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An application of DEMATEL and fuzzy DEMATEL to evaluate the interaction of safety management system and cybersecurity management system in automated vehicles. Survey Paper

  • To ensure the safety and security of Automated Vehicles (Avs), the interaction between the Functional Safety (FuSa) and the Cybersecurity (CS) domains needs to be managed systematically. There is a demand to develop effective and structured management systems to support the homologation process. From this motivation, identifying the interaction between the Safety Management System (SMS) and the Cybersecurity Management System (CSMS) is a fundamental aspect and needs to be improved for HAD systems. Hence, the classical Decision Making Trial and Evaluation Laboratory (DEMATEL) method and fuzzy DEMATEL are applied to evaluate the influential factors that can impact the safety and security of the HAD systems. This paper proposes a list of influencing factors focusing on the interaction between SMS and CSMS for HAD systems. Additionally, the results of an anonymously conducted survey among experts from industry and research are presented and used as inputs for the methods. This work helps to understand the relationship between influencingTo ensure the safety and security of Automated Vehicles (Avs), the interaction between the Functional Safety (FuSa) and the Cybersecurity (CS) domains needs to be managed systematically. There is a demand to develop effective and structured management systems to support the homologation process. From this motivation, identifying the interaction between the Safety Management System (SMS) and the Cybersecurity Management System (CSMS) is a fundamental aspect and needs to be improved for HAD systems. Hence, the classical Decision Making Trial and Evaluation Laboratory (DEMATEL) method and fuzzy DEMATEL are applied to evaluate the influential factors that can impact the safety and security of the HAD systems. This paper proposes a list of influencing factors focusing on the interaction between SMS and CSMS for HAD systems. Additionally, the results of an anonymously conducted survey among experts from industry and research are presented and used as inputs for the methods. This work helps to understand the relationship between influencing factors and provides a simplified, easy-to-visualized, and valuable guide for developing HAD systems. The result of this study shows that the most important influential factor is F13. Moreover, the cause and effect of the factors are illustrated numerically and graphically. The influential factors F1 to F7 are identified as the cause and F8 to F13 are reasoned to effect. Finally, a circular representation of the influential factors and their interaction is presented in this paper.show moreshow less

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Metadaten
Author:Marzana KhatunORCiD, Florence Wagner, Rolf Jung, Michael GlaßORCiD
DOI:https://doi.org/10.1016/j.engappai.2023.106566
Identifier:0952-1976 OPAC HS OPAC extern
Parent Title (English):Engineering Applications of Artificial Intelligence
Publisher:Elsevier Science
Place of publication:Amsterdam
Document Type:Article
Language:English
Date of Publication (online):2023/06/17
Year of first Publication:2023
Tag:Cybersecurity management system (CSMS); Decision Making Trial and Evaluation Laboratory (DEMATEL); Functional safety (FuSa); Fuzzy DEMATEL; Safety management system (SMS)
Volume:Volume 124
Issue:September 2023
Article Number:106566
Number of pages:15 Seiten
First Page:1
Last Page:15
Institutes:Fakultät Informatik
IFM - Institut für Fahrerassistenz und vernetzte Mobilität
Dewey Decimal Classification:6 Technik, Medizin, angewandte Wissenschaften / 62 Ingenieurwissenschaften
Open Access:open_access
Research focus:FSP2: Mobilität
Publication Lists:Jung, Rolf
Khatun, Marzana
Wagner, Florence
Research Project:MLPaSSAD – New Multi-Layer Platforms for Security and Safety-Relevant Automated Driving Functions
Publication reviewed:begutachtet
Licence (German):Creative Commons - CC BY - Namensnennung 4.0 International
Release Date:2023/06/20
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