A survey and classification of web phishing detection schemes

被引:72
作者
Varshney, Gaurav [1 ]
Misra, Manoj [1 ]
Atrey, Pradeep K. [2 ]
机构
[1] Indian Inst Technol Roorkee, Dept Comp Sci & Engn, Roorkee, Uttarakhand, India
[2] SUNY Albany, Dept Comp Sci, Albany, NY 12222 USA
关键词
phishing; deception; search engine; WEBSITES;
D O I
10.1002/sec.1674
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 is a fraudulent technique that is used over the Internet to deceive users with the goal of extracting their personal information such as username, passwords, credit card, and bank account information. The key to phishing is deception. Phishing uses email spoofing as its initial medium for deceptive communication followed by spoofed websites to obtain the needed information from the victims. Phishing was discovered in 1996, and today, it is one of the most severe cybercrimes faced by the Internet users. Researchers are working on the prevention, detection, and education of phishing attacks, but to date, there is no complete and accurate solution for thwarting them. This paper studies, analyzes, and classifies the most significant and novel strategies proposed in the area of phished website detection, and outlines their advantages and drawbacks. Furthermore, a detailed analysis of the latest schemes proposed by researchers in various subcategories is provided. The paper identifies advantages, drawbacks, and research gaps in the area of phishing website detection that can be worked upon in future research and developments. The analysis given in this paper will help academia and industries to identify the best anti-phishing technique. Copyright (C) 2016 John Wiley & Sons, Ltd.
引用
收藏
页码:6266 / 6284
页数:19
相关论文
共 92 条
[1]  
Abdelhamid Neda, 2015, Applied Computing and Informatics, V11, P29, DOI 10.1016/j.aci.2014.07.002
[2]   Phishing detection based Associative Classification data mining [J].
Abdelhamid, Neda ;
Ayesh, Aladdin ;
Thabtah, Fadi .
EXPERT SYSTEMS WITH APPLICATIONS, 2014, 41 (13) :5948-5959
[3]   Intelligent phishing detection system for e-banking using fuzzy data mining [J].
Aburrous, Maher ;
Hossain, M. A. ;
Dahal, Keshav ;
Thabtah, Fadi .
EXPERT SYSTEMS WITH APPLICATIONS, 2010, 37 (12) :7913-7921
[4]  
Alexa, 2015, TOP 500 SIT WEB
[5]   A Survey of Phishing Email Filtering Techniques [J].
Almomani, Ammar ;
Gupta, B. B. ;
Atawneh, Samer ;
Meulenberg, A. ;
Almomani, Eman .
IEEE COMMUNICATIONS SURVEYS AND TUTORIALS, 2013, 15 (04) :2070-2090
[6]  
[Anonymous], 2005, SOUPS '05: Proceedings of the 2005 Symposium on Usable Privacy and Security, Pittsburgh, Pennsylvania
[7]  
[Anonymous], 2014, 2014 23 INT C COMP C
[8]  
[Anonymous], 2014, Crime Science, DOI [10.1186/s40163-014-0009-y, DOI 10.1186/S40163-014-0009-Y]
[9]  
[Anonymous], 2007, P 3 S US PRIV SEC, DOI DOI 10.1145/1280680.1280692
[10]  
[Anonymous], 2007, P 16 INT C WORLD WID, DOI DOI 10.1145/1242572.1242660