On the Anarchy of Multiple False Data Injectors for Age of Incorrect Information in Sensor Networks
Leonardo Badia, Thomas Marchioro · 2025
Sensor networks, especially when deployed in a field with little supervision, are vulnerable to a broad range of attacks. In this paper, we study a scenario where multiple competitive adversaries inject false content in the sensed data with the intent of impairing network control. We use game theory to analyze the different behavior of adversaries acting independently or in a coordinated fashion. This analysis ultimately results in the evaluation of efficiency metrics for the utility of uncoordinated attackers, based on the Age of Incorrect Information (AoII), which is compared to the coordinated case. Our numerical results show that generally the lack of coordination is detrimental for the two attackers. With the exception of few edge cases, competition leads the attackers to be more concerned with prevailing over each other than actually compromising the system.