Grobner Bases Method for Biometric Traits Identification and Encryption


Biometric identification systems are principally related to the information security as well as data protection and encryption. The paper proposes a method to integrate biometrics data encryption and authentication into error correction techniques. The normal methods of biometric templates matching are replaced by a more powerful and high quality identification approach based on Grobner bases computations. In the normal biometric systems, where the data are always noisy, an approximate matching is expected; however, our cryptographic method gives particularly exact matching.

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Sayed, M. (2015) Grobner Bases Method for Biometric Traits Identification and Encryption. Journal of Information Security, 6, 241-249. doi: 10.4236/jis.2015.63024.

Conflicts of Interest

The authors declare no conflicts of interest.


[1] Raina, V.K. (2011) Integration of Biometric Authentication Procedure in Customer Oriented Payment System in Trusted Mobile Devices. International Journal of Information Technology Convergence and Services, 1, 15-25.
[2] Vacca, J.R. (2007) Biometric Technologies and Verification Systems. Elsevier Science & Technology.
[3] Sayed, M. and Jradi, F. (2014) Biometrics: Effectiveness and Applications within the Blended Learning Environment. Journal of Computer Engineering and Intelligent Systems (CEIS), 5, 1-8.
[4] Rosdi, B.A., Shing, C.W. and Suandi, S.A. (2011) Finger Vein Recognition Using Local Line Binary Pattern. Sensors, 11, 11357-11371.
[5] Zhou, Y. and Kumar, A. (2011) Human Identification Using Palm-Vein Images. IEEE Transactions on Information Forensics and Security, 6, 1259-1274.
[6] Xi, X., Yang, G., Yin, Y. and Meng, X. (2013) Finger Vein Recognition with Personalized Feature Selection. Sensors, 13, 11243-11259.
[7] Yang, J.F. and Yan, M.F. (2010) An Improved Method for Finger-Vein Image Enhancement. Proceedings of the 2010 IEEE 10th International Conference on Signal Processing, Beijing, 24-28 October 2010, 1706-1709.
[8] Teoh, A., Gho, A. and Ngo, D. (2006) Random Multispace Quantization as an Analytic Mechanism for Biohashing of Biometric and Random Identity Inputs. IEEE Transactions on Pattern Analysis and Machine Intelligence, 28, 1892-1901.
[9] Tome, P., Vanoni, M. and Marcel, S. (2014) On the Vulnerability of Finger Vein Recognition to Spoofing. IEEE International Conference of the Biometrics Special Interest Group (BIOSIG), 230.
[10] Raina, V.K. and Pandey, U.S. (2011) Biometric and ID Based User Authentication Mechanism Using Smart Cards for Multi-Server Environment. 5th National Conference on Computing for Nation Development, 5BVICAM, New Delhi, 10-11 March 2011.
[11] Jain, A. and Aggarwal, S. (2012) Multimodal Biometric System: A Survey. International Journal of Applied Science and Advance Technology, 1, 58-63.
[12] Yang, J. (2010) Biometric Verification Techniques Combing with Digital Signature for Multimodal Biometrics Payment Systems. IEEE 4th International Conference on Management of e-Commerce and e-Government, Chengdu, 23-24 October 2010, 405-410.
[13] Yang, J.F. and Yang, J.L. (2009) Multi-Channel Gabor Filter Design for Finger-Vein Image Enhancement. Proceedings of the 5th International Conference on Image and Graphics, Xi’an, 20-23 September 2009, 87-91.
[14] Sutcu, Y., Rane, S., Yedidia, J.S., Draper, S.C. and Vetro, A. (2008) Feature Transformation for a Slepian-Wolf Biometric System Based on Error Correcting Codes. Computer Vision and Pattern Recognition (CVPR) Biometrics Workshop, Anchorage, 1-6.
[15] Kang, W. and Wu, Q. (2014) Contactless Palm Vein Recognition Using a Mutual Foreground-Based Local Binary Pattern. IEEE Transactions on Information Forensics and Security, 9, 1974-1985.
[16] Gallager, R. (1962) Low-Density Parity-Check Codes. IEEE Transactions on Information Theory, 8, 21-29.
[17] Buchberger, B. (1985) Grobner Bases: An Algorithmic Method in Polynomial Ideal Theory. In: Bose, N.K., Ed., Multidimensional System Theory, D. Reidel, Dordrecht.
[18] Becker, T., Kredel, H. and Weispfenning, V. (1993) Grobner Bases: A Computational Approach to Commutative Algebra. Springer-Verlag, London.
[19] Borges-Trenard, M.A., Borges-Quintana, M.M. and Mora, T. (2000) Computing Grobner Bases by FGLM Techniques in a Non-Commutative Setting. Journal of Symbolic Computation, 30, 429-449.
[20] Sayed, M. (2009) Coset Enumeration of Symmetrically Generated Groups Using Grobner Bases. International Journal of Algebra, 3, 693-705.
[21] Cooper, A.B. (1992) Towards a New Method of Decoding Algebraic Codes Using Grobner Bases. 10th Army Conference on Applied Mathematics and Computing, 93, 293-297.
[22] Arnold, E.A. (2003) Modular Algorithms for Computing Grobner Bases. Journal of Symbolic Computation, 35, 403-419.
[23] Sayed, M. (2011) Coset Decomposition Method for Decoding Linear Codes. International Journal of Algebra, 5, 1395-1404.
[24] Heegard, C., Little, J. and Saints, K. (1995) Systematic Encoding via Grobner Bases for a Class of Algebraic-Geometric Goppa Codes. IEEE Transactions on Information Theory, 41, 1752-1761.
[25] Bulygin, S. and Pellikaan, R. (2009) Bounded Distance Decoding of Linear Error-Correcting Codes with Grobner Bases. Journal of Symbolic Computation, 44, 1626-1643.
[26] Sayed, M. (2015) Coset Decomposition Method for Storing and Decoding Fingerprint Data. Journal of Advanced Computer Science & Technology, 4, 6-11.
[27] Sayed, M. (2015) Palm Vein Authentication Based on the Coset Decomposition Method. Journal of Information Security, 6, 197-205.
[28] Yang, G.P., Xi, X.M. and Yin, Y.L. (2012) Finger Vein Recognition Based on a Personalized Best Bit Map. Sensors, 12, 1738-1757.
[29] Bosma, W., Cannon, J.J., Fieker, C. and Steel, A., Eds. (2010) Handbook of Magma Functions, Edition 2.16.

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