Civil aviation 5G network security data storage method and system and electronic equipment

Abstract

The invention relates to the technical field of network data security storage, in particular to a civil aviation 5G network security data storage method and system and electronic equipment. The method comprises the following steps: acquiring operation data of an aircraft at each moment; according to the change difference between each type of operation data and the environment data, obtaining an environment response value of each type of operation data; decomposing the operation data curve into IMF components, and obtaining a storage degree value of each type of operation data at each moment according to distribution of component data in the IMF components and instantaneous frequency at each moment in the IMF components; and according to the environment response value and the storage degree value, obtaining a storage response value of each type of operation data at each moment, and storing each type of operation data in a preset time period. According to the method, the storage response value of each type of operation data at each moment is accurately obtained, and the operation data is accurately and efficiently stored in sequence, so that the network congestion condition is avoided, and the safety and integrity of the operation data are ensured.

Description

Technical Field

[0001] The present invention relates to the technical field of network data security storage, and particularly to a civil aviation 5G network security data storage method, system and electronic device. Background Art

[0002] With the digital transformation in the civil aviation field and the wide application of 5G network technology, the importance of data security in the aviation field has become increasingly prominent. In the civil aviation field, 5G network technology has begun to be applied. The 5G network can not only provide higher bandwidth and lower latency, but also has the ability to connect a large number of devices, which is of great significance for the networking and intelligent development of avionics equipment. Among them, civil aviation 5G network security data refers to all kinds of operation data related to civil aviation security transmitted and processed through the 5G network in the civil aviation field, such as engine speed data, engine temperature data, engine pressure data and other various operation data of aircraft. It is known that the amount of civil aviation 5G network security data is huge. In order to better manage and call civil aviation 5G network security data, it is necessary to perform real-time processing and storage on civil aviation 5G network security data to ensure the security and integrity of civil aviation 5G network security data.

[0003] In the existing methods, civil aviation 5G network security data is directly stored. However, in actual situations, due to the huge amount of civil aviation 5G network security data information, there is a situation where it is impossible to perform real-time storage on civil aviation 5G network security data. Instead, it is easy to have network congestion or interruption during the storage of civil aviation 5G network security data, which may lead to the leakage or loss of civil aviation 5G network security data, unable to ensure the security and integrity of civil aviation 5G network security data, not conducive to subsequent processing of civil aviation 5G network security data, unable to respond to abnormal operation data in a timely manner, and thus unable to detect abnormal situations of aircraft in a timely manner. Summary of the Invention

[0004] In order to solve the technical problem that network congestion or interruption is likely to occur during the storage of civil aviation 5G network security data, which may lead to the leakage or loss of civil aviation 5G network security data and unable to ensure the security and integrity of civil aviation 5G network security data, the purpose of the present invention is to provide a civil aviation 5G network security data storage method, system and electronic device, and the specific technical solutions adopted are as follows:

[0005] In the first aspect, an embodiment of the present invention provides a civil aviation 5G network security data storage method, and the method includes the following steps:

[0006] Obtain each type of operation data and each type of environmental data of the aircraft at each moment within a preset time period;

[0007] Each type of operation data and each type of environmental data within a preset time period are each fitted to a curve to obtain each operation data curve and each environmental data curve; according to the variation differences between each operation data curve and each environmental data curve, the environmental response value of each type of operation data is obtained.

[0008] Each operation data curve is decomposed into IMF components, and each data in the IMF components is used as component data. According to the differences between each component data and every other component data in its IMF component, as well as the distribution of the component data with the same size as each component data in the IMF component where each component data is located, the special degree value of each component data is obtained; according to the special degree values of the component data at the same moment in all IMF components after decomposition of any operation data curve and the variation of the instantaneous frequency at the same moment, the storage degree value of this type of operation data at the corresponding moment is obtained.

[0009] According to the environmental response value of each type of operation data and the storage degree value of each type of operation data at each moment, the storage response value of each type of operation data at each moment is obtained.

[0010] Based on the storage response value, each type of operation data within the preset time period is stored.

[0011] Furthermore, the method for obtaining the environmental response value is as follows:

[0012] The tangent slope of each data in each data curve is obtained. According to the difference in tangent slope between adjacent two data in each data curve and the difference between the maximum amplitude and the minimum amplitude in each data curve, the fluctuation degree value of each data curve is obtained.

[0013] According to the difference in fluctuation degree value between each operation data curve and each environmental data curve, as well as the difference in the moment corresponding to the maximum amplitude, the environmental response value of each type of operation data is obtained.

[0014] Furthermore, the calculation formula for the fluctuation degree value is:

[0015] where T r is the fluctuation degree value of the r-th data curve; N is the total number of data in the r-th data curve; K r,n is the tangent slope of the n-th data in the r-th data curve; K r,n+1 is the tangent slope of the (n + 1)-th data in the r-th data curve; H r,max is the maximum amplitude in the r-th data curve; H r,min is the minimum amplitude in the r-th data curve; || is the absolute value function.

[0016] Furthermore, the calculation formula for the environmental response value is:

[0017] In the formula, J k is the environmental response value of the k-th kind of operation data; I is the total number of environmental data types; T k is the fluctuation degree value of the k-th kind of operation data curve; T i is the fluctuation degree value of the i-th kind of environmental data curve; is the moment corresponding to the maximum amplitude in the k-th kind of operation data curve; is the moment corresponding to the maximum amplitude in the i-th kind of environmental data curve; || is the absolute value function.

[0018] Furthermore, the method for obtaining the special degree value is as follows:

[0019] For any component data, the differences between this component data and each other component data in the IMF component where it is located are all taken as the first differences;

[0020] The number of all component data with the same size as this component data in the IMF component where this component data is located is taken as the first quantity;

[0021] According to the ratio of the total number of all component data in the IMF component where this component data is located to the first quantity, and the mean value of the first differences, the special degree value of this component data is obtained; wherein, the ratio of the total number of all component data in the IMF component where this component data is located to the first quantity, and the mean value of the first differences are both positively correlated with the special degree value.

