AT-IDS: An Adaptive Transformer-Based Intrusion Detection System with Dynamic Feature Learning and Dual-Path Attention
The problem of intrusion detection in networks is of major concern due to an increase in the number of sophisticated attack patterns. Typical machine learning models are limited either in terms of feature importance ranking capability or their ability to adapt to ever-changing traffic patterns in high-dimensional and c...