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Learning Intrusion Response Strategies for OT Systems

Paper recorded by Signals 4 on 2026-09-09 in cs.AI. Abstract reproduced from arXiv; link to the original below.

Published 2026-09-09 on arXiv · recorded by Signals 4 on 2026-09-10

Category: cs.AI · 人工智能 · first seen 2026-09-10

Abstract

Cyberattacks against Operational Technology (OT) systems, which monitor and control industrial processes, pose an increasing threat to essential societal services. For this reason, developing automated intrusion response strategies is highly important. In this paper, we present a formal model of an OT intrusion response use case using the POMDP framework. It includes a realistic model of partial o

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#139 most recent of 300 cs.AI papers we have recorded · ↑ newer: RiLM: Parameter-Efficient Language Modeling via Geodesic Decoding · ↓ older: GANDR: Claim Auditing for Verifiable Legal Answer Generation
Cite this page: Learning Intrusion Response Strategies for OT Systems: the #139 most recent of 300 cs.AI papers we have recorded (as of 2026-09-09). Source: Signals 4 (Signals API) — https://data.jiangzhang.ca/signals4/t/papers/learning-intrusion-response-strategies-for-ot-systems.html
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