Feature based Phishing Website Detection using Random Forest Classifier

Abstract

In today’s world, one of the most vulnerable security threat which poses a problem to the internet users is phishing. Phishing is an attack made to steal the sensitive information of the users such as password, PIN, card details etc., In a phishing attack, the attacker creates a fake website to make the users click it and steal the sensitive information of users. . In this paper, we propose a feature-based phishing detection technique that uses uniform resource locator (URL) features. This paper focuses on the extracting the features which are then classified based on their effect within a website. The feature groups include address- bar related features, abnormal- based features, HTML – JavaScript based features and domain based features. We plan to use machine learning and implement some classification algorithms and compare the performance of these algorithms on our dataset.