Phishing Detection using Random Forest, SVM and Neural Network with Backpropagation

Abstract

Phishing is a common attack used to obtain sensitive information using visually similar websites to that of legitimate websites. With the growing technology, phishing attacks are on the rise. Machine Learning is a very popular approach to detect phishing websites. This paper explains the existing machine learning methods that are used to detect phishing websites. The paper explains the improved Random Forest classification method, SVM classification algorithm and Neural Network with backpropagation classification methods which have been implemented with accuracies of 97.369%, 97.451% and 97.259% respectively.