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A Novel Approach for Behavior Based Charge Card Fraud Detection using Support Vector Machines


D.Manjula , Research Scholar; J.Thilagavathi, Assistant Professsor


E-Payment, E-Commerce, Fraud deduction, cluster analysis


Online payments are provided with extreme safety, even though, it is not unrestricted from faults. Decline in virtual extortions is the essential for the current day. One of the primary e-transactions that face these threats are the credit/debit cards. This method habits bundling and outlier discovery for discovery the illicit communications. Primarily, the communications are clustered translation to the attribute measured as obligatory for the finding process. Then each gathering is useful with the outlier discovery method for the discovery of data that departs from the existing data flow. This data has the highest possibility of being the fake data. The next procedure uses SVM, a binary classifier for healthier location. Then these methods are disposed to grips high level of fabricated positives. To decline these lying positives, multi-clustering is used. Hence, this suggest the manipulator with an in effect, mutual outlier finding appliance that reduces faults and offers more precise results for the user.

Other Details

Paper ID: IJSRDV3I60577
Published in: Volume : 3, Issue : 6
Publication Date: 01/09/2015
Page(s): 1094-1098

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