Multi-Factor Authentication for Biometric Verification Using Facial Recognition

Abstract

Facial recognition technology has revolutionized election systems globally, and most notably in helping to solve issues of accessibility, fraudulency, and cost-effectiveness in conventional voting systems. This paper examines how the application of biometric verification using facial recognition coupled with multi-factor authentication technologies such as OTP can dramatically boost security and efficiency levels in voting systems. The suggested model is validated at 90-95% with low administrative expenses by automating but raising the rate of turnout of voters among disabled, aged, and geographically distant voters. Comparative studies point to spectacular gains in accuracy in validation, authentication frameworks, and performance in systems whose response times have been cut down to 3-10 seconds from 5-30 seconds. Blockchain technology universality further facilitates immutable storage of votes and end-to-end tracing. High-cost initial infrastructure investment however the system is cost-efficient in the long term for varied electoral contexts. Sophisticated biometric technologies, real-time processing, multi-language capabilities, and machine learning-based fraud detection could be some of the emerging upgrades that would be a groundbreaking shift in election technology realizing harmony between security and convenience.