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Motif-aware temporal GCN for fraud detection in signed cryptocurrency trust networks. (arXiv:2211.13123v1 [cs.LG])
Nov. 24, 2022, 2:10 a.m. | Chong Mo, Song Li, Geoffrey K. F. Tso, Jiandong Zhou, Yiyan Qi, Mingjie Zhu
cs.CR updates on arXiv.org arxiv.org
Graph convolutional networks (GCNs) is a class of artificial neural networks
for processing data that can be represented as graphs. Since financial
transactions can naturally be constructed as graphs, GCNs are widely applied in
the financial industry, especially for financial fraud detection. In this
paper, we focus on fraud detection on cryptocurrency truct networks. In the
literature, most works focus on static networks. Whereas in this study, we
consider the evolving nature of cryptocurrency networks, and use local
structural as …
aware cryptocurrency detection fraud fraud detection networks temporal trust
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