CN110413256B - Binary random sequence detection method, system, equipment and computer medium - Google Patents
Binary random sequence detection method, system, equipment and computer medium Download PDFInfo
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Abstract
The application discloses a binary random sequence detection method, a binary random sequence detection system, a binary random sequence detection device and a computer medium, wherein the binary random sequence detection method, the binary random sequence detection system, the binary random sequence detection device and the computer medium are applied to detection equipment for installing an FFTW software package, and a target binary random sequence is obtained from an undetected binary random sequence; and detecting the target binary random sequence in the FFTW software package to obtain a detection result of the target binary random sequence. That is, the binary random sequence detection method provided by the application detects a target binary random sequence by means of the FFTW software package to obtain a corresponding detection result, and compared with the existing technology for detecting the target binary random sequence by means of NIST-STS randomness test codes and tools, the detection efficiency is high. The binary random sequence detection system, the binary random sequence detection equipment and the computer readable storage medium solve the corresponding technical problems.
Description
Technical Field
The present application relates to the field of information security technologies, and in particular, to a binary random sequence detection method, system, device, and computer medium.
Background
In the field of information security, in order to securely transmit information, a cryptographic operation needs to be performed on the information, for example, encryption and decryption are performed on the information by using a key, digital signature is performed on the information, identity authentication is performed on the information, and in the process, a binary random sequence needs to be generated and applied, and accordingly, randomness of the binary random sequence is called a factor affecting the cryptographic operation, and therefore the generated binary random sequence needs to be detected.
The existing binary random sequence detection method comprises the following steps: the generated binary random sequences were subjected to discrete Fourier detection using NIST-STS randomness test codes and tools provided by NIST (National Institute of Standards and Technology ).
However, the existing binary random sequence detection method has low detection efficiency.
In summary, how to improve the detection efficiency of the binary random sequence is a problem to be solved urgently by those skilled in the art.
Disclosure of Invention
The application aims to provide a binary random sequence detection method, which can solve the technical problem of improving the detection efficiency of a binary random sequence to a certain extent. The application also provides a binary random sequence detection system, equipment and a computer readable storage medium.
In order to achieve the above purpose, the present application provides the following technical solutions:
a binary random sequence detection method is applied to detection equipment for installing an FFTW software package, and comprises the following steps:
obtaining a target binary random sequence from the undetected binary random sequences;
and detecting the target binary random sequence in the FFTW software package to obtain a detection result of the target binary random sequence.
Preferably, the detecting the target binary random sequence to obtain a detection result of the target binary random sequence includes:
converting bit 0 in the target binary random sequence into a numerical value-1, and converting bit 1 into a numerical value 1 to obtain a converted binary random sequence;
performing discrete Fourier transform on the converted binary random sequence through an fftw _ execute function to obtain a complex number group;
calculating the modulus value of the first part of the complex numbers in the complex number group;
counting a first number value of the complex numbers with the modulus value smaller than a threshold value;
calculating a statistic based on the first number value and a total number value of complex numbers in the complex set;
and comparing the statistical value with a preset significance level value to obtain a detection result of the target binary random sequence.
Preferably, the converting bit 0 in the target binary random sequence into a value-1 and converting bit 1 into a value 1 to obtain a converted binary random sequence includes:
analyzing the representation type of the target binary random sequence;
if the representation type of the target binary random sequence is bit representation, converting the target binary random sequence into the conversion binary random sequence in a preset first lookup table through a first lookup formula;
the first lookup formula includes: xi＝Z[εi]；
Wherein epsiloniRepresenting the ith element in the target binary random sequence; xiRepresenting the ith element in the transformed binary random sequence; z represents the first lookup table, and Z [0 ]]＝-1，Z[1]＝1。
Preferably, the converting bit 0 in the target binary random sequence into a value-1 and converting bit 1 into a value 1 to obtain a converted binary random sequence includes:
analyzing the representation type of the target binary random sequence;
if the representation type of the target binary random sequence is byte representation, converting the target binary random sequence into the conversion binary random sequence through a second lookup formula in a preset second lookup table;
the second lookup formula includes: xi＝U[i]；
Wherein i represents the value of the ith byte in the target binary random sequence; xiRepresenting the ith element in the transformed binary random sequence; u denotes the second look-up table, Ud]＝(y0,y1,y2,...y7) D represents an element in the second lookup table, and yj＝2ej-1,0≤j≤7，ejRepresents the j-th bit of d, and d is more than or equal to 0 and less than or equal to 255.
Preferably, the calculating the modulus value of each of the first half complex numbers in the complex number group includes:
and calculating the square value of each modulus value of the first half of the plurality of groups.
Preferably, the first number value of the complex numbers with the statistical modulus value smaller than the threshold value includes:
calculating a square value of the threshold value;
among the plurality of values, the first number value of the square value of the statistical modulus value is smaller than the square value of the threshold value.
Preferably, the calculating statistics based on the first number value and the total number value of the complex numbers in the complex number set comprises:
calculating the statistic based on the first number value and a total number value of the complex numbers in the complex group by a statistic calculation formula;
the statistical value calculation formula includes:
wherein V represents the statistical value; n is a radical of1Representing the first number value; n represents the total number value.
