Sequences of “random” numerical values are used in many statistical procedures, in numerical mathematics, in physics, and also in number-theoretic applications to replace statistical observations or to automate the input of variable quantities. Random numbers are used:
to select random samples from a larger set,
in cryptography to generate keys and in running security protocols,
as initial values in procedures to generate prime numbers,
to test computer programs (a topic to which we shall return),
as well as in many additional applications. In computer simulations of natural phenomena random numbers can be used to represent measured values, thereby representing a natural process (Monte Carlo methods). Random numbers are useful even when numbers are required that can be selected arbitrarily. Before we set out in this chapter to produce some functions for the generation of large random numbers, which will be required, in particular, for cryptographic applications, we should take care of some methodological preparations.
Internal State Hash Function Random Number Generator Pseudorandom Number Advance Encryption Standard
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
This is a preview of subscription content, log in to check access