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arXiv cs.CRpublished ()ingested Stefan Lenz

Poster: Towards Selecting Threat Appropriate Industrial Intrusion Detection Systems

infoResearchimportance 12
AI summary · glm-5.3

Poster proposes counter-threat-intelligence-based detector selection for industrial control systems, showing IDS performance varies strongly by attack scenario.

The poster proposes a counter-threat intelligence sharing mechanism to select appropriate intrusion detection systems for the current threat situation in industrial control system environments. Attack-level performance evaluations of various IDSs show detection performance varies depending on the attack scenario. The results emphasize the benefit of dynamically matching detectors to evolving ICS threats.

  • Proposes counter-threat-intelligence sharing to select ICS detectors for current threats
  • Attack-level evaluations show IDS detection performance varies by attack scenario
Full article88 words · extracted from arxiv.org · click to collapse

As the threat landscape against industrial control systems is dynamic, effective security requires detection strategies capable of timely reactions to these evolving threat situations. To address this problem, we propose the idea of a counter-threat intelligence sharing based mechanism to select appropriate detectors for current circumstances. To highlight the potential of this mechanism, we conduct attack-level performance evaluations of various intrusion detection systems. Results show the variance of intrusion detection performance depending on the attack scenario, emphasizing the benefits of such a mechanism for industrial control system security

Text extracted automatically; images, tables and formatting may be missing. Original: https://arxiv.org/abs/2609.12646