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Publication:Sa2019BICT
Abstract The possibility of cyberattacks in Network The possibility of cyberattacks in Networked Control Systems (NCS), along with the growing use of networked controllers in industry and critical infrastructures, is motivating studies about the cybersecurity of these systems. The literature on cybersecurity of NCSs indicates that accurate and covert model-based attacks require high level of knowledge about the models of the attacked system. In this sense, recent works recognize that Bio-inspired System Identification (BiSI) attacks can be considered an effective tool to provide the attacker with the required system models. However, while BiSI attacks have obtained sufficiently accurate models to support the design of model-based attacks, they have demonstrated loss of accuracy in the presence of noisy signals. In this work, a noise processing technique is proposed to improve the accuracy of BiSI attacks in noisy NCSs. The technique is implemented along with a bio-inspired metaheuristic that was previously used in other BiSI attacks: the Backtracking Search Optimization Algorithm (BSA). The results indicate that, with the proposed approach, the accuracy of the estimated models improves. With the proposed noise processing technique, the attacker is able to obtain the model of an NCS by exploiting the noise as a useful information, instead of having it as a negative factor for the performance of the identification process. performance of the identification process.
Author Alan Oliveira de Sá + , António Casimiro + , Raphael Carlos Santos Machado + , Luiz Fernando Rust da Costa Carmo +
Booktitle Bio-inspired Information and Communication Technologies. BICT 2019.  +
Document Document for Publication-Sa2019BICT.pdf +
Editor Compagnoni A. + , Casey W. + , Cai Y. + , Mishra B. +
Key Sa2019BICT  +
Month mar  +
NumPubDate 2,019.03  +
Pages 28–38  +
Publisher Springer, Cham  +
ResearchLine Timeliness and Adaptation in Dependable Systems (TADS) +
Series Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering  +
Title Bio-inspired System Identification Attacks in Noisy Networked Control Systems  +
Type incollection  +
Url https://doi.org/10.1007/978-3-030-24202-2_3  +
Volume 289  +
Year 2019  +
Categories Publication  +
Modification dateThis property is a special property in this wiki. 25 November 2019 23:39:01  +
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