A secured automated bimodal biometric electronic voting system

Kennedy Okokpujie (Covenant University)
John Abubakar (Covenant University)
Samuel John (Nigerian Defence Academy)
Etinosa Noma-Osaghae (Covenant University)
Charles Ndujiuba (Air Force Institute of Technology)
Imhade Princess Okokpujie (Covenant University)

IAES International Journal of Artificial Intelligence (IJ-AI)
Vol 10, No 1: March 2021

Insecurity, rigging and violence continue to mar electoral processes in developing nations. It has been difficult to enforce security and transparency in the voting process. This paper proposes a secure and automated bimodal voting system. The system uses three security layers, namely, a unique ID code, a token passcode that expires every five minutes and biometrics (iris and fingerprint). A scanner captures the fingerprint and iris of eligible voters. The fingerprint and iris images stored along with the corresponding particulars in a database. The software implemented is a .net managed code in C#. The result of this system shows the system is transparent, fast and fraud-free. The proposed method had a failure to enroll (FTE) and a failure to capture (FTC) of zero.