SMS hashing system (Real-Time) for the reliability of financial transactions

International Journal of Research in Engineering and Science (IJRES)
ISSN (Online): 2320-9364, ISSN (Print): 2320-9356
www.ijres.org Volume 3 Issue 4 ǁ April. 2015 ǁ PP.10-15
www.ijres.org 10 | Page
SMS hashing system (Real-Time) for the reliability of financial
transactions
*Eshwar Kumar Reddy Chyagari, **Akhil Reddy Laxmanagari
Graduate Student, Cleveland State University
Graduate Student, Cleveland State University
Abstract-The sole reason to go with this project is to increase the security for the people using ATM. Once the
card and password related to it is stolen it might be a huge loss to the card holder, so to rectify this problem we
are implementing this project. Now a day’s using the ATM (Automated Teller Machine) which provide
customers with the convenient banknote trading is very common. In the recent times the cases regarding the
illegal transactions has shown a considerable increase. How to carry on the valid identity to the customer
becomes the focus in current financial circle. Traditional ATM systems authenticate generally by using the
credit card and the password, the method has some defects. In recent years, the algorithm of fingerprint
recognition has been continuously updated, which has offered new verification means for us. The original
password authentication method combined with the biometric identification technology verify the clients’
identity better and achieve the purpose that use of ATM machines improve the safety effectively.
Keywords-ATM terminal; ARM9; fingerprint recognition; Gabor filtering.
I. INTRODUCTION
With the development of computer network technology and e-commerce, the self-service banking system
has got extensive popularization with the characteristic offering high-quality 24hours service for customer.
Nowadays, using the ATM (Automatic Teller Machine) which provides customers with the convenient banknote
trading is very common. However, the financial crime cases rises repeatedly in recent years, a lot of criminals
tamper with the ATM terminal and steal user's credit card and password by illegal means. Once user's bank card
is lost and the password is stolen, the criminal will draw all cash in the shortest time, which will bring enormous
financial losses to customer. How to carry on the valid identity to the customer becomes the focus in current
financial circle.
Traditional ATM systems authenticate generally by using the credit card and the password, the method has
some defects. Using credit card and password cannot verify the client's identity exactly. In recent years, the
algorithm that the fingerprint recognition continuously updated, which has offered new verification means for
us, the original password authentication method combined with the biometric identification technology verify
the clients' identity better and achieve the purpose that use of ATM machines improve the safety effectively.
II. THE CHARACTERISTICS OF THE SYSTEM DESIGN
The embedded ATM client authentication system is based on fingerprint recognition which is designed
after analysed existed ATM system. The S3C2440 chip is used as the core of these embedded systems which is
associated with the technologies of fingerprint recognition and current high- speed network communication. The
primary functions are shown as follows:
Fingerprint recognition: The masters' fingerprint information was used as the standards of identification. It
must certify the feature of the human fingerprint before using ATM system.
Remote authentication: System can compare current Client’s fingerprint information with remote Finger print
data server.
Telephone alarming: Once an exception happens, such as log in as the fake identity, the system will start the
phone alarm to inform client and bank staff as soon as possible.
Message alarming: The message can be send to the relevant staff’s mobile phone without any noise, in order to
carry on emergency processing.
Police network connection: The system can call the police via the police network.
Two discriminant analysis methods: Besides the fingerprint recognition, the mode of password

SMS hashing system (Real-Time) for the reliability of financial transactions
recognitioncan be also used for the system.
III. HARDWARE & SOFTWARE DESIGN
The design of entire system consisted of two part which are hardware and software. The hardware are
designed by the rules of embedded system, and the steps of software consisted of three parts. The more details
are shown as follows.
A. Hardware Design
The S3C2440 chip is used as the core of entire hardware. Furthermore, the modules of LCD, keyboard,
alarm, fingerprint recognition are connected with the main chip (S3C2440).The SRAM and FLASH are also
embodied in the system. There are some modules consisted of the system as follows:
•
LCD module: The OMAP5910 is used in this module as a LCD controller, it supported 1024*1024 image
of 15 grey-scale or 3375 colours.
•
Keyboard module: It can be used for inputting passwords.
•
Alarming module: TC35i alarming module is based on GSM technology implement which can call the
credit card owner and send message to relevant staffs without any sound.
•
SRAM and FLASH: The 16-bit 29LV160BB-70REC of FLASH chip and the 32-bit HY57V561620CT-6
of SRAM chip are connected with the main chip. Their functions are storing the running code, the
information of fingerprint and the algorithm. Fingerprint recognition module: Atmel Company's
AT77CI04B be used as a fingerprint recognition. It has a 500dpi resolution, anti-press, anti-static, anti-
corrosion.
•
Ethernet switch controller: RTL8308B can provides eight 10/1 00 Mbps RMII Ethernet ports, which can
Connect police network and remote fingerprint data server.
Before using the ATM terminal, the client's fingerprint feature will be connected to the remote fingerprint
data server to match fingerprint data with the master's, if the result isn't correct, the system will call police
automatically and send alarm to the credit card owner. The block diagram of hardware design is shown in figure
1.
Figure 1: Block diagram of Hardware
Software design
The design of software is very important for this embedded system the design was component of three parts
including the design of main program flow chart, the initializing once and algorithm of fingerprint recognition
of flow chart.

