International Journal of Research In Science & Engineering
Volume: 1 Issue: 1
e-ISSN: 2394-8299
p-ISSN: 2394-8280
TOUCH ID FOR MOBILE BANKING
Sanket Kulkarni1, Akshay Kalokhe2, Shubham S.Kale3, Siddharth Joshi4
1
Student, Computer Department, SRTTC, sanket.kulkarni20@gmail.com
Student, Computer Department, SRTTC, akshaykalokhe22@gmail.com
3
Student, Computer Department, DYPIEMR, shubham.kale27@gmail.com
4
Student, Computer Department, PCCOE, siddharth9527@gmail.com
2
ABSTRACT
In today’s life everyone has their account in the bank. To access their account they have to go to the bank all the
time. Due to this there is waste of time standing in a queue for their turn to come. To avoid this now-a-days
everyone uses e-banking on their phones. This saves time for going in the bank and standing in a queue. But to
use e-banking on the phone they need password for authentication. But password authentication can be of risk.
The password can be hacked. Sometimes people forget password. To overcome this problem biometric system can
be used for authentication. Biometrics has been used efficiently for more than a decade for time and attendance
and workforce management. Despite wide use, misperception about the technology and its capabilities persist.
These concerns are easily dissipated when the facts about biometrics are recognized. Biometrics offers
unparalleled ability to quickly and accurately capture instantaneous, work data and provide a nonrepudiated
audit trail. Biometrics has undergone intense scrutiny and the results are in - when properly organized,
biometrics work well and are safe, secure, and accurate. Biometric can be of many type. For example, iris scan,
finger scan, palm scan, face recognition, etc. We can use fingerprint scanner for confirmation on our
phone. Your fingerprints are like unique keys you carry everywhere. The pattern on your finger is unique, no
one has the same pattern as you have.
Keywords : Mobile Banking, Fingerprint, Authentication, Touch ID
----------------------------------------------------------------------------------------------------------------------------1. INTRODUCTION
Imagine how expedient it would be to activate the security alarm at your home with the touch of a finger, or
to enter your home by just employing your hand on the door handle. How would you like to walk up to a nearby
ATM which will scan your iris so you can extract money without ever inserting a card or entering a PIN. You will
basically be able to achieve access to everything you are approved to, by presenting yourself as your identity. These
methods have proven to be in secure and unsafe time and time again. Similarly, when we want to access our bank
account for doing some transactions we can use finger scan for authentication instead of remembering password all
the time. The concept of biometric fingerprint was found in late 20 th century. Fingerprint recognition is a method of
biometric authentication that uses pattern-recognition methods centered on high-resolution images of the fingerprint
of an individual's finger.
2. PROPOSED SOLUTION
As we have seen earlier that password authentication for mobile banking is not safe in today’s world. To
overcome this problem we have found a solution. We can use biometric system for authentication on our phone. We
can use fingerprint scan for authentication. Because fingerprint is a unique key that you can carry with you
anywhere.
If a person want to use the e-banking on his/her mobile phone then that person has to use his/her fingerprint
to scan and access their account. If the scan is recognized then the phone will allow the user to access their account.
IJRISE| www.ijrise.org|editor@ijrise.org
International Journal of Research In Science & Engineering
Volume: 1 Issue: 1
e-ISSN: 2394-8299
p-ISSN: 2394-8280
3. PATTERN-BASED (OR IMAGE-BASED) ALGORITHM
Pattern based algorithms equate the basic fingerprint patterns (arch, whorl, and loop) between a previously
stored template and a applicant fingerprint. This requires that the images be aligned in the same orientation. To do
this, the algorithm finds a crucial point in the fingerprint image and centers on that. In a pattern-based algorithm, the
template contains the type, size, and positioning of patterns within the aligned fingerprint image. The candidate
fingerprint image is graphically equated with the template to determine the degree to which they match and a match
score is generator.
FINGERPRINT RECOGNITION SYSTEM
FINGERPRINT IMAGE CAPTURING
IMAGE PROCESSING
FEATURE EXTRACTION
TEMPLATE MATCHING
AUTHENTICATE/IMPOSTER
FIG.1. FINGERPRINT RECOGNITION SYSTEM
3.1 HOW DOES A FINGERPRINT OPTICAL SCANNER WORK?
A fingerprint scanner system has two elementary jobs -- it needs to get an image of your finger, and it
needs to determine whether the pattern of crests and valleys in this image matches the pattern of ridges and valleys
in pre-scanned images. Only specific features, which are unique to every fingerprint, are filtered and saved as an
encrypted biometric key or mathematical depiction. No image of a fingerprint is ever saved, only a series of
numbers (a binary code), which is used for authentication. The algorithm cannot be reconverted to an image, so no
one can duplicate your fingerprints.
IJRISE| www.ijrise.org|editor@ijrise.org
International Journal of Research In Science & Engineering
Volume: 1 Issue: 1
e-ISSN: 2394-8299
p-ISSN: 2394-8280
3.2 CAPACITANCE SCANNER
Like optical scanners, the capacitive fingerprint scanners generate an image of the ridges and valleys that
make up a fingerprint. But in its place sensing the print using light, the capacitors use electrical current.
