Abstract
In this paper, we mainly study the distributed estimation problem under attacks, which is mainly used to estimate an unknown parameter. To solve this problem, a correction-based secure diffusion least mean square (CS-dLMS) algorithm, which is a hybrid algorithm that composes of a non-cooperative LMS (nc-LMS) algorithm and a correction-based diffusion least-mean squares (C-dLMS) algorithm, is proposed for distributed estimation. The nc-LMS algorithm is used to provide a reliable reference system, which can detect reliable neighbor nodes by setting a threshold under network attacks. The correction-based least mean square algorithm can estimate an unknown parameter by interacting with neighbor nodes. In order to guarantee the mean performance of the CS-dLMS algorithm under attacks, a sufficient condition is proposed. Finally, simulation results are provided to verify the effectiveness of the proposed algorithm and it outperforms the C-dLMS algorithm and nc-LMS algorithm.
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