ATM System Design Using Fingerprint
Keywords:
Fingershield ATM, Fingerprint, Minutiae, Smart Card, Database Server, SkimmingAbstract
The proliferation of ATM Fraud case in Indonesia
is still the main concern for the society especially
bank customers. In March 2017, a total loss of 5
billion rupiah was recorded as a result of ATM
Frauds. While the only solution which ensures
security of ATM machines is a 6-digit PIN, there
are still a lot of security cracks that can be used by
the criminals to steal customer data and the 6-digit
PIN itself. One of the most frequent method of
ATM Fraud is skimming. Therefore, the authors
bring the concept of Finger shield ATM, ATM
Machine that implements biometric identification
in the form of fingerprints which is integrated with
smart card and database server. Fingerprint
technology is powerful identification because of its
unique characteristics of each of the minutiae.
Despite the fact that customers have to add
additional authentication time around 1.5 seconds
for fingerprint verification, the security is much
improved and guaranteed. This research will use
experimental descriptive method. With this
method, hopefully ATM Fraud can be minimized
so that the customers can feel more secure while
using ATM Machines. Based on implementation
and test results which had been done before, Finger
shield ATM functions run well and some security
parameters have passed the test, as well as almost
all specifications are met.
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References
Bank Indonesia. Statictics on ATM Card
Transaction (Online).
https://www.bi.go.id/id/statistik/sistempembayaran.
Accessed 30th of January 2018 20:00
[2] Istnick, Anna C. and Emilio Caligaris. ATM
Fraud and Security. DIEBOLD. Amerika Serikat
(2003)
[3] Vellani, Karim H. and Mark Batterson.
Security Solutions for ATM. Threat Analysis
Group (2003)
[4] Bhanushali, Nisha and Meghna Chapaneria.
Fingerprint based ATM System. Journal for
Research, Vol 2 Issue 12 pp 33-34 (2017)
[5] Patil, Mahesh, Sachin.P. ATM Transaction
Using Biometric Fingerprint Technology.
International Journal of Electronics, Vol 2 (2012)
[6] Rhydo Labz. R30X Series Fingerprint
Indentification Module User Manual. (Online).
https://rhydolabz.com/documents/fingerprintmodule.
pdf. Accessed 13th February 2018
19:10
[7] Secured Command and Protocol 7816
(XIRKA).2017. Xirka Silicon Tec.
[8] MariaDB. 2012. Basic SQL Statements
(Online). https://mariadb.com/kb/en/library/basicsql-
statements/. Accessed 20th of January 23:00
[ 9] Sergey Tulyakov, Faisal Farooq, Praveer
Mansukhani, Venu Govindaraju, “Symmetric Hash
functions for Secure Finger print biometric
systems”.
[10] Y.Donis, L. Reyzin and A.Smith, “Fuzzy
Extractors”In security with Noisy Data: Private
Biometrics, Secure key Storage and Anti-
Counterfeiting, P.Tuyls, B.Skoric and T.Kevenaar,
Eds., chpt5,pp.79-77, Springer-Verlag, 20012.
[11]. Direct Indirect Human Computer Interaction
Based Biometrics International Journal of
Emerging Engineering Research and Technology
Volume 3, Issue 3, March 2015.
[12] A.A.E. Ahmed, I. Traore, “A new biometric
technology based on mouse dynamics, IEEE
Transactions on dependable and Secure
Computing” 4 (3) (2007) 165–179.
[13]. Deshpande, S. Chikkerur, V. Govindaraju,
Accent classification in speech, Fourth IEEE
Workshop on Automatic Identification Advanced
Technologies, 17–18 October, 2014, pp. 139– 143.
[14]. F. Bannister and R. Connolly, “New Problems
for Old? Defining e-Governance”, proceedings of
the 44th Hawaii International Conference on
System Sciences, (2012).
[15]. W.-S. Chen, K.-H. Chih, S.-W. Shih and C.-
M. Hsieh, “Personal Identification Technique based
on Human Iris Recognition with Wavelet
