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Dice are an example of a mechanical hardware random number generator. When a cubical die is rolled, a random number from 1 to 6 is obtained. 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.
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.
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 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 ...
Easter eggs by Google. A Pacman related interactive Google Doodle from 2010 will be shown to users searching for "google pacman" or "play pacman". The American technology company Google has added Easter eggs into many of its products and services, such as Google Search, YouTube, and Android since the 2000s. [1][2]
Wichmann–Hill. 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.
To illustrate, imagine if a simple 32 bit linear congruential pseudo-random number generator of the type supplied with most programming languages (e.g., as the 'rand' or 'rnd' function) is used as a source of keys. There will only be some four billion possible values produced before the generator repeats itself.
Random.org (stylized as RANDOM.ORG) is a website that produces random numbers based on atmospheric noise. [1] In addition to generating random numbers in a specified range and subject to a specified probability distribution, which is the most commonly done activity on the site, it has free tools to simulate events such as flipping coins, shuffling cards, and rolling dice.
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