Stabilisation of randomly sampled unmanned surface vehicles under energy-harvesting-powered deception attacks

This paper addresses the secure control problem for a class of randomly sampled networked unmanned surface vehicles (USVs) subject to energy-harvesting-powered deception attacks. Specifically, the system suffers from stochastic perturbations in sampling intervals, while simultaneously being vulnerable to deception attacks powered by ambient energy harvesting. A discrete-time stochastic system model is developed to capture the explicit effects of both the deception attacks and noisy sampling intervals. Furthermore, the attacker's energy dynamics are modelled as a stochastic process, based on which the probability of successful attacks is derived. Building on the above results, an LMI-based secure controller synthesis scheme is further proposed to guarantee the mean-square stability of the studied system under energy-harvesting-powered deception attacks. Finally, numerical simulations are carried out to validate the developed method, demonstrating its effectiveness in safeguarding networked USV systems against such malicious attacks.