Adaptive Intrusion Detection System Using Transformer-Based Neural Networks and Continual Learning Approach with Adversarial Investigation

Network intrusion detection systems IDS trained on fixed traffic snapshots decay silently after deployment as threat distributions shift. Fine-tuning models on new attacks triggers catastrophic forgetting, while retraining from scratch is computationally infeasible. Replay-based continual learnin...