Network security monitoring method and system for intelligent coal mine production

Abstract

The invention relates to the technical field of coal mine production, in particular to a network security monitoring method and system for intelligent coal mine production, and the method comprises the steps: building a database through extracting sample data information of different production chain links of the coal mine production of each mining area, and calculating network risk highlighting characterization parameters of each production chain link of the coal mine production of each mining area; therefore, the network risk highlighting sequencing sequence of each production chain link of coal mine production in each mining area is rapidly determined, and the efficiency of coal mine production network safety monitoring is improved. The maximum network risk highlighting characterization parameter of each production chain link of the to-be-mined coal mine area can be accurately obtained by obtaining the coal mine production actual data uploaded by the user side and uploaded by the to-be-mined coal mine area and the sample data information of the corresponding production chain link, and the accuracy of coal mine production network safety monitoring is improved. And the network security monitoring efficiency is improved on the premise of ensuring the reliability.

Description

Technical Field

[0001] The present invention relates to the technical field of coal mine production, and in particular to a network security monitoring method and system for intelligent coal mine production. Background Art

[0002] Intelligent coal mine production realizes the interconnection of devices, visualization of the production process, and intelligent management through the deep integration of technologies such as the Internet of Things, industrial control technology, 5G communication, cloud computing, and big data. This integration makes the coal mine production network more open, but also brings new network security risks. Because a large amount of sensitive data is involved in intelligent coal mine production, including production data, equipment status data, and personnel information, etc. Therefore, technologies such as data encryption, access control, prevention of equipment aging, data backup and recovery have become important components of network security monitoring. Therefore, the security protection of the coal mine industrial Internet is the core content of intelligent coal mine network security monitoring and an urgent problem to be solved.

[0003] Chinese Patent Publication No.: CN110568829B discloses an intelligent control system for the whole production chain link of a mine. By combining an intelligent management platform, an intelligent fully-mechanized mining platform, and a smart mine platform, based on technologies such as centralized control, mobile applications, the Internet of Things, cloud computing, and big data, it realizes an integrated intelligent control system for the whole production chain link of the mine that conducts real-time production monitoring, remote control, mobile command, and intelligent decision-making management on the production and production auxiliary automation systems of the mine; this system can enable managers, technical engineers, and multi-level scheduling, and on the premise of ensuring production safety and data security in the whole production chain link, monitor the working conditions of various system devices such as coal mine production and auxiliary production at any time underground, on the ground PC side, web page, and mobile side, and conduct efficient scheduling management work and decision-making command.

[0004] However, the following problems still exist in the prior art:

[0005] In the existing method of intelligent coal mine production by combining an intelligent management platform, an intelligent fully-mechanized mining platform, and a smart mine platform, the data representativeness in the network security dimension of different production chain links of coal mine production in different mining areas is not considered. In actual situations, there are obvious characteristics in some production chain links of coal mine production in some mining areas, and some characteristics of coal mine production in some mining areas are more similar to the corresponding production chain links of coal mines in other mining areas. If the same network security analysis method is used for the production chain links of coal mine production in various mining areas, when facing a large amount of data information, the network security monitoring speed is slow and the efficiency is low. Summary of the Invention

[0006] To this end, the present invention provides a network security monitoring method and system for intelligent coal mine production to overcome the problem in the prior art that the data representativeness of different production chain links in coal mine production in different mining areas is not considered in the dimension of network security. In actual situations, there are obvious characteristics in some production chain links of coal mine production in some mining areas, and some characteristics of coal mine production in some mining areas are similar to the corresponding production chain links of coal mines in other mining areas. If the same network security analysis method is used for the production chain links of coal mine production in various mining areas, when facing a large amount of data information, the network security monitoring speed is slow and the efficiency is low.

[0007] To achieve the above object, the present invention provides a network security monitoring method for intelligent coal mine production, including:

[0008] Extract the sample data information of each production chain link of coal mine production in each mining area to determine the network risk highlighting factors of each production chain link of coal mine production in different mining areas, including,

[0009] Compare the sample data information of each production chain link of a single mining area with the sample data information of the corresponding production chain links of coal mine production in other mining areas respectively, solve the average similarity, and obtain the network complexity of each production chain link of the coal mine production in the single mining area;

[0010] Calculate the network risk highlighting characterization parameters of each production chain link of coal mine production in each mining area according to the network risk highlighting factors of each production chain link of coal mine production in different mining areas to determine the network risk highlighting ranking sequence of each production chain link of coal mine production in each mining area;

[0011] Obtain the actual data of coal mine production uploaded by the mining area of the coal mine to be mined and the sample data information of the corresponding production chain link, obtain the maximum network risk highlighting characterization parameter of each production chain link of coal mine production in the corresponding mining area according to the sample data information, and analyze the actual data of the mining area of the coal mine to be mined according to the determination result, including,

[0012] Obtain the network risk highlighting ranking sequence according to the sample data information of the corresponding production chain link, determine the comparison order for the actual data of the mining area of the coal mine to be mined according to the network risk highlighting ranking sequence, and sequentially call the actual data of the corresponding production chain link to compare with the sample data information of the corresponding production chain link according to the comparison order to determine the similarity, so as to determine whether the network security of the production chain link of coal mine production meets the standard and determine whether to enable the security monitoring and auditing system;

[0013] Or, compare the actual data of the complete production chain link of the mining area of the coal mine to be mined with the sample data information of the corresponding complete production chain link to determine the similarity, so as to determine whether to enable the security monitoring and auditing system.

