IEEE-International Conference On Advances In Engineering, Science And Management (ICAESM -2012) March 30, 31, 2012 16

Fingerprint Based Authentication System Using Threshold Visual Cryptographic Technique

Rajeswari Mukeshi, V.J.Subashini2

I Department of Computer Science and Engineering, Meenakshi College of Engineering, Chennai, India

2 Department of Computer Applications, Jerusalem College of Engineering, Chennai, India

'rajimukesh9s@yahoo.co.in, 2vjsubashini@yahoo.co.in

Abstract-Biometrics deals with automated method of identifying a person or verifying the identity of a person based on the physiological or behavioural characteristic, and so is used for authentication in many of the online transactions. The biometric that has been chosen for implementation is fingerprint, since fingerprint biometric is easily available and highly reliable compared to many other biometrics. In the existing biometric authentication system the fingerprint template of a person is stored as such in the authentication server and is prone to security attacks at the server side. To overcome this kind of server side attack, in the proposed system the fingerprint template is divided into two or more shares using visual cryptographic technique followed by compression. One of these shares is stored into the server and the remaining shares are given to the users. Only these two participants who possess these transparencies can reconstruct the secret (biometric template) by superimposition of shares. This kind of approach solves two major problems related to fingerprint based automatic access control systems such as falsification and costly maintenance of the large fingerprint database.

Keywords- Visual threshold cryptography, fingerprint, Compression , template, server side attack

1. I.INTRODUCTION

The main idea of this paper is to efficiently apply the Visual Cryptographic (VC) techniques [1] onto the area of authentication using fingerprints. This paper proposes an approach of using the fingerprints, attempting to solve two major problems related to fingerprint based automatic access control systems which are falsification and the costly maintenance of the large fingerprint database. The proposed system consists of two phases. In the first phase the input fingerprint image is divided into two shares with the help of the basic visual cryptographic techniques, keeping one with the participant's ID card [2] in the compressed form and saving the other share in the biometric database of the server. In the second phase input fingerprint image is divided into N shares with the help of threshold visual cryptographic techniques, keeping one with the server and the remaining with the users participant's ID card. The share kept in the database will be the same for all the participants and it can be permuted[4] periodically. When the ID card is inserted at the

client side for authentication the share(s) extracted from it, is superimposed with the share present in the biometric database.

This superimposed image forms a secret image that is compared with the acquired fingerprint image from the user through the fingerprint sensor. For comparison of fingerprints, the minutiae are extracted from the fingerprint using image processing techniques[3]. So the administrative database needs to store only the dummy shjre and the integer seed for permuting the shares. Thus the pl'oblem of falsification and costly maintenance of the large fingerprint database is overcome. One of the main draw backs of visual cryptography implemented in phase 1 is that it would be relatively easy to manipulate the image share and arrive at the original one or hack the information. Hence in the second phase , instead of dividing the biometric template into two shares, the template is divided into n shares using threshold visual cryptographic scheme so that the hacker is not able to construct all the shares and make a biometric database attack.

II.RELATED WORKS

In popular VC schemes[I], the image is divided into two shares such that the image cannot be reconstructed from any one of the shares alone. The Threshold Visual Cryptography provides an alternate method to overcome the deficiencies available in Visual Cryptographic Schemes. The secret is reconstructed by simply superimposing enough share images, and no computation is needed. Unless more than a certain number of share images are obtained, it is impossible to disclose the secret image. This feature enables visual threshold schemes to be used conveniently in highly confidential cases where the secret is shared by several members. Shamir's Secret Sharing[ 1] is an threshold cryptographic algorithm. It is a form of secret sharing, where a secret is divided into parts, giving each participant its own unique part, where some of the parts or all of them are needed in order to reconstruct the secret. Counting on all participants to combine together the secret might be impractical, and therefore we sometimes use the threshold scheme where any k of the parts are sufficient to reconstruct the original secret. Formally, our goal is to divide some data D (e.g., the safe combination) into n pieces Dl,D2 . . . Dn in such a way that:

1. Knowledge of any k or more Di pieces makes D easily computable.

ISBN: 978-81-909042-2-3 ©2012 IEEE

IEEE-International Conference On Advances In Engineering, Science And Management (ICAESM -2012) March 30, 31, 2012 17

2. Knowledge of any k-lor fewer Di pieces leaves D completely undetermined (in the sense that all its possible values are equally likely).

This scheme is called (k,n) threshold scheme. If k=n then all participants are required to reconstruct the secret. If n shares of the image are created, then it would be sometimes impractical to have all the n shares for reconstruction of the image. Therefore, a new technique wherein a subset of n shares of the image (say 't' ) will be sufficient to reconstruct the image. This is called Threshold Visual Cryptography Scheme. The existing system biometric based authentication does not make use of the Threshold Visual Cryptographic techniques of extracting k shares from n shares of the image created. Therefore, in this paper an attempt is made to implement the TVC technique for biometric authentication.

