Data transmission protection method

Abstract

The present invention relates to the field of data security, and in particular to a data transmission protection method. The present invention pre-constructs an association relationship between each control instruction set and a data performance characteristic, obtains a control instruction set sequence for pre-execution of a control target, analyzes the simulated data performance characteristic, extracts data transmission law characterization characteristics, calculates data transmission law characterization coefficients, sets a transmission law label for the current control instruction sequence set, collects data packets converted from the control instruction sequence set into an electrical signal transmission process, sorts the control instruction sets according to the transmission law label combined with the discreteness of the control instruction set, determines the transmission time domain of the data packets corresponding to each control instruction set, extracts the data packets in the corresponding transmission time domain for verification, and determines whether the transmission process is abnormal; or directly extracts the data characterization characteristics during the electrical signal transmission process, compares them with the corresponding simulated data performance characteristics, and determines whether the transmission process is abnormal.

Description

Technical Field

[0001] The present invention relates to the field of data security, and in particular to a data transmission protection method. Background Art

[0002] With the rapid development of the digital economy, data has become a vital factor of production, driving social and economic change. As a critical link in the data lifecycle, data transmission security is directly related to data availability, integrity, and confidentiality. With the increasing popularity of the internet and the acceleration of digitalization, the volume and speed of data transmission are constantly increasing, making data transmission security a key issue. Demand for data transmission security is also growing across various industries. For example, industries such as finance, healthcare, and the internet have extremely high requirements for data sensitivity and security. Enterprises need to enhance data transmission security through technical means and management measures. At the same time, data transmission protection has become a crucial aspect of enterprise compliance operations and competitiveness. Data transmission protection methods will face new challenges and opportunities in the future.

[0003] Chinese Patent Publication No. CN114400632A discloses a wireless channel-based pilot protection data transmission method. This method employs a fault identification method that combines multiple identification methods. When the pilot protection devices on either side determine that there is no fault within the protected range using this fault identification method, they periodically transmit short data frame format data, excluding sampled data, to the opposing pilot protection device according to a sampling sequence. When the pilot protection device determines that a fault has occurred within the protected range, it periodically transmits post-startup data frame format data, containing sampled data, to the opposing pilot protection device according to a sampling sequence. The post-startup data frame data is longer than the short data frame format data. After receiving the sampled data from the opposing pilot protection device, the pilot protection device activates differential protection for fault identification. This fault identification method utilizes low-volume data transmission when determining line normal operation, and then transmits real-time sampled data after identifying a fault within the protected range. This significantly reduces data transmission and ensures the reliability of fault identification within the protected range.

[0004] Chinese Patent Publication No. CN116866157A discloses a data transmission method based on 5G longitudinal differential protection. The method includes calculating the real-time data of each sampling channel based on the sampled data when the protection logic is running, composing the calculated real-time data into short message frames, and sending the short message frames to the opposite protection device via the 5G channel; giving priority to the opposite short message data sent by the opposite protection device, and aligning the stored data according to the time scale; calculating the line differential current and braking current in real time, and running the differential protection logic based on the calculation results; when the differential current reaches the differential current threshold, initiating the device differential protection and simultaneously initiating the long message frame transmission; after the opposite protection device obtains the long message frame transmission data, aligning the stored data according to the time scale to complete the data transmission process. This invention can not only effectively ensure the ease of use and reliability requirements of relay protection, but also effectively reduce 5G data traffic, thereby improving the economic efficiency of equipment use.

[0005] However, the prior art still has the following problems:

[0006] During the data transmission process, the control instruction set is composed of several data packets. The data in the data packets have different regularities and the probability of being invaded by external data will also be different. If the same analysis method is used for the data packets in the control instruction set, the transmission efficiency of the data will be reduced and the data security will be reduced. Summary of the Invention

[0007] To this end, the present invention provides a data transmission protection method to overcome the problem that during the data transmission process, a control instruction set is composed of several data packets, and the data in the data packets have different regularities, and the probability of being invaded by external data will also be different. If the same analysis method is adopted for the data packets in the control instruction set, the transmission efficiency of the data transmission will be reduced and the security of the data will be reduced.

