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Encryption of Biometric Templates using One Time Biometric Transform

Dr. Aditya, Amit Vijayat, Dr. Sunil Kumar, Dr. Stephanie Schuckers

Abstract


Securing biometric information has become essential with growing biometric applications in different sectors of society. Vulnerability assessment plays a key role in improving the security of any security system by identifying the potential vulnerabilities and proposing countermeasures to mitigate the threats posed by them. In this work self-generated and dynamic helper data based system is proposed to encrypt the biometric templates. Biometric information is statistically learned and probabilistic matching is performed to discriminate genuine from imposters. We call this system as One Time Biometric Transformation (OTBT) system. The system was tested using CASIA iris database and by probabilistic matching an EER of 1.96% is achieved. Strength analysis of the system for three different challenging databases is also presented.


Keywords


technology and services,Securing biometric information

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References


N. Ratha, “Enhancing security and privacy in biometrics-based authentication systems,” IBM systems journal, vol. 40, pp. 614–6134, 2001.

D. Osten, H. Carim, M. Arneson, and B. Blan, “Biometrics, personal authentication system,” US Patent #5,719,950, Feb 1998.

U. Uludag, S. Pankanti, S. Prabhakar, and A. K. Jain, “Biometric cryptosystems: Issues and challenges,” Proceedings of the IEEE, vol. 92,no. 6, 2004.

J. Daugman, “High confidence visual recognition of persons by a test of statistical independence.” IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 15, no. 11, 1993.

C. Scott and R. Nowak, “Templar: A wavelet-based framework for pattern learning and analysis,” IEEE Transactions on Signal Processing, vol. 52,no. 8, pp. 2264–2274, 2004.

A. Abhyankar, L. Hornak, and S. Schuckers, “Bi-orthogonal wavelet based iris recognition,” SPIE, Defence and Security Symposium, p. 5406,2005.

S. Furui, “Speaker independent isolated word recognition using dynamic features of speech spectrum,” IEEE Transactions on Acoust.,Speech and Signal Process, vol. 34, no. 1, pp. 52–59, 1986.

C. A. of Sciences Institute of Automation, “Database of 756 greyscale eye images,” http://www.sinobiometrics.com, 2003.


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