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Auteurs principaux: Anand, Sribalaji C., Hassan, Kamil, Sandberg, Henrik
Format: Preprint
Publié: 2025
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Accès en ligne:https://arxiv.org/abs/2503.11417
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author Anand, Sribalaji C.
Hassan, Kamil
Sandberg, Henrik
author_facet Anand, Sribalaji C.
Hassan, Kamil
Sandberg, Henrik
contents This paper considers the problem of detector tuning against false data injection attacks. In particular, we consider an adversary injecting false sensor data to maximize the state deviation of the plant, referred to as impact, whilst being stealthy. To minimize the impact of stealthy attacks, inspired by moving target defense, the operator randomly switches the detector thresholds. In this paper, we theoretically derive the sufficient (and in some cases necessary) conditions under which the impact of stealthy attacks can be made smaller with randomized switching of detector thresholds compared to static thresholds. We establish the conditions for the stateless ($χ^2$) and the stateful (CUSUM) detectors. The results are illustrated through numerical examples.
format Preprint
id arxiv_https___arxiv_org_abs_2503_11417
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle Feasibility of Randomized Detector Tuning for Attack Impact Mitigation
Anand, Sribalaji C.
Hassan, Kamil
Sandberg, Henrik
Systems and Control
This paper considers the problem of detector tuning against false data injection attacks. In particular, we consider an adversary injecting false sensor data to maximize the state deviation of the plant, referred to as impact, whilst being stealthy. To minimize the impact of stealthy attacks, inspired by moving target defense, the operator randomly switches the detector thresholds. In this paper, we theoretically derive the sufficient (and in some cases necessary) conditions under which the impact of stealthy attacks can be made smaller with randomized switching of detector thresholds compared to static thresholds. We establish the conditions for the stateless ($χ^2$) and the stateful (CUSUM) detectors. The results are illustrated through numerical examples.
title Feasibility of Randomized Detector Tuning for Attack Impact Mitigation
topic Systems and Control
url https://arxiv.org/abs/2503.11417