PDMLP: Phishing Detection Using Multilayer Perceptron

International Journal of Network Security & Its Applications (IJNSA) Vol. 12, No.3, May 2020

14 Pages Posted: 20 Aug 2020

See all articles by Saad Al-Ahmadi

Saad Al-Ahmadi

King Saud University - College of Computer and Information Sciences

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Date Written: 2020

Abstract

A phishing website is a significant problem on the internet. It’s one of the Cyber-attack types where attackers try to obtain sensitive information such as username and password or credit card information. The recent growth in deploying a Detection phishing URL system on many websites has resulted in a massive amount of available data to predict phishing websites. In this paper, we purpose a new method to develop a phishing detection system called phishing detection based on a multi-layer perceptron (PDMLP), which used on two types of datasets. The performance of these mechanisms evaluated in terms of Accuracy, Precision, Recall, and F-measure. Results showed that PDMLP provides better performance in comparison to KNN, SVM, C4.5 Decision Tree, RF, and RoF to classifiers.

Keywords: MLP, Phishing, Machine Learning, Features

Suggested Citation

Al-Ahmadi, Saad, PDMLP: Phishing Detection Using Multilayer Perceptron (2020). International Journal of Network Security & Its Applications (IJNSA) Vol. 12, No.3, May 2020, Available at SSRN: https://ssrn.com/abstract=3624621

Saad Al-Ahmadi (Contact Author)

King Saud University - College of Computer and Information Sciences

Riyadh
Saudi Arabia

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