期刊文献+

Two-Factor Cancelable Biometrics Authenticator

Two-Factor Cancelable Biometrics Authenticator
原文传递
导出
摘要 Biometrics-based authentication system offers advantages of providing high reliability and accuracy. However the contemporary authentication system is impuissance to compromise. If a biometrics data is compromised, it cannot be replaced and rendered unusable. In this paper, a cancelable biometrics-based authenticator is proposed to solve this irrevocability issue. The proposed approach is a two-factor authentication system, which requires both of the random data and facial feature in order to access the system. In this system, tokenized pseudo-random data is coupled with momentbased facial feature via inner product algorithm. The output of the product is then discretized to generate a set of private binary code, coined as 2factor-Hashing code, which is acted as verification key. If this biometrics-based verification key is compromised, a new one can be issued by replacing a different set of random number via token replacement. Then, the compromised one is rendered completely useless. This feature offers an extra protection layer against biometrics fabrication since the verification code is replaceable. Experimental results demonstrate that the proposed system provides zero Equal Error Rate in which there is a clear separation in between the genuine and the imposter distribution populations. Biometrics-based authentication system offers advantages of providing high reliability and accuracy. However the contemporary authentication system is impuissance to compromise. If a biometrics data is compromised, it cannot be replaced and rendered unusable. In this paper, a cancelable biometrics-based authenticator is proposed to solve this irrevocability issue. The proposed approach is a two-factor authentication system, which requires both of the random data and facial feature in order to access the system. In this system, tokenized pseudo-random data is coupled with momentbased facial feature via inner product algorithm. The output of the product is then discretized to generate a set of private binary code, coined as 2factor-Hashing code, which is acted as verification key. If this biometrics-based verification key is compromised, a new one can be issued by replacing a different set of random number via token replacement. Then, the compromised one is rendered completely useless. This feature offers an extra protection layer against biometrics fabrication since the verification code is replaceable. Experimental results demonstrate that the proposed system provides zero Equal Error Rate in which there is a clear separation in between the genuine and the imposter distribution populations.
出处 《Journal of Computer Science & Technology》 SCIE EI CSCD 2007年第1期54-59,共6页 计算机科学技术学报(英文版)
关键词 cancelable biometrics face recognition Geometric moments pseudo Zernike moment cancelable biometrics, face recognition, Geometric moments,pseudo Zernike moment
  • 相关文献

参考文献13

  • 1Schneier B. Secret & Lies: Digital Security in a Networked World, New York: John Wiley & Sons, 2000, pp.141-145.
  • 2Braithwaite M, Ulf Cahn yon Seelen, Cambier J et al.Application-specific biometrics templates. In Proc. IEEE Workshop on Automatic Identification Advanced Technologies, Tarrytown, NY, 2002, pp.167 171.
  • 3Bolle R M, Connel J H, Ratha N K. Biometric perils and patches. Pattern Recognition, 2002, 35: 2727-2738.
  • 4Umut U, Sharah P, Salil P et al. Biometric cryptosystems:Issues and challenges. Proc. the IEEE, 2004, 92(6): 948-960.
  • 5Goh A, Ngo D. Computation of cryptographic keys from face biometrics. In Proc. 7th IEEE Communications and Multimedia Security, Torino, 2003, pp.1-13.
  • 6Ratha N, Connell J, Bolle R M: Enhancing security and privacy in biometrics-based authentication systems. IBM Syst.J., 2001, 40(3): 614-634.
  • 7Davida G I, Frankel Y, Matt B J. On enabling secure applications through off-line biometric identification. In Proc. IEEE Syrup. Privacy and Security, 1998, pp.148-157.
  • 8Mukundan R, Ramakrishnan K R. Moment Functions in Image Analysis-Theory and Applications. World Scientific Publishing, 1998.
  • 9Teh C H, Chin R T. On image analysis by the methods of moments. IEEE Trans. Pattern Anal. Machine Intell., 1998,10: 496-512.
  • 10Khotanzad A. Inwriant image recognition by Zernike moments.IEEE Trans. Pattern. Anal. Machine Intell, 1990,12(5): 489-497.

相关作者

内容加载中请稍等...

相关机构

内容加载中请稍等...

相关主题

内容加载中请稍等...

浏览历史

内容加载中请稍等...
;
使用帮助 返回顶部