Explainable and perturbation-resilient model for cyber-threat detection in industrial control systems Networks
Abstract Deep learning-based intrusion detection systems (DL-IDS) have proven effective in detecting cyber threats.However, their vulnerability to adversarial attacks and environmental noise, particularly in industrial settings, limits practical application.Current IDS models often assume ideal conditions, overlooking noise and adversarial manipula