This increase in crime has caused both researchers and law enforcement to look for ways to trace criminal proceeds. Although tracing algorithms have improved recently, they still yield an enormous amount of data of which very few datapoints are relevant or interesting to investigators, let alone ordinary bitcoin owners interested in provenance. In this work we describe efforts to visualize relevant data on a blockchain. To accomplish this we come up with a graphical model to represent the stolen coins and then implement this using a variety of visualization techniques.

中文翻译:

犯罪的触须:可视化被盗比特币的扩散

2018 年前六个月发生了 7.61 亿美元的加密货币盗窃案,该技术也是洗钱的最新和最强大的工具。犯罪率的增加促使研究人员和执法部门寻找追踪犯罪所得的方法。尽管追踪算法最近有所改进,但它们仍然产生大量数据,其中很少有数据点与调查人员相关或感兴趣,更不用说对出处感兴趣的普通比特币所有者了。在这项工作中,我们描述了在区块链上可视化相关数据的努力。为了实现这一点,我们提出了一个图形模型来表示被盗硬币,然后使用各种可视化技术实现这一点。
更新日期:2020-03-16
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