In recent years, money laundering has become much easier to be achieved but more challenging to be detected than before, which has enormous adversary effects on finance, military, and other related fields. In the real-time scenario, every money laundering case has a unique structure in terms of transactions. It is not sufficient to detect suspicious behavior by just following the probability theory, where usually the thresholds are given by experts. Since the crime of money laundering is more prevalent and sophisticated nowadays, it will increase the complexity of the detection if the accounts with the personal information are combined with the form of the transaction topology. Hence, the graph topology analysis could be used for antimoney laundering tools. This article proposes eight common topologies based on coupling and connection from simple to much more complicated structures to solve various kinds of problems concerning money laundering in the real world. Moreover, we also propose an efficient solution based on graph and subgraph isomorphism and distance measurement to detect money laundering behavior. In this way, the detection of money laundering behavior will be more efficient and effective for various situations while referencing the proposed eight topological structures.

中文翻译：

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基于耦合和连接的洗钱常见拓扑检测高效解决方案

近年来，洗钱变得比以前更容易实现，但检测起来却更具挑战性，这对金融，军事和其他相关领域产生了巨大的不利影响。在实时场景中，每个洗钱案件在交易方面都有其独特的结构。仅根据概率理论（通常由专家给出阈值）来检测可疑行为是不够的。由于当今洗钱犯罪更为普遍和复杂，如果将具有个人信息的帐户与交易拓扑的形式结合起来，它将增加检测的复杂性。因此，图拓扑分析可用于反洗钱工具。本文提出了八种基于从简单结构到复杂得多的结构的耦合和连接的常见拓扑，以解决现实世界中与洗钱有关的各种问题。此外，我们还提出了一种基于图和子图同构以及距离测量来检测洗钱行为的有效解决方案。这样，在参考所提出的八种拓扑结构的同时，洗钱行为的检测将在各种情况下更加有效。