Detection of Network Irregularities Using Machine Learning Techniques
The proposed BAT framework achieves superior classification accuracy of 96%, effectively combining feature-level attention with gradient-boosted ensemble learning to improve detection precision, reduce manual feature engineering, and handle diverse attack categories including DoS, Probe, R2L, and U2R.