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Seemingly robust ML-based network intrusion detection systems crumble when attacked with realistic, host-space perturbations, like a single-character change in a command string.
NIDS research is often disconnected from real-world deployments because it overlooks fundamental characteristics of these systems, like the impact of compromised components and the need for realistic evaluation environments.