A Multiperspective Fraud Detection Method for Multiparticipant E-Commerce Transactions

Author:

Yu Wangyang1ORCID,Wang Yadi1ORCID,Liu Lu2ORCID,An Yisheng3,Yuan Bo2ORCID,Panneerselvam John2ORCID

Affiliation:

1. Key Laboratory of Modern Teaching Technology, Ministry of Education, and the School of Computer Science, Shaanxi Normal University, Xi’an, China

2. School of Computing and Mathematical Sciences, University of Leicester, Leicester, U.K.

3. School of Information Engineering, Chang’an University, Xi’an, China

Funder

Natural Science Foundation of Shaanxi Province

National Natural Science Foundation of China

Fundamental Research Funds for the Central Universities

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

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

Cited by 6 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. Supply chain fraud prediction with machine learning and artificial intelligence;International Journal of Production Research;2024-06-07

2. Machine Learning-Powered Fraud Detection & Prevention: A Comprehensive Implementation;2024 2nd International Conference on Intelligent Data Communication Technologies and Internet of Things (IDCIoT);2024-01-04

3. Modeling and Analyzing Logic Vulnerabilities of E-Commerce Systems at the Design Phase;IEEE Transactions on Systems, Man, and Cybernetics: Systems;2023-12

4. Grading and Calculation of Synchronic Distance in Petri Nets for Trustworthy Modeling and analyzing;2023 IEEE 22nd International Conference on Trust, Security and Privacy in Computing and Communications (TrustCom);2023-11-01

5. A cost-sensitive ensemble deep forest approach for extremely imbalanced credit fraud detection;Quantitative Finance;2023-07-26

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