Asian Journal of Information Technology

Year: 2016
Volume: 15
Issue: 21
Page No. 4422 - 4425

Experimental Method to Improve the Accuracy of Phishing URL Detection Using Theil Classifier

Authors : R. Rakesh and A. Kannan

Abstract: Web security pertains with the proposal of efficient security measures to guard against attacks carried over the internet. Different attacks such as denial of service, cross site scripting, injection, authentication and session management, social engineering, etc., exist as a hindrance to web services and end users. Phishing is a kind of social engineering attack. Phishing is a malicious activity where personal and confidential information from the end user is obtained by luring them towards an illegitimate web page or Uniform Resource Locator (URL). In this study, a novel approach to anti-phishing using Theil decision tree classifier is proposed, where the proposed algorithm computes optimal node values, essential in identifying the splitting attribute for the constructed decision tree which is then used to classify malicious web pages or URL’s.

How to cite this article:

R. Rakesh and A. Kannan, 2016. Experimental Method to Improve the Accuracy of Phishing URL Detection Using Theil Classifier. Asian Journal of Information Technology, 15: 4422-4425.

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