A Review on Supervised Machine Learning Techniques for Enhancing Cyber Threat Prediction Accuracy
Experimental results demonstrate that an ensemble-optimized model achieves improved predictive accuracy, reduced false positives, and enhanced generalization to unseen attack patterns, providing a scalable and adaptive defense against evolving cyber threats in online banking.