@article{article_371637, title={DETECTING PHISHING WEBSITES USING SUPPORT VECTOR MACHINE ALGORITHM}, journal={PressAcademia Procedia}, volume={5}, pages={139–142}, year={2017}, DOI={10.17261/Pressacademia.2017.582}, author={Aksu, Dogukan and Abdulwakil, Abdullah and Aydin, M. Ali}, keywords={Cyber security,phishing,machine learning,support vector machine,matlab}, abstract={<p class="MsoNormal" style="margin-top:0cm;margin-right:0cm;margin-bottom:.0001pt;margin-left:-.25pt;line-height:103%;"> <span style="font-size:8pt;line-height:103%;">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.  </span> </p> <p> </p>}, number={1}, publisher={Suat TEKER}