Skip to content
AI Atlas
PaperActive

Learning Intrusion Response Strategies for OT Systems

arxiv.org/abs/2609.10298

quality89

Updated 5 h ago · first seen 11 Sept 2026

paper_01M294GNE4H20KV50EFNX8T4Q5

Published
11 Sept 2026
T1 · 5 h ago
arXiv
2609.10298
T1 · 5 h ago
Category
cs.CR
T1 · 5 h ago

As of

Rewind the record: see this entity's attributes exactly as AI Atlas knew them on a given day.

Claim history

9 claims · 9 properties

Official pageofficial_url1

Claim history for Official page
ValueValid from → toStatusSourceConfidenceExtractor
https://arxiv.org/abs/2609.10298currentcurrentarXiv (Atom API + RSS)T1highdeterministic

Abstractabstract1

Claim history for Abstract
ValueValid from → toStatusSourceConfidenceExtractor
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 observability that is based on traffic measurements. This approach allows us to develop tractable, learning-based solution methods for automated intrusion response, which are based on PPO. We evaluate the obtained response strategies on an emulated OT system and find that they are effective against several types of MITRE attacks for the studied use case.currentcurrentarXiv (Atom API + RSS)T1highdeterministic

Arxiv announce typearxiv_announce_type1

Claim history for Arxiv announce type
ValueValid from → toStatusSourceConfidenceExtractor
crosscurrentcurrentarXiv (Atom API + RSS)T1highdeterministic

arXiv idarxiv_id1

Claim history for arXiv id
ValueValid from → toStatusSourceConfidenceExtractor
2609.10298currentcurrentarXiv (Atom API + RSS)T1highdeterministic

Authorsauthors1

Claim history for Authors
ValueValid from → toStatusSourceConfidenceExtractor
Duc Huy Le, Rolf StadlercurrentcurrentarXiv (Atom API + RSS)T1highdeterministic

Categoriescategories1

Claim history for Categories
ValueValid from → toStatusSourceConfidenceExtractor
cs.CR, cs.AIcurrentcurrentarXiv (Atom API + RSS)T1highdeterministic

PDFpdf_url1

Claim history for PDF
ValueValid from → toStatusSourceConfidenceExtractor
https://arxiv.org/pdf/2609.10298currentcurrentarXiv (Atom API + RSS)T1highdeterministic

Primary categoryprimary_category1

Claim history for Primary category
ValueValid from → toStatusSourceConfidenceExtractor
cs.CRcurrentcurrentarXiv (Atom API + RSS)T1highdeterministic

Publishedpublished_at1

Claim history for Published
ValueValid from → toStatusSourceConfidenceExtractor
11 Sept 2026currentcurrentarXiv (Atom API + RSS)T1highdeterministic

Claims are temporal and append-only: a new observation closes the previous claim (valid_to) instead of overwriting it. Conflicting claims from different sources are kept side by side and flagged — never averaged. Methodology →