Preferably, the comparing the statistical value with a preset significance level value to obtain a detection result of the target binary random sequence includes:
calculating a critical value based on the preset significance level value through a critical value calculation formula, wherein the critical value is a statistic value for distinguishing the type of the detection result;
judging whether the statistic value is smaller than the critical value, if so, obtaining a detection result indicating that the target binary random sequence passes the detection, and if not, obtaining a detection result indicating that the target binary random sequence does not pass the detection;
the critical value calculation formula includes: erfc (| V)B|/2)＝α；
Wherein, VBRepresenting the critical value; a represents the preset significance level value; erfc denotes the complementary error function.
Preferably, before obtaining a target binary random sequence from the undetected binary random sequences, the method further includes:
allocating a detection space for binary random sequence detection through an fftw _ malloc function, and creating a detection scheme for binary random sequence detection through an fftw _ plan _ dft _ r2c _1d function;
after the target binary random sequence is detected to obtain a detection result of the target binary random sequence, the method further includes:
and judging whether an undetected binary random sequence exists, if so, returning to the step of executing the target binary random sequence in the undetected binary random sequence, and if not, releasing the detection space through the fftw _ free function.
A binary random sequence detection system for use in a detection device for installing an FFTW software package, comprising:
the first acquisition module is used for acquiring a target binary random sequence from the undetected binary random sequences;
and the first detection module is used for detecting the target binary random sequence in the FFTW software package to obtain a detection result of the target binary random sequence.
A binary random sequence detection device, having an FFTW software package installed, comprising:
a memory for storing a computer program;
a processor for implementing the steps of any of the above binary random sequence detection methods when executing the computer program.
A computer-readable storage medium, in which a computer program is stored which, when being executed by a processor, carries out the steps of the binary random sequence detection method according to any one of the preceding claims.
The binary random sequence detection method is applied to detection equipment for installing an FFTW software package, and a target binary random sequence is obtained from undetected binary random sequences; and detecting the target binary random sequence in the FFTW software package to obtain a detection result of the target binary random sequence. That is, the binary random sequence detection method provided by the application detects a target binary random sequence by means of the FFTW software package to obtain a corresponding detection result, and compared with the existing technology for detecting the target binary random sequence by means of NIST-STS randomness test codes and tools, the detection efficiency is high. The binary random sequence detection system, the binary random sequence detection equipment and the computer readable storage medium solve the corresponding technical problems.
Drawings
In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings needed to be used in the description of the embodiments or the prior art will be briefly introduced below, it is obvious that the drawings in the following description are only embodiments of the present application, and for those skilled in the art, other drawings can be obtained according to the provided drawings without creative efforts.
FIG. 1 is a first flowchart of a binary random sequence detection method according to an embodiment of the present disclosure;
FIG. 2 is a second flowchart of a binary random sequence detection method provided by an embodiment of the present application;
FIG. 3 is a third flowchart of a binary random sequence detection method provided in the embodiment of the present application;
FIG. 4 is a fourth flowchart of a binary random sequence detection method according to an embodiment of the present disclosure;
fig. 5 is a schematic structural diagram of a binary random sequence detection system according to an embodiment of the present disclosure;
fig. 6 is a schematic structural diagram of a binary random sequence detection apparatus according to an embodiment of the present disclosure;
fig. 7 is another schematic structural diagram of a binary random sequence detection device according to an embodiment of the present application.
Detailed Description
The technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the drawings in the embodiments of the present application, and it is obvious that the described embodiments are only a part of the embodiments of the present application, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present application.
In the field of information security, in order to securely transmit information, a cryptographic operation needs to be performed on the information, for example, encryption and decryption are performed on the information by using a key, digital signature is performed on the information, identity authentication is performed on the information, and in the process, a binary random sequence needs to be generated and applied, and accordingly, randomness of the binary random sequence is called a factor affecting the cryptographic operation, and therefore the generated binary random sequence needs to be detected. The existing binary random sequence detection method comprises the following steps: the generated binary random sequences were subjected to discrete Fourier detection using NIST-STS randomness test codes and tools provided by NIST (National Institute of Standards and Technology ). However, the existing binary random sequence detection method has low detection efficiency. The binary random sequence detection method can improve the detection efficiency of the binary random sequence.
Referring to fig. 1, fig. 1 is a first flowchart of a binary random sequence detection method according to an embodiment of the present application.
The binary random sequence detection method provided by the embodiment of the application is applied to detection equipment for installing an FFTW software package, and can comprise the following steps:
step S101: and acquiring a target binary random sequence from the undetected binary random sequences.
In practical application, the detection device may first obtain a target binary random sequence from the undetected binary random sequence, where the type and number of the undetected binary random sequence may be determined according to a specific application scenario, and the purpose of the binary random sequence may also be determined according to the specific application scenario, such as for generating a key, generating a signature, and the like. It should be noted that the type of detection device that installs the fftw (the fast Fourier Transform in the west) software package described herein may also be determined according to a specific application scenario; and the FFTW referred to in this application refers to a standard C language set of programs that rapidly compute the discrete fourier transform, which was developed by m.frigo and s.johnson of MIT.
Step S102: and detecting the target binary random sequence in the FFTW software package to obtain a detection result of the target binary random sequence.
In practical application, after the detection device obtains the target binary random sequence, the detection device can detect the target binary random sequence in the FFTW software package to obtain a detection result of the target binary random sequence. It should be noted that the detection method for detecting the target binary random sequence may be flexibly selected according to a specific application scenario, and the application is not specifically limited herein.
The binary random sequence detection method is applied to detection equipment for installing an FFTW software package, and a target binary random sequence is obtained from undetected binary random sequences; and detecting the target binary random sequence in the FFTW software package to obtain a detection result of the target binary random sequence. That is, the binary random sequence detection method provided by the application detects a target binary random sequence by means of the FFTW software package to obtain a corresponding detection result, and compared with the existing technology for detecting the target binary random sequence by means of NIST-STS randomness test codes and tools, the detection efficiency is high.
