Remarks on BioHashing based cancelable biometrics in verification system

Research output: Contribution to journalArticle

11 Citations (Scopus)

Abstract

Biometric characteristics are immutable and hence their compromise is permanent. To address this problem, cancelable biometrics was introduced to denote biometric templates that can be canceled and replaced. BioHash is a form of cancelable biometrics which mixes a set of user-specific random numbers with the biometric features. The main drawback of BioHash is its great degradation in performance when the legitimate token is stolen and used by the imposter to claim as the legitimate user. In this paper, we employ a modified probabilistic neural network as the classifier to alleviate this problem. The experiments are tested on the FERET face data set with promising results.

Original languageEnglish
Pages (from-to)2461-2464
Number of pages4
JournalNeurocomputing
Volume69
Issue number16-18
DOIs
Publication statusPublished - 2006 Oct 1

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Biometrics
Classifiers
Datasets
Neural networks
Degradation
Experiments

All Science Journal Classification (ASJC) codes

  • Computer Science Applications
  • Cognitive Neuroscience
  • Artificial Intelligence

Cite this

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abstract = "Biometric characteristics are immutable and hence their compromise is permanent. To address this problem, cancelable biometrics was introduced to denote biometric templates that can be canceled and replaced. BioHash is a form of cancelable biometrics which mixes a set of user-specific random numbers with the biometric features. The main drawback of BioHash is its great degradation in performance when the legitimate token is stolen and used by the imposter to claim as the legitimate user. In this paper, we employ a modified probabilistic neural network as the classifier to alleviate this problem. The experiments are tested on the FERET face data set with promising results.",
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Remarks on BioHashing based cancelable biometrics in verification system. / Jin, Andrew Teoh Beng; Connie, Tee.

In: Neurocomputing, Vol. 69, No. 16-18, 01.10.2006, p. 2461-2464.

Research output: Contribution to journalArticle

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