Cyber risk management: Theories, frameworks, models, and practices

Cheryl Ann Alexander, Lidong Wang

Article ID: 3118
Vol 3, Issue 1, 2025
DOI: https://doi.org/10.54517/cte3118
Received: 2 December 2024; Accepted: 7 March 2025; Available online: 14 March 2025; Issue release: 31 March 2025


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Abstract

Cyber risks have been a major concern even if more advanced technologies have been used to deter or mitigate cyberattacks. Much research has been conducted in the areas of cyber risks and cybersecurity. Handling cyber risks needs the specific support of the theories, frameworks, and models of cyber risk management. This paper introduces theories for managing cyber risks, frameworks for handling cyber risks, models for managing cyber risks, and cyber risk management and practices. Cyber risk management and threat intelligence provide their technologies and standards. Healthcare organizations must provide robust cybersecurity procedures. Big data analytics, artificial intelligence (AI)/machine learning (ML)/deep learning (DL), etc., have thus far offered significant advances in cybersecurity for healthcare agencies. This paper will also present a case study of managing cyber risks, which will demonstrate how successful these theories, frameworks, models, and practices have been in healthcare. This paper is not a more in-depth qualitative or quantitative analysis but focuses on identifying, justifying, and describing certain key issues regarding cyber risks.


Keywords

cybersecurity; cyber risks; deep learning (DL); game theoretic approach (GTA); goal and effect (G&E) model; threat intelligence; healthcare


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License URL: https://creativecommons.org/licenses/by/4.0/