CN102520908A - Pseudo-random number generator and pseudo-random number generating method - Google Patents
Pseudo-random number generator and pseudo-random number generating method Download PDFInfo
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Abstract
The invention discloses a pseudo-random number generator and a pseudo-random number generating method. High-quality pseudo-random numbers are efficiently generated according to hyperbolic square algorithm, and the pseudo-random number generator comprises an odd and even digit judgment module, a square processing module and a hyperbolic processing module, wherein the odd and even digit judgment module is used for judging whether a current pseudo-random number ai is an odd number or an even number, transmitting the current pseudo-random number into the square processing module if the current pseudo-random number is the even number, and transmitting the current pseudo-random number into the hyperbolic processing module if the current pseudo-random number is the odd number, the square processing module is used for generating a next pseudo-random number ai+1 for the current pseudo-random number ai according to the square algorithm, and the hyperbolic processing module is used for generating a next pseudo-random number ai+1 for the current pseudo-random number ai according to the hyperbolic algorithm. Furthermore, overflow handling can be performed for the pseudo-random numbers in overflow. The hyperbolic square algorithm is small in occupied space and fast in execution speed, and the pseudo-random numbers generated by the pseudo-random number generator are better in randomness and can meet the higher and higher requirement on randomness of pseudo-random numbers at present.
Description
Technical field
The present invention relates to data-signal generation technique field, relate in particular to a kind of PRNG and pseudo-random number generation method.
Background technology
Pseudo random number has a wide range of applications in fields such as computer software, hardware, safety, thereby the pseudo random number of generation high-efficiency high-quality (being that randomness is high) becomes extremely important.The scheme of current generation pseudo random number is the pseudorandom number generator generation through the module exponent definition.In the pseudo random number generative process, need data to be asked the n power always, and preserve data in order.The data of utilizing this existing method to produce, its length is changeable, waits destruction pseudo random number data Quality but occur easily following.In general, existing pseudo random number generates the pseudo random number that scheme produced, and it is big to take up room, and efficient is low, and the randomness of the data that produce is also not high enough, can not satisfy in the current practical application the increasingly high requirement of randomness.
Therefore, how to generate high-quality pseudo random number efficiently and become a current problem that needs solution.
Summary of the invention
Technical matters to be solved by this invention is; A kind of PRNG and pseudo-random number generation method are provided; Be used to overcome the low and second-rate defective of current pseudo random number formation efficiency, solve the technical matters that how to realize generating efficiently the high-quality pseudo random number.
In order to address the above problem, the present invention proposes a kind of PRNG, comprising:
The odd even judge module is used to judge current pseudo random number a
iBe odd number or even number, if even number is then sent current pseudo random number into a square processing module, if odd number is then sent current pseudo random number into the hyperbolic processing module;
Said square of processing module is used for current pseudo random number a
iGenerate next pseudo random number a according to square algorithm
I+1
Said hyperbolic processing module is used for current pseudo random number a
iGenerate next pseudo random number a according to the hyperbolic algorithm
I+1
Wherein, said square of processing module is at a
iWhen being even number, when carrying out square handling, make a
I+1=S (a
i) obtain new pseudo random number a
I+1Wherein, function S (x)=x
2Mod p; P is a prime number.
Wherein, said hyperbolic processing module is at a
iWhen being odd number, when carrying out the hyperbolic processing, make a
I+1=T (a
i) obtain new pseudo random number a
I+1Wherein, function T (x)=(x-x
-1) mod p; P is a prime number.
The present invention also provides a kind of PRNG, comprising:
Parameter input module is used to dispose initial parameter and initial pseudorandom is counted a
0
The odd even judge module is used to judge current pseudo random number a
iBe odd number or even number, if even number is then sent current pseudo random number into a square processing module, if odd number is then sent current pseudo random number into the hyperbolic processing module;
Said square of processing module is used for current pseudo random number a
iGenerate next pseudo random number a according to square algorithm
I+1Export the counting judge module to;
Said hyperbolic processing module is used for current pseudo random number a
iGenerate next pseudo random number a according to the hyperbolic algorithm
I+1Export the counting judge module to;
Said counting judge module is used to receive next pseudo random number a
I+1, count value i is added 1 increase progressively and make i=i+1, square handle or hyperbolic is handled the pseudo random number a of back gained utilizing
I+1As current pseudo random number a
i, judge current count value i whether greater than preset counting thresholding L, if the count value after increasing progressively is greater than preset counting thresholding, i.e. i＞L then jumps to and overflows processing module and handle, otherwise, with current pseudo random number a
iSend to output module;
Overflow processing module, be used for when i＞L, pseudo random number a
iOverflow processing, make a
i=(a
i-a
I-L) mod p, with a
iExport output module to as pseudo random number;
Said output module is used for the externally newly-generated pseudo random number a of output on the one hand
i, on the other hand with newly-generated pseudo random number a
iReach current count value i and feed back to the odd even judge module, be used for continuing to generate next pseudo random number.
