• Mrs. S. DEEPIKA
• M.PRATHIBA

This paper is used to detect the website fraud by using popup window. Because Website Site Fraud Detection is a crucial point that applies to numerous ventures including the monetary areas, banking, government organizations, protection, and law requirement, and other industries also. In spite of battles with respect to the grieved associations, countless amounts are squandered to misrepresentation every year. Pop-up windows are mostly generated by the websites. Web traffic is measured in visits, sometimes called "sessions," and is a common way to measure an online business effectiveness at attracting an audience. Website traffic refers to web users who visit a website. By using pop-up window and website traffic we are going to detect the fraud which are occurring in website.

NAIVE BAYES classifier, Machine learning.

"A NEW APPROACH IN WEBSITE FRAUD DEDUCTION BY CLASSIFYING FEATURE SELECTION METHOD", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.8, Issue 4, page no.24-26, April-2021, Available :http://www.jetir.org/papers/JETIRER06006.pdf

"A NEW APPROACH IN WEBSITE FRAUD DEDUCTION BY CLASSIFYING FEATURE SELECTION METHOD", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.8, Issue 4, page no. pp24-26, April-2021, Available at : http://www.jetir.org/papers/JETIRER06006.pdf