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Title

Phishing Email Detection Using Machine Learning Techniques

Author

Meaad Alammar and Maria Altaib Badawi

Citation

Vol. 22  No. 5  pp. 277-283

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 Na?ve Bayes algorithms by accuracy of 99.03 %.

Keywords

WEKA, Random Forest, Phishing Email, Cybersecurity, Data Mining,.

URL

http://paper.ijcsns.org/07_book/202205/20220538.pdf