SECURE ONLINE VOTING USING MULTIBIOMETRIC AUTHENTICATION

Abstract

The use of online voting systems has been increasing in recent years as a way to increase accessibility and convenience for voters. However, ensuring the security and accuracy of these systems remains a critical challenge. This paper proposes a face and email OTP based voting system using Convolutional Neural Network (CNN) methodology as a solution to these challenges. Additionally, the use of a secure database and a user-friendly interface ensures the privacy and accuracy of the voting process. Development and implementation of such a system must take into consideration the legal and ethical implications of using facial recognition technology in a voting system, including privacy concerns and potential biases in the algorithms. Face and email OTP based voting system using CNN methodology offers a secure and efficient solution for online voting, while still maintaining the privacy and accuracy of the voting process. With careful implementation and consideration of legal and ethical implications, it has the potential to increase accessibility and convenience for voters while ensuring the security and accuracy of the voting process.