A Filtering Approach for Resiliency of Distributed Observers against Smart Spoofers
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For a Linear Time-Invariant (LTI) system, a network of observers is considered where through asynchronous (with bounded delay) communications, they all obtain the state variables of the LTI system. In such setting, a new type of adversarial nodes might affect the observation process by impersonating the identity of the regular nodes, which is a violation against communication authenticity. These adversaries also inherit the capabilities of Byzantine nodes making them more powerful threats called smart spoofers. We show how asynchronous networks are vulnerable to smart spoofing attack. In the estimation scheme considered in this paper, the estimated state variables are flowed from the sets of source nodes, which can detect a portion of the state variables each, to the other follower nodes. The regular nodes, to avoid getting misguided by the impersonation threats, distributively filter the extreme values received from the nodes in their neighborhood. A topological condition based on graph strong robustness is obtained to guarantee the convergence. Two simulation scenarios are provided to verify the results.
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