Cybersecurity Framework for Healthcare Systems

Abstract

The increasing digitization of healthcare systems has significantly improved patient care and data accessibility but has also introduced critical cybersecurity challenges. This paper presents a Cybersecurity Framework for Healthcare Systems aimed at protecting sensitive medical data and ensuring secure system operations. The proposed framework integrates multiple layers of security, including data encryption, authentication mechanisms, intrusion detection systems, and network security protocols. Machine learning techniques are incorporated to detect anomalous activities and potential cyber threats in real time. The framework also emphasizes compliance with healthcare data protection standards and supports secure data sharing across interconnected systems. Additionally, risk assessment and vulnerability analysis are performed to strengthen system resilience against cyberattacks. Experimental evaluation demonstrates that the proposed approach enhances threat detection accuracy and minimizes security breaches. The integration of prior research in machine learning and healthcare analytics further improves adaptability and robustness. The study highlights the importance of implementing comprehensive cybersecurity strategies to safeguard healthcare infrastructures, particularly in environments with increasing reliance on digital health technologies.