Network node evaluation system based on grid information parameter analysis

Abstract

The application discloses a network node evaluation system based on power grid information parameter analysis and relates to the technical field of network evaluation systems. In order to solve the problem that in the prior art, with the increase of each node, corresponding information is increased, each node is calculated respectively, and the calculation amount is large, the system burden is increased, and the overall operation of the system is affected, the network node evaluation system based on power grid information parameter analysis comprises a power grid parameter processing unit, a network node analysis unit and a network node evaluation unit. The standard power grid information parameters are input into a power grid parameter classification model for classification, the power grid parameter data is classified, efficient vector calculation is performed, accurate and rapid classification and label storage of a large amount of data are completed, the data position is quickly located by relying on the label, the system search time is reduced, the system processing burden is reduced for subsequent network node analysis, the system operation efficiency is improved, and the reliable operation of the system is further ensured.

Description

Technical Field

[0001] This invention relates to the field of network evaluation system technology, and in particular to a network node evaluation system based on power grid information parameter analysis. Background Technology

[0002] Network nodes in a power grid are the basic units of the power information network; only by ensuring their security can risks be effectively reduced. There are already relevant patents regarding network node assessment in power grid information systems. For example, Chinese patent CN113379248A discloses a power grid risk assessment and early warning method based on complex network theory. This method includes: step 1, establishing an abstract complex network with the power grid as the object; step 2, calculating the node degree index, betweenness index, efficiency loss coefficient index, and network cohesion change rate index for each node; step 3, combining these indices into a power grid risk index; and step 4, outputting the risk assessment results for each node. This invention can achieve power grid network risk assessment and early warning.

[0003] While the aforementioned patents can achieve power grid network risk assessment and early warning, the following problems still exist in practical use:

[0004] In existing technologies, each additional node adds a corresponding amount of information. Calculating each node separately can easily lead to a large amount of computation and increase the system burden, thereby affecting the overall operation of the system.

[0005] 2. In existing technologies, for complex network environments, the risks present in the real environment cannot be accurately reflected in practical applications, and a unified evaluation model cannot be established for data evaluation, resulting in low accuracy of evaluation results. Summary of the Invention

[0006] The purpose of this invention is to provide a network node evaluation system based on power grid information parameter analysis. By classifying the power grid information parameters to obtain multiple sub-power grid parameter data, and evaluating the network nodes based on the network node evaluation model, the system achieves network node security risk assessment, thereby solving the problems mentioned in the background art.

[0007] To achieve the above objectives, the present invention provides the following technical solution:

[0008] A network node evaluation system based on power grid information parameter analysis includes:

[0009] A power grid parameter processing unit is used to acquire power grid information parameters, construct a power grid parameter classification model based on the power grid information parameters, and simultaneously input the power grid information parameters into the power grid parameter classification model for classification to obtain multiple sub-power grid parameter data.

[0010] The network node analysis unit is used to obtain each data receiving terminal from the data transmission link corresponding to the subgrid parameter data, and at the same time, obtain the interaction record of the network layer of each data receiving terminal when receiving data, and extract the network node.

[0011] The network node evaluation unit is used to construct a network node evaluation model, input the network node into the network node evaluation model for calculation, determine the maximum risk assessment value of the data transmission link of the power grid information parameters, and perform qualification screening of the network node based on the maximum risk assessment value.

[0012] Furthermore, the power grid parameter processing unit includes:

[0013] The data acquisition module is used to acquire the power grid information parameters from the power grid, determine the standard data format of the power grid information parameters, and standardize the power grid information parameters according to the standard data format to obtain standard power grid information parameters.

[0014] The data classification module is used for:

[0015] The standard power grid information parameters are input into the power grid parameter classification model for classification, and the parameter data labels corresponding to the data are obtained based on the power grid parameter classification model.

[0016] Based on the parameter data labels, the standard power grid information parameters are clustered to obtain multiple sub-power grid parameter data.

[0017] Furthermore, after obtaining multiple sub-grid parameter data, it also includes:

[0018] The power grid parameter data is integrated and mapped into a fixed-dimensional vector space based on the labels for classification and storage.

[0019] The classification features corresponding to the power grid parameter data are determined, the data format of the power grid parameter data is obtained based on the classification features, and the data format of the power grid parameter data is converted based on the data format to generate a target data transmission file.

[0020] Furthermore, the network node analysis unit includes:

[0021] The information synchronization module is used to determine the data transmission link between the target data transmission file and the data receiving terminal, receive the target data transmission file based on the data receiving terminal, read multiple sub-grid parameter data in the target data transmission file, and determine whether the multiple sub-grid parameter data are complete.

