The Design of Fingerprint Biometric Authentication on Smart Card for PULAPOT Main Entrance System Computer Science Department, Faculty of Technology Science and Defence Universiti Pertahanan Nasional Malaysia (UPNM), Kuala Lumpur, Malaysia. rizal@upnm.edu.my, afizi@upnm.edu.my, adib@upnm.edu.my, yuhanim@upnm.edu.my, hazali@upnm.edu.my, kamaruzaman@upnm.edu.my Abstract Reliable personal authentication and identification is necessary due to the necessity of security and access restriction. The main task is to verify the person is who they claim to be. Biometrics personal authentication utilizing fingerprints have been studied and applied in numerous applications. Everyone is known to possess a unique fingerprint and it does not change throughout his lifetime. Therefore fingerprint matching is considered one of the most reliable techniques of people identification. Smart card is also being widely adopted in many applications and refers as an essential platform to hold biometrics information. This paper presents a fingerprint verification that can be embedded in a smart card. The smart card plays a data storage for storing the cardholder s fingerprint data. The card holder is required to scan his/her fingerprint on a sensor. The scanned fingerprint image is then sent to the card for matching. KeyWords Fingerprint, Biometrics, Smart Card, Personal Authentication. 1. Introduction A smart card is a credit card sized plastic card with an embedded chip that equipped with memory and microprocessor. The microprocessor chip inside the smart card can manipulate the data and consequently offer data security functionalities. They are consequently being used to carry keys and password and store personal information in secure applications such as electronic payment systems, transportation ticket systems, and identification card systems [1]. However, the user validation could still be a setback because only a valid user has the private key and knows the password to use it. Therefore, the degree of the security would depend on user s senses of security and it is not technically controlled. For example, a password that is associated with a user s private information, such as a name or birth date, would be easily remembered. There is an increasing trend using biometrics, which refers to the personal biological or behavioural characteristics used for verification or identification [2, 3]. Biometric authentication uses data taken from measurements of a person s body, such as fingerprints, faces, irises, retinal patterns, palm prints, voice prints, hand-written signatures and so on, to identify individuals by means of image processing [4]. Of all the biometric techniques being used today, fingerprint-based identification is the oldest method, which has been successfully used in numerous applications [4]. Everyone is known to possess a unique fingerprint and it does not change throughout his lifetime. Since fingerprints cannot be lost or forgotten like passwords, fingerprints have the potential to offer higher security and more convenience for user authentication. International Journal of Advancements in Computing Technology(IJACT) Volume4, Number16,September 2012 doi:10.4156/ijact.vol4.issue16.57 487
This paper presents the integration design of fingerprint biometrics into a smart card. The design has been implemented to PULAPOT Main Entrance System (PMES) application. The following parts of this paper are organized as follows. The fingerprint biometrics is explained in Section II. Section III describes the integration of fingerprint into the smart card. The implementation of the integration is presented in Section IV and the conclusion is given in Section V. 2. Fingerprint Biometrics Among all the biometrics, fingerprints have one of the highest levels of reliability [4]. It has been used as a mean of identifying individuals for a very long time. Today, the use of computers for fingerprint matching and identification is highly desirable in many applications such as building security system. A fingerprint matching looks at the pattern found on fingertip. The lines of fingertip have three characteristics [5]: There are no similar fingertip in the world Fingerprints are unchangeable Fingerprints are one of the unique features for identification systems. A fingerprint consists of ridge lines on a finger. A ridge is defined as a single curved segment, and a valley is the region between two adjacent ridges. Fingerprints are distinguished by minutiae which are the abnormal points of ridges. There are three main methods to capture fingerprint images, which are optical, applicative and thermo conductive [6]. The optical method is implemented with a small camera and light source to capture an image of a fingerprint. The capacitive method makes full use of the human body s natural electrical charge to measure the differences in capacitance value between ridges and valley in a fingerprint and certain algorithms are used to construct an image from the capacitance values. The last method, which is the thermo conductive method, is done by measuring the human tissue s then a conductivity characteristic difference between the ridges and valleys of a fingerprint. In other words, the ridges and valleys conduct heat at different rates and these minute differences can be registered. This research will use the capacitive method provided by AET63 USB Biotrustkey as shown in figure 1. Figure 1. AET63 Bio TrustKey 488
3. Integrating Fingerprint Into The Smart Card Fingerprint identification is suitable as a method to authenticate users to use a smart card [7]. This can elaborate by using two factors [7]: space complexity and time complexity. A common available smart card has approximately 8K to 16K of non-volatile memory. The current state-of-art fingerprint technology [8] shows that the minimum size of a fingerprint template adequate for comparison can be as small as several hundreds of bytes. So space complexity is not a major problem as the smart card can store the entire fingerprint template. For time complexity, it refers to whether the in-card processor is capable to accomplish the entire fingerprint matching calculation in real time [7]. There are three approaches in integrating fingerprint biometric information to smart card [9, 10, 11]: Template-On-Card (TOC) In this template the original identifying fingerprint biometric template is stored on a smart card. Data acquisition, feature extraction and matching are done on the reader side. During the authentication process, the reading device requests the identifying template from the smart card and matches it on the reader side with newly scanned template. In Match-On-Card (MOC) - The original template is stored on