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An MWC generator is a special form of Lehmer random number generator = which allows efficient implementation of a prime modulus much larger than the machine word size. Normal Lehmer generator implementations choose a modulus close to the machine word size.
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 ...
Cryptographic attacks that subvert or exploit weaknesses in this process are known as random number generator attacks. A high quality random number generation (RNG) process is almost always required for security, and lack of quality generally provides attack vulnerabilities and so leads to lack of security, even to complete compromise, in ...
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
When the maximum number of bits output from this PRNG is equal to the 2 blocksize, the resulting output delivers the mathematically expected security level that the key size would be expected to generate, but the output is shown to not be indistinguishable from a true random number generator. [24] When the maximum number of bits output from ...
Fortuna is a cryptographically secure pseudorandom number generator (CS-PRNG) devised by Bruce Schneier and Niels Ferguson and published in 2003. It is named after Fortuna, the Roman goddess of chance. FreeBSD uses Fortuna for /dev/random and /dev/urandom is symbolically linked to it since FreeBSD 11. [1] Apple OSes have switched to Fortuna ...
Dual_EC_DRBG (Dual Elliptic Curve Deterministic Random Bit Generator) [1] is an algorithm that was presented as a cryptographically secure pseudorandom number generator (CSPRNG) using methods in elliptic curve cryptography.
If one has a pseudo-random number generator whose output is "sufficiently difficult" to predict, one can generate true random numbers to use as the initial value (i.e., the seed), and then use the pseudo-random number generator to produce numbers for use in cryptographic applications.