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Pseudo-Random Number Generator Based on Logistic Chaotic System

机译:基于逻辑混沌系统的伪随机数生成器

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In recent years, a chaotic system is considered as an important pseudo-random source to pseudo-random number generators (PRNGs). This paper proposes a PRNG based on a modified logistic chaotic system. This chaotic system with fixed system parameters is convergent and its chaotic behavior is analyzed and proved. In order to improve the complexity and randomness of modified PRNGs, the chaotic system parameter denoted by floating point numbers generated by the chaotic system is confused and rearranged to increase its key space and reduce the possibility of an exhaustive attack. It is hard to speculate on the pseudo-random number by chaotic behavior because there is no statistical characteristics and infer the pseudo-random number generated by chaotic behavior. The system parameters of the next chaotic system are related to the chaotic values generated by the previous ones, which makes the PRNG generate enough results. By confusing and rearranging the output sequence, the system parameters of the previous time cannot be gotten from the next time which ensures the security. The analysis shows that the pseudo-random sequence generated by this method has perfect randomness, cryptographic properties and can pass the statistical tests.
机译:近年来,混沌系统被视为伪随机数生成器(PRNG)的重要伪随机源。提出了一种基于改进的逻辑混沌系统的PRNG。该具有固定系统参数的混沌系统是收敛的,并对其混沌行为进行了分析和证明。为了提高修改后的PRNG的复杂度和随机性,将混沌系统生成的浮点数表示的混沌系统参数进行混淆和重新排列,以增加其密钥空间并减少穷举攻击的可能性。很难通过混沌行为来推测伪随机数,因为它没有统计特征并且无法推断出由混沌行为产生的伪随机数。下一个混沌系统的系统参数与前一个混沌系统产生的混沌值有关,这使得PRNG产生了足够的结果。通过混淆和重新排列输出顺序,无法从下一次获得上一次的系统参数,从而确保了安全性。分析表明,该方法生成的伪随机序列具有很好的随机性,密码学性质,可以通过统计检验。

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