Paper Info
Title
Securing templates in a face recognition system using Error-Correcting Output Code and chaos theory
Abstract
In biometric cryptosystems, biometric data is combined with cryptography algorithms to generate secure templates. In these systems, creating protected templates with both high discriminability and high security is a challenging issue. To address this issue, this paper proposes a new face cryptosystem based on binarization transformation, chaos feature permutation and fuzzy commitment scheme. To enhance discriminability, real-valued templates are converted into their binary versions using a new discriminant binarization transformation based on Error-Correcting Output Code. Then, the chaos feature permutation is used to increase the security and privacy of binary templates, and also to protect the fuzzy commitment scheme against cross-matching attacks. The proposed scheme is evaluated on three well-known face databases, i.e. CMU PIE, FEI, and Extended Yale B. Experimental results show that the proposed method improves discriminability, as well as privacy and security of the system, compared to the existing face template protection algorithms.
Year
DOI
Venue
2018
10.1016/j.compeleceng.2018.01.029
Computers & Electrical Engineering
Keywords
Field
DocType
Face template protection,Cryptosystem,Chaos feature permutation,Error-Correcting Output Code,Discriminant binarization transformation
Facial recognition system,Pattern recognition,Cryptography,Computer science,Permutation,Fuzzy logic,Commitment scheme,Real-time computing,Cryptosystem,Artificial intelligence,Template,Binary number
Journal
Volume
ISSN
Citations 
72
0045-7906
4
PageRank 
References 
Authors
0.37
15
3
Name
Order
Citations
PageRank
Sara Nazari1101.48
Mohammad Shahram Moin2102.12
Hamidreza Rashidy Kanan319516.32