Scholarlink

The anonymity and decentralization features of cryptocurrencies have facilitated complex on-chain money laundering activities, as exemplified by the Bybit attack in February 2025, where hackers exploited a multi-signature vulnerability to steal approximately $1.4 billion worth of ETH. This study constructs a multidimensional framework utilizing labeled data, transaction network structures, and cross-chain path analysis to investigate money laundering behaviors on the Ethereum network. Through graph model analysis of a large-scale network (11000+ nodes and 14000+ edges), we explore account attributes, transaction topology, and fund flows, systematically dissecting money laundering strategies. Key findings reveal that money laundering accounts exhibit unique patterns throughout the laundering cycle: short lifespan, high transaction frequency, small-value transfers, decentralized cross-chain dispersal, and the utilization of coin mixing pathways. This research provides essential methodologies and empirical references for cryptocurrency regulation, risk account monitoring, and blockchain forensic audits.

错误：搜索内容不能为空，请输入英文关键词
错误：关键词超出字数限制，请精简
高级检索

Understanding Ethereum Money Laundering via Transaction Network Analysis: A Case Study of the Bybit Incident

  • 会议论文

  • 发表日期：

    2026年

查看全文
  • Yanli Ding,
  • Dan Lin,
  • Weipeng Zou,
  • Bozhao Zhang,
  • Jun Wang,
  • Ting Chen,
  • Letian Sha,
  • Jiajing Wu

摘要

The anonymity and decentralization features of cryptocurrencies have facilitated complex on-chain money laundering activities, as exemplified by the Bybit attack in February 2025, where hackers exploited a multi-signature vulnerability to steal approximately $1.4 billion worth of ETH. This study constructs a multidimensional framework utilizing labeled data, transaction network structures, and cross-chain path analysis to investigate money laundering behaviors on the Ethereum network. Through graph model analysis of a large-scale network (11000+ nodes and 14000+ edges), we explore account attributes, transaction topology, and fund flows, systematically dissecting money laundering strategies. Key findings reveal that money laundering accounts exhibit unique patterns throughout the laundering cycle: short lifespan, high transaction frequency, small-value transfers, decentralized cross-chain dispersal, and the utilization of coin mixing pathways. This research provides essential methodologies and empirical references for cryptocurrency regulation, risk account monitoring, and blockchain forensic audits.