[0022] Furthermore, the method for obtaining the storage degree value is as follows:

[0023] Perform Hilbert transform on each IMF component to obtain the instantaneous frequency at each moment in each IMF component;

[0024] For any kind of operation data curve, the instantaneous frequencies at the same moment in each IMF component after decomposing this kind of operation data curve are sequentially constructed into a sequence, as the instantaneous frequency sequence of this kind of operation data at the corresponding moment;

[0025] The serial numbers of all IMF components after decomposing this kind of operation data curve are sequentially constructed into a serial number sequence;

[0026] The result of taking the absolute value of the correlation coefficient between the instantaneous frequency sequence of this kind of operation data at each moment and the serial number sequence and making it negatively correlated is used as the first eigenvalue of this kind of operation data at each moment;

[0027] According to the mean of the special degree values ​​of the component data at the same time in all IMF components after the decomposition of the operation data curve and the first eigenvalue of the operation data at the same time, the storage degree value of the operation data at the corresponding time is obtained; wherein, the mean of the special degree value and the first eigenvalue are positively correlated with the storage degree value.

[0028] Furthermore, the method for obtaining the stored response value is:

[0029] The environmental response value and the storage degree value are both positively correlated with the storage response value.

[0030] Furthermore, the method for storing each type of operation data within a preset time period based on the stored response value is:

[0031] The storage response value of each type of operation data at each moment in the preset time period is obtained, and each type of operation data at the corresponding moment is stored in sequence according to the storage response value from large to small.

[0032] In a second aspect, an embodiment of the present invention provides a civil aviation 5G network security data storage system, the system comprising a data acquisition module, an environmental response value acquisition module, a storage degree value acquisition module, a storage response value acquisition module and a data processing module:

[0033] A data acquisition module, used to acquire each type of operation data and each type of environmental data of the aircraft at each moment within a preset time period;

[0034] The environmental response value acquisition module is used to fit each operating data and each environmental data within a preset time period into a curve to obtain each operating data curve and each environmental data curve; according to the change difference between each operating data curve and each environmental data curve, the environmental response value of each operating data is obtained;

[0035] The storage degree value acquisition module is used to decompose each operation data curve into IMF components, take each data in the IMF component as component data, and obtain the special degree value of each component data according to the difference between each component data and each other component data in the IMF component where it is located, and the distribution of component data with the same size as each component data in the IMF component where each component data is located; according to the special degree value of the component data at the same time in all IMF components after any operation data curve is decomposed and the change of the instantaneous frequency at the same time, obtain the storage degree value of the operation data at the corresponding time;

[0036] A storage response value acquisition module, used to acquire the storage response value of each operating data at each moment according to the environmental response value of each operating data and the storage degree value of each operating data at each moment;

[0037] A data processing module, configured to store each type of operation data within a preset time period based on the stored response value.

[0038] In a third aspect, an embodiment of the present invention provides a civil aviation 5G network security data storage electronic device, including a memory, a processor, and a computer program stored on the memory and executable on the processor. When the processor executes the program, the steps of any of the above methods are implemented.

[0039] In a fourth aspect, an embodiment of the present invention provides a computer-readable storage medium, on which a computer program is stored. When the program is executed by a processor, the steps of any of the above methods are implemented.

[0040] The present invention has the following beneficial effects:

[0041] Each type of operation data and each type of environmental data within a preset time period are each fitted into a curve to obtain each operation data curve and each environmental data curve, which is convenient for more accurate and efficient analysis of the changes in each type of operation data and each type of environmental data within the preset time period; furthermore, according to the change differences between each operation data curve and each environmental data curve, the environmental response value of each type of operation data is obtained, the degree to which each type of operation data is affected by environmental factors is determined, and the possibility of each type of operation data being preferentially stored is initially determined; in order to more accurately determine the priority storage order of each operation data, further according to the differences between each component data and other each component data in its IMF component, and the distribution of component data with the same size as each component data in the IMF component where each component data is located, the special degree value of each component data is obtained, which accurately reflects the importance degree of the information represented by each component data, and prepares for accurately determining the priority storage degree of each operation data. Furthermore, according to the change conditions of the special degree values of the component data at the same moment and the instantaneous frequency at the same moment in all IMF components after the decomposition of any operation data curve, the storage degree value of this type of operation data at the corresponding moment is obtained, and the possibility of each type of operation data being preferentially stored at each moment is initially determined; further according to the environmental response value of each type of operation data and the storage degree value of each type of operation data at each moment, the storage response value of each type of operation data at each moment is obtained, which is beneficial to accurately classify and store the operation data in sequence, ensure that important operation data is preferentially stored, avoid network congestion and interruption phenomena during the storage process, and then store each type of operation data within the preset time period based on the storage response value, ensuring the security and integrity of the operation data, and being beneficial to accurately analyze the operation state of the aircraft based on the stored operation data. Description of the Drawings

[0042] To more clearly illustrate the technical solutions and advantages in the embodiments of the present invention or the prior art, the following will briefly introduce the drawings required for the description of the embodiments or the prior art. Obviously, the drawings in the following description are only some embodiments of the present invention. For those of ordinary skill in the art, without creative efforts, other drawings can be obtained based on these drawings.

