论文标题
如何剥离一百万：验证和扩展比特币簇
How to Peel a Million: Validating and Expanding Bitcoin Clusters
论文作者
论文摘要
比特币的定义特征之一以及从中得出的数千个加密货币是全球可见的交易分类帐。虽然比特币使用假名作为隐藏参与者身份的一种方式，但一长串的研究表明，比特币不是匿名的。这也许是通过开发聚类启发式方法来说明的，这反过来又产生了跟踪比特币流动的能力，因为它们是从一个实体发送到另一个实体的。 在本文中，我们设计了一种新的启发式方法，旨在跟踪某种类型的流动，称为果皮链，代表了同一实体执行的许多交易。在这样做的过程中，我们将这些交易及其相关的假名集中在一起。然后，我们使用这种启发式式来验证和扩大现有的聚类启发式方法的结果。我们还开发了一种基于机器学习的验证方法，并使用基地真实数据集评估我们的所有方法并将其与最新的状态进行比较。最终，我们的目标不仅是启用更强大的跟踪技术，而且还引起人们对这些系统匿名限制的关注。
One of the defining features of Bitcoin and the thousands of cryptocurrencies that have been derived from it is a globally visible transaction ledger. While Bitcoin uses pseudonyms as a way to hide the identity of its participants, a long line of research has demonstrated that Bitcoin is not anonymous. This has been perhaps best exemplified by the development of clustering heuristics, which have in turn given rise to the ability to track the flow of bitcoins as they are sent from one entity to another. In this paper, we design a new heuristic that is designed to track a certain type of flow, called a peel chain, that represents many transactions performed by the same entity; in doing this, we implicitly cluster these transactions and their associated pseudonyms together. We then use this heuristic to both validate and expand the results of existing clustering heuristics. We also develop a machine learning-based validation method and, using a ground-truth dataset, evaluate all our approaches and compare them with the state of the art. Ultimately, our goal is to not only enable more powerful tracking techniques but also call attention to the limits of anonymity in these systems.
