2nd International Conference on Materials Science and Sustainable Manufacturing Technology
E-mail Spam Detection and Phishing link Detection Using Machine Learning
Keerthika J, Adisvara A, Akash S, Jayanesh B, Arul Prakash T, Department of Computer Science and Engineering, Sri Eshwar College of Engineering, Coimbatore, India.
Phishing, which tricks individuals into revealing delicatedata like login credentials and financial details, is the
most widespread type of cybercrime. Attackers typically use electronic mail, prompt messaging, and telephone calls to
initiate these attacks. Despite ongoing efforts to prevent phishing attacks, current measures are not entirely effective, as
the amount of phishing emails has enlarged significantly in current years. While numerous methods have been developed
to filter out phishing emails, there is still a need for a comprehensive solution. This survey is the first of its kind to
examine the use of N-L-P and ML methods for identifying phishing electronic mail. The analyzesof state_of_the_art N-
L-P approaches that are presently being used to detect phishing electronic mail at different periods of the outbreak, with a
focus on M-L methods. These methods are compared and evaluated in-depth.
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Cite this article
Keerthika J, Adisvara A, Akash S, Jayanesh B, Arul Prakash T, “E-mail Spam Detection and Phishing link Detection Using Machine Learning”, Advances in Computational Intelligence in Materials Science, pp. 047-053, May. 2023. doi:10.53759/acims/978-9914-9946-9-8_9