[0008] To achieve the above object, the present invention provides a data transmission protection method, which includes:

[0009] Pre-establishing the correlation between each control instruction set and the data performance characteristics during the corresponding electrical signal transmission process;

[0010] Acquire a control instruction set sequence for pre-execution of a control target, and simulate data performance characteristics during transmission of the control instruction set based on the association relationship;

[0011] Analyze the performance characteristics of the simulation data, extract the data transmission law representation characteristics, calculate the data transmission law representation coefficient, and set a transmission law label for the current control instruction sequence set;

[0012] Collecting data packets converted from the control instruction sequence set into electrical signal transmission, and determining whether the transmission process is abnormal based on the transmission rule label, including:

[0013] Analyze the discreteness of the control instruction set, sort each control instruction set according to the discreteness, determine the transmission time domain of the data packet corresponding to each control instruction set one by one according to the sorting order, extract the data packet in the corresponding transmission time domain for verification, and determine whether the transmission process is abnormal;

[0014] Alternatively, directly extracting data characterization features during the electrical signal transmission process, comparing the data characterization features with corresponding analog data performance features, and determining whether the transmission process is abnormal;

[0015] Among them, the data performance characteristics include data signal frequency, data volume, and bit error rate. The verification includes determining whether the data packet corresponding to the transmission time domain segment is the data packet corresponding to the control instruction set, and determining whether the content of each data packet has been tampered with.

[0016] Furthermore, the process of analyzing the performance characteristics of the simulation data and extracting the characteristics representing the data transmission rules includes:

[0017] To determine the value of the performance characteristics of the simulation data in the time domain dimension;

[0018] Used to construct a signal periodic change curve, a data volume change curve, and a bit error rate change curve based on each value;

[0019] It is used to determine the peak variance of the signal periodic change curve, the data volume change curve and the bit error rate change curve, and determine each peak variance as a characteristic feature of the data transmission law.

[0020] Furthermore, the process of calculating the coefficient representing the data transmission law includes:

[0021] Determine the ratio of the peak value variance of the reference signal periodic variation curve to the peak value variance of the signal periodic variation curve as the signal frequency influencing factor;

[0022] Determine the ratio of the peak variance of the benchmark data volume change curve to the peak variance of the data volume change curve as the data volume influencing factor;

[0023] Determine the ratio of the peak variance of the reference bit error rate variation curve to the peak variance of the bit error rate variation curve as a bit error rate influencing factor;

[0024] Determine a weighted sum of the signal frequency impact factor, the data volume impact factor, and the bit error rate impact factor as the data transmission law characterization coefficient.

[0025] Furthermore, the transmission rule label is set for the current control instruction sequence set, wherein:

[0026] If the data transmission regularity characterization coefficient is greater than or equal to the benchmark data transmission regularity characterization coefficient threshold, the transmission regularity label is set to strong regularity transmission;

[0027] If the data transmission regularity characterization coefficient is less than the benchmark data transmission regularity characterization coefficient threshold, the transmission regularity label is set to weak regularity transmission.

[0028] Furthermore, the determining whether the transmission process is abnormal based on the transmission rule label includes:

[0029] If the transmission regularity label is strong regularity transmission, the discreteness of the control instruction set is analyzed, each control instruction set is sorted according to the discreteness, the transmission time domain of the data packet corresponding to each control instruction set is determined one by one according to the sorting order, and the data packets in the corresponding transmission time domain are extracted for verification to determine whether the transmission process is abnormal;

[0030] If the transmission regularity label is weak regularity transmission, the data characterization features during the electrical signal transmission process are directly extracted, and the data characterization features are compared with the corresponding analog data performance features to determine whether the transmission process is abnormal.

