A phishing website is a common social engineering method that mimics trustful uniform resource locators (URLs) and webpages.Phishing websites are created to dupe unsuspecting users into thinking they are on a legitimate site. The criminals will spend a lot of time making the site seem as credible as possible and many sites will appear almost indistinguishable from the real thing.The objective of this project is to train machine learning models and deep neural nets on the dataset created to predict phishing websites. Both phishing and benign URLs of websites are gathered to form a dataset and from them required URL and website content-based features are extracted. The performance level of each model is measures and compared. To find the best machine learning algorithm to detect phishing websites.
