ATM Simulation with Fingerprint Verification

Submitted to

Amity University Uttar Pradesh

in partial fulfillment of the requirements for the award of the Degree of

Bachelor of Technology inComputer Science & Engineering

by

Shashank VermaTanya Gupta

under the guidance of

Mrs. Divya Sharma

DEPARTMENT OF COMPUTER SCIENCE & ENGINEERING AMITY SCHOOL OF ENGINEERING AND TECHNOLOGY

AMITY UNIVERSITY UTTAR PRADESHNOIDA (U.P.)

1

DECLARATION

We, Tanya Gupta and Shashank Verma student(s) of B.Tech (Computer Science And

Engineering) hereby declare that the project titled “ATM Simulation with Fingerprint

Verification” which is submitted by us to Department of Computer Science And

Engineering, Amity School of Engineering and Technology, Amity University Uttar

Pradesh, Noida, in partial fulfillment of requirement for the award of the degree of

Bachelor of Technology in Computer Science And Engineering, has not been

previously formed the basis for the award of any degree, diploma or other similar title

or recognition.

2

Certificate

On the basis of declaration submitted by Tanya Gupta and Shashank Verma,

student(s) of B. Tech Computer Science And Engineering, I hereby certify that the

project titled “ATM simulation using Fingerprint Verification” which is submitted to

Department of Computer Science And Engineering, Amity School of Engineering and

Technology, Amity University Uttar Pradesh, Noida, in partial fulfillment of the

requirement for the award of the degree of Bachelor of Technology in Information

Technology is an original contribution with existing knowledge and faithful record of

work carried out by them under my guidance and supervision.

To the best of my knowledge this work has not been submitted in part or full for any

Degree or Diploma to this University or elsewhere.

Noida

Date (Guide)

Department of Computer Science And

Engineering

3

ABSTRACT

The need to control access to certain information and resources has been taken

seriously nowadays due to fraud and other threats to current security systems. This

research believes that that no single method, algorithm, key or procedure is entirely

secure. Hence a combination of multiple security components is mandatory to

provide a high level of protection against fraud and other threats. This project is

about enhancing the security feature of an ATM feature by fingerprint verification.

It looks into the vulnerabilities of ATM cards, Personal Identification numbers

(PIN) or passwords widely used in systems today. As a result, the aim of the project

is to propose a framework for user identification and authentication in automated

teller machines (ATM) as opposed to PIN. This robust method of user identification

and authentication would hopefully reduce the vulnerabilities of ATM in the future.

ACKNOWLEDGEMENT

Our sincere gratitude goes to all those who cooperated and showed unconditional

interest in helping us out in this project work.

4

This Project is a result of the persistent guidance, enthusiastic views and provoking

suggestions of our Faculty Guide, Mrs.Divya Sharma. We well appreciate the time

she took out from his busy schedules to tend to all our queries. We express our

genuine gratitude to him for welcoming and accepting our ideas, for providing all the

facilities needed during the project development and for always bringing out the best

in us.

We must acknowledge our deep debt of gratitude to numerous faculty members

whose great and masterly work we have consulted during the preparation of this Final

Year Project.

Last but never the least, we would like to acknowledge the ongoing support of our

respective family members as well as friends who helped us throughout our project by

providing moral support and helping us in solving problems we faced during the

project.

