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A Hybrid Technique for Credit Card Fraud Detection

Shipra Rathore, Megha Jain. Published in Security.

Communications on Applied Electronics
Year of Publication: 2016
Publisher: Foundation of Computer Science (FCS), NY, USA
Authors: Shipra Rathore, Megha Jain
10.5120/cae2016652299

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.

References

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Keywords

PGNN(Parallel Granular Neural Network), CBM(Cost Based Model), HMM(Hidden Markov Model), Credit Card Fraud Detection.