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Security and Communication Networks
Volume 2017 (2017), Article ID 5421046, 20 pages
Review Article

Phishing Detection: Analysis of Visual Similarity Based Approaches

National Institute of Technology, Kurukshetra, India

Correspondence should be addressed to B. B. Gupta

Received 4 July 2016; Accepted 28 August 2016; Published 10 January 2017

Academic Editor: Muhammad Khurram Khan

Copyright © 2017 Ankit Kumar Jain and B. B. Gupta. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


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.