Assessing Techniques for Reducing Cyber Risks and AI Applications
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Abstract
This paper introduces techniques specifically designed to reduce cyber risks and presents techniques for reducing cyber risks and for artificial intelligence (AI) applications in healthcare. A case study introducing the reduction of cyber risks and the use of artificial intelligence (AI)/machine learning (ML)/deep learning (DL) in healthcare is also presented. The case study includes techniques and countermeasures for reducing cyber risks and protecting data assets in the Emerald Healthcare System in the USA; provisions for giving access and extending access to suppliers and customers in the healthcare system; and the implications of outsourcing, consulting, service providers, and/or other external links that have access to privileged areas. Extended access to data will increase cyber risks. Access to privileged areas puts data at a higher cyber risk. Data encryption is necessary for important data in motion and at rest to prevent hijacked data. Cybersecurity and techniques for reducing cyber risks in this paper are significant, especially in the healthcare industry. The methodology of the case study also applies to most other healthcare systems.
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Copyright (c) 2026 Alexander CA, et al.
This work is licensed under a Creative Commons Attribution 4.0 International License.
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