CN116346637A - Network node evaluation system based on power grid information parameter analysis - Google Patents
Network node evaluation system based on power grid information parameter analysis Download PDFInfo
- Publication number
- CN116346637A CN116346637A CN202310178043.8A CN202310178043A CN116346637A CN 116346637 A CN116346637 A CN 116346637A CN 202310178043 A CN202310178043 A CN 202310178043A CN 116346637 A CN116346637 A CN 116346637A
- Authority
- CN
- China
- Prior art keywords
- network node
- data
- power grid
- parameter
- information
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Pending
Links
- 238000011156 evaluation Methods 0.000 title claims abstract description 59
- 238000004458 analytical method Methods 0.000 title claims abstract description 33
- 238000004364 calculation method Methods 0.000 claims abstract description 25
- 238000012545 processing Methods 0.000 claims abstract description 18
- 238000013145 classification model Methods 0.000 claims abstract description 15
- 230000005540 biological transmission Effects 0.000 claims description 108
- 238000013210 evaluation model Methods 0.000 claims description 28
- 238000013441 quality evaluation Methods 0.000 claims description 18
- 238000012502 risk assessment Methods 0.000 claims description 15
- 230000002159 abnormal effect Effects 0.000 claims description 13
- 238000001303 quality assessment method Methods 0.000 claims description 12
- 230000003993 interaction Effects 0.000 claims description 11
- 238000000605 extraction Methods 0.000 claims description 6
- 238000000034 method Methods 0.000 claims description 6
- 238000006243 chemical reaction Methods 0.000 claims description 5
- 238000012216 screening Methods 0.000 claims description 5
- 238000010276 construction Methods 0.000 claims description 4
- 238000013507 mapping Methods 0.000 claims description 3
- 238000012797 qualification Methods 0.000 claims description 3
- 230000007246 mechanism Effects 0.000 description 4
- 230000009286 beneficial effect Effects 0.000 description 3
- 238000011157 data evaluation Methods 0.000 description 2
- 230000000246 remedial effect Effects 0.000 description 2
- 241000700605 Viruses Species 0.000 description 1
- 230000003044 adaptive effect Effects 0.000 description 1
- 230000008859 change Effects 0.000 description 1
- 238000004891 communication Methods 0.000 description 1
- 238000013329 compounding Methods 0.000 description 1
- 238000009833 condensation Methods 0.000 description 1
- 230000005494 condensation Effects 0.000 description 1
- 230000008878 coupling Effects 0.000 description 1
- 238000010168 coupling process Methods 0.000 description 1
- 238000005859 coupling reaction Methods 0.000 description 1
- 238000010586 diagram Methods 0.000 description 1
- 230000000694 effects Effects 0.000 description 1
- 238000005516 engineering process Methods 0.000 description 1
- 239000000284 extract Substances 0.000 description 1
- 238000012986 modification Methods 0.000 description 1
- 230000004048 modification Effects 0.000 description 1
- 230000008569 process Effects 0.000 description 1
- 230000008439 repair process Effects 0.000 description 1
- 238000012360 testing method Methods 0.000 description 1
- 230000009385 viral infection Effects 0.000 description 1
Images
Classifications
-
- H—ELECTRICITY
- H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
- H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
- H02J3/00—Circuit arrangements for ac mains or ac distribution networks
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L41/00—Arrangements for maintenance, administration or management of data switching networks, e.g. of packet switching networks
- H04L41/06—Management of faults, events, alarms or notifications
- H04L41/0631—Management of faults, events, alarms or notifications using root cause analysis; using analysis of correlation between notifications, alarms or events based on decision criteria, e.g. hierarchy, tree or time analysis
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L41/00—Arrangements for maintenance, administration or management of data switching networks, e.g. of packet switching networks
- H04L41/14—Network analysis or design
- H04L41/142—Network analysis or design using statistical or mathematical methods
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L63/00—Network architectures or network communication protocols for network security
- H04L63/14—Network architectures or network communication protocols for network security for detecting or protecting against malicious traffic
- H04L63/1433—Vulnerability analysis
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L63/00—Network architectures or network communication protocols for network security
- H04L63/14—Network architectures or network communication protocols for network security for detecting or protecting against malicious traffic
- H04L63/1441—Countermeasures against malicious traffic
- H04L63/145—Countermeasures against malicious traffic the attack involving the propagation of malware through the network, e.g. viruses, trojans or worms
