Beyond Cards and PINs: Enhancing ATM Security with Iris Recognition and CNN

M. D. Narmadha, M. Sabarieesh, V. Sivaashankar, N. Vijayaragavan, S. Pavithra, V. Sridhar

2025

Abstract

This study intends to modernize the ATMs by introducing iris recognition technology as the primary mode of authentication. This innovative method has the potential to strengthen security since it does away with the vulnerabilities associated with traditional card-based systems such as card theft and skimming. Iris recognition provides a highly secure and user-friendly authentication process since the human eye's iris offers unique patterns. It would minimize the risk of fraud and identity theft at ATMs because iris patterns are very unique and very difficult to replicate. Further, it would simplify the authentication process by not having users carry physical cards or remembering PIN codes. That way, it would give a convenient and efficient experience to the customers. This paper deals with the technical aspects of the implementation of iris recognition in ATMs, potential benefits toward security and convenience, challenges posed, and future directions toward this emerging technology. Adoption of iris recognition technology can serve banks in achieving more enhanced security as well as facilitating a more convenient and futuristic banking experience for its customers. This approach has the advantage of aligning with the fast-growing trend of biometric authentication and will change how people interact with their technology and financial services. This project deploys the CNN algorithm to optimize ATM security through Irish recognition technology. By convolving user biometric data--facial features--and learned filters, the CNN algorithm extracts discriminative features for verification. The activation function verifies user identity through the matching of features, while the pooling reduces false positives and negatives through data augmentation. The output is an ATM transaction processing system with security, eliminating the requirement for ATM cards, making it more secure, and convenient, and reducing the possibility of identity theft and unauthorized transactions.

Paper Citation

in Harvard Style

Narmadha M., Sabarieesh M., Sivaashankar V., Vijayaragavan N., Pavithra S. and Sridhar V. (2025). Beyond Cards and PINs: Enhancing ATM Security with Iris Recognition and CNN. In Proceedings of the 1st International Conference on Research and Development in Information, Communication, and Computing Technologies - ICRDICCT`25; ISBN 978-989-758-777-1, SciTePress, pages 421-424. DOI: 10.5220/0013899400004919

in Bibtex Style

@conference{icrdicct`2525,
author={M. Narmadha and M. Sabarieesh and V. Sivaashankar and N. Vijayaragavan and S. Pavithra and V. Sridhar},
title={Beyond Cards and PINs: Enhancing ATM Security with Iris Recognition and CNN},
booktitle={Proceedings of the 1st International Conference on Research and Development in Information, Communication, and Computing Technologies - ICRDICCT`25},
year={2025},
pages={421-424},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0013899400004919},
isbn={978-989-758-777-1},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 1st International Conference on Research and Development in Information, Communication, and Computing Technologies - ICRDICCT`25
TI - Beyond Cards and PINs: Enhancing ATM Security with Iris Recognition and CNN
SN - 978-989-758-777-1
AU - Narmadha M.
AU - Sabarieesh M.
AU - Sivaashankar V.
AU - Vijayaragavan N.
AU - Pavithra S.
AU - Sridhar V.
PY - 2025
SP - 421
EP - 424
DO - 10.5220/0013899400004919
PB - SciTePress