Randomness testing method of pseudorandom sequence based on packet handling

A technology of randomness detection and pseudo-random sequence, which is applied in the field of randomness detection of pseudo-random sequence, and can solve the problems that affect the detection accuracy and fail to meet the requirements of safety and effectiveness.

Inactive Publication Date: 2010-04-07
XIDIAN UNIV
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  • Abstract
  • Description
  • Claims
  • Application Information

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Problems solved by technology

[0007] 5) The complexity of the sequence, such as linear complexity;
[0010] At present, there are more than 60 kinds of randomness tests for sequences, all of which can only test some properties of randomness, such as the intra-block frequency test, which is used to test whether the proportion of symbols "0" and "1" in the sequence appears Equalization, cumulative sum test to judge whether the maximum offset of the sequence to be checked is too large, matrix rank test is used to test the linear indep

Method used

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  • Randomness testing method of pseudorandom sequence based on packet handling
  • Randomness testing method of pseudorandom sequence based on packet handling
  • Randomness testing method of pseudorandom sequence based on packet handling

Examples

Experimental program
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Effect test

Embodiment 1

[0074] In the first embodiment, the randomness detection of the pseudo-random sequence is performed after the sequence to be tested is grouped and linearly mapped.

[0075] refer to figure 1 and figure 2 , the implementation steps of this example are as follows:

[0076] Step 1, the input length is n=10 8 The sequence to be tested a 1 , a 2 ,...,a n .

[0077] Step 2, take the packet length d=100, set the length to 10 8 The original sequence is divided into length 10 6 100 subgroups of b 1 , b 2 ,...,b 100 ,in 1≤i≤100, record m=10 6 .

[0078] Step 3, group b i (1≤i≤100) respectively use the penetration test method for statistics:

[0079] 1) Take a standard random sequence S, and calculate the standard statistical data DEV=(H 1 , H 2 ,...,H 100 ),in 1≤j≤100, MAX layer j The maximum value of layer tree burning corresponding to the jth ignition method determined by the standard random sequence S, MEAN layer j The average value of layer tree burning cor...

Embodiment 2

[0089] In the second embodiment, the randomness detection of the pseudo-random sequence is carried out after the secondary nonlinear transformation is performed on the sequence to be tested.

[0090] refer to figure 1 and image 3 , the implementation steps of this example are as follows:

[0091] Step 1, the input length is n=1.01×10 8 The sequence to be tested a 1 , a 2 ,...,a n .

[0092] Step 2, take the packet length d=101, and set the length to 1.01×10 8 The original sequence is divided into 10 of length 101 6 small group b 1 , b 2 ,...,b m , record m=10 6 , group each small group b i =(a 101(i-1)+1 , a 101(i-1)+2 ,...,a 101(i-1)+101 ) as a function coefficient into the quadratic nonlinear function f(x 1 , x 2 ,...,x 101 )=x 1 x 2 +x 3 x 4 +...+x 99 x 100 +x 101 , seek c i =f(a 101(i-1)+1 , a 101(i-1)+2 ,...,a 101(i-1)+101 ), i=1, 2, ..., 10 6 , get the length m=10 6 sequence c 1 , c 2 ,...,c m .

[0093] Step 3, for the sequence c afte...

Embodiment 3

[0102] In the third embodiment, the randomness detection of the pseudo-random sequence is performed after the sequence to be tested is voted by a large number.

[0103] refer to figure 1 and Figure 4 , the implementation steps of this example are as follows:

[0104] Step A, the input length is n=1.01×10 8 sequence to be tested a 1 , a 2 ,...,a n .

[0105] Step B, take the packet length d=101, and set the length to 1.01×10 8 The original sequence is divided into 10 of length 101 6 small group b 1 , b 2 ,...,b m , record m=10 6 , for each small group b i =(a 101(i-1)+1 , a 101(i-1)+2 ,...,a 101(i-1)+101 ),begging 1≤i≤m, get a sequence c of length m 1 , c 2 ,...,c m .

[0106] Step C, the sequence c after voting on the large number 1 , c 2 ,...,c m Statistics with penetration testing methods:

[0107] (C1) Take a standard random sequence S, and seek standard data DEV=(H 1 , H 2 ,...,H 100 ),

[0108] in 1≤j≤100. MAX layer j The maximum value o...

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Abstract

The invention discloses a randomness testing method of pseudorandom sequence, belonging to the testing field. The method aims to solve the problem that the testing of randomness characters is limited and unilateral in the existing randomness testing method. The method comprises the following steps: firstly performing grouped linear mapping or grouped cascade linear mapping or odd integer grouped second nonlinear transformation or grouped majority voting or grouped modulo 2 additon to a sequence to be tested to obtain a new sequence after grouping process; then selecting set pair standard sequences for statistics to obtain standard statistics value DEV; counting the new sequences after grouping process to obtain new sequence statistics value dev; then calculating to obtain the biggest distance D between the standard statistics value DEV and the new sequence statistics value dev; and finally comparing the biggest distance D and the distance standard value D epsilon to judge whether the tested sequence satisfy the randomness or not. The testing method of the invention has the advantage of comprehensive testing result, reliable use and effective effect and can be widely used in fields such as measurement and range-finding, spread spectrum communication, radar navigation and data security.

Description

technical field [0001] The invention belongs to the field of signal detection, in particular to a randomness detection method of a pseudo-random sequence, which can be widely used in the fields of distance measurement, spread spectrum communication, software testing, radar navigation, data security and the like. Background technique [0002] The randomness of the pseudo-random sequence generated by the random number generator directly affects the security and effectiveness of the application. Therefore, to judge whether the application is safe and effective, it is necessary to ensure that the randomness of the pseudo-random sequence is good. For pseudo-random Sequence randomness detection has always been a difficult point in sequence randomness detection. To detect whether a sequence has the characteristics of a truly random sequence, it can be detected from several aspects: [0003] 1) periodic characteristics; [0004] 2) The proportion of symbols "0" and "1" in the sequ...

Claims

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Application Information

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IPC IPC(8): H04B1/707H04L25/03H04L25/02
Inventor 马文平刘维博傅佩龙
Owner XIDIAN UNIV
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