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5 - Biometric-based security systems

from II - E-system and network security tools

Published online by Cambridge University Press:  11 September 2009

Mohammad Obaidat
Affiliation:
Monmouth University, New Jersey
Noureddine Boudriga
Affiliation:
Université du 7 Novembre à Carthage, Tunis
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Summary

Biological features have been investigated extensively by many researchers and practitioners in order to identify the users of information, computer, and communications systems. There are an increasing number of biometric-based identification systems that are being developed and deployed for both civilian and forensic applications. Biometric technology is now a multi-billion dollar industry and there is extensive Federal, industrial, business and academic research funding for this vital technology especially after September 2001.

An automated biometric system uses biological, physiological or behavioral characteristics to automatically authenticate the identity of an individual based on a previous enrollment event. In this context, human identity authentication is the focus. However, generally this should not necessarily be the case.

This chapter aims at reviewing state-of-the-art techniques, methodologies, and applications of biometrics to secure access to e-based systems and computer networks. It will also shed some light on its effectiveness and accuracy of identification as well as trends, concerns, and challenges.

Introduction

Biometrics deals with the process of identifying persons based on their biological or behavioral characteristics. This area has received recently a great deal of attention due to its ability to give each person unique and accurate characteristics. Moreover, the cost of implementing such technology to identify people has decreased tremendously. Biometrics techniques have been widely accepted by the public due to their strengths and robustness (Obaidat, 1997; Obaidat, 1999).

Identifying the identity of an individual involves solving two major issues: (a) verification, and (b) recognition.

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Chapter
Information
Publisher: Cambridge University Press
Print publication year: 2007