Wherein, comprising of said parameter input module configuration initial parameter: a big prime number p, one is used to limit initial a
0The Integer N of length; An integer L is used for as count value i being carried out the threshold value that size is judged; Said initial pseudorandom is counted a
0Be the big number of a non-trivial (nonuniform), i.e. count value i=0.
Wherein, said square of processing module is at a
iWhen being even number, when carrying out square handling, make a
I+1=S (a
i); Wherein, function S (x)=x
2Mod p; P is a prime number.
Wherein, said hyperbolic processing module is at a
iWhen being odd number, when carrying out the hyperbolic processing, make a
I+1=T (a
i); Wherein, function T (x)=(x-x
-1) mod p; P is a prime number.
The present invention also provides a kind of generation method of pseudo random number, comprising:
At first, confirm that initial parameter and initial pseudorandom count a
0
Then, judge current pseudo random number a
iBe odd number or even number: if even number, then to current pseudo random number a
iGenerate next pseudo random number a according to square algorithm
I+1If odd number is then to current pseudo random number a
iGenerate next pseudo random number a according to the hyperbolic algorithm
I+1
Afterwards, make i=i+1, with utilizing square processing or hyperbolic to handle the pseudo random number a of back gained
I+1As current pseudo random number a
iJudge count value i increase progressively after whether greater than the counting thresholding L that sets:
If i＞L then makes a
i=(a
i-a
I-L) mod p, p is a prime number, with a
iExport as pseudo random number; Otherwise directly output utilizes square processing or hyperbolic to handle the newly-generated pseudo random number a in back
i
At last, externally export newly-generated pseudo random number a on the one hand
i, on the other hand with newly-generated pseudo random number a
iAnd current count value i feeds back to current pseudo random number a
iCarry out the step that odd even is judged, continue to carry out and utilize square processing or hyperbolic to handle the flow process that generates pseudo random number.
Wherein, if judge current pseudo random number a
iBe even number, then to current pseudo random number a
iGenerate next pseudo random number a according to square algorithm
I+1, generating mode is:
Make a
I+1=S (a
i); Wherein, S (x)=x
2Mod p.
Wherein, if judge current pseudo random number a
iBe odd number, then to current pseudo random number a
iGenerate next pseudo random number a according to the hyperbolic algorithm
I+1, generating mode is:
Make a
I+1=T (a
i); Wherein, T (x)=(x-x
-1) mod p.
PRNG of the present invention and pseudo-random number generation method, the hyperbolic square algorithm of employing innovative design, this hyperbolic square algorithm occupies little space, and execution speed is fast, can efficiently produce pseudo random number, and formation speed is faster, more can satisfy practical requirement.And it is better to use the pseudo random number randomness that the present invention produced, and can satisfy current to the increasingly high requirement of random number randomness.
Description of drawings
Fig. 1 is the structured flowchart of PRNG;
Fig. 2 is the process flow diagram of pseudo-random number generation method;
Fig. 3 is the structured flowchart of the PRNG of another kind of designs simplification.
Embodiment
For making the object of the invention, technical scheme and advantage clearer, the present invention is done to specify further below in conjunction with accompanying drawing.
The present invention is based on the deep research in Galois field field; A kind of PRNG and pseudo-random number generation method have been proposed; Adopt the hyperbolic square algorithm when generating pseudo random number; The pseudo random number of high-quality can be produced efficiently, the problem of low and its quality of randomness difference of generation pseudo random number efficient that existing method exists can be solved.Test shows, the hyperbolic square algorithm of the generation high-quality pseudo random number of this innovative design can efficiently produce the pseudo random number of high-quality.
