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A Study on A Biometric Bits Extraction Method Using Subpattern-based PCA and A Helper Data  

Lee, Hyung-Gu (Yonsei University, Biometric Engineering Research Center)
Jung, Ho-Gi (Yonsei University, Biometric Engineering Research Center)
Publication Information
Journal of the Institute of Electronics Engineers of Korea SP / v.47, no.5, 2010 , pp. 183-191 More about this Journal
Abstract
Unique and invariant biometric characteristics have been used for secure user authentication. Storing original biometric data is not acceptable due to privacy and security concerns of biometric technology. In order to enhance the security of the biometric data, the cancelable biometrics was introduced. Using revocable and non-invertible transformation, the cancelable biometrics can provide a way of more secure biometric authentication. In this paper, we present a new cancelable bits extraction method for the facial data. For the feature extraction, the Subpattern-based Principle Component Analysis (PCA) is adopted. The Subpattern-based PCA divides a whole image into a set of partitioned subpatterns and extracts principle components from each subpattern area. The feature extracted by using Subpattern-based PCA is discretized with a helper data based method. The elements of the obtained bits are evaluated and ordered according to a measure based on the fisher criterion. Finally, the most discriminative bits are chosen as the biometric bits string and used for authentication of each identity. Even if the generated bits string is compromised, new bits string can be generated simply by changing the helper data. Because, the helper data utilizes partial information of the feature, the proposed method does not reveal privacy sensitive biometric information of the user. For a security evaluation of the proposed method, a scenario in which the helper is compromised by an adversary is also considered.
Keywords
Biometric bits string extraction; cancelable biometrics; Subpattern-based PCA;
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