Joint attack detection and secure state estimation of cyber‐physical systems

Forti, Nicola; Battistelli, Giorgio; Chisci, Luigi; Sinopoli, Bruno

doi:10.1002/rnc.4724

Title: Joint attack detection and secure state estimation of cyber‐physical systems

Journal Article · Thu Aug 29 00:00:00 EDT 2019 · International Journal of Robust and Nonlinear Control

DOI:https://doi.org/10.1002/rnc.4724· OSTI ID:1564494

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^[2]; Sinopoli, Bruno ^[3]

Dipartimento di Ingegneria dell'Informazione Università di Firenze Firenze Italy, NATO‐STO Centre for Maritime Research and Experimentation (CMRE) viale San Bartolomeo 400 19126 La Spezia Italy
Dipartimento di Ingegneria dell'Informazione Università di Firenze Firenze Italy
Department of Electrical and Systems Engineering Washington University in St. Louis St. Louis Missouri

Summary This paper deals with secure state estimation of cyber‐physical systems subject to switching (on/off) attack signals and injection of fake packets (via either packet substitution or insertion of extra packets). The random set paradigm is adopted in order to model, via random finite sets (RFSs), the switching nature of both system attacks and the injection of fake measurements. The problem of detecting an attack on the system and jointly estimating its state, possibly in the presence of fake measurements, is then formulated and solved in the Bayesian framework for systems with and without direct feedthrough of the attack input to the output. This leads to the analytical derivation of a hybrid Bernoulli filter (HBF) that updates in real time the joint posterior density of a Bernoulli attack RFS and of the state vector. A closed‐form Gaussian mixture implementation of the proposed HBF is fully derived in the case of invertible direct feedthrough. Finally, the effectiveness of the developed tools for joint attack detection and secure state estimation is tested on two case studies concerning a benchmark system for unknown input estimation and a standard IEEE power network application.

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Sponsoring Organization:: USDOE

Grant/Contract Number:: OE0000779

OSTI ID:: 1564494

Journal Information:: International Journal of Robust and Nonlinear Control, Journal Name: International Journal of Robust and Nonlinear Control Vol. 30 Journal Issue: 11; ISSN 1049-8923

Publisher:: Wiley Blackwell (John Wiley & Sons)Copyright Statement

Country of Publication:: United Kingdom

Language:: English

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Cited by: 14 works

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