DETECTING PHISHING WEBSITES USING SUPPORT VECTOR MACHINE ALGORITHM

Year 2017, , 139 - 142, 30.06.2017

Dogukan Aksu Abdullah Abdulwakil M. Ali Aydin

https://doi.org/10.17261/Pressacademia.2017.582

Abstract

Cybersecurity
is one of the most important areas which aims to protect computers or computer
systems, networks, programs and data from an attack such as; financial systems,
biometric security systems, military systems, personal information security
etc. Nowadays, there are a lot of rule-based phishing detection systems which
are created to help people who can't understand which URL is real and which one
is fake URL address. This paper proposes a method with supervised machine
learning that classifies the URLs to legitimate and phishing. By using support
vector machine (SVM) classification, a machine-learning algorithm, with an
MATLAB-based computer program to give a warning message to the users about the
reliability of the web page. In this paper, phishing detection system is
implemented with SVM to avoid the internet users from becoming a victim of
phishers to do not lose financial and personal information. 

Keywords

Cyber security, phishing, machine learning, support vector machine, matlab

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