ZeroTrustBlock: Enhancing Security, Privacy, and Interoperability of Sensitive Data through ZeroTrust Permissioned Blockchain

Author:

Thantharate Pratik1ORCID,Thantharate Anurag2ORCID

Affiliation:

1. Independent Researcher, Jersey City, NJ 07304, USA

2. School of Computing and Engineering, University of Missouri, Kansas City, MO 64112, USA

Abstract

With the digitization of healthcare, an immense amount of sensitive medical data are generated and shared between various healthcare stakeholders—however, traditional health data management mechanisms present interoperability, security, and privacy challenges. The centralized nature of current health information systems leads to single points of failure, making the data vulnerable to cyberattacks. Patients also have little control over their medical records, raising privacy concerns. Blockchain technology presents a promising solution to these challenges through its decentralized, transparent, and immutable properties. This research proposes ZeroTrustBlock, a comprehensive blockchain framework for secure and private health information exchange. The decentralized ledger enhances integrity, while permissioned access and smart contracts enable patient-centric control over medical data sharing. A hybrid on-chain and off-chain storage model balances transparency with confidentiality. Integration gateways bridge ZeroTrustBlock protocols with existing systems like EHRs. Implemented on Hyperledger Fabric, ZeroTrustBlock demonstrates substantial security improvements over mainstream databases via cryptographic mechanisms, formal privacy-preserving protocols, and access policies enacting patient consent. Results validate the architecture’s effectiveness in achieving 14,200 TPS average throughput, 480 ms average latency for 100,000 concurrent transactions, and linear scalability up to 20 nodes. However, enhancements around performance, advanced cryptography, and real-world pilots are future work. Overall, ZeroTrustBlock provides a robust application of blockchain capabilities to transform security, privacy, interoperability, and patient agency in health data management.

Publisher

MDPI AG

Subject

Artificial Intelligence,Computer Science Applications,Information Systems,Management Information Systems

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