A Security Posture Assessment of Industrial Control Systems Based on Evidential Reasoning and Belief Rule Base

With the rapid advancements in information technology and industrialization, the sustainability of industrial production has garnered significant attention. Industrial control systems (ICS), which encompass various facets of industrial production, are deeply integrated with the Internet, resulting i...

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Main Authors: Huishan Song, Yanbin Yuan, Yuhe Wang, Jianbai Yang, Hang Luo, Shiming Li
Format: Article
Language:English
Published: MDPI AG 2024-11-01
Series:Sensors
Subjects:
Online Access:https://www.mdpi.com/1424-8220/24/22/7135
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author Huishan Song
Yanbin Yuan
Yuhe Wang
Jianbai Yang
Hang Luo
Shiming Li
author_facet Huishan Song
Yanbin Yuan
Yuhe Wang
Jianbai Yang
Hang Luo
Shiming Li
author_sort Huishan Song
collection DOAJ
description With the rapid advancements in information technology and industrialization, the sustainability of industrial production has garnered significant attention. Industrial control systems (ICS), which encompass various facets of industrial production, are deeply integrated with the Internet, resulting in enhanced efficiency and quality. However, this integration also introduces challenges to the continuous operation of industrial processes. This paper presents a novel security assessment model for ICS, which is based on evidence-based reasoning and a library of belief rules. The model consolidates diverse information within ICS, enhancing the accuracy of assessments while addressing challenges such as uncertainty in ICS data. The proposed model employs evidential reasoning (ER) to fuse various influencing factors and derive security assessment values. Subsequently, a belief rule base is used to construct an assessment framework, grounded in expert-defined initial parameters. To mitigate the potential unreliability of expert knowledge, the chaotic mapping adaptive whale optimization algorithm is incorporated to enhance the model’s accuracy in assessing the security posture of industrial control networks. Finally, the model’s effectiveness in security assessment was validated through experimental results. Comparative analysis with other assessment models demonstrates that the proposed model exhibits superior performance in ICS security assessment.
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spelling doaj-art-7ff73f61fc5d4282b41093c0dbb223fb2025-08-20T02:27:39ZengMDPI AGSensors1424-82202024-11-012422713510.3390/s24227135A Security Posture Assessment of Industrial Control Systems Based on Evidential Reasoning and Belief Rule BaseHuishan Song0Yanbin Yuan1Yuhe Wang2Jianbai Yang3Hang Luo4Shiming Li5School of Sports Science, Harbin Normal University, Harbin 150025, ChinaSchool of Computer Science and Information Engineering, Harbin Normal University, Harbin 150025, ChinaSchool of Computer Science and Information Engineering, Harbin Normal University, Harbin 150025, ChinaSchool of Computer Science and Information Engineering, Harbin Normal University, Harbin 150025, ChinaSchool of Computer Science and Information Engineering, Harbin Normal University, Harbin 150025, ChinaSchool of Computer Science and Information Engineering, Harbin Normal University, Harbin 150025, ChinaWith the rapid advancements in information technology and industrialization, the sustainability of industrial production has garnered significant attention. Industrial control systems (ICS), which encompass various facets of industrial production, are deeply integrated with the Internet, resulting in enhanced efficiency and quality. However, this integration also introduces challenges to the continuous operation of industrial processes. This paper presents a novel security assessment model for ICS, which is based on evidence-based reasoning and a library of belief rules. The model consolidates diverse information within ICS, enhancing the accuracy of assessments while addressing challenges such as uncertainty in ICS data. The proposed model employs evidential reasoning (ER) to fuse various influencing factors and derive security assessment values. Subsequently, a belief rule base is used to construct an assessment framework, grounded in expert-defined initial parameters. To mitigate the potential unreliability of expert knowledge, the chaotic mapping adaptive whale optimization algorithm is incorporated to enhance the model’s accuracy in assessing the security posture of industrial control networks. Finally, the model’s effectiveness in security assessment was validated through experimental results. Comparative analysis with other assessment models demonstrates that the proposed model exhibits superior performance in ICS security assessment.https://www.mdpi.com/1424-8220/24/22/7135industrial control systemsbelief rule base (BRB)evidential reasoning (ER)security posture assessmentsustainable industrial productionchaotic mapping adaptive whale optimization algorithm (WOA)
spellingShingle Huishan Song
Yanbin Yuan
Yuhe Wang
Jianbai Yang
Hang Luo
Shiming Li
A Security Posture Assessment of Industrial Control Systems Based on Evidential Reasoning and Belief Rule Base
Sensors
industrial control systems
belief rule base (BRB)
evidential reasoning (ER)
security posture assessment
sustainable industrial production
chaotic mapping adaptive whale optimization algorithm (WOA)
title A Security Posture Assessment of Industrial Control Systems Based on Evidential Reasoning and Belief Rule Base
title_full A Security Posture Assessment of Industrial Control Systems Based on Evidential Reasoning and Belief Rule Base
title_fullStr A Security Posture Assessment of Industrial Control Systems Based on Evidential Reasoning and Belief Rule Base
title_full_unstemmed A Security Posture Assessment of Industrial Control Systems Based on Evidential Reasoning and Belief Rule Base
title_short A Security Posture Assessment of Industrial Control Systems Based on Evidential Reasoning and Belief Rule Base
title_sort security posture assessment of industrial control systems based on evidential reasoning and belief rule base
topic industrial control systems
belief rule base (BRB)
evidential reasoning (ER)
security posture assessment
sustainable industrial production
chaotic mapping adaptive whale optimization algorithm (WOA)
url https://www.mdpi.com/1424-8220/24/22/7135
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