Data transmission protection method

Abstract

The invention relates to the field of data security, in particular to a data transmission protection method, which comprises the following steps of: pre-constructing an association relationship between each control instruction set and a data performance characteristic, acquiring a control instruction set sequence pre-executed by a control target, analyzing the simulated data performance characteristic, extracting a data transmission rule representation characteristic, and performing data transmission on the data transmission rule representation characteristic. The method comprises the following steps: calculating a data transmission rule representation coefficient, setting a transmission rule label for a current control instruction sequence set, collecting a data packet in an electric signal transmission process converted from the control instruction sequence set, sorting control instruction sets according to the transmission rule label in combination with the dispersion of the control instruction sets, determining the transmission time domain of the data packet corresponding to each control instruction set, extracting the data packet in the corresponding transmission time domain for verification, and judging whether the transmission process is abnormal or not; or directly extracting the data representation characteristics in the electric signal transmission process, comparing the data representation characteristics with the corresponding simulation data representation characteristics, and judging whether the transmission process is abnormal or not.

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 an important production factor, driving social and economic changes. As a key link in the entire life cycle of data, the security of data transmission is directly related to the availability, integrity and confidentiality of data. With the popularization of the Internet and the acceleration of the digitalization process, the amount and speed of data transmission are increasing, and the security of data transmission has become a key issue. The demand for data transmission security in various industries is also growing. For example, the financial, medical, and Internet industries have extremely high requirements for data sensitivity and security. Enterprises need to improve the security of data transmission through technical means and management measures. At the same time, data transmission protection has also become an important aspect of corporate compliance operations and enhancing competitiveness. Data transmission protection methods will face new challenges and opportunities in the future.

[0003] Chinese Patent Publication No.: CN114400632A discloses a method for transmitting longitudinal protection data based on wireless channels, which adopts a fault discrimination method combining multiple discrimination methods. When the longitudinal protection devices on both sides use the fault discrimination method to judge that there is no fault in the protected range, they send short data frame format data without sampling data to the longitudinal protection device on the opposite side according to the sampling timing; when the longitudinal protection device judges that a fault occurs in the protection range, it sends the start-up data frame format data containing sampling data to the longitudinal protection device on the opposite side according to the sampling timing, wherein the start-up data frame data is longer than the short data frame format data; after the longitudinal protection device receives the sampling data sent by the longitudinal protection device on the opposite side, it puts into differential protection for fault discrimination. By adopting the fault discrimination method, when judging the normal operation of the line, low-flow data is transmitted, and after identifying the fault in the protection range, real-time sampling data is transmitted, which saves a lot of data transmission and ensures the reliability of fault discrimination within the protection range.

[0004] China Patent Publication No.: CN116866157A, discloses a data transmission method based on 5G longitudinal differential protection, including: when running the protection logic, calculating the real-time data of each sampling channel on this side according to the sampling data, and composing the calculated real-time data on this side into a short message frame, and sending the short message frame to the opposite side protection device through the 5G channel; giving priority to the opposite side short message data sent by the opposite side protection device, and aligning the storage data according to the time scale; calculating the line differential current and braking current in real time, and running the differential protection logic according to the calculation results; when it is detected that the differential current reaches the differential current threshold value, starting the device differential protection, and starting the long message frame transmission at the same time; after the opposite side protection device obtains the long message frame transmission data, aligning the storage data according to the time scale to complete the data transmission process. This invention can not only effectively guarantee the ease of use and reliability requirements of relay protection, but also effectively reduce 5G data traffic, thereby improving the economy of equipment use.

