Phishing Attacks Detection by Using Support Vector Machine

Abstract

Today's world is heading towards complete digital transformation, and with all its advantages, this transformation involves many risks, the most important of which is phishing. This article proposes a system that extracts features from all parts of the email, initially brought from different data sets, and uses one of the machine learning algorithms (K-means algorithm) to extract the valuable features, as used four methods to calculate the distance in the K-means algorithm. This work used SVM as a classifier to classify emails into phishing and legitimate and tuned its parameters to obtain a high percentage of accuracy. The proposed model gave accuracy equal to 98.8 %.