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- W2761773886 abstract "The joint task of detecting attacks and securely monitoring the state of a cyber-physical system is addressed over a cluster-based network wherein multiple fusion nodes collect data from sensors and cooperate in a neighborwise fashion in order to accomplish the task. The attack detection–state estimation problem is formulated in the context of random set theory by representing joint information on the attack presence/absence, on the system state, and on the attack signal in terms of a hybrid Bernoulli random set (HBRS) density. Then, combining previous results on HBRS recursive Bayesian filtering with novel results on Kullback–Leibler averaging of HBRSs, a novel distributed HBRS filter is developed and its effectiveness is tested on a case study concerning wide-area monitoring of a power network." @default.
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- W2761773886 date "2018-03-01" @default.
- W2761773886 modified "2023-10-02" @default.
- W2761773886 title "Distributed Joint Attack Detection and Secure State Estimation" @default.
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- W2761773886 doi "https://doi.org/10.1109/tsipn.2017.2760804" @default.
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