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A pseudorandom number generator ( PRNG ), also known as a deterministic random bit generator ( DRBG ), [ 1] is an algorithm for generating a sequence of numbers whose properties approximate the properties of sequences of random numbers. The PRNG-generated sequence is not truly random, because it is completely determined by an initial value ...
Pseudorandom generators may also be used to construct symmetric key cryptosystems, where a large number of messages can be safely encrypted under the same key. Such a construction can be based on a pseudorandom function family, which generalizes the notion of a pseudorandom generator.
In many applications, the deterministic process is a computer algorithm called a pseudorandom number generator, which must first be provided with a number called a random seed. Since the same seed will yield the same sequence every time, it is important that the seed be well chosen and kept hidden, especially in security applications, where the ...
Blum Blum Shub ( B.B.S.) is a pseudorandom number generator proposed in 1986 by Lenore Blum, Manuel Blum and Michael Shub [ 1] that is derived from Michael O. Rabin 's one-way function. Blum Blum Shub takes the form. where M = pq is the product of two large primes p and q. At each step of the algorithm, some output is derived from xn+1; the ...
Random number generation is a process by which, often by means of a random number generator ( RNG ), a sequence of numbers or symbols that cannot be reasonably predicted better than by random chance is generated. This means that the particular outcome sequence will contain some patterns detectable in hindsight but impossible to foresee.
Wichmann–Hill is a pseudorandom number generator proposed in 1982 by Brian Wichmann and David Hill. [1] It consists of three linear congruential generators with different prime moduli, each of which is used to produce a uniformly distributed number between 0 and 1. These are summed, modulo 1, to produce the result. [2]
Multiply-with-carry pseudorandom number generator. In computer science, multiply-with-carry (MWC) is a method invented by George Marsaglia [ 1] for generating sequences of random integers based on an initial set from two to many thousands of randomly chosen seed values.
Non-uniform random variate generation or pseudo-random number sampling is the numerical practice of generating pseudo-random numbers (PRN) that follow a given probability distribution . Methods are typically based on the availability of a uniformly distributed PRN generator. Computational algorithms are then used to manipulate a single random ...