Supervised Machine (SVM) Learning for Credit Card Fraud Detection
|International Journal of Engineering Trends and Technology (IJETT)||
|© 2014 by IJETT Journal|
|Year of Publication : 2014|
|Authors : Sitaram patel , Sunita Gond
Sitaram patel , Sunita Gond."Supervised Machine (SVM) Learning for Credit Card Fraud Detection ", International Journal of Engineering Trends and Technology(IJETT), 8(3),137-139 February 2014. ISSN:2231-5381. www.ijettjournal.org. published by seventh sense research group
The growth of e commerce increases the money transaction via electronic network which is designed for hassle free fast & easy money transaction. The facility involves greater risk of misuse for fraud one of them is credit card fraud which can happen by many types as by stolen card, by INTERNET hackers who can hack your system & get important information about your card or by information leakage during the transaction. Several researchers have proposed their work for credit card fraud detection by characterizing the user spending profile. In this thesis we are proposing the SVM (Support Vector Machine) based method with multiple kernel involvement which also includes several fields of user profile instead of only spending profile. The simulation result shows improvement in TP (true positive), TN (true negative) rate, & also decreases the FP (false positive) & FN (false negative) rate.
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MATLAB, e-commerce, online banking, classification support vector machine