[0043] Figure 1 The flowchart of a method for storing civil aviation 5G network security data provided by an embodiment of the present invention;

[0044] Figure 2 The flowchart of a method for obtaining an environmental response value provided by an embodiment of the present invention;

[0045] Figure 3 The structural diagram of a system for storing civil aviation 5G network security data provided by an embodiment of the present invention;

[0046] Figure 4 The schematic diagram of an electronic device for storing civil aviation 5G network security data provided by an embodiment of the present invention. Detailed implementation manners

[0047] To further elaborate on the technical means and effects adopted by the present invention to achieve the intended invention purpose, the following, in conjunction with the accompanying drawings and preferred embodiments, details the specific implementation manners, structures, features, and effects of a method, system, and electronic device for storing civil aviation 5G network security data proposed according to the present invention. In the following description, different "one embodiment" or "another embodiment" do not necessarily refer to the same embodiment. In addition, the specific features, structures, or characteristics in one or more embodiments can be combined in any suitable form.

[0048] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by those of ordinary skill in the technical field to which the present invention belongs.

[0049] The following specifically describes the specific solution of a method for storing civil aviation 5G network security data provided by the present invention in conjunction with the accompanying drawings.

[0050] Embodiment 1: This embodiment discloses a method for storing civil aviation 5G network security data;

[0051] Please refer to Figure 1 , which shows the flowchart of a method for storing civil aviation 5G network security data provided by an embodiment of the present invention. The method includes the following steps:

[0052] Step S1: Obtain each type of operation data and each type of environmental data of the aircraft at each moment within a preset time period.

[0053] Specifically, in this embodiment, an operating aircraft is taken as an example for analysis, and all subsequent aircraft mentioned represent this aircraft. Various sensors are installed on the engine of the aircraft to obtain various operating data of the aircraft at each moment within a preset time period, such as engine speed data, engine temperature data, engine pressure data, and various other operating data of the aircraft. To optimize the storage of operating data subsequently and accurately screen out the operating data with important features, various environmental data of the aircraft at each moment within the preset time period are then obtained through the environmental monitoring system in the aircraft, such as wind speed data, humidity data, temperature data, and various other environmental data. In this embodiment, the preset time period is set to 30 minutes, and the time interval between two adjacent moments is set to 0.1 second. The implementer can set the size of the preset time period and the time interval between two adjacent moments according to the actual situation, which is not limited herein.

[0054] It is known that the amount of information of the operating data within the preset time period is huge. To avoid network congestion or delay during the storage of the operating data within the preset time period, resulting in the leakage or loss of network security data, i.e., operating data, therefore, in this embodiment, the variation differences between each type of operating data and each type of environmental data within the preset time period are first analyzed. When the variation situations between a certain type of operating data and each type of environmental data are all similar, it indicates that this type of operating data is more susceptible to environmental factors. For accurate analysis of the aircraft, this type of operating data should be stored preferentially. Furthermore, according to the variation differences between each type of operating data and each type of environmental data within the preset time period, the environmental response value of each type of operating data is obtained. The larger the environmental response value, the more the corresponding type of operating data should be stored preferentially. To preferentially store the operating data with important features and ensure the integrity of the information represented by the operating data to the greatest extent, in this embodiment, each type of operating data at each moment within the preset time period is further analyzed to obtain the storage degree value of each type of operating data at each moment. Among them, the larger the storage degree value, the greater the importance of the corresponding type of operating data at the corresponding moment and the more it should be stored preferentially. Therefore, further according to the environmental response value of each type of operating data and the storage degree value of each type of operating data at each moment, the storage response value of each type of operating data at each moment is obtained. Among them, the larger the storage response value, the more the corresponding type of operating data at the corresponding moment should be stored preferentially. Therefore, the operating data within the preset time period is accurately stored in sequence according to the storage response value, avoiding network congestion or delay phenomena, facilitating the orderly storage of the operating data according to the importance level, ensuring the security and integrity of the operating data, and facilitating the accurate analysis of the operating conditions of the aircraft based on the stored operating data.

[0055] Step S2: Fit each piece of operation data and each piece of environmental data within a preset time period into curves to obtain each operation data curve and each environmental data curve; according to the variation differences between each operation data curve and each environmental data curve, obtain the environmental response value of each piece of operation data.

[0056] Specifically, in order to accurately and efficiently analyze the variation of each piece of operation data and each piece of environmental data within a preset time period, in this embodiment, each piece of operation data and each piece of environmental data within the preset time period are both fitted into curves to obtain each operation data curve and each environmental data curve. Among them, the curve fitting method is a well-known technology and will not be elaborated here. It is known that the operation data that is more affected by environmental factors needs to be accurately controlled during the operation of the aircraft to make the operation of the aircraft more stable. Therefore, when storing the operation data, the operation data that is greatly affected by environmental factors needs to be stored preferentially to ensure accurate analysis of the operation characteristics of the aircraft subsequently. Furthermore, in this embodiment, the variation differences between each operation data curve and each environmental data curve are analyzed. When the variation of a certain operation data curve is more similar to the variation of each environmental data curve, it indicates that the degree of influence of this operation data by the environment is greater, and this operation data should be stored preferentially. Therefore, according to the variation differences between each operation data curve and each environmental data curve, obtain the environmental response value of each piece of operation data. The larger the environmental response value, the greater the degree of influence of the corresponding type of operation data by the environment, the more it can reflect the operation characteristics of the aircraft, and the more it should be stored preferentially.

[0057] Preferably, in some possible implementation manners of this embodiment, standardize the fluctuation ranges of each operation data curve and each environmental data curve so that the fluctuation ranges of each operation data curve and each environmental data curve are the same, which is beneficial to more accurately analyze the variation differences between each operation data curve and each environmental data curve. Among them, the method for standardizing the fluctuation range is a well-known technology and will not be elaborated here.

[0058] Preferably, in some possible implementation manners of this embodiment, for the method of obtaining the environmental response value, please refer to Figure 2 which shows a flowchart of a method for obtaining an environmental response value provided by an embodiment of the present invention. The method includes:

[0059] Step S201: Obtain the tangent slope of each data in each data curve, and according to the difference in the tangent slopes between adjacent two data in each data curve and the difference between the maximum amplitude and the minimum amplitude in each data curve, obtain the fluctuation degree value of each data curve.

