Phishing uniform resource locator detection using machine learning: A step towards secure system

Abstract

The advancement in technology has led to increase in cyber‐attacks. Hackers have become more skilled at finding the loopholes in the system and can penetrate easily on to host network. The rate of cybercrimes is increasing exponentially with the growth of digital era. Phishing is considered as one of the top cybercrimes that has impacted the society at large. As per Kaspersky reports 2021, around 22% attacks were phishing attacks. This paper explores methods for detecting phishing uniform resource locator (URLs) by analyzing various features using Machine Learning techniques. Various data mining algorithms are used to learn data patterns that can identify and differentiate between benign and phishing websites using phishing website data set. The best results are shown by an XGBoost Model that provides more than 90% accuracy on the balanced class dataset.