Please use this identifier to cite or link to this item: http://repository.futminna.edu.ng:8080/jspui/handle/123456789/18688
Title: A Bi-Factor Biometric Authentication System for Secure Electronic Voting System
Authors: Buhari, Ugbede Umar
Olaniyi, Olayemi Mikail
Abisoye, Blessing Olatunde
Ademoh, Agbogunde Isah
Haq, Arifa Khatoon
Ajayi, Isaac Taiwo
Keywords: Fingerprint Authentication
Iris Recognition
Pattern Match
RFID
Issue Date: 17-May-2022
Publisher: 2022 IEEE Nigeria 4th International Conference on Disruptive Technologies for Sustainable Development (NIGERCON)
Citation: 2022 IEEE Nigeria 4th International Conference on Disruptive Technologies for Sustainable Development (NIGERCON), DOI: 10.1109/NIGERCON54645.2022.9803174
Abstract: Because voting is the most important way for people to express their thoughts and choose their preferred candidates or administrations, it is an essential aspect of the democratic process. The Nigerian Independent National Electoral Commission (INEC) employed a partial e-voting device with the use of a card reader to identify and authenticate the electorate in general elections in 2015 and 2019. As a result of the deployment of the card reader, the country's voting processes have improved considerably in terms of legitimacy and trustworthiness. This great concept, however, was not without problems, since a lack of fingerprint recognition and identification prevented a substantial number of people from voting. This is due to the continual shifting of the skin of the finger as a result of the vast majority of voters in this category's farming and tiresome work. If this remains unchecked, it will not only disenfranchise a large number of voters, but it will also call into question the process' legitimacy. This work proposed a voting system with a bi-factor biometric authentication mechanism to address these concerns (fingerprint and iris). This will speed up the voter identification and authentication procedure, as well as prevent voting fraud and voter disenfranchisement as a result of the card reader failing to identify them. An accuracy of 94 percent was obtained as a result of the analyses. The Iris response time for voter enrolment and verification is 15s and 20s, respectively, while the fingerprint response time is 3s and 9s, respectively.
URI: http://repository.futminna.edu.ng:8080/jspui/handle/123456789/18688
Appears in Collections:Computer Engineering

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