Phishing URL Detection using Machine Learning

Abstract

Phishing attack is an easy way to obtain sensitive information from innocent users and also there are many tools and techniques available to do so. The main aim of the attackers is to get the critical information like username, password, bank account details and etc. and by this they can harm the innocent users. As a security perspective there should be a system or tools that would be able to overcome such issues. So this paper deals with machine learning technologies for the detection of phishing URLs by analyzing and extracting different types of features of legitimate and phishing URLs. Various machine learning algorithms like Decision Tree, Random Forest and Support Vector Machine are used to detect phishing websites. Aim of this paper is to detect phishing urls as well as narrow down to best machine learning algorithm by comparing the accuracy rate, false positive and false negative rate of each algorithm