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L63/00—Network architectures or network communication protocols for network security
- H04L63/20—Network architectures or network communication protocols for network security for managing network security; network security policies in general
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L67/00—Network arrangements or protocols for supporting network services or applications
- H04L67/01—Protocols
- H04L67/12—Protocols specially adapted for proprietary or special-purpose networking environments, e.g. medical networks, sensor networks, networks in vehicles or remote metering networks
-
- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y04—INFORMATION OR COMMUNICATION TECHNOLOGIES HAVING AN IMPACT ON OTHER TECHNOLOGY AREAS
- Y04S—SYSTEMS INTEGRATING TECHNOLOGIES RELATED TO POWER NETWORK OPERATION, COMMUNICATION OR INFORMATION TECHNOLOGIES FOR IMPROVING THE ELECTRICAL POWER GENERATION, TRANSMISSION, DISTRIBUTION, MANAGEMENT OR USAGE, i.e. SMART GRIDS
- Y04S10/00—Systems supporting electrical power generation, transmission or distribution
- Y04S10/50—Systems or methods supporting the power network operation or management, involving a certain degree of interaction with the load-side end user applications
Landscapes
- Engineering & Computer Science (AREA)
- Computer Security & Cryptography (AREA)
- Computer Networks & Wireless Communication (AREA)
- Signal Processing (AREA)
- Computing Systems (AREA)
- General Engineering & Computer Science (AREA)
- Computer Hardware Design (AREA)
- General Health & Medical Sciences (AREA)
- Health & Medical Sciences (AREA)
- Algebra (AREA)
- Mathematical Analysis (AREA)
- General Physics & Mathematics (AREA)
- Mathematical Optimization (AREA)
- Pure & Applied Mathematics (AREA)
- Physics & Mathematics (AREA)
- Power Engineering (AREA)
- Probability & Statistics with Applications (AREA)
- Mathematical Physics (AREA)
- Virology (AREA)
- Medical Informatics (AREA)
- Management, Administration, Business Operations System, And Electronic Commerce (AREA)
Abstract
The invention 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 problems that in the prior art, corresponding information is increased when one node is added, each node is calculated respectively, the calculated amount is large, the system load is increased easily, and the overall operation of the system is affected; a network node evaluation system based on grid information parameter analysis, comprising: the system 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 the power grid parameter classification model to classify the power grid parameter data, the accurate and rapid classification and labeled storage of a large amount of data are completed through efficient vector calculation, the data positions are rapidly positioned by means of labels, the system retrieval time is shortened, 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
The invention relates to the technical field of network evaluation systems, in particular to a network node evaluation system based on power grid information parameter analysis.
Background
The network nodes in the power grid are basic units in the power information network, and risks can be effectively reduced only if the safety of the network nodes is ensured. Network node evaluation of grid information, related patents exist; for example, publication No.: the Chinese patent of CN113379248A discloses a power grid risk assessment and early warning method based on a complex network theory, which comprises the steps of establishing an abstract complex network taking a power grid as an object, respectively calculating node degree indexes, medium number indexes, efficiency loss coefficient indexes and network condensation degree change rate indexes of each node in step 2, compounding each index into a power grid risk index in step 3, and outputting risk assessment results of each node in step 4. The invention can realize power grid network risk assessment and early warning.
Although the patent can realize the risk assessment and early warning of the power grid network, the following problems still exist in the actual use process:
1. in the prior art, corresponding information is increased when one node is added, each node is calculated respectively, and the conditions of large calculated amount and increased system load are easily caused, so that the overall operation of the system is influenced;
2. in the prior art, for a complex network environment, risk factors existing in the real environment cannot be accurately reflected in practical application, and a unified evaluation model cannot be established for data evaluation, so that the accuracy of an evaluation result is low.
Disclosure of Invention
The invention aims to provide a network node evaluation system based on power grid information parameter analysis, which is used for classifying the power grid information parameters to obtain a plurality of sub-power grid parameter data and evaluating network nodes based on a network node evaluation model, so that network node security risk evaluation is realized, and the problems in the background technology are solved.