Referring to fig. 2, fig. 2 is a second flowchart of a binary random sequence detection method according to an embodiment of the present application.
The binary random sequence detection method provided by the embodiment of the application can comprise the following steps:
step S201: and acquiring a target binary random sequence from the undetected binary random sequences.
It should be noted that, in practical application, when the FFTW software is used, the detection space for binary random sequence detection needs to be allocated through the FFTW _ malloc function of the FFTW software package, the detection scheme for binary random sequence detection needs to be created through the FFTW _ plan _ dft _ r2c _1d function of the FFTW software package, and accordingly, after the detection result of the target binary random sequence is obtained, the detection space needs to be released through the FFTW _ free function of the FFTE software package.
Step S202: in the FFTW software package, 0 in the target binary random sequence is converted into-1 to obtain a converted binary random sequence.
In practical application, the detection device may perform discrete fourier detection on the target binary random sequence through the FFTW software, and after obtaining a target binary random sequence, it is necessary to convert bit 0 in the target binary random sequence into value-1 and convert bit 1 into value 1 in the FFTW software package, so as to generate a new binary random sequence, that is, a converted binary random sequence.
In a specific application scenario, in the process of converting a target binary random sequence, in order to facilitate data conversion in an FFTW software package and further improve detection efficiency, the conversion process of the target binary random sequence can be simplified by means of a lookup table, in addition, the conversion process can be hidden by means of the lookup table, and certain safety is provided;
if the representation type of the target binary random sequence is bit representation, converting the target binary random sequence into a conversion binary random sequence in a preset first lookup table through a first lookup formula; the first lookup formula includes: xi＝Z[εi](ii) a Wherein epsiloniRepresenting the ith element in the target binary random sequence; xiRepresenting the ith element in the transformed binary random sequence; z represents a first lookup table, and Z [0 ]]＝-1，Z[1]＝1；
If the representation type of the target binary random sequence is byte representation, converting the target binary random sequence into a conversion binary random sequence in a preset second lookup table through a second lookup formula; the second lookup formula includes: xi＝U[i](ii) a Wherein i represents a targetThe value of the ith byte in the binary random sequence; xiRepresenting the ith element in the transformed binary random sequence; u denotes a second look-up table, Ud]＝(y0,y1,y2,...yh) D denotes an element in the second lookup table, and yj＝2ej-1,0≤j≤h，ejRepresents the j-th bit of d, and d is more than or equal to 0 and less than or equal to 255.
It should be noted that in the second lookup table, h represents a bit value corresponding to a byte in the target binary random sequence in the conversion binary random sequence, which may be determined according to actual needs, for example, if the value of h may be 7, then a byte in the target binary random sequence corresponds to 8 bits of data in the conversion binary random sequence; furthermore, U [ d ]]Middle y0,y1,y2,...yhThe sequence of (A) and (B) can be determined according to specific application scenarios, for example, according to y0y1y2...yhMay be arranged in the order of yh...y2y1y0The order of arrangement, etc.
Step S203: discrete Fourier transform is performed on the converted binary random sequence through an fftw _ execute function to obtain a complex number group.
In practical application, after the converted binary random sequence is obtained, discrete fourier transform can be performed on the converted binary random sequence through an FFTW _ execute function in an FFTW software package to obtain a complex group, and the number of complex numbers in the obtained complex group can be determined according to actual conditions.
Step S204: calculating the modulus value of the first half complex number in the complex number group.
In practical application, the formula can be used
Calculating the respective modulus values of the first half of the complex numbers in the complex number group, wherein, | fiAnd | represents the modulus value of the ith complex number, i is more than or equal to 0 and less than or equal to n/2-1, and n represents the number of the complex numbers in the complex number group.
Step S205: counting a first number of the complex numbers with the modulus value smaller than the threshold value.
In practical applicationAfter the modulus value is obtained through calculation, a first number value of the complex numbers with the modulus value smaller than a threshold value can be counted, and the threshold value can be determined according to the number of the complex numbers in the complex number group, for example, the threshold value can be
In a specific application scenario, in order to facilitate calculation of the modulus value and comparison of the magnitude relationship between the modulus value and the threshold value, when calculating the respective modulus value of the first half complex number in the complex group, the square value of the respective modulus value of the first half complex number in the complex group can be calculated; correspondingly, when the statistical modulus value is smaller than the first number value of the complex number of the threshold value, the square value of the threshold value can be calculated; in the complex number, the square value of the statistical modulus value is smaller than the first number value of the square value of the threshold value. The formula for calculating the square value of the modulus value of the first half complex number can be expressed as: l fi|2＝a2+b2I is more than or equal to 0 and less than or equal to n/2-1, wherein n represents the total number of the complex numbers in the complex group; the expression formula for the square of the threshold value may be: 2.995732274 n.
Step S206: a statistic is calculated based on the first number value and a total number value of the complex numbers in the complex set.
In practical applications, in order to facilitate calculation of the statistical value, when the statistical value is calculated based on the first number value and the total number value of the complex numbers in the complex group, the statistical value can be calculated based on the first number value and the total number value of the complex numbers in the complex group through a statistical value calculation formula; the statistical value calculation formula comprises:
wherein V represents a statistical value; n is a radical of1Representing a first number value; n represents the total number value.
