Random Number Generators—Principles and Practices: A Guide for Engineers and Programmers

Front Cover
Walter de Gruyter GmbH & Co KG, Sep 10, 2018 - Computers - 439 pages
0 Reviews

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.

 

What people are saying - Write a review

We haven't found any reviews in the usual places.

Contents

1 Introduction
1
2 Entropy Sources
23
3 Entropy Extraction
41
4 Cryptographically Secure Pseudorandom Number Generators
95
5 Nondeterministic Random Number Generators
119
6 Statistically Uniform Noncryptographic PRNGs
123
7 Gaussian or Normally Distributed PRNGs
137
8 Testing Random Numbers
145
15 Making a Uniform Random Number Between Nonpower of Two Bounds
329
16 Generating Random Prime Numbers
337
17 Additive Distributions
345
18 Probability Distributions
349
19 Quantifying Entropy
383
20 Random Methods to Generate π
393
Appendix A Adaptive Proportion Test Cutoff Tables
397
Appendix B HighPrecision Incomplete Beta Function Implementation
403

9 Online Random Number Testing
173
10 SP80022 Distinguishability Tests
199
11 Software Tools
251
12 RdRand and RdSeed Instructions in x86 CPUs
289
13 Accessing RNGs from Software
295
14 FloatingPoint Random Numbers
317
Appendix C Incomplete Gamma Function Implementation
409
Appendix D Software Tool Sources
415
Appendix E Listing Reference
417
Bibliography
421
Index
423
Copyright

Common terms and phrases

About the author (2018)

David Johnston, Principal Engineer, Intel Corporation

Bibliographic information