International Journal of Network Security & Its Applications (IJNSA)
ISSN: 0974 - 9330 (Online); 0975 - 2307 (Print)
Webpage URL: https://airccse.org/journal/ijnsa.html
PDMLP: Phishing Detection using Multilayer Perceptron
Saad Al-Ahmadi and Tariq Lasloum, King Saud University, Saudi Arabia
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 multilayer 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
Original Source URL: https://aircconline.com/ijnsa/V12N3/12320ijnsa04.pdf
Volume URL: https://airccse.org/journal/jnsa20_current.html
