Mitigating email spam: leveraging machine learning for precise detection of fraudulent emails
P. Vasantha Lakshmi, Ratnam Dodda, V. Nithish, N. Ganesh Reddy, N. Sai Pavan Reddy · 2025
The exponential rise in internet users has led to a concurrent surge in email spam, presenting a significant challenge. Spam emails are increasingly employed for illegal activities such as phishing and fraud, posing threats to individuals and organizations alike. Spammers exploit the ease of creating fake profiles and email accounts to impersonate genuine entities, targeting unsuspecting individuals. Addressing this issue requires the identification of fraudulent spam emails. This paper focuses on utilizing machine learning techniques to discern spam emails from legitimate ones. Various machine learning algorithms are explored and applied to datasets, with emphasis on precision and accuracy to select the optimal algorithm for effective email spam detection.