[0060] In order to accurately and detailedly analyze the variation of each data curve, and then obtain the tangent slope of each data in each data curve. The method for obtaining the tangent slope is a well-known technology and will not be elaborated here. When the difference in the tangent slope between any two adjacent data in a certain data curve is greater, it indicates that the fluctuation degree of this data curve is greater. In order to more accurately reflect the fluctuation degree of each data curve, the difference between the maximum amplitude and the minimum amplitude in each data curve is further obtained. When the difference between the maximum amplitude and the minimum amplitude in a certain data curve is greater, it indicates that the fluctuation degree of this data curve is greater. Therefore, in this embodiment, according to the difference in the tangent slope between two adjacent data in each data curve and the difference between the maximum amplitude and the minimum amplitude in each data curve, the fluctuation degree value of each data curve is obtained. The greater the fluctuation degree value, the more unstable the corresponding curve is within the preset time period.

[0061] As an example, taking the r-th data curve as an example, the calculation formula for obtaining the fluctuation degree value of the r-th data curve is:

[0062] In the formula, T r is the fluctuation degree value of the r-th data curve; N is the total number of data in the r-th data curve; K r,n is the tangent slope of the n-th data in the r-th data curve; K r,n+1 is the tangent slope of the (n + 1)-th data in the r-th data curve; H r,max is the maximum amplitude in the r-th data curve; H r,min is the minimum amplitude in the r-th data curve; || is the absolute value function.

[0063] It should be noted that the larger |K r,n -K r,n+1 | is, the greater the difference between K r,n and K r,n+1 , the more inconsistent the change trend between the n-th data and the (n + 1)-th data in the r-th data curve, indirectly indicating that the fluctuation degree of the r-th data curve is greater, and T r is larger; H r,max -H r,min must be greater than or equal to 0. The larger H r,max -H r,min is, the greater the difference between H r,max and H r,min , indicating that the change range of the r-th data curve is larger, that is, the fluctuation degree of the r-th data curve is greater, and T r is larger; Therefore, the larger T r is, the greater the fluctuation degree of the r-th data curve.

[0064] According to the method for obtaining the fluctuation degree value of the r-th data curve, obtain the fluctuation degree values of each operating data curve and each environmental data curve.

[0065] Step S202: Obtain the environmental response value of each operating data according to the difference in the fluctuation degree values between each operating data curve and each environmental data curve, and the difference in the corresponding moments of the maximum amplitudes.

[0066] When the differences in the fluctuation degree values between a certain operating data curve and each environmental data curve are all smaller, it indicates that the change situation of this operating data is more consistent with the change situation of the environmental data, and the degree to which this operating data is affected by the environment may be greater. To more accurately analyze the change consistency between each operating data and each environmental data, in this embodiment, the difference in the corresponding moments of the maximum amplitudes between each operating data curve and each environmental data curve is further obtained. When the corresponding moments of the maximum amplitudes between a certain operating data curve and each environmental data curve are all closer, it indicates that the change situation of this operating data is more consistent with the environmental data, indirectly indicating that the degree to which this operating data is affected by the environment may be greater. It should be noted that if there are multiple maximum amplitudes in a certain data curve, the mean value of the corresponding moments of the maximum amplitudes in this data curve is obtained as the corresponding moment of the maximum amplitude in this data curve. Therefore, in this embodiment, the environmental response value of each operating data is obtained according to the difference in the fluctuation degree values between each operating data curve and each environmental data curve, and the difference in the corresponding moments of the maximum amplitudes. Among them, the larger the environmental response value, the greater the degree to which the corresponding type of operating data is affected by the environment, the more it can reflect the operating characteristics of the aircraft, and the more it should be preferentially stored.

[0067] As an example, taking the k-th operating data as an example, the calculation formula for obtaining the environmental response value of the k-th operating data is:

[0068] In the formula, J k is the environmental response value of the k-th operating data; I is the total number of environmental data types; T k is the fluctuation degree value of the k-th operating data curve; T i is the fluctuation degree value of the i-th environmental data curve; is the moment corresponding to the maximum amplitude in the k-th operating data curve; is the moment corresponding to the maximum amplitude in the i-th environmental data curve; || is the absolute value function.

[0069] It should be noted that The smaller, The smaller it is, it indicates that the variation of the k-th type of operation data within the preset time period is more similar to that of each type of environmental data, indirectly indicating that the k-th type of operation data is more affected by environmental factors, J k The larger it is; therefore, J k The larger it is, it indicates that the k-th type of operation data can better reflect the characteristics of the aircraft's operation data, and the k-th type of operation data should be preferentially stored.

[0070] According to the method for obtaining the environmental response value of the k-th type of operation data, obtain the environmental response value of each type of operation data.

[0071] Step S3: Decompose each operation data curve into IMF components, and take each data in the IMF components as component data. According to the difference between each component data and every other component data in its IMF component, as well as the distribution of the component data with the same size as each component data in the IMF component where each component data is located, obtain the special degree value of each component data; according to the change of the special degree value of the component data at the same moment and the instantaneous frequency at the same moment among all the IMF components after the decomposition of any operation data curve, obtain the storage degree value of this type of operation data at the corresponding moment.

[0072] Specifically, to further ensure that each operation data with important features is preferentially stored, in this embodiment, each operation data in each operation data curve is analyzed to preliminarily predict the importance degree of each operation data. To accurately analyze each operation data, in this embodiment, each operation data curve is decomposed by the empirical mode decomposition algorithm, and each operation data curve is decomposed into IMF (Intrinsic Mode Functions) components. For better description, each data in the IMF component is regarded as component data. Among them, the empirical mode decomposition algorithm is a well-known technology and will not be elaborated here. Analyze each component data. When the difference between a certain component data and each other component data in its corresponding IMF component is larger, it indicates that the component data is more special, indirectly indicating that the corresponding type of operation data at the corresponding moment of the component data is more special and should be preferentially stored. To more accurately analyze the characteristic situation of each component data, and then obtain the distribution of component data with the same size as each component data in the IMF component where each component data is located. When the number of component data with the same size as a certain component data in its corresponding IMF component is smaller, it indicates that the component data is more special in its corresponding IMF component. Therefore, in this embodiment, according to the difference between each component data and each other component data in its corresponding IMF component, and the distribution of component data with the same size as each component data in the IMF component where each component data is located, the special degree value of each component data is obtained. Among them, the larger the special degree value, the more special the corresponding component data, indirectly indicating that the corresponding type of operation data at the corresponding moment of the corresponding component data should be preferentially stored.

