Method and device for evaluating quality of random number generator

A random number generator and random number technology, applied in random number generators, biological neural network models, etc., can solve the problem of lack of randomness in calculating pseudo-random numbers

Active Publication Date: 2021-06-15
BEIJING KUANGSHI TECH CO LTD +1
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

However, there is currently a lack of methods for computing the randomness of pseudorandom numbers

Method used

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  • Method and device for evaluating quality of random number generator
  • Method and device for evaluating quality of random number generator
  • Method and device for evaluating quality of random number generator

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Experimental program
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Embodiment Construction

[0022] In order to make the objects, technical solutions and advantages of the present invention more apparent, exemplary embodiments according to the present invention will be described in detail below with reference to the accompanying drawings. Apparently, the described embodiments are only some embodiments of the present invention, rather than all embodiments of the present invention, and it should be understood that the present invention is not limited by the exemplary embodiments described here. Based on the embodiments of the present invention described in the present invention, all other embodiments obtained by those skilled in the art without creative effort shall fall within the protection scope of the present invention.

[0023] First, refer to figure 1 An example electronic device 100 for implementing the method and apparatus for evaluating the quality of a random number generator according to an embodiment of the present invention will be described.

[0024] Such...

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Abstract

The present invention provides a method and device for evaluating the quality of a random number generator, the method comprising: using the random number generator to be evaluated to generate a plurality of random number sequences; inputting part of the random number sequences in the plurality of random number sequences into The cyclic neural network is used to train the cyclic neural network; the trained cyclic neural network is used to predict some random numbers in the remaining random number sequences in the multiple random number sequences; and the quality of the random number generator is determined according to the predicted results. The method and device for evaluating the quality of a random number generator provided by the present invention are based on a cyclic neural network to model the correlation of the random number sequence generated by the random number generator, so that the cyclic neural network can be used to carry out the correlation of the random number sequence Estimation, to achieve an objective and effective evaluation of the quality of random number generators, can be used as a reference for comparison, selection and design of random number generators, and has important value in the fields of file encryption and data transmission.

Description

technical field [0001] The present invention relates to the technical field of random number generators, in particular to a method and device for evaluating the quality of random number generators. Background technique [0002] In various computer programs, a random number generator (Random Number Generator, RNG) is a widely used module, and its main function is to generate a series of random numbers for computer programs to use in various situations. These generated numbers are called pseudo-random numbers because they are calculated by some algorithm and are not truly random. [0003] However, different random number generators are not of the same quality. The quality of a random number generator can be measured by the randomness of the sequence of random numbers it produces. Obviously, the higher the randomness of the random number sequence, the better the quality of the random number generator. The randomness of pseudo-random numbers is a statistical law whose main fe...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06F7/58
CPCG06F7/58G06N3/02
Inventor 姚聪周舒畅周昕宇何蔚然
Owner BEIJING KUANGSHI TECH CO LTD
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