Detecting phishing website with machine learning

Abstract

Attacks are many types to disturb the network or any other websites. Phishing attacks (PA) are a type of attacks which attack the website and damage the website and may lose the data. Many types of research have been done to prevent the attacks. To overcome this, in this paper, the integrated phishing attack detection system which is adopted with SVM classifier is implemented to detect phishing websites. Phishing is the cyber attack that will destroy the website and may attack with the virus. There are two parameters that can detect the final phishing detection rate such as Identity, and security. Phishing attacks also occur in various banking and e-commerce websites. This paper deals with the UCL machine learning phishing dataset which consists of 32 attributes. The proposed algorithm implements on this dataset and shows the performance.