一个简单易懂的伪随机数生成器和特定的安全模型指南

IF 11 Q1 STATISTICS & PROBABILITY Statistics Surveys Pub Date : 2022-01-01 DOI:10.1214/22-ss136
Elena Almaraz Luengo
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引用次数: 1

摘要

随机序列的生成是模拟的基础,可用于许多不同的领域,如统计学、计算机科学、系统管理与控制、生物学、粒子物理学、密码学或网络安全等。至关重要的是,生成的数字是随机的,或者至少表现为随机的。这些序列所要求的基本统计性质是随机性和独立性,从密码学的角度来看,是不可预测性。有多种方法可以生成这些序列。主要有物理方法和算术方法。本文对主要的算法进行了详细的研究。另一方面,将分析安全序列生成的必要性,并描述正在进行的新研究方向,以引起物联网应用和新的发生器设计。
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A brief and understandable guide to pseudo-random number generators and specific models for security
: The generation of random sequences is the basis of simulation and can be used in many different areas such as Statistics, Computer Science, Systems Management and Control, Biology, Particle Physics, Cryp- tography or Cyber-Security, among others. It is crucial that the numbers generated were random or at least, behave as such. The fundamental sta- tistical properties required for such sequences are randomness and independence and, from a cryptographic perspective, unpredictability. There is a variety of methods to generate these sequences. The main ones are physical and arithmetic methods. In this work, a detailed study of the main arith- metic methods is carried out. On the other hand, the necessity of secure sequence generation will be analyzed and new lines of ongoing research fo- cusing applications in Internet of Things and new generator designs will be described.
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来源期刊
Statistics Surveys
Statistics Surveys STATISTICS & PROBABILITY-
CiteScore
11.70
自引率
0.00%
发文量
5
期刊介绍: Statistics Surveys publishes survey articles in theoretical, computational, and applied statistics. The style of articles may range from reviews of recent research to graduate textbook exposition. Articles may be broad or narrow in scope. The essential requirements are a well specified topic and target audience, together with clear exposition. Statistics Surveys is sponsored by the American Statistical Association, the Bernoulli Society, the Institute of Mathematical Statistics, and by the Statistical Society of Canada.
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