[0031] Furthermore, the process of analyzing the discreteness of the control instruction set includes:

[0032] Determine the ratio of the type of data in the control instruction set to the sum of the types of data in each control instruction set as a type impact factor;

[0033] Determine the ratio of the time series length of the data in the control instruction set to the sum of the time series lengths of the data in each control instruction set as the time series length influencing factor;

[0034] The weighted sum of the category influencing factor and the time series length influencing factor is determined to be the dispersion.

[0035] Furthermore, the process of sorting the control instruction sets according to the discreteness includes:

[0036] Determine the discreteness corresponding to each control instruction set;

[0037] The control instruction sets are sorted in descending order according to the dispersion.

[0038] Furthermore, the process of extracting data packets in the corresponding transmission time domain for verification and determining whether the transmission process is abnormal includes:

[0039] If the data packet corresponding to the transmission time domain segment is the data packet corresponding to the control instruction set and the content of the data packet has not been tampered with, it is determined that no abnormality has occurred in the transmission process;

[0040] If the data packet corresponding to the transmission time domain segment is not the data corresponding to the control instruction set and / or the content of the data packet has been tampered with, it is determined that an abnormality has occurred in the transmission process.

[0041] Furthermore, the process of comparing the data characterization features with the corresponding simulation data performance features to determine whether the transmission process is abnormal includes:

[0042] If the data representation characteristics differ from the corresponding simulation data representation characteristics, it is determined that an abnormality has occurred in the transmission process;

[0043] If there is no difference between the data characterization characteristics and the corresponding simulation data performance characteristics, it is determined that no abnormality has occurred in the transmission process.

[0044] Furthermore, if an abnormality occurs during the transmission process, the transmission control instruction set is stopped.

[0045] Compared with the prior art, the present invention pre-constructs the association relationship between each control instruction set and the data performance characteristics, obtains the control instruction set sequence pre-executed by the control target, analyzes the simulated data performance characteristics, extracts the data transmission law characterization characteristics, calculates the data transmission law characterization coefficient, sets a transmission law label for the current control instruction sequence set, collects the data packets converted from the control instruction sequence set during the electrical signal transmission process, sorts the control instruction sets according to the transmission law label combined with the discreteness of the control instruction set, determines the transmission time domain of the data packets corresponding to each control instruction set, extracts the data packets within the corresponding transmission time domain for verification, and determines whether the transmission process is abnormal; or directly extracts the data characterization characteristics during the electrical signal transmission process, compares them with the corresponding simulated data performance characteristics, and determines whether the transmission process is abnormal. The present invention improves the security of the transmission process by setting a transmission law label and taking different methods to determine whether the transmission process is abnormal.

[0046] In particular, the present invention extracts the characterization features of data transmission rules, calculates the characterization coefficients of data transmission rules, and sets labels according to the characterization coefficients of data transmission rules, providing a theoretical basis for determining the analysis method of the transmission process. In actual situations, when making abnormality judgments on the data transmission process, most of the time, the entire transmission process is targeted, and the influence of the regularity of the control instruction set on the data abnormality is not considered, resulting in low efficiency and low accuracy in the judgment of abnormalities. Based on this, the present invention considers calculating the characterization coefficients of data transmission rules and setting labels, and adopts different abnormality judgment methods for the control instruction sequence sets corresponding to different labels, thereby improving the efficiency and accuracy of data abnormality judgment and improving the security of the transmission process.

[0047] In particular, the present invention extracts characteristics that characterize data transmission rules to identify the forms of expression of data expression characteristics of different instruction data sets during electrical signal transmission. Generally speaking, in actual situations, if data theft or tampering occurs, the form of data expression will fluctuate, but because some control instruction sets are inherently highly discrete, they are prone to introduce noise, which masks the characteristics of data theft or tampering. Based on this, the present invention considers extracting characteristics that characterize data transmission rules, and through targeted analysis of the characteristics, determines anomalies in the data transmission process, thereby improving the efficiency and accuracy of data anomaly determination and improving the security of the transmission process.