III.OUR CONTRIBUTION

The function of the existing fingerprint authentication using visual cryptography, when one share of the image from ID card is received, it searches the Database in the Data Server and retrieves the other share of the image and reconstructs the image by superimposition of these two shares. From the retrieved image above, minutiae are extracted. During authentication the fingerprint received through online scanner is also processed and minutiae extracted. The output of the above two processes are compared. If found matching, person is authenticated. The disadvantage of the existing method is that since only two shares are available it will be easy for any intruder to reconstruct the image with one share

that is available on the card.

Thumb impression of the person to be authenticated

lD card with One share of image

Application Client

Data Server

�� ��

�� ��

Figure 1 : Fingerprint Based TVC authentication System

To overcome this disadvantage threshold visual cryptographic technique is used to protect the biometric information stored in the server.The level of protection against hacking of information and also the level of decryption of the encrypted image is very high comparing to Visual

Cryptography for the simple reason that n number of secret images or shares of the original image is created and stored. In threshold visual cryptographic technique, during registration the original biometric image is divided into n shares [5][6] where one of the shares known as dummy share is compressed and stored into the users ID card and the remaining n-l shares are stored into the server. The threshold determines the minimum number of shares (say t), out of the n shares created, that are required to reconstruct the image. It would not be possible to extract the original image if the number of shares available are less than the threshold. In the authentication system, it is proposed to have one share of the t shares stored in the ID card of the person. Therefore, it is necessary to identify t-l shares from the n shares and while combining the one share that is available on ID card, will extract the original image. This will be compared with the actual fingerprint that will be obtained from the person to authenticate the identity of the person. The general block diagram for the proposed system is given in the figurel. There are four major processes to be done during authentication . They are Process 1 When one share of the image from ID card is received, it searches the Database in the Server and retrieves t-l shares of the image and reconstructs the image using Threshold Visual Cryptography (TVC) Techniques. Process2 From the retrieved image above, minutiae extracted. Process 3 Thumb impression received through online scanner is processed and minutiae extracted. Process4 Minutiae output of Process 2 and Process 3 are compared. If found matching, person is authenticated.

In the proposed approach the secret image is divided into n- shares, which are printed into transparencies (shares) and can be stored into N back end servers. Only these participants who possess the transparencies can reconstruct the secret image by superimposition of shares.

4.1 Registration phase

4.1.1 Creation of shares

IV RESULTS

In the proposed approach the secret image is divided into n­shares, which are printed into transparencies (shares) and given to the participants (server and user). Only these participants who possess the transparencies can reconstruct the secret image by superimposition of shares. One cannot recover the secret image without the other shares. The fingerprint image is first pre-processed and divided in terms of pixels called shares. The division of the fingerprint into n number of shares is done by using visual cryptographic algorithms. The shares are images represented on transparencies consisting of black and white (transparent, actually) pixels. The algorithm for division of the original image into n shares is given below.

ISBN: 978-81-909042-2-3 ©2012 IEEE

IEEE-International Conference On Advances In Engineering, Science And Management (ICAESM -2012) March 30, 31, 2012 18

Step 1:

Step 2:

Step 3:

Step 4:

Step 5:

Assign the pixel values of Sharel randomly. Assign the pixel value of Share2. Reverse Share2,that is Temp[ x Hy]= Share2[20-x ][y]. Assign the pixel value of Share 1. Assign the pixel value of Share 2.

The result of share creations is given below.

Original image

:

:::::::::::::::::::::::::

::" ..

.......... .

Share2

Share 4

Figure 2 : Image shares

4.1.2 Compression Technique

Share 1

Share3

Share 5

The share of the image to be placed in the ID card is compressed to be space efficient. Also, this compressed image cannot be replicated. In order to achieve this objective, a lossy compression technique DeT is used for compressing the share. Lossy compression is a data encoding method which compresses data by discarding (losing) some unwanted portion of it. The procedure aims to minimise the amount of data that needs to be held, handled, and/or transmitted by a computer. Usage of lossy compression has its own advantages hence it has been implemented for betterment in compression. The compressed share is given below

4.2

4.2.1

Authentication Phase

Extraction of T -Shares from N-Shares

A (k,n)-threshold visual cryptography scheme (yeS) is a method to encode a secret image S1 into n shadow images called shares such that any k or more shares enable the visual recovery of the secret image. However, by inspecting less than k shares one cannot gain any information on the secret image. The visual recovery consists of copying the shares onto transparencies and then stacking them. Any k shares will reveal the secret image without any cryptographic computation.