[0073] To clearly illustrate the analysis of each piece of operation data, this embodiment takes the y-th type of operation data at the q-th moment within a preset time period as an example for analysis. Hilbert transform is performed on each IMF component of the y-th type of operation data curve within the preset time period to obtain the instantaneous frequency at each moment in each IMF component. Among them, the Hilbert transform is a well-known technology and will not be elaborated further. It should be noted that the component data at the q-th moment in each IMF component decomposed from the y-th type of operation data curve are all the decomposition results corresponding to the y-th type of operation data at the q-th moment. Therefore, when the special degree values of the component data at the q-th moment in all IMF components of the y-th type of operation data curve are all larger, it indicates that the y-th type of operation data at the q-th moment should be given priority for storage. It is known that according to the decomposition rule of the empirical mode decomposition algorithm, the IMF components decomposed from the y-th type of operation data curve are arranged in the order from high frequency to low frequency. Then, the instantaneous frequencies at the q-th moment in the corresponding IMF components should also be in the order from high to low. At the same time, the serial numbers of the IMF components decomposed from the y-th type of operation data curve are from small to large. To more accurately analyze the particularity of the y-th type of operation data at the q-th moment, this embodiment analyzes the variation law of the instantaneous frequencies at the q-th moment in all IMF components decomposed from the y-th type of operation data curve. When the variation law of the instantaneous frequencies does not conform to the decomposition rule of the empirical mode decomposition algorithm, it indicates that the y-th type of operation data at the q-th moment is more special and should be given priority for storage. Therefore, this embodiment obtains the storage degree value of this type of operation data at the corresponding moment according to the special degree value of the component data at the same moment in all IMF components decomposed from any operation data curve and the variation of the instantaneous frequencies at the same moment. The larger the storage degree value, the more the corresponding type of operation data at the corresponding moment should be given priority for storage.

[0074] Preferably, in some possible implementation manners of this embodiment, the method for obtaining the special degree value is as follows: for any component data, obtaining the differences between this component data and each other component data in its IMF component where it is located are all used as the first differences; when the first differences are all larger, it indicates that this component data is more special in its IMF component where it is located, and the information reflected by this component data is more likely to be important. In order to more accurately reflect the particularity of this component data in its IMF component where it is located, this embodiment obtains the number of all component data with the same size as this component data in the IMF component where this component data is located as the first quantity; when the first quantity is smaller, it indicates that the distinctiveness of this component data in its IMF component where it is located is higher, that is, more special. Therefore, this embodiment obtains the special degree value of this component data according to the ratio of the total number of all component data in the IMF component where this component data is located to the first quantity, and the average value of the first differences. The larger the special degree value is, the more special this component data is, and the information reflected may be more important. Among them, the ratio of the total number of all component data in the IMF component where this component data is located to the first quantity, and the average value of the first differences are both positively correlated with the special degree value.

[0075] As an example, taking the ath component data in the pth IMF component as an example, the calculation formula for obtaining the special degree value of the ath component data in the pth IMF component is:

[0076] In the formula, V p,a is the special degree value of the ath component data in the pth IMF component; G p is the total number of all component data in the pth IMF component; g p,a is the first quantity; M is the total number of all other component data except the ath component data in the pth IMF component; h p,a is the ath component data in the pth IMF component; h p,m is the mth component data except the ath component data in the pth IMF component; || is the absolute value function; |h p,a -h p,m | is the first difference; norm is the normalization function.

[0077] It should be noted that the smaller g p,a is, the more special the ath component data in the pth IMF component is, the larger, the larger V p,a is; the larger the first difference |h p,a -h p,m | is, the larger the difference between the ath component data and the mth component data in the pth IMF component is, the larger, the more special the ath component data in the pth IMF component is, Vp,a The larger it is; thus, V p,a The larger V is, the more abnormal the information reflected by the a-th component data in the p-th IMF component is, and the corresponding type of operation data at the corresponding moment of the a-th component data should be preferentially stored to ensure that important information is not lost or leaked.

[0078] According to the method for obtaining the special degree value of the a-th component data in the p-th IMF component, obtain the special degree value of each component data in each IMF component.

[0079] Preferably, in some possible implementation manners of this embodiment, the method for obtaining the storage degree value is: for any operation data curve, the instantaneous frequencies at the same moment in each IMF component after decomposing the operation data curve are sequentially constructed into a sequence as the instantaneous frequency sequence of the operation data at the corresponding moment; the serial numbers of all IMF components after decomposing the operation data curve are sequentially constructed into a serial number sequence; the absolute value of the correlation coefficient between the instantaneous frequency sequence and the serial number sequence of the operation data at each moment is negatively correlated as the first eigenvalue of the operation data at each moment; according to the mean value of the special degree values of the component data at the same moment in all IMF components after decomposing the operation data curve and the first eigenvalue of the operation data at the same moment, obtain the storage degree value of the operation data at the corresponding moment; where the mean value of the special degree value and the first eigenvalue are both positively correlated with the storage degree value.

