International Journal For Multidisciplinary Research

E-ISSN: 2582-2160   •   Impact Factor: 9.24

A Widely Indexed Open Access Peer Reviewed Multidisciplinary Bi-monthly Scholarly International Journal

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Volume 7 Issue 2
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Iris Recognition Based Modern Voting System Using Deep Learning

Author(s) Prof. Ms. E Goma, MANASA G, MANJULA B, SANCHANA S
Country India
Abstract This project introduces a Face and Iris Recognition-Based Voting System utilizing Convolutional Neural Networks (CNNs) to enhance voter authentication and prevent electoral fraud. The system captures a voter's face and iris via a webcam and verifies their identity using a CNN-trained model on registered voters’ biometric data. Additionally, fingerprint authentication adds another layer of security. After successful biometric verification, a One-Time Password (OTP) is sent to the voter's registered mobile number for final authentication before granting access to the voting interface. This multi-layered security approach ensures only legitimate voters can participate, mitigating risks like impersonation, multiple voting, and unauthorized access. A secure database stores voter details and ballots, ensuring data confidentiality and integrity. Designed with a user-friendly interface, the system improves accessibility while maintaining the privacy, security, and accuracy of the electoral process, making online elections more reliable and efficient.
Keywords Online voting system, biometric authentication, face recognition, iris recognition, fingerprint verification, Convolutional Neural Networks (CNNs), voter authentication, fraud prevention, OTP verification, multi-layered security, secure database, data confidentiality, electoral integrity, secure voting mechanism, artificial intelligence, machine learning, webcam-based authentication, election security, voter identity verification, real-time authentication, deep learning, online elections, digital democracy.
Field Engineering
Published In Volume 7, Issue 2, March-April 2025
Published On 2025-04-05
DOI https://doi.org/10.36948/ijfmr.2025.v07i02.40527
Short DOI https://doi.org/g9dg3d
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