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Ethereum Fraud Detection with Heterogeneous Graph Neural Networks. (arXiv:2203.12363v1 [cs.LG])
March 24, 2022, 1:20 a.m. | Hiroki Kanezashi, Toyotaro Suzumura, Xin Liu, Takahiro Hirofuchi
cs.CR updates on arXiv.org arxiv.org
While transactions with cryptocurrencies such as Ethereum are becoming more
prevalent, fraud and other criminal transactions are not uncommon. Graph
analysis algorithms and machine learning techniques detect suspicious
transactions that lead to phishing in large transaction networks. Many graph
neural network (GNN) models have been proposed to apply deep learning
techniques to graph structures. Although there is research on phishing
detection using GNN models in the Ethereum transaction network, models that
address the scale of the number of vertices and …
More from arxiv.org / cs.CR updates on arXiv.org
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