Email Phishing Detection Model using CNN Model

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.