In order to achieve the above purpose, the present invention provides the following technical solutions:
a network node evaluation system based on grid information parameter analysis, comprising:
the power grid parameter processing unit is used for acquiring power grid information parameters, constructing a power grid parameter classification model based on the power grid information parameters, and simultaneously inputting the power grid information parameters into the power grid parameter classification model for classification to acquire a plurality of sub-power grid parameter data;
the network node analysis unit is used for acquiring each data receiving terminal from the data transmission link corresponding to the sub-grid parameter data, acquiring the interaction record of the network layer of each data receiving terminal when receiving the data, and extracting the network node;
the network node evaluation unit is used for constructing a network node evaluation model, inputting the network node into the network node evaluation model for calculation, determining a maximum risk evaluation value of a data transmission link of the power grid information parameter, and screening the network node for qualification according to the maximum risk evaluation value.
Further, the power grid parameter processing unit includes:
the data acquisition module is used for acquiring the power grid information parameters from the power grid, determining a standard data format of the power grid information parameters, and carrying out data standardization on 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:
inputting the standard power grid information parameters into a power grid parameter classification model for classification, and acquiring parameter data labels corresponding to the data based on the power grid parameter classification model;
and clustering the standard power grid information parameters based on the parameter data labels to obtain a plurality of sub-power grid parameter data.
Further, after the power grid parameter data are obtained, the method further includes:
integrating and mapping the power grid parameter data into a vector space with a fixed dimension according to a label for classified storage;
determining classification characteristics corresponding to the power grid parameter data, acquiring a data format of the power grid parameter data based on the classification characteristics, and converting the data format of the power grid parameter data based on the data format to generate a target data transmission file.
Further, the network node analysis unit includes:
the information synchronization module is used for determining a data transmission link between the target data transmission file and the data receiving terminal, receiving the target data transmission file based on the data receiving terminal, reading a plurality of sub-grid parameter data in the target data transmission file, and determining whether the plurality of sub-grid parameter data are complete;
the network node extraction module is used for determining a data acquisition rule of the data receiving terminal, generating a data transmission network protocol between the data acquisition rule and the classification characteristic of the target data transmission file according to the data acquisition rule and the classification characteristic of the target data transmission file, and acquiring a network node of each target data transmission file in a data transmission link based on the data transmission network protocol.
Further, the network node extraction module is further configured to:
searching a standard network flow of a network node in a network flow table, and determining initial data characteristics of the network node according to the standard network flow;
the data receiving terminal invokes a data resource sample, runs the data transmission network protocol based on the data resource sample, and obtains a running result;
Acquiring a network node between a data receiving terminal and a target data transmission file according to the operation result, generating an interaction record, and acquiring data transmission characteristic parameters of a data transmission network protocol according to the interaction record;
and generating a grid chain between each data receiving terminal and the target data transmission file based on the data transmission characteristic parameters.
Further, the network node evaluation unit includes:
the evaluation model construction module is used for constructing a network node data calculation formula based on the network node data, constructing a power grid parameter data calculation formula based on the power grid parameter data, combining the network node data calculation formula and the power grid parameter data calculation formula, and constructing a network node evaluation model;
the node evaluation module is used for inputting the network node into the network node evaluation model for calculation, obtaining a network node safety quality evaluation coefficient, and judging whether the network node is qualified or not based on the network node safety quality evaluation coefficient.
Further, the obtaining the network node security quality assessment coefficient specifically includes:
respectively deducting the network node data and the power grid parameter data, determining the load of the network node data in the power grid parameter data, and determining the maximum risk assessment value of the network node according to the network node safety quality assessment coefficient;
Acquiring historical transmission success data of each data receiving terminal, analyzing the historical transmission success data to determine the integrity and the safety of the data receiving terminal, and evaluating threat risk indexes and vulnerability risk indexes of the data receiving terminal according to the integrity and the safety;
and inputting the maximum risk evaluation value, the threat risk index and the vulnerability risk index of the network node into a network node evaluation model to calculate a network node safety quality evaluation coefficient when carrying out power grid parameter data transmission on the network node data.