This system of software is implemented by the steps as follows: first of all, the Linux kernel and the file
system loaded into the main chip. The next, the system is initialized to implement specific task, such as
checking ATM system, GSM commutation and so on, and then each module reset for ready to run commend.
Before using ATM terminal, the password and finger print is required. First need to enter owner’s
password, if password is successful then the system is required the owner’s fingerprint. If all the recognition is
right the system would enter into the waiting status. In addition, the number of time that recognition of
fingerprint and password are restricted to 3.1 for more than 3 times, the system will call police through police
network, telephone to the owner and send message to relevant staff. Then locked the owner’s credit card. The
overall flow chart of software is shown in figure 2.
Figure 2. The overall flow chart of software
In the process of inputting fingerprint, the AT77CI04B which is a linear sensor that captures fingerprint
images by sweeping the finger over the sensing area, will used for acquiring the image of fingerprint. These
products embed true hardware based 8-way navigation and click functions. The Fingerprint information will be
temporarily stored in SRAM and upload to the remote finger data server to compare through bank network. The
result of process will be controlled by main chip (S3C2440).
The initializing process means that set the hardware and software and then start the multiple mission
module, each module will be started according to the priority processes. At first, initialize the system clock, and
execute the codes of open interrupt and the open interrupt task. Then, the system would judge and enter process
of module finally, the system would start to attempt multiple tasks. The initializing flowchart is shown in
figure 3.
C. The design of fingerprint recognition algorithm
The design of algorithm based on fingerprint recognition is so vital for the whole system. We would
approach two steps to process the images of fingerprint.

Figure 3: Flow chart of fingerprint recognition
1) The detail of fingerprint recognition process:
The first step was the acquisition of fingerprint image by above device mentioned in the algorithm, and the
results could be sent to the following process.
Secondly, pre-processing the images acquired. After obtain the fingerprint image, it must be pre-
processing. Generally, pre-processing of ones is filtering, histogram computing, image enhancement and image
binarization.
Lastly, the characteristic value was extracted, and the results of the above measures would be compared
with the information of owner's fingerprint in the database so as to verify whether the character is matched, and
then the system returned the results matched or not.
2) The design of fingerprint image enhancement:
Fingerprint recognition module is an extremely important part of the system, the high-quality images was
the major factors of influencing the performance in the system. There is a lot of noise in fingerprint image, the
image enhancement was the precondition for recognition of fingerprint characteristics. The algorithm of
fingerprint recognition based on the algorithm of Gabor and direction filter was used. Finger print enhancement
algorithm based on Gabor filter could be better to remove noise, strengthen the definition between the ridge and
valley, it could significantly improve the image enhancement processing capacity, but this algorithm was slow
in dealing with the high capacity requirements. Fingerprint enhancement algorithm based on direction filter has
a faster processing capabilities, but it was not good to handing the large noise areas. so combination of these two
algorithms could obtain better effects. The algorithm based on direction filter was used in the clear area, and
based on Gabor filter was used in the recoverable region.
a) The Gabor filter algorithms
For each point, according to its frequency, direction, using formula(l) calculate the Gabor filter coefficients,
calculate the filter values of each point and then ,move to the next point, repeat the process above.

G(u, v) is normalized after the fingerprint image, g (u, v) as a template filter coefficient.
Proposed image block average M, the calculation using image block average gray level range, if the mean
was small, the variance was small, that is not to restore area; if the mean moderate, have a great variance, the
smaller the ratio of mean and variance, it could be regard as the clear area; if the mean moderate, variance and
they were smaller than the ratio of non-recovery area, it could be regard as confusion region. Image block
average calculated as follows: The fingerprint image was divided into w x w area, using equation (5), (6) in
each of a gray-scale mean and variance, And the statistics is greater than the number of M ,marked as m and
less than the number of M , markedas n.
IV. CONCLUSION
The design of ATM terminal system based on fingerprint recognition took advantages of the stability and
reliability of fingerprint characteristics, a new biological technology based on the image enhancement algorithm
of Gabor and direction filter. Additional, the system also contains the original verifying methods which were
inputting owner's password. The security features were enhanced largely for the stability and reliability of owner
recognition. The whole system was built on the technology of embedded system & Computer network which
makes the system more safe, reliable and easy to use.

REFERENCES
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[4] Cheng J, Tian J. Fingerprint enhancement with dyadic scale-space. Pattern Recognition Letters, 2004, 25(11): 1273-1284.
[5] Chen H, Tian J. A fingerprint matching algorithm with registration pattern inspection. Journal of Software, 2005, 16(6): 1046-
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[6] Smits G FJordaan E M.Improved SVMRegression using Mixtures of Kernels [A]. Proceedings of the 2002 International Joint
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