Random Number Generators-Principles and Practices

1 Introduction

1.1 Tools

1.2 Terminology

1.3 The Many Types of Random Numbers

1.3.1 Uniform Random Numbers

2 Random Number Generators

2.1 Classes of Random Number Generators

2.2 Names for RNGs

3 Making Random Numbers

3.1 A Quick Overview of the RNG Types

3.2 The Structure of Full RNG Implementations

3.3 Pool Extractor Structures

3.4 Multiple Input Extractors

4 Physically Uncloneable Functions 21

4.1 The other kind âAS Static vs. Dynamic Random Number Generators .

5 Testing Random Numbers

5.1 Known Answer Tests

5.2 Distinguishing From Random

5.3 PRNG Test Suites

5.4 Entropy Measurements

5.5 Min Entropy Estimation

5.6 Model Equivalence Testing

5.7 Statistical Prerequisite Testing

5.8 The problem Distinguishing Entropy and Pseudo-randomness

5.9 PRNG Tests: DieHarder, NIST SP800-22,TestU01, China ICS 35.040

5.10 Entropy Measurements

5.11 Min Entropy Measurements

5.12 Modeling to Test a Source

5.13 Statistical Prerequisites

5.14 Testing for bias .

5.15 results that are âA too goodâAZ (E.G. Chi-square == 0.5)

5.16 Distinguishing Correlation from Bias

5.17 Testing for Stationary properties

5.18 FFT analysis

5.19 Online Testing

5.20 Working From the Source RNG

5.21 Tools

5.22 Summary

6 Entropy Extraction or Distillation

6.1 A simple extractor, the XOR gate

6.2 A simple way of improving the distribution of random numbers that have known missing

values using XOR

7 Quantifying Entropy

7.1 Rényi Entropy

7.2 Distance From Uniform



Topics to put somewhere in the book- in existing chapters and new chapters

David Johnston, Principal Engineer, Intel Corporation