Step S207: and comparing the statistical value with a preset significance level value to obtain a detection result of the target binary random sequence.
In practical application, the relationship between the statistical value and the preset significance level value determines the detection result of the target binary random sequence, so after the statistical value is calculated, the statistical value needs to be compared with the preset significance level value to obtain the detection result of the target binary random sequence, and the preset significance level value is determined according to a specific application scene. For example, a value of erfc (| V |/2) may be calculated, V represents a statistical value, erfc represents a complementary error function, and it is determined whether the value of erfc (| V |/2) is greater than or equal to a preset significance level value, if yes, it is determined that the target binary random sequence passes the detection, and if not, it is determined that the binary random sequence does not pass the detection.
In a specific application scenario, in order to facilitate comparison of the statistical value with a preset significance level value, when the statistical value is compared with the preset significance level value to obtain a detection result of a target binary random sequence, a critical value can be calculated based on the preset significance level value through a critical value calculation formula, wherein the critical value is a statistical value for distinguishing the type of the detection result; judging whether the statistical value is smaller than a critical value, if so, obtaining a detection result indicating that the target binary random sequence passes the detection, and if not, obtaining a detection result indicating that the target binary random sequence does not pass the detection; the formula for calculating the critical value includes: erfc (| V)BI/2) ═ α; wherein, VBRepresents a critical value; alpha represents a preset significance level value; erfc represents the complementary error function; it should be noted that when α is 0.01, VBIs 1.821386, the statistical value can be directly compared with 10821386 to obtain the corresponding detection result.
Referring to fig. 3, fig. 3 is a third flowchart of a binary random sequence detection method according to an embodiment of the present application.
In the binary random sequence detection method provided by the application, when there are a plurality of undetected binary random sequences, taking the representation type of a target binary random sequence as bit representation as an example, when a detection device detects a plurality of binary random sequences through an FFTW software package, the following steps are performed for each binary random sequence:
step S301: the detection space for binary random sequence detection is allocated by the fftw _ malloc function, and a detection scheme for binary random sequence detection is created by the fftw _ plan _ dft _ r2c _1d function.
Step S302: and acquiring a target binary random sequence from the undetected binary random sequences.
Step S303: converting a target binary random sequence into a conversion binary random sequence in a preset first lookup table through a first lookup formula; the first lookup formula includes: xi＝Z[εi](ii) a Wherein epsiloniRepresenting the ith element in the target binary random sequence; xiRepresenting the ith element in the transformed binary random sequence; z represents a first lookup table, and Z [0 ]]＝-1，Z[1]＝1。
Step S304: discrete Fourier transform is performed on the converted binary random sequence through an fftw _ execute function to obtain a complex number group.
Step S305: and calculating the modulus value of the first half complex number in the complex number group in the square mode.
Step S306: calculating a threshold value in a square mode; in the complex numbers, the modulus value in the square mode is counted as a first number value smaller than the threshold value in the square mode.
Step S307: calculating a statistic value based on the first number value and the total number value of the complex numbers in the complex number group through a statistic value calculation formula; the statistical value calculation formula comprises:
wherein V represents a statistical value; n is a radical of1Representing a first number value; n represents the total number value.
Step S308: and calculating a critical value based on a preset significance level value through a critical value calculation formula, wherein the critical value is a statistic value for distinguishing the types of the detection results.
Step S309: judging whether the statistical value is smaller than a critical value, if so, obtaining a detection result indicating that the target binary random sequence passes the detection, and if not, obtaining a detection result indicating that the target binary random sequence does not pass the detection; critical valueThe calculation formula comprises: erfc (| V)BI/2) ═ α; wherein, VBRepresents a critical value; alpha represents a preset significance level value; erfc denotes the complementary error function.
Step S310: the detection space is released by the fftw _ free function.
In practical application, when the number of undetected binary random sequences is 1000, the method provided by the embodiment runs 1000 times under the test environment of Dual Core Intel Core 3, 3.4GHZ, the total time consumption is 77.4 seconds, and the discrete fourier detection method runs 1000 times by means of NIST-STS randomness test codes and tools, the time consumption is 261.2 seconds, so that the detection efficiency of the binary random sequence detection method provided by the application is high. It should be noted that the method provided by the present embodiment is also applicable to binary random sequences with byte as the representation type.
Referring to fig. 4, fig. 4 is a fourth flowchart of a binary random sequence detection method according to an embodiment of the present disclosure.
In the binary random sequence detection method provided by the application, when there are a plurality of undetected binary random sequences, taking the representation type of the target binary random sequence as byte representation as an example, when the detection device detects the plurality of binary random sequences through the FFTW software package, the following steps may be performed:
step S401: the detection space for binary random sequence detection is allocated by the fftw _ malloc function, and a detection scheme for binary random sequence detection is created by the fftw _ plan _ dft _ r2c _1d function.
Step S402: and acquiring a target binary random sequence from the undetected binary random sequences.
Step S403: converting the target binary random sequence into a conversion binary random sequence in a preset second lookup table through a second lookup formula; the second lookup formula includes: xi＝U[i](ii) a Wherein i represents the value of the ith byte in the target binary random sequence; xiRepresenting the ith element in the transformed binary random sequence; u denotes a second look-up table, Ud]＝(y0,y1,y2,...yh) And d represents an element in the second lookup tableAnd y isj＝2ej-1,0≤j≤h，ejRepresents the j-th bit of d, and d is more than or equal to 0 and less than or equal to 255.
