DocumentCode :
3668329
Title :
Phishing websites detection through supervised learning networks
Author :
Priyanka Singh;Yogendra P.S. Maravi;Sanjeev Sharma
Author_Institution :
School of Information Technology, Ragiv Gandhi Proudyogiki Vishwavidyalaya, Bhopal, INDIA
fYear :
2015
Firstpage :
61
Lastpage :
65
Abstract :
Phishing is an unlawful activity of making gullible people to reveal their insightful information into fake websites. The Aim of these phishing websites is to acquire confidential information such as usernames, passwords, banking credentials and some other personal information. Phishing website looks similar to legitimate website therefore people cannot make difference among them. Today users are heavily relying on the internet for online purchasing, ticket booking, bill payments, etc. As technology advances, the phishing approaches being used are also getting progressed and hence it stimulates anti-phishing methods to be upgraded. In this paper, we have implemented two algorithms named Adaline and Backpropion along with the support vector machine to enhance the detection rate and classification.
Keywords :
"Support vector machines","Feature extraction","Uniform resource locators","Classification algorithms","Training","Accuracy","Supervised learning"
Publisher :
ieee
Conference_Titel :
Computing and Communications Technologies (ICCCT), 2015 International Conference on
Type :
conf
DOI :
10.1109/ICCCT2.2015.7292720
Filename :
7292720
Link To Document :
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