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An Efficient Biometric Cryptosystem using Autocorrelators

Authors: R. Bremananth, A. Chitra


Cryptography provides the secure manner of information transmission over the insecure channel. It authenticates messages based on the key but not on the user. It requires a lengthy key to encrypt and decrypt the sending and receiving the messages, respectively. But these keys can be guessed or cracked. Moreover, Maintaining and sharing lengthy, random keys in enciphering and deciphering process is the critical problem in the cryptography system. A new approach is described for generating a crypto key, which is acquired from a person-s iris pattern. In the biometric field, template created by the biometric algorithm can only be authenticated with the same person. Among the biometric templates, iris features can efficiently be distinguished with individuals and produces less false positives in the larger population. This type of iris code distribution provides merely less intra-class variability that aids the cryptosystem to confidently decrypt messages with an exact matching of iris pattern. In this proposed approach, the iris features are extracted using multi resolution wavelets. It produces 135-bit iris codes from each subject and is used for encrypting/decrypting the messages. The autocorrelators are used to recall original messages from the partially corrupted data produced by the decryption process. It intends to resolve the repudiation and key management problems. Results were analyzed in both conventional iris cryptography system (CIC) and non-repudiation iris cryptography system (NRIC). It shows that this new approach provides considerably high authentication in enciphering and deciphering processes.

Keywords: Wavelets, Autocorrelators, biometrics cryptography, irispatterns

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[1] G. I. Davida, Y. Frankel, and B. J. Matt, "On enabling secure applications through off-line biometric identification," in Proc. IEEE Symp. Privacy and Security, pp. 148-157, May 1998.
[2] G. I. Davida, Y. Frankel, B. J. Matt, and R. Peralta, "On the relation of error correction and cryptography to an offline biometric based identification scheme," in Proc. Workshop Coding and Cryptography (WCC-99), pp. 129-138, 1999.
[3] M. G. Linnartz, P. Tuyls. New Shielding Functions to Enhance Privacy and Prevent Misuse of Biometric Templates, AVBPA 2003, pp. 393- 402, 2003.
[4] T. Clancy, N. Kiyavash, D.J.Lin. "Secure Smartcard-Based Fingerprint Authentication", Proc. of the 2003 ACM SIGMM workshop on Multimedia, Biometric Methods and Applications, pp 45-52, 2003.
[5] F. Monrose, M. Reiter, Q. Li, S. Wetzel. Cryptographic key generation from voice, Proc. IEEE Symp. on Security and Privacy, pp. 201-213, 2001.
[6] Uludag, U., Sharath Pankanti, Salil Prabhakar, Anil Jain, Biometric Cryptosystems: Issues and Challenges, Proc. of the IEEE, VOL.92, No.6, pp.948-960, June 2004.
[7] John Daugman, How Iris Recognition Works, IEEE Transactions On Circuits and Systems For Video Technology, Vol. 14, No. 1, pp.21-30, January 2004.
[8] Li Ma, Tieniu Tan, Yunhong Wang, and Dexin Zhang, Efficient Iris Recognition by Characterizing key Local variations, IEEE Transaction on Image processing, Vol.13, No.6, June 2004.
[9] Shinyoung Lim , Kwanyong Lee, Okhwan Byeon, and Taiyun Kim, Efficient Iris Recognition through Improvement of Feature Vector and Classifier, ETRI J., Vol. 23, No. 2, PP. 61-70, June 2001.
[10] A.Chitra and R.Bremananth, Efficient Identification Based on Human Iris Patterns, Proceedings of Fourth Indian Conf. on Computer Vision, Graphics and Image processing (ICVGIP), PP. 177-183, December 2004.
[11] A. Chitra and R.Bremananth, Secure PID using iris pattern based on circular symmetric and Gabor filters, Proceedings of Inter. Conf. Advanced Computing and Communication (ADCOM), PP. 36, December 2003.
[12] Canny, John. "A Computational Approach to Edge Detection", IEEE Transactions on Pattern Analysis and Machine Intelligence, Vol. 8, No. 6, pp. 679-698, 1986.
[13] Rafael C. Gonzalez, Richard E. Woods, Steven L.Eddins, "Digital Images processing using MATLAB", Pearson Education, 2004.
[14] Jane Miller, "Statistics for Advanced level", Second edition, Cambridge University press, 1996.
[15] Michael Negin Thomas A. Chmielewski,et al., "An iris biometric system for public and personal use", IEEE catalog No. 0018-9162, 2000.