Step S404: discrete Fourier transform is performed on the converted binary random sequence through an fftw _ execute function to obtain a complex number group.
Step S405: and calculating the modulus value of the first half complex number in the complex number group in the square mode.
Step S406: calculating a threshold value in a square mode; in the complex numbers, the modulus value in the square mode is counted as a first number value smaller than the threshold value in the square mode.
Step S407: calculating a statistic value based on the first number value and the total number value of the complex numbers in the complex number group through a statistic value calculation formula; the statistical value calculation formula comprises:
wherein V represents a statistical value; n is a radical of1Representing a first number value; n represents the total number value.
Step S408: and calculating a critical value based on a preset significance level value through a critical value calculation formula, wherein the critical value is a statistic value for distinguishing the types of the detection results.
Step S409: judging whether the statistical value is smaller than a critical value, if so, obtaining a detection result indicating that the target binary random sequence passes the detection, and if not, obtaining a detection result indicating that the target binary random sequence does not pass the detection; the formula for calculating the critical value includes: erfc (| V)BI/2) ═ α; wherein, VBRepresents a critical value; alpha represents a preset significance level value; erfc denotes the complementary error function.
Step S410: judging whether an undetected binary random sequence exists, if so, returning to the step S402, otherwise, executing the step S411: the detection space is released by the fftw _ free function.
In practical applications, still taking the number of undetected binary random sequences as an example of 1000, in the test environment of Dual Core Intel Core 3, 3.4GHZ, the total time consumption of the method provided by the present embodiment is 47.3 seconds, and the time consumption of 261.2 seconds is reached when the discrete fourier test method is 1000 times run by means of NIST-STS randomness test codes and tools, so that the detection efficiency of the binary random sequence detection method provided by the present application is high. It should be noted that the method provided by the present embodiment is equally applicable to binary random sequences represented in bits.
The application also provides a binary random sequence detection system, which has the corresponding effect of the binary random sequence detection method provided by the embodiment of the application. Referring to fig. 5, fig. 5 is a schematic structural diagram of a binary random sequence detection system according to an embodiment of the present disclosure.
The binary random sequence detection system provided by the embodiment of the application is applied to a detection device for installing an FFTW software package, and can include:
a first obtaining module 101, configured to obtain a target binary random sequence from undetected binary random sequences;
the first detecting module 102 is configured to detect a target binary random sequence in an FFTW software package to obtain a detection result of the target binary random sequence.
The binary random sequence detection system provided by the embodiment of the application is applied to a detection device for installing an FFTW software package, and the first detection module may include:
the first conversion submodule is used for converting a bit 0 in the target binary random sequence into a numerical value-1 and converting a bit 1 into a numerical value 1 to obtain a conversion binary random sequence;
the first transformation submodule is used for performing discrete Fourier transformation on the transformed binary random sequence through an fftw _ execute function to obtain a complex number group;
the first calculation submodule is used for calculating the modulus value of each first half complex number in the complex number group;
the first statistic submodule is used for counting a first number value of the complex numbers of which the modulus values are smaller than a threshold value;
a second calculation sub-module for calculating a statistical value based on the first number value and a total number value of the complex numbers in the complex number group;
and the first comparison submodule is used for comparing the statistical value with a preset significance level value to obtain a detection result of the target binary random sequence.
The binary random sequence detection system provided by the embodiment of the application is applied to a detection device for installing an FFTW software package, and the first conversion submodule can include:
the first analysis unit is used for analyzing the representation type of the target binary random sequence;
the first conversion unit is used for converting the target binary random sequence into a conversion binary random sequence in a preset first lookup table through a first lookup formula when the representation type of the target binary random sequence is bit representation;
the first lookup formula includes: xi＝Z[εi]；
Wherein epsiloniRepresenting the ith element in the target binary random sequence; xiRepresenting the ith element in the transformed binary random sequence; z represents a first lookup table, and Z [0 ]]＝-1，Z[1]＝1。
The binary random sequence detection system provided by the embodiment of the application is applied to a detection device for installing an FFTW software package, and the first conversion submodule can include:
the second analysis unit is used for analyzing the representation type of the target binary random sequence;
the second conversion unit is used for converting the target binary random sequence into a conversion binary random sequence in a preset second lookup table through a second lookup formula when the representation type of the target binary random sequence is byte representation;
the second lookup formula includes: xi＝U[i]；
Wherein i represents the value of the ith byte in the target binary random sequence; xiRepresenting the ith element in the transformed binary random sequence; u denotes a second look-up table, Ud]＝(y0,y1,y2,...y7) D denotes an element in the second lookup table, and yj＝2ej-1,0≤j≤7，ejRepresents the j-th bit of d, and d is more than or equal to 0 and less than or equal to 255.
The binary random sequence detection system provided by the embodiment of the application is applied to a detection device for installing an FFTW software package, and the first calculation submodule may include:
the first calculating unit is used for calculating the square value of each modulus value of the first half complex number in the complex number group.
The binary random sequence detection system provided by the embodiment of the application is applied to a detection device for installing an FFTW software package, and the first statistical submodule may include:
the second calculating unit is used for calculating a square value of the threshold value;
the first statistic unit is used for counting a first number value of a square value of the modulus value smaller than a square value of the threshold value in the complex number.
The binary random sequence detection system provided by the embodiment of the application is applied to a detection device for installing an FFTW software package, and the second calculation submodule may include:
a third calculating unit, configured to calculate a statistical value based on the first number value and a total number value of the complex numbers in the complex number group through a statistical value calculating formula;
the statistical value calculation formula comprises:
wherein V represents a statistical value; n is a radical of1Representing a first number value; n represents the total number value.