[0005] However, there are still the following problems in the prior art:

[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 data transmission will be reduced and the security of data 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 a plurality of data packets, and the data in the data packets have different regularities and the probability of being invaded by external data is also 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 comprises:

[0009] Pre-constructing 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 pre-executed by the control target, and simulate data performance characteristics during the 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 the transmission law label for the current control instruction sequence set;

[0012] Collecting the data packets converted from the control instruction sequence set into the electrical signal transmission process, and determining whether the transmission process is abnormal according to 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] Or, directly extract the data characterization features during the transmission of the electrical signal, compare the data characterization features with the corresponding analog data performance features, and determine 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 simulated data and extracting the characteristics representing the data transmission rules includes:

[0017] Used to determine the numerical 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 reference 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 the 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 law characterization coefficient is less than the benchmark data transmission law characterization coefficient threshold, the transmission law label is set to weak law 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 packet in the corresponding transmission time domain is 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 in 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 the type influencing 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 influence factor and the time series length influence factor is determined as the dispersion.

[0035] Furthermore, the process of sorting the control instruction sets according to complexity 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 the 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 in the transmission process, the transmission control instruction set is stopped.

[0045] Compared with the prior art, the present invention pre-constructs the association 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 the transmission law label for the current control instruction sequence set, collects the data packets converted from the control instruction sequence set to 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 in the corresponding transmission time domain for verification, and determines whether the transmission process is abnormal; or directly extracts the data characterization characteristics in 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 sets the transmission law label and adopts different methods to determine whether the transmission process is abnormal, thereby improving the security of the transmission process.

[0046] In particular, the present invention extracts data transmission law characterization features, calculates data transmission law characterization coefficients, and sets labels based on the data transmission law characterization coefficients, 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 accuracy in abnormality judgment. Based on this, the present invention considers calculating data transmission law characterization coefficients and setting labels, and adopts different abnormality judgment methods for 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 characterizing the laws of data transmission 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. However, since some control instruction sets are highly discrete in themselves, 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 the laws of data transmission, and through targeted analysis of the characteristics, determines the 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 of the strong regular transmission label, sorts each control instruction set according to the discreteness, and extracts the data packets to make an abnormality judgment on the transmission process. In actual situations, when judging the abnormal data, most of the data packets in the control instruction set are in a disordered state, and only the transmission is ensured, 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 verifying the abnormality of 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 A logic block diagram of determining whether a transmission process is abnormal based on the transmission rule label according to an embodiment of the invention;

[0052] Figure 4 This is a logic block diagram of an embodiment of the invention for comparing data characterization features with corresponding simulation data representation features to determine whether the transmission process is abnormal. 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 only used to explain the present invention and are not used to limit the present invention.

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

[0055] Pre-constructing 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 pre-executed by the control target, and simulate data performance characteristics during the 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 the transmission law label for the current control instruction sequence set;

[0058] Collecting the data packets converted from the control instruction sequence set into the electrical signal transmission process, and determining whether the transmission process is abnormal according to 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] Or, directly extract the data characterization features during the transmission of the electrical signal, compare the data characterization features with the corresponding analog data performance features, and determine 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, the process of establishing an association relationship is not limited. 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 a corresponding number of control instruction sets, which can be obtained in advance by technical personnel in this field, and this will not be repeated.

[0064] Specifically, simulating the data expression characteristics in the transmission process 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 simulated data and extracting the characteristics representing the data transmission rules includes:

[0066] Used to determine the numerical 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 an interpolation method or a 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 determination coefficient. The closer the determination coefficient is to 1, the better the fit effect is.

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

[0075] Acquire peak data to determine peak data sets, 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 by determining the average of the sum of squares of the differences.

[0078] Specifically, the present invention extracts characteristics characterizing the laws of data transmission 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. However, since 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 the laws of data transmission, 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.

[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 reference 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 the 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 pre-acquired to calculate the 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 calculated in advance, and a number of historical bit error rate variation curve peak variances are obtained in advance 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 influence factor, the data volume influence factor and the bit error rate influence factor is 1, the weight coefficient of the signal frequency influence factor is 0.32, the weight coefficient of the data volume influence factor is 0.35, and the weight coefficient of the bit error rate influence factor is 0.33.

