Paper Info
Title
Phishing Detection: Analysis of Visual Similarity Based Approaches.
Abstract
Phishing is one of the major problems faced by cyber-world and leads to financial losses for both industries and individuals. Detection of phishing attack with high accuracy has always been a challenging issue. At present, visual similarities based techniques are very useful for detecting phishing websites efficiently. Phishing website looks very similar in appearance to its corresponding legitimate website to deceive users into believing that they are browsing the correct website. Visual similarity based phishing detection techniques utilise the feature set like text content, text format, HTML tags, Cascading Style Sheet (CSS), image, and so forth, to make the decision. These approaches compare the suspicious website with the corresponding legitimate website by using various features and if the similarity is greater than the predefined threshold value then it is declared phishing. This paper presents a comprehensive analysis of phishing attacks, their exploitation, some of the recent visual similarity based approaches for phishing detection, and its comparative study. Our survey provides a better understanding of the problem, current solution space, and scope of future research to deal with phishing attacks efficiently using visual similarity based approaches.
Year
DOI
Venue
2017
10.1155/2017/5421046
SECURITY AND COMMUNICATION NETWORKS
Field
DocType
Volume
HTML element,World Wide Web,Phishing,Tabnabbing,Computer security,Computer science,Cascading Style Sheets,Formatted text,Feature set,Spoofed URL,Phishing detection
Journal
2017
ISSN
Citations 
PageRank 
1939-0114
10
0.56
References 
Authors
26
2
Name
Order
Citations
PageRank
Ankit Kumar Jain1817.77
B. B. Gupta251846.49