Preeminent System for Detecting Venomous Banking Sites in Online Business

Abstract:

. Phishing has become most notorious security issues in online real time web pages. Many studies and ideas have been proposed related to phishing attack in order to overcome the security issues. Phishing attack can be easily done by Uniform resource locator (URL) obfuscation. It is the trick where the user will be forwarded to fake web page which has look and feel effect as the original web page when they click through the fake link. Organizations which use online business and transaction like ebay, paypal use many preventive approaches like blacklist, whitelist of URL in order to prevent any online theft using phishing attack. This paper propose a novel idea for detecting Phishing attack by checking the URL patterns of the suspected page with generated legitimate common URL pattern by inspecting different international URL patterns of that particular banking site.

• Periodical: Applied Mechanics and Materials (Volume 573)
• Pages: 519-522
• DOI: https://doi.org/10.4028/www.scientific.net/AMM.573.519
• Online since: June 2014
• Authors: N.S. Sudharsan*, K. Latha
• Keywords: Blacklist, Phishing, URL Obfuscation, Whitelist

References

[1] Ian Fette Norman Sadeh Anthony Tomasic. Learning to Detect Phishing Emails, Institute for Software Research International School of Computer Science Carnegie Mellon University, june (2006).

DOI: 10.21236/ada456046

[2] Internet Threats Trend Report April 2013. Available: http: /static. altn. com/Collateral/Security-Threat-Trend-Reports/2013-Q1_Email- Threat- Trend-Report. pdf.

[3] Mitsuaki Akiyama, Takeshi Yagi, and Takeo Hariu. Blacklisting: Inspecting the Structural Neighborhood of Malicious URLs, NTT Secure Platform Laboratories, Japan, July/August (2013).

DOI: 10.1109/mitp.2012.118

[4] Christian Ludl, Sean McAllister, Engin Kirda, Christopher Kruegel. On the Effectiveness of Techniques to Detect Phishing Sites,. Available: http: /iseclab. org/papers/phishingstudy. pdf.

[5] Neil Chou Robert Ledesma Yuka Teraguchi Dan Boneh John C. Mitchell. Client-side defense against web-based identity theft,. Computer Science Department, Stanford University. Available: http: /crypto. stanford. edu/SpoofGuard/webspoof. pdf.

[6] Dr Matt Foster. Netcraft Analysis: Online Speed Testing Tools", 25th February 2013. Available: http: /www. setda. org/c/document_library/get_file, folderId=353&name=DLFE-1647. pdf.

[7] Ye Cao, Weili Han, Yueran Le. Anti-phishing Based on Automated Individual White-List,. ACM, Fairfax, Virginia, USA, October 31, 2008. Available: http: /crypto. fudan. edu. cn/People/weili/papers/han-dim08. pdf.

DOI: 10.1145/1456424.1456434

[8] N.S. Sudharsan, Dr. K. Latha. Improvising Seeker Satisfaction in Cloud Community Portal: Dropbox,. IEEE- International conference on Communication and Signal Processing, April 3-5, 2013, pp.321-325.

DOI: 10.1109/iccsp.2013.6577067

[9] Yeu Zhang, Jason Hong, Lorrie Cranor. CANTINA: A Content-Based Approach to Detecting Phishing Web Sites,. WWW 2007 / Track: Security, Privacy, Reliability, and Ethics.

DOI: 10.1145/1242572.1242659

[10] Haijun Zhang, Gang Liu, Tommy W. S. Chow Textual and Visual Content-Based Anti-Phishing: A Bayesian Approach, IEEE TRANSACTIONS ON NEURAL NETWORKS, VOL. 22, NO. 10, OCTOBER (2011).

DOI: 10.1109/tnn.2011.2161999

[11] http: /www. regular-expressions. info/reference. html.