Phishing URL Detection Using Machine Learning

Abstract

Phishing attack is used to obtain the information like username, password, bank account details, and credit card details. It is a most popular cybercrime today. Phishing attacks also affect the online payment sector financial institution, file hosting or cloud storage, and many others. Phishing attack always targets to these Web sites which are related to the online payment sector and Web mail. Many techniques are used to prevent the phishing attack like blacklist, Heuristic, visual similarity, and machine learning. Blacklist technique is most commonly used because it is easy to implement, but this technique cannot detect a new phishing attack. So, now, machine learning is most efficient technique to detect the phishing attack and this technique is able to detect all drawback of other phishing detect techniques. So this research work is completely based on machine learning algorithms which are logistic regression, decision tree, random forest, and SVM to detect phishing Web site. In this research work, select the best model on the basis of six analysis factors.