基于离散时间混沌随机数发生器的改进Logistic映射

Magfirawaty, A. A. Lestari, M. Suryadi, K. Ramli
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引用次数: 2

摘要

本文设计了一种基于离散时间(DT)混沌的随机数发生器(RNG),该发生器在精馏过程中使用一维混沌修正作为确定性函数。一维混沌(1D)是一种简单的动态系统,广泛应用于随机数的生成。我们的工作修改了将应用于基于DT混沌的RNG的逻辑映射。逻辑映射是一种混沌系统,通常应用于密码系统。修正后的确定性方程能够处理实数数据,并能生成正数和负数。通过经验验证,得到阈值为0.718的提取函数,将确定性函数生成的实数转换为具有高熵值的比特序列。通过NIST 800-22随机检验,得到的比特序列的频率检验、累积和检验、秩检验和线性复杂度检验的比例值均在0.9804 ~ 0.9994区间,p值均大于0.01。使用ZedBoard Zynq 7000实现基于DT混沌的RNG方法,所使用的资源数量为LUT=3.9%, FF=1.6%, DSP =12.7%。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Modified Logistic Maps for Discrete Time Chaos Based Random Number Generator
This research designs a discrete time (DT) chaos based random number generator (RNG), which uses one-dimension chaos modification as deterministic function in the destillation process. One-dimensional chaos (1D) is a simple dynamic system, which is widely applied to generate random numbers. Our work modifies logistic map that will be applied as DT chaos-based RNG. The logistic map is a chaotic system that is usually applied in the cryptosystem. The modification performed yields a new deterministic equations, which is capable to process data of real numbers, and generate positive and negative numbers. Through empirical verification the extractor function is obtained with the threshold value=0.718 to convert the real number that is generated by a deterministic function into a sequence of bits which has high entropy value. Through NIST 800-22 randomness test it is revealed that the obtained bit sequences have the proportion values at intervals 0.9804-0.9994 and P-values are greater than 0.01 for the frequency test, the cumulative sums test, the rank test, and a linear complexity test. Implementation of the DT chaos-based RNG method with the our proposed function using ZedBoard Zynq 7000 presents the number of resources used are LUT=3.9%, FF=1.6% and DSP =12.7%.
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