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GB/T 32915-2016: Information security technology - Randomness test methods for binary sequence Delivery: 9 seconds. True-PDF full-copy in English & invoice will be downloaded + auto-delivered via email. See step-by-step procedure Status: Valid
Similar standardsGB/T 32915-2016: Information security technology - Randomness test methods for binary sequence---This is an excerpt. Full copy of true-PDF in English version (including equations, symbols, images, flow-chart, tables, and figures etc.), auto-downloaded/delivered in 9 seconds, can be purchased online: https://www.ChineseStandard.net/PDF.aspx/GBT32915-2016GB NATIONAL STANDARD OF THE PEOPLE’S REPUBLIC OF CHINA ICS 35.040 L 80 Information security technology - Randomness test methods for binary sequence Issued on. AUGUST 29, 2016 Implemented on. MARCH 01, 2017 Issued by. General Administration of Quality Supervision Inspection and Quarantine of PRC; Standardization Administration of PRC. Table of ContentsForeword... 5 1 Scope... 6 2 Terms and definitions... 6 3 Symbol... 7 4 Randomness test... 9 5 Random number generator test... 23 Appendix A (Informative) Random test principle... 25 Appendix B (Informative) Randomness test parameter setting table... 35ForewordThis standard was drafted in accordance with the rules given in GB/T 1.1-2009. Please note that some of the contents of this document may involve patents. The issuing organization of this document is not responsible for identifying these patents. This standard was proposed by the National Cryptography Authority. This standard shall be under the jurisdiction of the National Information Security Standardization Technical Committee (SAC/TC 260). Drafting organizations of this standard. National Cryptographic Authority Commercial Password Testing Center, Institute of Software of Chinese Academy of Sciences, Beijing Institute of Information Science and Technology. The main drafters of this standard. Li Dawei, Feng Dengguo, Chen Hua, Zhang Chao, Zhou Yongbin, Dong Fang, Fan Limin, Xu Weiwei, Deng Kaiyong, Luo Peng. Information security technology - Randomness test methods for binary sequence1 ScopeThis standard specifies the randomness test indicators and test methods in commercial password applications. This standard applies to the randomness test of binary sequences generated by random number generators.2 Terms and definitionsThe following terms and definitions apply to this document. 2.1 Binary sequence A bit string consisting of “0” and “1”. 2.2 Random number generator A device or program that produces a random binary sequence. 2.3 Randomness hypothesis When performing randomness test on a binary sequence, first assume that the sequence is random. This assumption is called the original hypothesis or null hypothesis and is recorded as H0.The hypothesis opposite to the null hypothesis, that this sequence is not random, is called the alternative hypothesis, which is denoted as Hα. 2.4 Randomness test A function or process used for binary sequence test to determine whether to accept the randomness null hypothesis. 2.5 Significance level The probability of erroneously determining a random sequence as a non- random sequence in randomness test, which is represented by α.3 SymbolThe following symbols apply to this document. α. Significance level H0.Original hypothesis (null hypothesis) Hα. Alternative hypothesis ε. Sequence to be tested n. Bit length of the sequence to be tested4 Randomness test4.1 Single bit frequency test method 4.1.1 Overview Single-bit frequency test is the most basic test, which is used to detect whether the number of 0 and 1 in a binary sequence are similar. That is, if a binary sequence of length n is known, it is tested whether the sequence has a good 0, 1 balance. 4.1.2 Test procedures The single-bit frequency test procedures are as follows. Step 1.This test converts 0 and 1 in the sequence ε to be tested into -1 and 1, 4.1.3 Result determination The P_value result calculated in 4.1.2 is compared with the significance level α. If P_value ≥ α, the sequence to be tested is deemed to pass the single bit frequency test; otherwise, the sequence to be tested is deemed not to pass the single bit frequency test. 4.2 Block internal frequency test method 4.3 Poker test method 4.3.1 Overview Poker test is used to test whether the number of 2m subsequence types of length m is close. For random sequences, the number of 2m subsequences shall be close. 