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@article{142568,
        author = {Dr. M. Balamurugan and P. Mathiazhagan},
        title = {Credit Card Transaction Fraud Detection System Using Fuzzy Logic and K-Means Algorithm},
        journal = {International Journal of Innovative Research in Technology},
        year = {},
        volume = {2},
        number = {3},
        pages = {171-176},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=142568},
        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.},
        keywords = {Online, Credit card  fraud detection, Fuzzy logic, k-means clustering.},
        month = {},
        }