Enhancing Healthcare Data Security with Homomorphic Encryption: A Case Study on Electronic Health Records (EHR) Systems

Abstract

The protection of healthcare data, particularly Electronic Health Records (EHR), is paramount due to the sensitive nature of the information and the growing prevalence of cyber threats. Traditional encryption techniques, while effective, may not fully address the need for data processing and analysis on encrypted information. Homomorphic encryption (HE) presents a promising solution by enabling computations on encrypted data without decryption, thus maintaining both privacy and security. This paper explores the application of homomorphic encryption in securing EHR systems, examining its potential to enhance data confidentiality while supporting secure analytics and machine learning applications. Through a case study, we demonstrate the integration of HE in a real-world EHR environment, focusing on its impact on privacy protection, computational efficiency, and system performance. The study also addresses the challenges of implementing HE in healthcare systems, including computational overhead and system integration complexity. We conclude with insights on the feasibility of scaling homomorphic encryption for large healthcare datasets and its potential to transform data security in the healthcare sector, paving the way for more secure, privacy-preserving, and efficient EHR management solutions.