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Title |
Phishing Email Detection Using Machine Learning Techniques |
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Author |
Meaad Alammar and Maria Altaib Badawi |
| Citation |
Vol. 22 No. 5 pp. 277-283 |
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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 %. |
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Keywords |
WEKA, Random Forest, Phishing Email, Cybersecurity, Data Mining,. |
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