Detection of Phishing Page Using Machine Learning and Response HTML

Abstract

Currently people face social engineering attacks as a major threat for the internet users. All most every process have become online including banking transactions. It might be great advantage for people. But, at the same time it arises major security issues. Some of the server side and client-side security bugs can be fixed by the companies or they may take the total responsibility of the loss. But companies cannot be able to prevent the social engineering attacks and they won’t be responsible for any cause happened due to social engineering attacks like phishing. The only thing they can do is to spread awareness to the users. But some identical fake websites are built in trustworthy manner to steal credentials or sensitive information from the users. As a solution to this we have decided to choose to build an extension which can able to detect phishing site in advance and warn the users not to give any sensitive information through the website. The backend of the extension is build using machine learning and we have built the user interface using flask. To identify the phishing we have trained our ML model with the dataset containing about 5 lakhs + URLs and also used Who Is data analysis and selenium response to detect the phishing site and safe guard users from getting trapped.