Further, the node evaluation module is further configured to:
determining a security assessment value of the network node based on the network node security quality assessment coefficient, comparing the security assessment value with a preset security assessment threshold value, and judging whether the network node is in a security operation range;
when the security assessment score is equal to or greater than the score threshold, judging that the network node has risk, and meanwhile, when the network node has risk, generating an early warning report and acquiring a data transmission link corresponding to the network node;
determining a data receiving terminal based on a data transmission link corresponding to the network node, and simultaneously transmitting the early warning report to the data receiving terminal based on the Internet of things;
Otherwise, judging the security of the network node.
Further, the data acquisition module acquires the power grid information parameters from the power grid, determines a standard data format of the power grid information parameters, performs data standardization on the power grid information parameters according to the standard data format to obtain standard power grid information parameters, and comprises the following steps:
dividing the core data of the power grid information parameters, and determining the associated data distribution of each core data according to the division result;
acquiring a data structure corresponding to the power grid information parameter based on the associated data distribution of each core data;
generating a protocol configuration file corresponding to the power grid information parameters according to the data structure;
decomposing the power grid information parameters into a plurality of types of power grid sub-information according to the protocol configuration file;
determining a data structure object of each type of power grid sub-information according to information data distribution conditions in the power grid sub-information;
carrying out serialization processing on the data structure object of each type of power grid sub-information to obtain a byte sequence containing all information contents in the type of power grid sub-information;
inputting byte sequences of all information contents in each type of power grid sub-information into a standardized dictionary library to determine a matched standardized dictionary of the type of power grid sub-information;
Acquiring a preset matching model corresponding to a matching standardized dictionary of each type of power grid sub-information;
determining a standard data format of the power grid information parameters based on a preset matching model corresponding to a matching standardized dictionary of each type of power grid sub-information;
converting all the power grid sub-information in the power grid information parameters into the standard data format, and acquiring a standardized differential data set of each power grid sub-information according to a conversion result;
acquiring the current field of abnormal data in the standardized differential data set of each power grid sub-information;
a standardized component corresponding to the current field is called from a preset database, and the current field of abnormal data in the standardized differential data set of each power grid sub-information is converted into a standard field by utilizing the standardized component;
and generating standard power grid information parameters according to the converted abnormal data and the converted normal data.
Further, the calculating the network node security quality evaluation coefficient when the network node data is transmitted with the network parameter data based on the network node maximum risk evaluation value, the threat risk index and the vulnerability risk index is input to a network node evaluation model includes:
Determining the self risk attitude of the network node according to the maximum risk evaluation value of the network node;
determining an active external risk attitude of the network node based on the threat risk index, and determining a passive risk attitude of the network node based on the vulnerability risk index;
calculating the comprehensive security situation index of the network node by using a preset security situation assessment function on the self risk situation degree, the active external risk situation degree and the passive external risk situation degree of the network node:
wherein Q is expressed as an integrated security situation index of the network node, f () is expressed as a preset security situation assessment function, A 1 Denoted as firstThe weight value is 0.5, B is expressed as the self risk attitude of the network node, A 2 Expressed as a second weight value, the value is 0.25, C is expressed as the active external risk attitude of the network node, A 3 The value is expressed as a third weight value, the value is 0.25, D is expressed as the passive risk attitude of the network node, e is expressed as a natural constant, the value is 2.72, and alpha is expressed as the network security assurance coefficient of the network and the node;
judging the belonging grade of the security quality of the network node according to the comprehensive security situation index of the network node, judging the security of the network node when the belonging grade of the security quality is medium grade or high grade, and judging the unsafe of the network node when the belonging grade of the security quality is low grade;
Inputting the network node maximum risk assessment value, the threat risk index and the vulnerability risk index into a network node assessment model to calculate a network node safety quality assessment coefficient when carrying out power grid parameter data transmission on the network node data:
wherein F is represented as a network node safety quality evaluation coefficient when the network node data are subjected to power grid parameter data transmission, and G is represented as a network node safety quality evaluation coefficient when the network node data are subjected to power grid parameter data transmission 1 Expressed as a network node maximum risk assessment value, G 2 Represented as network node risk reference threshold, K, under standard conditions entered in the network node assessment model 1 Expressed as threat risk index, K 2 Expressed as threat risk index reference threshold, L under standard state entered in the network node assessment model 1 Expressed as vulnerability risk index, L 2 The vulnerability risk index reference threshold value under the standard state recorded in the network node evaluation model is represented, beta is represented as the utilization rate of the network node when the network node data is subjected to power grid parameter data transmission, and delta is represented as the time delay rate of the network node when the network node data is subjected to power grid parameter data transmission.
