Fraud Feature Boosting Mechanism and Spiral Oversampling Balancing Technique for Credit Card Fraud Detection

Author:

Ni Lina1ORCID,Li Jufeng1ORCID,Xu Huixin1,Wang Xiangbo1,Zhang Jinquan1ORCID

Affiliation:

1. College of Computer Science and Engineering, Shandong University of Science and Technology, Qingdao, China

Funder

National Science Foundation of Shandong Province

Humanity and Social Science Fund of the Ministry of Education

Open Project of Tongji University Embedded System and Service Computing of Ministry of Education of China

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Human-Computer Interaction,Social Sciences (miscellaneous),Modeling and Simulation

Cited by 17 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Credit card fraud detection based on federated graph learning;Expert Systems with Applications;2024-12

2. DBROA based Convolutional Auto Encoder for European Credit Card Fraud Detection;2024 Second International Conference on Data Science and Information System (ICDSIS);2024-05-17

3. Deep learning in fringe projection: A review;Neurocomputing;2024-05

4. An Overview of Clustering Algorithms for Credit Card Fraud Detection;2024 International Conference on Optimization Computing and Wireless Communication (ICOCWC);2024-01-29

5. Detecting Frauds and Payment Defaults on Credit Card Data Inherited With Imbalanced Class Distribution and Overlapping Class Problems: A Systematic Review;IEEE Access;2024

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