论文标题
示踪剂：基于图形的可扩展交易跟踪，用于基于帐户的区块链交易系统
TRacer: Scalable Graph-based Transaction Tracing for Account-based Blockchain Trading Systems
论文作者
论文摘要
诸如骗局和黑客之类的安全事件已成为对区块链生态系统健康的主要威胁，每年为区块链用户造成数十亿美元的损失。为了揭示假名区块链帐户背后的实际实体并从大规模交易数据中恢复了被盗的资金，最近努力努力追踪最近在区块链中的非法资金流动。但是，大多数基于启发式和污点分析的当前追踪方法在普遍性，有效性和效率方面都有局限性。本文将区块链事务记录为区块链事务图，并将区块链交易跟踪作为图形搜索任务进行建模。我们提出了Tracer，这是一种可扩展的交易跟踪工具，用于基于帐户的区块链。为了推断图形搜索过程中的帐户之间的相关性，我们根据定向，加权，时间和多关系区块链交易图开发了一种新型的个性化Pagerank方法。据我们所知，Tracer是基于帐户的区块链中的第一个智能交易跟踪工具，可以处理分散融资（DEFI）中的复杂交易行动。实验结果和理论分析证明，示踪剂可以以低成本有效地完成交易跟踪任务。所有示踪剂的代码均可在GitHub上找到。
Security incidents such as scams and hacks, have become a major threat to the health of the blockchain ecosystem, causing billions of dollars in losses each year for blockchain users. To reveal the real-world entities behind the pseudonymous blockchain account and recover the stolen funds from the massive transaction data, much effort has been devoted to tracing the flow of illicit funds in blockchains recently. However, most current tracing approaches based on heuristics and taint analysis have limitations in terms of universality, effectiveness, and efficiency. This paper models the blockchain transaction records as a blockchain transaction graph and tackles blockchain transaction tracing as a graph searching task. We propose TRacer, a scalable transaction tracing tool for account-based blockchains. To infer the relevance between accounts during graph searching, we develop a novel personalized PageRank method in TRacer based on the directed, weighted, temporal, and multi-relationship blockchain transaction graphs. To the best of our knowledge, TRacer is the first intelligent transaction tracing tool in account-based blockchains that can handle complex transaction actions in decentralized finance (DeFi). Experimental results and theoretical analysis prove that TRacer can complete the transaction tracing task effectively at a low cost. All codes of TRacer are available at GitHub.