[0022] The network node extraction module is used to determine the data acquisition rules of the data receiving terminal, generate a data transmission network protocol between the two based on the data acquisition rules and the classification characteristics of the target data transmission file, and obtain the network node of each target data transmission file in the data transmission link based on the data transmission network protocol.

[0023] Furthermore, the network node extraction module is also used for:

[0024] The standard network flow of a network node is found in the network flow table, and the initial data characteristics of the network node are determined based on the standard network flow.

[0025] The data receiving terminal retrieves a data resource sample, runs the data transmission network protocol based on the data resource sample, and obtains the running results.

[0026] Based on the running results, obtain the network nodes between the data receiving terminal and the target data transmission file, generate an interaction record, and obtain the data transmission characteristic parameters of the data transmission network protocol based on the interaction record;

[0027] Based on the data transmission characteristic parameters, a grid chain is generated between each data receiving terminal and the target data transmission file.

[0028] Furthermore, the network node evaluation unit includes:

[0029] The evaluation model construction module is used to construct network node data calculation formulas based on network node data, construct power grid parameter data calculation formulas based on the power grid parameter data, and merge the network node data calculation formulas and the power grid parameter data calculation formulas to construct a network node evaluation model.

[0030] The node evaluation module is used to input the network node into the network node evaluation model for calculation, obtain the network node security quality evaluation coefficient, and determine whether the network node is qualified based on the network node security quality evaluation coefficient.

[0031] Furthermore, the process of obtaining the network node security quality assessment coefficient specifically involves:

[0032] The network node data and power grid parameter data are respectively analyzed to determine the load of the network node data in the power grid parameter data, and the maximum risk assessment value of the network node is determined according to the safety quality assessment coefficient of the network node.

[0033] Obtain historical successful transmission data for each data receiving terminal, parse the historical successful transmission data to determine its integrity and security, and assess the threat risk index and vulnerability risk index of the data receiving terminal based on the integrity and security.

[0034] Based on the maximum risk assessment value of the network node and the threat risk index and vulnerability risk index, the network node assessment model is used to calculate the network node security quality assessment coefficient when transmitting power grid parameter data to the network node.

[0035] Furthermore, the node evaluation module is also used for:

[0036] The security assessment score of the network node is determined based on the network node security quality assessment coefficient, and the security assessment score is compared with a preset security assessment threshold to determine whether the network node is within the safe operating range.

[0037] When the security assessment score is equal to or greater than the preset security assessment threshold, the network node is determined to be at risk. At the same time, when the network node is at risk, an early warning report is generated and the data transmission link corresponding to the network node is obtained.

[0038] The data receiving terminal is determined based on the data transmission link corresponding to the network node, and the early warning report is transmitted to the data receiving terminal via the Internet of Things.

[0039] Otherwise, the network node is determined to be secure.

[0040] Furthermore, the data acquisition module obtains the power grid information parameters from the power grid, determines the standard data format of the power grid information parameters, and standardizes the power grid information parameters according to the standard data format to obtain standard power grid information parameters, including:

[0041] The power grid information parameters are divided into core data segments, and the distribution of associated data for each core data segment is determined based on the segmentation results.

[0042] The data structure corresponding to the power grid information parameters is obtained based on the associated data distribution of each core data.

[0043] Generate a protocol configuration file corresponding to the power grid information parameters based on the data structure;

[0044] According to the protocol configuration file, the power grid information parameters are decomposed into multiple types of power grid sub-information;

[0045] Determine the data structure object of each type of power grid sub-information based on the information data distribution in each type of power grid sub-information;

[0046] The data structure object of each type of power grid sub-information is serialized to obtain a byte sequence containing all the information content in the power grid sub-information of that type;

[0047] Input the byte sequence of all information content in each type of power grid sub-information into the standardized dictionary library to determine the matching standardized dictionary for that type of power grid sub-information;

[0048] Obtain the corresponding preset matching model from the standardized matching dictionary for each type of power grid sub-information;

[0049] Based on the standardized matching dictionary for each type of power grid sub-information and the corresponding pre-set matching model

[0050] Determine the standard data format for the power grid information parameters;

[0051] All power grid sub-information in the power grid information parameters is converted into the standard data format, and a standardized differential dataset for each power grid sub-information is obtained based on the conversion result.

[0052] Retrieve the current field of outlier data in the standardized differential dataset of each power grid sub-information;

[0053] Retrieve the standardization component corresponding to the current field from the preset database, and use the standardization component to convert the current field of the abnormal data in the standardized differential dataset of each power grid sub-information into a standard field;

[0054] Standard power grid information parameters are generated based on the transformed abnormal and normal data.

