Detection of Phishing Websites using Machine Learning

Trying to access personal information nowadays has become more common. Phishing is an attack where the hackers take advantage of the trust factor of the target and try to gather sensitive information of a target such as a username, password, etc. by disguising as a trustworthy entity. There are many anti-phishing methods such as blacklist, heuristic, visual similarity and, machine learning. The blacklist method is widely used because it is easy to use and execute, but it fails to detect new phishing attacks. This paper proposes a methodology of phishing identification framework where various machine learning algorithms like random forest, support vector machine, logistic regression are used for the comparison conciseness to predict more accuracy. It also includes data analysis, data visualization, and, detecting the phishing website. After detailed research, we proposed a framework that overcomes the disadvantages of other approaches.