Random number generation

Implementation and Statistical Characterization of High Efficiency True Random Number Generators (RNGs) for Cryptographic Applications

Wed, Jul 17 2024

Random number generation Cryptography Analog-to-digital converters chaos

Practical implementations of RNGs can be classified into two major categories, namely pseudo-RNGs and physical-RNGs. Pseudo-RNGs are deterministic, numeric algorithms that expand short seeds into long bit sequences. Conversely, physical-RNGs rely on microscopic processes resulting in macroscopic observables which can be regarded as random noise (quantum, thermal,…). Pseudo-RNGs generally depart more from the ideal specifications: are based on finite memory algorithms, thus exhibit periodic behaviors and generate correlated samples and are therefore unsuitable for data security and cryptography