An encoding mechanism for secrecy of remote state estimation

Abstract

We consider a secure remote state estimation problem where the observations transmitted from the sensors to a remote estimator could be intercepted by an eavesdropper. To prevent the eavesdropper from acquiring the system states, we propose an encoding–decoding mechanism by combining linear transformation and artificial noise to ensure the exact values of observations unavailable to the eavesdropper but available to the estimator. Further, we propose an algorithm by which the eavesdropper may infer the approximate values of the observations and thus to further estimate the system states. We reveal how the amplitude of the artificial noise affects the accuracy of the eavesdropper inference, which helps the designing of the encoding–decoding mechanism. Simulation experiments are conducted to verify the derived results.