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ABSTRACT
The rapid increase of phishing attacks has led individuals and organizations losing billions of dollars as well as worried about the confidentiality and privacy of their data. This tremendous annual increase of phishing attacks shows that the current detection methods available are not sufficient, therefore more effective phishing detection methods should be developed. This paper proposed a novel phishing detection model using machine learning, to improve efficacy and accuracy in phishing detection. This paper explores the current state-of-the-art in phishing detection along with their drawbacks and proposes a new novel method using the Random forest machine learning classification technique and features extraction to detect phishing url. The algorithms architecture and proposes framework where developed using standard software design technique. The system design was able meet the objective of designing and implementing a phishing detection website using machine learning technique.
