Skip to content


  • Research Article
  • Open Access

Secure Hashing of Dynamic Hand Signatures Using Wavelet-Fourier Compression with BioPhasor Mixing and Discretization

EURASIP Journal on Advances in Signal Processing20062007:059125

Received: 28 February 2006

Accepted: 18 September 2006

Published: 17 December 2006


We introduce a novel method for secure computation of biometric hash on dynamic hand signatures using BioPhasor mixing and discretization. The use of BioPhasor as the mixing process provides a one-way transformation that precludes exact recovery of the biometric vector from compromised hashes and stolen tokens. In addition, our user-specific discretization acts both as an error correction step as well as a real-to-binary space converter. We also propose a new method of extracting compressed representation of dynamic hand signatures using discrete wavelet transform (DWT) and discrete fourier transform (DFT). Without the conventional use of dynamic time warping, the proposed method avoids storage of user's hand signature template. This is an important consideration for protecting the privacy of the biometric owner. Our results show that the proposed method could produce stable and distinguishable bit strings with equal error rates (EERs) of and for random and skilled forgeries for stolen token (worst case) scenario, and for both forgeries in the genuine token (optimal) scenario.


Error RateQuantum InformationError CorrectionDiscrete Wavelet TransformDiscrete Fourier Transform


Authors’ Affiliations

Faculty of Information Science and Technology (FIST), Multimedia University, Bukit Beruang, Malaysia


