Research Article
Learning Model for Phishing Website Detection
@ARTICLE{10.4108/eai.13-7-2018.163804, author={A. Suryan and C. Kumar and M. Mehta and R. Juneja and A. Sinha}, title={Learning Model for Phishing Website Detection}, journal={EAI Endorsed Transactions on Scalable Information Systems}, volume={7}, number={27}, publisher={EAI}, journal_a={SIS}, year={2020}, month={3}, keywords={Information systems, phishing, machine learning, feature extraction, classification, dimensionality reduction, security}, doi={10.4108/eai.13-7-2018.163804} }
- A. Suryan
C. Kumar
M. Mehta
R. Juneja
A. Sinha
Year: 2020
Learning Model for Phishing Website Detection
SIS
EAI
DOI: 10.4108/eai.13-7-2018.163804
Abstract
Website portal empowered with information technology are of great importance in present scenario. With access to data all around the world, securing our information becomes an issue of topmost priority. Over the decade there have been numerous attacks by phishing websites and people have lost huge resources. Such malicious websites, also known as phishing website, steal information of authenticate users and carry out illegal transactions by misusing the personal information. Phishing website links and associated e-mails are sent to billions of users daily, thereby becoming a big concern for cyber security. In this paper, we address the phishing problem using machine learning approach applied on our proposed model, which uses 30 distinct features for phishing detection. We extracted multiple features from the website link and applied appropriate algorithms to classify the link as legitimate or phishing links.
Copyright © 2020 A. Suryan et al., licensed to EAI. This is an open access article distributed under the terms of the Creative Commons Attribution licence (http://creativecommons.org/licenses/by/3.0/), which permits unlimited use, distribution and reproduction in any medium so long as the original work is properly cited.