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InfoResearchPeer-reviewed
Principled Uncertainty Decomposition With Bayesian Ensemble Transformers for Trustworthy Intrusion Detection
- Published
- Record updated
Summary
Researchers introduce a Bayesian ensemble transformer framework for uncertainty-aware network intrusion detection. It splits prediction uncertainty into epistemic and aleatoric components and reports F1-scores of 77.55% to 97.00% across NSL-KDD, CICIDS2017, UNSW-NB15 and SWaT, with ECE between 0.0248 and 0.2278. Under C&W and PGD attacks, performance dropped by 3.6% and 8.0%, respectively.