VISVESVARAYA TECHNOLOGICAL UNIVERSITY
“Jnana Sangama”, Belagavi, Karnataka, India.
A Seminar Report
On
Biometric in Secure E-Transaction
Submitted in partial fulfillment of the requirement for the award of the degree
of
Bachelor of Engineering
in
Computer Science and Engineering
Submitted By
ANUSHREE H R
[1DT20CS017]
Under the guidance of
Dr. Bhagyashri R Hanji
Professor
Department of Computer Science and Engineering
(Accredited by NBA 2019-2022)
DAYANANDA SAGAR ACADEMY OF TECHNOLOGY AND MANAGEMENT
Kanakapura Road, Udayapura, Bengaluru- 560082
2023–2024
DAYANANDA SAGAR ACADEMY OF TECHNOLOGY AND
MANAGEMENT
Department of Computer Science and Engineering
Bengaluru – 560082
CERTIFICATE
Certified that the Technical Seminar Entitled “Biometric in Secure E-Transaction” carried out by
ANUSHREE H R, bearing 1DT20CS017, bonafide student of Dayananda Sagar Academy of
Technology and Management,in partial fulfillment for the award of the BACHELOR OF
ENGINEERING in Computer Science and Engineering from Visvesvaraya Technological
University, Belagavi during theyear2022-2023.Thereporthasbeenapproved as it satisfies the academic
requirements in respect of the Technical Seminar work prescribed for the said degree.
Dr. Bhagyashri R Dr. Kavitha C
Hanji Professor & Head
Professor Dept. of CSE
Dept. of CSE DSATM, Bengaluru
DSATM,Bengaluru
ACKNOWLEDGEMENT
The satisfaction and the euphoria that accompany the successful completion of any task
wouldbeincompletewithoutthementionofthepeoplewhomadeitpossible.Theconstantguidance
ofthesepersonsandencouragementprovided,crownedoureffortswithsuccessandglory.Although it is
not possible to thank all the members who helped for the completion of the seminar work
individually, I take this opportunity to express my gratitude to one andall.
I am grateful to the management and our institute DAYANANDA SAGAR ACADEMY OF
TECHNOLOGY AND MANAGEMENTwith its very ideals and inspiration for having provided
me with the facilitieswhich made thiswork a success.
I express my sincere gratitude to Dr. M Ravishankar, Principal, Dayananda Sagar Academy of
Technology and Management for the support and encouragement.
I wish to place on record, my grateful thanks to Dr. Kavitha C, Head, Department of CSE,
Dayananda Sagar Academy of Technology and Management, for the constant encouragement
provided to me.
I am indebted with a deep sense of gratitude for the constant inspiration, encouragement, timely
guidance and valid suggestion given to me by my guide Dr. Bhagyashri R Hanji, Proffesor,
Department of CSE, Dayananda Sagar Academy of Technology and Management.
I am thankful to all the staff members of the department for providing relevant information and
helped in different capacities in carrying out this academic work.
Last, but not least, I owe my debts to my parents, friends and also those who directly or indirectly
have helped me to make the seminar a success.
Date: 26-03-2024 Anushree H R [1DT20CS017]
ABSTRACT
Information security is concerned with the assurance of confidentially, integrity and availability of
information in all forms. This is the ancient Greek word: bios = “life” and metron = “measure.” In the
present day world, online shopping using WAP enabled mobile phone has widely come into use. Credit
cards serve as the currency during e-business and e-Shopping. As the Hacking or Spoofing or the Misuse
of the credit card is continuously increasing even you are using a secure network. Also, some Spam
software is sent to your system or device through the internet that helps spammers to get the desires
relevant information about your credit card and financial data. To solve these problems or get out of these
insecurities the Bio-metric System that provides the secure E-transaction by improving the prevention of
data spoofing. So in this paper, we have proposed a multi-biometric model (integrating voice, fingerprint
and facial scanning) that can be embedded in a mobile phone, this making e-transactions more secure.
In the digital age, secure e-transactions are vital for ensuring the integrity and confidentiality of sensitive
financial and personal information. Traditional authentication methods such as passwords and PINs are
susceptible to various security threats including phishing attacks and brute-force hacking. Biometric
authentication has emerged as a promising solution to bolster the security of e-transactions by utilizing
unique physiological or behavioural characteristics of individuals.
This paper presents an overview of biometric authentication methods and their application in secure e-
transactions. We explore various biometric modalities including fingerprint recognition, iris scanning,
facial recognition, and voice authentication, highlighting their strengths and limitations in the context of
e-commerce and online banking. Additionally, we discuss the importance of multi-factor authentication
incorporating biometrics alongside other authentication factors for enhanced security.
