【Author】
Zhang, Zongyang; Yin, Jiayuan; Hu, Bin; Gao, Ting; Li, Weihan; Wu, Qianhong; Liu, Jianwei
【Source】COMPUTERS & SECURITY
【Abstract】With the proliferation of cryptocurrency, many automated cross-ledger trading platforms were set up. These platforms introduce new challenges in tracing the money flows and getting evidence of illicit behaviors. Yousaf, Kappos, and Meiklejohn (USENIX Security'19) are the first to link the cross-ledger money flows. However, their scheme is only applicable to one platform and requires real-time monitoring to obtain transaction lists. To extend the cross-ledger tracing techniques, we design CLTRACER, a general and non-real-time framework based on address relationships. In our implementation, we discover more than 1.7 million cross-ledger transactions on ShapeShift. We further design a combined heuristic of cross-ledger clustering and obtain 24,925 cross-ledger clusters. Two methods are then proposed to analyze the false positives, and the biggest clusters are inspected to understand their behaviors. Finally, we study the deposit and withdrawal mechanisms of 19 other trading platforms and adapt our techniques to nine of them. Our work could provide insights to the supervising authority in collecting evidence of illicit cross-ledger trading behaviors. (C) 2021 Elsevier Ltd. All rights reserved.
【Keywords】Cross-ledger tracing, Address relationship, Clustering; Cryptocurrency, Blockchain
【标题】CLTracer:基于地址关系的交叉分类账跟踪框架
【摘要】随着加密货币的普及，许多自动化的跨账本交易平台应运而生。这些平台在追踪资金流动和获取非法行为证据方面带来了新的挑战。Yousaf, Kappos和Meiklejohn (USENIX Security’19)是第一个将交叉账本资金流动联系起来的人。但是，他们的方案只适用于一个平台，需要实时监控才能获得交易列表。为了扩展跨账本跟踪技术，我们设计了CLTRACER，一个基于地址关系的通用非实时框架。在我们的实现中，我们发现超过170万的交叉分类账交易在shapesshift。我们进一步设计了一个跨分类账聚类的联合启发式算法，得到24,925个跨分类账聚类。然后提出了两种方法来分析假阳性，并检查最大的聚类来了解它们的行为。最后，我们研究了其他19个交易平台的存取款机制，并将我们的技术应用于其中9个平台。我们的工作可以为监管部门收集非法交叉账本交易行为的证据提供见解。(C) 2021年爱思唯尔有限公司保留所有权利。
【关键词】跨账本跟踪;地址关系;聚类;加密货币,区块链
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