ViBioChain: a blockchain-enabled architecture for privacy-preserving, ethically governed, and explainable personalized gene editing
- 1School of Computer Science and Engineering, Vellore Institute of Technology
Abstract
Personalized gene editing demands robust mechanisms for privacy, ethical governance, and verifiable data integrity. This paper proposes ViBioChain, a modular blockchain-anchored architecture integrating five components: (1) differential chain-of-custody audit combining quantum fingerprinting with post-quantum signatures for immutable genomic audit trails; (2) proof-of-bioethical-compliance employing zero-knowledge proofs and AI-based ontology evaluation for automated bioethical gating; (3) federated genomic trust mesh (FGTM) enabling privacy-preserving collaborative model training with Renyi differential privacy accounting and trust-weighted federated aggregation; (4) ethical smart orchestration network for modular smart-contract-based workflow governance; and (5) genomic impact estimator via ethical explainability graphs (GIE-EEG) for ancestry-aware, ethically constrained phenotypic forecasting. Afterexpert-driven reconciliation, the implementation was rerun using 800 simulated individuals per dataset, 120 binary loci, five institutional clients, five independent seeds (42–46), and a true trust-weighted federated logistic aggregation path for FGTM rather than the earlier centralized accuracy proxy. Across three genomic cohorts and three domain-comparable baselines, ViBioChain achieved 92.16% ethical violation interception, 100.00% audit trail accuracy, 99.47% workflow traceability, 0.9183 ethical score alignment, and the highest global model accuracy among the tested methods (74.36%). The formal Renyi differential privacy accountant remained within budget ( ε =1.8578 , δ =10−5 ); however, the conservative clean-versus-noisy update leakage proxy did not support the earlier lowest-empirical-leakage assertion. That claim has therefore been removed. Additional IID and non-IID experiments show that severe Dirichlet client heterogeneity ( α =0.1 ) reduced final accuracy by 1.70–4.10 percentage points relative to IID partitions. The revised results provide a more conservative and reproducible blueprint for secure, ethically governed, and explainable genomic medicine in multi-institutional settings.
Related
- Secure and explainable fraud detection in healthcare claims using blockchain-based machine learning
- BREAKING THE BLACK BOX IN HEMATOPOIETIC STEM CELL TRANSPLANTATION: AN EXPLAINABLE MACHINE LEARNING WEB APPLICATION FOR PERSONALIZED SURVIVAL PREDICTION
- Pathway Modeling of Genomic and Tissue-Specific Transcriptomic Architecture Identifies Personalized Mechanisms of Atrial Fibrillation Risk
- A long-term organotypic slice culture model of patient high-grade glioma preserving tumor heterogeneity and architecture, and specificity of CAR T cell targeting
- Holistic and proactive machine learning approaches to predict cyberattacks in blockchain networks
BibTeX
@article{prabakaran2026vibiochain,
title = {{ViBioChain: a blockchain-enabled architecture for privacy-preserving, ethically governed, and explainable personalized gene editing}},
author = {C. Prabakaran and R. Kannadasan},
journal = {Scientific Reports},
year = {2026},
month = jul,
doi = {10.1038/s41598-026-59495-7},
url = {https://doi.org/10.1038/s41598-026-59495-7},
note = {CC BY},
}
RIS
TY - JOUR
TI - ViBioChain: a blockchain-enabled architecture for privacy-preserving, ethically governed, and explainable personalized gene editing
AU - C. Prabakaran
AU - R. Kannadasan
PY - 2026
DA - 2026/07/01
JO - Scientific Reports
DO - 10.1038/s41598-026-59495-7
UR - https://doi.org/10.1038/s41598-026-59495-7
AB - Personalized gene editing demands robust mechanisms for privacy, ethical governance, and verifiable data integrity. This paper proposes ViBioChain, a modular blockchain-anchored architecture integrating five components: (1) differential chain-of-custody audit combining quantum fingerprinting with post-quantum signatures for immutable genomic audit trails; (2) proof-of-bioethical-compliance employing zero-knowledge proofs and AI-based ontology evaluation for automated bioethical gating; (3) federated genomic trust mesh (FGTM) enabling privacy-preserving collaborative model training with Renyi differential privacy accounting and trust-weighted federated aggregation; (4) ethical smart orchestration network for modular smart-contract-based workflow governance; and (5) genomic impact estimator via ethical explainability graphs (GIE-EEG) for ancestry-aware, ethically constrained phenotypic forecasting. Afterexpert-driven reconciliation, the implementation was rerun using 800 simulated individuals per dataset, 120 binary loci, five institutional clients, five independent seeds (42–46), and a true trust-weighted federated logistic aggregation path for FGTM rather than the earlier centralized accuracy proxy. Across three genomic cohorts and three domain-comparable baselines, ViBioChain achieved 92.16% ethical violation interception, 100.00% audit trail accuracy, 99.47% workflow traceability, 0.9183 ethical score alignment, and the highest global model accuracy among the tested methods (74.36%). The formal Renyi differential privacy accountant remained within budget ( ε =1.8578 , δ =10^−5 ); however, the conservative clean-versus-noisy update leakage proxy did not support the earlier lowest-empirical-leakage assertion. That claim has therefore been removed. Additional IID and non-IID experiments show that severe Dirichlet client heterogeneity ( α =0.1 ) reduced final accuracy by 1.70–4.10 percentage points relative to IID partitions. The revised results provide a more conservative and reproducible blueprint for secure, ethically governed, and explainable genomic medicine in multi-institutional settings.
SN - 2045-2322
ER -