AI & ML
Adaptive Dynamic Security for Operational Technology Against AI-Powered Attacks
arXiv cs.NI0 views
arXiv:2610.41007v1 Announce Type: cross Abstract: Operational technology now faces attackers whose tempo is set by AI. We present ADS-OT, an adaptive dynamic security framework modelling defensive posture as a partially observable decision problem. A reinforcement-learning policy adapts monitoring, access, deception, and segmentation under a safety-governance layer, reducing attack-path completion, detection, and containment versus static baselines.
Source：https://arxiv.org/abs/2610.41007PreviousLiHA: Worse is Better for Lightweight Hash-based Source AuthenticationNextDeepWeave: Weaving Neural and Symbolic Evidence for ML-Based Network Intrusion Detection System
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