DocumentCode :
2424964
Title :
An Optimized SVM Model for Detection of Fraudulent Online Credit Card Transactions
Author :
Xu Wei ; Liu Yuan
Author_Institution :
Sch. of Inf. & Safety Eng., Zhongnan Univ. of Econ. & Law, Wuhan, China
fYear :
2012
fDate :
20-21 Oct. 2012
Firstpage :
14
Lastpage :
17
Abstract :
In order to identify the credit card fraudulent transactions, in this paper we propose an optimized SVM model for detection of fraudulent online credit card model. The model use non-liner SVM and RBF for the sparse transaction data, and use grid algorithm to determine the optional combination of parameters. There dose not exist local minima problem, the curse of dimensionality, small sample size problem and nonlinear problem. In the experiment of the simulation environment, the proposed model performance better than other models which verifies its feasibility.
Keywords :
credit transactions; fraud; radial basis function networks; support vector machines; RBF; fraudulent online credit card transactions; grid algorithm; nonlinear problem; nonliner SVM; optimized SVM model; small sample size problem; sparse transaction data; Business; Credit cards; Data models; Educational institutions; Kernel; Support vector machines; Training; SVM; credit card; fraud detection;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Management of e-Commerce and e-Government (ICMeCG), 2012 International Conference on
Conference_Location :
Beijing
Print_ISBN :
978-1-4673-2943-9
Type :
conf
DOI :
10.1109/ICMeCG.2012.39
Filename :
6374872
Link To Document :
بازگشت