TY  - JOUR
T1  - Experimental Method to Improve the Accuracy of Phishing URL Detection
Using Theil Classifier
AU - Rakesh, R. AU - Kannan, A. 
JO  - Asian Journal of Information Technology
VL  - 15
IS  - 21
SP  - 4422
EP  - 4425
PY  - 2016
DA  - 2001/08/19
SN  - 1682-3915
DO  - ajit.2016.4422.4425
UR  - https://makhillpublications.co/view-article.php?doi=ajit.2016.4422.4425
KW  - Web security
KW  -anti-phishing
KW  -decision tree
KW  -classification
KW  -India
AB  - 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.
ER  -