Framework for Securing and Querying Healthcare Data using Blockchain

Abstract

Technological advancements are significantly transforming operations within organizations. When it comes to the healthcare sector, the development rate is touching new heights and being supported by cutting-edge technology as the whole system moves towards a patient-centred approach. Healthcare service providers have begun to use Electronic Health Record (EHR) management systems to overcome issues associated with traditional, manual, paper-based, outdated systems that can make the diagnosis time-consuming and complicated for the doctor. EHRs, primarily used to improve health-related information management, are frequently approached for a secondary purpose by other medical/non-medical institutions or Third-Party Administrators/Alliance (TPAs) such as insurance companies and data analysts. However, the existing EHR systems are centralized and always at risk of a single point of failure. With exponential growth in size of EHRs, scalability issues arise, making the systems more susceptible to cyber-attacks that risk patient privacy and data integrity. To address these challenges, decentralized solutions are required. Blockchain technology, with its decentralized and cryptographic behaviour, provides a powerful solution to these issues. It ensures data security, integrity, confidentiality, and non-repudiation, making it an ideal candidate for healthcare applications. This research proposes a decentralized permission-based blockchain framework for the secure sharing and querying of healthcare data. The framework is divided into three stages: During first stage, a permissioned blockchain architecture involving multiple healthcare entities for transparent, trusted, and immutable storage, sharing, and querying of EHR data is proposed and implemented. Further, for better data accessibility and security, the algorithms in terms of smart contracts are defined. In the existing approaches, LevelDB (key store database) is used as a state database that is insufficient for handling complex queries. To overcome this issue, this research utilized CouchDB (document store database) as a state database, enabling searches to be conducted using both keys and data values rather than just keys alone. Further, "Hyperledger Caliper", a benchmarking tool, is utilized to evaluate the various performance indicators for this framework, such as transaction throughput and latency. The system is also evaluated for handling complex queries with examples. In the second stage, the Identity-Based Proxy Re-Encryption (IB-PRE) algorithm is utilized to improve the privacy and security of the EHR data. In addition to this, to overcome scalability issues and achieve data integrity in managing EHRs, an Interplanetary Distributed File System (IPFS), a distributed off-chain storage, is employed. It is a content-addressable storage that ensures the integrity of the content such that a slight modification in the stored EHR records results in a change in the obtained hash value. In the third stage, the framework implements a dual-channel blockchain architecture combined with two cryptographic algorithms, i.e. Rivest-Shamir-Adleman (RSA) and Advanced Encryption Standard (AES), to provide the security and rapid retrieval of healthcare information. Furthermore, the concept of private data collection is incorporated to securely store confidential patient information, guaranteeing privacy, security and limited access. Also, an Access Control List (ACL) is defined for different users to implement access permissions, i.e., grant and revoke access to viewers while sharing information. The proposed framework is tested and validated by conducting a qualitative assessment of the designed contracts to ensure proper functionality and interaction among various components. The system performance is evaluated by considering different scenarios, including varied transaction loads, transaction types, number of channels, etc. Experimental results demonstrate that throughput increases significantly at a specific transaction rate when using dual channel, making the system more efficient compared to a single channel. v Additionally, latency drops considerably, leading to a notable improvement in system performance. The proposed framework’s security analysis is also conducted through two vulnerability assessment tools. This work also compares the proposed framework’s effectiveness and efficiency with other related works. The evaluation metrics include security attack resistance, features offered, scalability, transaction throughput, and latency. The proposed framework is intended to strictly enforce security and privacy standards while also improving data management and accessibility in healthcare applications