International Journal For Multidisciplinary Research

E-ISSN: 2582-2160   •   Impact Factor: 9.24

A Widely Indexed Open Access Peer Reviewed Multidisciplinary Bi-monthly Scholarly International Journal

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Volume 7 Issue 3
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MITIGATING CYBERSECURITY RISKS IN HEALTHCARE WITH AI: DEVELOPING ADAPTIVE DEFENSE MODELS AGAINST EMERGING THREATS

Author(s) Pelumi Oladokun
Country United States
Abstract The healthcare sector has become an increasingly prominent target for cyberattacks, with data breaches, ransomware incidents, and system disruptions posing severe risks to patient safety, data privacy, and organizational stability. As healthcare organizations continue to adopt emerging technologies such as telemedicine platforms, IoT-enabled medical devices, and cloud-based data systems, the attack surface expands, necessitating more adaptive and intelligent defense mechanisms. This review investigates the role of artificial intelligence (AI) in mitigating cybersecurity risks within healthcare infrastructures. It further explores the design and application of AI-powered predictive analytics for early threat detection, autonomous mitigation strategies, dynamic policy adjustments, automated network segmentation, and intelligent threat containment without disrupting critical clinical operations. Findings highlight that integrating adaptive AI systems into cybersecurity architectures enhances resilience against attack vectors, ensuring more robust protection of sensitive patient data and operational continuity. This study concludes that intelligent, self-evolving defense models are imperative for safeguarding healthcare ecosystems in an era of accelerating technological complexity and cyber threat sophistication.
Keywords AI-Powered Cybersecurity; Healthcare Data Protection; Ransomware Prevention; Predictive Cyber Risk Analytics
Field Computer > Network / Security
Published In Volume 7, Issue 3, May-June 2025
Published On 2025-06-06
DOI https://doi.org/10.36948/ijfmr.2025.v07i03.46651
Short DOI https://doi.org/g9pzwx
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