[0048] In particular, the present invention analyzes the discreteness of the control instruction sequence set with a strong regular transmission tag, sorts each control instruction set by the discreteness, and extracts data packets to make abnormality judgments on the transmission process. In actual situations, when judging abnormal data, most of the data packets in the control instruction set are in a disordered state, and only need to ensure that they can be transmitted, which brings great difficulties to the abnormality judgment of the data. Based on this, the present invention considers sorting the data packets corresponding to each control instruction set according to the discreteness of the control instruction sequence set, and performing abnormality verification on the data packets in the order of arrangement of the data packets, thereby improving the efficiency and accuracy of data abnormality judgment and improving the security of the transmission process. BRIEF DESCRIPTION OF THE DRAWINGS

[0049] Figure 1 A schematic diagram of the steps of a data transmission protection method according to an embodiment of the invention;

[0050] Figure 2 A logic block diagram of setting a transmission rule label for a current control instruction sequence set according to an embodiment of the invention;

[0051] Figure 3 This is a logic block diagram of an embodiment of the invention for determining whether a transmission process is abnormal based on the transmission rule label;

[0052] Figure 4 This is a logic block diagram for comparing data characterization features with corresponding simulation data performance features to determine whether the transmission process is abnormal according to an embodiment of the invention. DETAILED DESCRIPTION

[0053] In order to make the objects and advantages of the present invention more clearly understood, the present invention is further described below in conjunction with embodiments; it should be understood that the specific embodiments described herein are merely used to explain the present invention and are not intended to limit the present invention.

[0054] See also Figure 1 , Figure 1 The present invention is a step diagram of a data transmission protection method according to an embodiment of the present invention. The data transmission protection method according to the present invention includes:

[0055] Pre-establishing the correlation between each control instruction set and the data performance characteristics during the corresponding electrical signal transmission process;

[0056] Acquire a control instruction set sequence for pre-execution of a control target, and simulate data performance characteristics during transmission of the control instruction set based on the association relationship;

[0057] Analyze the performance characteristics of the simulation data, extract the data transmission law representation characteristics, calculate the data transmission law representation coefficient, and set a transmission law label for the current control instruction sequence set;

[0058] Collecting data packets converted from the control instruction sequence set into electrical signal transmission, and determining whether the transmission process is abnormal based on the transmission rule label, including:

[0059] Analyze the discreteness of the control instruction set, sort each control instruction set according to the discreteness, determine the transmission time domain of the data packet corresponding to each control instruction set one by one according to the sorting order, extract the data packet in the corresponding transmission time domain for verification, and determine whether the transmission process is abnormal;

[0060] Alternatively, directly extracting data characterization features during the electrical signal transmission process, comparing the data characterization features with corresponding analog data performance features, and determining whether the transmission process is abnormal;

[0061] Among them, the data performance characteristics include data signal frequency, data volume, and bit error rate. The verification includes determining whether the data packet corresponding to the transmission time domain segment is the data packet corresponding to the control instruction set, and determining whether the content of each data packet has been tampered with.

[0062] Specifically, there is no limitation on the process of establishing the association relationship. In implementation, the control instruction set is collected and converted into the corresponding data representation characteristics during the transmission of the data packet in the form of an electrical signal, and the control instruction set is associated with the data representation characteristics. This will not be repeated.

[0063] Specifically, there is no limitation on the method of obtaining the control instruction set sequence for pre-execution of the control target. It can be understood that for industrial control equipment, the control instructions can be pre-compiled to form several corresponding control instruction sets, which can be obtained in advance by technicians in this field, and this will not be repeated.

[0064] Specifically, simulating the data expression characteristics during the transmission of the control instruction set based on the association relationship includes determining each control instruction set to be transmitted one by one, determining the data expression characteristics associated with each control instruction, and obtaining the simulated data expression characteristics.