[0055] Furthermore, the step of calculating the network node security quality assessment coefficient when transmitting power grid parameter data to the network node based on the maximum risk assessment value of the network node and the threat risk index and vulnerability risk index inputted into the network node assessment model includes:

[0056] The risk profile of a network node is determined based on its maximum risk assessment value.

[0057] Based on the aforementioned threat risk index, the proactive external risk posture of network nodes is determined.

[0058] The vulnerability risk index is used to determine the passive risk status of network nodes;

[0059] The comprehensive security posture index of a network node is calculated by using a preset security posture assessment function to evaluate the node's own risk posture, active external risk posture, and passive external risk posture.

[0060]

[0061] in, Let f() represent the comprehensive security posture index of network nodes, and let f() represent the preset security posture assessment function. This is represented as the first weight value, with a value of 0.5. This represents the risk profile of a network node. This is represented as the second weight value, with a value of 0.25. This represents the proactive external risk posture of network nodes. This is represented as the third weight value, with a value of 0.25. This represents the passive risk attitude of a network node, where e is the natural constant with a value of 2.72. This represents the network security assurance coefficient for the network and its nodes.

[0062] The security quality level of a network node is determined based on its comprehensive security posture index.

[0063] When the security quality level is medium or high, the network node is considered secure; when the security quality level is low, the network node is considered insecure.

[0064] The maximum risk assessment value of the network node, the threat risk index, and the vulnerability risk index are input into the network node assessment model to calculate the network node security quality assessment coefficient when transmitting power grid parameter data from the network node:

[0065]

[0066] Wherein, F represents the network node when transmitting power grid parameter data to the network node.

[0067] Safety and quality assessment coefficient This represents the maximum risk assessment value for a network node. This represents the network node risk reference threshold under standard conditions, entered into the network node assessment model. This is expressed as a threat risk index. This represents the reference threshold for the threat risk index under standard conditions, entered into the network node assessment model. This is represented as a vulnerability risk index. This represents the reference threshold for the vulnerability risk index under standard conditions, entered into the network node assessment model. This represents the utilization rate of the network nodes when transmitting power grid parameter data to the network nodes. This represents the latency of the network node when transmitting power grid parameter data to the network node.

[0068] Compared with the prior art, the beneficial effects of the present invention are:

[0069] By inputting standard power grid information parameters into the power grid parameter classification model for classification, the power grid parameter data can be classified. Through efficient vector calculation, a large amount of data can be accurately and quickly classified and tagged for storage. Relying on the tags, the data location can be quickly located, reducing the system retrieval time, alleviating the system processing burden for subsequent network node analysis, improving system operating efficiency, and further ensuring the reliable operation of the system.

[0070] By classifying power grid parameter data and converting and transmitting the data according to the classification results, accurate and effective evaluation of network nodes in different transmission links is achieved, improving the accuracy of network node analysis. The data transmission network protocol is determined to serve as the data transmission carrier, the operating data of data resource samples is obtained and interactive records are generated, and a grid chain is generated between each data receiving terminal and the target data transmission file, ensuring the stability and efficiency of the data transmission process and improving the adaptability and scalability of the mechanism.

[0071] By calculating the security index of each data receiving terminal, risky terminals and secure terminals can be effectively distinguished. This prevents data receiving terminals from introducing their own vulnerabilities or security threats into the power grid along with the data, thus avoiding data loss or power grid infection by viruses. This improves security and stability. When network nodes are at risk, an early warning report is generated and transmitted to the data receiving terminal via the Internet of Things. This allows staff to promptly understand and accurately locate data receiving terminals at risk and take corresponding remedial measures. This improves practicality and reduces the economic losses and other harms to the power grid caused by network security issues. Attached Figure Description

[0072] Figure 1 This is a block diagram of the network node evaluation system based on power grid information parameter analysis of the present invention;

[0073] Figure 2 This is a flowchart of the network node evaluation system based on power grid information parameter analysis of the present invention. Detailed Implementation

[0074] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0075] To address the technical challenge that refined modeling consumes significant computational resources and negatively impacts risk assessment and early warning effectiveness due to increased grid load, expanded coverage, and increased integration with communication and integrated energy systems, please refer to [link to relevant documentation]. Figure 1-2 This embodiment provides the following technical solution:

[0076] A network node evaluation system based on power grid information parameter analysis includes: a power grid parameter processing unit, used to acquire power grid information parameters, construct a power grid parameter classification model based on the power grid information parameters, and input the power grid information parameters into the power grid parameter classification model for classification to obtain multiple sub-power grid parameter data; a network node analysis unit, used to acquire each data receiving terminal from the data transmission link corresponding to the sub-power grid parameter data, and simultaneously acquire the interaction record of the network layer of each data receiving terminal when receiving data, and extract the network node; and a network node evaluation unit, used to construct a network node evaluation model, input the network node into the network node evaluation model for calculation, determine the maximum risk assessment value of the data transmission link of the power grid information parameters, and perform qualification screening of the network node based on the maximum risk assessment value.

