Efficient chaotic-Baker-map-based cancelable face recognition

Abstract

Biometric recognition schemes are commonly utilized for security purposes. These schemes face two major challenges: security challenge and reliance on a particular biometric for authentication. The protection challenge comes from the use of basic biometrics in records. Therefore, if these records are compromised, the biometrics will no longer be valid. Consequently, it is necessary to preserve basic biometrics by protecting them from being used in biometric records. Cancelable biometric recognition systems rely on changing the information or biometric features to different formats, so that persons can use their specific biometric models in single or multiple systems. The mixture of chaos theory and cryptography shapes a crucial area for information security. The newest development in encryption systems is chaos-based for various distinctive attributes such as sensitivity to preliminary conditions, non-convergence, non-periodicity, and control parameters. This paper introduces a method to produce numerous encrypted biometric templates that are re-created by various convolution kernels generated from employing chaotic Baker map in different domains. Our proposed method has superior performance in treating variations in illumination, occlusion and facial expressions. It also has the added novelty of being able to perform authentication in the encrypted domain. In addition, the same approach can be applied on different databases. The chaotic map effect in different domains is evaluated on the widely-used AT&T, YALE, UFI, LFW, and FERET databases. The cancelable biometric system using the proposed Discrete Wavelet Transform (DWT) domain encryption with various keys has the best performance among all other implementations. In average, we achieved a 2% error probability, a 0.3 s authentication time, a 0.02% False Rejection Rate (FRR), a 0% False Acceptance Rate (FAR), a 0.0% Equal Error Rate (EER) and a 98.43% accuracy. Our proposed method also provides template diversity.

Feature extraction and learning approaches for cancellable biometrics: A survey

“…The extracted features are then transformed and averaged at the feature level in each direction to generate a cancellable face template. Faragallah et al [60] designed numerous encrypted biometric templates that are created and recreated by employing a variety of convolution kernels produced by the chaotic Baker mapping of domains. The encrypted cancellable biometric system mapped from the domain after the discrete wavelet transform (DWT) exhibits the best performance among all implementations.…”

“…� The YMU dataset [124] -17 number of cancellable face systems are tested and the system of Bamoriya et al [108] achieves the best performance with EER = 0%. On another database FERET [127], the system designed by Faragallah et al [60] obtains the best EER of 0.014976%.…”

“…On another database FERET [127], the system designed by Faragallah et al. [60] obtains the best EER of 0.014976%.…”

Flexible Multi-Layered Security System: Secure 6G Mobile Network Considerations

“…The dependency of Baker map encryption on the stretch-and-fold concept. Thismeans that the plain image is randomly distributed in the encrypted image [31], [46]. Figure 4 2D chaotic encryption of an 8 * 8 matrix.…”

Optical Ciphering Scheme for Cancellable Speaker Identification System

“…In order to become effective, each biometric template scheme must meet certain fundamental requirements for security and privacy. These are listed below [17][18][19][20]:…”