Neurogenetic reconstruction of biometric templates: A new security threat?

Joshua Adams,Gerry Dozier,Kelvin Bryant,Joseph Shelton,Aniesha Alford,Derrick Leflore,Tamirat Abegaz

Orlando, FL（2012）

Cited 4|Views7

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Abstract

In this paper, we demonstrate how neurogenetic reconstruction can be used to reconstruct facial images from biometric templates extracted using Local Binary Patterns (LBPs). We also demonstrate the process of neurogenetic distortion of biometric templates in order to mitigate neurogenetic reconstruction. Our results show that reconstructed images can be used to recognize individuals within a dataset with a high degree of accuracy. Our results also show that neurogenetic distortion can be used to successfully distort biometric templates to prevent image reconstruction.

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Key words

biometrics (access control),feature extraction,image reconstruction,biometric template extraction,facial image reconstruction,local binary patterns,neurogenetic image reconstruction distortion,security threat,general regression neural network (grnn),genetic algorithms (ga),local binary patterns (lbp),steady state genetic algorithm (ssga),local binary pattern,kernel,genetic algorithm,accuracy,genetic algorithms,biometrics,histograms

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