Marco Ehrlich, Andre Bröring, C. Diedrich, J. Jasperneite
{"title":"Towards automated risk assessments for modular manufacturing systems","authors":"Marco Ehrlich, Andre Bröring, C. Diedrich, J. Jasperneite","doi":"10.1515/auto-2022-0098","DOIUrl":null,"url":null,"abstract":"Abstract Manufacturing systems based on Industry 4.0 concepts provide a greater availability of data and have modular characteristics enabling frequent changes. This raises the need for new security engineering concepts that cover the increasing complexity and frequency of mandatory security risk assessments. In contrast, the current standardization landscape used for the assessment of these systems only offers abstract, static, manual, and resource-intensive procedures. Therefore, this work proposes a method that further specifies the IEC 62443 aiming to automate the security risk assessments in such a way that manual efforts can be reduced and a consistent quality can be achieved. The methodology is presented using network segmentation as a guiding example and consists of four main steps: Information collection based on a process analysis, information formalisation with a semi-formal model, information usage applying first order logic to extract expert knowledge, and information access using the concept of the digital twin. In addition, the applicability of the IEC 62443 standard to the risk assessment of modular manufacturing systems is evaluated.","PeriodicalId":55437,"journal":{"name":"At-Automatisierungstechnik","volume":"71 1","pages":"453 - 466"},"PeriodicalIF":0.7000,"publicationDate":"2023-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"At-Automatisierungstechnik","FirstCategoryId":"94","ListUrlMain":"https://doi.org/10.1515/auto-2022-0098","RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"AUTOMATION & CONTROL SYSTEMS","Score":null,"Total":0}
引用次数: 1
Abstract
Abstract Manufacturing systems based on Industry 4.0 concepts provide a greater availability of data and have modular characteristics enabling frequent changes. This raises the need for new security engineering concepts that cover the increasing complexity and frequency of mandatory security risk assessments. In contrast, the current standardization landscape used for the assessment of these systems only offers abstract, static, manual, and resource-intensive procedures. Therefore, this work proposes a method that further specifies the IEC 62443 aiming to automate the security risk assessments in such a way that manual efforts can be reduced and a consistent quality can be achieved. The methodology is presented using network segmentation as a guiding example and consists of four main steps: Information collection based on a process analysis, information formalisation with a semi-formal model, information usage applying first order logic to extract expert knowledge, and information access using the concept of the digital twin. In addition, the applicability of the IEC 62443 standard to the risk assessment of modular manufacturing systems is evaluated.
期刊介绍:
Automatisierungstechnik (AUTO) publishes articles covering the entire range of automation technology: development and application of methods, the operating principles, characteristics, and applications of tools and the interrelationships between automation technology and societal developments. The journal includes a tutorial series on "Theory for Users," and a forum for the exchange of viewpoints concerning past, present, and future developments. Automatisierungstechnik is the official organ of GMA (The VDI/VDE Society for Measurement and Automatic Control) and NAMUR (The Process-Industry Interest Group for Automation Technology).
Topics
control engineering
digital measurement systems
cybernetics
robotics
process automation / process engineering
control design
modelling
information processing
man-machine interfaces
networked control systems
complexity management
machine learning
ambient assisted living
automated driving
bio-analysis technology
building automation
factory automation / smart factories
flexible manufacturing systems
functional safety
mechatronic systems.