The binary random sequence detection system provided by the embodiment of the application is applied to a detection device for installing an FFTW software package, and the first comparison submodule can comprise:
a fourth calculating unit, configured to calculate a critical value based on a preset significance level value through a critical value calculation formula, where the critical value is a statistical value for distinguishing a type of the detection result;
the first judging unit is used for judging whether the statistic value is smaller than a critical value, if so, obtaining a detection result indicating that the target binary random sequence passes the detection, and if not, obtaining a detection result indicating that the target binary random sequence does not pass the detection;
the formula for calculating the critical value includes: erfc (| V)B|/2)＝α；
Wherein, VBRepresents a critical value; alpha represents a preset significance level value; erfc denotes the complementary error function.
The binary random sequence detection system provided by the embodiment of the application is applied to a detection device for installing an FFTW software package, and may further include:
a first allocation module, configured to allocate, by the first obtaining module, a detection space for binary random sequence detection through an fftw _ malloc function before obtaining a target binary random sequence from an undetected binary random sequence, and create a detection scheme for binary random sequence detection through an fftw _ plan _ dft _ r2c _1d function;
and the first judgment module is used for judging whether the undetected binary random sequence exists after the first detection module detects the target binary random sequence to obtain the detection result of the target binary random sequence, prompting the first acquisition module to execute the step of acquiring one target binary random sequence from the undetected binary random sequence if the undetected binary random sequence exists, and releasing the detection space through the fftw _ free function if the undetected binary random sequence does not exist.
The application also provides binary random sequence detection equipment and a computer readable storage medium, which have corresponding effects possessed by the binary random sequence detection method provided by the embodiment of the application. Referring to fig. 6, fig. 6 is a schematic structural diagram of a binary random sequence detection apparatus according to an embodiment of the present disclosure.
The binary random sequence detection device provided by the embodiment of the application is provided with an FFTW software package, and comprises a memory 201 and a processor 202, wherein the memory 201 stores a computer program, and the processor 202 realizes the following steps when executing the computer program stored in the memory 201:
obtaining a target binary random sequence from the undetected binary random sequences;
and detecting the target binary random sequence in the FFTW software package to obtain a detection result of the target binary random sequence.
The binary random sequence detection device provided by the embodiment of the application is provided with an FFTW software package, and comprises a memory 201 and a processor 202, wherein a computer program is stored in the memory 201, and the following steps are specifically realized when the processor 202 executes the computer program stored in the memory 201: converting bit 0 in the target binary random sequence into value-1, and converting bit 1 into value 1 to obtain a converted binary random sequence; performing discrete Fourier transform on the converted binary random sequence through an fftw _ execute function to obtain a complex number group; calculating the respective modulus values of the first half of the plurality of groups; counting a first number value of the complex numbers with the modulus value smaller than a threshold value; calculating a statistic based on the first number value and a total number value of the complex numbers in the complex group; and comparing the statistical value with a preset significance level value to obtain a detection result of the target binary random sequence.
The binary random sequence detection device provided by the embodiment of the application is provided with an FFTW software package, and comprises a memory 201 and a processor 202, wherein a computer program is stored in the memory 201, and the following steps are specifically realized when the processor 202 executes the computer program stored in the memory 201: analyzing the representation type of the target binary random sequence; if the representation type of the target binary random sequence is bit representation, converting the target binary random sequence into a conversion binary random sequence in a preset first lookup table through a first lookup formula; the first lookup formula includes: xi＝Z[εi](ii) a Wherein epsiloniRepresenting the ith element in the target binary random sequence; xiRepresenting the ith element in the transformed binary random sequence; z represents a first lookup table, and Z [0 ]]＝-1，Z[1]＝1。
The binary random sequence detection device provided by the embodiment of the application is provided with an FFTW software package, and comprises a memory 201 and a processor 202, wherein a computer program is stored in the memory 201, and the following steps are specifically realized when the processor 202 executes the computer program stored in the memory 201: analyzing the representation type of the target binary random sequence; if the representation type of the target binary random sequence is byte representation, a preset second lookup table is usedConverting the target binary random sequence into a conversion binary random sequence through a second search formula; the second lookup formula includes: xi＝U[i](ii) a Wherein i represents the value of the ith byte in the target binary random sequence; xiRepresenting the ith element in the transformed binary random sequence; u denotes a second look-up table, Ud]＝(y0,y1,y2,...yh) D denotes an element in the second lookup table, and yj＝2ej-1,0≤j≤h，ejRepresents the j-th bit of d, and d is more than or equal to 0 and less than or equal to 255.
The binary random sequence detection device provided by the embodiment of the application is provided with an FFTW software package, and comprises a memory 201 and a processor 202, wherein a computer program is stored in the memory 201, and the following steps are specifically realized when the processor 202 executes the computer program stored in the memory 201: the square value of the respective modulus values of the first half of the plurality of sets is calculated.
The binary random sequence detection device provided by the embodiment of the application is provided with an FFTW software package, and comprises a memory 201 and a processor 202, wherein a computer program is stored in the memory 201, and the following steps are specifically realized when the processor 202 executes the computer program stored in the memory 201: calculating a square value of the threshold value; in the complex number, the square value of the statistical modulus value is smaller than the first number value of the square value of the threshold value.
