Learning Model for Phishing Website Detection

Suryan, A. and Kumar, C. and Mehta, M. and Juneja, R. and Sinha, A. (2020) Learning Model for Phishing Website Detection. EAI Endorsed Transactions on Scalable Information Systems, 7 (27): e6. ISSN 2032-9407

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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.

Item Type: Article
Uncontrolled Keywords: Information systems, phishing, machine learning, feature extraction, classification, dimensionality reduction, security
Subjects: Q Science > QA Mathematics > QA75 Electronic computers. Computer science
QA75 Electronic computers. Computer science
Depositing User: EAI Editor II.
Date Deposited: 22 Oct 2020 12:32
Last Modified: 22 Oct 2020 12:32
URI: https://eprints.eudl.eu/id/eprint/726

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