[0014] Further, the process of calculating the network risk prominent characterization parameters for each production chain link in coal mining in each mining area includes

[0015] Obtaining network risk prominent factors, including the similarity mean value and network complexity;

[0016] Determining the ratio of the preset similarity standard threshold to the similarity mean value as the first network risk prominent factor;

[0017] Determining the ratio of the network complexity to the preset network complexity standard threshold as the second network risk prominent factor;

[0018] Determining the sum of the first network risk prominent factor and the second network risk prominent factor as the network risk prominent characterization parameter.

[0019] Further, the process of obtaining the network complexity of each production chain link in coal mining in a single mining area includes

[0020] Calibrating the types of equipment and the total number of equipment in the network of the production chain link in a single mining area;

[0021] Calculating the ratio of the number of equipment types in the network to the threshold of the number of benchmark equipment types as the first network complexity factor;

[0022] Calculating the ratio of the total number of equipment in the network to the threshold of the total number of benchmark equipment as the second network complexity factor;

[0023] Determining the weighted sum of the first network complexity factor and the second network complexity factor as the network complexity.

[0024] Further, the process of determining the network risk prominent ranking sequence for each production chain link in coal mining in each mining area includes

[0025] Determining the network risk prominent characterization parameters corresponding to each production chain link in coal mining in a single mining area;

[0026] Arranging the network risk prominent characterization parameters in descending order to obtain the network risk prominent ranking sequence.

[0027] Further, analyzing the actual data of the coal mining area to be mined according to the determination result, including

[0028] Obtaining the maximum network risk prominent characterization parameter for each production chain link in coal mining in the corresponding mining area according to the sample data information;

[0029] If the maximum network risk prominent characterization parameter is greater than the predetermined prominent characterization parameter threshold benchmark, obtain the network risk prominence ranking sequence according to the sample data information of the corresponding production chain link, determine the comparison order of the actual data for the coal mine mining area to be mined according to the network risk prominence ranking sequence, and sequentially call the actual data of the corresponding production chain link and the sample data information of the corresponding production chain link for comparison to determine the similarity, so as to determine whether the network security of the production chain link of coal mine production meets the standard, and to determine whether to enable the security monitoring and auditing system;

[0030] If the maximum network risk prominent characterization parameter is less than or equal to the predetermined prominent characterization parameter threshold benchmark, obtain the actual data of the complete production chain link of the coal mine mining area to be mined and compare it with the sample data information of the corresponding complete production chain link to determine the similarity, so as to determine whether to enable the security monitoring and auditing system.

[0031] Furthermore, the process of determining the comparison order of the actual data for the coal mine mining area to be mined according to the network risk prominence ranking sequence includes,

[0032] Sequentially determine the production chain links corresponding to the network risk prominence ranking sequence, obtain the ranking of each production chain link, and generate the serial number ranking of the production chain links;

[0033] Among them, each production chain link corresponds to the serial number of the production chain link one by one.

[0034] Furthermore, sequentially call the actual data of the corresponding production chain link and the sample data information of the corresponding production chain link for comparison according to the comparison order to determine the similarity, so as to determine whether the network security of the production chain link of coal mine production meets the standard, and to determine whether to enable the security monitoring and auditing system, including,

[0035] If the similarity corresponding to the actual data of any production chain link is greater than the preset production chain link similarity standard threshold, it is determined that the network security meets the standard, and stop calling the actual data of the corresponding production chain link and the sample data information of the corresponding production chain link for comparison;

[0036] If the similarity corresponding to the actual data of each production chain link is less than the preset production chain link similarity standard threshold, it is determined to enable the security monitoring and auditing system.

[0037] Furthermore, obtain the actual data of the complete production chain link of the coal mine mining area to be mined and compare it with the sample data information of the corresponding complete production chain link to determine the similarity, so as to determine whether to enable the security monitoring and auditing system, including,

[0038] If the similarity between the actual data of the complete production chain link in the coal mine area to be mined currently and the sample data information of the corresponding complete production chain link is less than the preset complete coal mine similarity standard threshold, it is determined to enable the safety monitoring and auditing system.

[0039] Furthermore, the actual data of coal mine production uploaded by the coal mine area to be mined needs to include the actual data of each production chain link in coal mine production and the actual data of the complete production chain link in coal mine production.