The core of hyperbolic square algorithm can be decomposed into two subalgorithms:
(1) square algorithm: S (x)=x
2Mod p
(2) hyperbolic algorithm: T (x)=(x-x
-1) mod p
Wherein, Mod is the computing that rems, and p is arbitrarily big prime number.
x
-1Be defined as: x * x
-1=1 mod p
As shown in Figure 1, provided a kind of structured flowchart that is used to generate the PRNG of pseudo random number of the present invention.Said PRNG utilizes the hyperbolic square algorithm to generate pseudo random number, and this PRNG comprises:
Parameter input module is used to dispose initial parameter and initial pseudorandom is counted a
0Said initial parameter comprises: a big prime number p is used to get surplus calculating; An Integer N is used to limit initial a
0Length, a
0Length should be less than or equal to the N position; An integer L is used for as count value i being carried out the threshold value that size is judged.Make initial pseudorandom count a
0It is the big number of a non-trivial (nonuniform); Make count value i=0.
The odd even judge module is used to judge current pseudo random number a
iBe odd number or even number, if even number is then sent current pseudo random number into a square processing module, if odd number is then sent current pseudo random number into the hyperbolic processing module;
Said square of processing module is used for current pseudo random number a
iGenerate next pseudo random number a according to square algorithm
I+1Export the counting judge module to; Wherein, if a
iBe even number, when carrying out square handling, make a
I+1=S (a
i); S (x)=x
2Mod p;
Said hyperbolic processing module is used for current pseudo random number a
iGenerate next pseudo random number a according to the hyperbolic algorithm
I+1Export the counting judge module to; Wherein, if a
iBe odd number, when carrying out the hyperbolic processing, make a
I+1=T (a
i); T (x)=(x-x
-1) mod p;
Said counting judge module is used to receive next pseudo random number a
I+1, count value i is added 1 increases progressively, make i=i+1 (after i increases progressively, this moment pseudo random number a
iA before increasing progressively exactly
I+1), whether judge current count value i greater than preset counting thresholding L, if the count value after increasing progressively is greater than preset counting thresholding L; Be i＞L; Then jump to and overflow processing module and handle, otherwise directly output utilizes and square handles or hyperbolic is handled the pseudo random number a of back gained
iExport the pseudo random number that is produced to output module.
The said processing module of overflowing is used for when i＞L, to pseudo random number a
iOverflow processing, make a
i=(a
i-a
I-L) mod p, with a
iExport output module to as pseudo random number.
Said output module is used for externally exporting pseudo random number, on the one hand simultaneously also with newly-generated pseudo random number a
iReach current count value i and feed back to the odd even judge module, as the next pseudo random number of input parameter continuation generation of odd even judge module.The final pseudo-random number sequence a that exports along with increasing progressively of count value i
1, a
2...., a
i... ...
Pseudo-random number generation method of the present invention, its idiographic flow is as shown in Figure 2.
At first, confirm that initial parameter and initial pseudorandom count a
0
Said initial parameter comprises: a big prime number p is used to get surplus calculating; An Integer N is used to limit initial a
0Length, a
0Length should be less than or equal to the N position; An integer L is used for as count value i being carried out the threshold value that size is judged, the pseudo random number that when i is less than or equal to L, can directly adopt square hyperbolic method to obtain as i during greater than L, then need be done and overflow processing.Make initial pseudorandom count a
0It is the big number of a non-trivial (nonuniform); Make count value i=0.
Then, judge current pseudo random number a
iBe odd number or even number:
If a
iBe even number, then carry out a square processing, make a
I+1=S (a
i); Wherein, S (x)=x
2Mod p;
If a
iBe odd number, then carry out hyperbolic and handle, make a
I+1=T (a
i); Wherein, T (x)=(x-x
-1) mod p;
Afterwards, make i=i+1; Judge count value i increase progressively after whether greater than L: after i increases progressively, the pseudo random number a of this moment
iEmploying before increasing progressively exactly square processing or hyperbolic are handled the pseudo random number a that is generated
I+1If i＞L then makes a
i=(a
i-a
I-L) mod p, with a
iExport as pseudo random number; Otherwise directly output utilizes square processing or hyperbolic to handle the pseudo random number a of back gained
i
At last, on the one hand with newly-generated pseudo random number a
iOutput is on the other hand with gained pseudo random number a
iReach new count value i and feed back to the step that odd even is judged, to a
iJust judge that continued utilization square processing or hyperbolic processing generate pseudo random number, so circulate, finally generate pseudo-random number sequence a
1, a
2...., a
i... .. obtains high-quality pseudo random number.
