LYCOS RETRIEVER 
Pseudorandom Number Generator: Random Number Generators
built 783 days ago
Generator: [G]sl_rng_uni32 This is a reimplementation of the 16-bit SLATEC random number generator RUNIF. A generalisation of the generator to 32 bits is provided by gsl_rng_uni32. The original source code is available from NETLIB.
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RngPack is a pseudorandom number generator package for Java. Pseudorandom means that the "random" numbers are generated by a deterministic mathematical process, not by a fundamentally random physical process such as radioactive decay or Johnson noise. RngPack contains base classes that add value to random number generators, four research grade generators, as well as a wrapper for Java's built in random number generator and a demonstration application. RngPack comes with java class documentation. Because RngPack is a set of Java classes it can be used in both applications and in applets. RngPack is available under the BSD License.
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Pseudo Random Number Generator is a software that generate a so called Random Number based on some algorithm. Actually it is not a real random number but a Pseudo Random Number. Ultimately Pseudo Random Number remain predictable to one degree or another. And the random number generator is a pseudo random number generator.
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A pseudorandom number generator (PRNG) is an algorithm to generate a sequence of numbers that approximate the properties of random numbers. The sequence is not truly random in that it is completely determined by a relatively small set of initial values, called the PRNG's state. Although sequences that are closer to truly random can be generated using hardware random number generators, pseudo-random numbers are important in practice for simulations (e.g., of physical systems with the Monte Carlo method), and are central in the practice of cryptography.
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A good random number generator will satisfy both theoretical and statistical properties. Theoretical properties are often hard to obtain (they require real math!), but one prefers a random number generator with a long period, low serial correlation, and a tendency not to "fall mainly on the planes." Statistical tests are performed with numerical simulations. Generally, a random number generator is used to estimate some quantity for which the theory of probability provides an exact answer. Comparison to this exact answer provides a measure of "randomness".
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The Blum Blum Shub (BBS) random number generator is a provably secure pseudorandom number generator. See this paper for reference about its necessity and references to formal proof of its cryptographic strength.
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Random Number Generators