Cybersecurity risk analysis model using fault tree analysis and fuzzy decision theory
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DOI: 10.1016/j.ijinfomgt.2018.08.008
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Cited by:
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- Rodrigues, Ana Rita D. & Ferreira, Fernando A.F. & Teixeira, Fernando J.C.S.N. & Zopounidis, Constantin, 2022. "Artificial intelligence, digital transformation and cybersecurity in the banking sector: A multi-stakeholder cognition-driven framework," Research in International Business and Finance, Elsevier, vol. 60(C).
- Hooks, D. & Davis, Z. & Agrawal, V. & Li, Z., 2022. "Exploring factors influencing technology adoption rate at the macro level: A predictive model," Technology in Society, Elsevier, vol. 68(C).
- Alanen, Jarmo & Linnosmaa, Joonas & Malm, Timo & Papakonstantinou, Nikolaos & Ahonen, Toni & Heikkilä, Eetu & Tiusanen, Risto, 2022. "Hybrid ontology for safety, security, and dependability risk assessments and Security Threat Analysis (STA) method for industrial control systems," Reliability Engineering and System Safety, Elsevier, vol. 220(C).
- Ben Krishna & Satish Krishnan & M. P. Sebastian, 2023. "Examining the Relationship between National Cybersecurity Commitment, Culture, and Digital Payment Usage: An Institutional Trust Theory Perspective," Information Systems Frontiers, Springer, vol. 25(5), pages 1713-1741, October.
- Liseth Contreras Hernandez & Hanser S. Jiménez G. & Priscilla P. L. Dantas & Cristiano A. V. Cavalcante, 2022. "Using multi-criteria decision making for selecting picking strategies," Operational Research, Springer, vol. 22(4), pages 3265-3290, September.
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Keywords
Cybersecurity; Information security; Risk analysis model; Fuzzy decision theory; Fault tree analysis;All these keywords.
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