As shown in Figure 3, further provided the simplified structure block diagram of another kind of PRNG, said PRNG comprises:
The odd even judge module is used to judge current pseudo random number a
iBe odd number or even number, if even number is then sent current pseudo random number into a square processing module, if odd number is then sent current pseudo random number into the hyperbolic processing module;
Said square of processing module is used for current pseudo random number a
iGenerate next pseudo random number a according to square algorithm
I+1Said square of processing module is at a
iWhen being even number, when carrying out square handling, make a
I+1=S (a
i); Wherein, function S (x)=x
2Mod p; P is a prime number.
Said hyperbolic processing module is used for current pseudo random number a
iGenerate next pseudo random number a according to the hyperbolic algorithm
I+1Said hyperbolic processing module is at a
iWhen being odd number, when carrying out the hyperbolic processing, make a
I+1=T (a
i); Wherein, function T (x)=(x-x
-1) mod p; P is a prime number.
China's " random number detection standard " is Chinese domestic authority's detection standard; Comprise that the single-bit frequency detects, frequency detects in the piece, playing card detect, folded subsequence detects, distance of swimming sum detects, the distance of swimming distributes detects, in the piece maximum " 1 " detect, Dyadic derivation detection, Autocorrelation Detection, rank of matrix detect, add up and 15 detection contents such as detection, approximate entropy detections, the detection of linear complexity, the detection of general statistics, discrete fourier detection.
According to China's " random number detection standard " pseudo random number that existing methods and applications hyperbolic square algorithm of the present invention produces is carried out complete detection, testing result is as shown in table 1:
Table 1: pseudo random number testing result
| Detect index | Existing method | The hyperbolic square algorithm |
| Generate the average ratio consuming time of equivalent pseudo random number | 4.36 | 1 |
| Generate the average quality of pseudo random number | 0.981 | 0.988 |
Testing result according to shown in the above-mentioned table 1 can know that with respect to existing algorithm, the speed of hyperbolic square algorithm when generating pseudo random number is faster, and the randomness of the pseudo random number that is produced is better, has the characteristics of efficient generation high-quality pseudo random number.
The above is merely embodiments of the invention, is not limited to the present invention, and for a person skilled in the art, the present invention can have various changes and variation.All within spirit of the present invention and principle, any modification of being done, be equal to replacement, improvement etc., all should be included within the claim scope of the present invention.
Claims (10)
1. PRNG comprises:
The odd even judge module is used to judge current pseudo random number a
iBe odd number or even number, if even number is then sent current pseudo random number into a square processing module, if odd number is then sent current pseudo random number into the hyperbolic processing module;
Said square of processing module is used for current pseudo random number a
iGenerate next pseudo random number a according to square algorithm
I+1
Said hyperbolic processing module is used for current pseudo random number a
iGenerate next pseudo random number a according to the hyperbolic algorithm
I+1
2. PRNG as claimed in claim 1 is characterized in that,
Said square of processing module is at a
iWhen being even number, when carrying out square handling, make a
I+1=S (a
i) obtain new pseudo random number a
I+1Wherein, function S (x)=x
2Mod p; P is a prime number.
3. according to claim 1 or claim 2 PRNG is characterized in that,
Said hyperbolic processing module is at a
iWhen being odd number, when carrying out the hyperbolic processing, make a
I+1=T (a
i) obtain new pseudo random number a
I+1Wherein, function T (x)=(x-x
-1) mod p; P is a prime number.