[0040] Furthermore, the present invention also provides a network security monitoring system for intelligent coal mine production, including,

[0041] A database module, which is used to store the sample data information of each production chain link in coal mine production of each mining area extracted in advance, and determine the network risk highlighting factors of each production chain link in different mining areas;

[0042] A network risk assessment module, which is connected to the database module, and is used to calculate the network risk highlighting characterization parameters of each production chain link in coal mine production of each mining area according to the network risk highlighting factors of each production chain link in coal mine production of different mining areas, so as to determine the network risk highlighting ranking sequence of each production chain link in coal mine production of each mining area;

[0043] An information receiving module, which is connected to the user terminal, and the user obtains the actual data of coal mine production uploaded by the coal mine area to be mined and the sample data information of the corresponding production chain link uploaded by the user terminal;

[0044] A verification module, which is respectively connected to the database module, the network risk assessment module and the information receiving module, and is used to obtain the maximum network risk highlighting characterization parameter of each production chain link in coal mine production of the corresponding mining area according to the sample data information, and analyze the actual data of the coal mine area to be mined according to the determination result, including,

[0045] Obtain the network risk highlighting ranking sequence according to the sample data information of the corresponding production chain link, determine the comparison order for the actual data of the coal mine area to be mined according to the network risk highlighting ranking sequence, and call the actual data of the corresponding production chain link and the sample data information of the corresponding production chain link for comparison in turn according to the comparison order to determine the similarity, so as to determine whether the network security of the production chain link in coal mine production meets the standard, so as to determine whether to enable the safety monitoring and auditing system;

[0046] Or, obtain the actual data of the complete production chain link in the coal mine area to be mined and compare it with the sample data information of the corresponding complete production chain link to determine the similarity, so as to determine whether to enable the safety monitoring and auditing system.

[0047] Compared with the prior art, the present invention establishes a database by extracting sample data information of different production chain links in coal mine production in each mining area. By determining the network risk highlighting factors of each production chain link in coal mine production in different mining areas, the network risk highlighting characterization parameters of each production chain link in coal mine production in each mining area can be calculated, so as to quickly determine the network risk highlighting ranking sequence of each production chain link in coal mine production in each mining area, improving the efficiency of coal mine production network security monitoring. At the same time, by obtaining the actual data of coal mine production uploaded by the user side for the coal mining area to be mined and the sample data information of the corresponding production chain link, the maximum network risk highlighting characterization parameter of each production chain link in the coal mining area to be mined can be accurately obtained, improving the accuracy of coal mine production network security monitoring, and overcoming the problems of low efficiency and low accuracy in determining the network security of coal mine production in the corresponding mining area due to different network risk highlighting factors in different production chain links of coal mine production in different mining areas in the prior art. By determining the comparison order of the actual data for each production chain link in coal mine production, and by sequentially calling the actual data of the corresponding production chain link and the sample data information of the corresponding production chain link for comparison according to the comparison order, it is possible to accurately determine whether to enable the security monitoring and auditing system for the coal mine production network of the coal mining area to be mined uploaded by the user side.

[0048] In particular, the present invention compares the sample data information of different production chain links in the coal mine production of a single mining area with the data information of the corresponding production chain links in other mining areas, comprehensively considering the differences in network security monitoring of different production chain links. In actual situations, there are obvious network risk characteristics in some production chain links of coal mine production in some mining areas, and some network risk characteristics of coal mine production in some mining areas are more similar to the corresponding production chain links of coal mine production in other mining areas. Therefore, the network risk representativeness of the data information characteristics of each production chain link is different. In some cases, it is possible to identify whether to enable the security monitoring and auditing system based on the sample data information of the production chain link with obvious network risk representativeness. Therefore, the present invention considers determining the network risk highlighting characterization parameters of each production chain link, providing data support for selecting the network security monitoring method when performing network security analysis on the actual data of the coal mining area to be mined subsequently, and then adaptively selecting the network security analysis method for the actual data, reducing the data processing volume while ensuring reliability and improving the efficiency of coal mine production network security monitoring.

[0049] In particular, the present invention provides an important characteristic dimension for whether to turn on the network security monitoring and auditing system by obtaining the network complexity of each production chain link in the coal mine production of a single mining area. The network complexity reflects the structural characteristics of each production chain link in coal mine production, and environmental factors in different mining areas may cause differences in the network complexity of different production chain links in coal mine production. Combining the network complexity with the similarity of sample data information characterizes the network risk highlighting situation and data representativeness of the production chain link.

[0050] In particular, the present invention analyzes the actual data in the case where the maximum network risk prominent characterization parameter is greater than the predetermined prominent characterization parameter threshold benchmark. In the above case, it represents the production chain links where the network risk characteristics of coal mine production in the corresponding mining area are relatively prominent, and the data has strong representativeness. Therefore, determining the comparison order of the actual data for each production chain link in the mining area according to the network risk prominence ranking sequence, and sequentially calling the actual data of the corresponding production chain link and the corresponding production chain sample data information for comparison according to the comparison order can reduce the noise data introduced by the comparison of the entire production chain sample data information. Moreover, analyzing the actual data corresponding to the part with strong data representativeness first can improve the network security monitoring efficiency on the premise of ensuring reliability and ensure the accuracy of network security monitoring. BRIEF DESCRIPTION OF THE DRAWINGS

[0051] Figure 1 It is a flowchart of the steps of the network security monitoring method for intelligent coal mine production in an embodiment of the present invention;

[0052] Figure 2 It is a flowchart of the steps of calculating the network risk prominent characterization parameters of each production chain link in coal mine production in each mining area in an embodiment of the present invention;

[0053] Figure 3 It is a flowchart of the steps of obtaining the network complexity of each production chain link in coal mine production in a single mining area in an embodiment of the present invention;

[0054] Figure 4 It is a structural block diagram of the network security monitoring system for intelligent coal mine production in an embodiment of the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0055] In order to make the purpose and advantages of the present invention clearer, the present invention will be 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.

