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This project forked from pratiknn/detection-of-phishing-websites-using-supervised-machine-learning-techniques

Phishing is a website forgery with an intention to track and steal the sensitive information of online users. It is a form of identity theft, in which criminals build replicas of target websites and lure unsuspecting victims to disclose their sensitive information like passwords, PIN, etc. A huge volume of information is downloaded and uploaded constantly to the web. This gives opportunities for criminals to hack important personal information. To overcome the issues faced here, developed a phishing websites detection technique based on machine learning classifiers with a wrapper features selection method. Classification algorithms used are Artificial Neural Network, Random Forest and Support Vector Machine. Dynamic features extraction is made from the entered URL and the trained model is used for the detection of phishing URL.