Resilient Path Planning of UAVs against Covert Attacks on UWB Sensors

TL;DR

This paper presents a resilient UAV path planning method that minimizes energy use while defending against covert attacks on UWB sensors, using game theory and optimal control to detect and mitigate malicious sensor spoofing.

Contribution

It introduces a novel resilient navigation scheme based on Pontryagin's maximum principle that effectively counters covert sensor attacks in UAVs, formulated as a Stackelberg game.

Findings

The proposed scheme reduces deviation caused by covert attacks.

Simulation and UAV experiments validate the method's effectiveness.

The approach enhances UAV resilience against sophisticated sensor spoofing attacks.

Abstract

In this letter, a resilient path planning scheme is proposed to navigate a UAV to the planned (nominal) destination with minimum energy-consumption in the presence of a smart attacker. The UAV is equipped with two sensors, a GPS sensor, which is vulnerable to the spoofing attacker, and a well-functioning Ultra-Wideband (UWB) sensor, which is possible to be fooled. We show that a covert attacker can significantly deviate the UAV's path by simultaneously corrupting the GPS signals and forging control inputs without being detected by the UWB sensor. The prerequisite for the attack occurrence is first discussed. Based on this prerequisite, the optimal attack scheme is proposed, which maximizes the deviation between the nominal destination and the real one. Correspondingly, an energy-efficient and resilient navigation scheme based on Pontryagin's maximum principle \cite{gelfand2000calculus} is formulated, which depresses the above covert attacker effectively. To sum up, this problem can be seen as a Stackelberg game \cite{bacsar1998dynamic} between a secure path planner (defender) and a covert attacker. The effectiveness and practicality of our theoretical results are illustrated via two series of simulation examples and a UAV experiment.