Blockchain provides a decentralized environment for applications and information systems in various fields. It is an innovative revolution for the traditional Internet. However, without proper regulatory mechanisms, the blockchain technology has gradually become a hotbed of criminal activities, such as Ponzi scheme that brings huge economic losses to people. To maintain the security of the blockchain system, the machine learning technique, which can detect smart Ponzi schemes automatically has recently received extensive attention. However, the existing method has potential target leakage and prediction shift problems when dealing with category features and calculating gradient estimates. Besides, they also ignore the imbalance and repeatability of smart contracts, which often causes the model to overfit. In this paper, we introduce a novel method for detecting smart Ponzi schemes in blockchain. Specifically, we first expand the dataset of smart Ponzi schemes and eliminate the unbalanced dataset via data enhancement. Then, we leverage ordered target statistics (TS) to handle the category features of smart contract without target leakage. Finally, we propose an anti-leakage smart Ponzi schemes detection (Al-SPSD) model based on the idea of ordered boosting. Experimental results show that our proposal outperforms the competitive methods and is effective and reliable in detecting smart Ponzi schemes. Al-SPSD achieves 96% F-score and detects about 1,621 active smart Ponzi schemes in Ethereum.

区块链为各个领域的应用程序和信息系统提供了去中心化的环境。这是传统互联网的一次创新革命。但是，没有适当的监管机制，区块链技术已逐渐成为犯罪活动的温床，例如庞氏骗局给人们带来了巨大的经济损失。为了维护区块链系统的安全性，可以自动检测智能庞氏骗局的机器学习技术最近受到了广泛关注。但是，现有方法在处理类别特征和计算梯度估计时存在潜在的目标泄漏和预测偏移问题。此外，他们还忽略了智能合约的不平衡性和可重复性，这通常会导致模型过拟合。在本文中，我们介绍了一种用于检测区块链中智能庞氏骗局的新方法。具体来说，我们首先扩展智能庞氏骗局的数据集，并通过数据增强消除不平衡的数据集。然后，我们利用有序目标统计（TS）来处理智能合约的类别特征，而不会造成目标泄漏。最后，基于有序升压的思想，提出了一种防泄漏智能庞氏骗局检测模型。实验结果表明，我们的建议优于竞争方法，并且在检测智能庞氏骗局方面是有效和可靠的。Al-SPSD的F分数达到96％，并在以太坊中检测到约1,621个活跃的智能庞氏骗局。我们利用有序目标统计（TS）来处理智能合约的类别功能，而不会导致目标泄漏。最后，基于有序升压的思想，提出了一种防泄漏智能庞氏骗局检测模型。实验结果表明，我们的建议优于竞争方法，并且在检测智能庞氏骗局方面是有效和可靠的。Al-SPSD的F分数达到96％，并在以太坊中检测到约1,621个活跃的智能庞氏骗局。我们利用有序目标统计（TS）来处理智能合约的类别功能，而不会导致目标泄漏。最后，基于有序升压的思想，提出了一种防泄漏智能庞氏骗局检测模型。实验结果表明，我们的建议优于竞争方法，并且在检测智能庞氏骗局方面是有效和可靠的。Al-SPSD的F分数达到96％，并在以太坊中检测到约1,621个活跃的智能庞氏骗局。