Random Number Generators for Computer Simulation and Cyber Security : Design, Search, Theory, and Application / by Lih-Yuan Deng, Nirman Kumar, Henry Horng-Shing Lu, Ching-Chi Yang.

Format:

Book

Author/Creator:

Deng, Lih-Yuan.

Contributor:

Kumar, Nirman.

Lu, Henry Horng-Shing.

Yang, Ching-Chi.

Series:

Synthesis Lectures on Mathematics & Statistics, 1938-1751

Language:

English

Subjects (All):

Mathematics.

Mathematics--Data processing.

Mathematical statistics--Data processing.

Mathematical statistics.

Statistics.

Computer science--Mathematics.

Computer science.

Discrete mathematics.

Applications of Mathematics.

Computational Mathematics and Numerical Analysis.

Statistics and Computing.

Statistics in Engineering, Physics, Computer Science, Chemistry and Earth Sciences.

Mathematics of Computing.

Discrete Mathematics in Computer Science.

Local Subjects:

Applications of Mathematics.

Computational Mathematics and Numerical Analysis.

Statistics and Computing.

Statistics in Engineering, Physics, Computer Science, Chemistry and Earth Sciences.

Mathematics of Computing.

Discrete Mathematics in Computer Science.

Physical Description:

1 online resource (410 pages)

Edition:

1st ed. 2025.

Place of Publication:

Cham : Springer Nature Switzerland : Imprint: Springer, 2025.

Summary:

This book discusses the theory and practice of random number generators that are useful for computer simulation and computer security applications. Random numbers are ubiquitous in computation. They are used in randomized algorithms to perform sampling or choose randomly initialized parameters or perform Markov Chain Monte Carlo (MCMC). They are also used in computer security applications for various purposes such as cryptographic nuances or in authenticators. In practice, the random numbers used by any of these applications are from a pseudo-random sequence. These pseudo-random sequences are generated by RNGs (random number generators). This book discusses the theory underlying such RNGs, which are used by all programmers. However, few try to understand the theory behind them. This topic is an active area of research, particularly when the generators are used for cryptographic applications. The authors introduce readers to RNGs, how they are judged for quality, the mathematical and statistical theory behind them, as well as provide details on how these can be implemented in any programming language. The book discusses non-linear transformations that use classical linear generators for cryptographic applications and how to optimize to make such generators more efficient. In addition, the book provides up-to-date research on RNGs including a modern class of efficient RNGs and shows how to search for new RNGs with good quality and how to parallelize these RNGs. In summary, this book: Discusses the theoretical basis and intuition of various random number generators without overly detailed proofs Enables readers to design, develop, modify, or experiment with new random number generators Provides comprehensive coverage of random number generation for both simulation and cryptographic applications.

Contents:

Introduction

Classical Random Number Generators for Computer Simulation

Searching for Large Order MRG's

Methods to Improve Basic Generators and Statistical Justifications

Family of Efficient MRGs

Quality Assessment for Random Number Generators

Spectral Test for Judging MRG Quality

Parallel RNG Methods

MRGs with Many Non-zero Terms and its Efficient Implementation

Empirical Tests on RNG

Review of Secure Random Number Generators

Secure RNG for Security Applications

Review of Classical Ciphers

Modern Software and Hardware Stream Ciphers

Design of Secure Random Number Generators

General Design Principle of New Class of Secure RNGs

Specific Classes of Secure and Efficient RNGs

Design and Implementation of R packages.

Notes:

Description based on publisher supplied metadata and other sources.

ISBN:

9783031767227

3031767225

OCLC:

1511109617