US Department of Commerce-National Institute of Standards and Technology (1994). “A universal statistical test for random bit generators.” Journal of Cryptology, 5 (2), 89–105. Computer Science and Information Processing, Vol. “How to protect data with ciphers that are really hard to break.” Electronics, 46, 99–101. “On the security of random sources.” Proceedings of PKC'99, Lecture Notes in Computer Science, vol. Pseudo-random generators aimed for cryptographic applications must not be confused with those used for most other purposes (simulations, probabilistic algorithms. This property makes PRNGs suitable for use as stream ciphers. It is important to note that a PRNG is a deterministic process: put back in the same state, it will reproduce the same sequence, as will two PRNGs initialized with the same seed.
One possible method for such generation is to use a pseudo-random numbers generator.Ī pseudo-random number generator (PRNG) is a function that, once initialized with some random value (called the seed), outputs a sequence that appears random, in the sense that an observer who does not know the value of the seed cannot distinguish the output from that of a (true) random bit generator. However, generating random values on a computer is in fact a very difficult task. Many cryptographic primitives require random numbers, to be used as keys, challenges, unique identifiers, etc.
