Detection of Fraudulent Websites

Abstract

The frequency of phishing attacks through spoofed websites and using opens source tools like ngrok, metasploit payloads etc. have become very high. This paper deals with methods and techniques to counter these issues. This paper mainly deals with countering website phishing attacks through data mining algorithms and feature detection. The J48 algorithm used in this project is based on decision tree. And is very effective in predicting the phishing website. This paper also deals with precision of different classifiers JRIP, J48 and Naive base. The feature detection is not only the process used but also detects through the manual entry of data sets which we have explained in the following sections.