Lightweight Deep Learning Model and Genetic Algorithm Based Optimal Phishing Website Detection
Brij Bhooshan Gupta, Akshat Gaurav, Priyanka Chaurasia, Kwok Tai Chui · 2024
Phishing attacks, exploiting human vulnerabilities to steal sensitive information, pose a persistent threat in cybersecurity. Traditional detection methods, often computationally intensive, struggle to keep pace with evolving cybercriminal tactics. Our study presents a novel detection approach using a genetic algorithm for optimal feature selection and a lightweight deep learning model for classification. Leveraging the DEAP library, the algorithm reduced 31 features to 9 critical ones, boosting model efficiency. The model achieved high precision rates—0.97 for normal and 0.81 for phishing sites—highlighting the effectiveness of integrating genetic algorithms with deep learning for enhanced, efficient phishing detection.