About This Publication
Phishing is one of the most prevalent threats in the internet era. Phishing is a sophisticated method where a legitimate website is cloned and victims are lured to the fake website to provide their personal and financial information, which often proves to be costly.
Our proposed methodology tends to establish phishing websites employing a combined approach by constructing Resource Description Framework (RDF) models and using ensemble learning algorithms for the classification of websites. Our approach uses supervised learning techniques to train our system.
As our system explores the strength of RDF and ensemble learning methods, and both these approaches work hand in hand, a highly promising accuracy rate of 97% is achieved.