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References

Adler, F. H. (1965). Physiology of the Eye: Clinical Application, 4th edn, C. V. Mosby.Google Scholar
Bencheikh, R. and Vasiu, L. (2005). Hybrid authentication systems. Proc. of the 2005 International Workshop in Wireless Security Technologies, pp. 130–7.Google Scholar
Bleha, S. and Obaidat, M. S. (1991). Dimensionality reduction and feature extraction applications in identifying computer users. IEEE Transactions Systems, Man, and Cybernetics, Vol. 21, No. 2.CrossRefGoogle Scholar
Bleha, S. and Obaidat, M. S. (1993). Computer user verification using the perceptron. IEEE Transactions Systems, Man, and Cybernetics, Vol. 23, No. 3, 900–2.CrossRefGoogle Scholar
Bryan, W. L. and N. Harter (1973). Studies in the physiology and psychology of the telegraphic language. In The Psychology of Skill: Three Studies. Gardener, E. H. and Gardner, J. K. (eds.), NY Time Co., pp. 35–44.Google Scholar
Card, S., Moran, T., and Newell, A. (1980). The keystroke level model for user performance time with interactive systems. Communications of ACM, Vol. 23, 396–410.CrossRefGoogle Scholar
CavoukianA., (2005). Consumer Biometric Applications. Information and Privacy Commissioner of Ontario, Canada. http://www.ipc.on.ca/docs/cons-bio.pdf
Clarke, R. (2001). Biometrics and privacy. Notes available at: http://www.anu.edu.au/people/Roger.Clarke/DV/Biometrics.html
Cooper, W. E. (1983). Cognitive Aspects of Skilled Typewriting. Springer-Verlag.CrossRefGoogle Scholar
Daugman, J. G. (1993). High confidence visual recognition of persons by a test of statistical independence. IEEE Trans. Pattern Recognition Machine Intelligence, Vol. 15, No. 11, 1148–61.CrossRefGoogle Scholar
Daugman, J. G. (1999). Recognizing persons by their iris patterns. In Biometrics: Personal Identification in Networked Society, Jain, A., Bolle, R., and Pankanti, S. (eds.), Kluwer, pp. 103–21.CrossRefGoogle Scholar
Hill, R. (1999). Retina identification. In Biometrics: Personal Identification in Networked Society, Jain, A., Bolle, R., and Pankanti, S. (eds.), Kluwer, pp. 123–41.CrossRefGoogle Scholar
Jain, A., Hong, L., Pankanti, S., and Bolle, R. (1997). An identity-authentication system using fingerprints, Proc. of IEEE, Vol. 85, No. 9, 1366.CrossRefGoogle Scholar
Jain, A., R. Bolle, and S. Pankanti (1999). Introduction to biometrics. In Biometrics: Personal Identification in Networked Society, Jain, A., Bolle, R., and Pankanti, S. (eds.), Kluwer, pp. 1–43.CrossRefGoogle Scholar
Joyce, R. and Gupta, G. (1990). Identity authentication based on keystroke latencies. Communications of ACM, Vol. 33, No. 2, 168–76.CrossRef
Langeand, L. and Leopold, G. (1997). Digital identification: it is now at our fingertips, EEtimes, March 24, Vol. 946 (http://techweb.cmp.com/eet/823/).Google Scholar
LiuS., and Silverman, M. (2001). A practical guide to biometric security technology. IEEE Computer Magazine, January/February 2001, 27–32.Google Scholar
NIST (2000). Report to the United States Congress, Summary of NIST Standards for Biometric Accuracy, Tamper Resistance and Interoperability.
Obaidat, M. S. (1993a). A methodology for improving computer access security. Computers & Security, Vol. 12, 657–62.CrossRefGoogle Scholar
Obaidat, M. S. and Macchairolo, D. T. (1993b). An on-line neural network system for computer access security. IEEE Transactions Industrial Electronics, Vol. 40, No. 2, 235–41.CrossRefGoogle Scholar
Obaidat, M. S. and Macchairolo, D. T. (1994). A multilayer neural network system for computer access security. IEEE Transactions Systems, Man and Cybernetics, Vol. 24, No. 5, 806–13.CrossRefGoogle Scholar
Obaidat, M. S. and Sadoun, B. (1997). Verification of computer users using keystroke dynamics. IEEE Transactions on Systems, Man and Cybernetics, Vol. 27, No. 2, 261–9.CrossRefGoogle ScholarPubMed
Obaidat, M. S. and Sadoun, B. (1999). Keystroke dynamics based authentication. In Biometrics: Personal Identification in Networked Society, Jain, A., Bolle, R., and Pankanti, S. (eds.), Kluwer, pp. 213–30.Google Scholar
Obaidat, M. S., Brodzik, A. and Sadoun, B. (1998). A performance evaluation study of four Wavelet algorithms for pitch period estimation of speech signals. Information Sciences Journal, Vol. 112, No. (1–4), 213–21.CrossRefGoogle Scholar
Obaidat, M. S., Lee, C., Sadoun, B. and Nelson, D. (1999). Estimation of pitch period of speech signals using a new dyadic Wavelet algorithm. Information Sciences Journal, Vol. 119, No. 1, 21–39.CrossRefGoogle Scholar
Rhodes, K. A. (2003). Information Security: Challenges in Using Biometrics. United States General Accounting Office. http://www.gao.gov/new.items/d031137t.pdfGoogle Scholar
Ross, A. and Jain, A. (2001). Information Fusion in Biometrics. In Proceedings of AVBPA, Halmstad, Sweden, June 2001, Springer, pp. 354–9.Google Scholar
Shaffer, L. H. (1973). Latency mechanisms in transcription. In Attention and Performance, Vol. IV, Kornblum, S. (ed.), Academic Press.Google Scholar
Snelik, R., Indovina, M., Yen, J., and Mink, A. (2003). Multimodal biometrics: issues in design and testing. In Proc. of the 2003 International Conference on Multimodal Interfaces (IMCI 2003), Vancouver, Canada, ACM.Google Scholar
Umphress, D. and Williams, G. (1985). Identity verification through keyboard characteristics. International Journal Man-Machine Studies, Vol. 23, 263–73.CrossRefGoogle Scholar
Woodward, J. D. (1997). Biometrics: privacy' foe or privacy's friend?Proceedings of the IEEE-Special Issue on Automated Biometrics, Vol. 85, 1480–92.Google Scholar
Weng, J. and D. Swets (1999). Face recognition. In Biometrics: Personal Identification in Networked Society, Jain, A., Bolle, R., and Pankanti, S. (eds.), Kluwer, pp. 65–86.CrossRefGoogle Scholar
Young, J. R. and Hammon, R. W. (1981). Automatic Palmprint Verification Study. Rome Air Development Center, Report No. RAD-TR-81-161, Griffith AF Base, New York.Google Scholar
Zunkel, R. L. (1999). Hand geometry based verification. In Biometrics: Personal Identification in Networked Society, Jain, A., Bolle, R., and Pankanti, S. (eds.), Kluwer, pp. 1–43.CrossRefGoogle Scholar

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