[0077] Specifically, by classifying the power grid information parameters to obtain multiple sub-power grid parameter data, obtaining each data receiving terminal from the data transmission link corresponding to the sub-power grid parameter data, extracting network nodes from the data transmission link, evaluating the network nodes based on the network node evaluation model, screening network nodes for qualification based on the calculation results, and assessing the security risks of the nodes and the risks of the data receiving terminals, the network node security risk assessment is realized.

[0078] To address the technical problem in existing technologies where adding a new node increases information and requires separate calculations for each node, leading to excessive computation and increased system load, thus impacting overall system operation, please refer to [link to relevant documentation]. Figure 1-2 This embodiment provides the following technical solution:

[0079] The power grid parameter processing unit includes a data acquisition module, which is used to acquire the power grid information parameters from the power grid, determine the standard data format of the power grid information parameters, and standardize the power grid information parameters according to the standard data format to obtain standard power grid information parameters.

[0080] The data classification module is used to input the standard power grid information parameters into the power grid parameter classification model for classification, and obtain the parameter data label corresponding to the data based on the power grid parameter classification model; and to perform clustering processing on the standard power grid information parameters based on the parameter data label to obtain multiple sub-power grid parameter data.

[0081] After obtaining multiple sub-grid parameter data, the method further includes: integrating the grid parameter data according to the labels and mapping it to a fixed-dimensional vector space for classification and storage; determining the classification features corresponding to the grid parameter data; obtaining the data format of the grid parameter data based on the classification features; and performing data format conversion of the grid parameter data based on the data format to generate a target data transmission file.

[0082] Specifically, by inputting standard power grid information parameters into the power grid parameter classification model for classification, the power grid parameter data is classified, and the power grid parameters are tagged and stored, mapped to a fixed-dimensional vector space. Through efficient vector calculation, a large amount of data is accurately and quickly classified and tagged for storage. Relying on the tags, the data location is quickly located, reducing the system retrieval time, alleviating the system processing burden for subsequent network node analysis, improving system operating efficiency, and further ensuring the reliable operation of the system.

[0083] To address the shortcomings of existing network node analysis techniques, such as the inability to determine the data reception rules of data receiving terminals, which leads to omissions in network node extraction, please refer to [the relevant documentation / reference]. Figure 1-2 This embodiment provides the following technical solution:

[0084] The network node analysis unit includes an information synchronization module, which is used to determine the data transmission link between the target data transmission file and the data receiving terminal, receive the target data transmission file based on the data receiving terminal, and read multiple sub-grid parameter data in the target data transmission file to determine whether the multiple sub-grid parameter data are complete;

[0085] The network node extraction module is used to determine the data acquisition rules of the data receiving terminal, generate a data transmission network protocol between the two based on the data acquisition rules and the classification characteristics of the target data transmission file, and obtain the network node of each target data transmission file in the data transmission link based on the data transmission network protocol.

[0086] The network node extraction module is further configured to: search for standard network flows of network nodes in the network flow table; determine the initial data characteristics of network nodes based on the standard network flows; retrieve data resource samples at the data receiving terminal; run the data transmission network protocol based on the data resource samples; obtain the running results; obtain the network nodes between the data receiving terminal and the target data transmission file based on the running results; generate interaction records; obtain data transmission characteristic parameters of the data transmission network protocol based on the interaction records; and generate a mesh chain between each data receiving terminal and the target data transmission file based on the data transmission characteristic parameters.

[0087] Specifically, by classifying power grid parameter data and converting and transmitting the data according to the classification results, accurate and effective evaluation of network nodes in different transmission links is achieved, improving the accuracy of network node analysis. A data transmission network protocol is determined to serve as the data transmission carrier. Operational data of data resource samples is acquired and interaction records are generated. A grid chain is created between each data receiving terminal and the target data transmission file, ensuring the stability and efficiency of the data transmission process. The constructed grid chain provides a data sharing mechanism, ensuring stable operation of both in the same network space and making subsequent data sharing mechanisms more adaptable to both, thus improving the mechanism's adaptability and scalability.