[0080] As an example, taking the y-th operation data at the q-th moment as an example, the serial numbers corresponding to the IMF components after decomposing the y-th operation data curve are 1, 2, 3... in sequence. In this embodiment, the IMF components after decomposing the y-th operation data curve are arranged in sequence to construct a serial number sequence. The instantaneous frequencies at the q-th moment in each IMF component after decomposing the y-th operation data curve are sorted according to the decomposition order of the corresponding IMF component in sequence to obtain the instantaneous frequency sequence of the y-th operation data at the q-th moment. For example, if the y-th operation data curve is decomposed into 5 IMF components, from high frequency to low frequency are IMF1, IMF2, IMF3, IMF5, and IMF5 in sequence, then the serial number sequence is (1, 2, 3, 4, 5). Among them, the time periods corresponding to IMF1, IMF2, IMF3, IMF5, and IMF5 are the same and are all preset time periods. It is set that the instantaneous frequency at the q-th moment in IMF1 is l q1 and the instantaneous frequency at the q-th moment in IMF2 is l q2 and the instantaneous frequency at the q-th moment in IMF3 is l q3 and the instantaneous frequency at the q-th moment in IMF4 is l q4 and the instantaneous frequency at the q-th moment in IMF5 is l q5, then the instantaneous frequency sequence of the y-th operating data at the q-th moment is (l q1 , l q2 , l q3 , l q4 , l q5 ). Given that the decomposition rule of IMF components is from high frequency to low frequency, therefore, the order in (l q1 , l q2 , l q3 , l q4 , l q5 ) should also be from high to low. Among them, (1, 2, 3, 4, 5) is from small to large. Therefore, under normal circumstances, (1, 2, 3, 4, 5) and (l q1 , l q2 , l q3 , l q4 , l q5 ) are negatively correlated. The closer the correlation coefficient between (1, 2, 3, 4, 5) and (l q1 , l q2 , l q3 , l q4 , l q5 ) tends to -1. Among them, the method for obtaining the correlation coefficient is a well-known technology and will not be elaborated here. In summary, when the absolute value of the correlation coefficient between the serial number sequence and the instantaneous frequency sequence tends to 1, it indicates that the y-th operating data at the q-th moment is more normal. On the contrary, when the absolute value of the correlation coefficient between the serial number sequence and the instantaneous frequency sequence tends to 0, it indicates that the y-th operating data at the q-th moment is more special and needs to be stored. Therefore, in this embodiment, the negative correlation result of the absolute value of the correlation coefficient between the serial number sequence and the instantaneous frequency sequence is used as the first eigenvalue of the y-th operating data at the q-th moment. The larger the first eigenvalue, the more special the y-th operating data at the q-th moment and the more it needs to be preferentially stored. At the same time, when the special degree values of the component data at the q-th moment in all IMF components after the decomposition of the y-th operating data curve are all larger, it indicates that the information represented by the y-th operating data at the q-th moment is more important and the y-th operating data at the q-th moment should be preferentially stored. Therefore, in this embodiment, according to the mean value of the special degree values of the component data at the q-th moment in all IMF components after the decomposition of the y-th operating data curve and the first eigenvalue of the y-th operating data at the q-th moment, the storage degree value of the y-th operating data at the q-th moment is obtained; among them, both the mean value of the special degree value and the first eigenvalue are positively correlated with the storage degree value. The calculation formula for obtaining the storage degree value of the y-th operating data at the q-th moment in this embodiment is:

[0081] In the formula, S q,yis the storage level value of the y-th type of operation data at the q-th moment; B is the total number of IMF components obtained by decomposing the y-th type of operation data curve; is the specialness value of the component data at the q-th moment in the b-th IMF component obtained by decomposing the y-th type of operation data curve; γ q,y is the correlation coefficient between the instantaneous frequency sequence of the y-th type of operation data at the q-th moment and the sequence number sequence constructed by the IMF component sequence numbers obtained by decomposing the y-th type of operation data curve; β is the first preset constant, greater than 0; || is the absolute value function; is the first eigenvalue of the y-th type of operation data at the q-th moment.

[0082] In this embodiment, β is set to 1 to avoid a zero denominator. The implementer can set the value of β according to the actual situation, which is not limited here.

[0083] It should be noted that The larger, the more special the y-th type of operation data at the q-th moment, the more important the information represented by the y-th type of operation data at the q-th moment, and the more the y-th type of operation data at the q-th moment should be preferentially stored, S q,y The larger; |γ q,y | The smaller, the more the change of the instantaneous frequency in the instantaneous frequency sequence of the y-th type of operation data at the q-th moment does not conform to the correct situation, indirectly indicating that the y-th type of operation data at the q-th moment is more special, and the first eigenvalue The larger, the more the y-th type of operation data at the q-th moment should be preferentially stored, S q,y The larger; Therefore, S q,y The larger, the more important the y-th type of operation data at the q-th moment, and the more it should be preferentially stored. In other embodiments, S and The sum result of is used to obtain S q,y to ensure that and are both positively correlated with S q,y The method for obtaining S is not limited here. q,y

[0084] According to the method for obtaining the storage level value of the y-th type of operation data at the q-th moment, obtain the storage level values of each type of operation data at each moment.

[0085] Step S4: According to the environmental response value of each type of operation data and the storage level value of each type of operation data at each moment, obtain the storage response value of each type of operation data at each moment.

[0086] Specifically, it can be known from step S2 that the larger the environmental response value is, the greater the degree to which the corresponding type of operation data is affected by the environment, the more it can reflect the operation characteristics of the aircraft, and the more it should be preferentially stored. It can be known from step S3 that the larger the storage degree value is, the more the corresponding type of operation data at the corresponding moment should be preferentially stored. Therefore, in this embodiment, according to the environmental response value of each type of operation data and the storage degree value of each type of operation data at each moment, the storage response value of each type of operation data at each moment is obtained. The larger the storage response value is, the more accurately it indicates that the corresponding type of operation data at the corresponding moment should be preferentially stored. Among them, both the environmental response value and the storage degree value are positively correlated with the storage response value.

