Biometrics in E-Secure Transactions: Security and Privacy Analysis

This report explores the application of biometrics in e-secure transactions, highlighting the increasing adoption of biometric devices for user identification and authentication. It focuses on the use of fingerprint scanning in mobile applications like Google Pay and Phone Pay, emphasizing the convenience and security benefits, such as eliminating the need for passwords or PINs. The report categorizes biometrics into physical, behavioral, and chemical traits, with a focus on physical traits like fingerprints. It also touches upon sensor-level fusion classes. The analysis includes the role of biometric imaging software, its advantages for customers and the banking sector, and potential issues such as sensor malfunctions. The report concludes by underscoring the importance of biometrics in securing transactions and its potential for broader applications while acknowledging potential disadvantages and security vulnerabilities.

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Biometrics in E-secure transactions
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Biometrics in e secure transaction 1
A report on biometrics in e secure transaction
Biometrics is highly used in many processes and it provides better in results in terms of security
and privacy. It is the next level of security. From the last two decades, most of the companies adopt
biometric devices in many processes for identification of the person (Bobde & Satange, 2013).
In addition, mobile applications are used to identify the user and provide access to a system. It is
the best way to identify a person. In the present time, transactions are possible through fingerprints
through a mobile application, such as Google pay, phone pay, and many others. Those applications take
a five sample of the figure of a person to authorize for a particular transaction from their mobile
application.
Most of the smartphone is having a finger scanner and it is used to identify a person through
biometrics. It provides two most important benefits, which are physically present for identification, and
no need to remember a password or PIN number (Mahto & Yadav, 2017).
Source: (Bobde & Satange, 2013)
It is having three basic types, which are physical traits, behavioral traits, and chemical traits. In
transactions, physical traits are mostly used, such as fingerprint, face, and others.

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Sensor-level fusion can be distributed in three classes, which areas:
1. Single sensor-multiple instances,
2. Intra-class multiple sensors, and
3. Inter-class multiple sensors.
Source: (Bobde & Satange, 2013)
Biometric imaging software is installed in the smartphones and it takes samples of fingerprint
and stores them into the database, which is used to the comparison between stored and present time
samples for authentication.
Moreover, it is fast and suitable for customers to use biometrics in their transactions. The
banking sector is also feeling better after this technology because of fewer issues in terms of security
and frauds. In addition, it is better for both customers and banks. Third party software is helping into
this feature, such as Google Pay (Gladis, 2018).
However, sometimes it faces a few issues in different conditions. As an example, the user got a
mark on the figure and the sensor is not sense properly. In that case, it provides alternatives, which are
PIN numbers or password, which has been generated by the user only at the time of the creation of
biometrics. Biometrics is the best way for transitions and it will use in other things as well, such as
attendance, and many others. It is a unique method to secure transactions. However, sometime hacker

Biometrics in e secure transaction 3
uses alternatives to hack their mobile phones. It has a few disadvantages as well (Ogbanufe & Kim,
2018).
References
Bobde, M., & Satange, D. (2013). Biometrics in Secure e-Transaction. International Journal of Emerging
Trends & Technology in Computer Science, 2(2).
Gladis, R. (2018, December 20). How biometrics will shape the future of mobile authentication. Retrieved
from atmmarketplace.com: https://www.atmmarketplace.com/blogs/how-biometrics-will-
shape-the-future-of-mobile-authentication/
Mahto, D., & Yadav, D. K. (2017). Security improvement of one-time password using crypto-biometric
model. In Proceedings of 3rd International Conference on Advanced Computing, Networking and
Informatics (pp. 347-353). New Delhi: Springer.
Ogbanufe, O., & Kim, D. (2018). Comparing fingerprint-based biometrics authentication versus
traditional authentication methods for e-payment. Decision Support Systems, 1-14.