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 feedforward 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.
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This project is partially supported by university SBK0366-2017 research grant.
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Soon, G.K., Chiang, L.C., On, C.K., Rusli, N.M., Fun, T.S. (2020). Comparison of Ensemble Simple Feedforward Neural Network and Deep Learning Neural Network on Phishing Detection. In: Alfred, R., Lim, Y., Haviluddin, H., On, C. (eds) Computational Science and Technology. Lecture Notes in Electrical Engineering, vol 603. Springer, Singapore. https://doi.org/10.1007/978-981-15-0058-9_57
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DOI: https://doi.org/10.1007/978-981-15-0058-9_57
Publisher Name: Springer, Singapore
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