PRIVACY-PRESERVING TECHNIQUES IN HEALTHCARE DATA REPOSITORIES: A COMPARATIVE ANALYSIS

Abstract: Digital healthcare systems generate vast amounts of sensitive patient data, creating significant privacy challenges including data breaches, re-identification attacks and regulatory compliance issues. This study evaluates privacy-preserving techniques (PPTs) for healthcare data repositories, including anonymization, homomorphic encryption, differential privacy, federated learning and blockchain solutions. Each technique was assessed based on privacy guarantees, data utility, scalability, implementation feasibility and regulatory compliance. Results demonstrate substantial improvements in privacy measures: encryption effectiveness increased to 90%, access controls reached 85%, and user satisfaction improved by 30%. No single technique provides optimal solutions across all criteria; hybrid approaches offer the best privacy-utility balance. The study provides guidance for implementing secure, compliant healthcare data systems.

Keywords: Privacy-preserving techniques, Healthcare data repositories, Differential privacy, Federated learning, HIPAA compliance.