Multichannel EfficientNet B7 with attention mechanism using multimodal biometric- based authentication for ATM transaction

Abstract

Automatic Teller Machine (ATM) offers rapid and user-friendly avenues to reach their bank accounts and engage in financial operations. A crucial component of ATM security is the “Personal Identification Number (PIN) or password”. This PIN or password serves as a fundamental element in safeguarding and preserving customers’ financial data from unauthorized entry. Within the financial realm, an ongoing necessity exists to enhance security measures. In the realm of identity verification, modern ATM systems traditionally require the combination of an access card and the input of a PIN. However, the landscape has evolved with the emergence of cutting-edge biometric authentication methods like fingerprint scanning, retina recognition, and facial identification. These innovations have significantly mitigated the security vulnerabilities previously associated with ATMs. To surmount such challenging factors, a novel multimodal biometric-based authentication is introduced for ATM transactions. Traditionally, the MultiBank Provider (Pvt Company) provides an ATM card with all bank access for an individual. With the help of ATM machines, multimodal authentication is accomplished by using the Multichannel EfficientNet B7 with Attention Mechanism (MEB7-AM), in which each channel carries information about each image from the Face, Retina, Fingerprint, and spectrogram. Once it is done, a single pin is required to select the bank. Further, from the selected bank with proper credentials, the money is withdrawn from the ATM machine. Lastly, the efficacy of the model is analyzed using various measures and compared among existing methodologies. Therefore, the proposed system provides the precise results of better authentication for ATM machines.