Improved fuzzy commitment scheme

被引:8
作者
Chauhan S. [1 ]
Sharma A. [1 ]
机构
[1] Department of Computer Science and Engineering, Delhi-NCR, Haryana, Sonipat
关键词
BCH code; Biometrics; Fuzzy commitment scheme; RS Code;
D O I
10.1007/s41870-018-0275-0
中图分类号
学科分类号
摘要
To ensure privacy and secrecy of biometric data, template protection schemes are widely used. Template protection schemes ensure renewability, irreversibility, and unlinkability among the templates. The Fuzzy Commitment Scheme is one of the widely used template protection schemes. This biometric cryptosystem combines cryptography and error correction codes. The original fuzzy commitment scheme is not secure. In this paper, an improved fuzzy commitment scheme has been introduced. The introduced scheme is validated using biometric data from the CASIA-Iris-Thousand dataset. In this paper, improved fuzzy commitment scheme or code-offset constructions are presented that use more than one key to secure the biometric data. The additional keys increase the exhaustive search space. The additional key made it impossible for an intruder to utilize the decoding algorithms to gain information about the user biometrics. © 2019, Bharati Vidyapeeth's Institute of Computer Applications and Management.
引用
收藏
页码:1321 / 1331
页数:10
相关论文
共 53 条
  • [1] Teoh A.B.J., Goh A., Ngo D.C.L., Random Multispace Quantization as an Analytic Mechanism for BioHashing of Biometrics and Random Identity Inputs, IEEE Trans Pattern Anal Mach Intell, 28, 12, pp. 1892-1901, (2006)
  • [2] Teoh A.B.J., Yuang C.T., Cancelable biometrics realization with multispace random projections, IEEE Trans Syst Man Cybern Part B Cybern, 37, 5, pp. 1096-1106, (2007)
  • [3] Pillai J.K., Patel V.M., Chellappa R., Ratha N.K., Sectored Random Projections for Cancelable Iris Biometrics, Proceedings of International Conference on Acoustics Speech and Signal Processing (ICASSP), pp. 1838-1841, (2010)
  • [4] Pillai J.K., Patel V.M., Chellappa R., Ratha N.K., Secure and robust iris recognition using random projections and sparse representations, IEEE Trans Pattern Anal Mach Intell, 33, 9, pp. 1877-1893, (2011)
  • [5] Savvides M., Kumar B., Khosla P., Cancelable biometric filters for face recognition, Proc Int Conf Pattern Recognit, 3, pp. 922-925, (2004)
  • [6] Hirata S., Takahashi K., Cancelable biometrics with perfect secrecy for correlation-based matching, Adv Biom LNCS, 5558, pp. 868-878, (2009)
  • [7] Takahashi K., Hirata S., Cancelable biometrics with provable security and its application to fingerprint verification, IEICE Trans Fundam Electron Commun Comput Sci, 94-A, 1, pp. 233-244, (2011)
  • [8] Generating provably secure cancelable fingerprint templates based on correlation-invariant random filtering. In: Proceedings of IEEE 3rd international conference on biometrics: Theory, applications, and systems, Pp 1–6, (2000)
  • [9] Lu H., Bone P., Young R., Chatwin C., A Novel Logarithmic Mapping Algorithm for the Human IRIS Recognition using MACH Filter, Proceedings of IEEE 15Th Signal Processing and Communications Applications, pp. 1-4, (2007)
  • [10] Yan Y., Zhang Y.-J., Multimodal biometrics fusion using Correlation Filter Bank, Proceedings of 19Th International Conference on Pattern Recognition, pp. 1-4, (2008)