[0087] As an example, taking the y-th type of operation data at the q-th moment in step S3 as an example, the calculation formula for obtaining the storage response value of the y-th type of operation data at the q-th moment is:

[0088] In the formula, δ q,y is the storage response value of the y-th type of operation data at the q-th moment; J y is the environmental response value of the y-th type of operation data; S q,y is the storage degree value of the y-th type of operation data at the q-th moment.

[0089] In this embodiment, δ is obtained through q,y , and in other embodiments, δ y can be obtained through the product of J q,y and S y , or the sum of J q,y and S q,y , ensuring that both the environmental response value and the storage degree value are positively correlated with the storage response value. The method for obtaining the storage response value is not limited herein.

[0090] According to the method for obtaining the storage response value of the y-th type of operation data at the q-th moment, the storage response value of each type of operation data at each moment within the preset time period is obtained.

[0091] Step S5: Store each type of operation data within the preset time period based on the storage response value.

[0092] Specifically, the storage response value of each type of operation data at each moment within the preset time period is obtained, and according to the order from large to small of the storage response value, each type of operation data at the corresponding moment is stored in sequence, that is, the operation data with a large storage response value is preferentially stored, which can effectively manage the storage resources and improve the performance and security of the system.

[0093] Classify and store the operation data within a preset time period according to the storage response value, which can maximize the utilization of storage resources. Moreover, the system can more efficiently ensure that no network latency and congestion occur during the process of storing a large amount of operation data, avoiding the loss and leakage of operation data, and being beneficial to ensuring the integrity and security of operation data, i.e., network security data.

[0094] In summary, this embodiment obtains the operation data of the aircraft at each moment; obtains the environmental response value of each type of operation data according to the change difference between each type of operation data and environmental data; decomposes the operation data curve into IMF components, and obtains the storage degree value of each type of operation data at each moment according to the distribution of the component data in the IMF components and the instantaneous frequency at each moment in the IMF components; obtains the storage response value of each type of operation data at each moment according to the environmental response value and the storage degree value, and stores each type of operation data within the preset time period. By accurately obtaining the storage response value of each type of operation data at each moment, the present invention stores the operation data accurately and efficiently in sequence, avoiding network congestion and ensuring the security and integrity of the operation data.

[0095] Embodiment 2: This embodiment discloses a civil aviation 5G network security data storage system;

[0096] As Figure 3 shown, it shows a structural diagram of a civil aviation 5G network security data storage system provided in this embodiment. The system includes a data acquisition module 10, an environmental response value acquisition module 20, a storage degree value acquisition module 30, a storage response value acquisition module 40, and a data processing module 50:

[0097] The data acquisition module 10 is used to acquire each type of operation data and each type of environmental data of the aircraft at each moment within a preset time period.

[0098] The environmental response value acquisition module 20 is used to fit each type of operation data and each type of environmental data within a preset time period into curves, obtaining each type of operation data curve and each type of environmental data curve; and obtaining the environmental response value of each type of operation data according to the change difference between each type of operation data curve and each type of environmental data curve.

[0099] A storage degree value acquisition module 30 is configured to decompose each operation data curve into IMF components, use each data in the IMF components as component data, and obtain the special degree value of each component data according to the difference between each component data and each other component data in the IMF component where it is located, and the distribution of the component data with the same size as each component data in the IMF component where each component data is located; according to the special degree value of the component data at the same moment in all IMF components after decomposition of any operation data curve and the change of the instantaneous frequency at the same moment, obtain the storage degree value of this type of operation data at the corresponding moment.

[0100] A storage response value acquisition module 40 is configured to obtain the storage response value of each type of operation data at each moment according to the environmental response value of each type of operation data and the storage degree value of each type of operation data at each moment.

[0101] A data processing module 50 is configured to store each type of operation data within a preset time period based on the storage response value.

[0102] Embodiment 3: This embodiment discloses an electronic device for storing civil aviation 5G network security data. Please refer to Figure 4 , which includes a memory 401, a processor 402, and a computer program 403 stored in the memory 401 and executable on the processor 402. Among them, when the processor 402 executes the computer program 403, the steps of the method in any of the above embodiments are implemented. In the embodiments of the present application, the processor is the control center of the computer system, and can be the processor of a physical machine or the processor of a virtual machine.

[0103] Embodiment 4: This embodiment provides a computer-readable storage medium, on which a computer program is stored. When the program is executed by a processor, the steps of the method in any of the foregoing embodiments are implemented. Among them, the computer-readable storage medium may include, but is not limited to, any type of disk, including floppy disks, optical disks, DVDs, CD-ROMs, microdrives, and magneto-optical disks, ROMs, RAMs, EPROMs, EEPROMs, DRAMs, VRAMs, flash memory devices, magnetic cards or optical cards, nano-systems (including molecular memory ICs), or any type of medium or device suitable for storing instructions and / or data.

[0104] The steps involved in the above Embodiments 2, 3, and 4 correspond to those in Method Embodiment 1. For specific implementation manners, reference may be made to the relevant description part of Embodiment 1. The term "computer-readable storage medium" should be understood to include a single medium or multiple media including one or more instruction sets; it should also be understood to include any medium that can store, encode, or carry an instruction set for execution by a processor and enable the processor to execute any method in the present invention.

[0105] It should be noted that the above order of the embodiments of the present invention is only for description and does not represent the superiority or inferiority of the embodiments. The processes depicted in the drawings do not necessarily require the particular order or sequential order shown to achieve the desired results. In some embodiments, multitasking and parallel processing are also possible or may be advantageous.

[0106] Each embodiment in this specification is described in a progressive manner. For the same or similar parts among the embodiments, reference can be made to each other, and the key point of each embodiment is to illustrate the differences from other embodiments.

