A Survey of Phishing Email Filtering Techniques

被引:115
作者
Almomani, Ammar
Gupta, B. B. [1 ]
Atawneh, Samer [2 ]
Meulenberg, A. [2 ]
Almomani, Eman [2 ]
机构
[1] Univ Pune, RSCOE, Pune, Maharashtra, India
[2] Univ Sains Malaysia, George Town, Malaysia
来源
IEEE COMMUNICATIONS SURVEYS AND TUTORIALS | 2013年 / 15卷 / 04期
关键词
Phishing email; Filtering; Classifiers; Machine learning; Authentication; Network level protection; CLASSIFICATION; MACHINE;
D O I
10.1109/SURV.2013.030713.00020
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Phishing email is one of the major problems of today's Internet, resulting in financial losses for organizations and annoying individual users. Numerous approaches have been developed to filter phishing emails, yet the problem still lacks a complete solution. In this paper, we present a survey of the state of the art research on such attacks. This is the first comprehensive survey to discuss methods of protection against phishing email attacks in detail. We present an overview of the various techniques presently used to detect phishing email, at the different stages of attack, mostly focusing on machine-learning techniques. A comparative study and evaluation of these filtering methods is carried out. This provides an understanding of the problem, its current solution space, and the future research directions anticipated.
引用
收藏
页码:2070 / 2090
页数:21
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