Security Analysis of IoT Traffic Classification Systems Under Adversarial Machine Learning Attacks
A constraint-aware adversarially robust Internet of Things (IoT) traffic classification system with protocol validity, device behavior consistency, and manifold-aware training and evaluation is presented, demonstrating improved robustness, realism, and deployability compared to existing approaches.