In this paper we analyze the contrast of the reconstructed image for a (k,n)-threshold yes. We define a canonical form for a (k,n)-threshold yes and provide a characterization of a (k"n)-threshold yes. We completely characterize a contrast optimal (n-l,n)-threshold yeS in canonical form. We first describe a family of (k,n)-threshold yes achieving various values of contrast and pixel expansion. Then we prove an upper bound on the contrast of any (k,n)­threshold yeS and show that a scheme in the described family has optimal contrast.

4.2.2 Superimposing of the T-Shares with ID Card Share

and Detection of Minutiae Points

The t-shares extracted are stored separately in the database. For authentication, user provides one share which is available on the IDcard. The share extracted from this card is superimposed with t- shares that is extracted and stored in the database. This generates the Fingerprint template image. From this fingerprint template image minutiae detection is done and from which minutiae points are obtained.

ALGORITHM: Step 1: Select pixel Pi share si and the corresponding pixel Pj

from share sj.

Step 2: Let P denote the corresponding pixel in the secret image 1.

When superimposing p i and pj, the number of black sub-pixels in the result is given by wI (Pi OR Pj).

Step 3: Recall that Pi and Pj were obtained by applying the same permutation to rows iandj of Mp Hence we have,

wI (Pi OR Pj) =wl (Mp[i] OR MpUD

for all l:Si<j:Sn. hence, if P=O, then

wI (Pi OR Pj) =w,

Whereas if P=I, then

wI (Pi OR Pj) 2:w+ym.

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Step 4: Reconstructed white pixel is wlm black and a reconstructed black pixel is (at least) (w+ym)lm black. V.CONCLUSIONS

Step 5: The difference between white and black reconstructed pixels is (at least) ym of the m sub-pixels. The fraction

y is therefore a measure of the relative contrast.

Figure 4 : Superimposed image

Figure 5: Minutia Detection in filtered superimposed image

Given two sets of minutia, one set taken from the stored data base and the other from the live thumb impression of the person to be authenticated, the minutia match algorithm determines whether the two minutia sets are the same or not. An alignment-based match algorithm [7][8] is used. It includes two consecutive stages: one is alignment stage and the second is match stage. 1. Alignment stage: Given two fingerprint images to be matched, any one minutia from each image is chosen, and the similarity of the two ridges associated with the two referenced minutia points is calculated. If the similarity is larger than a threshold, each set of minutia is transformed to a new coordination system whose origin is at the referenced point and whose x-axis is coincident with the direction of the referenced point. 2. Match stage: After obtaining two sets of transformed minutia points, the elastic match algorithm is used to count the matched minutia pairs by assuming two minutia having nearly the same position and direction are identical. For each fingerprint, all other minutia are translated and rotated with respect to the reference minutia.

The fingerprint based authentication system using threshold visual cryptographic technique has been implemented and tested for its efficiency.!t is also proved that this system has less than 0.2% of False Acceptance Rate and False Rejection Rate and is proved to be efficient than the existing biometric based authentication systems. This system is secure against biometric template attack done at the server side.Because the biometric template is divided into n shares out of which only t shares are taken for authentication where t is a secret.To enhance the security instead of storing the shares into a single server, the shares can also be stored into different servers in the distributed environment.

REFERENCES

[1] Noar M., Shamir A., Visual cryptography. Advances in Cryptography. Eurocrypt' 94, Lecture Notes in Computer Science, 1995,voI.950, Springer-Verlag. ppl - 12.

[2] Y.V. Subba Rao, Ms. Yulia Sukonkina "Fingerprint based authentication application using visual cryptography methods (Improved ID card),' , IEEE TENCON 2008, pp 1-5.

[3] Jain A., Hong L., Pankanti S., Bolle R.,. An Identity Authentication System Using Fingerprints. Department of Computer Science, Michigan State University, USA. 1997,pp 1- 66.

[4] Stinson D.R., Tavares S.,. The Pseudo-Random Number. Selected Areas in Cryptography. 7th Annual International Workshop, Waterloo,Ontario, Canada. 2000,pp 100 - 101.

[5] Tsai e.S., Chang e.e., Chen T.S.,. Sharing multiple secrets in digital images. Department of Computer Science and InformationEngineering, 2001 Taiwan. ppl - 8.

[6] Subba Rao Y.V.,. Presentation on Visual Cryptography and Its Applications. Department of Computer and Information Sciences, University of Hyderabad, India. 2007,ppl- 42.

[7] Bistarelli S., Boffi G., Rossi F., Computer Algebra for Fingerprint Matching. Universita"G. d'Annunzio", Dipartimento di Scienze, Pescara, Italy. 2003.,ppl- 10.

[8] Davide Maltoni . Handbook of Fingerprint Recognition. 2003,ppl- 366.

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