PHISHING URL DETECTION WEBSITE

Abstract

Phishing websites are one of the types of internet security issues that target human vulnerabilities rather than software flaws. It's the technique of luring online users in order to get sensitive information like usernames and passwords. We present an intelligent technique for detecting phishing websites in this research. The technology works as an add on to an internet browser, notifying the user when it finds a phishing website. The system is based on supervised learning, which is a type of machine learning. We chose the Random Forest approach because of its high categorization performance. Our goal is to develop a higher performing classifier by examining the characteristics of phishing websites and combining them in the best way possible.