Compared with the prior art, the invention has the beneficial effects that:
1. The standard power grid information parameters are input into the power grid parameter classification model to classify the power grid parameter data, the accurate and rapid classification and labeled storage of a large amount of data are completed through efficient vector calculation, the data positions are rapidly positioned by means of labels, the system retrieval time is shortened, 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.
2. By classifying the power grid parameter data and carrying out format conversion and transmission on the data according to the classification result, the network nodes in different transmission links are accurately and effectively evaluated, the accuracy of analysis on the network nodes is improved, a data transmission network protocol is determined to be used as a data transmission carrier, the operation data of a data resource sample is obtained and an interaction record is generated, a grid chain between each data receiving terminal and a target data transmission file is generated, the stability and the high efficiency of the data transmission process are ensured, and the adaptability and the expansibility of a mechanism are improved.
3. The risk terminal and the safety terminal can be effectively distinguished by calculating the safety index of each data receiving terminal, so that the situation that the data receiving terminal brings own loopholes or safety threats into the power grid along with data to cause data loss or power grid virus infection is avoided, safety and stability are improved, when the risk exists on a network node, an early warning report is generated, the early warning report is transmitted to the data receiving terminal based on the Internet of things, workers can conveniently and accurately know and position the data receiving terminal with the risk in time, corresponding remedial measures are timely made, practicability is improved, and economic losses and other related hazards brought to the power grid due to network safety problems are reduced.
Drawings
FIG. 1 is a block diagram of a network node evaluation system based on power grid information parameter analysis according to the present invention;
fig. 2 is a flowchart of a network node evaluation system based on power grid information parameter analysis according to the present invention.
Detailed Description
The following description of the embodiments of the present invention will be made clearly and completely with reference to the accompanying drawings, in which it is apparent that the embodiments described are only some embodiments of the present invention, but not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
In order to solve the technical problem that as the load capacity of the power grid is increased, the coverage area is enlarged, the coupling degree with the communication system and the comprehensive energy system is increased, the refined modeling occupies a large computing resource, and influences the risk assessment and the early warning effect, referring to fig. 1-2, the embodiment provides the following technical scheme:
a network node evaluation system based on grid information parameter analysis, comprising: the power grid parameter processing unit is used for acquiring power grid information parameters, constructing a power grid parameter classification model based on the power grid information parameters, and simultaneously inputting the power grid information parameters into the power grid parameter classification model for classification to acquire a plurality of sub-power grid parameter data; the network node analysis unit is used for acquiring each data receiving terminal from the data transmission link corresponding to the sub-grid parameter data, acquiring the interaction record of the network layer of each data receiving terminal when receiving the data, and extracting the network node; the network node evaluation unit is used for constructing a network node evaluation model, inputting the network node into the network node evaluation model for calculation, determining a maximum risk evaluation value of a data transmission link of the power grid information parameter, and screening the network node for qualification according to the maximum risk evaluation value.
Specifically, the grid information parameters are classified to obtain a plurality of sub-grid parameter data, each data receiving terminal is obtained from a data transmission link corresponding to the sub-grid parameter data, network nodes are extracted from the data transmission link, the network nodes are evaluated based on a network node evaluation model, qualified screening is carried out on the network nodes according to a calculation result, and the security risk of the nodes and the risk of the data receiving terminals are evaluated, so that the network node security risk evaluation is realized.
