【Author】
Zheng, Baokun; Zhu, Liehuang; Shen, Meng; Du, Xiaojiang; Yang, Jing; Gao, Feng; Li, Yandong; Zhang, Chuan; Liu, Sheng; Yin, Shu
【Source】MOBILE NETWORKS AND MANAGEMENT (MONAMI 2017)
【Abstract】Since the generation of Bitcoin, it has gained attention of all sectors of the society. Law breakers committed crimes by utilizing the anonymous characteristics of Bitcoin. Recently, how to track malicious Bitcoin transactions has been proposed and studied. To address the challenge, existing solutions have limitations in accuracy, comprehensiveness, and efficiency. In this paper, we study Bitcoin blackmail virus WannaCry event incurred in May 2017. The three Bitcoin addresses disclosed in this blackmail event are only restricted to receivers accepting Bitcoin sent by victims, and no further transaction has been found yet. Therefore, we acquire and verify experimental data by example of similar Bitcoin blackmail virus CryptoLocker occurred in 2013. We focus on how to track malicious Bitcoin transactions, and adopt a new heuristic clustering method to acquire incidence relation between addresses of Bitcoin and improved Louvain clustering algorithm to further acquire incidence relation between users. In addition, through a lot of experiments, we compare the performance of our algorithm with another related work. The new heuristic clustering method can improve comprehensiveness and accuracy of the results. The improved Louvain clustering algorithm can increase working efficiency. Specifically, we propose a method acquiring internal relationship between Bitcoin addresses and users, so as to make Bitcoin transaction deanonymisation possible, and realize a better utilization of Bitcoin in the future.
【Keywords】Bitcoin; Blockchain; Incidence relation; Cluster
【摘要】比特币自诞生以来，受到了社会各界的广泛关注。不法分子利用比特币的匿名性进行犯罪。近年来，如何跟踪恶意比特币交易已经被提出和研究。为了应对这一挑战，现有的解决方案在准确性、全面性和效率方面都有局限性。本文以2017年5月发生的比特币勒索病毒WannaCry事件为研究对象。此次勒索事件中披露的三个比特币地址仅限于接收受害者发送的比特币的收件人，目前尚未发现进一步的交易。因此，我们以2013年发生的类似比特币勒索病毒CryptoLocker为例，获取并验证实验数据。重点研究如何跟踪恶意比特币交易，采用一种新的启发式聚类方法获取比特币地址之间的关联关系，并采用改进的Louvain聚类算法进一步获取用户之间的关联关系。另外，通过大量的实验，我们将我们的算法与其他相关的算法进行了性能比较。新的启发式聚类方法提高了结果的全面性和准确性。改进的Louvain聚类算法可以提高工作效率。具体来说，我们提出了一种获取比特币地址与用户之间内部关系的方法，从而使比特币交易去匿名化成为可能，实现比特币在未来更好的利用。
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