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2008 IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops
Fuzzy extractors for asymmetric biometric representations
Anchorage, AK, USA
June 23-June 28
ISBN: 978-1-4244-2339-2
Qiming Li, Institute for Infocomm Research, Singapore
Muchuan Guo, National University of Singapore, Singapore
Ee-Chien Chang, National University of Singapore, Singapore
Fuzzy extractors are recently proposed error-tolerant cryptographic primitives that are potentially useful to protect biometric templates. However, there are challenges in adopting these primitives. Firstly, fuzzy extractors require the data obtained during both enrollment and verification to be in the same feature representation. However, for better performance on ROC, multiple high quality samples can be obtained during enrollment, which result in an asymmetric setting whereby data obtained in enrollment and verification are stored in different representations. Secondly, fuzzy extractors only concern about the strength of the secret key extracted, and does not directly assure that privacy is preserved. In this paper, we consider a simplified asymmetric setting and propose a sketch scheme. We analyze the key strength measured by the number of secret bits that can be extracted, and the privacy measured by the information leakage on the user identities. We next apply and investigate the scheme on FVC fingerprint datasets.
Citation:
Qiming Li, Muchuan Guo, Ee-Chien Chang, "Fuzzy extractors for asymmetric biometric representations," cvprw, pp.1-6, 2008 IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops, 2008
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