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  2. Fortuna (PRNG) - Wikipedia

    en.wikipedia.org/wiki/Fortuna_(PRNG)

    With a 128-bit block cipher, this would produce statistically identifiable deviations from randomness; for instance, generating 2 64 genuinely random 128-bit blocks would produce on average about one pair of identical blocks, but there are no repeated blocks at all among the first 2 128 produced by a 128-bit cipher in counter mode.

  3. Ghost leg - Wikipedia

    en.wikipedia.org/wiki/Ghost_Leg

    The actors' names would go on top, and the roles on the bottom. Then, vertical lines are drawn connecting each actor with the role directly below it. The names of the actors or roles are then concealed so that people do not know which actor is on which line, or which role is on which line. Next, each actor adds a leg to the board.

  4. List of random number generators - Wikipedia

    en.wikipedia.org/wiki/List_of_random_number...

    Default generator in R and the Python language starting from version 2.3. Xorshift: 2003 G. Marsaglia [26] It is a very fast sub-type of LFSR generators. Marsaglia also suggested as an improvement the xorwow generator, in which the output of a xorshift generator is added with a Weyl sequence.

  5. ISAAC (cipher) - Wikipedia

    en.wikipedia.org/wiki/ISAAC_(cipher)

    ISAAC (indirection, shift, accumulate, add, and count) is a cryptographically secure pseudorandom number generator and a stream cipher designed by Robert J. Jenkins Jr. in 1993. [1] The reference implementation source code was dedicated to the public domain. [2] "I developed (...) tests to break a generator, and I developed the generator to ...

  6. Mersenne Twister - Wikipedia

    en.wikipedia.org/wiki/Mersenne_Twister

    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.

  7. Pseudorandom number generator - Wikipedia

    en.wikipedia.org/wiki/Pseudorandom_number_generator

    It can be shown that if is a pseudo-random number generator for the uniform distribution on (,) and if is the CDF of some given probability distribution , then is a pseudo-random number generator for , where : (,) is the percentile of , i.e. ():= {: ()}. Intuitively, an arbitrary distribution can be simulated from a simulation of the standard ...

  8. ACORN (random number generator) - Wikipedia

    en.wikipedia.org/.../ACORN_(random_number_generator)

    In 1992, further results were published, [11] implementing the ACORN Pseudo-Random Number Generator in exact integer arithmetic which ensures reproducibility across different platforms and languages, and stating that for arbitrary real-precision arithmetic it is possible to prove convergence of the ACORN sequence to k-distributed as the ...

  9. Key generation - Wikipedia

    en.wikipedia.org/wiki/Key_generation

    A PRNG is a computer algorithm that produces data that appears random under analysis. PRNGs that use system entropy to seed data generally produce better results, since this makes the initial conditions of the PRNG much more difficult for an attacker to guess.