期刊
INFORMATION PROCESSING & MANAGEMENT
卷 58, 期 4, 页码 -出版社
ELSEVIER SCI LTD
DOI: 10.1016/j.ipm.2021.102587
关键词
Blockchain; Smart Ponzi scheme; Ethereum; Machine learning; Data mining
资金
- Open Foundation of State Key Laboratory of Cryptology, China [MMKFKT201617]
- National Key Research and Development Program of China, China [2018YFB0204301]
Blockchain provides a decentralized environment for applications and information systems in various fields, but without proper regulation, it can become a breeding ground for criminal activities such as Ponzi schemes. Machine learning techniques are being used to automatically detect smart Ponzi schemes in order to maintain security, but existing methods may have leakage and overfitting issues. A new method, Al-SPSD, has been proposed in this paper to address these challenges and has shown to outperform competitive methods in detecting smart Ponzi schemes in Ethereum.
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.
作者
我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。
推荐
暂无数据