[0088] To address the technical problem in existing technologies that fail to accurately reflect real-world hazards in complex network environments and lack a unified evaluation model for data assessment, resulting in low accuracy of evaluation results, please refer to [link to relevant documentation]. Figure 1-2 This embodiment provides the following technical solution:

[0089] The network node evaluation unit includes an evaluation model construction module, which is used to construct a network node data calculation formula based on network node data, construct a power grid parameter data calculation formula based on the power grid parameter data, and merge the network node data calculation formula and the power grid parameter data calculation formula to construct a network node evaluation model; and a node evaluation module, which is used to input the network node into the network node evaluation model for calculation, obtain a network node safety quality evaluation coefficient, and determine whether the network node is qualified based on the network node safety quality evaluation coefficient.

[0090] The node evaluation module is further configured to determine the security evaluation score of the network node based on the network node security quality evaluation coefficient, and compare the security evaluation score with a preset security evaluation threshold to determine whether the network node is within a safe operating range; when the security evaluation score is equal to or greater than the preset security evaluation threshold, the network node is determined to be at risk, and an early warning report is generated, and the data transmission link corresponding to the network node is obtained; a data receiving terminal is determined based on the data transmission link corresponding to the network node, and the early warning report is transmitted to the data receiving terminal via the Internet of Things; otherwise, the network node is determined to be safe.

[0091] Specifically, by calculating the security index of each data receiving terminal, risky terminals and secure terminals can be effectively distinguished. This prevents data receiving terminals from introducing their own vulnerabilities or security threats into the power grid along with the data, thus avoiding data loss or power grid infection by viruses. This improves security and stability. When network nodes are at risk, an early warning report is generated and transmitted to the data receiving terminal via the Internet of Things. This allows staff to promptly understand and accurately locate data receiving terminals at risk and take corresponding remedial measures. This improves practicality, makes the processing results more reasonable and accurate, and reduces the economic losses and other related harms to the power grid caused by network security issues.

[0092] To address the technical problem in existing technologies where the inability to select qualified network nodes based on data transmission efficiency and transmission channels for power grid parameters significantly increases the risks associated with power grid parameter transmission, please refer to [link to relevant documentation]. Figure 1-2 This embodiment provides the following technical solution:

[0093] The network node security quality assessment coefficient is obtained by: performing simulations on the network node data and power grid parameter data respectively to determine the load of the network node data in the power grid parameter data; determining the maximum risk assessment value of the network node based on the network node security quality assessment coefficient; acquiring historical successful transmission data of each data receiving terminal; parsing the historical successful transmission data to determine its integrity and security; assessing the threat risk index and vulnerability risk index of the data receiving terminal based on the integrity and security; and inputting the maximum risk assessment value of the network node and the threat risk index and vulnerability risk index into the network node assessment model to calculate the network node security quality assessment coefficient when transmitting power grid parameter data from the network node data.

[0094] Specifically, by calculating network node data and power grid parameter data and determining the maximum risk assessment value of the network node, and by calculating the network node safety quality assessment coefficient, the security of the network node when receiving data for each data receiving terminal can be guaranteed. At the same time, it also avoids data loss during transmission, thereby improving stability and data transmission efficiency.

[0095] In one embodiment, the data acquisition module acquires the power grid information parameters from the power grid, determines the standard data format of the power grid information parameters, and standardizes the power grid information parameters according to the standard data format to obtain standard power grid information parameters, including:

[0096] The power grid information parameters are divided into core data segments, and the distribution of associated data for each core data segment is determined based on the segmentation results.

[0097] The data structure corresponding to the power grid information parameters is obtained based on the associated data distribution of each core data.

[0098] Generate a protocol configuration file corresponding to the power grid information parameters based on the data structure;

[0099] According to the protocol configuration file, the power grid information parameters are decomposed into multiple types of power grid sub-information;

[0100] Determine the data structure object of each type of power grid sub-information based on the information data distribution in each type of power grid sub-information;

[0101] The data structure object of each type of power grid sub-information is serialized to obtain a byte sequence containing all the information content in the power grid sub-information of that type;

[0102] Input the byte sequence of all information content in each type of power grid sub-information into the standardized dictionary library to determine the matching standardized dictionary for that type of power grid sub-information;

[0103] Obtain the corresponding preset matching model from the standardized matching dictionary for each type of power grid sub-information;

[0104] Based on the standardized matching dictionary for each type of power grid sub-information and the corresponding pre-set matching model

[0105] Determine the standard data format for the power grid information parameters;

[0106] All power grid sub-information in the power grid information parameters is converted into the standard data format, and a standardized differential dataset for each power grid sub-information is obtained based on the conversion result.

