From Passive Monitoring to Active Defence: Resilient Control of Manipulators Under Cyberattacks

• URL: http://arxiv.org/abs/2603.13003v1
• Date: Fri, 13 Mar 2026 14:08:41 GMT
• Title: From Passive Monitoring to Active Defence: Resilient Control of Manipulators Under Cyberattacks
• Abstract summary: False data injection attacks (FDIAs) can induce substantial end-effector deviations without triggering alarms.<n>This paper studies the resilience of redundant manipulators to stealthy FDIAs and advances the architecture from passive monitoring to active defence.
• Score: 42.72791770760975
• License: http://creativecommons.org/licenses/by-nc-nd/4.0/
• Abstract: Cyber-physical robotic systems are vulnerable to false data injection attacks (FDIAs), in which an adversary corrupts sensor signals while evading residual-based passive anomaly detectors such as the chi-squared test. Such stealthy attacks can induce substantial end-effector deviations without triggering alarms. This paper studies the resilience of redundant manipulators to stealthy FDIAs and advances the architecture from passive monitoring to active defence. We formulate a closed-loop model comprising a feedback-linearized manipulator, a steady-state Kalman filter, and a chi-squared-based anomaly detector. Building on this passive monitoring layer, we propose an active control-level defence that attenuates the control input through a monotone function of an anomaly score generated by a novel actuation-projected, measurement-free state predictor. The proposed design provides probabilistic guarantees on nominal actuation loss and preserves closed-loop stability. From the attacker perspective, we derive a convex QCQP for computing one-step optimal stealthy attacks. Simulations on a 6-DOF planar manipulator show that the proposed defence significantly reduces attack-induced end-effector deviation while preserving nominal task performance in the absence of attacks.

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