AI-Driven Phishing Detection: A Neural Network Approach for Enhanced Cybersecurity

Phishing continues to pose a significant threat to cybersecurity, exploiting social engineering to deceive users and steal sensitive data. This paper proposes a robust machine learning framework utilizing a feedforward neural network for detecting phishing attempts by analyzing features from URLs and email content. By evaluating various classification algorithms and applying extensive preprocessing, the model achieves high performance across multiple metrics, including precision, recall, F1-score, and accuracy. The results highlight the neural model’s effectiveness in distinguishing legitimate from malicious inputs, offering a scalable and intelligent solution for digital defense.