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http://dx.doi.org/10.22937/IJCSNS.2022.22.5.38

Phishing Email Detection Using Machine Learning Techniques  

Alammar, Meaad (College of Science, Department of Computer Science and Information in Majmaah University)
Badawi, Maria Altaib (College of Science, Department of Computer Science and Information in Majmaah University)
Publication Information
International Journal of Computer Science & Network Security / v.22, no.5, 2022 , pp. 277-283 More about this Journal
Abstract
Email phishing has become very prevalent especially now that most of our dealings have become technical. The victim receives a message that looks as if it was sent from a known party and the attack is carried out through a fake cookie that includes a phishing program or through links connected to fake websites, in both cases the goal is to install malicious software on the user's device or direct him to a fake website. Today it is difficult to deploy robust cybersecurity solutions without relying heavily on machine learning algorithms. This research seeks to detect phishing emails using high-accuracy machine learning techniques. using the WEKA tool with data preprocessing we create a proposed methodology to detect emails phishing. outperformed random forest algorithm on Naïve Bayes algorithms by accuracy of 99.03 %.
Keywords
WEKA; Random Forest; Phishing Email; Cybersecurity; Data Mining;
Citations & Related Records
Times Cited By KSCI : 1  (Citation Analysis)
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