Mining Bytecode Features of Smart Contracts to Detect PonziScheme on Blockchain  

作　　者：Xiajiong Shen Shuaimin Jiang Lei Zhang 

机构地区：[1]Henan Key Laboratory of Big Data Analysis and Processing,Henan University,Kaifeng,47500,China [2]Institute of Data and Knowledge Engineering,Henan University,Kaifeng,47500,China [3]School of Computer and Information Engineering,Henan University,Kaifeng,47500,China

出　　处：《Computer Modeling in Engineering & Sciences》2021年第6期1069-1085,共17页工程与科学中的计算机建模（英文）

基　　金：This work was supported by the Scientific and Technological Project of Henan Province(Grant No.202102310340);Foundation of University Young Key Teacher of Henan Province(Grant Nos.2019GGJS040,2020GGJS027);Key Scientific Research Projects of Colleges and Universities in Henan Province(Grant No.21A110005);National Natual Science Foundation of China(61701170).

摘　　要：The emergence of smart contracts has increased the attention of industry and academia to blockchain technology,which is tamper-proofing,decentralized,autonomous,and enables decentralized applications to operate in untrustworthy environments.However,these features of this technology are also easily exploited by unscrupulous individuals,a typical example of which is the Ponzi scheme in Ethereum.The negative effect of unscrupulous individuals writing Ponzi scheme-type smart contracts in Ethereum and then using these contracts to scam large amounts of money has been significant.To solve this problem,we propose a detection model for detecting Ponzi schemes in smart contracts using bytecode.In this model,our innovation is shown in two aspects:We first propose to use two bytes as one characteristic,which can quickly transform the bytecode into a high-dimensional matrix,and this matrix contains all the implied characteristics in the bytecode.Then,We innovatively transformed the Ponzi schemes detection into an anomaly detection problem.Finally,an anomaly detection algorithm is used to identify Ponzi schemes in smart contracts.Experimental results show that the proposed detection model can greatly improve the accuracy of the detection of the Ponzi scheme contracts.Moreover,the F1-score of this model can reach 0.88,which is far better than those of other traditional detection models.

关 键 词：Ponzi scheme blockchain security smart contracts anomaly detection 

分 类 号：TN9[电子电信—信息与通信工程]