Random number generators - principles and practices : a guide for engineers and programmers / David Johnston.

By:

Johnston, David [author.]

Material type: Text

TextPublisher: Berlin ; Boston : Walter de Gruyter GmbH, [2018]Description: 1 online resource (xvi, 424 pages)Content type:

text

Media type:

computer

Carrier type:

online resource

ISBN:

9781501506062
1501506064
9781501506260
1501506269

Subject(s): Genre/Form:

Electronic books.

Additional physical formats: Print version:: Random Number Generators : Principles and Practice - A Guide for Engineers and Programmers.DDC classification:

004.01/51 23

LOC classification:

QA76.5 .J64 2018

Online resources:

Click here to access online

Contents:

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.

Summary: 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.

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Holdings
Item type	Home library	Collection	Call number	Materials specified	Status	Date due	Barcode
Electronic-Books	OPJGU Sonepat- Campus	E-Books EBSCO			Available

Includes bibliographical references and index.

880-01 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.

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.

Online resource; title from digital title page (viewed on October 22, 2018).

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