Please use this identifier to cite or link to this item: https://doi.org/10.1109/CVPRW.2008.4563113
Title: Fuzzy extractors for asymmetric biometric representations
Authors: Li, Q.
Guo, M.
Chang, K.-C. 
Issue Date: 2008
Source: Li, Q.,Guo, M.,Chang, K.-C. (2008). Fuzzy extractors for asymmetric biometric representations. 2008 IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops, CVPR Workshops. ScholarBank@NUS Repository. https://doi.org/10.1109/CVPRW.2008.4563113
Abstract: 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. © 2008 IEEE.
Source Title: 2008 IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops, CVPR Workshops
URI: http://scholarbank.nus.edu.sg/handle/10635/39902
ISBN: 9781424423408
DOI: 10.1109/CVPRW.2008.4563113
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