24-06-2014, 10:38 AM
Method to Improve the Security Level of ATM Banking Systems Using AES Algorithm
A Method to Improve the Security Level of ATM Banking.pdf (Size: 184.19 KB / Downloads: 47)
ABSTRACT
An embedded Crypto-Biometric authentication scheme for ATM
banking systems is proposed in our paper. In this scheme,
cryptography and biometric techniques are fused together for
person authentication to ameliorate the security level. The
fingerprint template including singular points, frequency of
ridges and minutiae are stored at the central banking server when
enrollment. At the time of transaction fingerprint image is
acquired at the ATM terminal using high resolution fingerprint
scanner. The fingerprint image is enhanced and then encrypted
using 128 bit private key algorithm. The encrypted image is
transmitted to the central server via secured channel. At the
banking terminal the image is decrypted using the same key.
Based on the decrypted image, minutiae extraction and matching
are performed to verify the presented fingerprint image belongs
to the claimed user. The authentication is signed if the minutiae
matching are successful. The proposed scheme is fast and more
secure. Computer simulations and statistical analysis are
presented
INTRODUCTION
Biometrics based authentication is a potential candidate to
replace password-based authentication. Among all the
biometrics, fingerprint based identification is one of the most
mature and proven technique. Cryptography provides the
necessary tools for accomplishing secure and authenticated
transactions [3]. It not only protects the data from theft or
alteration, but also can be used for user authentication. In a
conventional cryptographic system, the user authentication is
possession based. The weakness of such authentication systems
is that it cannot assure the identity of the maker of a transaction;
it can only identify the maker’s belongings (cards) or what he
remembers (passwords, PINs etc.) Automatic biometric
authentication is an emerging field to address this problem.
Fingerprint authentication is the most popular method among
biometric authentication. However, it is infeasible to encrypt
such a large volume of image using conventional cryptography
for the purpose of centralized fingerprint matching [6]. A strong
interest in biometric authentication is to integrate encryption key
with biometrics.
The project aims at developing a novel crypto-biometric
authentication scheme in ATM banking systems. It mainly
reduces the accessing time, when compared with manual based
banking system. ATMs are now a normal part of daily life, it
explores the accessibility barriers that ATMs present to people
with a variety of disabilities, particularly examining the access
barriers experienced by the people who are blind, vision
impaired or who have reading, learning or intellectual
disabilities.
EMBEDDED CRYPTO-BIOMETRIC AUTHENTICATION PROTOCOL
Generally, there are two basic fingerprint authentication
schemes, namely the local and the centralized matching [11]. In
the central matching scheme, fingerprint image captured at the
terminal is sent to the central server via the network and then it
is matched against the minutiae template stored in the central
server.
There are three stages in the protocol namely registration, login
and authentication. In the registration phase, the fingerprints of
ATM users are enrolled and the derived fingerprint templates are
stored in the central server. The login phase is performed at an
ATM terminal equipped with a fingerprint sensor. The proposed
block schematic of embedded crypto biometric authentication
system is shown in Fig
SIMULATION, STATISTICAL AND STRENGTH ANALYSIS
In this section, the proposed encryption scheme is tested.
Simulation results and its evaluation are presented.
5.1 Simulations
The gray level fingerprint image is shown Fig.3(a). The first 3D
permutation is performed with the key {32, 21, 0, 18, 35, 5, 15,
14, 9, 16, 12, 4, 18, 21, 6, 30}. After first round of 3D
permutation, the encrypted fingerprint image is shown in
Fig.3(b). The second round permutation is performed with the
key {7, 16, 20, 12, 4, 8, 13, 8, 9, 39, 28, 27, 1, 16, 50, 42}. After
that, the image is shown in Fig.3©. The third round permutation
is finished with a key {1, 23, 8, 19, 32, 3, 25, 12, 75, 31, 4, 10,
14, 5, 25, 13}. After this, the image is shown in Fig.3(d), which
is random looking.
CONCLUSION
An embedded Crypto-Biometric authentication scheme for ATM
banking systems has been proposed. The claimed user’s
fingerprint is required during a transaction. The fingerprint
image is encrypted via 3D chaotic map as soon as it is captured,
and then transmitted to the central server using symmetric key
algorithm [14]. The encryption keys are extracted from the
random pixel distribution in a raw image of fingerprint, some
stable global features of fingerprint and/or from pseudo random
number generator. Different rounds of iterations use different
keys.
At the banking terminal the image is decrypted using the same
key. Based on the decrypted image, minutiae extraction
and matching are performed to verify the presented
fingerprint image belongs to the claimed user. Future
work will focus on the study of stable features (as part
of encryption key) of fingerprint image, which may
help to set up a fingerprint matching dictionary so that
to narrow down the workload of fingerprint matching
in a large database