Abstract

It is important to ensure the security of biometric authentication information, because its leakage causes serious risks, such as replay attacks using the stolen biometric data, and also because it is almost impossible to replace raw biometric information. In this paper, we propose a secure biometric authentication scheme that protects such information by employing an optical data ciphering technique based on compressed sensing. The proposed scheme is based on two-factor authentication, the biometric information being supplemented by secret information that is used as a random seed for a cipher key. In this scheme, a biometric image is optically encrypted at the time of image capture, and a pair of restored biometric images for enrollment and verification are verified in the authentication server. If any of the biometric information is exposed to risk, it can be reenrolled by changing the secret information. Through numerical experiments, we confirm that finger vein images can be restored from the compressed sensing measurement data. We also present results that verify the accuracy of the scheme.

© 2013 Optical Society of America

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References

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2011 (1)

J. K. Pillai, V. Patel, R. Chellappa, and N. Ratha, “Secure and robust iris recognition using random projections and sparse representations,” IEEE Trans. Pattern Anal. Mach. Intell. 33, 1877–1893 (2011).
[CrossRef]

2010 (1)

2009 (1)

J. Breebaart, B. Yang, I. Buhan-Dulman, and C. Busch, “Biometric template protection: the need for open standards,” Datenschutz Datensicherheit 33, 299–304 (2009).
[CrossRef]

2008 (1)

E. J. Candès and M. B. Wakin, “Introduction to compressive sampling,” IEEE Signal Process. Mag. 25(2), 21–30 (2008).
[CrossRef]

2006 (1)

2001 (1)

N. K. Ratha, J. H. Connell, and R. M. Bolle, “Enhancing security and privacy in biometrics-based authentication systems,” IBM Syst. J. 40, 614–634 (2001).
[CrossRef]

1995 (1)

1987 (1)

Baraniuk, R. G.

M. B. Wakin, J. N. Laska, M. F. Duarte, D. Baron, S. Sarvotham, D. Takhar, K. F. Kelly, and R. G. Baraniuk, “An architecture for compressive imaging,” Proceedings of the International Conference on Image Processing (ICIP) (2006).

Baron, D.

Y. Rachlin and D. Baron, “The secrecy of compressed sensing measurements,” in IEEE 46th Annual Allerton Conference on Communication, Control, and Computing (2008), pp. 813–817.

M. B. Wakin, J. N. Laska, M. F. Duarte, D. Baron, S. Sarvotham, D. Takhar, K. F. Kelly, and R. G. Baraniuk, “An architecture for compressive imaging,” Proceedings of the International Conference on Image Processing (ICIP) (2006).

Bolle, R. M.

N. K. Ratha, J. H. Connell, and R. M. Bolle, “Enhancing security and privacy in biometrics-based authentication systems,” IBM Syst. J. 40, 614–634 (2001).
[CrossRef]

Breebaart, J.

J. Breebaart, B. Yang, I. Buhan-Dulman, and C. Busch, “Biometric template protection: the need for open standards,” Datenschutz Datensicherheit 33, 299–304 (2009).
[CrossRef]

Buhan-Dulman, I.

J. Breebaart, B. Yang, I. Buhan-Dulman, and C. Busch, “Biometric template protection: the need for open standards,” Datenschutz Datensicherheit 33, 299–304 (2009).
[CrossRef]

Busch, C.

J. Breebaart, B. Yang, I. Buhan-Dulman, and C. Busch, “Biometric template protection: the need for open standards,” Datenschutz Datensicherheit 33, 299–304 (2009).
[CrossRef]

Candès, E. J.

E. J. Candès and M. B. Wakin, “Introduction to compressive sampling,” IEEE Signal Process. Mag. 25(2), 21–30 (2008).
[CrossRef]

Chellappa, R.

J. K. Pillai, V. Patel, R. Chellappa, and N. Ratha, “Secure and robust iris recognition using random projections and sparse representations,” IEEE Trans. Pattern Anal. Mach. Intell. 33, 1877–1893 (2011).
[CrossRef]

Clemente, P.

Connell, J. H.

N. K. Ratha, J. H. Connell, and R. M. Bolle, “Enhancing security and privacy in biometrics-based authentication systems,” IBM Syst. J. 40, 614–634 (2001).
[CrossRef]

Duarte, M. F.

M. B. Wakin, J. N. Laska, M. F. Duarte, D. Baron, S. Sarvotham, D. Takhar, K. F. Kelly, and R. G. Baraniuk, “An architecture for compressive imaging,” Proceedings of the International Conference on Image Processing (ICIP) (2006).

Durán, V.

Gonzalez, R. C.

R. C. Gonzalez and R. E. Woods, Digital Image Processing, 3rd ed. (Addison-Wesley, 1992).

Hirata, S.

