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A Hybrid Technique for Credit Card Fraud Detection
Shipra Rathore and Megha Jain. A Hybrid Technique for Credit Card Fraud Detection. Communications on Applied Electronics 5(5):20-23, July 2016. BibTeX
@article{10.5120/cae2016652299, author = {Shipra Rathore and Megha Jain}, title = {A Hybrid Technique for Credit Card Fraud Detection}, journal = {Communications on Applied Electronics}, issue_date = {July 2016}, volume = {5}, number = {5}, month = {Jul}, year = {2016}, issn = {2394-4714}, pages = {20-23}, numpages = {4}, url = {http://www.caeaccess.org/archives/volume5/number5/618-2016652299}, doi = {10.5120/cae2016652299}, publisher = {Foundation of Computer Science (FCS), NY, USA}, address = {New York, USA} }
Abstract
Credit card fraud occurs when user provide their information to the unknown persons or stolen by the unknown persons, that information can be used for unauthorized online purchase and some other situation. A technique is required to detect such fraud events. Many techniques are exist to detect such frauds. But these existing techniques are not efficient to provide better performance to detect such credit card fraud events. In this paper a hybrid technique which uses the properties of PGNN and Cost based model is presented which provides enhanced functionality to detect credit card frauds. The analysis of hybrid technique shows that the proposed technique provides an accurate and efficient way to detect credit card frauds.
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Keywords
PGNN(Parallel Granular Neural Network), CBM(Cost Based Model), HMM(Hidden Markov Model), Credit Card Fraud Detection.