Automated Teller Machine Authentication Using Biometric

Aljuaid, Shumukh M.; Ansari, Arshiya S.

doi:10.32604/csse.2022.020785

Cited by 7 publications

(2 citation statements)

References 17 publications

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“…The authors in [9] further introduce the use of three biometric features for ATM authentication. In their paper, fingerprint, face, and retinal feature recognitions are combined to improve accuracy using deep convolutional neural networks and hybrid optimization algorithms.…”

Section: Literature Reviewmentioning

confidence: 99%

Versatile Multimodal Biometrics to Prevent ATM Identity Frauds

Nkgapele¹,

Tu²,

Olaifa³

2023

IJETAE

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—Automated Teller Machine (ATM) frauds have increased over the years resulting in the loss of customers and trust in current ATM security measures. In order to fight identity fraud and regain trust and reliability, biometric recognition technologies have become a necessity for ATMs. Using a card and pin is no longer reliable due to the rise of ATM identity fraud over the years. Studies have been carried out to solve this uprising issue, such as replacing the memorized pin with a one-time pin (OTP) and others using biometrics. There are still many gaps and challenges in the systems, with a common challenge being their accuracy rate, dependencies, and reliability. This study is conducted to alleviate the problem by introducing a versatile multimodal biometrics system. After a careful review of different biometric techniques and their differences in human identification inboth accuracy and reliability, physical biometrics isadopted in this study. Unlike behaviouralbiometrics, physical biometric features cannot easily be copied, replicated, or mimicked, and they are unique per individual. The three body features chosen for this study are the face, fingerprint, and iris. A real-time feature quality evaluation method is employed to assess the reliability of the biometric recognition results. The system provides independent anytime ATM access and prevents card-based theft and fraud, it can be relied on to always deliver uninterrupted ATM services to customers. Customers register their fingerprint, face, and iris to be able to use the biometric ATMs. A combination of any two of the registered biometric features can be used to authenticate users with high accuracy and reliability on ATMs with a 0% false acceptance rate. It has been found that allowing multiple options for users reduces false rejections and provides a 100% ATM access guarantee.

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Section: Literature Reviewmentioning

confidence: 99%

Versatile Multimodal Biometrics to Prevent ATM Identity Frauds

Nkgapele¹,

Tu²,

Olaifa³

2023

IJETAE

View full text Add to dashboard Cite

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“…Since the development of openness and extensive interconnection in IIoT, security has become a global challenge in M2M communication. Although authentication is the cornerstone of providing adequate protection, and numerous schemes have been proposed to ensure security in traditional IT networks [2][3][4][5][6][7][8][9][10], these schemes cannot be readily applied for IIoT. Because in IIoT, many resourceconstrained devices are limited to computation power and communication bandwidth, such as Radio Frequency Identification (RFID) chips, wireless sensors, and so on.…”

Section: Introductionmentioning

confidence: 99%

Lightweight Authentication Protocol Based on Physical Unclonable Function

Luo¹,

Zou²,

Wu³

et al. 2022

Computers, Materials &Amp; Continua

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In the emerging Industrial Internet of Things (IIoT), authentication problems have become an urgent issue for massive resource-constrained devices because traditional costly security mechanisms are not suitable for them. The security protocol designed for resource-constrained systems should not only be secure but also efficient in terms of usage of energy, storage, and processing. Although recently many lightweight schemes have been proposed, to the best of our knowledge, they are unable to address the problem of privacy preservation with the resistance of Denial of Service (DoS) attacks in a practical way. In this paper, we propose a lightweight authentication protocol based on the Physically Unclonable Function (PUF) to overcome the limitations of existing schemes. The protocol provides an ingenious authentication and synchronization mechanism to solve the contradictions amount forward secrecy, DoS attacks, and resource-constrained. The performance analysis and comparison show that the proposed scheme can better improve the authentication security and efficiency for resource-constrained systems in IIoT.

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Stratified Transfer Learning of Touchscreen Behavior on Cross-Device for User Identification

Sun

Zhang

et al. 2022

Advances in Artificial Intelligence and Security

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Automated Teller Machine Authentication Using Biometric

Cited by 7 publications

References 17 publications

Versatile Multimodal Biometrics to Prevent ATM Identity Frauds

Versatile Multimodal Biometrics to Prevent ATM Identity Frauds

Lightweight Authentication Protocol Based on Physical Unclonable Function

Stratified Transfer Learning of Touchscreen Behavior on Cross-Device for User Identification

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