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Robust Conformal Intrusion Detection via Traffic-Aware Calibration and Attack-Orbit Invariance
Large language models fine-tuned for network intrusion detection emit single-point predictions without statistical validity guarantees. Conformal prediction supplies a finite-sample coverage guarantee, but a threshold calibrated on clean traffic fails once an adversary perturbs controllable network
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