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Testing for Randomness in Pseudo Random Number Generators Algorithms in a Cryptographic Application

机译:密码学应用中的伪随机数生成器算法中的随机性测试

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The most effective cryptographic algorithm has more randomness in the numbers a generator generates, and the more secured it is to be used for protecting confidential data. Sometimes developers find it difficult to determine which Random Number Generators (RNGs) can provide a much secured Cryptographic System for secured enterprise application implementations. This research aims to find an effective Pseudo Random Number Generator algorithm among Fibonacci Random Numbers Generator Algorithms, Gaussian Random Numbers Generator Algorithm, Specific Range Random Numbers Generator Algorithms, and Secure Random numbers Generators, which are the most common Pseudo Random Numbers Generators Algorithms, that can be used to improve the security of Cryptographic software systems. The researchers employed Chi-Square test on the first 100 random numbers between 0 to 1000 generated using the above generators and it concluded that, Fibonacci Random Numbers Generator Algorithms can provide a more secured cryptographic application. Keywords Pseudo Random Number Generators, Randomness, Cryptography, Software.
机译:最有效的密码算法在生成器生成的数字中具有更大的随机性,并且将更安全地用于保护机密数据。有时,开发人员发现很难确定哪些随机数生成器(RNG)可以为安全的企业应用程序实现提供高度安全的加密系统。本研究旨在在斐波那契随机数生成器算法,高斯随机数生成器算法,特定范围随机数生成器算法和安全随机数生成器(这是最常见的伪随机数生成器算法)中找到一种有效的伪随机数生成器算法。可用于提高密码软件系统的安全性。研究人员对使用上述生成器生成的0到1000之间的前100个随机数进行了卡方检验,得出的结论是,斐波那契随机数生成器算法可以提供更安全的加密应用。伪随机数发生器,随机性,密码学,软件。

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