Securing the Future: AI-Driven Cybersecurity in Healthcare Data Protection
Keywords:
AI-driven cybersecurity, healthcare data protection, federated learning, anomaly detection, electronic health records, Internet of Medical Things, zero-trust architectureAbstract
The proliferation of electronic health records (EHRs), Internet of Medical Things (IoMT)devices, and interconnected hospital information systems (HIS) has exponentially increasedthe attack surface for cyber adversaries targeting healthcare infrastructure. Traditional signature-based security mechanisms
References
M. Fredrikson, S. Jha, and T. Ristenpart, "Model inversion attacks that exploit confidence information and basic countermeasures," in Proc. 22nd ACM SIGSAC Conf. Computer and Communications Security, Denver, CO, USA, Oct. 2015, pp. 1322-1333.
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Published
2023-03-15
How to Cite
Ramya Vani Rayala. (2023). Securing the Future: AI-Driven Cybersecurity in Healthcare Data Protection. Journal of Computational Analysis and Applications (JoCAAA), 31(3), 826–850. Retrieved from https://eudoxuspress.com/index.php/pub/article/view/4596
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