ReviewBlockchain in healthcare today2026
Lightweight Privacy-Preserving Blockchain Framework for Healthcare: A Simulation-Based Approach to Reducing Computational Overhead.
Review in Blockchain in healthcare today, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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4 authors.
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Abstract
Background: The privacy and security of electronic health records (HER) in blockchain-based systems remains a major research problem because of high computational overhead and scalability restrictions. Privacy-preserving techniques such as encryption and zero-knowledge proofs strengthen blockchain's transparency and immutability but often add significant latency and resource use. This study proposes a lightweight, simulation-based blockchain model balancing privacy protection and computational efficiency for healthcare data-sharing, incorporating hybrid encryption (AES with asymmetric-key exchange), zero-knowledge verification (zk-SNARK), and homomorphic aggregation to protect patient information while reducing processing cost. Methods: A five-stage simulation tested encryption/decryption latency, IPFS-based upload/download performance, proof generation/verification time, and scalability across key sizes, plus a sixth phase validating the framework on two real, publicly available, de-identified healthcare datasets-the Medical Information Mart for Intensive Care (MIMIC)-IV demo (100 real ICU patients) and the University of California "Diabetes 130-US Hospitals" dataset (101,766 real inpatient encounters). Every metric is reported as a mean with a 95% confidence interval from 15 to 20 repeated trials. Results: The AES-128 has the lowest overhead among tested key sizes (10% to 14% below AES-192/256), zk-SNARK verification averages 30.8 to 32.4 ms ( Conclusions: This work demonstrates that efficient cryptographic integration and optimization through simulation can produce a privacy-preserving blockchain for healthcare that streamlines EHR handling securely and at scale.
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