Phishing Detection Using Machine Learning Algorithm
Jibrilla Tanimu, Stavros N. Shiaeles · 2022
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 based on image visualisation of website code and features extraction from malicious URLs which is under development.