[0088] See also Figure 2 , Figure 2 This is a logic block diagram of setting a transmission rule label for a current control instruction sequence set according to an embodiment of the invention. Specifically, a transmission rule label is set for a 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 law characterization coefficient is less than the benchmark data transmission law characterization coefficient threshold, the transmission law label is set to weak law transmission.

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

[0092] Specifically, the present invention extracts data transmission law characterization features, calculates data transmission law characterization coefficients, and sets labels according to the data transmission law characterization coefficients, 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 them focus on the entire transmission process, and do not consider the influence of the regularity of the control instruction set on the data anomaly, which leads to low efficiency and low accuracy in the judgment of anomalies. Based on this, the present invention considers calculating the data transmission law characterization coefficients 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 anomaly judgment and improving the security of the transmission process.

[0093] See also Figure 3 , Figure 3 The present invention is a logic block diagram for determining whether the transmission process is abnormal according to the transmission law label according to an embodiment of the invention. Specifically, determining whether the transmission process is abnormal according to 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 packet in the corresponding transmission time domain is 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 in 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 the type influencing 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 influence factor and the time series length influence factor is determined as 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 complexity 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 of the strong regular transmission label, sorts each control instruction set according to the discreteness, and extracts the data packets to make an abnormality judgment on the transmission process. In actual situations, when judging the 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 verifying the abnormality of 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 the 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 TCP protocol checksum mechanism to detect data integrity. Technical personnel in this field can make a choice based on actual conditions, which will not be elaborated here.

[0109] See also Figure 4 , Figure 4 The present invention provides a logic block diagram 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 features and the corresponding simulation data performance features can be determined by fitting the data characterization feature time domain curve with the simulation data characterization feature time domain curve, and solving the fit of the two curves. If the fit is lower than a 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, wherein data characterization features of several control instruction sets under normal transmission are obtained, the degree of fit is determined with corresponding simulation data characterization features, and the mean of the degree of fit is calculated, and the degree of fit threshold is set between 0.85 times and 0.95 times the mean of the degree of fit.

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

[0115] So far, the technical solutions of the present invention have been described in conjunction with the preferred embodiments shown in the accompanying drawings. However, it is easy for those skilled in the art to understand that the protection scope of the present invention is obviously not limited to these specific embodiments. Without departing from the principle of the present invention, those skilled in the art can make equivalent changes or substitutions to the relevant technical features, and the technical solutions after these changes or substitutions will fall within the protection scope of the present invention.

[0116] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. For those skilled in the art, the present invention may have various modifications and variations. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present invention shall be included in the protection scope of the present invention.

Claims

1. A data transmission protection method, characterized in that: include: Pre-constructing 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 pre-executed by the control target, and simulate data performance characteristics during the 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 the transmission law label for the current control instruction sequence set; Collecting the data packets converted from the control instruction sequence set into the electrical signal transmission process, and determining whether the transmission process is abnormal according to 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; Or, directly extract the data characterization features during the transmission of the electrical signal, compare the data characterization features with the corresponding analog data performance features, and determine whether the transmission process is abnormal; The data performance characteristics include: Data signal frequency, data volume, 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.

2. The data transmission protection method according to claim 1, characterized in that: The process of analyzing the performance characteristics of the simulated data and extracting the characteristics representing the data transmission rules includes: Used to determine the numerical 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.

3. The data transmission protection method according to claim 2, 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 reference 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 the 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.

4. 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 law characterization coefficient is less than the benchmark data transmission law characterization coefficient threshold, the transmission law label is set to weak law transmission.

5. 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 packet in the corresponding transmission time domain is extracted for verification to determine whether the transmission process is abnormal; If the transmission regularity label is weak regularity transmission, the data characterization features in 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.

6. 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 the type influencing 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 influence factor and the time series length influence factor is determined as the dispersion.

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

8. The data transmission protection method according to claim 1, characterized in that: The process of extracting the 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.

9. 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.

10. 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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