Date –

Noida

Tanya Gupta

Shashank Verma

5

CONTENTS

Candidate’s Declaration iii

Certificate iv

Acknowledgements v

Abstract vi

Contents xv

List of Figures

List of Tables

CHAPTER 1 INTRODUCTION 17

1.1 Problem Statement . . . . . . . . . . . . . . . . . . . . . . . . . . . . 17

1.2 Motivation and Challenges . . . . . . . . . . . . . . . . . . . . . . . . 17

1.3 Using Biometrics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 18

1.4 What is fingerprint? . . . . . . . . . . . . . . . . . . . . . . . . . . . 18

1.5 Why use fingerprints? . . . . . . . . . . . . . . . . . . . . . . . . . . . 19

1.6 Using fingerprint recognition system for ATM System. . . . . . . . . 19

1.7 Organization of the thesis . . . . . . . . . . . . . . . . . . . . . . . . 19

CHAPTER 2 AUTOMATED TELLER MACHINE FRAMEWORK 21

2.1 Hardware - Software Level Design . . . . . . . . . . . . . . . . . . . . 21

2.2 Attendance Management Approach . . . . . . . . . . . . . . . . . . . 22

6

2.3 On-Line Attendance Report Generation . . . . . . . . . . . . . . . . . 23

2.4 Network and Database Management . . . . . . . . . . . . . . . . . . 24

2.5 Using wireless network instead of LAN and bringing portability . . . 24

2.5.1 Using Portable Device . . . . . . . . . . . . . . . . . . . . . . 30

2.6 Comparison with other student attendance systems . . . . . . . . . . 30

CHAPTER 3 FINGERPRINT IDENTIFICATION SYSTEM 33

3.1 How Fingerprint Recognition works? . . . . . . . . . . . . . . . . . . 33

3.2 Fingerprint Identification System Flowchart . . . . . . . . . . . . . . 33

9 Conclusion 73

9.1 Outcomes of this Project . . . . . . . . . . . . . . . . . . . . . . . . . 74

10 Future Work and Expectations 75

10.1 Approach for Future Work . . . . . . . . . . . . . . . . . . . . . . . 75

7

List of Figures

1.1 Example of a ridge ending and a bifurcation . . . . . . . . . . . . . . 18

2.1 Hardware present in classrooms . . . . . . . . . . . . . . . . . . . . . 22

2.2 Classroom Scenario . . . . . . . . . . . . . . . . . . . . . . . . . . . . 23

2.3 Network Diagram . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 25

2.4 ER Diagram . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 26

2.5 Level 0 DFD . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 27

2.6 Level 1 DFD . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 27

2.7 Level 2 DFD . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 28

2.8 Portable Device . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 29

3.1 Fingerprint Identification System Flowchart . . . . . . . . . . . . . . 34

8

List of Tables

9

2.1 Estimated Budget . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 22

10

Chapter 1

Introduction

Over the past three decades, consumers have been largely depending on and trust the

Automatic Teller Machine, better known as ATM machine to conveniently meet their

banking needs. Using an ATM, customers can access their bank accounts in order to

make cash withdrawals, debit card cash advances, and check their account balances as well

as purchase prepaid cellphone credit. Most ATMs are connected to interbank networks,

enabling people to withdraw and deposit money from machines not belonging to the bank

where they have their accounts or in the countries where their accounts are held (enabling

cash withdrawals in local currency).

1.1 Problem Statement

Designing a prototype model of ATM system and enhanching its security with the help of

fingerprint recognition technique.

11

Figure 1. Context diagram for the prototype system

1.2 Motivation and Challenges

Despite the numerous advantages of ATM system, ATM fraud has recently become more

widespread. Fraud techniques such as card skimming, shoulder surfing etc. have been

observed recently. In order to increase the level of security of the ATM networks use of a

biometric technique for verification along with existing PIN has been thought of a solution

to decrease the increasing number of frauds. Also in rural areas people are not educated

enough to use the ATM system. So, use of only biometric verification can help those

people access the ATMs in an easier manner and hence increase its popularity among rural

masses.

We tried to develop a prototype model for the same, which would use PIN number along

with the fingerprint verification scheme to verify the user before he/she can access his /her

account and make the transactions. However ATMs using single layer of verification ie.

Biometric verification can also be developed using our prototype model.

1.6 Using fingerprint recognition system for ATM system

12

Managing the security of the ATM system is a challenging task. This could be achieved

only by increasing the levels of protection of the system. It can be done with the help of a

fingerprint identification system developed in this project. This fingerprint

identification system uses existing as well as new techniques in fingerprint recognition

and matching. A new one to many matching algorithm for large databases has been

introduced in this identification system.

