{"title":"PDMLP: Phishing Detection using Multilayer Perceptron","authors":"Saad Al-Ahmadi, Tariq Lasloum","doi":"10.5121/ijnsa.2020.12304","DOIUrl":null,"url":null,"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.","PeriodicalId":93303,"journal":{"name":"International journal of network security & its applications","volume":"9 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2020-05-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"14","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"International journal of network security & its applications","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.5121/ijnsa.2020.12304","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 14
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.