S. Hirata and K. Takahashi, “Cancelable biometrics with perfect secrecy for correlation-based matching,” ICB ’09 Proceedings of the Third International Conference on Advances in Biometrics, LNCS 5558 (2009), pp. 868–878.

Javidi, B.

Juels, A.

A. Juels and M. Sudan, “A fuzzy vault scheme,” in IEEE International Symposium on Information Theory (2002).

A. Juels and M. Wattenberg, “A fuzzy commitment scheme,” in Proceedings of the ACM Conference on Computer and Communications Security (1999), pp. 28–36.

Kelly, K. F.

M. B. Wakin, J. N. Laska, M. F. Duarte, D. Baron, S. Sarvotham, D. Takhar, K. F. Kelly, and R. G. Baraniuk, “An architecture for compressive imaging,” Proceedings of the International Conference on Image Processing (ICIP) (2006).

Kirby, M.

Lancis, J.

Laska, J. N.

M. B. Wakin, J. N. Laska, M. F. Duarte, D. Baron, S. Sarvotham, D. Takhar, K. F. Kelly, and R. G. Baraniuk, “An architecture for compressive imaging,” Proceedings of the International Conference on Image Processing (ICIP) (2006).

Obi, T.

Ohyama, N.

Patel, V.

J. K. Pillai, V. Patel, R. Chellappa, and N. Ratha, “Secure and robust iris recognition using random projections and sparse representations,” IEEE Trans. Pattern Anal. Mach. Intell. 33, 1877–1893 (2011).
[CrossRef]

Pillai, J. K.

J. K. Pillai, V. Patel, R. Chellappa, and N. Ratha, “Secure and robust iris recognition using random projections and sparse representations,” IEEE Trans. Pattern Anal. Mach. Intell. 33, 1877–1893 (2011).
[CrossRef]

Rachlin, Y.

Y. Rachlin and D. Baron, “The secrecy of compressed sensing measurements,” in IEEE 46th Annual Allerton Conference on Communication, Control, and Computing (2008), pp. 813–817.

Ratha, N.

J. K. Pillai, V. Patel, R. Chellappa, and N. Ratha, “Secure and robust iris recognition using random projections and sparse representations,” IEEE Trans. Pattern Anal. Mach. Intell. 33, 1877–1893 (2011).
[CrossRef]

Ratha, N. K.

N. K. Ratha, J. H. Connell, and R. M. Bolle, “Enhancing security and privacy in biometrics-based authentication systems,” IBM Syst. J. 40, 614–634 (2001).
[CrossRef]

Refregier, P.

Sarvotham, S.

M. B. Wakin, J. N. Laska, M. F. Duarte, D. Baron, S. Sarvotham, D. Takhar, K. F. Kelly, and R. G. Baraniuk, “An architecture for compressive imaging,” Proceedings of the International Conference on Image Processing (ICIP) (2006).

Sirovich, L.

Sudan, M.

A. Juels and M. Sudan, “A fuzzy vault scheme,” in IEEE International Symposium on Information Theory (2002).

Suzuki, H.

Tajahuerce, E.

Takahashi, K.

S. Hirata and K. Takahashi, “Cancelable biometrics with perfect secrecy for correlation-based matching,” ICB ’09 Proceedings of the Third International Conference on Advances in Biometrics, LNCS 5558 (2009), pp. 868–878.

Takhar, D.

M. B. Wakin, J. N. Laska, M. F. Duarte, D. Baron, S. Sarvotham, D. Takhar, K. F. Kelly, and R. G. Baraniuk, “An architecture for compressive imaging,” Proceedings of the International Conference on Image Processing (ICIP) (2006).

Tashima, H.

Torres-Company, V.

Wakin, M. B.

E. J. Candès and M. B. Wakin, “Introduction to compressive sampling,” IEEE Signal Process. Mag. 25(2), 21–30 (2008).
[CrossRef]

M. B. Wakin, J. N. Laska, M. F. Duarte, D. Baron, S. Sarvotham, D. Takhar, K. F. Kelly, and R. G. Baraniuk, “An architecture for compressive imaging,” Proceedings of the International Conference on Image Processing (ICIP) (2006).

Wattenberg, M.

A. Juels and M. Wattenberg, “A fuzzy commitment scheme,” in Proceedings of the ACM Conference on Computer and Communications Security (1999), pp. 28–36.

Woods, R. E.

R. C. Gonzalez and R. E. Woods, Digital Image Processing, 3rd ed. (Addison-Wesley, 1992).

Yachida, M.

Yamaguchi, M.

Yang, B.