[0065] Specifically, the process of analyzing the performance characteristics of the simulation data and extracting the characteristics representing the data transmission rules includes:

[0066] To determine the value of the performance characteristics of the simulation data in the time domain dimension;

[0067] Used to construct a signal periodic change curve, a data volume change curve, and a bit error rate change curve based on each value;

[0068] It is used to determine the peak variance of the signal periodic change curve, the data volume change curve and the bit error rate change curve, and determine each peak variance as a characteristic feature of the data transmission law.

[0069] Specifically, there is no limitation on the method of constructing each change curve. For example, the curve can be constructed by interpolation method or fitting method. It only needs to ensure that the change curve can be successfully constructed. In implementation, the change curve is constructed by fitting. The specific steps are as follows:

[0070] Clean the data, including removing outliers, filling missing values, and standardizing or normalizing the data;

[0071] Select appropriate fitting models, including linear regression models and nonlinear regression models;

[0072] The fitting parameters are determined by minimizing the sum of squared errors and the curve is constructed.

[0073] It can be understood that the goodness of fit of the model is evaluated by calculating the coefficient of determination. The closer the coefficient of determination is to 1, the better the fit effect.

[0074] Specifically, the calculation steps of peak variance are as follows,

[0075] Acquire peak data to determine a peak data set, and calculate an average value of each peak data set;

[0076] Calculate the difference between each peak value and the average value;

[0077] The peak variance is determined as the average of the sum of squares of the differences.

[0078] Specifically, the present invention extracts characteristics characterizing data transmission rules to identify the manifestation forms of data manifestation characteristics of different instruction data sets during electrical signal transmission. Generally speaking, in actual situations, if data theft or tampering occurs, the manifestation form of the data will fluctuate. However, because some control instruction sets are inherently highly discrete, noise is easily introduced, and the noise masks the characteristics of data theft or tampering. Based on this, the present invention considers extracting characteristics characterizing data transmission rules, and through targeted analysis of the characteristics, determines anomalies in the data transmission process, thereby improving the efficiency and accuracy of data anomaly judgment and improving the security of the transmission process.

[0079] Specifically, the process of calculating the coefficients representing the data transmission law includes:

[0080] Determine the ratio of the peak value variance of the reference signal periodic variation curve to the peak value variance of the signal periodic variation curve as the signal frequency influencing factor;

[0081] Determine the ratio of the peak variance of the benchmark data volume change curve to the peak variance of the data volume change curve as the data volume influencing factor;

[0082] Determine the ratio of the peak variance of the reference bit error rate variation curve to the peak variance of the bit error rate variation curve as a bit error rate influencing factor;

[0083] Determine a weighted sum of the signal frequency impact factor, the data volume impact factor, and the bit error rate impact factor as the data transmission law characterization coefficient.

[0084] Specifically, the peak variance of the reference signal periodic change curve is pre-calculated, and the peak variances of several historical signal periodic change curves are pre-acquired to calculate the average value, and the average value is determined as the peak variance of the reference signal periodic change curve.

[0085] Specifically, the peak variance of the benchmark data volume change curve is pre-calculated, and the peak variances of several historical data volume change curves are obtained in advance to calculate an average value, and the average value is determined as the peak variance of the benchmark data volume change curve.

[0086] Specifically, the peak variance of the reference bit error rate variation curve is pre-calculated, and several historical peak variances of the bit error rate variation curves are pre-obtained to calculate an average value, and the average value is determined as the peak variance of the reference bit error rate variation curve.

[0087] Specifically, the sum of the weight coefficients of the signal frequency impact factor, the data volume impact factor and the bit error rate impact factor is 1, the weight coefficient of the signal frequency impact factor is 0.32, the weight coefficient of the data volume impact factor is 0.35, and the weight coefficient of the bit error rate impact factor is 0.33.