[0056] The preferred embodiments of the present invention will be described below with reference to the accompanying drawings. Those skilled in the art should understand that these embodiments are only used to explain the technical principle of the present invention and do not limit the protection scope of the present invention.

[0057] It should be noted that in the description of the present invention, unless otherwise clearly specified and limited, the term "connection" should be understood in a broad sense. For example, it can be a fixed connection, a detachable connection, or an integral connection; it can be a mechanical connection or an electrical connection; it can be directly connected or indirectly connected through an intermediate medium, and it can be the communication inside two components. For those skilled in the art, the specific meaning of the above terms in the present invention can be understood according to specific situations.

[0058] Please refer to Figure 1 as shown, which is a flowchart of the steps of the network security monitoring method for intelligent coal mine production in an embodiment of the present invention. The present invention provides a network security monitoring method for intelligent coal mine production, including:

[0059] Step S1: Extract the sample data information of each production chain link of coal mine production in each mining area to determine the network risk highlighting factors of each production chain link of coal mine production in different mining areas, including

[0060] Compare the sample data information of each production chain link in a single mining area with the sample data information of the corresponding production chain links of coal mine production in other mining areas respectively, calculate the average similarity, and obtain the network complexity of each production chain link of coal mine production in the single mining area;

[0061] Step S2: Calculate the network risk highlighting characterization parameters of each production chain link of coal mine production in each mining area according to the network risk highlighting factors of each production chain link of coal mine production in different mining areas, so as to determine the network risk highlighting ranking sequence of each production chain link of coal mine production in each mining area;

[0062] Step S3: Obtain the actual data of coal mine production uploaded by the mining area of the coal mine to be mined and the sample data information of the corresponding production chain link, obtain the maximum network risk highlighting characterization parameter of each production chain link of coal mine production in the corresponding mining area according to the sample data information, and analyze the actual data of the mining area of the coal mine to be mined according to the determination result, including

[0063] Obtain the network risk highlighting ranking sequence according to the sample data information of the corresponding production chain link, determine the comparison order for the actual data of the mining area of the coal mine to be mined according to the network risk highlighting ranking sequence, and sequentially call the actual data of the corresponding production chain link and the sample data information of the corresponding production chain link for comparison to determine the similarity, so as to determine whether the network security of the production chain link of coal mine production meets the standard, and determine whether to enable the security monitoring and auditing system;

[0064] Or, compare the actual data of the complete production chain link of the mining area of the coal mine to be mined with the sample data information of the corresponding complete production chain link to determine the similarity, so as to determine whether to enable the security monitoring and auditing system.

[0065] Specifically, for the mining areas of coal mine production, they are generally divided into Mine 1, Mine 2, Mine 3... Mine n (n is a positive integer) according to the mining order, which will not be elaborated here.

[0066] Specifically, there is no limit to the division of the production chain links of coal mine production. In implementation, it can be divided into data acquisition equipment links, data transmission cable links, production monitoring visualization equipment links, full life cycle management equipment links, or other forms can also be adopted, which will not be elaborated here.

[0067] Specifically, the present invention establishes a database by extracting sample data information of different production chain links in coal mine production in each mining area. By determining the network risk highlighting factors of each production chain link in coal mine production in different mining areas, the network risk highlighting characterization parameters of each production chain link in coal mine production in each mining area can be calculated. The purpose is to quantify the network risk highlighting situation of the corresponding production chain links in coal mine production in each mining area. In actual situations, there are obvious differences between the production chain links of coal mine production in some mining areas and the corresponding production chain links of coal mine production in other mining areas, and the production chain links have a certain network complexity. In this case, the network risk highlighting of the corresponding production chain links in such mining areas has strong data representativeness. Therefore, by identifying the network risk highlighting factors and calculating the network risk highlighting parameters corresponding to each production chain link to represent the above situation, for such mining areas, when conducting network security monitoring subsequently, data information of production chain links with strong data representativeness can be preferentially extracted for analysis, thereby improving the network security monitoring efficiency on the premise of ensuring the accuracy of network security monitoring.

[0068] Specifically, there is no limitation on the method for determining the similarity between data information. Corresponding data information processing algorithms or models can be imported into the logic component to achieve the corresponding functions. There is no specific limitation on the data information processing algorithms. For example, the method of calculating the similarity index can be adopted, or a pre-trained deep learning model can be used to extract the feature representation of the data information, and then the cosine similarity between the features can be calculated as the similarity. Of course, other methods can also be adopted, which will not be elaborated here.

