Email Phishing Detection Model using CNN Model

Gurumurthy, M. and Chitra, K (2024) Email Phishing Detection Model using CNN Model. Journal of Innovation and Technology, 2024 (43). pp. 1-8. ISSN 2805-5179

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Abstract

Phishing is the most common cybercrime tactic that convinces victims to divulge sensitive information, including passwords, account IDs, sensitive bank information, and dates of birth. Cybercriminals commonly use phone calls, text messages, and emails to launch these kinds of attacks. Despite continuous reworking of the tactics to keep a safe distance from these cyberattacks, the severe outcome is currently absent. However, in recent years, the number of phishing emails has increased dramatically, indicating the need for more advanced and effective ways to combat them. Although several tactics have been put in place to divert phishing emails, a comprehensive solution is still required. To the best of our knowledge, this is the first study to focus on using machine learning (ML) and natural language processing (NLP) techniques to identify phishing emails. With a focus on machine learning techniques, this research examines the many NLP techniques now in use to identify phishing emails at various stages of the attack. These methods are investigated and their comparative assessment is made. This provides an overview of the problem, its immediate workspace, and the expected implications for further research.

Item Type:	Article
Uncontrolled Keywords:	Phishing email, Machine Learning, Skip-connections
Subjects:	Q Science > QA Mathematics > QA75 Electronic computers. Computer science T Technology > T Technology (General) T Technology > TK Electrical engineering. Electronics Nuclear engineering
Depositing User:	Unnamed user with email masilah.mansor@newinti.edu.my
Date Deposited:	12 Dec 2024 09:23
Last Modified:	12 Dec 2024 09:23
URI:	http://eprints.intimal.edu.my/id/eprint/2093

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