Lexical URL analysis for discriminating phishing and legitimate websites
Document Type
Conference Proceeding
Publisher
ACM
Faculty
Faculty of Computing, Health and Science
School
School of Computer and Security Science / Security Research Centre (secAU)
RAS ID
12292
Abstract
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.
DOI
10.1145/2030376.2030389
Access Rights
subscription content
Comments
Khonji, M., Iraqi, Y., & Jones, A. (2011). Lexical URL analysis for discriminating phishing and legitimate websites. Paper presented at the Annual Collaboration, Electronic messaging, Anti-Abuse and Spam (CEAS) Conference. Perth, WA.