Ethereum voting prototype offers public audit for hospital ethics committees
A Lightweight Ethereum Voting Prototype for Hospital Ethics Committees with Receipt-Based Inclusion Verification
Cryptography and SecuritySoftware Engineering
Summary
Hospitals often need to vote on ethical decisions but struggle with secure and trustworthy methods. This paper shows a prototype using Ethereum blockchain technology to record votes transparently while keeping voter identities partially hidden. The system provides a way for anyone to verify votes were included correctly, but it does not guarantee full anonymity or protection against coercion. The authors tested the system with simulated votes and identified areas for security improvements.
What this means in practice
- •For hospital it teams: Implement transparent, pseudonymous voting systems for ethics committees using blockchain technology with public vote verification.
- •For blockchain developers: Build lightweight Ethereum-based voting applications that support role management and receipt-based inclusion checks.
Authors
Edwin Clatus, Madhusudan Singh
Abstract
This paper presents a Solidity, Hardhat, React, MetaMask, and ethers.js prototype for hospital ethics committee voting. Role controls, case-state checks, duplicate vote controls, and a receipt hash support public audit and transaction inclusion verification. Because vote events expose wallet addresses and vote values, the design provides pseudonymous auditability, not anonymous or secret-ballot voting; the receipt is neither receipt-free nor coercion-resistant. Evaluation reports 22 passing functional tests and local Hardhat gas use, including 284,137 gas per vote. A 12-participant simulation used assumed probabilities and is not human-subject evidence. Residual risks include multiple wallets, administrator or frontend compromise, credential reassignment, front-running, denial of service, and untested adversarial paths. Confidential deployment requires governed enrollment, encrypted ballots, independent audit, adversarial testing, reproducible benchmarks, and a real user study.