Cryptographic pseudo-random numbers in simulation

  • Nick Maclaren
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 809)


A fruitful source of confusion on the Internet is that both cryptologists and statisticians use pseudo-random numbers, but their objectives and constraints are subtly different. This paper will describe some of the requirements for a good generator for statistical simulations, and attempt to put them into cryptological terms.

It is important to note that there is no consensus on when a pseudo-random number generator can be regarded as adequate, both because the theory is very incomplete and because so many different fields are involved. Every journal that includes work on either cryptology or statistical methods is likely to include important papers, and no worker in the field is familiar with the whole literature. Broad agreement on criteria is the best that can be expected.


Random Number Generator Differential Cryptanalysis Fruitful Source Random Uniformity Spectral Test 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer-Verlag Berlin Heidelberg 1994

Authors and Affiliations

  • Nick Maclaren
    • 1
  1. 1.University of Cambridge Computer LaboratoryCambridge

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