[0088] See also Figure 2 , Figure 2 This is a logic block diagram of setting a transmission rule tag for the current control instruction sequence set according to an embodiment of the invention. Specifically, a transmission rule tag is set for the current control instruction sequence set, wherein:

[0089] If the data transmission regularity characterization coefficient is greater than or equal to the benchmark data transmission regularity characterization coefficient threshold, the transmission regularity label is set to strong regularity transmission;

[0090] If the data transmission regularity characterization coefficient is less than the benchmark data transmission regularity characterization coefficient threshold, the transmission regularity label is set to weak regularity transmission.

[0091] Specifically, the threshold value of the coefficient representing the benchmark data transmission law is selected within the interval [0.63, 0.81].

[0092] Specifically, the present invention extracts the characterization features of data transmission rules, calculates the characterization coefficients of data transmission rules, and sets labels according to the characterization coefficients of data transmission rules, providing a theoretical basis for determining the analysis method of the transmission process. In actual situations, when making abnormality judgments on the data transmission process, most of the time, the entire transmission process is targeted, and the influence of the regularity of the control instruction set on data abnormalities is not considered, resulting in low efficiency and low accuracy in the judgment of abnormalities. Based on this, the present invention considers calculating the characterization coefficients of data transmission rules and setting labels, and adopts different abnormality judgment methods for the control instruction sequence sets corresponding to different labels, thereby improving the efficiency and accuracy of data abnormality judgment and improving the security of the transmission process.

[0093] See also Figure 3 , Figure 3 This is a logic block diagram of an embodiment of the invention for determining whether a transmission process is abnormal based on the transmission law label. Specifically, determining whether a transmission process is abnormal based on the transmission law label includes:

[0094] If the transmission regularity label is strong regularity transmission, the discreteness of the control instruction set is analyzed, each control instruction set is sorted according to the discreteness, the transmission time domain of the data packet corresponding to each control instruction set is determined one by one according to the sorting order, and the data packets in the corresponding transmission time domain are extracted for verification to determine whether the transmission process is abnormal;

[0095] If the transmission regularity label is weak regularity transmission, the data characterization features during the electrical signal transmission process are directly extracted, and the data characterization features are compared with the corresponding analog data performance features to determine whether the transmission process is abnormal.

[0096] Specifically, the process of analyzing the discreteness of the control instruction set includes,

[0097] Determine the ratio of the type of data in the control instruction set to the sum of the types of data in each control instruction set as a type impact factor;

[0098] Determine the ratio of the time series length of the data in the control instruction set to the sum of the time series lengths of the data in each control instruction set as the time series length influencing factor;

[0099] The weighted sum of the category influencing factor and the time series length influencing factor is determined to be the dispersion.

[0100] Specifically, the sum of the weight coefficients of the type impact factor and the time series length impact factor is 1, the weight coefficient of the type impact factor is 0.56, and the weight coefficient of the time series length impact factor is 0.44.

[0101] Specifically, the process of sorting each control instruction set according to the discreteness includes:

[0102] Determine the discreteness corresponding to each control instruction set;

[0103] The control instruction sets are sorted in descending order according to the dispersion.

[0104] Specifically, the present invention analyzes the discreteness of the control instruction sequence set with a strong regular transmission tag, sorts each control instruction set according to the discreteness, and extracts data packets to perform abnormality judgment on the transmission process. In actual situations, when judging abnormal data, most of the data packets in the control instruction set are in a disordered state, and only need to ensure that they can be transmitted, which brings great difficulties to the abnormality judgment of the data. Based on this, the present invention considers sorting the data packets corresponding to each control instruction set according to the discreteness of the control instruction sequence set, and performing abnormality verification on the data packets in the order of arrangement of the data packets, thereby improving the efficiency and accuracy of data abnormality judgment and improving the security of the transmission process.

[0105] Specifically, the process of extracting data packets in the corresponding transmission time domain for verification and determining whether the transmission process is abnormal includes:

[0106] If the data packet corresponding to the transmission time domain segment is the data packet corresponding to the control instruction set and the content of the data packet has not been tampered with, it is determined that no abnormality has occurred in the transmission process;

[0107] If the data packet corresponding to the transmission time domain segment is not the data corresponding to the control instruction set and / or the content of the data packet has been tampered with, it is determined that an abnormality has occurred in the transmission process.

