Comparison of simple feedforward neural network, recurrent neural network and ensemble neural networks in phishing detection

Abstract

The internet has been one of the greatest advancements in technologies. It has brought many advantages to today's society in many domains such as e-commerce, entertainment and supply chain, amongst others. However, it is also a double-edged sword which has brought many threats to the computer systems and devices known as cyber-attack, and one of these threats would be phishing attack. A phishing attack is where the scammer tries to impose or clone the legitimate email or website in order to deceive the victim to key in their personal information such as username and password. Phishing attack has been one of the most common attacks that happens every day on the Internet especially through email. Many methods have been devised to encounter phishing attack, and one of approaches is through training and monitoring team. These manual approaches, however, are user's experience-dependent and cost-inefficient. Therefore, many have adopted AI approach instead to detect phishing attack. This paper is one of the many efforts to detect the phishing attack through email by adopting AI method. The objective of this paper is to investigate the performance of feedforward neural network, recurrent neural network and ensemble neural network in phishing email detection. The result of this comparison is empirically evaluated.