Safety Impact Analysis Considering Physical Failures and Cyber-Attacks for Mechanically Pumped Loop Systems (MPLs).

cyber-attack mechanically pumped loop systems physical failure safety impact analysis

Journal

Sensors (Basel, Switzerland)
ISSN: 1424-8220
Titre abrégé: Sensors (Basel)
Pays: Switzerland
ID NLM: 101204366

Informations de publication

Date de publication:
24 Jun 2022
Historique:
received: 26 05 2022
revised: 17 06 2022
accepted: 23 06 2022
entrez: 9 7 2022
pubmed: 10 7 2022
medline: 14 7 2022
Statut: epublish

Résumé

As complex systems composed of physical and cyber components, mechanically pumped loop systems (MPLs) are vulnerable to both passive threats (e.g., physical failures) and active threats such as cyber-attacks launched on the network control systems. The impact of the aforementioned two threats on MPL operations is yet unknown, and there is no practical way to evaluate their severity. To assess the severity of the impact of physical failures and cyber-attacks on MPLs, a safety impact analysis framework based on Elman Neural Network (ENN) observers and the Gaussian Mixture Model (GMM) algorithm is suggested. The framework discusses three common attack and failure modes: sensor hard failure that occurs suddenly, sensor soft failure that occurs gradually over time, and denial-of-service (DoS) attacks that prevent communication between the controller and valve. Both sensor failures and DoS attacks render the system unsafe, according to simulation data. In comparison to DoS attacks, however, sensor failures, particularly soft failures, inflict the greatest harm to the MPLs. Furthermore, sensors engaged in global control, rather than those involved in local control, need additional protection.

Identifiants

pubmed: 35808275
pii: s22134780
doi: 10.3390/s22134780
pmc: PMC9269518
pii:
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Références

Philos Trans A Math Phys Eng Sci. 2016 Apr 13;374(2065):20150202
pubmed: 26953178
ACM Comput Surv. 2018;51:
pubmed: 31092968
Entropy (Basel). 2020 Jan 06;22(1):
pubmed: 33285846

Auteurs

Wenbo Wu (W)

Technology and Engineering Center for Space Utilization, Chinese Academy of Sciences, Beijing 100094, China.
The Key Laboratory of Space Utilization, 9 Dengzhuang South Road, Haidian Distirct, Beijing 100094, China.

Lu Zhang (L)

Technology and Engineering Center for Space Utilization, Chinese Academy of Sciences, Beijing 100094, China.
The Key Laboratory of Space Utilization, 9 Dengzhuang South Road, Haidian Distirct, Beijing 100094, China.

Hongyong Fu (H)

Technology and Engineering Center for Space Utilization, Chinese Academy of Sciences, Beijing 100094, China.
The Key Laboratory of Space Utilization, 9 Dengzhuang South Road, Haidian Distirct, Beijing 100094, China.

Ke Wang (K)

Technology and Engineering Center for Space Utilization, Chinese Academy of Sciences, Beijing 100094, China.
The Key Laboratory of Space Utilization, 9 Dengzhuang South Road, Haidian Distirct, Beijing 100094, China.

Xuzhi Li (X)

Technology and Engineering Center for Space Utilization, Chinese Academy of Sciences, Beijing 100094, China.
The Key Laboratory of Space Utilization, 9 Dengzhuang South Road, Haidian Distirct, Beijing 100094, China.

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Classifications MeSH