Smart Email Client To Detect Malicious URLs

The aim of this project was to detect phishing emails or URLs with a high accuracy. For the same, our deliverable was in the form of an improved email client that scrapes the last unread email from a user’s inbox and checks if it is safe or malicious. A series of Machine Learning algorithms were tried and experiments and research was conducted. From the results obtained, it was determined that a Balanced Random Forest algorithm after optimization in the form of algorithm tuning, training-testing split, feature analysis and other methods, was the most suitable choice for the project as it gave an accuracy of around 98% and after some experiments on optimization, it even reached a 100% accuracy.