  1. Vielhauer C, Steinmetz R, Mayerhorf A: Biometric hash based on statistical features of online signatures. Proceedings of 16th International Conference on Pattern Recognition (ICPR '02), August 2002, Quebec, Canada 1: 123-126.Google Scholar
  2. Vielhauer C, Steinmetz R: Handwriting: feature correlation analysis for biometric hashes. EURASIP Journal on Applied Signal Processing 2004,2004(4):542-558. special issue on Biometric Signal Processing 10.1155/S1110865704309248View ArticleGoogle Scholar
  3. Feng H, Chan CW: Private key generation from on-line handwritten signatures. Information Management & Computer Security 2002,10(4):159-164. 10.1108/09685220210436949View ArticleGoogle Scholar
  4. Chang Y-J, Zhang W, Chen T: Biometrics-based cryptographic key generation. Proceedings of the IEEE International Conference on Multimedia and Expo (ICME '04), June 2004, Taipei, Taiwan 3: 2203-2206.Google Scholar
  5. Soutar C, Roberge D, Stoianov A, Gilroy R, Kumar BV: Biometric encryption using image processing. Optical Security and Counterfeit Deterrence Techniques II, January 1998, San Jose, Calif, USA, Proceedings of SPIE 3314: 178-188.View ArticleGoogle Scholar
  6. Juels A, Wattenberg M: A fuzzy commitment scheme. In Proceedings of the 6th ACM Conference on Computer and Communications Security (CCS '99), November 1999, Singapore Edited by: Tsudik G. 28-36.View ArticleGoogle Scholar
  7. Juels A, Sudan M: A fuzzy vault scheme. In Proceedings of IEEE International Symposium on Information Theory (ISIT '02), June-July 2002, Lausanne, Switzerland Edited by: Lapidoth A, Teletar E. 408.View ArticleGoogle Scholar
  8. Clancy TC, Kiyavash N, Lin DJ: Secure smartcard-based fingerprint authentication. Proceedings of the ACM SIGMM Workshop on Multimedia Biometrics Methods and Applications (WBMA '03), November 2003, Berkley, Calif, USA 45-52.Google Scholar
  9. Goh A, Ngo D-CL: Computation of cryptographic keys from face biometrics. Proceedings of 7th IFIP International Conference on Communications and Multimedia Security (CMS '03), October 2003, Torino, Italy, Lecture Notes in Computer Science 2828: 1-13.Google Scholar
  10. Yip W-K, Goh A, Ngo D-CL, Teoh A-BJ: Generation of replaceable cryptographic keys from dynamic handwritten signatures. Proceedings of International Conference on Advances in Biometrics (ICB '06), 2006, Hong Kong, Lecture Notes in Computer Science 3832: 509-515.View ArticleGoogle Scholar
  11. Yip W-K, Goh A, Ngo D-CL, Teoh A-BJ: Cryptographic keys from dynamic hand-signatures with biometric secrecy preservation and replaceability. Proceedings of the 4th IEEE on Automatic Identification Advanced Technologies (AutoID '05), October 2005, Buffalo, NY, USA 27-32.Google Scholar
  12. Liu K, Kargupta H, Ryan J: Random projection-based multiplicative data perturbation for privacy preserving distributed data mining. IEEE Transactions on Knowledge and Data Engineering 2006,18(1):92-106.View ArticleGoogle Scholar
  13. Kholmatov A, Yanikoglu B: Biometric authentication using online signatures. Proceedings of the 19th International Symposium on Computer and Information Sciences (ISCIS '04), October 2004, Kemer-Antalya, Turkey, Lecture Notes in Computer Science 3280: 373-380.Google Scholar
  14. Feng H, Chan CW: Online signature verification using a new extreme points warping technique. Pattern Recognition Letters 2003,24(16):2943-2951. 10.1016/S0167-8655(03)00155-7View ArticleGoogle Scholar
  15. Martinez JCR, Lopez JJV, Rosas FJL: A low-cost system for signature recognition. Proceedings of International Congress on Research in Electrical and Electronics Engineering (ELECTRO '02), 2002Google Scholar
  16. Hastie T, Kishon E, Clark M, Fan J: A model for signature verification. Proceedings of IEEE International Conference on Systems, Man, and Cybernetics, October 1991, Charlottesville, VA, USA 1: 191-196.Google Scholar
  17. Vergara da Silva A, Santana de Freitas D: Wavelet-based compared to function-based on-line signature verification. Proceedings of the 15th Brazilian Symposium on Computer Diagramics and Image Processing (SIBGRAPI '02), October 2002, Fortaleza-CE, Brazil 218-225.View ArticleGoogle Scholar
  18. Deng PS, Liao H-YM, Ho CW, Tyan H-R: Wavelet-based off-line handwritten signature verification. Computer Vision and Image Understanding 1999,76(3):173-190. 10.1006/cviu.1999.0799View ArticleGoogle Scholar
  19. Lejtman DZ, George SE: On-line handwritten signature verification using wavelets and back-propagation neural networks. Proceedings of 6th International Conference on Document Analysis and Recognition (ICDAR '01), September 2001, Seattle, Wash, USA 992-996.View ArticleGoogle Scholar
  20. Nakanishi I, Nishiguchi N, Itoh Y, Fukui Y: On-line signature verification method utilizing feature extraction based on DWT. Proceedings of IEEE International Symposium on Circuits and Systems (ISCAS '03), May 2003, Bangkok, Thailand 4: IV-73-IV-76.Google Scholar
  21. Lam CF, Kamins D: Signature recognition through spectral analysis. Pattern Recognition 1989,22(1):39-44. 10.1016/0031-3203(89)90036-8View ArticleGoogle Scholar
  22. SVC First International Signature Verification Competition, 2004,
  23. Teoh A-BJ, Ngo D-CL: Cancellable biometrics realization through biophasoring. Proceedings of 9th IEEE International Conference on Control, Automation, Robotics and Vision (ICARCV '06), December 2006, SingaporeGoogle Scholar
  24. Cover TM, Thomas JA: Elements of Information Theory. 2nd edition. John Wiley & Sons, New York, NY, USA; 1991.View ArticleMATHGoogle Scholar
  25. Shannon CE: Communication Theory of Secrecy Systems. Bell Systems Technical Journal 1949, 28: 656-715.MathSciNetView ArticleMATHGoogle Scholar


© Yip Wai Kuan et al. 2007

This article is published under license to BioMed Central Ltd. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.