A Blockchain and Face Recognition Based E-Voting System

Abstract

This paper describes a project-specific electronic voting (e-voting) system that integrates blockchain technology with face recognition for robust voter authentication. The goal is to design a decentralized platform in which every vote is recorded immutably on an Ethereum-based blockchain, while face recognition ensures that only a uniquely verified individual can cast a ballot. We detail the system architecture, methodology, and implementation steps, and we compare our approach to other blockchain-based e-voting systems worldwide, including Voatz, Follow My Vote, Zug e-Voting, and Moscow Blockchain Voting. Finally, we reference the open-source repository on which our project is based, demonstrating its real-world applicability and transparency.

Introduction

This paper presents a blockchain-based electronic voting system that integrates facial recognition for voter authentication, aiming to address the vulnerabilities of traditional voting methods such as fraud, tampering, and impersonation.

I. Background and Motivation

Challenges in Conventional Voting:

• Vote Tampering: Centralized or paper-based records can be manipulated.

• Double Voting: Insufficient identity checks allow individuals to vote multiple times.

• Identity Fraud: Impersonation undermines confidence in the electoral process.link.springer.com

Blockchain as a Secure Ledger:

• Decentralization: Distributes data across multiple nodes, reducing single points of failure.

• Immutability: Ensures votes cannot be altered post-recording.

• Auditability: Transactions (votes) are publicly verifiable, enhancing transparency.

Face Recognition for Voter Authentication:

• Utilizes unique facial features to confirm an individual's identity, ensuring that each ballot is associated with a single, legitimate voter.

II. System Architecture and Methodology

Architecture Overview:

• Front End (React.js): Provides voter registration, facial capture, and vote casting via Metamask.

• Back End (Node.js/Express): Processes API requests, handles user data in MongoDB, and coordinates the face recognition module.

• Blockchain Layer (Ethereum): Smart contracts (Solidity) deployed on a Ganache test network to record votes.

• Face Recognition Module (Python): Uses OpenCV and the face_recognition library for biometric verification.

Voting Procedure:

1. Voter Registration:

   • Users register by submitting personal details and a live facial image.

   • Facial data is encrypted and linked to a unique blockchain address in MongoDB.

   • Email verification confirms user legitimacy prior to biometric usage.

2. Voting Process:

   • The system captures a live image, comparing it with stored data to confirm identity.

   • After successful verification, the user selects a candidate and submits the vote.

   • The ballot is recorded on the Ethereum blockchain, ensuring immutability.

   • The voter receives real-time feedback indicating the ballot's secure recording.

Security Measures:

• Data Encryption: Facial data is encrypted for voter privacy.

• Immutable Ledger: Blockchain ensures ballots cannot be retroactively altered.

• Multi-Factor Authentication: Email checks plus face recognition fortify the voter identity layer.

III. Comparative Analysis with Global E-Voting Systems

IV. Discussion and Future Directions

Discussion:

• The integration of blockchain and facial recognition enhances the security and transparency of the voting process, addressing many vulnerabilities in traditional and centralized e-voting systems.

Future Enhancements:

1. Layer-Two Solutions: Exploring off-chain transactions or sidechains to accommodate a higher number of voters.

2. Deep Learning Models: Potentially improving face recognition speed and accuracy through advanced neural networks.

3. Pilot Deployments: Conducting real-world trials in smaller institutional or municipal elections to evaluate user experience.

4. API Integration: Developing standardized interfaces for interoperability with existing electoral systems and identity databases.

Conclusion

This paper described a project-specific blockchain-based e-voting system that employs face recognition to enhance security and reliability in the electoral process. By lever- aging Ethereum smart contracts for immutable vote record- ing and a real-time biometric layer for voter authentication, our approach aims to address common issues such as vote tampering, identity fraud, and double voting. A compara- tive analysis with Voatz, Follow My Vote, Zug e-Voting, and Moscow Blockchain Voting highlights the advantages of merging decentralized ledger technology with robust biometric verification. Future work will focus on scaling, regulatory compliance, and pilot studies to validate the systems real- world applicability.

References

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Copyright

Copyright © 2025 Harsh Mittal, Dr. Nidhi Sengar. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.