Lei Wang 等：Knowledge-Based Systems，2021（228）

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更新时间：2021-11-14 点击次数：2930

作者：Lei Wang, Hao Cheng, Zibin Zheng, Xiaohu Zhu

题名：Ponzi scheme detection via oversampling-based Long Short-Term Memory for smart contracts

期刊：Knowledge-Based Systems，2021（228）

摘要：based on oversampling-based Long Short-Term Memory (LSTM) for smart contracts in this paper. PSD-OL takes the contract account features and the contract code features together into consideration. Oversampling technique is utilized to fill the class-imbalanced Ponzi scheme smart contracts’ sample feature data. An LSTM model is trained by learning from the feature data for future Ponzi scheme detection. Experimental results conducted on the well-known XBlock dataset demonstrate the effectiveness of the proposed method.