Comparison of ensemble simple feedforward neural network and deep learning neural network on phishing detection

Gan Kim Soon and Chiang L.C. and Chin Kim On and Nordaliela Mohd Rusli and Tan Soo Fun (2020) Comparison of ensemble simple feedforward neural network and deep learning neural network on phishing detection.

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Abstract

Phishing attack is one of wide spread cybercrimes due to the advancement of the Internet. There are many forms of phishing attack and the most common one is through email. The attacker tries to pretend by sending email from an official organization or body to deceive the user in giving in their credential user name and password. The username and password are then used for malicious purpose. Many methods have been used to detect these phishing attacks; however, the attack evolved too quickly to be solved by manual approach. Therefore, automated phishing detection through artificial intelligence approach would be more feasible. In this paper, a comparison study for phishing detection between two neural networks which are the feed forward neural network and the deep learning neural network is carried out. The result is empirically evaluated to determine which method performs better in phishing detection.

Item Type:	Proceedings
Keyword:	Deep learning neural network , Feedforward neural network , Phishing attack
Subjects:	T Technology > T Technology (General) T Technology > TK Electrical engineering. Electronics Nuclear engineering
Department:	FACULTY > Faculty of Computing and Informatics
Depositing User:	DG MASNIAH AHMAD -
Date Deposited:	06 Jul 2021 11:18
Last Modified:	06 Jul 2021 11:18
URI:	https://eprints.ums.edu.my/id/eprint/27632

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