【Author】
Chen, Weili; Zheng, Zibin; Cui, Jiahui; Ngai, Edith; Zheng, Peilin; Zhou, Yuren
【Source】WEB CONFERENCE 2018: PROCEEDINGS OF THE WORLD WIDE WEB CONFERENCE (WWW2018)
【Abstract】Blockchain technology becomes increasingly popular. It also attracts scams, for example, Ponzi scheme, a classic fraud, has been found making a notable amount of money on Blockchain, which has a very negative impact. To help dealing with this issue, this paper proposes an approach to detect Ponzi schemes on blockchain by using data mining and machine learning methods. By verifying smart contracts on Ethereum, we first extract features from user accounts and operation codes of the smart contracts and then build a classification model to detect latent Ponzi schemes implemented as smart contracts. The experimental results show that the proposed approach can achieve high accuracy for practical use. More importantly, the approach can be used to detect Ponzi schemes even at the moment of its creation. By using the proposed approach, we estimate that there are more than 400 Ponzi schemes running on Ethereum. Based on these results, we propose to build a uniform platform to evaluate and monitor every created smart contract for early warning of scams.
【Keywords】Blockchain; Smart Contract; Ponzi Schemes; Ethereum
【标题】检测以太坊上的庞氏骗局:迈向更健康的区块链技术
【摘要】区块链技术变得越来越流行。它也吸引诈骗，例如，庞氏骗局，一个典型的诈骗，已经被发现在区块链上赚了大量的钱，这有非常负面的影响。为了解决这一问题，本文提出了一种利用数据挖掘和机器学习方法检测区块链上的庞氏骗局的方法。通过验证以太坊上的智能合约，我们首先从用户账户和智能合约的操作代码中提取特征，然后构建分类模型，检测作为智能合约实现的潜在庞氏骗局。实验结果表明，该方法具有较高的精度，可用于实际应用。更重要的是，这种方法可以用来检测庞氏骗局，甚至在它产生的那一刻。通过使用提出的方法，我们估计以太坊上运行着400多个庞氏骗局。基于这些结果，我们建议建立一个统一的平台来评估和监控每一个创建的智能合约，用于诈骗预警。
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