- PressAcademia Procedia
- Vol: 5 Issue: 1
- DETECTING PHISHING WEBSITES USING SUPPORT VECTOR MACHINE ALGORITHM
DETECTING PHISHING WEBSITES USING SUPPORT VECTOR MACHINE ALGORITHM
Authors : Dogukan AKSU, Abdullah ABDULWAKİL, M. Ali AYDİN
Pages : 139-142
Doi:10.17261/Pressacademia.2017.582
View : 6 | Download : 2
Publication Date : 2017-06-30
Article Type : Research
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