论文标题
商业随机数生成器的通用美白算法
A universal whitening algorithm for commercial random number generators
论文作者
论文摘要
由于制造偏见和技术缺陷，随机数发生器是不完美的。使用后处理算法将这些缺陷删除，这些算法一般会压缩数据，并且在每种情况下都不起作用。在这项工作中，我们使用n Qubit置换矩阵提出了一种通用的美白算法，以消除商业随机数发生器中没有压缩的不完美。具体而言，我们在几种随机数生成器中及其与加密哈希函数和阻止密码的比较来证明我们的算法在几种随机数发生器中的功效。我们已经在使用ENT随机测试套件评估的几乎所有随机参数方面都取得了进步。在RAW随机数据文件中应用我们的算法后获得的修改后的随机数文件通过两种情况下通过NIST SP 800-22测试。1。原始文件并未通过所有测试。 2。原始文件还通过所有测试。
Random number generators are imperfect due to manufacturing bias and technological imperfections. These imperfections are removed using post-processing algorithms that in general compress the data and do not work in every scenario. In this work, we present a universal whitening algorithm using n-qubit permutation matrices to remove the imperfections in commercial random number generators without compression. Specifically, we demonstrate the efficacy of our algorithm in several categories of random number generators and its comparison with cryptographic hash functions and block ciphers. We have achieved improvement in almost every randomness parameter evaluated using ENT randomness test suite. The modified random number files obtained after the application of our algorithm in the raw random data file pass the NIST SP 800-22 tests in both the cases: 1. The raw file does not pass all the tests. 2. The raw file also passes all the tests.
