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  2. Lavarand - Wikipedia

    en.wikipedia.org/wiki/Lavarand

    Lavarand, also known as the Wall of Entropy, is a hardware random number generator designed by Silicon Graphics that worked by taking pictures of the patterns made by the floating material in lava lamps, extracting random data from the pictures, and using the result to seed a pseudorandom number generator. [1]

  3. Blum Blum Shub - Wikipedia

    en.wikipedia.org/wiki/Blum_Blum_Shub

    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 x n+1; the output is commonly either the bit parity of x n+1 or one or more of the least significant bits of x n+1.

  4. List of random number generators - Wikipedia

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

    These approaches combine a pseudo-random number generator (often in the form of a block or stream cipher) with an external source of randomness (e.g., mouse movements, delay between keyboard presses etc.). /dev/random – Unix-like systems; CryptGenRandom – Microsoft Windows; Fortuna

  5. RDRAND - Wikipedia

    en.wikipedia.org/wiki/RdRand

    The random number generator is compliant with security and cryptographic standards such as NIST SP 800-90A, [6] FIPS 140-2, and ANSI X9.82. [1] Intel also requested Cryptography Research Inc. to review the random number generator in 2012, which resulted in the paper Analysis of Intel's Ivy Bridge Digital Random Number Generator .

  6. Pseudorandomness - Wikipedia

    en.wikipedia.org/wiki/Pseudorandomness

    Before modern computing, researchers requiring random numbers would either generate them through various means (dice, cards, roulette wheels, [5] etc.) or use existing random number tables. The first attempt to provide researchers with a ready supply of random digits was in 1927, when the Cambridge University Press published a table of 41,600 ...

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    mail.aol.com

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  8. Applications of randomness - Wikipedia

    en.wikipedia.org/wiki/Applications_of_randomness

    Random numbers have uses in physics such as electronic noise studies, engineering, and operations research. Many methods of statistical analysis, such as the bootstrap method, require random numbers. Monte Carlo methods in physics and computer science require random numbers. Random numbers are often used in parapsychology as a test of precognition.

  9. Randomness test - Wikipedia

    en.wikipedia.org/wiki/Randomness_test

    There have been a fairly small number of different types of (pseudo-)random number generators used in practice. They can be found in the list of random number generators, and have included: Linear congruential generator and Linear-feedback shift register; Generalized Fibonacci generator; Cryptographic generators; Quadratic congruential generator