IDEAS home Printed from https://ideas.repec.org/a/bjf/journl/v11y2026i5p593-598.html

An Optimised Artificial Neural Network Model for a Three-Level Authentication Security Scheme Utilising Fingerprint, Facial Recognition, and Optical Character Recognition

Author

Listed:
  • Adeyemi Biliqees Temitope

    (Department of Computer Science, Kwara State College of Education, Ilorin)

  • Makinde, Oladayo Ezekiel

    (Department of computer science, Ajayi Crowther University, Oyo)

Abstract

The rapid increase in the use of digital technologies in daily activities has created both opportunities and threats. The paper reports an optimized Artificial Neural Network (ANN) model for implementing a three-tier authentication system using fingerprint biometrics (Level 1), facial recognition (Level 2) and Optical Character Recognition (OCR) (Level 3). The model is created using a multi-layer perceptron optimized using Adam and L2 regularization in order to have better accuracy and stability under environmental changes. On NIST SD4, LFW, and IAM datasets, an overall accuracy of 97.8% was reached with a false acceptance rate (FAR) of less than 1.0% was attained through experimental evaluation. The results show that the suggested model is better than unimodal techniques by about 16%, which proves its possible ability to protect e-learning and administrative systems at Nigerian universities.

Suggested Citation

  • Adeyemi Biliqees Temitope & Makinde, Oladayo Ezekiel, 2026. "An Optimised Artificial Neural Network Model for a Three-Level Authentication Security Scheme Utilising Fingerprint, Facial Recognition, and Optical Character Recognition," International Journal of Research and Innovation in Applied Science, International Journal of Research and Innovation in Applied Science (IJRIAS), vol. 11(5), pages 593-598, May.
    • Handle: RePEc:bjf:journl:v:11:y:2026:i:5:p:593-598
    as

    Download full text from publisher

    File URL: https://rsisinternational.org/journals/ijrias/uploads/vol11-iss5-pg593-598-202605_pdf.pdf
    Download Restriction: no
    File URL: https://rsisinternational.org/journals/ijrias/view/an-optimised-artificial-neural-network-model-for-a-three-level-authentication-security-scheme-utilising-fingerprint-facial-recognition-and-optical-character-recognition/
    Download Restriction: no
    ---><---

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:bjf:journl:v:11:y:2026:i:5:p:593-598. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Dr. Renu Malsaria (email available below). General contact details of provider: https://rsisinternational.org/journals/ijrias/ .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.