A Practical Biometric Random Number Generator for Mobile Security Applications

Abstract

IDMs are getting more effective and secure with biometric recognition and more privacy-preserving with advanced cryptosystems. In order to meet privacy and security needs of an IDM, the cryptographic background should rely on reliable random number generation. In this study, a Biometric Random Number Generator (BRNG) is proposed which plays a crucial role in a typical cryptosystem. The proposed novel approach extracts the high-frequency information in biometric signal which is associated with uncertainty existing in nature of biometrics. This bio-uncertainty, utilized as an entropy source, may be caused by sensory noise, environmental changes, position of the biometric trait, accessories worn, etc. The filtered nondeterministic information is then utilized by a postprocessing technique to obtain a random number set fulfilling the NIST 800-22 statistical randomness criteria. The proposed technique presents random number sequences without need of an additional hardware.