A novel cancellable biometric recognition system based on Rubik’s cube technique for cyber-security applications

Abstract

ObjectiveTen years ago, biometrics became an efficient tool of security and authentication enforcement. In a classical access system, a user can easily change password if it is compromised. However, user’s biometrics are limited and unique, and if a user biometric trait is compromised, it will be impossible to change it. Hence, cancellable biometric systems depend on the transformation of data or a biometric feature into a new format, so that users can replace their biometric templates in the same or a different system. In this paper, an efficient cancellable biometric recognition system is presented. In this system, both signal-and feature-level transformations are used to generate the cancellable templates MethodsA novel hybrid encryption framework based on the Rubik’s cube technique is presented to allow efficient encryption of face, iris, and fingerprint biometric templates. This framework begins with extraction of biometric features using the Scale-Invariant Feature Transform (SIFT). After that, the resulting biometric features are encrypted with the optical Double Random Phase Encoding (DRPE) algorithm. Then, the resulting encrypted biometric features are further encrypted with the chaotic Baker map permutation, Advanced Encryption Standard (AES), or Ron's Code (RC6) algorithm in the Cipher Feed Back (CFB) mode of operation. Finally, the resulting encrypted biometrics are additionally encrypted with the Rubik’s cube technique. The chaotic, RC6, or AES encrypted biometrics are utilized on the faces of the Rubik’s cube. From the concepts of image encryption, the DRPE, RC6, and the AES algorithms introduce a degree of diffusion, whilst the chaotic Baker map adds a degree of permutation. Moreover, the Rubik’s cube technique adds more permutation to the encrypted biometrics, simultaneously. The quality evaluation of the proposed cancellable biometric system reveals good performance. ResultsThe simulation results prove that the suggested hybrid encryption framework is reliable, and it presents recommended security and robustness levels for its utilization for building efficient cancellable biometric systems compared to the traditional techniques.