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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)
  • Received : 2022.05.05
  • Published : 2022.05.30

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

Acknowledgement

First and foremost praise is to Allah. his constant grace and mercy were with us during life and throughout this project duration. we are extremely grateful to our parents for their love and continued support in preparing for my future. we would like to thank the Department of Computer Science & information, Majmaah University for their constant support, guidance, and encouragement. We appreciate the discussions, suggestions, criticism, and support of our colleagues, and friends, We would also like to thank them for all the aspects that facilitated the smooth work of my project. Finally, we owe everything to our family who at every point of our personal and academic life, supported and motivated us, and longed to see this accomplishment come true.

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