The binary random sequence detection device provided by the embodiment of the application is provided with an FFTW software package, and comprises a memory 201 and a processor 202, wherein a computer program is stored in the memory 201, and the following steps are specifically realized when the processor 202 executes the computer program stored in the memory 201: calculating a statistic value based on the first number value and the total number value of the complex numbers in the complex number group through a statistic value calculation formula; the statistical value calculation formula comprises:
wherein V represents a statistical value; n is a radical of1Representing a first number value; n represents the total number value.
The binary random sequence detection device provided by the embodiment of the application is provided with an FFTW software package, and comprises a memory 201 and a processor 202, wherein a computer program is stored in the memory 201, and the following steps are specifically realized when the processor 202 executes the computer program stored in the memory 201: calculating a critical value based on a preset significance level value through a critical value calculation formula, wherein the critical value is a statistic value for distinguishing the types of the detection results; judging whether the statistical value is smaller than a critical value, if so, obtaining a detection result indicating that the target binary random sequence passes the detection, and if not, obtaining a detection result indicating that the target binary random sequence does not pass the detection; the formula for calculating the critical value includes: erfc (| V)BI/2) ═ α; wherein, VBRepresents a critical value; alpha represents a preset significance level value; erfc denotes the complementary error function.
The binary random sequence detection device provided by the embodiment of the application is provided with an FFTW software package, and comprises a memory 201 and a processor 202, wherein a computer program is stored in the memory 201, and the following steps are specifically realized when the processor 202 executes the computer program stored in the memory 201: before a target binary random sequence is acquired from an undetected binary random sequence, allocating a detection space for binary random sequence detection through an fftw _ malloc function, and creating a detection scheme for binary random sequence detection through an fftw _ plan _ dft _ r2c _1d function; correspondingly, after the target binary random sequence is detected to obtain the detection result of the target binary random sequence, whether the undetected binary random sequence exists or not is judged, if yes, the step of executing the undetected binary random sequence to obtain one target binary random sequence is returned, and if not, the detection space is released through the fftw _ free function.
Referring to fig. 7, another binary random sequence detection apparatus provided in the embodiment of the present application may further include: an input port 203 connected to the processor 202, for transmitting externally input commands to the processor 202; a display unit 204 connected to the processor 202, for displaying the processing result of the processor 202 to the outside; and the communication module 205 is connected with the processor 202 and is used for realizing the communication between the binary random sequence detection device and the outside world. The display unit 204 may be a display panel, a laser scanning display, or the like; the communication method adopted by the communication module 205 includes, but is not limited to, mobile high definition link technology (HML), Universal Serial Bus (USB), High Definition Multimedia Interface (HDMI), and wireless connection: wireless fidelity technology (WiFi), bluetooth communication technology, bluetooth low energy communication technology, ieee802.11s based communication technology.
The computer-readable storage medium provided in the embodiments of the present application stores a computer program, and when the computer program is executed by a processor, the steps of the binary random sequence detection method described in any of the above embodiments are implemented.
The computer-readable storage media to which this application relates include Random Access Memory (RAM), memory, Read Only Memory (ROM), electrically programmable ROM, electrically erasable programmable ROM, registers, hard disk, a removable disk, a CD-ROM, or any other form of storage media known in the art.
For a description of relevant parts in the binary random sequence detection system, the binary random sequence detection device, and the computer-readable storage medium provided in the embodiments of the present application, reference is made to detailed descriptions of corresponding parts in the binary random sequence detection method provided in the embodiments of the present application, and details are not repeated here. In addition, parts of the above technical solutions provided in the embodiments of the present application, which are consistent with the implementation principles of corresponding technical solutions in the prior art, are not described in detail so as to avoid redundant description.
It is further noted that, herein, relational terms such as first and second, and the like may be used solely to distinguish one entity or action from another entity or action without necessarily requiring or implying any actual such relationship or order between such entities or actions. Also, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising an … …" does not exclude the presence of other identical elements in a process, method, article, or apparatus that comprises the element.
The previous description of the disclosed embodiments is provided to enable any person skilled in the art to make or use the present application. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the generic principles defined herein may be applied to other embodiments without departing from the spirit or scope of the application. Thus, the present application is not intended to be limited to the embodiments shown herein but is to be accorded the widest scope consistent with the principles and novel features disclosed herein.
Claims (9)
1. A binary random sequence detection method is applied to a detection device for installing an FFTW software package, and comprises the following steps:
obtaining a target binary random sequence from the undetected binary random sequences;
detecting the target binary random sequence in the FFTW software package to obtain a detection result of the target binary random sequence;
the detecting the target binary random sequence to obtain a detection result of the target binary random sequence includes:
converting bit 0 in the target binary random sequence into a numerical value-1, and converting bit 1 into a numerical value 1 to obtain a converted binary random sequence;
performing discrete Fourier transform on the converted binary random sequence through an fftw _ execute function to obtain a complex number group;
calculating the modulus value of the first part of the complex numbers in the complex number group;
counting a first number value of the complex numbers with the modulus value smaller than a threshold value;
calculating a statistic based on the first number value and a total number value of complex numbers in the complex set;
comparing the statistical value with a preset significance level value to obtain a detection result of the target binary random sequence;
wherein, converting bit 0 in the target binary random sequence into a value-1 and converting bit 1 into a value 1 to obtain a converted binary random sequence, includes:
analyzing the representation type of the target binary random sequence;
if the representation type of the target binary random sequence is bit representation, converting the target binary random sequence into the conversion binary random sequence in a preset first lookup table through a first lookup formula;
the first lookup formula includes: xi＝Z[εi]；
Wherein epsiloniRepresenting the ith element in the target binary random sequence; xiRepresenting the ith element in the transformed binary random sequence; z represents the first lookup table, and Z [0 ]]＝-1，Z[1]＝1；
Or
Analyzing the representation type of the target binary random sequence;
if the representation type of the target binary random sequence is byte representation, converting the target binary random sequence into the conversion binary random sequence through a second lookup formula in a preset second lookup table;
the second lookup formula includes: xi＝U[i]；
Wherein i represents the ith byte in the target binary random sequence; xiRepresenting the ith element in the transformed binary random sequence; u denotes the second look-up table, Ud]＝(y0,y1,y2,...y7) D represents an element in the second lookup table, and yj＝2ej-1,0≤j≤7，ejRepresents the j-th bit of d, and d is more than or equal to 0 and less than or equal to 255.
