Traffic-Aware Randomized Smoothing for LLM-Based Network Intrusion Detection

arXiv cs.AI · 18 hours ago

Researchers developed Traffic-Aware Randomized Smoothing (TA-RS), a certified defense method for LLM-based intrusion detection systems that adds Gaussian noise only to network features attackers can control during both training and certification. The method achieved 55-100% certified accuracy on CIC-IDS-2018 and HIKARI-2021 datasets at sigma=0.25, with certified radii exceeding the baseline threshold by 1.8-5 times. This approach improves robustness against traffic manipulation attacks by aligning the noise injection with the attacker's actual capabilities rather than applying uniform noise across all features.