PREDICTION OF PHISHING WEBSITE USING MACHINELEARNING

Phishing attack is a simplest way to obtain sensitive information from innocent users. The Internet has become an indispensable part of our life, However, It also has provided opportunities to anonymously perform malicious activities like Phishing. Phishers try to deceive their victims by social engineering or creating mockup websites to steal information such as account ID, username, password from individuals and organizations. Although many methods have been proposed to detect phishing websites, Phishers have evolved their methods to escape from these detection methods.Phishes use the websites which are visually and semantically similar to those real websites. One of the most successful methods for detecting these malicious activities is Machine Learning. Phishing is popular among attackers, since it is easier to trick someone into clicking a malicious link which seems legitimate than trying to break through a computer's defense systems.This is because most Phishing attacks have some common characteristics which can be identified by machine learning methods.Decision Tree, random forest and Support vector machine algorithms are used to detect phishing websites.we compared the results of multiple machine learning methods for predicting phishing websites.