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Hierarchical Clustering Detection Based Secure Fusion Filtering for Multiple False Data Injection Attacks

This paper concerns the secure fusion filtering under multiple false data injection attack scenarios. A hierarchical clustering based secure fusion filtering approach is proposed for the remote-measuring system with a known secure node. The fusion filtering approach includes two parts. In the local filtering part, the remote measurement is utilized to estimate the system sate locally, after detected by Chi-square detector. In the distributed fusion part, a novel hierarchical clustering detection based distributed fusion method is provided to obtain the final fusion filtering results. The simulation results are presented to illustrate the effectiveness of the proposed approach.