A Blockchain-Based End-to-End Data Protection Model for Personal Health Records Sharing: A Fully Homomorphic Encryption Approach

• Published in: Sensors (Basel, Switzerland) Switzerland), 2022-12, Vol.23 (1), p.14
• Main Authors: Vanin, Fausto Neri da Silva, Policarpo, Lucas Micol, Righi, Rodrigo da Rosa, Heck, Sandra Marlene, da Silva, Valter Ferreira, Goldim, José, da Costa, Cristiano André
• Format: Article
• Language: English
• Subjects: Algorithms; Blockchain; Coronaviruses; COVID-19; Cryptography; Data analysis; Data security; distributed systems; Electronic health records; encryption; Health Insurance Portability & Accountability Act 1996-US; health record; Interoperability; Medical informatics; Medical records; Metadata; Methods; Pandemics; Peers; Personal health; Personal information; Privacy; Safety and security measures; Storage
• ISSN: 1424-8220; 1424-8220
• DOI: 10.3390/s23010014

Personal health records (PHR) represent health data managed by a specific individual. Traditional solutions rely on centralized architectures to store and distribute PHR, which are more vulnerable to security breaches. To address such problems, distributed network technologies, including blockchain and distributed hash tables (DHT) are used for processing, storing, and sharing health records. Furthermore, fully homomorphic encryption (FHE) is a set of techniques that allows the calculation of encrypted data, which can help to protect personal privacy in data sharing. In this context, we propose an architectural model that applies a DHT technique called the interplanetary protocol file system and blockchain networks to store and distribute data and metadata separately; two new elements, called data steward and shared data vault, are introduced in this regard. These new modules are responsible for segregating responsibilities from health institutions and promoting end-to-end encryption; therefore, a person can manage data encryption and requests for data sharing in addition to restricting access to data for a predefined period. In addition to supporting calculations on encrypted data, our contribution can be summarized as follows: (i) mitigation of risk to personal privacy by reducing the use of unencrypted data, and (ii) improvement of semantic interoperability among health institutions by using distributed networks for standardized PHR. We evaluated performance and storage occupation using a database with 1.3 million COVID-19 registries, which showed that combining FHE with distributed networks could redefine e-health paradigms.