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Modified Logistic Maps for Discrete Time Chaos Based Random Number Generator

机译:基于离散时间混沌的随机数生成器的改进Logistic映射

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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%.
机译:本研究设计了一种基于离散时间(DT)混沌的随机数发生器(RNG),该发生器在蒸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,已广泛应用于生成随机数。我们的工作修改了逻辑地图,将其用作基于DT混沌的RNG。逻辑映射是通常在密码系统中应用的混沌系统。进行的修改产生了一个新的确定性方程,该方程能够处理实数数据,并生成正数和负数。通过经验验证,提取器函数获得阈值= 0.718,以将确定性函数生成的实数转换为具有高熵值的位序列。通过NIST 800-22随机性测试,发现所获得的比特序列在0.9804-0.9994间隔内具有比例值,并且对于频率测试,累积和测试,秩测试和线性复杂度,P值均大于0.01。测试。我们使用ZedBoard Zynq 7000提出的功能实现了基于DT混沌的RNG方法,该方法使用的资源数量为LUT = 3.9%,FF = 1.6%和DSP = 12.7%。

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