Intelligent phishing detection system using similarity matching algorithms Online publication date: Thu, 04-Jan-2018
by Ankur Mishra; B.B. Gupta
International Journal of Information and Communication Technology (IJICT), Vol. 12, No. 1/2, 2018
Abstract: Today, phishing attack is one of the most common and serious threat over internet. It is used to fraud users and steal their personal information either by using spoofed e-mails or fake websites or both. In this paper, we proposed a novel intelligent phishing detection system, i.e., CSS and URI matching-based phishing detection system (CUMP) to detect zero-day phishing attacks. Our proposed approach is based on the concept of uniform resource identifier (URI) and cascading style sheet (CSS) matching. This concept is used, as phisher always tries to mimic the URI pattern and visual design in the hope that even experienced user will not be able to detect phishing website by visualisation. To mimic the visual appearance, phishers generally use same CSS style. Without using same CSS, it is very difficult to achieve the same design. To defend against phishing websites attacks especially 'zero-day' attacks, our proposed system used the basic properties of any phishing attacks for URI and CSS matching. Our proposed solution is very effective in detecting a wide range of website phishing attacks with TP and TN rate of 93.27% and 100%, respectively and results in less false positive rate.
Online publication date: Thu, 04-Jan-2018
If you are not a subscriber and you just want to read the full contents of this article, buy online access here.Complimentary Subscribers, Editors or Members of the Editorial Board of the International Journal of Information and Communication Technology (IJICT):
Login with your Inderscience username and password:
Want to subscribe?
A subscription gives you complete access to all articles in the current issue, as well as to all articles in the previous three years (where applicable). See our Orders page to subscribe.
If you still need assistance, please email firstname.lastname@example.org