[0069] Specifically, there is no limitation on the security monitoring and auditing system, which can detect and evaluate network abnormal behaviors, security threats, and illegal operations. For example, it can be one of the Anheng industrial security monitoring and auditing platform, Tianrongxin industrial control security monitoring and auditing system, and Qi'anxin industrial security monitoring and auditing system. Other methods can also be adopted, which will not be elaborated here.

[0070] Please refer to Figure 2 As shown, it is the flowchart of the steps for calculating the network risk highlighting characterization parameters of each production chain link in coal mine production in each embodiment of the present invention. In step S1, the process of calculating the network risk highlighting characterization parameters of each production chain link in coal mine production in each mining area includes

[0071] Step S11: Obtain the network risk highlighting factors, including the similarity mean value and the network complexity;

[0072] Step S12: Determine the ratio of the preset similarity standard threshold to the similarity mean value as the first network risk highlighting factor;

[0073] Step S13: Determine the ratio of the texture complexity to the preset texture complexity standard threshold as the second network risk highlighting factor;

[0074] Step S14: Determine the sum of the first network risk highlighting factor and the second network risk highlighting factor as the network risk highlighting characterization parameter.

[0075] In implementation, the preset similarity standard threshold is set in advance. Specifically, the similarity mean value of the same production chain links in coal mine production of various mining areas is determined in advance, and the similarity threshold is set as the product of the similarity mean value and the precision coefficient, where the precision coefficient is selected within the range of [0.85, 0.95].

[0076] In implementation, the preset network complexity standard threshold is set in advance. Specifically, the network complexity of data information in different production links of coal mine production in various mining areas is determined in advance, the network complexity mean value is calculated, and the network complexity standard threshold is set as the product of the network complexity mean value and the complexity offset coefficient, where the complexity offset coefficient is between the range of [1.1, 1.2].

[0077] In the present invention, by comparing the sample data information of different production chain links in the coal mine production of a single mining area with the sample data information of the corresponding production chain links in other types of mining areas, the differences in network risk characteristics of different production chain links are comprehensively considered. In actual situations, in some production chain links of coal mine production in some mining areas, there are obvious network risk characteristics, and the network risk characteristics of the production chain links in the coal mine production of some mining areas are more similar to the corresponding production chain links in the coal mine production of other mining areas. Therefore, the network risk representativeness of the sample data information of each production chain link is different. In some cases, the network security situation can be identified based on the sample data information of the part with strong network risk representativeness. Therefore, the present invention considers determining the network risk highlighting characterization parameter of each production chain link, providing data support for selecting whether to enable the security monitoring and auditing system when performing network security monitoring on actual data subsequently, and then adaptively selecting the network security monitoring method for actual data, reducing the data processing volume and improving the network security monitoring efficiency on the premise of ensuring reliability.

[0078] Please refer to Figure 3 As shown, it is the flowchart of the steps for obtaining the network complexity of each production chain link in the coal mine production of a single mining area in the embodiment of the present invention. In step S1, the process of obtaining the texture complexity of each part of the river crabs from a single origin includes

[0079] Step S21: Calibrate the types of devices and the total number of devices in the network of the production chain link of the coal mine in a single mining area;

[0080] Step S22: Calculate the ratio of the number of device types in the network to the reference device type number threshold as the first network complexity factor;

[0081] Step S23: Calculate the ratio of the total number of devices in the network to the threshold of the total number of reference devices as the second network complexity factor;

[0082] Step S24: Determine the network complexity by weighted summation of the first network complexity factor and the second network complexity factor.

[0083] Specifically, the threshold of the number of reference device types and the threshold of the total number of reference devices are preset. Among them, the product of the average number of device types in the three-month historical period of this system and the accuracy coefficient is used as the threshold of the number of reference device types, and the accuracy coefficient is in the interval [0.90, 0.98]. The product of the average number of the total number of devices in the three-month historical period of this system and the deviation coefficient is used as the threshold of the total number of reference devices, and the deviation coefficient is in the interval [0.95, 0.99].

[0084] The present invention provides an important feature dimension for network security monitoring of the to-be-mined mining area by obtaining the network complexity of each production chain link in coal mine production of a single mining area. The network complexity reflects the network risk characteristics of production chain links such as the coal mine production data acquisition device link and the data transmission cable link. Environmental factors in different mining areas may cause the network complexity of different production chain links in coal mine production to be different. Combining the network complexity with the similarity of sample data information characterizes the prominent situation of network risks in production chain links.

[0085] Specifically, the process of determining the prominent ranking sequence of network risks in each production chain link of coal mine production in each mining area includes

[0086] Determine the prominent characterization parameters of network risks corresponding to each production chain link of coal mine production in a single mining area;

[0087] Arrange the prominent characterization parameters of network risks in descending order to obtain the prominent ranking sequence of network risks.