[0107] Retrieve the current field of outlier data in the standardized differential dataset of each power grid sub-information;

[0108] Retrieve the standardization component corresponding to the current field from the preset database, and use the standardization component to convert the current field of the abnormal data in the standardized differential dataset of each power grid sub-information into a standard field;

[0109] Standard power grid information parameters are generated based on the transformed abnormal and normal data.

[0110] In this embodiment, the core data is represented as the target sub-parameter with the highest correlation weight among the power grid information parameters and other sub-parameters;

[0111] In this embodiment, the data structure is represented as a data arrangement structure of power grid information parameters, for example:

[0112] Tree-like structures or pyramid structures, etc.;

[0113] In this embodiment, the protocol configuration file refers to a storage protocol configuration file for power grid information parameters;

[0114] In this embodiment, the data distribution is represented by the clustering and distribution of each type of power grid sub-information;

[0115] In this embodiment, the data structure object represents the data structure description object for each type of power grid sub-information;

[0116] In this embodiment, the standardized dictionary library refers to a database that stores standardized dictionaries of various types of data;

[0117] In this embodiment, the preset matching model represents the generation model of standard format data corresponding to each standardized dictionary;

[0118] In this embodiment, the standardized differential dataset is represented as a dataset generated by standardizing the changed data of each type of power grid sub-information;

[0119] In this embodiment, the current field represents the field representing abnormal data;

[0120] In this embodiment, the standardization component refers to a program component that standardizes and repairs the representation fields of abnormal data.

[0121] The beneficial effects of the above technical solution are as follows: By performing standardized dictionary matching on each type of power grid sub-information, the various types of data in the power grid information parameters can be standardized in all aspects, improving data processing efficiency and accuracy. Furthermore, by calling the standardization component to repair the fields of abnormal data, data that failed in the standardization process can be repaired to ensure data integrity and improve practicality.

[0122] In one embodiment, the step of calculating the network node security quality assessment coefficient when transmitting power grid parameter data to the network node based on the maximum risk assessment value of the network node and the threat risk index and vulnerability risk index inputted into the network node assessment model includes:

[0123] The risk profile of a network node is determined based on its maximum risk assessment value.

[0124] Based on the aforementioned threat risk index, the proactive external risk posture of network nodes is determined.

[0125] The vulnerability risk index is used to determine the passive risk status of network nodes;

[0126] The comprehensive security posture index of a network node is calculated by using a preset security posture assessment function to evaluate the node's own risk posture, active external risk posture, and passive external risk posture.

[0127]

[0128] in, Let f() represent the comprehensive security posture index of network nodes, and let f() represent the preset security posture assessment function. This is represented as the first weight value, with a value of 0.5. This represents the risk profile of a network node. This is represented as the second weight value, with a value of 0.25. This represents the proactive external risk posture of network nodes. This is represented as the third weight value, with a value of 0.25. This represents the passive risk attitude of a network node, where e is the natural constant with a value of 2.72. This represents the network security assurance coefficient for the network and its nodes.

[0129] The security quality level of a network node is determined based on its comprehensive security posture index.

[0130] When the security quality level is medium or high, the network node is considered secure; when the security quality level is low, the network node is considered insecure.

[0131] The maximum risk assessment value of the network node, the threat risk index, and the vulnerability risk index are input into the network node assessment model to calculate the network node security quality assessment coefficient when transmitting power grid parameter data from the network node:

[0132]

[0133] Wherein, F represents the network node when transmitting power grid parameter data to the network node.

[0134] Safety and quality assessment coefficient This represents the maximum risk assessment value for a network node. This represents the network node risk reference threshold under standard conditions, entered into the network node assessment model. This is expressed as a threat risk index. This represents the reference threshold for the threat risk index under standard conditions, entered into the network node assessment model. This is represented as a vulnerability risk index. This represents the reference threshold for the vulnerability risk index under standard conditions, entered into the network node assessment model. This represents the utilization rate of the network nodes when transmitting power grid parameter data to the network nodes. This represents the latency of the network node when transmitting power grid parameter data to the network node.

[0135] The beneficial effects of the above technical solution are: by calculating the comprehensive security posture index of network nodes...

[0136] This allows for an intuitive assessment of the security level of network nodes, providing a reference for subsequent security quality assessment calculations and further enhancing practicality. Furthermore, by comprehensively calculating the network node security quality assessment coefficients when transmitting power grid parameter data to the network nodes based on their operating parameters, test results, and models, the calculation results can be made more reasonable and objective, further improving practicality and stability.

