Análise de Componentes Principais para a Geração de Chaves Simétricas
(Principal Component Analysis for Symmetric Key Generation)
Gilmar Caiado Fleury Medeiros (firstname.lastname@example.org), Miguel Gustavo Lizárraga (email@example.com), Luan Ling Lee (firstname.lastname@example.org)
School of Electrical and Computer Engineering, State University of Campinas, Campinas, SP, Brazil
This paper appears in: Revista IEEE América Latina
Publication Date: March 2004
Volume: 2, Issue: 1
This work presents a novel biometric encryption scheme based on feature vectors extracted from a face recognition system. This system uses principal component analysis, in order to generate a symmetric secret key, being this key used to encrypt any information data, like a biometric template. The data is therefore concealed and only an individual having a similar biometric feature vector is capable to regenerate the correct key. This scheme is applied to a system using eigenfaces for recognition, where the corrected detected class from a sample image can guarantee the corrected generation of a symmetric key. Due to the efficiency of the system being dependent of the face recognition algorithm, the tests showed a rate of 90.4% of corrected symmetric key generation, or sucessfull encryption/ decryption scheme, for 25 face classes, with 5 images each.
biometrics, authentication, cryptography, feature extraction, eigenfaces
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