Claims

1. A civil aviation 5G network data storage method, characterized in that: The method comprises the following steps: Obtain each type of operation data and each type of environmental data of the aircraft at each moment within a preset time period; Fit each operating data and each environmental data within a preset time period into a curve to obtain each operating data curve and each environmental data curve; obtain the environmental response value of each operating data according to the change difference between each operating data curve and each environmental data curve; Decompose each operation data curve into IMF components, take each data in the IMF component as component data, and obtain the special degree value of each component data according to the difference between each component data and each other component data in the IMF component where it is located, and the distribution of component data with the same size as each component data in the IMF component where each component data is located; obtain the storage degree value of the operation data at the corresponding moment according to the special degree value of the component data at the same moment in all IMF components after any operation data curve is decomposed and the change of the instantaneous frequency at the same moment; According to the environmental response value of each operating data and the storage degree value of each operating data at each moment, the storage response value of each operating data at each moment is obtained; Each type of operation data within a preset time period is stored based on the stored response value.

2. A civil aviation 5G network data storage method as claimed in claim 1, characterized in that: The method for obtaining the environmental response value is: Obtain the tangent slope of each data in each data curve, and obtain the fluctuation degree value of each data curve according to the difference in the tangent slopes between two adjacent data in each data curve and the difference between the maximum amplitude and the minimum amplitude in each data curve; The environmental response value of each operating data is obtained according to the difference in fluctuation degree values ​​between each operating data curve and each environmental data curve, and the difference in the time corresponding to the maximum amplitude.

3. A civil aviation 5G network data storage method as claimed in claim 2, characterized in that: The calculation formula of the fluctuation degree value is: Where, T r is the fluctuation value of the rth data curve; N is the total number of data in the rth data curve; K r,n is the tangent slope of the nth data in the rth data curve; K r,n+1 is the tangent slope of the n+1th data in the rth data curve; H r,max is the maximum amplitude in the rth data curve; H r,min is the minimum amplitude in the rth data curve; || is the absolute value function.

4. A civil aviation 5G network data storage method as claimed in claim 2, characterized in that: The calculation formula of the environmental response value is: In the formula, J k is the environmental response value of the kth type of operating data; I is the total number of environmental data types; T k is the fluctuation value of the k-th operating data curve; T i is the fluctuation value of the i-th environmental data curve; t Hk,max is the time corresponding to the maximum amplitude in the k-th operating data curve; t Hi,max is the moment corresponding to the maximum amplitude in the i-th environmental data curve; || is the absolute value function.

5. A civil aviation 5G network data storage method as claimed in claim 1, characterized in that: The method for obtaining the special degree value is: For any component data, obtain the difference between the component data and each other component data in the IMF component to which it belongs, and take them as the first difference; Obtaining the number of all component data having the same size as the component data in the IMF component where the component data is located, as the first number; The special degree value of the component data is obtained based on the ratio of the total number of all component data in the IMF component where the component data is located to the first number, and the mean of the first difference; wherein the ratio of the total number of all component data in the IMF component where the component data is located to the first number, and the mean of the first difference are positively correlated with the special degree value.

6. A civil aviation 5G network data storage method as claimed in claim 1, characterized in that: The method for obtaining the storage level value is: Perform Hilbert transform on each IMF component to obtain the instantaneous frequency of each IMF component at each moment; For any operating data curve, the instantaneous frequency at the same time in each IMF component after decomposing the operating data curve is sequentially constructed into a sequence as the instantaneous frequency sequence of the operating data at the corresponding time; The serial numbers of all IMF components after decomposing the operation data curve are sequentially constructed into a serial number sequence; The result of negatively correlating the absolute value of the correlation coefficient between the instantaneous frequency sequence of the operation data at each moment and the sequence number sequence is used as the first eigenvalue of the operation data at each moment; According to the mean of the special degree values ​​of the component data at the same time in all IMF components after the decomposition of the operation data curve and the first eigenvalue of the operation data at the same time, the storage degree value of the operation data at the corresponding time is obtained; wherein, the mean of the special degree value and the first eigenvalue are positively correlated with the storage degree value.

7. A civil aviation 5G network data storage method as claimed in claim 1, characterized in that: The method for obtaining the stored response value is: The environmental response value and the storage degree value are both positively correlated with the storage response value.

8. A civil aviation 5G network data storage method as claimed in claim 1, characterized in that: The method for storing each type of operation data within a preset time period based on the stored response value is: The storage response value of each type of operation data at each moment in the preset time period is obtained, and each type of operation data at the corresponding moment is stored in sequence according to the storage response value from large to small.

9. A civil aviation 5G network security data storage system, characterized by: It includes data acquisition module, environmental response value acquisition module, storage degree value acquisition module, storage response value acquisition module and data processing module: A data acquisition module, used to acquire each type of operation data and each type of environmental data of the aircraft at each moment within a preset time period; The environmental response value acquisition module is used to fit each operating data and each environmental data within a preset time period into a curve to obtain each operating data curve and each environmental data curve; according to the change difference between each operating data curve and each environmental data curve, the environmental response value of each operating data is obtained; A storage degree value acquisition module is used to decompose each operation data curve into IMF components, take each data in the IMF component as component data, and acquire the special degree value of each component data according to the difference between each component data and each other component data in the IMF component where it is located, and the distribution of component data with the same size as each component data in the IMF component where each component data is located; According to the special degree values ​​of the component data at the same time in all IMF components after decomposition of any operation data curve and the change of the instantaneous frequency at the same time, the storage degree value of the operation data at the corresponding time is obtained; A storage response value acquisition module, used to acquire the storage response value of each operating data at each moment according to the environmental response value of each operating data and the storage degree value of each operating data at each moment; The data processing module is used to store each type of operation data within a preset time period based on the storage response value.

10. A civil aviation 5G network data storage electronic device, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that: When executing the computer program, the processor implements the steps of a civil aviation 5G network data storage method as described in any one of claims 1 to 8.

Images