Detection of Phishing Websites Using a Machine Learning Algorithm

Abstract

Phishing attack is a simplest way to obtain sensitive information from innocent users. Aim of the
phishers is to acquire critical information like username, password and bank account details. Cyber
security persons are now looking for trustworthy and steady detection techniques for phishing
websites detection. This paper deals with machine learning technology for detection of phishing
URLs by extracting and analyzing various features of legitimate and phishing URLs. Decision Tree,
random forest and Support vector machine algorithms are used to detect phishing websites. Aim of the
paper is to detect phishing URLs as well as narrow down to best machine learning algorithm by
comparing accuracy rate, false positive and false negative rate of each algorithm