Adversarial Robustness of Deep Learning-Based Intrusion Detection Systems: A Systematic Literature Review of Attacks, Defenses, Datasets, and Open Challenges
Deep learning has become the default approach for modern intrusion detection. However, the same models that classify benign and malicious traffic with very high accuracy can be fooled by small, deliberately crafted perturbations. We report a systematic literature review of how this vulnerability has been studied in dee...