Optimized Phishing Detection through URL Analysis By a Gradient Boosting-RNN Ensemble
T Nithya, K. Sathya, KUMMARA YASWANTHKUMAR, A B Shanmathi, J Sowmya Vasuki · 2024
Phishing detection is the process of identifying and preventing illegal attempts to get private data, including passwords or bank account information, by acting to be legitimate organizations via fake websites. A Phishing detection System, is a combination machine learning approach that combines the XGBoost, CatBoost, and Long Short-Term Memory(LSTM) algorithms is proposed it is possible to identify phishing URLs from fraudulent ones, feature extraction leverages components such as URL structure duration, and domain-specific indicators. In order of precision, recall, F1-score, and accuracy measurements the combined model’s weighted stacking ensemble method performs better than traditional methods. These performance metrics, which are calculated using a dataset comprising hundreds of URLs, demonstrate the enhanced classification accuracy of the proposed model. The system’s processing efficiency and scalability enable real-time detection, accurately determining whether a URL is phishing or legitimate.