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A two-phased approach to reducing the false accept rate of spoofed iris codes

Published: 15 April 2010 Publication History

Abstract

In this paper, we demonstrate how to reduce the chance of a spoofed iris code being falsely accepted by an iris recognition system. We simulate the system attack by taking one of the registered iris codes from a subject set and mutating it by several different rates and presenting the resultant iris codes to our system. Our approach uses the k-nearest neighbors from a training set to the known spoof to establish a critical distance. Presented iris codes from our mutant set that have a Hamming Ratio when compared to the spoof that is less than the critical distance are rejected. Those that are falsely accepted are totaled to produce a Spoof False Accept Rate (SP-FAR). The second phase of our approach uses traditional iris code recognition to reduce the SP-FAR by rejecting those spoofs that were mutated to a degree such that they will not match any of the other iris codes in the training set.

References

[1]
Bowyer, K. W., Hollingsworth, K. P., and Flynn, P. J. (2008). "Image Understanding for Iris Biometrics: A Survey", Computer Vision and Image Understanding, 110:281--307, 2008.
[2]
Daugman, J. 2004. "How iris recognition works," IEEE Transactions on Circuits and Systems for Video Technology, 14(1):21--30, 2004.
[3]
Daugman, J. 2008. "Iris Recognition," Handbook of Biometrics, Anil K. Jain, Patrick Flynn, Arun A. Ross, Eds., pp. 71--90, Springer.
[4]
Dozier, G. V., Savvides, M., Bryant, K., Munemoto, T., Ricanek, K., Jr., Woodard, D. (2009 "Developing Iris Templates via Bit Inconsistency and GRIT," Encyclopedia of Biometrics, Marios Savvides, Ed., Springer.
[5]
Dozier, G., Frederiksen, K., Meeks, R., Savvides, M., Bryant, K., Hopes, D., Munemoto, T. (2009). "Minimizing the Number of Bits Needed for Iris Recognition via Bit Inconsistency and GRIT," Proceedings of the 2009 IEEE Workshop on Computational Intelligence in Biometrics: Theory, Algorithms, and Applications, pp. 30--37, Nashville, March 30 April 2nd, 2009.
[6]
National Institute of Standards and Technology Iris Challenge Evaluation, 2006, http://iris.nist.gov/ice.
[7]
Thornton, Savvides, M., and Kumar, V. (2005). Robust Iris Recognition Using Advanced Correlation Techniques," Proc. Int'l Conf. Image Analysis and Recognition, pp. 1098--1105, 2005.
[8]
Nixon, K. A, Aimale, V., and Rowe, R. K. (2008). Spoof "Detection Schemes," Handbook of Biometrics, pp. 403--423, Springer.

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  1. A two-phased approach to reducing the false accept rate of spoofed iris codes

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      cover image ACM Conferences
      ACMSE '10: Proceedings of the 48th annual ACM Southeast Conference
      April 2010
      488 pages
      ISBN:9781450300643
      DOI:10.1145/1900008
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      Published: 15 April 2010

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      Author Tags

      1. Iris
      2. biometrics
      3. spoof

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      ACM SE '10
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      ACM SE '10: ACM Southeast Regional Conference
      April 15 - 17, 2010
      Mississippi, Oxford

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      ACMSE '10 Paper Acceptance Rate 48 of 94 submissions, 51%;
      Overall Acceptance Rate 502 of 1,023 submissions, 49%

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