Distributed Kalman Consensus Filtering over Wireless Sensor Networks with FDI Attacks

This paper is concerned with the distributed state estimation problem for wireless sensor networks with false data injection (FDI) attacks. A residual-based detector is designed to detect whether the attacks occur. Based on the detection information, a distributed Kalman consensus filter is established against FDI attacks where sensor nodes share the local information obtained by performing the local Kalman filtering. Sufficient conditions are provided to guarantee the stability of the proposed distributed estimator. Finally, the effectiveness of the proposed method is illustrated by a numerical simulation.