Johnston D. Random number generators - principles and practices: a guide for engineers and programmers

Berlin: Walter de Gruyter GmbH, 2018. — 436 p. — ISBN: 978-1-5015-0606-2.Random Number Generators, Principles and Practices has been written for programmers, hardware engineers, and sophisticated hobbyists interested in understanding random numbers generators and gaining the tools necessary to work with random number generators with confidence and knowledge. Using an approach that employs clear diagrams and running code examples rather than excessive mathematics, random number related topics such as entropy estimation, entropy extraction, entropy sources, PRNGs, randomness testing, distribution generation, and many others are exposed and demystified. If you have ever Wondered how to test if data is really random Needed to measure the randomness of data in real time as it is generated Wondered how to get randomness into your programs Wondered whether or not a random number generator is trustworthy Wanted to be able to choose between random number generator solutions Needed to turn uniform random data into a different distribution Needed to ensure the random numbers from your computer will work for your cryptographic application Wanted to combine more than one random number generator to increase reliability or security Wanted to get random numbers in a floating point format Needed to verify that a random number generator meets the requirements of a published standard like SP800-90 or AIS 31 Needed to choose between an LCG, PCG or XorShift algorithm Then this might be the book for you. Read more...About De/G PRESSEntropy Sources
Entropy Extraction
Cryptographically Secure Pseudorandom Number Generators
Nondeterministic Random Number Generators
Statistically Uniform Noncryptographic PRNGs
Gaussian or Normally Distributed PRNGs
Testing Random Numbers
Online Random Number Testing
SP800-22 Distinguishability Tests
Software Tools
RdRand and RdSeed Instructions in x86 CPUs
Accessing RNGs from Software
Floating-Point Random Numbers.