Assessment of Cyber Security Attacks in the Automotive Industry and Development of Strategies in a Fuzzy Environment
Abstract
The rapid digitalization of the automotive industry, accelerated by the integration of Industry 4.0 technologies and connected vehicle systems, has significantly expanded the sector's attack surface. This transformation has rendered the automotive ecosystem increasingly vulnerable to complex and multidimensional cyber threats, including ransomware attacks, data breaches, production disruptions, and supply chain infiltrations. This study aims to systematically assess these threats and to prioritize the most effective cybersecurity strategies under conditions of uncertainty. Given the lack of quantitative prioritization models in the existing literature, a comprehensive Multi-Criteria Decision-Making (MCDM) framework integrating Pythagorean Fuzzy Analytic Hierarchy Process (AHP) and Pythagorean Fuzzy Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) methods was employed. This fuzzy-based approach was adopted to minimize the subjectivity and ambiguity inherent in expert judgments and to yield more realistic outcomes. Within the scope of the study, six major cyber attack types prevalent in the sector were examined, and nine distinct defense strategies were evaluated against eight critical criteria. The Pythagorean Fuzzy AHP results revealed that "Supply Chain and Third-Party Risk Mitigation" and "Coverage Scope" constitute the most decisive factors in strategy selection. The subsequent Pythagorean Fuzzy TOPSIS ranking demonstrated that "Advanced Endpoint and Network Security" is the closest alternative to the positive ideal solution and thus the most effective strategy. Furthermore, "Real-Time Monitoring and Anomaly Detection Systems" emerged as a high-priority approach. The findings underscore the necessity of adopting proactive and holistic security architectures in the automotive sector, rather than relying on reactive measures. In conclusion, this research provides industry stakeholders with a quantitative and systematic decision support framework for optimizing cybersecurity investments and ensuring operational continuity. The findings obtained provide decision-makers with a quantitative and systematic decision support infrastructure for the prioritization of cybersecurity investments, both within the context of the Turkish automotive sector and at the global scale.
Keywords
- Cyber Threat
- Automotive Industry
- Pythagorean Fuzzy AHP
- Pythagorean Fuzzy TOPSIS
- Cybersecurity
- Supply Chain
Supporting Institution
Thanks
References
- Yeniman Yıldırım E. Cyber attacks targeting information systems and ensuring cyber security. Journal of Vocational Sciences. 2018;7(2):24-33.
- Yılmaz H. Establishment of information security management system within the scope of TS ISO/IEC 27001 information security management standard and information security risk analysis. Denetişim. 2014;(15):45-59.
- Karagöz K. The effect of automotive sector on economy in Turkey: an econometric analysis. The Journal of Van Yuzuncu Yil University Faculty of Economics and Administrative Sciences. 2021;6(12):126-143.
- Taştan NS, Taştan K. Automotive sector 2017-2023: a global analysis and Türkiye. Journal of Strategic Management Research. 2023;6(2):120-143. https://doi.org/10.54993/syad.1326969
- Presidency of the Republic of Türkiye, Strategy and Budget Office. Twelfth development plan (2024-2028) . Ankara: Presidency of the Republic of Türkiye, Strategy and Budget Office; 2023. https://www.sbb.gov.tr/wp-content/uploads/2024/06/Twelfth-Development-Plan_2024-2028.pdf
- Özarpa C, Avcı İ. Industry 4.0 and cybersecurity at automobile manufacturing in smart factories. Duzce University Journal of Science and Technology. 2022;10(4):2120-2132. https://doi.org/10.29130/dubited.1027236
- Bakioğlu G, Atahan AO. AHP integrated TOPSIS and VIKOR methods with Pythagorean fuzzy sets to prioritize risks in self-driving vehicles. Appl Soft Comput. 2021;99:106948. https://doi.org/10.1016/j.asoc.2020.106948
- Ayhan MB. A fuzzy AHP approach for supplier selection problem: a case study in a gearmotor company. Int J Manag Value Supply Chains. 2013;4(3):11-23. https://doi.org/10.5121/ijmvsc.2013.4302
Details
Primary Language
English
Subjects
Automotive Safety Engineering
Journal Section
Research Article
Authors
Özge Doğan
0009-0000-8792-9944
Türkiye
Ahmet Mesut Özer
0009-0001-9487-3798
Türkiye
Yusuf Bera Sanlı
0009-0003-7577-6671
Türkiye
Tamer Eren
*
0000-0001-5282-3138
Türkiye
Publication Date
September 2, 2026
Submission Date
February 2, 2026
Acceptance Date
August 12, 2026
Published in Issue
Year 2026 Volume: 10 Number: 3