Chapter 2 13

Literature Review

2.1 Biometrics

Biometrics is a technique that analyzes human characteristics to distinguish one

person from another. It uses unique, measurable characteristics or traits of a human

being for automatically recognizing or verifying identity. Measurable biometrics

characteristics can be divided into two categories. The first category is the physical

characteristics consisting of the eye, the iris, the retina, the face, the fingerprints, hand

geometry, finger geometry, palm print,

vein patterns, and ear shape. The second category is the behavioral characteristics

such as signature, voice, keystroke, and body odor. Nine biometrics technologies have

been compared and it was concluded that fingerprinting is the only technology that is

legally accepted, readily automated and matured which has been used and accepted

14 in forensic application since the 1970s. Although signatures are also legally

acceptable biometrics, they are facing issues on accuracy, forgery and behavioral

variability for automatic identification. Therefore, the best biometrics technique is

fingerprint recognition, since it is the most mature technology and has been accepted

all over the world.

2.1.1 The Fingerprint

The fingerprint is the easiest ‘something you are’ characteristic to capture

and process. It is also very easy for a user to supply and the technology is

neither invasive nor inconvenient. In fact, among all the biometrics

techniques, fingerprint based identification is the oldest method which has

been successfully used in numerous applications.

Fingerprinting is one of the most mature technologies and considered

legitimate evidence in courts of law all over the world (Jain er al., 2001). It

is also used in forensic investigations. Recently, an increasing number of

civilian and commercial applications are either using or actively considering

using fingerprint based identification because of a better understanding of

15fingerprints and furthermore, its matching perfonnance is better than any

14

other existing biometrics technologies (Jain er al. , 2001).

A fingerprint is believed to be unique to each person and also each finger. It

is unique in terms of the arrangement of its minutiae. Even identical twins

have different fingerprints and they do not change over time. This can be described by the

probabilistic model as:

P(C) = P(N).P(M).P(A) (2.1)

where: P(N) = f(Poisson’s Law)

P(M) = f(frequency of appearance of minutiae type)

P(A) = f(no. of possible permutations of minutiae)

From the probabilistic model, it is calculated that the

probability of finding two identical fingerprints is one over eight billions

fingerprints.

2.1.2 Capturing Fingerprint Methods

There are two ways of capturing the fingerprint image: inked (offline) and

live scan (ink less). For the inked methods, a fingerprint is

obtained by an impression of it on a paper and then scanned using a flatbed

document scanner. This method is usually used in law enforcement to

identify suspects from the crime scene.

In the live scanning, there are three main methods to capture fingerprint

images: the optical, the capacitive and the thermo conductive. The optical method is

implemented with a small camera and light

source to capture an image of a fingerprint. The capacitive method makes

full use of the human body’s natural electrical charge to measure the

differences in capacitance value between ridges and valleys in a fingerprint;

algorithms are then used to construct an image from the capacitance values.

The last method, which is the thermo conductive method, is done by

measuring the human tissue characteristic thermal conductivity differences

between the ridges and the valleys of a fingerprint. In other words, the

ridges and valleys conduct heat at different rates and these differences can

be registered. The last two methods are reliable for differentiating a living

finger and a dead finger.

15

2.1.3 Fingerprint Representation

Fingerprint representation, commonly known as template, can be classified

into two types: local and global. For the local type of fingerprint

representation, the information of the fingerprint is based on the entire

image, finger ridges, and pores on the ridges or salient features derived from

the ridges (Jain et al., 2001). Representation predominantly based on ridge

endings or bifurcations is the most common.

Figure 2 1: Ridge ending and ridge bifurcation.

The combination of ridge endings and ridge bifurcations is known as

minutiae. Representations of fingerprints based on minutiae are made

because the captured minutia consist of individual information and is

storage efficient and its detection is relatively robust to various sources of

fingerprint degradation. The template relies on the minutiae locations and

the directions of the ridges.

For the global type, on the other hand, the information is contained in the

global pattems of ridges, which provides more infonnation including the

fingerprint critical points such as core and delta (Figure 2 2). It can be used

in a large scale fingerprint identification system which classified the

fingerprints into categories based on the information contained in the global

patterns of ridges. The classification elaborates methods of manual systems

to index individuals into bins based classification of their fingerprint. These

methods eliminate the need to match an input fingerprint(s) to the entire

fingerprint database in identification system, hence reducing the computing

requirements.

