Multi-Modal Biometric Authentication and Secure Transaction Operation Framework for E-Banking

Sabharwal, Munish

doi:10.4018/ijbdcn.2017010109

Cited by 9 publications

(6 citation statements)

References 6 publications

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“…Clarke, et al [12] proposed smartphone's user perception of identification, in which results showed the system implicitly and continuously performing user identification in the background. Koreman, et al [47] recommended continuous multiple model-based approaches for user identification. Mantyjarvi, et al [41] used an accelerometer in television remote controls to identify individuals.…”

Section: Related Workmentioning

confidence: 99%

Extended sammon projection and wavelet kernel extreme learning machine for gait-based legitimate user identification

Khan

Mazzara

Distefano

et al. 2019

Proceedings of the 34th ACM/SIGAPP Symposium on Applied Computing

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Smartphones have ubiquitously integrated into our home and work environments, however, the user normally relies on explicit but inefficient identification processes in a controlled environment. Therefore, when the device is stolen, the attacker can have access to the user's personal information and services against the stored password/s. As a result of this potential scenario, this work demonstrates the possibilities of legitimate user identification in a semicontrolled environment through the built-in smartphones motion dynamics captured by two different sensors. This is a two-fold process, sub-activity recognition based user identification using the wavelet kernel extreme learning machine (KELM) to first recognize the performed activity and then identifies whether the recognized activity is performed by the legitimate user or impostor. Prior to the identification; Extended Sammon Projection (ESP) method has been deployed to reduce the redundancy between the features. To validate the proposed system, we first collected data from 20 users walking with their device freely placed in one of their pants pockets (front right, front left, back right and back left pocket). Through extensive experimentation's using overall and averageone-subject-cross-validation, we demonstrate that together time and frequency domain features optimized by ESP to train the KELM is an effective system to identify the legitimate user or an impostor with 97 − 98% overall accuracy.

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Section: Related Workmentioning

confidence: 99%

Extended sammon projection and wavelet kernel extreme learning machine for gait-based legitimate user identification

Khan

Mazzara

Distefano

et al. 2019

Proceedings of the 34th ACM/SIGAPP Symposium on Applied Computing

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“…al. [10] surveyed various kinds of biometric technologies updated until now. He has also suggested a multi-modal biometric authentication and secure transaction operation framework for e-banking and the same concept has been discussed by him in [11] [25] It shed some light on the concept of the confusion matrix and its related terms.…”

Section: Literature Reviewmentioning

confidence: 99%

“…That is the main reason for their rise. They can be proved to be useful in a situation where the data is not easily obtained and cannot guarantee its originality [10]. Hybrid biometrics deals with the combinational impact of both the biometrics, using human physiological patterns along with behavioral pattern [7].…”

Section: Introductionmentioning

confidence: 99%

Biometric Authentication and Identification using Behavioral Biometrics Technique of Signature Verification

2019

IJITEE

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Authentication using biometrics is on the rise due to various security concerns and especially in India with the advent of Digital India concept promoting the wide use of aadhar as an authentication mechanism. The authentication using a login and a password are fading away due to the various malpractices and fraudulent methods that have been developed which pose a threat to this kind of authentication and security mechanism. Signature verification is one of the important aspects of biometric authentication which is slowly finding its use in certain niche organizations. The present study uses an ensemble approach, stacking to authenticate or validate a user by his signature and proposes a hybrid model using three algorithms namely, Random Tree, Logistic Regression & Multi-Layer Perceptron for achieving better accuracy.

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“…The e-banking revolution, according to [1], is a tool for banks to attract and retain customers [2]. It is related to the competition among commercial banks, where consumers have the ability to become bankers, since diversity in e-banking for consumers is beyond conventional banking boundaries [3][4][5]. A secured and convenient way of making payments is the cashless transaction.…”

Section: Introductionmentioning

confidence: 99%

A cashless payment transaction (CPaT) using RFID technology

Ya’acob¹,

Yusoff²,

Sarnin³

et al. 2019

IJEECS

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<span>Virtual money is an actual money that a person own but in a form of a plastic card, an online account and a token or a ticket. Referring to the cash-base system, it is full of fraud and money scam activity. It even happens in a smaller division of a human population which are among family members. For example, when a child decided to do a money scam towards their parents by asking for extra money for what they actually needed to pay for school internal fee and with today’s technology, they can easily recreate a receipt of the payment based on the amount of money they have scammed. In this Cashless Payment Transaction (CPaT) in a school based on Low Frequency (LF) RFID Technology system, the system offers a virtual money transaction in the plastic card form and allows the transaction to be monitored by parents with the help of Radio Frequency Identification (RFID) technology, MySQL database and Email notification system. The MySQL database is paired with the PHP prgramming language where the calculation for deduction credit will be done before being updated to the RFID card and MySQL database. As a result, the system will allow a cash-free transaction for school payment activity and allow parents to monitor their child spending activity and nutrition intake via MySQL database that are designed based on Graphical User Interface (GUI) within one minute after the transaction is successfully done.</span>

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Multi-Modal Biometric Authentication and Secure Transaction Operation Framework for E-Banking

Cited by 9 publications

References 6 publications

Extended sammon projection and wavelet kernel extreme learning machine for gait-based legitimate user identification

Extended sammon projection and wavelet kernel extreme learning machine for gait-based legitimate user identification

Biometric Authentication and Identification using Behavioral Biometrics Technique of Signature Verification

A cashless payment transaction (CPaT) using RFID technology

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