A Defense Strategy for UAV Swarm Against GNSS Spoofing Attacks Based on Game Model

Addressing the defense problem against GNSS spoofing attacks faced by UAV swarms in long-distance transportation missions, this study considers the asymmetry between the swarm and the attacker in realistic victim scenarios. A modeling of the operational environment for the UAV swarm is established, and a collaborative defense strategy based on the Stackelberg game model with opaque utility and unequal information is proposed. In this approach, the swarm acts as follower and responds to the attacker’s decision actions. Both the attacker and the swarm calculate their attack and defensive utilities based on the available information and make action decisions accordingly. Experimental results demonstrate that the defense strategy based on the Stackelberg game model effectively mitigates the negative impacts caused by malicious attacks on the swarm. Furthermore, compared to random decision model, PSO model and the APF model with special conditions, results show that the game model exhibits favorable performance in terms of distance error, maximum drift, hijacking probability and other metrics, confirming the effectiveness of the proposed algorithm.