文章基本信息

标题：LEXICAL BASED METHOD FOR PHISHING URLS DETECTION
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作者：AMMAR YAHYA DAEEF ; R. BADLISHAH AHMAD ; YASMIN YACOB 等
期刊名称：Journal of Theoretical and Applied Information Technology
印刷版ISSN：1992-8645
电子版ISSN：1817-3195
出版年度：2016
卷号：88
期号：3
出版社：Journal of Theoretical and Applied
摘要：Phishing is a social engineering attack that exploits users ignorance during system processing has an impact on commercial and banking sectors. Numerous techniques are developed in the last years to detect phishing attacks such as authentication, security toolbars, blacklists, phishing emails, phishing websites, and URL analysis. Regrettably, nowadays detection system implemented for specific attack vectors such as email which make developing wide scope detection is much needed. Previous studies show that analysis of URLs proved to be a good option to detect malicious activities where this method mostly based on features of lexical, host information, and other complex method which requires a long processing time. In this paper, we present phishing detection system using features extracted from URLs lexical only to meet two important goals which are wide scope of protection and applicability in a real-time system. The system provides accuracy of 94% and can classify single URL in average time of 0.12 second.
关键词：Phishing; Classifiers; Machine Learning; Lexical Features.