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As healthcare systems utilize cloud technologies to manage patient data, integrating cybersecurity becomes urgent. Threat intelligence and cloud trust models are vital in safeguarding healthcare infrastructures against evolving cyber threats, data breaches, and compliance risks. By using real-time threat detection, risk assessment frameworks, and trust-based access controls, healthcare organizations can enhance their resilience while maintaining confidentiality, integrity, and availability of medical information. Further exploration into the integration of threat intelligence with cloud trust models may create a more secure and trustworthy digital environment for modern healthcare delivery. Threat Intelligence and Cloud Trust Models for Healthcare Security explores the landscape of healthcare systems powered by the Internet of Things (IoT). It examines the emerging security threats targeting healthcare IoT (HIoT) infrastructure and proposes intelligent threat detection frameworks and trust models tailored for secure cloud integration. This book covers topics such as machine learning, data science, and cloud computing, and is a useful resource for medical and healthcare professionals, engineers, academicians, researchers, and data scientists.
