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A USB-pluggable hardware true random number generator. In computing, a hardware random number generator (HRNG), true random number generator (TRNG), non-deterministic random bit generator (NRBG), [1] or physical random number generator [2] [3] is a device that generates random numbers from a physical process capable of producing entropy (in other words, the device always has access to a ...
However, generally they are considerably slower (typically by a factor 2–10) than fast, non-cryptographic random number generators. These include: Stream ciphers. Popular choices are Salsa20 or ChaCha (often with the number of rounds reduced to 8 for speed), ISAAC, HC-128 and RC4. Block ciphers in counter mode.
Among them, optical chaos [6] [7] has a high potential to physically produce high-speed random numbers due to its high bandwidth and large amplitude. A prototype of a high-speed, real-time physical random bit generator based on a chaotic laser was built in 2013. [8] Various imaginative ways of collecting this entropic information have been devised.
The Mersenne Twister is a general-purpose pseudorandom number generator (PRNG) developed in 1997 by Makoto Matsumoto (松本 眞) and Takuji Nishimura (西村 拓士). [ 1][ 2] Its name derives from the choice of a Mersenne prime as its period length. The Mersenne Twister was designed specifically to rectify most of the flaws found in older PRNGs.
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 ...
The ACORN or ″ A dditive Co ngruential R andom N umber″ generators are a robust family of pseudorandom number generators (PRNGs) for sequences of uniformly distributed pseudo-random numbers, introduced in 1989 and still valid in 2019, thirty years later. Introduced by R.S.Wikramaratna, [1] ACORN was originally designed for use in ...
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.
The diehard tests are a battery of statistical tests for measuring the quality of a random number generator. They were developed by George Marsaglia over several years and first published in 1995 on a CD-ROM of random numbers. [ 1] In 2006, the original diehard tests were extended into the dieharder tests.