2. The method of claim 1, wherein the calculating the modulus values of the first half of the complex numbers in the complex number set comprises:
and calculating the square value of each modulus value of the first half of the plurality of groups.
3. The method of claim 2, wherein the first number of complex numbers having the statistical modulus value less than the threshold value comprises:
calculating a square value of the threshold value;
among the plurality of values, the first number value of the square value of the statistical modulus value is smaller than the square value of the threshold value.
4. The method of claim 3, wherein the calculating statistics based on the first number value and a total number value of the complex numbers in the complex number set comprises:
calculating the statistic based on the first number value and a total number value of the complex numbers in the complex group by a statistic calculation formula;
the statistical value calculation formula includes:
wherein V represents the statistical value; n is a radical of1Representing the first number value; n represents the total number value.
5. The method of claim 1, wherein comparing the statistical value with a predetermined significance level value to obtain a detection result of the target binary random sequence comprises:
calculating a critical value based on the preset significance level value through a critical value calculation formula, wherein the critical value is a statistic value for distinguishing the type of the detection result;
judging whether the statistic value is smaller than the critical value, if so, obtaining a detection result indicating that the target binary random sequence passes the detection, and if not, obtaining a detection result indicating that the target binary random sequence does not pass the detection;
the critical value calculation formula includes: erfc (| V)B|/2)＝α；
Wherein, VBRepresenting the critical value; a represents the preset significance level value; erfc denotes the complementary error function.
6. The method of claim 1, wherein before obtaining a target binary random sequence among the undetected binary random sequences, further comprising:
allocating a detection space for binary random sequence detection through an fftw _ malloc function, and creating a detection scheme for binary random sequence detection through an fftw _ plan _ dft _ r2c _1d function;
after the target binary random sequence is detected to obtain a detection result of the target binary random sequence, the method further includes:
and judging whether an undetected binary random sequence exists, if so, returning to the step of executing the target binary random sequence in the undetected binary random sequence, and if not, releasing the detection space through the fftw _ free function.
7. A binary random sequence detection system for use in a detection device for installing an FFTW software package, comprising:
the first acquisition module is used for acquiring a target binary random sequence from the undetected binary random sequences;
the first detection module is used for detecting the target binary random sequence in the FFTW software package to obtain a detection result of the target binary random sequence;
wherein the first detection module comprises:
the first conversion submodule is used for converting a bit 0 in the target binary random sequence into a numerical value-1, and converting a bit 1 into a numerical value 1 to obtain a conversion binary random sequence;
the first transformation submodule is used for performing discrete Fourier transformation on the transformed binary random sequence through an fftw _ execute function to obtain a complex number group;
a first calculating submodule for calculating respective modulus values of the first half of the plurality of sets of the plurality of numbers;
the first statistic submodule is used for counting a first number value of the complex numbers of which the modulus values are smaller than a threshold value;
a second computation submodule for computing a statistical value based on the first number value and a total number value of the complex numbers in the complex number group;
the first comparison submodule is used for comparing the statistical value with a preset significance level value to obtain a detection result of the target binary random sequence;
wherein the first conversion submodule comprises:
the first analysis unit is used for analyzing the representation type of the target binary random sequence;
a first conversion unit, configured to, if the representation type of the target binary random sequence is bit representation, convert the target binary random sequence into the conversion binary random sequence through a first lookup formula in a preset first lookup table;
the first lookup formula includes: xi＝Z[εi]；
Wherein epsiloniRepresenting the ith element in the target binary random sequence; xiRepresenting the ith element in the transformed binary random sequence; z represents the first lookup table, and Z [0 ]]＝-1，Z[1]＝1；
Or
The second analysis unit is used for analyzing the representation type of the target binary random sequence;
the second conversion unit is used for converting the target binary random sequence into the conversion binary random sequence through a second lookup formula in a preset second lookup table if the representation type of the target binary random sequence is byte representation;
the second lookup formula includes: xi＝U[i]；
Wherein i represents the ith byte in the target binary random sequence; xiRepresenting the ith element in the transformed binary random sequence; u denotes the second look-up table, Ud]＝(y0,y1,y2,...y7) D represents an element in the second lookup table, and yj＝2ej-1,0≤j≤7，ejRepresents the j-th bit of d, and d is more than or equal to 0 and less than or equal to 255.
8. A binary random sequence detection device, wherein a FFTW software package is installed, comprising:
a memory for storing a computer program;
a processor for implementing the steps of the binary random sequence detection method according to any one of claims 1 to 6 when executing said computer program.
9. A computer-readable storage medium, in which a computer program is stored which, when being executed by a processor, carries out the steps of the binary random sequence detection method according to any one of claims 1 to 6.
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