research-article

SIEGE: Self-Supervised Incremental Deep Graph Learning for Ethereum Phishing Scam Detection

Authors:

Fengyuan XuAuthors Info & Claims

MM '23: Proceedings of the 31st ACM International Conference on Multimedia

Pages 8881 - 8890

https://doi.org/10.1145/3581783.3612461

Published: 27 October 2023 Publication History

Abstract

The phishing scams pose a serious threat to the ecosystem of Ethereum which is one of the largest blockchains in the world. Such a type of cyberattack recently has caused losses of millions of dollars. In this paper, we propose a Self-supervised IncrEmental deep Graph lEarning (SIEGE) model, for the phishing scam detection problem on Ethereum. To overcome the data scalability challenge, we propose splitting the original Ethereum transaction data and constructing transaction graphs for each split. Confronted with the minimal labeled data available, we resort to graph-based self-supervised learning. We design a spatial pretext task to learn high-quality node embeddings inside a single graph split, as well as an incremental learning paradigm and a temporal pretext task to facilitate information flow between different graph splits. To evaluate the effectiveness of SIEGE, we gather a real-world dataset consisting of six-month Ethereum transaction records. The results demonstrate that our model consistently outperforms baseline approaches in both transductive and inductive settings.

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Cited By

Chen ZHuang JLiu SLong H(2024)Multiscale Feature Fusion and Graph Convolutional Network for Detecting Ethereum Phishing ScamsElectronics10.3390/electronics1306101213:6(1012)Online publication date: 7-Mar-2024
https://doi.org/10.3390/electronics13061012
Pan BStakhanova NZhu Z(2024)EtherShield: Time-interval Analysis for Detection of Malicious Behavior on EthereumACM Transactions on Internet Technology10.1145/363351424:1(1-30)Online publication date: 8-Jan-2024
https://dl.acm.org/doi/10.1145/3633514
Zhang JSui HSun XGe CZhou LSusilo W(2024) GrabPhisher : Phishing Scams Detection in Ethereum via Temporally Evolving GNNs IEEE Transactions on Services Computing10.1109/TSC.2024.3411449(1-15)Online publication date: 2024
https://doi.org/10.1109/TSC.2024.3411449
Show More Cited By

Index Terms

SIEGE: Self-Supervised Incremental Deep Graph Learning for Ethereum Phishing Scam Detection
1. Applied computing
  1. Electronic commerce
    1. Digital cash
2. Computing methodologies
  1. Artificial intelligence

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cover image ACM Conferences

MM '23: Proceedings of the 31st ACM International Conference on Multimedia

October 2023

9913 pages

ISBN:9798400701085

DOI:10.1145/3581783

General Chairs:
Abdulmotaleb El Saddik
University of Ottawa, Canada & MBZUAI, UAE
,
Tao Mei
HiDream.ai, China
,
Rita Cucchiara
University of Modena and Reggio Emilia, Italy
,
Program Chairs:
Marco Bertini
University of Florence, Italy
,
Diana Patricia Tobon Vallejo
Unversidad de Medellin, Colombia
,
Pradeep K. Atrey
University at Albany, State University of New York, USA
,
M. Shamim Hossain
M. Shamim Hossain (King Saud University, KSA

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Published: 27 October 2023

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MM '23: The 31st ACM International Conference on Multimedia

October 29 - November 3, 2023

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Cited By

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https://doi.org/10.3390/electronics13061012
Pan BStakhanova NZhu Z(2024)EtherShield: Time-interval Analysis for Detection of Malicious Behavior on EthereumACM Transactions on Internet Technology10.1145/363351424:1(1-30)Online publication date: 8-Jan-2024
https://dl.acm.org/doi/10.1145/3633514
Zhang JSui HSun XGe CZhou LSusilo W(2024) GrabPhisher : Phishing Scams Detection in Ethereum via Temporally Evolving GNNs IEEE Transactions on Services Computing10.1109/TSC.2024.3411449(1-15)Online publication date: 2024
https://doi.org/10.1109/TSC.2024.3411449
Yang JYu WWu JLin DWu ZZheng Z(2024)2DynEthNet: A Two-Dimensional Streaming Framework for Ethereum Phishing Scam DetectionIEEE Transactions on Information Forensics and Security10.1109/TIFS.2024.348429619(9924-9937)Online publication date: 2024
https://doi.org/10.1109/TIFS.2024.3484296
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Hou WCui BLi R(2022)Detecting Phishing Scams on Ethereum Using Graph Convolutional Networks with Conditional Random Field2022 IEEE 24th Int Conf on High Performance Computing & Communications; 8th Int Conf on Data Science & Systems; 20th Int Conf on Smart City; 8th Int Conf on Dependability in Sensor, Cloud & Big Data Systems & Application (HPCC/DSS/SmartCity/DependSys)10.1109/HPCC-DSS-SmartCity-DependSys57074.2022.00230(1495-1500)Online publication date: Dec-2022
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