EVALUATION OF ELECTRONIC BASED VOTING SYSTEM AND DESIGN OF BLOCK-CHAIN-BASED ELECTRONIC VOTING SYSTEM ENHANCED WITH FINGERPRINT AND FACIAL RECOGNITION TECHNOLOGIES TO ADDRESS IMPERSONATION
Abstract
This study introduces a blockchain-based electronic voting system enhanced with fingerprint and facial recognition to address persistent challenges such as fraud, impersonation, and lack of transparency in electoral processes. Centered on Nigeria's electoral context and supported by data from the 2024 Edo State gubernatorial election, the system utilizes blockchain’s decentralized and tamper-proof ledger for secure vote recording, while multimodal biometrics ensure real-time, accurate voter authentication. Using SWOT analysis and IBM SPSS for statistical evaluation, the framework demonstrates improved security, transparency, and operational efficiency compared to conventional systems. Despite existing challenges related to infrastructure, biometric variability, and data privacy, the model presents a scalable, future-ready solution that can reinforce democratic legitimacy and restore public trust in elections. The findings contribute to advancing research in e-governance, secure computing, and electoral reform, advocating for technology-driven policy changes in emerging democracies.
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