Strategic Interactions in Multi-Sensor Networks Against False Data Injection

Ensuring secure and efficient data transmission in large-scale remote sensing is a critical challenge. We employ game theory to model the strategic interaction between multiple sensors, which independently optimize their data transmission, and an attacker seeking to maximize disruption. Each agent shapes its strategy through resource allocation constraints and cost functions associated with transmission and attack efforts. We seek to derive a Nash equilibrium that characterizes the optimal strategies of both transmitters and attacker. By solving Karush-Kuhn-Tucker (KKT) conditions, we obtain analytical equilibrium solutions between transmission efficiency and attack resilience. Our analysis highlights key trade-offs: increasing a sensor transmission cost reduces its activity rate but makes it a more attractive target for attacks, leading to a redistribution of adversarial efforts. Conversely, higher attack costs discourage malicious interference, prompting strategic adjustments in both transmission and defense mechanisms. These findings provide insights to enhance network resilience against strategic adversaries.