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

Description

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... Intro About De/G PRESS Contents Preface 1. Introduction 2. Entropy Sources 3. Entropy Extraction 4. Cryptographically Secure Pseudorandom Number Generators 5. Nondeterministic Random Number Generators 6. Statistically Uniform Noncryptographic PRNGs 7. Gaussian or Normally Distributed PRNGs 8. Testing Random Numbers 9. Online Random Number Testing 10. SP800-22 Distinguishability Tests 11. Software Tools 12. RdRand and RdSeed Instructions in x86 CPUs 13. Accessing RNGs from Software 14. Floating-Point Random Numbers.