[0137] The above description is only a preferred embodiment of the present invention, but the scope of protection of the present invention is not limited thereto. Any equivalent substitutions or modifications made by those skilled in the art within the scope of the technology disclosed in the present invention, based on the technical solution and inventive concept of the present invention, should be covered within the scope of protection of the present invention.

Claims

1. A network node evaluation system based on power grid information parameter analysis, characterized in that: include: A power grid parameter processing unit is used to acquire power grid information parameters, construct a power grid parameter classification model based on the power grid information parameters, and simultaneously input the power grid information parameters into the power grid parameter classification model for classification to obtain multiple sub-power grid parameter data. The network node analysis unit is used to obtain each data receiving terminal from the data transmission link corresponding to the subgrid parameter data, and at the same time, obtain the interaction record of the network layer of each data receiving terminal when receiving data, and extract the network node. A network node evaluation unit is used to construct a network node evaluation model, input the network node into the network node evaluation model for calculation, determine the maximum risk assessment value of the data transmission link of the power grid information parameters, and perform qualification screening of the network node based on the maximum risk assessment value. The network node evaluation unit includes: The evaluation model construction module is used to construct network node data calculation formulas based on network node data, construct power grid parameter data calculation formulas based on the power grid parameter data, and merge the network node data calculation formulas and the power grid parameter data calculation formulas to construct a network node evaluation model. The node evaluation module is used to input the network node into the network node evaluation model for calculation, obtain the network node security quality evaluation coefficient, and determine whether the network node is qualified based on the network node security quality evaluation coefficient. The method for obtaining the network node security quality assessment coefficient is as follows: The network node data and power grid parameter data are respectively analyzed to determine the load of the network node data in the power grid parameter data, and the maximum risk assessment value of the network node is determined according to the safety quality assessment coefficient of the network node. Obtain historical successful transmission data for each data receiving terminal, parse the historical successful transmission data to determine its integrity and security, and assess the threat risk index and vulnerability risk index of the data receiving terminal based on the integrity and security. Based on the maximum risk assessment value of the network node and the threat risk index and vulnerability risk index, the network node assessment model is used to calculate the network node security quality assessment coefficient when transmitting power grid parameter data to the network node.

2. The network node evaluation system based on power grid information parameter analysis as described in claim 1, characterized in that: The power grid parameter processing unit includes: The data acquisition module is used to acquire the power grid information parameters from the power grid, determine the standard data format of the power grid information parameters, and standardize the power grid information parameters according to the standard data format to obtain standard power grid information parameters. The data classification module is used for: The standard power grid information parameters are input into the power grid parameter classification model for classification, and the parameter data labels corresponding to the data are obtained based on the power grid parameter classification model. Based on the parameter data labels, the standard power grid information parameters are clustered to obtain multiple sub-power grid parameter data.

3. The network node evaluation system based on power grid information parameter analysis as described in claim 2, characterized in that: After obtaining parameter data for multiple sub-grids, the following is also included: The power grid parameter data is integrated and mapped into a fixed-dimensional vector space based on the labels for classification and storage. The classification features corresponding to the power grid parameter data are determined, the data format of the power grid parameter data is obtained based on the classification features, and the data format of the power grid parameter data is converted based on the data format to generate a target data transmission file.

4. The network node evaluation system based on power grid information parameter analysis as described in claim 3, characterized in that: The network node analysis unit includes: The information synchronization module is used to determine the data transmission link between the target data transmission file and the data receiving terminal, receive the target data transmission file based on the data receiving terminal, read multiple sub-grid parameter data in the target data transmission file, and determine whether the multiple sub-grid parameter data are complete. The network node extraction module is used to determine the data acquisition rules of the data receiving terminal, generate a data transmission network protocol between the two based on the data acquisition rules and the classification characteristics of the target data transmission file, and obtain the network node of each target data transmission file in the data transmission link based on the data transmission network protocol.

5. The network node evaluation system based on power grid information parameter analysis as described in claim 4, characterized in that: The network node extraction module is also used for: The standard network flow of a network node is found in the network flow table, and the initial data characteristics of the network node are determined based on the standard network flow. The data receiving terminal retrieves a data resource sample, runs the data transmission network protocol based on the data resource sample, and obtains the running results. Based on the running results, obtain the network nodes between the data receiving terminal and the target data transmission file, generate an interaction record, and obtain the data transmission characteristic parameters of the data transmission network protocol based on the interaction record; Based on the data transmission characteristic parameters, a grid chain is generated between each data receiving terminal and the target data transmission file.