In order to solve the technical problem that in the prior art, corresponding information is increased when a node is added, each node is calculated respectively, so that the situations of large calculation amount and increased system load are easy to cause, and the overall operation of the system is affected, referring to fig. 1-2, the embodiment provides the following technical scheme:
the power grid parameter processing unit comprises a data acquisition module, a data processing module and a data processing module, wherein the data acquisition module is used for acquiring the power grid information parameters from a power grid, determining a standard data format of the power grid information parameters, and carrying out data standardization on 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 inputting the standard power grid information parameters into a power grid parameter classification model for classification, and acquiring a parameter data tag corresponding to the data based on the power grid parameter classification model; clustering the standard power grid information parameters based on the parameter data labels to obtain a plurality of sub-power grid parameter data;
After obtaining the power grid parameter data, the method further comprises the following steps: integrating and mapping the power grid parameter data into a vector space with a fixed dimension according to a label for classified storage; determining classification characteristics corresponding to the power grid parameter data, acquiring a data format of the power grid parameter data based on the classification characteristics, and converting the data format of the power grid parameter data based on the data format to generate a target data transmission file.
Specifically, the standard power grid information parameters are input into the power grid parameter classification model to classify the power grid parameter data, the power grid parameters are subjected to label classification storage, mapped into a vector space with a fixed dimension, accurate and rapid classification and labeled storage of a large amount of data are completed through efficient vector calculation, the data positions are rapidly positioned by means of labels, the system retrieval time is reduced, the system processing burden is lightened for subsequent network node analysis, the system operation efficiency is improved, and the reliable operation of the system is further ensured.
In order to solve the technical problem that in the prior art, the analysis of the network node has certain drawbacks, and the data receiving rule of the data receiving terminal cannot be determined, so that the network node extracts omission, please refer to fig. 1-2, the present embodiment provides the following technical scheme:
The network node analysis unit comprises an information synchronization module and a data processing module, wherein the information synchronization module is used for determining a data transmission link of the target data transmission file and a data receiving terminal, receiving the target data transmission file based on the data receiving terminal, reading a plurality of sub-grid parameter data in the target data transmission file, and determining whether the plurality of sub-grid parameter data are complete;
the network node extraction module is used for determining a data acquisition rule of the data receiving terminal, generating a data transmission network protocol between the data acquisition rule and the classification characteristic of the target data transmission file according to the data acquisition rule and the classification characteristic of the target data transmission file, and acquiring a network node of each target data transmission file in a data transmission link based on the data transmission network protocol;
the network node extraction module is also used for searching a standard network flow of the network node in the network flow table and determining initial data characteristics of the network node according to the standard network flow; the data receiving terminal invokes a data resource sample, runs the data transmission network protocol based on the data resource sample, and obtains a running result; acquiring a network node between a data receiving terminal and a target data transmission file according to the operation result, generating an interaction record, and acquiring data transmission characteristic parameters of a data transmission network protocol according to the interaction record; and generating a grid chain between each data receiving terminal and the target data transmission file based on the data transmission characteristic parameters.
Specifically, by classifying the power grid parameter data and simultaneously carrying out format conversion and transmission on the data according to classification results, accurate and effective assessment on network nodes in different transmission links is realized, accuracy of analysis on the network nodes is improved, a data transmission network protocol is determined to be used as a data transmission carrier, operation data of a data resource sample is obtained, interaction records are generated, grid chains between each data receiving terminal and a target data transmission file are generated, stability and high efficiency of a data transmission process are guaranteed, the built grid chains provide a data sharing mechanism, stable operation of the data receiving terminal and the target data transmission file in the same network space can be guaranteed, meanwhile, the subsequently generated data sharing mechanism is more adaptive to the data receiving terminal and the target data transmission file, and adaptability and expansibility of the mechanism are improved.
