Studying Email Filtering Approach to Identify Spear Phishing Attacks

Abstract

Electronic mail is used daily by millions of people to communicate around the world and it is a critical application for many businesses. Because of the fame of emails, the attackers utilize it to gather the sensitive data. Beyond spam and phishing email designed to trick users into revealing personal information, spear phishing email exploits computer network and gather sensitive information from targeted network. Nowadays, detecting and filtering are still the most feasible ways for email security. This paper categorizes existing email filtering techniques and then proposes a filtering approach for spear phishing email based on Support Vector Machine (SVM) Classifier. The proposed system will use features from different literature and combination of these features together forms a feature set to identify spear phishing attacks.