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检测 Uniswap 上的诈骗代币与跑路行为

文章 arXiv papers · 作者: Pengcheng Xia et al.
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总结

本研究使用交易数据考察 Uniswap V2 上的欺诈代币，分析其交易活动并识别疑似诈骗。检测方法结合基于关联的启发式规则与机器学习技术，旨在标记可能涉及跑路的代币、资金池及关联地址。研究还报告称，一些诈骗合约包含意在欺骗或限制用户的机制。

作者识别出一万多个疑似诈骗代币，并估计其数据集中约一半已上架代币属于诈骗。作者还报告了相互勾结的地址、潜在受害者和估算的诈骗利润。这些发现针对研究所分析的 Uniswap V2 活动及其分类方法，并非对所有去中心化交易所或后续时期的普遍估计。文中将早期检测列为该方法的一种潜在用途，但此处未提供模型评估或误报率详情。

核心观点

  • 本研究分析 Uniswap V2 交易数据，以识别疑似诈骗代币和资金池并刻画其特征。
  • 检测方法结合基于关联的启发式规则与机器学习。
  • 作者报告称，许多已识别的诈骗采用跑路手法，部分合约还包含欺骗性机制。
  • 分析描述了数据集中的勾结地址，并估算受害者人数和诈骗所得。
  • 报告的诈骗占比和利润取决于研究数据及分类方法。

标签

加密资产去中心化金融机器学习链上数据市场微观结构
全文
# Trade or Trick? Detecting and Characterizing Scam Tokens on Uniswap Decentralized Exchange


# Trade or Trick? Detecting and Characterizing Scam Tokens on Uniswap Decentralized Exchange









The prosperity of the cryptocurrency ecosystem drives the need for digital asset trading platforms. Beyond centralized exchanges (CEXs), decentralized exchanges (DEXs) are introduced to allow users to trade cryptocurrency without transferring the custody of their digital assets to the middlemen, thus eliminating the security and privacy issues of traditional CEX. Uniswap, as the most prominent cryptocurrency DEX, is continuing to attract scammers, with fraudulent cryptocurrencies flooding in the ecosystem. In this paper, we take the first step to detect and characterize scam tokens on Uniswap. We first collect all the transactions related to Uniswap V2 exchange and investigate the landscape of cryptocurrency trading on Uniswap from different perspectives. Then, we propose an accurate approach for flagging scam tokens on Uniswap based on a guilt-by-association heuristic and a machine-learning powered technique. We have identified over 10K scam tokens listed on Uniswap, which suggests that roughly 50% of the tokens listed on Uniswap are scam tokens. All the scam tokens and liquidity pools are created specialized for the "rug pull" scams, and some scam tokens have embedded tricks and backdoors in the smart contracts. We further observe that thousands of collusion addresses help carry out the scams in league with the scam token/pool creators. The scammers have gained a profit of at least \$16 million from 39,762 potential victims. Our observations in this paper suggest the urgency to identify and stop scams in the decentralized finance ecosystem, and our approach can act as a whistleblower that identifies scam tokens at their early stages.

在遵守原作品许可的前提下，附作者信息全文展示。 许可协议: abstract CC0

此摘要由 Stratmill 研究智能体根据原文撰写，并非原文副本。