文章基本信息

标题：PHISHING EMAIL CLASSIFIERS EVALUATION: EMAIL BODY AND HEADER APPROACH
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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：2015
卷号：80
期号：2
出版社：Journal of Theoretical and Applied
摘要：The internet is a great importance to millions of people in their social and financial activities every day. This not only limited to individual users of the Internet, but also to organizations for the purposes of trade and others. A huge number of financial activities occur every day with millions of dollars are transferred where this large amount of financial events open the appetite of fraudsters to implement fraudulent activities. Thus, users vulnerable to many threats, including the theft of private information, banking information, and many more. Recently, phishing is a serious threat which steals user�s sensitive information and regarded as the most profitable cybercrime. Phishing mainly relies on email claiming originating from trusted source contains an embedded link to redirect victims to not benign website in order to get users financial data. As the risk of Phishing emails increases progressively, detecting and overriding this phenomenon has become very urgent, especially the zero day phishing campaigns which are new phishing emails not seen by anti-phishing tools. Although there are several solutions for phishing detection such as blacklists and heuristics, there is no clear discussion about the required processing time and the complexity of the designed solutions. This paper aims to make such dissection for server side solutions which proved to be the best choice to defeat zero day attacks.
关键词：Phishing; Emails; Body features; Header features; and Classifiers