Hybrid SMS and Email Fraud Detection using Machine Learning (Naïve Bayes + SVM)

The fake email detection system developed in this project demonstrates how machine learning can effectively help in identifying phishing and fraudulent emails. Through proper preprocessing, feature extraction, and model training, the system achieved reliable performance in detecting malicious emails. The project also showed how automated detection can reduce human effort and improve email security. At the same time, the study highlights the need for continuous improvement, as cyber attackers constantly develop new techniques to bypass security systems. Although the current model provides a strong foundation, integrating advanced algorithms and adaptive learning methods will be important for long- term effectiveness. Overall, this project offers a practical and scalable approach to improving digital communication security.

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