A privacy-preserving fusion filter is proposed for multi-sensor systems under multiple packet dropouts, with the legitimate user's error covariance bounded and the eavesdropper's mean estimation error divergent.
Towards invariant extended kalman filter-based resilient distributed state estimation for moving robots over mobile sensor networks under deception attacks,
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Privacy-Preserving Fusion for Multi-Sensor Systems Under Multiple Packet Dropouts
A privacy-preserving fusion filter is proposed for multi-sensor systems under multiple packet dropouts, with the legitimate user's error covariance bounded and the eavesdropper's mean estimation error divergent.