Distributed $H_\infty$ Secure Fusion Estimation for Energy-Constrained Multi-Sensor Systems Under Hybrid Attacks
Haiyu Song, Linyi Chen, Bo Chen, Wen‐An Zhang, Li Juan Yu · IEEE Transactions on Signal and Information Processing over Networks · 2025
This paper investigates the distributed$H_{\infty }$secure fusion estimation problem for energy-constrained multi-sensor systems subject to hybrid attacks. Given the limited energy supply, sensor nodes operate in two modes: high-energy mode, which ensures robust security during information transmission, and low-energy mode, which makes transmissions more vulnerable to hybrid attacks. The phenomenon of hybrid attacks is described as the stochastic occurrence of false data injection (FDI) and denial-of-service (DoS) attacks in the communication channels from sensors to local estimators. To handle these challenges, we propose a novel distributed$H_{\infty }$secure fusion estimation model designed specifically for energy-constrained multi-sensor systems under hybrid attacks scenarios. Subsequently, sufficient conditions are derived to ensure that the secure fusion estimation error system achieves exponential mean-square stability and$H_{\infty }$performance level. Additionally, the design of optimal fusion weight matrices is addressed. Finally, the effectiveness of the proposed distributed$H_{\infty }$secure fusion estimation method is demonstrated through an illustrative example.