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

✍ Scribed by David Johnston

• Publisher: De|G Press
• Year: 2018
• Tongue: English
• Leaves: 442
• Category: Library

✦ Synopsis

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.

• A practical guide to RNG
• Many examples included

• Written for practicing engineers

✦ Table of Contents

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
15. Making a Uniform Random Number Between Nonpower of Two Bounds
16. Generating Random Prime Numbers
17. Additive Distributions
18. Probability Distributions
19. Quantifying Entropy
20. Random Methods to Generate π
Appendix A. Adaptive Proportion Test Cutoff Tables
Appendix B. High-Precision Incomplete Beta Function Implementation
Appendix C. Incomplete Gamma Function Implementation
Appendix D. Software Tool Sources
Appendix E. Listing Reference
Bibliography
Index