A proportional-integral observer protocol for secure communication

Other authors

Universitat Politècnica de Catalunya. Departament d'Enginyeria de Sistemes, Automàtica i Informàtica Industrial

Universitat Politècnica de Catalunya. SAC - Sistemes Avançats de Control

Publication date

2024

Abstract

In this work, we present a novel observer-based masking protocol in order to secure the communication between nodes of a cyber-physical system. The approach is based on including multiplicative disturbances generated from a known autonomous system in the source node and then including an observer in the receiver node that exactly removes the noise and recovers the original signal. It is shown that, if the masking signal is appropriately designed, the de-masking module can be implemented through a simple proportional-integral observer. The approach is then validated through numerical simulations.


This research this initiative is carried out within the framework of the EU-funded Recovery, Transformation and Resilience Plan (Next Generation) thorugh the project ACROBA and the Spanish Ministry of Universities funded by the European Union - NextGenerationEU (2022UPC-MSC-93823). This work is part of the Project MAFALDA (PID2021-126001OB-C31) funded by MCIN/ AEI /10.13039/501100011033 and by ”ERDF A way of making Europe”. This work is part of the project MASHED (TED2021- 129927B-I00), funded by MCIN/ AEI/10.13039/501100011033 and by the European Union Next GenerationEU/PRTR.


Peer Reviewed


Postprint (published version)

Document Type

Conference report

Language

English

Publisher

Elsevier

Related items

https://www.sciencedirect.com/science/article/pii/S2405896324007973

info:eu-repo/grantAgreement/AEI/Plan Estatal de Investigación Científica y Técnica y de Innovación 2021-2023/PID2021-126001OB-C31/ES/ESTIMACION Y CONTROL EN BATERIAS DE FLUJO REDOX DE VANADIO/

info:eu-repo/grantAgreement/AEI/Plan estatal de investigación científica y técnica y de innovación 2021-2023/TED2021-129927B-I00

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Rights

http://creativecommons.org/licenses/by-nc-nd/4.0/

Open Access

Attribution-NonCommercial-NoDerivatives 4.0 International

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E-prints [73026]