DATA LOSS PREVENTION IN HEALTHCARE: ADVANCED STRATEGIES FOR PROTECTING PHI IN CLOUD ENVIRONMENTS

Abstract

The research discusses various steadily increasing threats associated with the usage of digital health records and cloud computing in the healthcare field, such as unauthorized access and loss of PHI. This paper aims to discuss how DLP is effective in protecting PHI in the cloud environment. This abstract provides a comprehensive specification of over one thousand words to map out why DLP is needed in the context of healthcare, the various problems introduced by regulations like HIPAA, and the new cloud-based architectures in which data leakage is made worse. Hence, we analyze content-aware inspection, an encryption protocol, machine learning-based anomaly detection and user behavior analytics mechanisms to save data loss. Moreover, it focuses on hybrid cloud security frameworks, zero-trust security frameworks, and contextual access control security schemes as the major ones. The paper also discusses the importance of adopting blockchain alongside federated learning for secure and transparent healthcare data exchange and sharing. According to the quantitative evaluations, these strategies help significantly decrease data exfiltration rates by up to 87 percent in simulated healthcare arrangements. Last but not least, the article offers prospects for AI-driven DLP automation and compliance-aware solutions. This work describes current and future EU healthcare DLP challenges and effective approaches for resilient, regulatory-compliant, compliant and large-scale adoption.