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A Hybrid Approach for Credit Card Fraud Detection using Rough Set and Decision Tree Technique

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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Year of Publication: 2016
Authors:
Rajni Jain, Bhupesh Gour, Surendra Dubey
10.5120/ijca2016909325

Rajni Jain, Bhupesh Gour and Surendra Dubey. Article: A Hybrid Approach for Credit Card Fraud Detection using Rough Set and Decision Tree Technique. International Journal of Computer Applications 139(10):1-6, April 2016. Published by Foundation of Computer Science (FCS), NY, USA. BibTeX

@article{key:article,
	author = {Rajni Jain and Bhupesh Gour and Surendra Dubey},
	title = {Article: A Hybrid Approach for Credit Card Fraud Detection using Rough Set and Decision Tree Technique},
	journal = {International Journal of Computer Applications},
	year = {2016},
	volume = {139},
	number = {10},
	pages = {1-6},
	month = {April},
	note = {Published by Foundation of Computer Science (FCS), NY, USA}
}

Abstract

To make the business accessible to a large number of customers worldwide, many companies small and big have put up their presence on the internet. Online businesses gave birth to e-commerce platforms which in turn use digital modes of transaction such as credit-card, debit card etc. This kind of digital transaction attracted millions of users to transact on the internet. Along came the risk of online credit card frauds.

Hence the need to have secure payment transactions arose and many techniques based on Neural Network, Decision Tree, Artificial Intelligence, Artificial Immune System, Fuzzy based systems, Nearest neighbor algorithm, Support Vector Machines, Genetic Algorithm were developed to detect the fraudulent online credit card transactions.

This paper presents hybrid Approach for Credit Card Fraud detection using Rough Set and Decision Tree Technique which can be used in credit card fraud detection mechanisms.

References

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Keywords

Credit card fraud detection, J48 classification, rough set, Support Vector Machines etc.