Credit Card Transaction Fraud Detection System Using Fuzzy Logic and K-Means Algorithm
Author(s):
Dr. M. Balamurugan, P. Mathiazhagan
Keywords:
Online, Credit card fraud detection, Fuzzy logic, k-means clustering.
Abstract
The usage of credit card has dramatically increased, credit card fraud has become increasing rampant in recent years. Nowadays credit card fraud is one of the major issues of great financial losses, for the merchants and individual clients are also affected. This fraud is difficult to find out fraudulent and concerning losses will be barred by issuing authorities. As a result, fraud detection is the important solution and almost certainly the best way to stop credit card fraud types. Fuzzy logic is to analyze the spending profile of each card holder Credit card fraud can be detected on analyzing of previous transactions data. In this study Fuzzy logic and k-means are developed and applied to credit card fraud detection problem. It will be the most effective method to counter fraud transaction through internet. Fuzzy logic and k-means produce a better result comparing to the other data mining techniques.
Article Details
Unique Paper ID: 142568

Publication Volume & Issue: Volume 2, Issue 3

Page(s): 171 - 176
Article Preview & Download


Share This Article

Conference Alert

NCSST-2021

AICTE Sponsored National Conference on Smart Systems and Technologies

Last Date: 25th November 2021

SWEC- Management

LATEST INNOVATION’S AND FUTURE TRENDS IN MANAGEMENT

Last Date: 7th November 2021

Latest Publication

Go To Issue



Call For Paper

Volume 8 Issue 4

Last Date 25 September 2021

About Us

IJIRT.org enables door in research by providing high quality research articles in open access market.

Send us any query related to your research on editor@ijirt.org

Social Media

Google Verified Reviews

Contact Details

Telephone:6351679790
Email: editor@ijirt.org
Website: ijirt.org

Policies