Figure 2 2: Sample fingerprint with core and delta marked

2.1.4 Feature Extraction16

Feature extraction deals with detecting the ridge endings and the ridge

bifurcations from the input fingerprint images. In practice, it is not always

possible to obtain a perfect ridge map in an input fingerprint due to a

number of factors such as aberrant formations of epidermal ridges of

fingerprints, postnatal marks, occupational marks, etc.. Therefore in order to

get a better feature of the fingerprint, there are five methods to extract the

feature on the fingerprint images:

i. Orientation Estimation

Orientation estimation deals with the orientation field of a fingerprint image

which represents the directionality of ridges in the fingerprint image. The

fingerprint image is divided into a non overlapping block such as 32 by 32

pixels and an orientation representative of the ridges in the block. The block

orientation could be determined from the pixel gradient using either

averaging method, voting method or optimization method (Jain et al., 2001).

ii. Segmentation

Segmentation is done to localize the portion of a fingerprint image depicting

the finger (foreground). Two ways of segmentation are known as global or

adaptive thresholding. A reliable approach for segmentation exploits the fact

that there is a significant difference in the magnitudes of variance in the

gray levels along and across the flow of a fingerprint ridge. The block size for variance

calculation typically spans one to two

inter ridge distances.

iii. Ridge Detection

Ridge detection can be done by either the simple or the thresholding

approach. These approaches might not work for noisy and low contrast

portions of a fingerprint image. The important criterion is the gray level

values of the ridges on a fingerprint image which attain their local maxima

along a direction normal to the local ridge orientation. Based on these

criteria, pixels are identified to be the ridge pixels. Extraction of ridges can

be thinned or cleaned using standard thinning and cormected components

algorithms. 17

iv. Minutiae Detection

After the thinning process is done, the ridge pixels with three ridge pixel

neighbors are identified as ridge bifurcations and those with one ridge pixel

neighbor is identified as ridge endings. However, the minutiae are not

genuine due to image processing artifacts and noise present in the

fingerprint image.

v. Postprocessing

Finally, genuine minutiae are gleaned from the extracted minutiae using a

number of heuristics. For example, too many minutiae in a small

neighborhood may indicate the presence of noise and can be discarded. Very

close ridge endings oriented anti parallel to each other may indicate

spurious minutiae generated by a break in the ridge due to poor contrast or a

cut in the finger. Two closely located bifurcations sharing a common short

ridge suggest the presence of extraneous minutiae generated by bridging of

adjacent ridges as a result of dirt or image processing artifacts.

2.1.5 Fingerprint Matching

The fingerprint is matched by comparing the captured image and the present

image provided by the user. The objective of fingerprint matching is to

determine whether the prints represent the same finger or not. Users are

identified by using several approaches either image based, ridge pattem

based or point (minutiae) pattern based fingerprint representations. The

point pattern matching (minutiae matching) approach facilitates the design

of a robust, simple and fast verification algorithm while maintaining a small

template size.

The matching phase defines the distance metric between two fingerprint

representations and determines whether a given pair of representations is

captured from the same finger (known as mated pair). The determination is

based on whether this quantified distance is greater than a certain threshold.

21Its distance metric or similarity is based on the concept of correspondence in

minutiae based matching. A minutia in the presented fingerprint and a18

minutia in the stored fingerprint template are said to be corresponding if

they are identical.

Characteristics registered for fingerprint matching includes the core, which

approximates the centre of the pattern, and the axis, which represents the

vertical orientation of the finger

Figure 2 3: A fingerprint image showing core, axis marker, and marked

minutae

Chapter 3

19

Project Design and Implementation

The application will employ vb.net on the front-end and Microsoft Access on the back-end.

4.1 Hardware Requirements

(i) Any screen resolution (more than or equal to 800 X 600) would work.

