Attack-resilient observer pruning for path-tracking control of Wheeled Mobile Robot

TL;DR

This paper introduces an attack-resilient observer pruning method that enhances the detection and mitigation of false data injection attacks in path-tracking control systems of wheeled mobile robots, improving system security and robustness.

Contribution

It proposes a novel pruning algorithm that isolates compromised measurement channels, increasing attack localization accuracy and enhancing the resilience of the UKF observer against FDIA in WMR control.

Findings

Pruning algorithm achieves 100% attack localization accuracy with high probability.

Enhanced observer resilience demonstrated through numerical simulation.

Improved control system robustness against malicious data injections.

Abstract

Path-tracking control of wheeled mobile robot (WMR) has gained a lot of research attention, primarily because of its wide applicability -- for example intelligent wheelchairs, exploration-assistant remote WMR. Recent increase in remote and autonomous operations\requirements for WMR has led to more and more use of IoT devices within the control loop. Consequently, providing interfaces for malicious interactions through false data injection attacks (FDIA). Moreover, optimization-based FDIAs have been shown to cause catastrophic consequences in feedback control systems while by-passing any residual-based monitoring system. Since these attacks target system measurement process, this paper focuses on the problem of improving the resiliency of dynamical observers against FDIA. Specifically, we propose an attack-resilient pruning algorithm which attempts to exclude compromised channels from being processed by the observer. The proposed pruning algorithm improves attack-localization precision to $100\%$ with high probability, which correspondingly improves the resiliency of the underlying UKF to FDIA. The improvements due to the developed resilient pruning-based observer is validated through a numerical simulation of a two-layer path-tracking control platform of differential-driven wheeled mobile robot (DDWMR) under FDIA.