Distributed H\infty Estimation Resilient to Biasing Attacks
We consider the distributed <inline-formula><tex-math notation="LaTeX">H_\infty</tex-math></inline-formula> estimation problem with an additional requirement of resilience to biasing attacks. An attack scenario is considered, where an adversary misappropriates some...
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| Vydáno v: | IEEE transactions on control of network systems Ročník 7; číslo 1; s. 458 - 470 |
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| Hlavní autor: | |
| Médium: | Journal Article |
| Jazyk: | angličtina |
| Vydáno: |
IEEE
01.03.2020
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| Témata: | |
| ISSN: | 2325-5870, 2372-2533 |
| On-line přístup: | Získat plný text |
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| Shrnutí: | We consider the distributed <inline-formula><tex-math notation="LaTeX">H_\infty</tex-math></inline-formula> estimation problem with an additional requirement of resilience to biasing attacks. An attack scenario is considered, where an adversary misappropriates some of the observer nodes and injects biasing signals into observer dynamics. This paper proposes a procedure for the derivation of a distributed observer, which endows each node with an attack detector, which also functions as an attack compensating feedback controller for the main observer. Connecting these controlled observers into a network results in a distributed observer whose nodes produce unbiased robust estimates of the plant. We show that the gains for each controlled observer in the network can be computed in a decentralized fashion, thus reducing vulnerability of the network. |
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| ISSN: | 2325-5870 2372-2533 |
| DOI: | 10.1109/TCNS.2019.2924192 |