(ii) Pentium IV processor, or above

(iii) Fingerprint scanner – URU4000B

4.2 Software Requirements

(i) Windows XP/Vista

(ii) Microsoft Visual Studio 2008

(iii) Microsoft Access

5.1 Hardware - Software Level Design

Required hardware used should be easy to maintain, implement and easily available.

Proposed model consists following parts:

(1)Fingerprint Scanner,

(2)Computer

Fingerprint scanner will be used to input fingerprint of customers into the

computer software. LCD display will be displaying the facilities that the customer can

avail and make the transactions. Computer Software will be interfacing fingerprint

scanner and LCD. It will input fingerprint, will process it and extract features for

matching. After matching, it will update database entries of the customer and keep

a record of any transaction made by him/her.

20

Figure 2.1: Fingerprint scanner

5.2 Approach

Our system integrate biometric identification into normal, traditional authentication

technique use by electronic ATM machines nowadays to ensure a strong, unbreakable

security and also non-repudiate transactions. In order to demonstrate the strength of our

proposed authentication protocol using the combination of three authentication methods of

card, PIN and fingerprint, we used U.are.U 4000 fingerprint biometrics development kit

manufactured by Digital Persona Software Limited.

The proposed design involves two phases namely registration phase and verification phase.

Each of the phases is briefly describe below.

Registration Phase

Prior to an individual being identified or verified by a biometric device, the registration

process must be completed. The objective of this registration process is to create a profile of

the user. This process is carried out by the administrator of the system. The process consists

of the following two steps:

1. Sample Capture: The user allows three biometric readings by placing a finger on a

fingerprint reader. The quality of the samples, together with the number of samples taken,

will influence the level of accuracy at the time of validation. Not all samples are stored; the

technology analyzes and measures various data points unique to each individual. The

number of measured data points varies in accordance to the type of device.

21

2. Conversion and Encryption: The individual’s measurements and data points are

converted to a mathematical algorithm and encrypted. These algorithms are extremely

complex and cannot be reversed engineered to obtain the original image. This algorithm is

further stored in the database or server.

Figure. Flowchart for the registration process

Identification and Verification - Once the individual has been enrolled in a system, he/she

can start to use biometric technology to have access to his account via the ATM machine to

authorize transactions.

1. Identification: a one-to-many match. The user provides a biometric sample and the

system looks at all user templates in the database. If there is a match, the user is granted

access, otherwise, it is declined.

22

2. Verification: a one-to-one match requiring the user provides identification such as a PIN

and valid ATM card in addition to the biometric sample. In other words, the user is

establishing who he/she is and the system simply verifies if this is correct. The biometric

sample with the provided identification is compared to the previously stored information in

the database. If there is a match, access is provided, otherwise, it is declined.

Figure. Flowchart for the verification process

After the verification process, the user can carry on with his/her transactions such as balance

inquiry, balance withdrawal, balance transfer etc.

3.1 User Interfaces

Administrator interface. Will enable administrator to add new users, view existing

23

users and delete users.

User interface. Will enable users to acess their accounts and make necessary

transactions.

3.2 Operations

The product release covers all automated aspects of the database. The tables in the database

have to be maintained on the server side.

3.3 Product Functions

The System will allow access to two kind of users(administrator and customers).The

administrator shall enter the details of the customers with the primary key being their

scanned fingerprint images . The Log-in times shall be monitored as a real time system,

since as soon as the customer authenticates himself/herself he/she is allowed to make the

required transactions. The system shall have all the transaction details entered into the

database, hence a proper account would be maintained of the customers transactions.

3.4 Constraints

Due to limited features in the Standalone Development, simultaneous log-ins of the Users

(i.e user and Administrator) is not feasible.

3.10 EXTERNAL INTERFACES

(i) Login Screen:

Input: login PIN

Data format: text or numeric

Output destination: Database table

(ii) Registration Screen:

Input: Username , fingerprint image, balance

Data format: text or numeric

Output destination: Database table

24

(iii)Home Page:

Displays the basic information of the user logged in along with the facilities the user can

avail.

Data format : text, numeric , pictorial.

