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Auteurs principaux: Tian, Meiqi, Liu, Yihan, Zhong, Bingzhuo
Format: Preprint
Publié: 2026
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Accès en ligne:https://arxiv.org/abs/2605.10098
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author Tian, Meiqi
Liu, Yihan
Zhong, Bingzhuo
author_facet Tian, Meiqi
Liu, Yihan
Zhong, Bingzhuo
contents Multi-sensor integration via error-state Kalman filter (KF) is widely employed for precise state estimation in cyber-physical systems (CPSs). However, this integration exposes the system to stealthy deception attacks that render conventional detection mechanisms ineffective. We propose an exposure framework to actively reveal such stealthy attacks without modifying sensor interfaces. The framework introduces a suspect mode in which the defender injects random exposure shakes into the nominal control inputs, thus creating a discrepancy between the defender's true state estimates and the attacker's manipulated state estimates, preventing the attack from remaining stealthy. We further derive an explicit exposure condition that characterizes the minimum shake magnitude to guarantee the finite-time exposure and a compensable condition that ensures the shakes do not degrade closed-loop performance. Simulation results based on a GNSS/INS-integrated UAV system verify the effectiveness of the proposed framework.
format Preprint
id arxiv_https___arxiv_org_abs_2605_10098
institution arXiv
publishDate 2026
record_format arxiv
spellingShingle Lure-and-Reveal: An Exposure Framework for Stealthy Deception Attack in Multi-sensor Uncertain Systems
Tian, Meiqi
Liu, Yihan
Zhong, Bingzhuo
Systems and Control
Multi-sensor integration via error-state Kalman filter (KF) is widely employed for precise state estimation in cyber-physical systems (CPSs). However, this integration exposes the system to stealthy deception attacks that render conventional detection mechanisms ineffective. We propose an exposure framework to actively reveal such stealthy attacks without modifying sensor interfaces. The framework introduces a suspect mode in which the defender injects random exposure shakes into the nominal control inputs, thus creating a discrepancy between the defender's true state estimates and the attacker's manipulated state estimates, preventing the attack from remaining stealthy. We further derive an explicit exposure condition that characterizes the minimum shake magnitude to guarantee the finite-time exposure and a compensable condition that ensures the shakes do not degrade closed-loop performance. Simulation results based on a GNSS/INS-integrated UAV system verify the effectiveness of the proposed framework.
title Lure-and-Reveal: An Exposure Framework for Stealthy Deception Attack in Multi-sensor Uncertain Systems
topic Systems and Control
url https://arxiv.org/abs/2605.10098