Investigating the impact of structural and temporal behaviors in Ethereum phishing users detection

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外文摘要：The recent surge of Ethereum in prominence has made it an attractive target for various kinds of crypto crimes.Phishing scams,for example,are an increasingly prevalent cybercrime in which malicious users attempt to steal funds from a user's crypto wallet.This research investigates the effects of network architectural features as well as the temporal aspects of user activities on the performance of detecting phishing users on the Ethereum transaction network.We employ traditional machine learning algorithms to evaluate our model on real-world Ethereum transaction data.The experimental results demonstrate that our proposed features identify phishing accounts efficiently and outperform the baseline models by 4％in Recall and 5％in F1-score.

外文关键词：

BlockchainCryptocurrencyEthereumPhishing scamMachine learning

作者：

Medhasree Ghosh、Dyuti Ghosh、Raju Halder、Joydeep Chandra

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作者单位：

Indian Institute of Technology,Patna,Bihta,Bihar,801106,India

University of Calcutta,Kolkata,West Bengal,700073,India

基金：

National Informatics Centre,MeitY,Government of India

项目编号：

1/2021-22GIA

出版年：

2023

DOI：

10.1016/j.bcra.2023.100153

区块链研究(英文)

ISSN：

年,卷(期)：2023.4(4)

参考文献量52