[0088] Specifically, in step S3, analyze the actual data of the to-be-mined coal mine mining area according to the determination result, including

[0089] Obtain the maximum prominent characterization parameter of network risks for each production chain link of coal mine production in the corresponding mining area according to the sample data information;

[0090] If the maximum network risk prominent characterization parameter is greater than the predetermined prominent characterization parameter threshold benchmark, obtain the network risk prominent ranking sequence according to the sample data information of the corresponding production chain link, determine the comparison order of the actual data for the coal mine mining area to be mined according to the network risk prominent ranking sequence, and call the actual data of the corresponding production chain link and the sample data information of the corresponding production chain link for comparison in turn to determine the similarity, so as to determine whether the network security of the production chain link of coal mine production meets the standard and whether to enable the security monitoring and auditing system;

[0091] If the maximum network risk prominent characterization parameter is less than or equal to the predetermined prominent characterization parameter threshold benchmark, obtain the actual data of the complete production chain link of the coal mine mining area to be mined and compare it with the sample data information of the corresponding complete production chain link to determine the similarity, so as to determine whether to enable the security monitoring and auditing system.

[0092] In implementation, the predetermined network risk prominent characterization parameter threshold is in the interval [2.15, 2.45].

[0093] Specifically, the process of determining the comparison order of the actual data of each production chain link of coal mine production in the mining area to be mined according to the network risk prominent ranking sequence includes,

[0094] Determine the corresponding parts of the network risk prominent ranking sequence in turn to obtain the production chain link ranking and generate the production chain link serial number ranking;

[0095] Among them, each production chain link corresponds to a production chain link serial number one by one.

[0096] In implementation, optionally,

[0097] Serial numbers can be assigned to the production chain links. Taking the division of four production chain links as an example, 1 - data acquisition equipment link, 2 - data transmission cable link, 3 - production monitoring visualization equipment link, 4 - full life cycle management equipment link;

[0098] For example, the network risk prominent characterization parameter of the data acquisition equipment link is 2.6, the network risk prominent characterization parameter of the data transmission cable link is 2.75, the network risk prominent characterization parameter of the production monitoring visualization equipment link is 2.55, and the network risk prominent characterization parameter of the full life cycle management equipment link is 2.65;

[0099] The corresponding feature prominent ranking sequence is 2.75, 2.65, 2.6, 2.55;

[0100] The corresponding part ranking is 2, 4, 1, 3.

[0101] Specifically, in step S3, the actual data of the corresponding production chain link and the sample data information of the corresponding production chain link are called in sequence according to the comparison order to determine the similarity, so as to determine whether the network security of the production chain link of coal mine production meets the standard, and to determine whether to enable the security monitoring and auditing system, including,

[0102] If the similarity corresponding to the actual data of any production chain link is greater than the preset similarity standard threshold of the production chain link, it is determined that the network security meets the standard, and the comparison of the actual data of the corresponding production chain link and the sample data information of the corresponding production chain link is stopped;

[0103] If the similarity corresponding to the actual data of each production chain link is less than the preset similarity standard threshold of the production chain link, it is determined to enable the security monitoring and auditing system.

[0104] In implementation, the similarity standard threshold of the production chain link is obtained by presetting. A number of sample data information of the same production chain link of coal mine production in the same mining area are obtained in advance, the average similarity between the sample data information is determined, and the ratio of the average similarity to the offset coefficient is determined as the similarity standard threshold of the production chain link. The local image offset coefficient is selected in the interval [0.85, 0.95].

[0105] Specifically, in step S3, the actual data of the complete production chain link of the coal mine to be mined in the mining area and the sample data information of the corresponding complete production chain link are obtained for comparison to determine the similarity, so as to determine whether to enable the security monitoring and auditing system, including,

[0106] If the similarity between the actual data of the complete production chain link of the current coal mine to be mined in the mining area and the sample data information of the corresponding complete production chain link is less than the preset similarity standard threshold of the complete coal mine, it is determined to enable the security monitoring and auditing system.

[0107] Specifically, the sample similarity standard threshold of the complete production chain link is obtained by presetting. A number of complete sample data information of all production chain links of coal mine production in the same mining area are obtained in advance, the average similarity between the complete sample data information is determined, and the ratio of the average similarity to the offset coefficient is determined as the similarity standard threshold of the production chain link. The complete image offset coefficient is selected in the interval [1.05, 1.15].

[0108] Specifically, the actual data of coal mine production uploaded by the coal mine to be mined in the mining area shall include the actual data of each production chain link of coal mine production and the actual data of the complete production chain link of coal mine production.