J. Breebaart, B. Yang, I. Buhan-Dulman, and C. Busch, “Biometric template protection: the need for open standards,” Datenschutz Datensicherheit 33, 299–304 (2009).
[CrossRef]

Datenschutz Datensicherheit (1)

J. Breebaart, B. Yang, I. Buhan-Dulman, and C. Busch, “Biometric template protection: the need for open standards,” Datenschutz Datensicherheit 33, 299–304 (2009).
[CrossRef]

IBM Syst. J. (1)

N. K. Ratha, J. H. Connell, and R. M. Bolle, “Enhancing security and privacy in biometrics-based authentication systems,” IBM Syst. J. 40, 614–634 (2001).
[CrossRef]

IEEE Signal Process. Mag. (1)

E. J. Candès and M. B. Wakin, “Introduction to compressive sampling,” IEEE Signal Process. Mag. 25(2), 21–30 (2008).
[CrossRef]

IEEE Trans. Pattern Anal. Mach. Intell. (1)

J. K. Pillai, V. Patel, R. Chellappa, and N. Ratha, “Secure and robust iris recognition using random projections and sparse representations,” IEEE Trans. Pattern Anal. Mach. Intell. 33, 1877–1893 (2011).
[CrossRef]

J. Opt. Soc. Am. A (1)

Opt. Express (1)

Opt. Lett. (2)

Other (6)

R. C. Gonzalez and R. E. Woods, Digital Image Processing, 3rd ed. (Addison-Wesley, 1992).

M. B. Wakin, J. N. Laska, M. F. Duarte, D. Baron, S. Sarvotham, D. Takhar, K. F. Kelly, and R. G. Baraniuk, “An architecture for compressive imaging,” Proceedings of the International Conference on Image Processing (ICIP) (2006).

Y. Rachlin and D. Baron, “The secrecy of compressed sensing measurements,” in IEEE 46th Annual Allerton Conference on Communication, Control, and Computing (2008), pp. 813–817.

S. Hirata and K. Takahashi, “Cancelable biometrics with perfect secrecy for correlation-based matching,” ICB ’09 Proceedings of the Third International Conference on Advances in Biometrics, LNCS 5558 (2009), pp. 868–878.

A. Juels and M. Wattenberg, “A fuzzy commitment scheme,” in Proceedings of the ACM Conference on Computer and Communications Security (1999), pp. 28–36.

A. Juels and M. Sudan, “A fuzzy vault scheme,” in IEEE International Symposium on Information Theory (2002).

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Figures (12)

Fig. 1.
Fig. 1.

CI system for capturing finger vein patterns.

Fig. 2.
Fig. 2.

Diagram of the proposed vein authentication system.

Fig. 3.
Fig. 3.

Cumulative contribution ratio of the KLT generated from 218 vein images.

Fig. 4.
Fig. 4.

Basis images and contribution ratios for KLT (CR, contribution ratio). (a) First order, CR=32.1[%], (b) second order, CR=22.7[%], and (c) third order, CR=11.1[%].

Fig. 5.
Fig. 5.

Coefficients of linear transforms. (a) Original finger vein image, (b) 2D-DCT (upper left is low frequency), (c) 2D-DWT (upper left is low frequency), and (d) KLT (x axis is order of KLT basis).

Fig. 6.
Fig. 6.

Restored finger vein images with the correct measurement matrix.

Fig. 7.
Fig. 7.

Accuracy of restored vein images depending on the number of CS measurement data. Each point denotes the average of the NCC maximum values, and each bar denotes the range of values.

Fig. 8.
Fig. 8.

Restored finger vein images with an incorrect measurement matrix, calculated from 2400 pieces of CS measurement data. In this case, random patterns like stationary white noise are obtained. (a) 2D-DCT, (b) 2D-DWT, and (c) KLT.

Fig. 9.
Fig. 9.

ROC curves from BPT. (a) M=50, (b) M=100, (c) M=200, (d) M=400, (e) M=800, (f) M=1600.

Fig. 10.
Fig. 10.

EER depending on the number of CS measurement data in BPT.

Fig. 11.
Fig. 11.

ROC curves from TPT. (a) M=50, (b) M=100, (c) M=200, (d) M=400, (e) M=800, (f) M=1600.

Fig. 12.
Fig. 12.

EER depending on the number of CS measurement data in TPT.

Equations (6)

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y=Φx,
s=Ψx,
y=ΦΨ1s,
Minimizes^1,subject toy=ΦΨ1s^,
x^=Ψ1s^.
NCC(p,q)=j=0Lyi=0Lx{f^(ip,jq)μf^}{f(i,j)μf}j=0Lyi=0Lx{f^(i,j)μf^}2j=0Lyi=0Lx{f(i,j)μf}2,

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