In order to solve the technical problem that in the prior art, for a complex network environment, risk factors existing in the real environment cannot be accurately reflected in practical application, a unified evaluation model cannot be established to perform data evaluation, so that the accuracy of an evaluation result is low, please refer to fig. 1-2, the embodiment provides the following technical scheme:
The network node evaluation unit comprises an evaluation model construction module, a network node evaluation module and a network node evaluation module, wherein the evaluation model construction module is used for constructing a network node data calculation formula based on the network node data, constructing a power grid parameter data calculation formula based on the power grid parameter data, combining the network node data calculation formula and the power grid parameter data calculation formula, and constructing a network node evaluation model; the node evaluation module is used for inputting the network node into the network node evaluation model for calculation, obtaining a network node safety quality evaluation coefficient, and judging whether the network node is qualified or not based on the network node safety quality evaluation coefficient;
the node evaluation module is further used for determining a security evaluation value of the network node based on the network node security quality evaluation coefficient, comparing the security evaluation value with a preset security evaluation threshold value and judging whether the network node is in a security operation range; when the security assessment score is equal to or greater than the score threshold, judging that the network node has risk, and meanwhile, when the network node has risk, generating an early warning report and acquiring a data transmission link corresponding to the network node; determining a data receiving terminal based on a data transmission link corresponding to the network node, and simultaneously transmitting the early warning report to the data receiving terminal based on the Internet of things; otherwise, judging the security of the network node.
Specifically, the risk terminal and the safety terminal can be effectively distinguished by calculating the safety index of each data receiving terminal, so that the situation that the data receiving terminal brings own loopholes or safety threats into the power grid along with data to cause data loss or the power grid infects viruses is avoided, safety and stability are improved, when the risk exists on a network node, an early warning report is generated, the early warning report is transmitted to the data receiving terminal based on the Internet of things, workers can conveniently and accurately know and position the data receiving terminal with the risk in time, corresponding remedial measures are timely made, practicability is improved, processing results are more reasonable and accurate, and economic losses and other related hazards caused to the power grid due to the network safety problem are reduced.
In order to solve the technical problem that in the prior art, qualified screening of network nodes cannot be performed according to data transmission efficiency and transmission channels of power grid parameters, so that risks are greatly increased during power grid parameter transmission, please refer to fig. 1-2, the present embodiment provides the following technical scheme:
the network node security quality evaluation coefficient is obtained, specifically: respectively deducting the network node data and the power grid parameter data, determining the load of the network node data in the power grid parameter data, and determining the maximum risk assessment value of the network node according to the network node safety quality assessment coefficient; acquiring historical transmission success data of each data receiving terminal, analyzing the historical transmission success data to determine the integrity and the safety of the data receiving terminal, and evaluating threat risk indexes and vulnerability risk indexes of the data receiving terminal according to the integrity and the safety; and inputting the maximum risk evaluation value, the threat risk index and the vulnerability risk index of the network node into a network node evaluation model to calculate a network node safety quality evaluation coefficient when carrying out power grid parameter data transmission on the network node data.
Specifically, by calculating network node data and power grid parameter data and determining a maximum risk evaluation value of the network node, the safety of the network node when each data receiving terminal receives the data can be ensured by calculating the network node safety quality evaluation coefficient, meanwhile, the loss condition of the data in the transmission process is avoided, and the stability and the data transmission efficiency are improved.
In one embodiment, the data obtaining module obtains the power grid information parameter from the power grid, determines a standard data format of the power grid information parameter, and performs data standardization on the power grid information parameter according to the standard data format to obtain a standard power grid information parameter, including:
dividing the core data of the power grid information parameters, and determining the associated data distribution of each core data according to the division result;
acquiring a data structure corresponding to the power grid information parameter based on the associated data distribution of each core data;
generating a protocol configuration file corresponding to the power grid information parameters according to the data structure;
decomposing the power grid information parameters into a plurality of types of power grid sub-information according to the protocol configuration file;
determining a data structure object of each type of power grid sub-information according to information data distribution conditions in the power grid sub-information;
Carrying out serialization processing on the data structure object of each type of power grid sub-information to obtain a byte sequence containing all information contents in the type of power grid sub-information;
inputting byte sequences of all information contents in each type of power grid sub-information into a standardized dictionary library to determine a matched standardized dictionary of the type of power grid sub-information;
acquiring a preset matching model corresponding to a matching standardized dictionary of each type of power grid sub-information;
determining a standard data format of the power grid information parameters based on a preset matching model corresponding to a matching standardized dictionary of each type of power grid sub-information;
converting all the power grid sub-information in the power grid information parameters into the standard data format, and acquiring a standardized differential data set of each power grid sub-information according to a conversion result;
acquiring the current field of abnormal data in the standardized differential data set of each power grid sub-information;
a standardized component corresponding to the current field is called from a preset database, and the current field of abnormal data in the standardized differential data set of each power grid sub-information is converted into a standard field by utilizing the standardized component;
and generating standard power grid information parameters according to the converted abnormal data and the converted normal data.
