A General Method to Evaluate the Correlation of Randomness Tests

Fan, Li; Chen, Hua; Gao, Si

doi:10.1007/978-3-319-05149-9_4

Cited by 18 publications

(21 citation statements)

References 3 publications

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“…Previous studies [23,24] showed that the correlation between the frequency and matrix tests is R = 0.025 < 0.2, showing some dependency or relevance. Therefore, the method of combining the frequency and matrix tests not only will not affect the correlation of test results, but also will make the test more convincing and more efficient.…”

Section: Randomness Tests Methods Of Zigbee Protocol Based On the Mmentioning

confidence: 96%

A Randomness Detection Method of ZigBee Protocol in a Wireless Sensor Network

Tang

Lian

et al. 2018

Sensors

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This study investigates the randomness detection of cryptographic algorithms in network security. To effectively test and verify the security of ZigBee protocol in the Internet of Things, the study combines with the characteristics of ZigBee networks, and it rationally organizes and divides test modes based on the binary matrix rank theory test. Then this paper proposes a randomness detection method of ZigBee protocol in a wireless sensor network. The proposed method solves the one-sidedness that the binary matrix rank test simply assesses random sequences by linear correlation. The proposed assessment method can effectively appraise whether the ZigBee protocol has an encryption mechanism and encryption strength. Simulation results show that this method has the characteristics of fewer errors and high reliability.

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Section: Randomness Tests Methods Of Zigbee Protocol Based On the Mmentioning

confidence: 96%

A Randomness Detection Method of ZigBee Protocol in a Wireless Sensor Network

Tang

Lian

et al. 2018

Sensors

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“…In a similar way, correlation is defined by examining at the distribution of a test's results in the region where the other test's results are lower than 0.01 [11]. Another method is defined by Fan et al [12]. In this method, firstly P-values are calculated by using two different sets.…”

Section: Correlationmentioning

confidence: 99%

Mutual correlation of NIST statistical randomness tests and comparison of their sensitivities on transformed sequences

Doğanaksoy¹,

Sulak²,

Uğuz³

et al. 2017

Turk J Elec Eng & Comp Sci

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In addition, we define five new methods for transforming a sequence. Our motivation is to detect those tests whose results are invariant under a certain transformation. To observe the correlation, we use two methods. One is the direct correlation between the tests and the other is the correlation between the results of a test on the sequence and its transformed form. In light of the observations, we conclude that some of the tests are correlated with each other.Furthermore, we conclude that in designing a reliable and efficient suite we can avoid overpopulating the list of test functions by employing transformations together with a reasonable number of statistical test functions.

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“…Huang and Lai [13] used the conditional entropy to construct a quantitative value for comparing the tests and proposed a basic method on how to determine the tests' optimal execution order. In [14], Fan et al gave a general hypothesis testing method to evaluate the correlation of statistical tests. And in [15], Sulak et al defined the coverage efficiency of a test suite which is used to determine the most efficient, the least efficient, and the optimal subsuites of the NIST SP800-22 test suite.…”

Section: Introductionmentioning

confidence: 99%

“…As the DFT computation is time-consuming and the time complexity is nonlinear, the test time will significantly increase along with the sequence length and the sequence number, which is unsuitable for some practical application scenarios, such as fast test of very long sequences on ordinary computers. Although the studies [13][14][15] for test items' correlations could reduce the test time by appropriately selecting partial test items, instead of performing the whole test items, they cannot fundamentally improve the test efficiency of any specific test item, including the DFT test. Third, the DFT algorithm requires high memory consumptions, previous DFT test methods have a high possibility to crash for long sequence test, due to the memory limitations of ordinary computers.…”

Section: Introductionmentioning

confidence: 99%