Enhancing Authentication Methods in Online Banking Using Face Recognition with Hybrid Pins
DOI:
https://doi.org/10.51699/cajitmf.v4i7.558Keywords:
Enhancing Authentication, Methods, Online Banking, Face Recognition, Hybrid PinsAbstract
Researchers have been drawn to this problem because of the increasing prevalence of authentication-related malware and the critical nature of authentication security. Since the current password-based authentication paradigms are inefficient, not robust enough, and susceptible to automated attacks, many such attacks succeed in gaining access to social network accounts. Alternatively, two-factor authentication (using a combination of a password and another piece of information, like a one-time PIN issued by the user's device or an SMS) can be used to bolster the security of single-factor authentication. This study presents a novel approach to preventing shoulder-surfing attacks on authentication systems by employing a three-layer-based authentication system. The first tier uses biometric authentication to solve security and privacy concerns in novel ways. The goal of incorporating face biometrics into a real-time authentication system is to ensure that only authorised users may access ATMs. OTP verification using reverse processing is provided at the second layer of security. Then, have a PIN-based authentication system in place that can be used with ATM software. A hybrid keypad is a keypad that employs the concept of merging two keypads with distinct digit orderings in such a way that the user, when up close to the device, sees one keypad to enter the PIN, but an attacker, when looking at the device from a further distance, sees only the other keypad. Upon entering their credentials, users activate the application's three-factor authentication process
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83. Suchismita Gupta, Bikramjit Sarkar, Subhrajyoti Saha, Indranath Sarkar, Prasun Chakrabarti, Sudipta Sahana, Tulika Chakrabarti, Ahmed A Elngar, “A Novel Approach Toward the Prevention of the Side Channel Attacks for Enhancing the Network Security”, Pre-print, 2022.
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85. K Suvarna Vani, Bui Thanh Hung, Prasun Chakrabarti, Tulika Chakrabarti, Ahmed A Elngar, “Detection and Classification of Invasive Ductal Carcinoma using Artificial Intelligence”, Pre-print, 2022.
86. KS Balamurugan, Prasun Chakrabarti, Tulika Chakrabarti, Amit Gupta, Ahmed A Elngar, Mohammad Nami, Vinayakumar Ravi, Grienggrai Rajchakit, M Ali Akbar, “Improving the Performance of Diagnosing Chronic obstructive Lung Disease Using Outlier Detection with Decision Tree Algorithm”, Pre-print, 2022.
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103. H. Patidar, P. Chakrabarti, A. Ghosh, “Parallel Computing Aspects in Improved Edge Cover Based Graph Coloring Algorithm”, Indian Journal of Science and Technology, Vol. 10, P. 25, Jul. 2017.
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2023-07-20
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Mohamed Azarudeen A, Shaik Abdullah J, Sourav Sardar, Taj Sadullah U, Taj Sadullah U, & N. Selvam ________________________________________. (2023). Enhancing Authentication Methods in Online Banking Using Face Recognition with Hybrid Pins. Central Asian Journal of Innovations on Tourism Management and Finance, 4(7), 96–113. https://doi.org/10.51699/cajitmf.v4i7.558
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