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Experimental method to improve the accuracy of phishing URL detection using theil classifier

Publication Type : Journal Article

Publisher : Asian Journal of Information Technology

Source : Asian Journal of Information Technology 15, 21, 4422-4425

Url : https://www.researchgate.net/publication/313597776_Experimental_method_to_improve_the_accuracy_of_phishing_URL_detection_using_theil_classifier

Campus : Chennai

School : School of Computing

Department : Computer Science and Engineering

Year : 2016

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.

Cite this Research Publication : Rakesh, R. and Kannan, A. Experimental method to improve the accuracy of phishing URL detection using theil classifier Asian Journal of Information Technology 15, 21, 4422-4425

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