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A Survey on Different Approaches used for Credit Card Fraud Detection

Anika Nahar, Sharmistha Roy, Syeda Shabnam Hasan. Published in Security

International Journal of Applied Information Systems
Year of Publication: 2016
Publisher: Foundation of Computer Science (FCS), NY, USA
Authors: Anika Nahar, Sharmistha Roy, Syeda Shabnam Hasan
10.5120/ijais2016451492
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  1. Anika Nahar, Sharmistha Roy and Syeda Shabnam Hasan. Article: A Survey on Different Approaches used for Credit Card Fraud Detection. International Journal of Applied Information Systems 10(4):29-34, January 2016. BibTeX

    @article{key:article,
    	author = "Anika Nahar and Sharmistha Roy and Syeda Shabnam Hasan",
    	title = "Article: A Survey on Different Approaches used for Credit Card Fraud Detection",
    	journal = "International Journal of Applied Information Systems",
    	year = 2016,
    	volume = 10,
    	number = 4,
    	pages = "29-34",
    	month = "January",
    	note = "Published by Foundation of Computer Science (FCS), NY, USA"
    }
    

Abstract

Now-a-days the use of credit card has dramatically increased due to rapid growth of e-commerce technology. It is the most popular mode of payment for both online as well as regular purchase.Credit card fraud has become a significant problem, as companies, banks other financial institutions faces huge amount of losses annually because of fraudulent activities of fraudsters. So the main aim of credit card fraud detection system is to learn different patterns used in previous frauds and train itself to identify fraudulent and non fraudulent transactions. In this paper a survey on different techniques used in credit card fraud detection such as Neural Network,Bayesian Network, Decision Trees, Hidden Markov Model, Support Vector Machines, Meta Learning, Blast-SSaha Algorithm, Fuzzy System with Neural Network, Fuzzy Darwinian System, and Genetic Algorithm is demonstrated.

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Keywords

Credit Card Fraud, Neural Network, Bayesian Network, Decision trees, Support Vector Machine, Genetic Algorithm, Hidden Markov Model, Meta Learning, Fuzzy Darwinian System.