Hybrid Design of Multiplicative Watermarking for Defense Against Malicious Parameter Identification

J. Zhang; Alexander J. Gallo; Riccardo M.G. Ferrari

doi:10.1109/CDC49753.2023.10383837

Hybrid Design of Multiplicative Watermarking for Defense Against Malicious Parameter Identification

J. Zhang, Alexander J. Gallo^*, Riccardo M.G. Ferrari^*

^*Corresponding author for this work

Team Riccardo Ferrari

Research output: Chapter in Book/Conference proceedings/Edited volume › Conference contribution › Scientific › peer-review

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Abstract

Multiplicative watermarking (MWM) is an active diagnosis technique for the detection of highly sophisticated attacks, but is vulnerable to malicious agents that use eaves-dropped data to identify and then remove or replicate the watermark. In this work, we propose a scheme to protect the parameters of MWM, by proposing a design strategy based on piecewise affine (PWA) hybrid dynamical systems, called hybrid multiplicative watermarking (HMWM). Due to the design decision to make certain states of the HMWM systems unobservable, we show that parameter reconstruction by an eavesdropper is infeasible, from both a computational and a system-theoretic perspective, while not altering the system's closed-loop performance.

Original language	English
Title of host publication	Proceedings of the 62nd IEEE Conference on Decision and Control (CDC 2023)
Publisher	IEEE
Pages	3858-3863
Number of pages	6
ISBN (Electronic)	979-8-3503-0124-3
DOIs	https://doi.org/10.1109/CDC49753.2023.10383837
Publication status	Published - 2023
Event	62nd IEEE Conference on Decision and Control, CDC 2023 - Singapore, Singapore Duration: 13 Dec 2023 → 15 Dec 2023

Publication series

Name	Proceedings of the IEEE Conference on Decision and Control
ISSN (Print)	0743-1546
ISSN (Electronic)	2576-2370

Conference

Conference	62nd IEEE Conference on Decision and Control, CDC 2023
Country/Territory	Singapore
City	Singapore
Period	13/12/23 → 15/12/23

Bibliographical note

Green Open Access added to TU Delft Institutional Repository 'You share, we take care!' - Taverne project https://www.openaccess.nl/en/you-share-we-take-care
Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public.

Keywords

Attack Detection
Cyber-Physical Security
Resilient Control Systems

Access to Document

10.1109/CDC49753.2023.10383837

Hybrid_Design_of_Multiplicative_Watermarking_for_Defense_Against_Malicious_Parameter_IdentificationFinal published version, 470 KB

Cite this

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title = "Hybrid Design of Multiplicative Watermarking for Defense Against Malicious Parameter Identification",

abstract = "Multiplicative watermarking (MWM) is an active diagnosis technique for the detection of highly sophisticated attacks, but is vulnerable to malicious agents that use eaves-dropped data to identify and then remove or replicate the watermark. In this work, we propose a scheme to protect the parameters of MWM, by proposing a design strategy based on piecewise affine (PWA) hybrid dynamical systems, called hybrid multiplicative watermarking (HMWM). Due to the design decision to make certain states of the HMWM systems unobservable, we show that parameter reconstruction by an eavesdropper is infeasible, from both a computational and a system-theoretic perspective, while not altering the system's closed-loop performance.",

keywords = "Attack Detection, Cyber-Physical Security, Resilient Control Systems",

author = "J. Zhang and Gallo, {Alexander J.} and Ferrari, {Riccardo M.G.}",

note = "Green Open Access added to TU Delft Institutional Repository 'You share, we take care!' - Taverne project https://www.openaccess.nl/en/you-share-we-take-care Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public.; 62nd IEEE Conference on Decision and Control, CDC 2023 ; Conference date: 13-12-2023 Through 15-12-2023",

year = "2023",

doi = "10.1109/CDC49753.2023.10383837",

language = "English",

series = "Proceedings of the IEEE Conference on Decision and Control",

publisher = "IEEE",

pages = "3858--3863",

booktitle = "Proceedings of the 62nd IEEE Conference on Decision and Control (CDC 2023)",

address = "United States",

}

Zhang, J, Gallo, AJ & Ferrari, RMG 2023, Hybrid Design of Multiplicative Watermarking for Defense Against Malicious Parameter Identification. in Proceedings of the 62nd IEEE Conference on Decision and Control (CDC 2023). Proceedings of the IEEE Conference on Decision and Control, IEEE, pp. 3858-3863, 62nd IEEE Conference on Decision and Control, CDC 2023, Singapore, Singapore, 13/12/23. https://doi.org/10.1109/CDC49753.2023.10383837

Hybrid Design of Multiplicative Watermarking for Defense Against Malicious Parameter Identification. / Zhang, J.; Gallo, Alexander J.; Ferrari, Riccardo M.G.
Proceedings of the 62nd IEEE Conference on Decision and Control (CDC 2023). IEEE, 2023. p. 3858-3863 (Proceedings of the IEEE Conference on Decision and Control).

Research output: Chapter in Book/Conference proceedings/Edited volume › Conference contribution › Scientific › peer-review

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AU - Ferrari, Riccardo M.G.

N1 - Green Open Access added to TU Delft Institutional Repository 'You share, we take care!' - Taverne project https://www.openaccess.nl/en/you-share-we-take-care Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public.

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AB - Multiplicative watermarking (MWM) is an active diagnosis technique for the detection of highly sophisticated attacks, but is vulnerable to malicious agents that use eaves-dropped data to identify and then remove or replicate the watermark. In this work, we propose a scheme to protect the parameters of MWM, by proposing a design strategy based on piecewise affine (PWA) hybrid dynamical systems, called hybrid multiplicative watermarking (HMWM). Due to the design decision to make certain states of the HMWM systems unobservable, we show that parameter reconstruction by an eavesdropper is infeasible, from both a computational and a system-theoretic perspective, while not altering the system's closed-loop performance.

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Hybrid Design of Multiplicative Watermarking for Defense Against Malicious Parameter Identification

Abstract

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Keywords

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