4. PRNG comprises:
Parameter input module is used to dispose initial parameter and initial pseudorandom is counted a
0
The odd even judge module is used to judge current pseudo random number a
iBe odd number or even number, if even number is then sent current pseudo random number into a square processing module, if odd number is then sent current pseudo random number into the hyperbolic processing module;
Said square of processing module is used for current pseudo random number a
iGenerate next pseudo random number a according to square algorithm
I+1Export the counting judge module to;
Said hyperbolic processing module is used for current pseudo random number a
iGenerate next pseudo random number a according to the hyperbolic algorithm
I+1Export the counting judge module to;
Said counting judge module is used to receive next pseudo random number a
I+1, count value i is added 1 increase progressively and make i=i+1, square handle or hyperbolic is handled the pseudo random number a of back gained utilizing
I+1As current pseudo random number a
i, judge current count value i whether greater than preset counting thresholding L, if the count value after increasing progressively is greater than preset counting thresholding, i.e. i＞L then jumps to and overflows processing module and handle, otherwise, with current pseudo random number a
iSend to output module;
Overflow processing module, be used for when i＞L, pseudo random number a
iOverflow processing, make a
i=(a
i-a
I-L) mod p, with a
iExport output module to as pseudo random number;
Said output module is used for the externally newly-generated pseudo random number a of output on the one hand
i, on the other hand with newly-generated pseudo random number a
iReach current count value i and feed back to the odd even judge module, be used for continuing to generate next pseudo random number.
5. PRNG as claimed in claim 4 is characterized in that,
Comprising of said parameter input module configuration initial parameter: a big prime number p, one is used to limit initial a
0The Integer N of length; An integer L is used for as count value i being carried out the threshold value that size is judged;
Said initial pseudorandom is counted a
0Be the big number of non-trivial, i.e. a count value i=0.
6. like claim 4 or 5 described PRNGs, it is characterized in that,
Said square of processing module is at a
iWhen being even number, when carrying out square handling, make a
I+1=S (a
i); Wherein, function S (x)=x
2Mod p; P is a prime number.
7. like claim 4 or 5 described PRNGs, it is characterized in that,
Said hyperbolic processing module is at a
iWhen being odd number, when carrying out the hyperbolic processing, make a
I+1=T (a
i); Wherein, function T (x)=(x-x
-1) mod p; P is a prime number.
8. the generation method of a pseudo random number is characterized in that, comprising:
At first, confirm that initial parameter and initial pseudorandom count a
0
Then, judge current pseudo random number a
iBe odd number or even number: if even number, then to current pseudo random number a
iGenerate next pseudo random number a according to square algorithm
I+1If odd number is then to current pseudo random number a
iGenerate next pseudo random number a according to the hyperbolic algorithm
I+1
Afterwards, make i=i+1, with utilizing square processing or hyperbolic to handle the pseudo random number a of back gained
I+1As current pseudo random number a
iJudge count value i increase progressively after whether greater than the counting thresholding L that sets:
If i＞L then makes a
i=(a
i-a
I-L) mod p, p is a prime number, with a
iExport as pseudo random number; Otherwise directly output utilizes square processing or hyperbolic to handle the newly-generated pseudo random number a in back
i
At last, externally export newly-generated pseudo random number a on the one hand
i, on the other hand with newly-generated pseudo random number a
iAnd current count value i feeds back to current pseudo random number a
iCarry out the step that odd even is judged, continue to carry out and utilize square processing or hyperbolic to handle the flow process that generates pseudo random number.
9. the generation method of pseudo random number as claimed in claim 8 is characterized in that,
If judge current pseudo random number a
iBe even number, then to current pseudo random number a
iGenerate next pseudo random number a according to square algorithm
I+1, generating mode is:
Make a
I+1=S (a
i); Wherein, S (x)=x
2Mod p.
10. like the generation method of claim 8 or 9 described pseudo random numbers, it is characterized in that,
If judge current pseudo random number a
iBe odd number, then to current pseudo random number a
iGenerate next pseudo random number a according to the hyperbolic algorithm
I+1, generating mode is:
Make a
I+1=T (a
i); Wherein, T (x)=(x-x
-1) mod p.
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| CN112181362A (en) * | 2020-09-28 | 2021-01-05 | 苏州矗联电子技术有限公司 | High-reliability physical random number generation system and method |
| CN116243887A (en) * | 2022-12-06 | 2023-06-09 | 北京海泰方圆科技股份有限公司 | Software random number generation method and device |
| CN116243887B (en) * | 2022-12-06 | 2023-11-14 | 北京海泰方圆科技股份有限公司 | Software random number generation method and device |
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