[0108] Specifically, the method for determining that the data packet corresponding to the transmission time domain segment is the data packet corresponding to the control instruction set and determining that the content of the data packet has not been tampered with can be to use a hash function (such as SHA-256) to generate a data digest and compare it, or to use the checksum mechanism of the TCP protocol to detect data integrity. Those skilled in the art can make a choice based on actual conditions, and this will not be repeated here.

[0109] See also Figure 4 , Figure 4 This is a logic block diagram of an embodiment of the invention for comparing data characterization features with corresponding simulation data performance features to determine whether the transmission process is abnormal. Specifically, the process of comparing data characterization features with corresponding simulation data performance features to determine whether the transmission process is abnormal includes:

[0110] If the data representation characteristics differ from the corresponding simulation data representation characteristics, it is determined that an abnormality has occurred in the transmission process;

[0111] If there is no difference between the data characterization characteristics and the corresponding simulation data performance characteristics, it is determined that no abnormality has occurred in the transmission process.

[0112] Specifically, the method for determining whether there is a difference between the data characterization characteristics and the corresponding simulation data performance characteristics can be determined by fitting the data characterization characteristic time domain curve with the simulation data characterization characteristic time domain curve, and solving the fit of the two curves. If the fit is lower than the preset fit threshold, it is determined that there is a difference.

[0113] The degree of fit can be determined by calculating the correlation coefficient, and the degree of fit threshold is predetermined. The data characterization features of several control instruction sets under normal transmission conditions are obtained, the degree of fit is determined by comparing with the corresponding simulation data characterization features, and the mean value of the degree of fit is calculated. The degree of fit threshold is set between 0.85 times and 0.95 times the mean value of the degree of fit.

[0114] Specifically, if an abnormality occurs during the transmission process, the transmission control instruction set is stopped.

[0115] Thus far, the technical solutions of the present invention have been described in conjunction with the preferred embodiments shown in the accompanying drawings. However, it will be readily understood by those skilled in the art that the scope of protection of the present invention is obviously not limited to these specific embodiments. Without departing from the principles of the present invention, those skilled in the art may make equivalent changes or substitutions to the relevant technical features, and the technical solutions after such changes or substitutions will fall within the scope of protection of the present invention.

[0116] The foregoing description is merely a preferred embodiment of the present invention and is not intended to limit the present invention. Those skilled in the art will readily appreciate that the present invention is susceptible to various modifications and variations. Any modifications, equivalent substitutions, or improvements made within the spirit and principles of the present invention are intended to be within the scope of protection of the present invention.

Claims

1. A data transmission protection method, characterized in that: include: Pre-establishing the correlation between each control instruction set and the data performance characteristics during the corresponding electrical signal transmission process; Acquire a control instruction set sequence for pre-execution of a control target, and simulate data performance characteristics during transmission of the control instruction set based on the association relationship; Analyze the performance characteristics of the simulation data, extract the data transmission law representation characteristics, calculate the data transmission law representation coefficient, and set a transmission law label for the current control instruction sequence set; Collecting data packets converted from the control instruction sequence set into electrical signal transmission, and determining whether the transmission process is abnormal based on the transmission rule label, including: Analyze the discreteness of the control instruction set, sort each control instruction set according to the discreteness, determine the transmission time domain of the data packet corresponding to each control instruction set one by one according to the sorting order, extract the data packet in the corresponding transmission time domain for verification, and determine whether the transmission process is abnormal; Alternatively, directly extracting data characterization features during the electrical signal transmission process, comparing the data characterization features with corresponding analog data performance features, and determining whether the transmission process is abnormal; The data performance characteristics include data signal frequency, data volume, and bit error rate. The verification includes determining whether the data packet corresponding to the transmission time domain segment is the data packet corresponding to the control instruction set, and determining whether the content of each data packet has been tampered with. The process of analyzing the performance characteristics of the simulation data and extracting the characteristics representing the data transmission rules includes: To determine the value of the performance characteristics of the simulation data in the time domain dimension; Used to construct a signal periodic change curve, a data volume change curve, and a bit error rate change curve based on each value; It is used to determine the peak variance of the signal periodic change curve, the data volume change curve and the bit error rate change curve, and determine each peak variance as a characteristic feature of the data transmission law.

