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- W2285835151 abstract "We consider the problem of robust state estimation in the presence of integrity attacks. There are $m$ sensors monitoring a dynamical process. Subject to the integrity attacks, $p$ out of $m$ measurements can be arbitrarily manipulated. The classical approach such as the MMSE estimation in the literature may not provide a reliable estimate under this so-called $(p,m)$-sparse attack. In this work, we propose a robust estimation framework where distributed local measurements are computed first and fused at the estimator based on a convex optimization problem. We show the sufficient and necessary conditions for robustness of the proposed estimator. The sufficient and necessary conditions are shown to be tight, with a trivial gap. We also present an upper bound on the damage an attacker can cause when the sufficient condition is satisfied. Simulation results are also given to illustrate the effectiveness of the estimator." @default.
- W2285835151 created "2016-06-24" @default.
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- W2285835151 date "2016-01-16" @default.
- W2285835151 modified "2023-10-18" @default.
- W2285835151 title "Robust State Estimation against Sparse Integrity Attacks" @default.
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- W2285835151 doi "https://doi.org/10.48550/arxiv.1601.04180" @default.
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