Knowledge Commons of Institute of Automation,CAS
A Graph-Based Semi-Supervised Fraud Detection Framework | |
Rongrong Jing1,2; Xiaolong Zheng1,2,3; Hu Tian1,2; Xingwei Zhang1,2; Weiyun Chen4; Dash Desheng Wu2; Daniel Dajun Zeng1,2,3 | |
2021-05 | |
会议名称 | 2019 4th IEEE International Conference on Cybernetics (Cybconf) |
会议日期 | 2021-05-31 |
会议地点 | Beijing, China |
摘要 | —Credit card payment has become one of the most commonly used consumption methods in modern society, yet risks of fraud transactions using credit cards also increased. Numerous methods have been proposed for credit card fraud detection during past decades. However, most of the existing frameworks mainly focus on directly processing structured data. While they lack inner relations between features of raw descriptions for credit owners, this could lead to information deficiency. Therefore, we proposed a graph-based semisupervised fraud detection framework. In this work, the structured dataset is translated to graph format through the sample similarity in order to improve the effect of label propagation on the graph. We further adopt the GraphSAGE algorithm which has been demonstrated to show excellent performance on node classification tasks. Experimental results on the real-world dataset show that our graph-based model can outperform state-of-the-art baselines. We argue that our model could be extended to other classification tasks using structured data. |
收录类别 | EI |
资助项目 | Ministry of Health of China[2017ZX10303401-002] ; Ministry of Health of China[2017YFC1200302] ; National Natural Science Foundation of China[71472175] ; National Natural Science Foundation of China[71602184] ; National Natural Science Foundation of China (NSFC)[71621002] |
文献类型 | 会议论文 |
条目标识符 | http://ir.ia.ac.cn/handle/173211/48804 |
专题 | 多模态人工智能系统全国重点实验室_互联网大数据与信息安全 |
通讯作者 | Xiaolong Zheng |
作者单位 | 1.Institute of Automation, Chinese Academy of Sciences 2.University of Chinese Academy of Sciences 3.Shenzhen Artificial Intelligence and Data Science Institute (Longhua) 4.School of Management, Huazhong University of Science & Technology |
第一作者单位 | 中国科学院自动化研究所 |
通讯作者单位 | 中国科学院自动化研究所 |
推荐引用方式 GB/T 7714 | Rongrong Jing,Xiaolong Zheng,Hu Tian,et al. A Graph-Based Semi-Supervised Fraud Detection Framework[C],2021. |
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文件名称/大小 | 文献类型 | 版本类型 | 开放类型 | 使用许可 | ||
A_Graph-Based_Semi-S(1227KB) | 会议论文 | 开放获取 | CC BY-NC-SA | 浏览 下载 |
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