4.3.3 Result determination The P_value result calculated in 4.3.2 is compared with the significance level α. If P_value ≥ α, the sequence to be tested is deemed to pass the poker test; otherwise, the sequence to be tested is deemed not to pass the poker test. 4.4 Overlapping subsequence test method 4.4.1 Overview For any positive integer m, the binary sequence of length m has 2m types. Overlapping subsequence test divides the sequence to be tested (length n) into n superimposable m-bit subsequences. For a random binary sequence, the probability of occurrence of each mode of the m-bit superimposable subsequence shall be close due to its uniformity. 4.4.3 Result determination Compare the two P_value results calculated in 4.4.2 with the significance level α. If P_value1 ≥ α and P_value2 ≥ α, the sequence to be tested is deemed to pass the overlapping subsequence test. 4.5 Total run number test method 4.5.1 Overview A run is a subsequence in a sequence consisting of consecutive “0” or “1”, and the preamble and successor elements of the subsequence are different from their own elements. The total run number test mainly tests whether the total number of runs in the sequence to be tested obeys the randomness requirements. 4.7 Maximum “1” run test method in block 4.7.1 Overview The maximum “1” run test in the block divides the sequence to be tested into N subsequences of length m, where. The longest “1” run length in each subsequence is counted, and by assigning it to the corresponding set, the randomness of the sequence to be tested is evaluated in accordance with the distribution of the largest 1 run in each subsequence. 4.7.3 Result determination Compare the P_value result calculated in 4.7.2 with the significance level α. If P_value ≥ α, then the sequence to be tested is deemed to pass the largest “1” run test in the block. 4.8 Binary derivation test method 4.8.1 Overview The purpose of the binary derivation test is to determine whether the number of 0 and 1 in the kth binary derivation sequence is close to coincide. 4.8.2 Test procedures The binary derivation test procedures are as follows. Step 1.For the sequence ε, perform XOR operation for the adjacent two bits in the initial sequence to obtain a new sequence ε', that is, ε'i = εi εi + 1. 4.8.3 Result determination Compare the P_value result calculated in 4.8.2 with the significance level α. If P_value ≥ α, the sequence to be tested is deemed to pass the binary derivation test. 4.9 Autocorrelation test method 4.10 Matrix rank test method 4.10.1 Overview Matrix rank test is used to test the linear independence between subsequences of a given length in the sequence to be tested. Construct a matrix from the sequence to be tested, then test the linear independence between the rows or columns of the matrix, the degree of offset of the matrix rank can give an understanding of the amount of linear independence, thereby affecting the evaluation of the randomness of the binary sequence. 4.11 Cumulative sum test methods 4.11.1 Overview The cumulative sum test determine the randomness of the sequence to be tested by determining the maximum offset (between 0) in each subsequence of the sequence to be tested, that is, the comparison between the maximum accumulation and the maximum offset that a random sequence shall have. 4.12 Approximate entropy test method 4.12.1 Overview The approximate entropy test evaluates the randomness by comparing the frequency of the m-bit overlappable subsequence mode with the frequency of the (m+1)-bit overlappable subsequence mode. 4.12.2 Test procedures The approximate entropy test procedures are as follows. 4.12.3 Result determination The P_value result calculated in 4.12.2 is compared to the significance level α. If P_value ≥ α, the sequence to be tested is deemed to pass the approximate entropy test. 4.13 Linear complexity test method 4.13.3 Result determination The P_value result calculated in 4.13.2 is compared to the significance level α. If P_value ≥ α, the sequence to be tested is deemed to pass the linear complexity test. ......Source: Above contents are excerpted from the full-copy PDF -- translated/reviewed by: www.ChineseStandard.net / Wayne Zheng et al. Tips & Frequently Asked Questions:Question 1: How long will the true-PDF of English version of GB/T 32915-2016 be delivered?Answer: The full copy PDF of English version of GB/T 32915-2016 can be downloaded in 9 seconds, and it will also be emailed to you in 9 seconds (double mechanisms to ensure the delivery reliably), with PDF-invoice.Question 2: Can I share the purchased PDF of GB/T 32915-2016_English with my colleagues?Answer: Yes. 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