The diagram below shows simple capacitive sensor. This sensor is made up of one or more semiconductor chips
containing an array of tiny cells. Each of these cell includes two conductor plates, covered with an insulating layer.
The cells are tiny -- smaller than the width of a ridge on a finger.
FIG.2. HARDWARE WORKING
The sensor is linked to an integrator, an electrical circuit built around an inverting operational amplifier.
The inverting amplifier is a intricate semiconductor device, made up of a number of transistors, resistors and
capacitors. The details of its procedure would fill an entire article by itself, but here we can get a general sense of
what it does in a capacitance scanner.
To scan the finger, the processor first closes the reset switch for each cell, which shorts each of the
amplifier's input and output to "balance" the integrator circuit. When the switch is opened again, and the processor
applies a secure charge to the integrator circuit, the capacitors charge up. The capacitance of the feedback loop's
capacitor shakes the voltage at the amplifier's input, which affects the amplifier's output. Since the distance to the
finger modifies capacitance, a finger ridge will result in a different voltage output than a finger valley.
IJRISE| www.ijrise.org|editor@ijrise.org
International Journal of Research In Science & Engineering
Volume: 1 Issue: 1
e-ISSN: 2394-8299
p-ISSN: 2394-8280
3.3 ANALYSIS
In movies, automated fingerprint analyzers classically overlay various fingerprint images to find a match.
In actuality, this isn't a mainly practical way to compare fingerprints. Smudging can make two images of the same
print look pretty dissimilar, so you're rarely going to get a perfect image overlay. Additionally, using the entire
fingerprint image in relative examination uses a lot of processing power, and it also makes it easier for somebody to
steal the print data.
In its place, most fingerprint scanner systems compare specific features of the fingerprint, generally known
as minutiae. Classically, human and computer detectives concentrate on points where ridge lines end or where one
ridge splits into two (bifurcations). Cooperatively, these and other distinctive features are sometimes called typica.
The scanner system software uses extremely intricate algorithms to identify and analyze these minutiae.
The basic idea is to measure the relative positions of details, in the same sort of way you might recognize a part of
the sky by the relative positions of stars. The simple way to think of it is to consider the shapes that various minutia
form when you draw straight lines amongst them. If two prints have three ridge endings and two bifurcations,
forming the same shape with the same scopes, there's a high likelihood they're from the same print.
3.4 PERFORMANCE EVALUATION
The algorithm that enrolls, classifies and confirms a user using the functions in libfprint library for minutiae
detection and empathy. Image goodness factor is the amount of minutiae returned by the feature extraction function
in the library. Image matching contrary to the database is done through comparison of the minutiae and subsequent
score group based on the degree of match. The library meaning BOZORTH3 does a fairly good job in image
identification and authentication and delivers the flexibility of setting the score threshold through only above which
the fingerprint is to be considered approved. The enactment of any fingerprint identification system is measured in
terms of two parameters i.e. The False Positive and The False Negative. False Positive is the situation in which an
invalid user is granted access to the system while the False Negative is a situation in which a valid user is denied
IJRISE| www.ijrise.org|editor@ijrise.org
International Journal of Research In Science & Engineering
Volume: 1 Issue: 1
e-ISSN: 2394-8299
p-ISSN: 2394-8280
access to the system. For any identification system it is very important not to grant access to an illegal user, so false
positive should be very low and ideally zero. While false negative is an troublesomeness faced by a valid user in
which he has to scan his finger again. Thus, in order to advance a more secure and accurate identification system the
rate of these two parameters should be as low as possible. With a BOZORTH score verge of 40 we observed 0 false
positive rate and 1 out of 10 false negative attempts. Finally we have a utility that can erase an enrolled user’s record
from the database.
4. ADVANTAGES
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Fingerprints are much tougher to fake than identity cards.
You can't guess a fingerprint pattern like you can guess a password.
You cannot misplace your fingerprint, like you can misplace an access card.
You can't forget your fingerprints like you can forget a password.
It also saves time from entering the password
5. CONCLUSION
This paper has presented a touch id mobile banking, in which segmentation was done using Pattern-based
(or image-based) algorithm. In this paper we are securing bank accounts of every individual. We are avoiding
hacking of the bank accounts and unwanted transactions. We are also providing the people an alternative for
remembering the password. This also saves time from entering the password and logging in. Biometric fingerprint
authentication is considered to be most secure system.
6. REFERENCES
1) Subhra Mazumdar, Venkata Dhulipala “Biometric Security Using Fingerprint
Recognition” University of California, San Diego
2) http://www.theinquirer.net/inquirer/news/2395885/mobile-banking-security-fears-raisedas-rbs-and-natwest-add-touch-id-support
3) http://www.bioelectronix.com/what_is_biometrics.html
4) http://www.explainthatstuff.com/fingerprintscanners.html
5) http://computer.howstuffworks.com/fingerprint-scanner.htm
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