Lexical URL analysis for discriminating phishing and legitimate websites
Faculty of Computing, Health and Science
School of Computer and Security Science / Security Research Centre (secAU)
A study that aims to evaluate the practical effectiveness of website classifcation by lexically analyzing URL tokens in addition to a novel tokenization mechanism to increase prediction accuracy. The study analyzes over 70,000 legitimate and phishing URLs collected over 6 months period from PhishTank1, Khalifa University HTTP logs and volunteers using an experimental HTTP proxy server. A statistical classifcation model is then constructed and evaluated to measure the practical effectiveness of the lexical URL analysis presented in this paper.