(iv)Withdraw Amount Screen:

Requests you to enter the amount you want to withdraw from your account.

Data format : text, numeric , pictorial.

(v)Balance Inquiry Screen:

Informs you how much balance you have in your account.

Data format : text, numeric , pictorial.

(vi)Mini Statement Screen:

Informs you about your last 5 transactions.

Data format : text, numeric , pictorial.

(vii)Funds transfer Screen:

Requests you to enter the account number and the amount of money you want to transfer to

that account.

Data format : text, numeric , pictorial.

.

5.6 Comparison with other ATM systems

Typically, a user inserts into the ATM a special plastic card that is encoded with

information on a magnetic strip. The strip contains an identification code that is transmitted

to the bank's central computer by modem. To prevent unauthorized transactions, a personal

25

identification number (PIN) must also be entered by the user using a keypad. The computer

then permits the ATM to complete the transaction; most machines can dispense cash, accept

deposits, transfer funds, and provide information on account balances..

Figure. ATM authentication process

Integrating ATM system with the biometric authentication techniques is a solution to avoid

the fraud. Biometric authentication ensures that a person is actually present rather than their

cards and passwords without requiring the user to remember anything. Among all the

biometrics, fingerprint based identification is one of the most mature and proven technique.

Banks can choose different authentication schemes for their customers at their ATM’s ie

single level (only biometric authentication) or dual level authentication (PIN combined with

biometric authentication).

Figure. Proposed prototype

5.7 Fingerprint Identification System

An identification system is one which helps in identifying an individual among

26

many people when detailed information is not available. It may involve matching

available features of customer like fingerprints with those already enrolled in database.

5.7.1 How Fingerprint Recognition works?

Fingerprint images that are found or scanned are not of optimum quality. So we

remove noises and enhance their quality. We extract features like minutiae and others

for matching. If the sets of minutiae are matched with those in the database, we call

it an identified fingerprint. After matching, we perform post-matching steps which

may include showing details of identified candidate, marking attendance etc. A brief

flowchart is shown in next section.

5.8. Fingerprint Identification System Flowchart

A brief methodology of our Fingerprint Identification System is shown here in follow-

ing flowchart. Each of these are explained in the later chapters.

27

Figure 3.1: Fingerprint Identification System

Flowchart

28

1. PLAN AND SCHEDULE

S. NO Set of definable

tasks

Start Date End Date Cost estimated

1. Planning and

reviewing

literature for the

project

10.12.11 23.12.11 Nil

2. Purchasing the

device and

finishing the

design and

coding modules

2.01.12 10.03.12 Rs. 5800

3. Testing and

error correction;

debugging;

Change

management

11.03.12 4.04.12 Nil

4. Report

generation

4.04.12 23.04.12 Rs. 500

TABLE 1: Schedule for the project completion

29

Chapter 4

Simulation

4.1 VB.NET

Visual Basic .NET is one of the two flagship languages (with C#) for the .NET framework

from Microsoft. Despite being called Visual Basic, it is actually not backwards-compatible

with VB6, and any code written in the old version will not compile under VB.NET.

As a language, Visual Basic.NET has the following traits:

Object-Oriented

As with all .NET languages, VB.NET includes full-blown support for object-oriented

concepts, including simple inheritance. Everything in VB.NET is an object, including all of

the primitives (Short, Integer, Long, String, Boolean, etc.) as well as types, events, and even

assemblies. Everything inherits from the Object base class.

Event-Driven

All previous versions of Visual Basic were event-driven, but this feature is heavily

enhanced under the .NET framework. Events are no longer recognized because they use a

certain naming convention (ObjectName_EventName), but now are declared with a Handles

ObjectName.EventName clause. Event handlers can also be declared at runtime using the

AddHandler command.

.NET Framework

As the name implies, VB.NET runs on top of Microsoft's .NET framework, meaning the

language has full access to all of the supporting classes in the framework. It's also possible

to run VB.NET programs on top of Mono, the open-source alternative to .NET, not only

under Windows, but even Linux or Mac OSX.