a smart card. During the authentication process, data acquisition and feature extraction are done at the reader side and the matching is done inside the smart card. The final matching result is computed inside the smart card itself. In System-On-Card (SOC) - The smart card incorporates original template, the entire biometric sensor, processor and algorithm. All authentication procedures are done inside the smart card itself. For this research, the most appropriate integration is the Match-On-Card (MOC) approach. Figure 2 shows the fingerprint matching process using MOC approach for this research [12]. The fingerprint sensor is used to capture fingerprints. The fingerprint is processed by comparing the captured image and the present image provided by the user [13]. Before comparing process can occur, the images need to be reduced to their key features called minutiae points. The fingerprint template having the minutiae information is transferred to the smart card through the smart card reader. Figure 2. Fingerprint Matching Process The following are the general steps in this fingerprint matching technique [12]: 1. Image Pre-Processing This refers to the refinement of the original fingerprint image against image distortion produced from the fingerprint scanner. 2. Minutiae Extraction 489
Minutiae extraction extracts features of the fingerprint image called minutiae. Minutiae generally refer to the ridge ends and branches that constitute a fingerprint pattern. 3. Minutiae Matching Minutiae matching conducted on the smart card compares the minutiae in the master fingerprint template saved in the smart card and those scanned fingerprint (live scanned). If the fingerprint matches then a user will be recognized as the valid cardholder. 4. Implementation The PMES has been developed using the Microsoft Visual Basic 6.0 for its interface design and programming. As for the database, Microsoft SQL Server 2003 has been chosen as it is easier to maintain and flexible configuration. Basically PMES consist of three modules which are administrator module, user module and tracking module. The administrator module is used to store user s information such as name, identity card number, rank, address and the fingerprint template. In the process of enrolling the user, the administrator will key in user s particulars, captures the fingerprint image and identify the key features, verify the fingerprint and stores it onto the smart card [14]. The user module works like an automatic teller machine (ATM) card except that it asks for the user s finger to be scanned and authenticated. When the user inserts a smart card into the AET63 BioTrustKey device, the user would be asked to momentarily put his/her fingerprint on the scanner. Then, the image captured is reduced to the key feature and compared to the stored template on the smart card. If the user identity is match, then the user will be recognized as the valid cardholder and allowed to enter the PULAPOT camp. For the military officers, they will be given a smart card containing their own fingerprint template and personal data. As for the civilian s visitors, all the information will be transfer from mykad to the system. Figure 3. Fingerprint Authentication Interface Another additional module implemented in PMES is the tracking module. Once the user have successfully authenticate, the system will capture the time and date of log in and log out in the database. 490
This module is important in monitoring the movement of log in and log out from the camp. A sample of tracking report is shown in figure 4. 5.Conclusion Figure 4: Tracking Report Biometric identification are becoming widely accepted and are slowly replacing traditional identification the methods of which identification using password is still most widely spread. The aim of this research is to point out the basic characteristics and possibilities of combining smart card and fingerprint biometrics in authentication and identification processes. This paper presents a fingerprint verification that can be embedded in a smart card. The fingerprint matching process has been implemented in PMES. As a challenge for future research work, we will examine the other types of fingerprint matching algorithm and evaluate the accuracy of the matching algorithm. References [1] H. Dreifus and T. Monk, Smart Cards, John Wiley & Sons, New York, NY, USA, 1997. [2] S.Nanavati, M. Thieme amd R. Nanavati, Biometrics: Identity Verification in a Networked World, John Wiley & Sons, New York, NY, USA, 2002. [3] D. Maltoni, D. Maio, A. Jain and S. Prabhakar, Handbook of Fingerprint Recognition, Springer, New York, NY, USA, 2003. [4] Jain A.K. et al.: BIOMETRICS: Personal Identification in Networked Society, Kluwer Academic Publishers.(1999) [5] Hassan Ghassemian, A Robust On Line Restoration Algorithm for Fingerprint Segmentation, IEEE Int. Conf. On Image Processing, vol2, pp.181-184, September 1996. [6] Jain, A.K., et al.: Matching and Classification: A Case Study in Fingerprint Domain. Proceeding of Indian National Science Academy (INSA-A). vol.67, no.2, pp.67-85. (2001) [7] Moon, Y.S. et al.: A Secure Card System with Biometrics Capability. Proceeding of IEEE Canadian Conference on Electrical and Engineering, May 9-12, Alberta, Canada. 261-266. (1999) [8] Maio, D., Maltoni, D.:Direct Gray-Scale Minutiae Detection in Fingerprints. IEEE Transactions on Pattern Analysis Machine Intelligence, vol. 19, no. 1, pp.25-29.(1997) [9] Y. S. Moon, H. C. Ho, K. L. Ng, S. F. Wan, and S. T. Wong, Collaborative fingerprint authentication by smart card and trusted host, in Proceedings of the Canadian Conference on Electrical and Computer Engineering, vol. I, pp. 108-112, 2000. 491
[10] L. Rila and C. Mitchell, Security analysis of smartcard to card reader communications for biometric cardholder authentication, in Proceedings of the 5 th Smart Card Research and Advanced Application Conference (CARDIS 02), pp. 19-28, 2002. [11] D. Moon, et al., Performance analysis of the Match-on-Card system for the fingerprint verification, in Proceedings of the International Workshop on Information Security Applications, pp. 449-459, 2001. [12] Y.H. Yahaya, M.R.M. Isa, and M.I Aziz, Fingerprint Biometrics Authentication on Smart Card, in Proceedings of the Second International Conference on Computer and Electrical Engineering, vol.2, pp.671-673, 2009. [13] Shuai Ren, Tao Zhang, "A High-performance Information Hiding Algorithm Based on CL Multi- Wavelet Transform and DCT", IJACT, Vol. 4, No. 8, pp. 137-144, 2012. [14] Hyung-Kyu Yang, Young-Hwa An, "Security Weaknesses and Improvements of a Fingerprintbased Remote User Authentication Scheme Using Smart Cards", IJACT, Vol. 4, No. 1, pp. 15-23, 2012. 492