{"title":"SCScan: A SVM-based Scanning System for Vulnerabilities in Blockchain Smart Contracts","authors":"Xiaohan Hao, Wei Ren, Wenwen Zheng, Tianqing Zhu","doi":"10.1109/TrustCom50675.2020.00221","DOIUrl":null,"url":null,"abstract":"The application of blockchain has moved beyond cryptocurrencies, to applications such as credentialing and smart contracts. The smart contract allows ones to achieve fair exchange for values without relying on a centralized entity. However, as the smart contract can be automatically executed with token transfers, an attacker can seek to exploit vulnerabilities in smart contracts for illicit profits. Thus, this paper proposes a support vector machine (SVM)-based scanning system for vulnerabilities on smart contracts. Our evaluation on Ethereum demonstrate that we achieve a identification rate of over 90% based on several popular attacks.","PeriodicalId":221956,"journal":{"name":"2020 IEEE 19th International Conference on Trust, Security and Privacy in Computing and Communications (TrustCom)","volume":"4 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2020-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"4","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2020 IEEE 19th International Conference on Trust, Security and Privacy in Computing and Communications (TrustCom)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/TrustCom50675.2020.00221","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 4
Abstract
The application of blockchain has moved beyond cryptocurrencies, to applications such as credentialing and smart contracts. The smart contract allows ones to achieve fair exchange for values without relying on a centralized entity. However, as the smart contract can be automatically executed with token transfers, an attacker can seek to exploit vulnerabilities in smart contracts for illicit profits. Thus, this paper proposes a support vector machine (SVM)-based scanning system for vulnerabilities on smart contracts. Our evaluation on Ethereum demonstrate that we achieve a identification rate of over 90% based on several popular attacks.