ISSN: 0974 - 9330 (Online); 0975 - 2307 (Print)
http://airccse.org/journal/ijnsa.html
PDMLP: PHISHING DETECTION USING MULTILAYER PERCEPTRON
Saad Al-Ahmadi1 and Tariq Lasloum2
1Department of Computer Science, College of Computer and Information Science, King Saud University, Riyadh, Saudi Arabia
2Department of Computer Engineering, College of Computer and Information Science, King Saud University, Riyadh, 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.
Original Source URL: https://aircconline.com/ijnsa/V12N3/12320ijnsa04.pdf
Volume Link: http://airccse.org/journal/jnsa20_current.html
http://airccse.org/journal/ijnsa.html
PDMLP: PHISHING DETECTION USING MULTILAYER PERCEPTRON
Saad Al-Ahmadi1 and Tariq Lasloum2
1Department of Computer Science, College of Computer and Information Science, King Saud University, Riyadh, Saudi Arabia
2Department of Computer Engineering, College of Computer and Information Science, King Saud University, Riyadh, 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.
Original Source URL: https://aircconline.com/ijnsa/V12N3/12320ijnsa04.pdf
Volume Link: http://airccse.org/journal/jnsa20_current.html
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