TY  - JOUR
TT  - DETECTING PHISHING WEBSITES USING SUPPORT VECTOR MACHINE ALGORITHM
AU  - Aksu, Dogukan
AU  - Abdulwakil, Abdullah
AU  - Aydin, M. Ali
PY  - 2017
DA  - June
DO  - 10.17261/Pressacademia.2017.582
JF  - PressAcademia Procedia
JO  - PAP
PB  - Suat TEKER
WT  - DergiPark
SN  - 2459-0762
SP  - 139
EP  - 142
VL  - 5
IS  - 1
KW  - Cyber security
KW  - phishing
KW  - machine learning
KW  - support vector machine
KW  - matlab
N2  - Cybersecurityis one of the most important areas which aims to protect computers or computersystems, networks, programs and data from an attack such as; financial systems,biometric security systems, military systems, personal information securityetc. Nowadays, there are a lot of rule-based phishing detection systems whichare created to help people who can't understand which URL is real and which oneis fake URL address. This paper proposes a method with supervised machinelearning that classifies the URLs to legitimate and phishing. By using supportvector machine (SVM) classification, a machine-learning algorithm, with anMATLAB-based computer program to give a warning message to the users about thereliability of the web page. In this paper, phishing detection system isimplemented with SVM to avoid the internet users from becoming a victim ofphishers to do not lose financial and personal information.
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UR  - https://doi.org/10.17261/Pressacademia.2017.582
L1  - https://dergipark.org.tr/en/download/article-file/392435
ER  -