Facial Recognition & Eye Blink Secured Cardless ATM Using CNN

ATM transactions have become essential for fulfilling our financial commitments in today's fast-paced world. Traditionally, using an ATM requires a debit card, but there are instances when individuals may forget to carry their cards, leading to transaction difficulties. Simultaneously, the use of mobile phones has become ubiquitous. Connecting these electronic devices has sparked a simple and efficient approach to withdrawing cash without needing a debit card. This method enhances "Cardless Cash Withdrawal" with two layers of security—facial recognition and eye-blink authentication, leveraging cutting-edge technology for secure ATM access. Utilizing CNN models, the system verifies user identity based on unique facial features. Biometric authentication reinforces ATM security, including facial recognition, eye blink patterns, and using an Aadhar number as a PIN. An OTP sent to the user's smartphone is an additional verification step for secure transactions. This system offers a user-friendly cardless cash withdrawal experience, supporting multi-banking functionalities for seamless banking.

Authors

Publication Details

Published
2024-10-17
DOI
https://doi.org/10.1109/icbds61829.2024.10837137
Primary Topic
Face recognition and analysis
Type
article
Field-Weighted Citation Impact
0.00
Controls
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Facial Recognition & Eye Blink Secured Cardless ATM Using CNN

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Facial Recognition & Eye Blink Secured Cardless ATM Using CNN

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article en

Abstract

ATM transactions have become essential for fulfilling our financial commitments in today's fast-paced world. Traditionally, using an ATM requires a debit card, but there are instances when individuals may forget to carry their cards, leading to transaction difficulties. Simultaneously, the use of mobile phones has become ubiquitous. Connecting these electronic devices has sparked a simple and efficient approach to withdrawing cash without needing a debit card. This method enhances "Cardless Cash Withdrawal" with two layers of security—facial recognition and eye-blink authentication, leveraging cutting-edge technology for secure ATM access. Utilizing CNN models, the system verifies user identity based on unique facial features. Biometric authentication reinforces ATM security, including facial recognition, eye blink patterns, and using an Aadhar number as a PIN. An OTP sent to the user's smartphone is an additional verification step for secure transactions. This system offers a user-friendly cardless cash withdrawal experience, supporting multi-banking functionalities for seamless banking.

Openalex Percentile: Top 74%
Face recognition and analysis
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