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Fraud Detection in Credit Card by Clustering Approach

International Journal of Computer Applications
© 2014 by IJCA Journal
Volume 98 - Number 3
Year of Publication: 2014

Vaishali. Article: Fraud Detection in Credit Card by Clustering Approach. International Journal of Computer Applications 98(3):29-32, July 2014. Full text available. BibTeX

	author = {Vaishali},
	title = {Article: Fraud Detection in Credit Card by Clustering Approach},
	journal = {International Journal of Computer Applications},
	year = {2014},
	volume = {98},
	number = {3},
	pages = {29-32},
	month = {July},
	note = {Full text available}


Fraud is an unauthorized activity taking place in electronic payments systems, but these are treated as illegal activities. Fraud detection methods are continuously developed to defend criminals in adapting to their strategies. Fraud can be identified quickly and easily through fraud detection techniques. In this paper, clustering approach is used for credit card fraud detection. Data is generated randomly for credit card and then K-means clustering algorithm is used for detecting the transaction whether it is fraud or legitimate. Clusters are formed to detect fraud in credit card transaction which are low, high, risky and high risky. K-means clustering algorithm is simple and efficient algorithm for credit card fraud detection.


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