期刊名称：International Journal of Network Security & Its Applications
印刷版ISSN：0975-2307
电子版ISSN：0974-9330
出版年度：2020
卷号：12
期号：3
页码：59-72
DOI：10.5121/ijnsa.2020.12304
出版社：Academy & Industry Research Collaboration Center (AIRCC)
摘要：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.
