Consensus-Based Distributed Estimator of Cyber-Physical Systems Against False Data Injection Attacks: A Two-Layer Estimation Approach

Abstract

The problem of consensus-based distributed estimation for cyber-physical systems (CPSs) against false data injection (FDI) attacks is taken into account. Different from most of the research perspectives, the FDI attack is modeled with high randomness in signal, target, and period, and the consensus problem with a group of sensor nodes and estimator nodes is considered in distributed estimation. An attack detector is proposed to establish the reconstructed measurement to avoid attack impact. The two-layer estimator, which includes measurement fusion estimation and interactive consensus estimation, is obtained by a strict mathematic derivation. The stability and convergence of the proposed estimator are proven by a partial differential equation and a Lyapunov function. Some numerical simulations of the 2-dimension tracking system are provided to illustrate the effectiveness of the proposed method.

Keywords: cyber-physical systems, random FDI attack, secure estimation, consensus problem