6. The network node evaluation system based on power grid information parameter analysis as described in claim 5, characterized in that: The node evaluation module is also used for: The security assessment score of the network node is determined based on the network node security quality assessment coefficient, and the security assessment score is compared with a preset security assessment threshold to determine whether the network node is within the safe operating range. When the security assessment score is equal to or greater than the preset security assessment threshold, the network node is determined to be at risk. At the same time, when the network node is at risk, an early warning report is generated and the data transmission link corresponding to the network node is obtained. The data receiving terminal is determined based on the data transmission link corresponding to the network node, and the early warning report is transmitted to the data receiving terminal via the Internet of Things. Otherwise, the network node is determined to be secure.

7. The network node evaluation system based on power grid information parameter analysis as described in claim 2, characterized in that: The data acquisition module obtains the power grid information parameters from the power grid, determines the standard data format of the power grid information parameters, and standardizes the power grid information parameters according to the standard data format to obtain standard power grid information parameters, including: The power grid information parameters are divided into core data segments, and the distribution of associated data for each core data segment is determined based on the segmentation results. The data structure corresponding to the power grid information parameters is obtained based on the associated data distribution of each core data. Generate a protocol configuration file corresponding to the power grid information parameters based on the data structure; According to the protocol configuration file, the power grid information parameters are decomposed into multiple types of power grid sub-information; Determine the data structure object of each type of power grid sub-information based on the information data distribution in each type of power grid sub-information; The data structure object of each type of power grid sub-information is serialized to obtain a byte sequence containing all the information content in the power grid sub-information of that type; Input the byte sequence of all information content in each type of power grid sub-information into the standardized dictionary library to determine the matching standardized dictionary for that type of power grid sub-information; Obtain the corresponding preset matching model from the standardized matching dictionary for each type of power grid sub-information; Based on the standardized matching dictionary for each type of power grid sub-information and the corresponding pre-set matching model Determine the standard data format for the power grid information parameters; All power grid sub-information in the power grid information parameters is converted into the standard data format, and a standardized differential dataset for each power grid sub-information is obtained based on the conversion result. Retrieve the current field of outlier data in the standardized differential dataset of each power grid sub-information; Retrieve the standardization component corresponding to the current field from the preset database, and use the standardization component to convert the current field of the abnormal data in the standardized differential dataset of each power grid sub-information into a standard field; Standard power grid information parameters are generated based on the transformed abnormal and normal data.

8. The network node evaluation system based on power grid information parameter analysis as described in claim 1, characterized in that: The calculation of the network node security quality assessment coefficient when transmitting power grid parameter data to the network node is based on the maximum risk assessment value of the network node, the threat risk index, and the vulnerability risk index, inputted into the network node assessment model. This includes: The risk profile of a network node is determined based on its maximum risk assessment value. Based on the aforementioned threat risk index, the proactive external risk posture of network nodes is determined. The vulnerability risk index is used to determine the passive risk status of network nodes; The comprehensive security posture index of a network node is calculated by using a preset security posture assessment function to evaluate the node's own risk posture, active external risk posture, and passive external risk posture. in, Let f() represent the comprehensive security posture index of network nodes, and let f() represent the preset security posture assessment function. This is represented as the first weight value, with a value of 0.

5. This represents the risk profile of a network node. This is represented as the second weight value, with a value of 0.

25. This represents the proactive external risk posture of network nodes. This is represented as the third weight value, with a value of 0.

25. This represents the passive risk attitude of a network node, where e is the natural constant with a value of 2.

72. This represents the network security assurance coefficient for the network and its nodes. The security quality level of a network node is determined based on its comprehensive security posture index. When the security quality level is medium or high, the network node is considered secure; when the security quality level is low, the network node is considered insecure. The maximum risk assessment value of the network node, the threat risk index, and the vulnerability risk index are input into the network node assessment model to calculate the network node security quality assessment coefficient when transmitting power grid parameter data from the network node: Wherein, F represents the network node safety quality assessment coefficient when transmitting power grid parameter data to the network node. This represents the maximum risk assessment value for a network node. This represents the network node risk reference threshold under standard conditions, entered into the network node assessment model. This is expressed as a threat risk index. This represents the reference threshold for the threat risk index under standard conditions, entered into the network node assessment model. This is represented as a vulnerability risk index. This represents the reference threshold for the vulnerability risk index under standard conditions, entered into the network node assessment model. This represents the utilization rate of the network nodes when transmitting power grid parameter data to the network nodes. This represents the latency of the network node when transmitting power grid parameter data to the network node.

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