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On the Generation of Random Numbers for Symmetric Cryptography utilizing Astronomical Data

机译:在利用天文数据的对称密码学的生成

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In this paper, a novel method for obtaining the random numbers utilizing astronomical data is proposed. The method uses two different algorithms for generation of random numbers sequence. Astronomical data collected from the scientific study of the universe, especially of the relative motions, relative positions of astronomical objects are utilized in our algorithms. The first algorithm uses a particular astronomical object in a fixed position for the random number generation. The random sequence is obtained from the relative positions of other astronomical objects with reference to the selected object. The second algorithm selects any diverse astronomical object as a reference in a varying mode for computation of the relative positions of different objects with that reference to generate the random number stream. Both algorithms use mathematical equations for computing the next jump or hop to the other astronomical object. The generated random numbers obtained from the two algorithms are tested with a standard statistical test suite including, frequency test, run test, random binary matrix rank test, complexity test, universal test and entropy test. The results obtained from the statistical tests of the two algorithms are compared with the other publicly available random number generation techniques, like, linear congruential and modular exponentiation. The preliminary results show that the algorithms perform well. The random numbers generated by our method has sufficient period and unpredictability that makes them suitable for consideration as encryption keys in symmetric cryptography.
机译:本文提出了一种利用天文数据的获取随机数的新方法。该方法使用两个不同的算法来产生随机数序列。从宇宙的科学研究中收集的天文数据,特别是对天文对象的相对位置在我们的算法中使用。第一算法使用特定的天文对象在固定位置的用于随机数生成。随机序列从其他天文对象的相对位置参考所选择的对象获得。第二算法选择任何不同的天文对象作为不同模式的参考,用于计算不同对象的相对位置,以产生随机数流。这两种算法都使用数学方程来计算下一个跳转或跳到其他天文对象。使用标准统计测试套件测试了从两种算法获得的产生的随机数,包括频率测试,运行测试,随机二进制矩阵等级测试,复杂性测试,通用测试和熵测试。从两种算法的统计测试获得的结果与其他公共可用的随机数生成技术进行比较,如,线性总体和模块化指数。初步结果表明该算法表现良好。由我们的方法生成的随机数具有足够的时期和不可预测性,使得它们适合考虑对称密码中的加密密钥。

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