Secure Blockchain E-Voting System with Biometric Authentication

Abstract

E-voting systems have emerged as a promising alternative to traditional paper-based voting; however, concerns related to security, voter authentication, transparency, and trust continue to hinder their widespread adoption. This paper proposes a Secure Blockchain-Based E-Voting System with Biometric Authentication that addresses these challenges by integrating biometric verification with blockchain technology. The system ensures accurate voter identification through biometric authentication methods such as fingerprint or facial recognition, eliminating voter impersonation and multiple voting. Biometric data is securely processed with encryption and hashing, ensuring privacy and preventing unauthorized access. Once authenticated, voters cast votes electronically through a secure interface. Blockchain technology stores votes as immutable transactions within a decentralized ledger, making the system resistant to tampering and fraud. Smart contracts enforce election rules and automate validation and counting. This decentralized approach removes reliance on a single authority, enhances transparency, and enables real-time verification of results without compromising voter anonymity. The combination of biometric authentication and blockchain ensures a high level of security, integrity, and transparency throughout the election process, reducing the risk of electoral fraud and increasing voter confidence and participation.

Introduction

The text describes a secure blockchain-based electronic voting system integrated with biometric authentication to improve the transparency, security, and reliability of elections.

Traditional voting systems and existing e-voting platforms face major issues such as centralized vulnerabilities, vote tampering, weak authentication, duplicate voting, slow counting, and lack of transparency, which reduce trust in electoral processes. These problems highlight the need for a more secure and decentralized solution.

To address these challenges, the proposed system combines blockchain technology with biometric verification (fingerprint and facial recognition). Each voter is authenticated before voting, and every vote is encrypted and stored as an immutable blockchain transaction, ensuring it cannot be altered or deleted. Smart contracts enforce election rules such as one voter, one vote, while also enabling real-time vote tracking and automatic counting.

The system also includes an admin module for managing voters, candidates, elections, and results, along with real-time monitoring and reporting features.

The methodology involves key steps:

• Voter registration with biometric data
• Biometric and login authentication
• Secure vote casting and encryption
• Blockchain recording and validation using smart contracts
• Automatic vote counting and result display

Testing results show that the system significantly improves authentication accuracy, security, and transparency, while eliminating duplicate voting and reducing result processing time. The decentralized blockchain structure ensures tamper-proof records and auditability, and biometric authentication prevents impersonation.

Conclusion

This paper introduced a Secure Blockchain E-Voting System that leverages biometric authentication to enhance the security and integrity of electronic elections. By combining fingerprint and facial recognition for accurate voter identification with blockchain’s tamper-proof vote storage, the system effectively eliminates duplicate voting and prevents vote manipulation. The decentralized architecture ensures transparency and removes dependency on central authorities, while real-time vote verification fosters greater trust in the election process. This solution is adaptable for use in college, organizational, and government elections. Looking ahead, the system can be further improved by adding mobile voting support, deploying on cloud platforms, and integrating AI-based fraud detection to increase scalability and security.

References

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Copyright

Copyright © 2026 Ms. Abirami K, Ms. Boomika K, Ms. Harshini M, Ms. Vaishnavi P, Mrs. Saranya S. 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.