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fraud detection on payment transaction networks via graph computing and visualization

High Technology Letters 2020年第3期26卷 253-261页

作者： Sun Quan Tang Tao Zheng Jianbin Lin Jiale Zhao Jintao Liu Hongbao School of Computer Science Fudan UniversityShanghai 200433P.R.China China UnionPay Research Institute of Electronic payment Shanghai 201201P.R.China School of Electronic Information and Electrical Engineering Shanghai Jiao Tong UniversityShanghai 200240P.R.China

With the fast development of Internet technology,more and more payments are fulfilled by mobile Apps in an electrical way which significantly saves time and efforts for *** a change has benefited a large number of individual users as well as merchants,and a few major players for payment service have emerged in *** a result,the payment service competition becomes even fierce,and various promotion activities have been launched for attracting more users by the payment service *** this paper,the problem focused on is fraud payment detection,which in fact has been a major concern for the providers who spend a significant amount of money to popularize their payment *** paper tries the graph computing-based visualization to the behavior of transactions occuring between the individual users and ***,a network analysisbased pipeline has been *** consists of the following key components:transaction network building based on daily records aggregation;transaction network filtering based on edge and node removal;transaction network decomposition by community detection;detected transaction community *** proposed approach is verified on the real-world dataset collected from the major player in the payment market in Asia and the qualitative results show the efficiency of the method.

关键词： payment fraud detection graph computing graph embedding machine learning

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