TABLE OF CONTENTS
Sl. Page
Contents
No No.
1. Acknowledgement 3
2. Abstract 4
3. Table of Contents 5
4. Introduction 6
5. System Architecture 7
6. Reflection Notes on Implementation 8-9
6.1 Steps in implementing Biometrics
6.2 Biometric Authentication Methods
7. Reflection Notes on Results 10-11
Conclusion 12
References 13
Biometric in secure e-transaction
CHAPTER 1
INTRODUCTION
This paper provides a broad overview of the subject of biometrics, their usage, how performance
is measured, the typical construction of systems and practical implementation issues. A basic
understanding of computer networks is requisite in order to understand the principles of network
security. A network has been defined as any set of interlinking lines resembling a net, a network
of roads an interconnected system, a network of alliances. This definition suits our purpose well.
A computer network is simply a system of inter connected computers.
Moving on to the definition of biometrics, a biometric system is a recognition system, which
makes a personal identification by determining the authenticity of a specific physiological or
behavioral characteristic possessed by the user. This method of identification is preferred over
traditional methods involving passwords and PIN numbers for various reasons. Bioinformatics is a
new engineering field served by traditional engineering curricula. Bioinformatics can be defined in
several ways, but the emphasis is always on the use of computer and statistical methods to
understand biological data, such as the voluminous data produced by high throughput biological
experimentation including gene sequencing and gene chips. Bioinformatics, the application of
computational techniques to analyze the information associated with bimolecular on a large-scale,
has now firmly established itself as a discipline in molecular biology and encompasses a wide
range of subject areas from structural biology, genomics to gene expression studies.
Bioinformatics is an integration of mathematical, statistical and computer methods to analyze
biological, biochemical and biophysical data. Biometric is a physical or biological attribute that
can be measured. Biometric identification accepts or rejects the person’s identity, based on his/her
physiological or behavior characteristics. A biometric identification system is essentially a pattern
-recognition system that recognized a person based on a feature derived from specific
physiological or behavior characteristics the person possessed for authentication or identification
purposes.
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Biometric in secure e-transaction
CHAPTER 2
SYSTEM ARCHITECTURE
System Architecture for Biometric Authentication:
1. Data Acquisition: Biometric sensors capture unique physiological or behavioural
characteristics like fingerprints, iris patterns, facial features, voice, or gait.
2. Pre-processing: Raw biometric data is processed to enhance quality, remove noise, and
extract features that are distinctive for each individual.
3. Feature Extraction: Algorithms extract key features from the biometric data to create a
unique template that represents an individual's biometric identity.
4. Template Creation: The extracted features are converted into a template, which is stored
securely in a database or on a smart card.
5. Matching Process: During authentication, the live biometric data is captured and compared
with the stored template using matching algorithms to determine if there is a match.
6. Decision Making: Based on the matching score obtained, a decision is made to either accept
or reject the individual's identity.
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Biometric in secure e-transaction
CHAPTER 3
REFLECTION NOTES ON IMPLEMENTATION
Steps in implementing Biometrics:
Implementing biometrics in secure e-transactions involves integrating biometric authentication
methods into the transaction process to enhance security and user verification. Here's an overview
of how it can be implemented:
1. Biometric Enrollment: Users need to enroll their biometric data (such as fingerprints, iris
scans, facial recognition, etc.) securely into the system. During this process, the biometric
data is captured and converted into a digital format.
2. Biometric Database: A secure database is created to store the enrolled biometric data. It's
crucial to ensure that this database is encrypted and follows strict security protocols to prevent
unauthorized access.
3. Integration with E-Transaction System: The biometric authentication system needs to be
integrated with the e-transaction platform. This integration can occur at various stages of the
transaction process, depending on the specific requirements and security measures.
4. Biometric Authentication: When a user initiates an e-transaction, they are prompted to
authenticate themselves using their biometric data. The system captures the biometric
information at that moment and compares it with the stored data in the biometric database.
5. Biometric Matching: The captured biometric data is compared with the stored biometric
templates using matching algorithms. These algorithms analyze the similarities between the
captured biometric data and the stored templates to determine if there is a match.
6. Authentication Decision: Based on the results of the biometric matching process, the system
makes an authentication decision. If the captured biometric data matches the enrolled data
within an acceptable threshold, the user is authenticated, and the e-transaction proceeds.
Otherwise, access is denied.
7. Transaction Confirmation: Once the user is successfully authenticated, they can proceed
with the e-transaction. Depending on the specific requirements of the transaction, additional
security measures such as OTP (One-Time Password) verification or transaction PIN may
also be employed.
