NIST SP 800-90B IID假设的附加卡方检验

Ju-Sung Kang, Hojoong Park, Yongjin Yeom
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引用次数: 2

摘要

最近,NIST发布了用于随机数生成器熵估计的SP 800-90B的第二稿。它是在熵源的加密模块验证程序(CMVP)框架内进行的。CMVP等官方的评价标准应该有严谨的理论基础作为支撑,从而实现评价过程的可信性和可靠性。对于熵估计的理论背景,在SP 800-90B中假设熵源的分布是未知的,因为我们无法对作为熵源组成部分的噪声源的分布进行适当的假设。在这种情况下,通常使用非参数统计方法。SP 800-90B的测试套件分为两个主要步骤。第一步是确定航迹、IID(独立且同分布)或非IID,第二步是估计给定源的熵。第一步使用置换检验和附加卡方检验对熵源的IID假设进行检验,当第一步的所有检验都通过时,确定给定源为IID。根据给定数据是否被确定为IID或非IID,在第二步中使用不同的估计器进行熵估计。本文主要讨论了附加卡方检验,并从非参数统计方法的角度对其进行了分析。在对二进制和非二进制数据进行独立性检验时,我们发现了自由度的几个缺陷。在此基础上修正了sp800 - 90B的自由度,巩固了sp800 - 90B的理论基础。此外,我们还提供了一些校正自由度的实验结果,表明校正后的测试是更有效的。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
On the Additional Chi-Square Tests for the IID Assumption of NIST SP 800-90B
Recently, NIST has published the second draft of SP 800-90B used for entropy estimations of random number generators. It is conducted within the framework of a cryptographic module validation program (CMVP) for the entropy source. The official evaluation criteria such as CMVP should be supported by rigorous and theoretical foundations so as to achieve the credibility and reliability of the evaluation process. For the theoretical background of the entropy estimation, it is assumed in SP 800-90B that the distribution of the entropy source is unknown since we cannot obtain an appropriate hypothesis about the distribution of the noise source which is a component of the entropy source. In this case, the nonparametric statistical method is commonly used. The test suite of SP 800-90B is divided into two major steps. The first step is to determine the track, IID(independent and identically distributed) or Non-IID, and the second step is to estimate the entropy of the given source. The permutation tests and additional chi-square tests are used to test IID assumption for entropy source in the first step, and when all tests in the first step are passed, the given source is determined as IID. Depending on whether the given data is determined as IID or Non-IID, the entropy estimation is conducted using different estimators in the second step. In this paper, we concentrate on the additional chi-square tests and analyze them from the view point of the nonparametric statistical method. We find out several defects of the degrees of freedom in the tests of independence for binary and non-binary data. We correct the degrees of freedom based on our analysis, and it solidifies the theoretical basis of SP 800- 90B. Furthermore, we provide some experimental results with the corrected degrees of freedom which show that the corrected tests are more effective.
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