A Blockchain-Based Framework With Zero-Knowledge Proof Incorporated for Safeguarded Sharing of Genomic Data Through Health Record Systems

Genomic data sharing remains a core problem in precision medicine because genomic data are highly sensitive and unchangeable. In this article, we propose a blockchain-based framework that utilizes zero-knowledge proofs (ZKPs), smart contracts, and off-chain storage to facilitate secure, privacy-preserving data sharing within health record systems. We implemented and evaluated a proof-of-concept prototype in Python on a simulated genomic dataset. The prototype uses a hybrid storage system where metadata is retained on a blockchain and encrypted data are placed in an emulated InterPlanetary File System (IPFS). Rule-based access is controlled using smart contracts, while privacy and security are achieved using ZKPs with interactive Schnorr protocol and elliptic curve cryptography (ECC). Empirical analysis using real-time testing over 100 iterations reported an average zero-knowledge proof with blockchain (ZKPB) query latency of 5.83 ms with a 90.00% accuracy, smart contract latency of under 0.01 ms with 90.00% accuracy, blockchain query time of 0.01 ms with 90.00% accuracy, and ECC latency of 8.72 ms with 90.00% accuracy. These empirical findings validate the effectiveness and privacy guarantees of the framework, which can be utilized in healthcare research, clinical genomics, and personalized medicine workflows. In the age of precision medicine, genomic data are becoming central to powering customized diagnosis and therapy. However, its permanent and sensitive nature raises concerns over privacy, misuse, and unauthorized exploitation. Legacy centralized architecture remains vulnerable to breaches, thus necessitating more resilient alternatives. Recent advances have turned towards blockchain for its decentralization and permanence but remain incomplete in terms of scalability and privacy. New research also combines federated learning, smart contracts, and consent mechanisms, but few attempt to adequately address the complexity of genomic data privacy, actual-world scalability, or data protection regulations compliance. We present Secure Chain, a decentralized, privacy-enhancing infrastructure for genomic data sharing with security. By drawing on blockchain, zero-knowledge proofs (ZKPs), off-chain storage (e.g. IPFS), and homomorphic encryption, the system provides confidentiality, verifiability, and scalability. The goal here is to compare this hybrid architecture’s performance on parameters such as security, computational cost, and query response time with full compliance with law (Health Insurance Portability and Accountability Act [HIPAA] and General Data Protection Regulation [GDPR]). By comparative outputs, the framework shall prove that combining ZKPs and blockchain provides an optimal trade-off between privacy and efficiency in making Secure Chain a feasible, practical solution for safe, regulation-compliant genomic data exchange.