Random Number Generators for Computer Simulation and Cyber Security: Design, Search, Theory, and Application (電腦模擬與網路安全的隨機數生成器：設計、搜尋、理論與應用)
Deng, Lih-Yuan, Kumar, Nirman, Lu, Henry Horng-Shing
相關主題
商品描述
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.
商品描述(中文翻譯)
本書探討隨機數生成器的理論與實踐，這些生成器對於計算機模擬和計算機安全應用非常有用。隨機數在計算中無處不在。它們被用於隨機化算法，以執行抽樣或隨機選擇初始化參數，或進行馬可夫鏈蒙特卡羅（MCMC）方法。它們也被用於計算機安全應用，目的多樣，例如加密細節或身份驗證器。在實際應用中，這些應用所使用的隨機數來自於一個偽隨機序列。這些偽隨機序列是由隨機數生成器（RNGs）生成的。本書討論了這些RNG的基礎理論，這些理論被所有程序員所使用。然而，了解其背後理論的人卻不多。這個主題是一個活躍的研究領域，特別是當生成器用於加密應用時。作者向讀者介紹RNG，如何評估其質量，背後的數學和統計理論，以及如何在任何程式語言中實現這些生成器的詳細資訊。本書討論了使用經典線性生成器的非線性轉換在加密應用中的應用，以及如何優化以提高這些生成器的效率。此外，本書提供了有關RNG的最新研究，包括一類現代高效的RNG，並展示如何尋找具有良好質量的新RNG以及如何對這些RNG進行並行化處理。
作者簡介
Lih-Yuan Deng, PhD, is a Professor in the Department of Mathematical Sciences at the University of Memphis. His research focuses on random number generators and has published several papers on the topic, as well as in other areas of statistics and data science.
Nirman Kumar, PhD, is currently a Consulting Member of Technical Staff at Oracle America, Inc. Prior to this, he was an Assistant Professor of Computer Science at the University of Memphis. His research work has focused on theoretical computer science and machine learning and he has several publications in the areas of computational geometry, randomized algorithms, and machine learning.
Henry Horng-Shing Lu, PhD, is a Professor in the Institute of Statistics at the National Yang Ming Chiao Tung University. His research focuses on statistics, image science, and bioinformatics with publications on related topics for scientific and industrial applications.
Ching-Chi Yang, PhD, is an Assistant Professor in the Department of Mathematical Sciences at the University of Memphis. His research focuses on statistical applications and has published several papers in the areas of statistical dimensional analysis.
作者簡介(中文翻譯)
Lih-Yuan Deng博士是孟菲斯大學數學科學系的教授。他的研究專注於隨機數生成器，並在該主題及其他統計和數據科學領域發表了多篇論文。
Nirman Kumar博士目前是甲骨文美國公司的顧問技術成員。在此之前，他曾擔任孟菲斯大學計算機科學的助理教授。他的研究工作專注於理論計算機科學和機器學習，並在計算幾何、隨機演算法和機器學習等領域發表了多篇論文。
Henry Horng-Shing Lu博士是國立陽明交通大學統計學研究所的教授。他的研究專注於統計學、影像科學和生物資訊學，並在相關主題上發表了針對科學和工業應用的論文。
Ching-Chi Yang博士是孟菲斯大學數學科學系的助理教授。他的研究專注於統計應用，並在統計維度分析領域發表了多篇論文。
