Motif-aware temporal GCN for fraud detection in signed cryptocurrency trust networks

@article{Mo2022MotifawareTG,
  title={Motif-aware temporal GCN for fraud detection in signed cryptocurrency trust networks},
  author={Chongji Mo and Song Li and Geoffrey Kwok Fai Tso and Jiandong Zhou and Yiyan Qi and Mingjie Zhu},
  journal={ArXiv},
  year={2022},
  volume={abs/2211.13123}
}
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…