Paper Info
Title
Detection of phishing attacks in financial and e-banking websites using link and visual similarity relation.
Abstract
Today, phishing is one of the biggest problems faced by the cyber-world. In this paper, we present an approach that can detect phishing attacks in commercial and e-banking websites using the link and visual similarity relations. Phisher always tries to mimic the visual design of the webpage and the fake webpage contains identity keywords and hyperlinks that point to the corresponding legitimate webpage to trap internet users. Therefore, our proposed approach analyse the keywords, hyperlinks and CSS layout of the webpage to detect phishing attack. In the proposed approach, we make a set of associate domains with the suspicious webpage and explore the link and similarity relation to identifying phishing webpages. Also, we use the login form and whitelist based filtering to increase the running time of the proposed approach. Our proposed approach is not only able to detect phishing webpages accurately but its source webpage also. Moreover, it does not require any prior training to detect zero hour phishing a...
Year
DOI
Venue
2018
10.1504/IJICS.2018.095303
IJICS
Field
DocType
Volume
Web page,Phishing,Information retrieval,Computer science,Computer security,Login,Cascading Style Sheets,Whitelist,Hyperlink,Document Object Model,The Internet
Journal
10
Issue
Citations 
PageRank 
4
2
0.43
References 
Authors
0
2
Name
Order
Citations
PageRank
Ankit Kumar Jain1817.77
Brij B. Gupta224.48