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On the jitter and entropy of the oscillator-based random source

机译:基于振荡器的随机源的抖动和熵

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True Random Number Generator (TRNG) is a research hotspot recently because it is the main part of many security chips. Random source is considered to be a pillar of TRNG. There are many types of TRNG and oscillator-based random source is widely used on chip. The design of it exploits the random cycle-to-cycle time drift(jitter) in clock of low frequency to produce random bit sequence. Entropy is a basic metric of randomness. In order to increase the randomness of sequence we have to increase the jitter in clock. In this work we propose a method to find the relationship between jitter and the entropy of a bit sequence. First we calculate the possibility of a single bit under the assumption of the normal distribution. Then we give the algorithm of L-bit entropy in the worst case. Finally, we generate a series of bit sequence with different jitters and calculate the entropy with the test of AIS31. Moreover, the paper will also analyze the threshold of the ratio of jitter and period to get a bit sequence with high randomness. From our theory and experimental results, if the ratio is greater than 9.16, the raw sequence has adequate randomness. This threshold is useful to the designers of TRNG.
机译:真正的随机数发生器(TRNG)是最近的研究热点,因为它是许多安全芯片的主要组成部分。随机来源被认为是TRNG的支柱。 TRNG的类型很多,基于振荡器的随机源在芯片上得到了广泛的应用。它的设计利用低频时钟中的随机周期到周期时间漂移(抖动)来产生随机位序列。熵是随机性的基本指标。为了增加序列的随机性,我们必须增加时钟的抖动。在这项工作中,我们提出了一种方法来找到抖动和比特序列的熵之间的关系。首先,我们在正态分布的假设下计算单个比特的可能性。然后给出最坏情况下的L比特熵算法。最后,我们生成一系列具有不同抖动的比特序列,并通过AIS31的测试来计算熵。此外,本文还将分析抖动与周期之比的阈值,以获得具有高随机性的比特序列。根据我们的理论和实验结果,如果比率大于9.16,则原始序列具有足够的随机性。此阈值对于TRNG的设计者很有用。

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