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Bank of Models: Sensor Attack Detection and Isolation in Industrial Control Systems

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Critical Information Infrastructures Security (CRITIS 2021)

Part of the book series: Lecture Notes in Computer Science ((LNSC,volume 13139))

Abstract

Attacks on sensor measurements can take the system to an unwanted state. The disadvantage of using a system model-based approach for attack detection is that it could not isolate which sensor was under attack. For example, if one of two sensors that are physically coupled is under attack, the attack would reflect in both. In this work, we propose an attack detection and isolation technique using a multi-model framework named Bank of Models (BoM) in which the same process will be represented by multiple system models. This technique can achieve higher accuracy for attack detection with low false alarm rates. We make extensive empirical performance evaluation on a realistic ICS testbed to demonstrate the viability of this technique.

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Acknowledgements

This research is supported by the National Research Foundation, Singapore, under its National Satellite of Excellence Programme “Design Science and Technology for Secure Critical Infrastructure” (Award Number: NSoE_DeST-SCI2019-0002). Any opinions, findings and conclusions or recommendations expressed in this material are those of the author(s) and do not reflect the views of National Research Foundation, Singapore.

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Correspondence to Chuadhry Mujeeb Ahmed .

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Ahmed, C.M., Zhou, J. (2021). Bank of Models: Sensor Attack Detection and Isolation in Industrial Control Systems. In: Percia David, D., Mermoud, A., Maillart, T. (eds) Critical Information Infrastructures Security. CRITIS 2021. Lecture Notes in Computer Science(), vol 13139. Springer, Cham. https://doi.org/10.1007/978-3-030-93200-8_1

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  • DOI: https://doi.org/10.1007/978-3-030-93200-8_1

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