Secured Electronic Voting System with Appropriate Authentication Using Blockchain
P. Kaladevi, R N Shreemathi, S Hariram, Muhammed Afzal K · 2023
As a means of making elections more accessible and more convenient for voters, the use of online voting systems has grown in recent years. However, maintaining these systems' accuracy and security remains a significant obstacle. A face-and-email OTP-based voting system based on Convolutional Neural Network (CNN) methodology is proposed in this study to address these issues. Facial recognition and email OTP verification are used to verify a voter's identity and capture their face for the system. A CNN model that has been trained on a database of faces belonging to registered voters is used to perform the facial recognition process. After their identification has been confirmed, the voter may utilize the technology to cast their ballot. An additional layer of security and protection against potential fraud or hacking is provided by the combination of email OTP verification and facial recognition. In addition, the privacy and accuracy of the voting process are guaranteed by making use of a secure database and a user-friendly interface. The legal and ethical ramifications of incorporating facial recognition technology into a voting system, including privacy concerns and the possibility of algorithmic bias, must be taken into account during system design and implementation. A face-and-email OTP-based voting system based on CNN methodology provides an effective and secure option for online voting while preserving voter privacy and accuracy.