An Efficient Data Mining for Credit Card Fraud Detection using Finger Print Recognition
V.Priyadharshini, G.Adiline Macriga
Abstract
Today there are millions of credit card transactions are being processed and mining techniques are highly applied to amount transaction and processing then the data’s are highly skewed Mining such massive amounts of data requires highly efficient techniques that scaled that can be extend transactions are legitimate than fraudulent fraud detection systems were widely used but this document gives the detection techniques. This paper contains multilayered techniques for providing the security for the credit card frauds. The first layer is communal detection and second is Spike detection layers that highly provides security for detection of frauds like probe resistant and mark the illegal user through their input details and mark it in a list. Then it removes attacks like defense in depths on cards and by removing the data redundancy of the attributes and it is being processed with millions of the credit cards.
Keyword
Knowledge based retrieval, Spike detection, Communal detection.