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
Reviews aren't verified, but Google checks for and removes fake content when it's identified

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.

Selected pages

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

Other editions - View all

Random Number Generators--Principles and Practices: A Guide for Engineers ...
David Johnston,His Excellency the Right Honourable David Johnston
Limited preview - 2018
Random Number Generators--Principles and Practices: A Guide for Engineers ...
David Johnston
No preview available - 2018

Common terms and phrases

algorithm bias biased binary binomial block block cipher bytes CBC-MAC circuit Compute count CPUID CPUs cryptographic CTR DRBG debiaser dieharder distribution djen djenrandom djent elif entropy extractor entropy source equation error error_prob example exponent filename floating-point frequency full entropy gamma function hash histogram HMAC implementation import math import random incomplete beta function incomplete gamma function integer Intel Iteration Listing loop mantissa matrix Metastable min-entropy multiple NIST nondeterministic normal number of bits ofthe online health test p_input pattern prime PRNG prob probability quantile function random bits random data random numbers random walk range RdRand RdSeed Rényi entropy result Ring Oscillator Salsa20 seed sequence serial correlation Serial correlation coefficient Shannon entropy specification statistical step symbol Table uint 32_t uint64_t uniform random update usr/bin/env python import voltage xrange Ziggurat algorithm

About the author (2018)

David Johnston, Principal Engineer, Intel Corporation

Bibliographic information

QR code for Random Number Generators—Principles and Practices
TitleRandom Number Generators—Principles and Practices: A Guide for Engineers and Programmers
AuthorDavid Johnston
Editionillustrated
PublisherWalter de Gruyter GmbH & Co KG, 2018
ISBN1501506064, 9781501506062
Length439 pages
Subjects ›  › 

Computers / Programming / Algorithms
Computers / Security / Cryptography & Encryption
Computers / Software Development & Engineering / Quality Assurance & Testing
Mathematics / General
Mathematics / Numerical Analysis
  
Export CitationBiBTeX EndNote RefMan