Phishing Website Detection Based on URL

Abstract

In today's era, due to the surge in the usage of the internet and other online platforms, security has been major attention. Many cyberattacks take place each day out of which website phishing is the most common issue. It is an act of imitating a legitimate website and thereby tricking the users and stealing their sensitive information. So, concerning this problem, this paper will introduce a possible solution to avoid such attacks by checking whether the provided URLs are phishing URLs or legitimate URLs. It is a Machine Learning based system especially Supervised learning where we have provided 2000 phishing and 2000 legitimate URL dataset. We have taken into consideration the Random Forest Algorithm due to its performance and accuracy. It considers 9 features and hence detects whether the URL is safe to access or a phishing URL.