[0109] Please refer to Figure 4As shown, it is a structural block diagram of the network security monitoring system for intelligent coal mine production in an embodiment of the present invention. The present invention also provides a network security monitoring system for intelligent coal mine production, including

[0110] A database module, which is used to store the sample data information of each production chain link of coal mine production in each mining area extracted in advance, and determine the network risk highlighting factors of each production chain link in different mining areas;

[0111] A network risk assessment module, which is connected to the database module, and is used to calculate the network risk highlighting characterization parameters of each production chain link of coal mine production in each mining area according to the network risk highlighting factors of each production chain link of coal mine production in different mining areas, so as to determine the network risk highlighting sorting sequence of each production chain link of coal mine production in each mining area;

[0112] An information receiving module, which is connected to the user terminal. The user obtains the actual data of coal mine production uploaded by the to-be-mined coal mine area uploaded by the user terminal and the sample data information of the corresponding production chain link;

[0113] A verification module, which is respectively connected to the database module, the network risk assessment module and the information receiving module, and is used to obtain the maximum network risk highlighting characterization parameter of each production chain link of coal mine production in the corresponding mining area according to the sample data information, and analyze the actual data of the to-be-mined coal mine area according to the determination result, including

[0114] Obtain the network risk highlighting sorting sequence according to the sample data information of the corresponding production chain link, determine the comparison order for the actual data of the to-be-mined coal mine area according to the network risk highlighting sorting sequence, and sequentially call the actual data of the corresponding production chain link and the sample data information of the corresponding production chain link for comparison to determine the similarity, so as to determine whether the network security of the production chain link of coal mine production meets the standard, so as to determine whether to enable the security monitoring and auditing system;

[0115] Or, obtain the actual data of the complete production chain link of the to-be-mined coal mine area and the sample data information of the corresponding complete production chain link for comparison to determine the similarity, so as to determine whether to enable the security monitoring and auditing system.

[0116] Specifically, each module can be composed of logic components, and the logic components include field programmable components, computers or microprocessors in computers.

[0117] The present invention analyzes the actual data in the case where the maximum network risk prominent characterization parameter is greater than the predetermined prominent characterization parameter threshold reference. In the above case, it represents the production chain link where the network risk characteristics of coal mine production in the corresponding mining area are relatively prominent, and the data has strong representativeness. Therefore, it is determined to determine the comparison order of the actual data of each production chain link for the coal mine production in the mining area according to the network risk prominence sorting sequence, and successively call the actual data of the corresponding production chain link and the corresponding production chain sample data information for comparison according to the comparison order, which can reduce the noise data introduced by the comparison of all industrial chain links. Moreover, the actual data corresponding to the industrial chain link with strong representativeness is preferentially analyzed, which can improve the network security monitoring efficiency on the premise of ensuring reliability and ensure the accuracy of network security monitoring.

[0118] So far, the technical solution of the present invention has been described in conjunction with the preferred embodiments shown in the 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.

Claims

1. A network security monitoring method for intelligent coal mine production, characterized in that, Including: Extracting the sample data information of each production chain link in coal mine production in each mining area to determine the network risk highlighting factors of each production chain link in coal mine production in different mining areas, including Comparing the sample data information of each production chain link in a single mining area with the sample data information of the corresponding production chain link in coal mine production in other mining areas respectively, solving the average similarity, and obtaining the network complexity of each production chain link in the coal mine production of the single mining area; Calculating the network risk highlighting characterization parameters of each production chain link in coal mine production in each mining area according to the network risk highlighting factors of each production chain link in coal mine production in different mining areas to determine the network risk highlighting ranking sequence of each production chain link in coal mine production in each mining area; Obtaining the actual data of coal mine production uploaded by the mining area of the coal mine to be mined and the sample data information of the corresponding production chain link, obtaining the maximum network risk highlighting characterization parameter of each production chain link in the coal mine production of the corresponding mining area according to the sample data information, and analyzing the actual data of the mining area of the coal mine to be mined according to the determination result, including Obtaining the network risk highlighting ranking sequence according to the sample data information of the corresponding production chain link, determining the comparison order for the actual data of the mining area of the coal mine to be mined according to the network risk highlighting ranking sequence, and sequentially calling the actual data of the corresponding production chain link and the sample data information of the corresponding production chain link for comparison according to the comparison order to determine the similarity, so as to determine whether the network security of the production chain link of coal mine production meets the standard and determine whether to enable the security monitoring and auditing system; Or, comparing the actual data of the complete production chain link in the mining area of the coal mine to be mined with the sample data information of the corresponding complete production chain link to determine the similarity, so as to determine whether to enable the security monitoring and auditing system.

2. The network security monitoring method for intelligent coal mine production according to claim 1, wherein The process of calculating the network risk highlighting characterization parameters of each production chain link in coal mine production in each mining area includes Obtaining network risk highlighting factors, including the average similarity and network complexity; Determining the ratio of the preset similarity standard threshold to the average similarity as the first network risk highlighting factor; Determining the ratio of the network complexity to the preset network complexity standard threshold as the second network risk highlighting factor; Determining the sum of the first network risk highlighting factor and the second network risk highlighting factor as the network risk highlighting characterization parameter.

3. The network security monitoring method for intelligent coal mine production according to claim 2, wherein, The process of obtaining the network complexity of each production chain link in the coal mine production of the single mining area includes Calibrating the types of equipment and the total number of equipment in the network of the production chain link in the coal mine of the single mining area; Calculating the ratio of the number of equipment types in the network to the reference number threshold of equipment types as the first network complexity factor; Calculating the ratio of the total number of equipment in the network to the reference total number threshold of equipment as the second network complexity factor; Determining the weighted sum of the first network complexity factor and the second network complexity factor as the network complexity.