4.2 Microsoft Access

Microsoft Office Access, previously known as Microsoft Access, is a database management

system from Microsoft that combines the relational Microsoft Jet Database Engine with

a graphical user interface and software-development tools. It is a member of the Microsoft

Office suite of applications, included in the Professional and higher editions or sold

separately. On May 12, 2010, the current version of Microsoft Access 2010 was released by

Microsoft in Office 2010; Microsoft Office Access 2007 was the prior version.30

MS Access stores data in its own format based on the Access Jet Database Engine. It can

also import or link directly to datastored in other applications and databases.[1]

Software developers and data architects can use Microsoft Access to develop application

software, and "power users" can use it to build software applications. Like other Office

applications, Access is supported by Visual Basic for Applications, an object-

oriented programming language that can reference a variety of objects including DAO (Data

Access Objects), ActiveX Data Objects, and many other ActiveX components. Visual

objects used in forms and reports expose their methods and properties in the VBA

programming environment, and VBA code modules may declare and call

Windows operating-system functions.

4.3 U.are.U 4000B Fingerprint Scanner

The U.are.U 4000B is a USB fingerprint reader designed for use with DigitalPersona’s

enterprise software applications and developer tools.

The user simply places their finger on the glowing reader window, and the reader quickly

and automatically scans the fingerprint. On-board electronics calibrate the reader and

encrypt the scanned data before sending it over the USB interface.

DigitalPersona products utilize optical fingerprint scanning technology for superior

quality and product reliability. The U.are.U 4000B Reader and DigitalPersona fingerprint

recognition software engine have an unmatched ability to recognize

even the most difficult fingerprints.

31

Chapter 5

Discussion of Results

32

Chapter 6

Conclusion

Throughout the project, the focus has been on enhancing the process of

identification and authentication on the automatic teller machine (ATM). The

project has proposed the use of the fingerprint as a suitable

substitution for the personal identification number (PIN). This chapter summarizes the

analysis for justifying the use of fingerprint and smart card, then concludes the project and

states future directions.

6.1 The Fingerprint vs. the Personal Identification Number (PIN)

Fingerprints are the most acceptable biometrics all over the world in identifying a

person. It is the characteristic that can prove a person is the person he/she claims to

be. It is also the mature technology for automated identification systems because it

has evolved way back since 1970. Until now some governments in the

world are still implementing fingerprint techniques to identify their citizens, and the

criminal from the scene of crimes in forensic work. In this research, fingerprint is

chosen for its uniqueness, ease of use and also convenience to the user. From the

experience and the analysis on the prototype, the advantages of the fingerprint are

listed below:

a. Fingerprints cannot be stolen, lost or inadvertently passed to others as the

fingerprint is always possessed by its owner.

b. It is not transferable, as it always attached to the body.

c. The user does not have to memorize the fingerprint. The only memory

needed by the user is which finger they need to use to gain access.

d. The uniqueness of a finger can be used repeatedly to gain access to other

applications as well without fear of it being duplicated.

The prototype system has implemented fingerprint identification to carefully identify

the authorized user for accessing the system, gain services offered and access their

account information.

33

From the analysis and experience gained throughout the research, it is found that the

fingerprint technology is the best technology to be used in identifying user. With the

help of the SDK, the implementation of the fingerprint was relatively easy. Without

the SDK, the prototype development process would be time consuming and

complicated.

The prototype system as a whole has integrated the fingerprint technologies for user

identification and authentication in accessing the ATM.

Database used in the research provides some data for the client

system to do the operations normally done by the ATM. Although it is a simple

database, it is adequate enough for the user to carry out the transaction using the

client system.

Even though the system has not been tested using the actual machine, the system was

found to be better than the conventional ATM system based on the advantages

possessed by the main components (i.e., fingerprint). The research

has shown that using ‘something you are’ (i.e., fingerprint), would be a better

identification method rather than using ‘something you know’ (i.e., PIN).

This robust prototype system that relies on some unchanging, difficult to forge entity will

hopefully reduce the ATM vulnerabilities.

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Chapter 7

Future Prospects

35