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Biometric in secure e-transaction
8. Logging and Auditing: All authentication attempts and transaction activities should be
logged for auditing purposes. This helps in tracking any suspicious activities and maintaining
a record of user interactions with the system.
9. Continuous Improvement: Continuous monitoring and updating of the biometric system are
essential to adapt to emerging threats and technological advancements. Regular security
assessments and updates should be performed to ensure the system's integrity and
effectiveness.
By implementing biometrics in secure e-transactions, organizations can significantly enhance
authentication security, reduce the risk of fraud, and improve the overall user experience by
offering a more convenient and reliable authentication method.
Biometric Authentication Methods:
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CHAPTER 4
REFLECTION NOTES ON RESULTS
The results of biometric authentication systems are generally presented in terms of their
effectiveness in correctly identifying or verifying individuals. These results are crucial for
evaluating the performance and reliability of biometric systems across various applications. The
key metrics used to measure the results include:
1. True Positive Rate (TPR) or Sensitivity
This metric indicates the proportion of genuine attempts that are correctly identified or verified by
the system. A high TPR means that the system is effectively recognizing legitimate users.
2. True Negative Rate (TNR) or Specificity
It measures the proportion of impostor attempts that the system correctly identifies as
unauthorized. A high TNR indicates effective security against unauthorized access.
3. False Accept Rate (FAR) or False Match Rate (FMR)
FAR refers to the percentage of times the system incorrectly identifies or verifies an impostor as a
legitimate user. It is crucial for security purposes, as a lower FAR means the system is less likely
to grant access to unauthorized users.
4. False Reject Rate (FRR) or False Non-Match Rate (FNMR)
FRR measures the frequency at which the system incorrectly rejects an access attempt by a
legitimate user. For user convenience and efficiency, a lower FRR is preferred, as it means
legitimate users are granted access more consistently.
5. Equal Error Rate (EER)
EER is the point at which the rates of false accepts and false rejects are equal. It is often used as a
summary measure of the system's accuracy. A lower EER indicates a better balance between
security and usability.
6. Decision Threshold
The system's performance can often be adjusted by changing the decision threshold, which affects
the trade-off between FAR and FRR. This adjustment allows system administrators to tailor the
biometric system’s performance to the specific security and usability requirements of an
application.
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Biometric in secure e-transaction
7. Throughput Rate
This metric indicates the speed at which the system processes authentication attempts. A
higher throughput rate means the system can handle more authentication attempts in a given time
frame, which is important for user experience in high-traffic scenarios.
Practical Implications
The results from these metrics provide a comprehensive overview of a biometric system's
effectiveness, but they need to be considered in the context of the specific application and its
requirements. For example:
High-security environments may prioritize a low FAR, even at the cost of a higher FRR.
Consumer applications, where user convenience is paramount, might accept a higher FAR to
ensure a lower FRR.
Ultimately, the results of biometric authentication systems are a balance between security,
convenience, and operational efficiency, tailored to the needs and priorities of the specific use
case.
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Biometric in secure e-transaction
CONCLUSION
Thus, this mobile multi-biometrics can be embedded in the mobile phone. The phone is cost
effective since no special hardware in required and is highly secured. Thus, this mobile phone
becomes a reality will provide more e-Business and transactions.
Implementation of biometric data can work optimally with the help of computer vision and
machine learning, the technology allows users to use the features provided in the library, data
face recognition can be used for personal data security or multi-detection, additional security
features can be used with the eye or Irish recognition , the use of this technology is strongly
influenced by camera input and lighting process, the weakness of the current face detection
technology viola jones algorithm cannot recognize the face area with a tilted position or back
to the camera then to overcome this weakness added body detection method so that the
process of securing and authentication of biometric data can be done optimally if one of the
features does not work.
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Biometric in secure e-transaction
REFERENCES
1) http://ijettcs.org/Volume2Issue2/IJETTCS-2013- 04-25-181.pdf
2) http://www.techrepublic.com/resourcelibrary/whitepapers/biometrics-in-secure-etransaction/
3) https://www.scribd.com/doc/21522715/BioMetrics-in-Secure-E-transaction
4) https://volumeoftech.wordpress.com/2013/06/07/se cure-e-transaction-through-bio-metric-system/
5) http://1000projects.org/biometric-in-secure-etransaction-computer-science-seminar-report.html
6) http://www.seminarsonly.com/computer%20scienc e/BIOMETRICS-in-SECURE-E-transactions.php
7) http://www.slideshare.net/Pathik504/slideshow-onbiometrics
8) https://www.youtube.com/watch?v=cisw-g7A_Gk
9) http://www.ijarcsms.com/docs/paper/volume3/issu e4/V3I4-0131.pdf
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