4. The network security monitoring method for intelligent coal mine production according to claim 1, wherein, The process of determining the network risk highlighting ranking sequence of each production chain link in coal mine production in each mining area includes Determining the network risk highlighting characterization parameters corresponding to each production chain link in the coal mine production of the single mining area; Arranging the network risk highlighting characterization parameters in descending order to obtain the network risk highlighting ranking sequence.

5. The network security monitoring method for intelligent coal mine production according to claim 1, wherein Analyze the actual data of the coal mine area to be mined according to the determination result, including Obtain the maximum network risk highlighting characterization parameters for each production chain link of coal mine production in the corresponding mining area according to the sample data information; If the maximum network risk highlighting characterization parameter is greater than the predetermined highlighting characterization parameter threshold benchmark, obtain the network risk highlighting ranking sequence according to the sample data information of the corresponding production chain link, determine the comparison order for the actual data of the coal mine area to be mined according to the network risk highlighting ranking sequence, and sequentially call the actual data of the corresponding production chain link and the sample data information of the corresponding production chain link for comparison according to the comparison order to determine the similarity, so as to determine whether the network security of the production chain link of coal mine production meets the standard and determine whether to enable the security monitoring and auditing system; If the maximum network risk highlighting characterization parameter is less than or equal to the predetermined highlighting characterization parameter threshold benchmark, obtain the actual data of the complete production chain link of the coal mine area to be mined and the sample data information of the corresponding complete production chain link for comparison to determine the similarity, so as to determine whether to enable the security monitoring and auditing system.

6. The network security monitoring method for intelligent coal mine production according to claim 4, wherein, The process of determining the comparison order for the actual data of the coal mine area to be mined according to the network risk highlighting ranking sequence includes Sequentially determine the production chain links corresponding to the network risk highlighting ranking sequence to obtain the ranking of each production chain link and generate the production chain link serial number ranking; Among them, each production chain link corresponds one-to-one with the production chain link serial number.

7. The network security monitoring method for intelligent coal mine production according to claim 1, characterized in that, Sequentially call the actual data of the corresponding production chain link and the sample data information of the corresponding production chain link for comparison according to the comparison order to determine the similarity, so as to determine whether the network security of the production chain link of coal mine production meets the standard and determine whether to enable the security monitoring and auditing system, including If the similarity corresponding to the actual data of any production chain link is greater than the preset production chain link similarity standard threshold, it is determined that the network security meets the standard, and the comparison of the actual data of the corresponding production chain link and the sample data information of the corresponding production chain link is stopped; If the similarity corresponding to the actual data of each production chain link is less than the preset production chain link similarity standard threshold, it is determined to enable the security monitoring and auditing system.

8. The network security monitoring method for intelligent coal mine production according to claim 1, wherein, Obtain the actual data of the complete production chain link of the coal mine area to be mined and the sample data information of the corresponding complete production chain link for comparison to determine the similarity, so as to determine whether to enable the security monitoring and auditing system, including If the similarity between the actual data of the complete production chain link of the current coal mine area to be mined and the sample data information of the corresponding complete production chain link is less than the preset complete coal mine similarity standard threshold, it is determined to enable the security monitoring and auditing system.

9. The network security monitoring method for intelligent coal mine production according to claim 1, wherein The actual data of coal mine production uploaded by the coal mine area to be mined shall include the actual data of each production chain link of coal mine production and the actual data of the complete production chain link of coal mine production.

10. A system using the network security monitoring method for intelligent coal mine production according to any one of claims 1 to 9, characterized in that, Including A database module for storing the sample data information of each production chain link of coal mine production in each mining area extracted in advance and determining the network risk highlighting factors of each production chain link in different mining areas; A network risk assessment module, which is connected to the database module and is used to calculate the network risk prominent characterization parameters of each production chain link of coal mine production in each mining area according to the network risk prominent factors of each production chain link of coal mine production in different mining areas, so as to determine the network risk prominent ranking sequence of each production chain link of coal mine production in each mining area; An information receiving module, which is connected to the user terminal, and the user obtains the actual data of coal mine production uploaded by the coal mine mining area to be mined and the sample data information of the corresponding production chain link; A verification module, which is respectively connected to the database module, the network risk assessment module and the information receiving module, and is used to obtain the maximum network risk prominent characterization parameter of each production chain link of coal mine production in the corresponding mining area according to the sample data information, and analyze the actual data of the coal mine mining area to be mined according to the determination result, including, Obtaining the network risk prominent ranking sequence according to the sample data information of the corresponding production chain link, determining the comparison order for the actual data of the coal mine mining area to be mined according to the network risk prominent ranking sequence, and sequentially calling the actual data of the corresponding production chain link and the sample data information of the corresponding production chain link for comparison according to the comparison order to determine the similarity, so as to determine whether the network security of the production chain link of coal mine production meets the standard, so as to determine whether to enable the security monitoring and auditing system; Or, obtaining the actual data of the complete production chain link of the coal mine mining area to be mined and the sample data information of the corresponding complete production chain link for comparison to determine the similarity, so as to determine whether to enable the security monitoring and auditing system.

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