Endpoint Security for Healthcare Devices: Protecting Patient Data on Windows and Samsung Assets

Abstract

Purpose: This work also involves conducting an assessment and improvement of endpoint defense initiatives in healthcare facilities, especially when it comes to cybersecurity issues with Windows types of workstations and Samsung medical/mobile devices. It touches on the growing danger of cyberattacks on patient records and the healthcare system caused by digitalization in the healthcare industry.

Methodology: The study presents a mixed-methods research design, where a complete vulnerability landscape, threat vectors and endpoint security products within healthcare settings will be reviewed. It invokes both simulation-based testing and empirical analysis to check the efficacy of a suggested multi-layered endpoint security architecture that is industry-specific to Windows and Samsung devices.

Findings: The suggested security model that incorporates the methods of encrypted storage, biometrics authentication, partitioned networking structure, and AI-based threat persistence identification augments ransomware, phishing, data misappropriation, and insider attacks considerably. The solution is then based on complying with the most important data protection standards, such as HIPAA and GDPR and shows a significant increase in endpoint resilience in simulations and practice tests.

A unique contribution to theory, practice, and policy: This study provides a new, flexible, next-generation endpoint defence model with healthcare systems in mind. It enhances cybersecurity practice proficiency by combining AI threat detection, asset-specific policies, and risk assessment conducted on a regular basis. The policy states that regulatory guidelines should be enhanced to require enhanced endpoint protection and achievement of a proactively focused cybersecurity culture at healthcare institutions.