It’s All Connected: Detecting Phishing Transaction Records on Ethereum Using Link Prediction

Chidimma Opara, Yingke Chen, Bo Wei

Research output: Chapter in Book/Report/Conference proceedingConference contribution

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Digital currencies are increasingly being used on platforms for virtual transactions, such as Ethereum, owing to new financial innovations. As these platforms are anonymous and easy to use, they are perfect places for phishing scams to grow. Unlike traditional phishing detection approaches that aim to distinguish phishing websites and emails using their HTML content and URLs, phishing attacks on Ethereum focus on detecting phishing addresses by analyzing the transaction relationships on the virtual transaction platform. This study proposes a link prediction framework for detecting phishing transactions on the Ethereum platform using 12 local network-based features extracted from the Ether receiving and initiating addresses. The framework was trained and tested on over 280,000 verified phishing and legitimate transaction records. Experimental results indicate that the proposed framework with a LightGBM classifier provides a high recall of 89% and an AUC score of 93%.
Original languageEnglish
Title of host publicationHybrid Intelligent Systems
Subtitle of host publication22nd International Conference on Hybrid Intelligent Systems (HIS 2022), December 13–15, 2022
EditorsAjith Abraham, Tzung-Pei Hong, Ketan Kotecha, Kun Ma, Pooja Manghirmalani Mishra, Niketa Gandhi
ISBN (Electronic)9783031274091
ISBN (Print)9783031274084
Publication statusPublished - 25 May 2023
Event22nd International Conference on Hybrid Intelligent Systems: On the World Wide Web - Online
Duration: 13 Dec 202215 Dec 2022

Publication series

NameLecture Notes in Networks and Systems
ISSN (Print)2367-3370
ISSN (Electronic)2367-3389


Conference22nd International Conference on Hybrid Intelligent Systems
Abbreviated titleHIS 2022
Internet address


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