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A Machine Learning Approach for Detection of Fraud Based on SVM


Affiliations
1 Department of Computer Science and Information Technology, SSSIST, Sehore, M.P., India
2 Aligarh Muslim University, Aligarh, India
 

The growth of e-commerce increases the money transaction via electronic network which is designed for hassle free fast & easy money transaction but the facility involves greater risk of misuse of facility for fraud one of them is credit card fraud it can be happened 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, although many person has proposed their work for credit card fraud detection by characterizing the user spending profile, but in this paper we are proposing the SVM(support vector machine) based method with multiple kernel involvement also including several fields of user profile instead of only spending profile & the simulation result shows improvement in TP(true positive), TN(true negative) rate, it also decreases the FP(false positive) & FN(false negative) rate.

Keywords

Fraud Detection, Kernels, SVM (Support Vector Machine).
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  • A Machine Learning Approach for Detection of Fraud Based on SVM

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Authors

Gajendra Singh
Department of Computer Science and Information Technology, SSSIST, Sehore, M.P., India
Ravindra Gupta
Department of Computer Science and Information Technology, SSSIST, Sehore, M.P., India
Ashish Rastogi
Department of Computer Science and Information Technology, SSSIST, Sehore, M.P., India
Mahiraj D. S. Chandel
Department of Computer Science and Information Technology, SSSIST, Sehore, M.P., India
Riyaz Ahmad
Aligarh Muslim University, Aligarh, India

Abstract


The growth of e-commerce increases the money transaction via electronic network which is designed for hassle free fast & easy money transaction but the facility involves greater risk of misuse of facility for fraud one of them is credit card fraud it can be happened 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, although many person has proposed their work for credit card fraud detection by characterizing the user spending profile, but in this paper we are proposing the SVM(support vector machine) based method with multiple kernel involvement also including several fields of user profile instead of only spending profile & the simulation result shows improvement in TP(true positive), TN(true negative) rate, it also decreases the FP(false positive) & FN(false negative) rate.

Keywords


Fraud Detection, Kernels, SVM (Support Vector Machine).