基于模型堆叠的以太坊钓鱼诈骗账户识别方法
Ethereum phishing scam account identification based on model stacking
陈伟利 1叶明顺 1唐明董 1郑子彬2
作者信息
- 1. 广东外语外贸大学信息科学与技术学院,广东广州 510006
- 2. 中山大学软件工程学院,广东珠海 528478
- 折叠
摘要
近年来,钓鱼诈骗已成为区块链平台中不可忽视的欺诈类型,对用户金融安全构成了重大威胁.为了解决这一问题,本文提出了一种基于区块链交易的网络钓鱼账户检测框架,并以以太坊为例验证了其有效性.具体而言,该框架通过引入数据样本过滤规则来缓解数据不均衡性以及减少计算量,采用级联特征抽取方法以提取有效特征,并基于模型堆叠构建集成分类算法建立模型以识别以太坊上的钓鱼诈骗账户.实验结果表明,该框架能够有效地识别以太坊上的钓鱼诈骗账户,具有一定的实际应用价值.
Abstract
In recent years,phishing scams have become a type of fraud that cannot be ignored in blockchain platforms,posing a major threat to users'financial security.To solve this problem,this paper proposes a framework for phishing account detection based on blockchain transactions,and verifies its effectiveness by taking ethereum as an example.Specif-ically,the framework alleviates data imbalances and reduces computational effort by introducing sample filtering rules,adopts a cascading feature extraction method to extract valid features,and builds an ensemble classification algorithm based on model stacking to identify phishing accounts.The experimental results show that the framework can effectively identify phishing fraud accounts on ethereum and has certain practical application value.
关键词
区块链/以太坊/钓鱼诈骗/模型堆叠Key words
blockchain/ethereum/phishing scam/model stacking引用本文复制引用
基金项目
国家重点研发计划项目(2020YFB1006002)
国家自然科学基金面上项目(61976061)
广东省基础与应用基础研究基金项目(2021A1515011939)
出版年
2024
国家科技期刊平台
NSTL
万方数据