An Efficient Biometric Cryptosystem using Autocorrelators
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.
[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.
[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.
@article{"International Journal of Information, Control and Computer Sciences:60675", author = "R. Bremananth and A. Chitra", title = "An Efficient Biometric Cryptosystem using Autocorrelators", abstract = "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 = "Autocorrelators, biometrics cryptography, irispatterns, wavelets.", volume = "2", number = "8", pages = "2808-7", }