Method for generating pseudo random numbers based on cellular neural network

Li-hua DONG; Guo-li YAO

doi:10.11959/j.issn.1000-436x.2016252

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Method for generating pseudo random numbers based on cellular neural network

Contents Papers | 更新时间：2024-06-05

- Method for generating pseudo random numbers based on cellular neural network
- Journal on Communications Vol. 37, Issue Z1, Pages: 85-91(2016)
- 作者机构：
  
  西安电子科技大学通信工程学院，陕西西安710071
- 作者简介：
- 基金信息：
  
  The National Key Research and Development Program(2016YFB0800601/02/03/04/05)
- DOI：10.11959/j.issn.1000-436x.2016252
  CLC： TN918
- Online First：2016-10，
  
  Published：25 October 2016
- 稿件说明：
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Li-hua DONG, Guo-li YAO. Method for generating pseudo random numbers based on cellular neural network[J]. Journal on Communications, 2016, 37(Z1): 85-91.
DOI：

Li-hua DONG, Guo-li YAO. Method for generating pseudo random numbers based on cellular neural network[J]. Journal on Communications, 2016, 37(Z1): 85-91. DOI： 10.11959/j.issn.1000-436x.2016252.

摘要

为了克服有限精度效应对混沌系统的退化影响，改善所生成随机序列的统计性能，设计了一种新的基于六维CNN（细胞神经网络）的64 bit伪随机数生成方法。在该方法中，通过控制六维CNN在每次迭代过程中的输入输出，改善了混沌退化对随机数的性能影响，同时，通过与Logistic映射所生成的随机序列和可变参数进行异或处理，有效避免了生成序列的重复出现，扩大了密钥空间和输出序列的周期。以新方法设计的PRNG（伪随机数生成器）易于在软件中实现，每次可生成64 bit的伪随机数，生成速率快。测试结果表明，该方法生成的伪随机序列可以完全通过随机数检测标准NIST SP800-22，因而具有很好的随机性，可用于保密通信等信息安全领域。

Abstract

To overcome the degradation characteristics of chaos system due to finite precision effect and improve the sta-tistical performance of the random number

a new method based on 6th-order cellular neural network (CNN) was given to construct a 64-bit pseudo random number generation (PRNG).In the method

the input and output data in every iteration of 6th-order CNN were controlled to improved the performance of the random number affected by chaos degradation.Then the data were XORed with a variable parameter and the random sequences generated by a Logistic map

by which the repeat of generated sequences was avoided

and the period of output sequences and the key space were expended.Be-sides

the new method was easy to be realized in the software and could generate 64 bit random numbers every time

thus has a high generating efficiency.Test results show that the generated random numbers can pass the statistical test suite NIST SP800-22 completely and thus has good randomness.The method can be applied in secure communication and other fields of information security.

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Keywords

references

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