2. The data transmission protection method according to claim 1, characterized in that: The process of calculating the coefficient representing the data transmission law includes: Determine the ratio of the peak value variance of the reference signal periodic variation curve to the peak value variance of the signal periodic variation curve as the signal frequency influencing factor; Determine the ratio of the peak variance of the benchmark data volume change curve to the peak variance of the data volume change curve as the data volume influencing factor; Determine the ratio of the peak variance of the reference bit error rate variation curve to the peak variance of the bit error rate variation curve as a bit error rate influencing factor; Determine a weighted sum of the signal frequency impact factor, the data volume impact factor, and the bit error rate impact factor as the data transmission law characterization coefficient.

3. The data transmission protection method according to claim 1, characterized in that: The transmission rule label is set for the current control instruction sequence set, wherein: If the data transmission regularity characterization coefficient is greater than or equal to the benchmark data transmission regularity characterization coefficient threshold, the transmission regularity label is set to strong regularity transmission; If the data transmission regularity characterization coefficient is less than the benchmark data transmission regularity characterization coefficient threshold, the transmission regularity label is set to weak regularity transmission.

4. The data transmission protection method according to claim 1, characterized in that: The determining whether the transmission process is abnormal based on the transmission rule label includes: If the transmission regularity label is strong regularity transmission, the discreteness of the control instruction set is analyzed, each control instruction set is sorted according to the discreteness, the transmission time domain of the data packet corresponding to each control instruction set is determined one by one according to the sorting order, and the data packets in the corresponding transmission time domain are extracted for verification to determine whether the transmission process is abnormal; If the transmission regularity label is weak regularity transmission, the data characterization features during the electrical signal transmission process are directly extracted, and the data characterization features are compared with the corresponding analog data performance features to determine whether the transmission process is abnormal.

5. The data transmission protection method according to claim 1, characterized in that: The process of analyzing the discreteness of the control instruction set includes: Determine the ratio of the type of data in the control instruction set to the sum of the types of data in each control instruction set as a type impact factor; Determine the ratio of the time series length of the data in the control instruction set to the sum of the time series lengths of the data in each control instruction set as the time series length influencing factor; The weighted sum of the category influencing factor and the time series length influencing factor is determined to be the dispersion.

6. The data transmission protection method according to claim 1, characterized in that: The process of sorting the control instruction sets according to the discreteness includes: Determine the discreteness corresponding to each control instruction set; The control instruction sets are sorted in descending order according to the dispersion.

7. The data transmission protection method according to claim 1, characterized in that: The process of extracting data packets in the corresponding transmission time domain for verification and determining whether the transmission process is abnormal includes: If the data packet corresponding to the transmission time domain segment is the data packet corresponding to the control instruction set and the content of the data packet has not been tampered with, it is determined that no abnormality has occurred in the transmission process; If the data packet corresponding to the transmission time domain segment is not the data corresponding to the control instruction set and / or the content of the data packet has been tampered with, it is determined that an abnormality has occurred in the transmission process.

8. The data transmission protection method according to claim 1, characterized in that: The process of comparing the data characterization features with the corresponding simulation data performance features to determine whether the transmission process is abnormal includes: If the data representation characteristics differ from the corresponding simulation data representation characteristics, it is determined that an abnormality has occurred in the transmission process; If there is no difference between the data characterization characteristics and the corresponding simulation data performance characteristics, it is determined that no abnormality has occurred in the transmission process.

9. The data transmission protection method according to claim 1, characterized in that: If an abnormality occurs during the transmission process, the transmission control instruction set is stopped.

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