Cryptographic Key Generation from Biometric Data Using Lattice Mapping

  • Authors:
  • Gang Zheng;Wanqing Li;Ce Zhan

  • Affiliations:
  • University of Wollongong, Australia;University of Wollongong, Australia;University of Wollongong, Australia

  • Venue:
  • ICPR '06 Proceedings of the 18th International Conference on Pattern Recognition - Volume 04
  • Year:
  • 2006

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Abstract

Crypto-biometric systems are recently emerging as an effective process of key management to address the security weakness of conventional key release systems using passcodes, tokens or pattern recognition based biometrics. This paper presents a lattice mapping based fuzzy commitment method for cryptographic key generation from biometric data. The proposed method not only outputs high entropy keys, but also conceals the original biometric data such that it is impossible to recover the biometric data even when the stored information in the system is open to an attacker. Simulated results have demonstrated that its authentication accuracy is comparable to the well-known k-nearest neighbour classification.