In this embodiment, the core data is represented as a target sub-parameter with the largest associated weight with other sub-parameters in the grid information parameters;
in this embodiment, the data structure is represented as a data arrangement structure of grid information parameters, for example: tree-like structures or pyramid structures, etc.;
in this embodiment, the protocol configuration file is represented as a stored protocol configuration file of the grid information parameter;
in this embodiment, the data distribution condition is represented as a clustering condition and a distribution condition of each type of grid sub-information;
in the present embodiment, the data structure object represents a data structure description object of each type of grid sub-information;
in the present embodiment, the normalized dictionary library is represented as a database storing normalized dictionaries of respective types of data;
in this embodiment, the preset matching model is represented as a generation model of standard format data corresponding to each standardized dictionary;
in this embodiment, the standardized differential data set is represented as a data set generated by changed data obtained by normalizing each type of grid sub-information;
in the present embodiment, the current field is represented as a representation field of the abnormal data;
in the present embodiment, the standardized component is represented as a program component that performs standardized repair of the representation field of the abnormal data.
The beneficial effects of the technical scheme are as follows: the standardized dictionary matching can be carried out on various types of data in the power grid information parameters in an omnibearing manner by carrying out standardized dictionary matching on each type of power grid information, so that the data processing efficiency and accuracy are improved, and furthermore, the abnormal data can be subjected to data restoration by calling the standardized component to carry out field restoration on the abnormal data, so that the integrity of the data is ensured, and the practicability is improved.
In one embodiment, the calculating the network node security quality assessment coefficient when the network node data is transmitted with the network parameter data based on the network node maximum risk assessment value and the threat risk index and the vulnerability risk index input to a network node assessment model includes:
determining the self risk attitude of the network node according to the maximum risk evaluation value of the network node;
determining an active external risk attitude of the network node based on the threat risk index, and determining a passive risk attitude of the network node based on the vulnerability risk index;
calculating the comprehensive security situation index of the network node by using a preset security situation assessment function on the self risk situation degree, the active external risk situation degree and the passive external risk situation degree of the network node:
Wherein Q is expressed as an integrated security situation index of the network node, f () is expressed as a preset security situation assessment function, A 1 Expressed as a first weight value, the value is 0.5, B is expressed as the self risk attitude of the network node, A 2 Expressed as a second weight value, the value is 0.25, C is expressed as the active external risk attitude of the network node, A 3 The value is expressed as a third weight value, the value is 0.25, D is expressed as the passive risk attitude of the network node, e is expressed as a natural constant, the value is 2.72, and alpha is expressed as the network security assurance coefficient of the network and the node;
judging the belonging grade of the security quality of the network node according to the comprehensive security situation index of the network node, judging the security of the network node when the belonging grade of the security quality is medium grade or high grade, and judging the unsafe of the network node when the belonging grade of the security quality is low grade;
inputting the network node maximum risk assessment value, the threat risk index and the vulnerability risk index into a network node assessment model to calculate a network node safety quality assessment coefficient when carrying out power grid parameter data transmission on the network node data:
wherein F is represented as a network node when the network node data is subjected to power grid parameter data transmission
Safety quality assessment coefficient, G 1 Expressed as a network node maximum risk assessment value, G 2 Represented as network node risk reference threshold, K, under standard conditions entered in the network node assessment model 1 Expressed as threat risk index, K 2 Expressed as threat risk index reference threshold, L under standard state entered in the network node assessment model 1 Expressed as vulnerability risk index, L 2 The vulnerability risk index reference threshold value under the standard state recorded in the network node evaluation model is represented, beta is represented as the utilization rate of the network node when the network node data is subjected to power grid parameter data transmission, and delta is represented as the time delay rate of the network node when the network node data is subjected to power grid parameter data transmission.
The beneficial effects of the technical scheme are as follows: the security level of the network node can be intuitively estimated by calculating the comprehensive security situation index of the network node, so that reference conditions are set for subsequent security quality estimation calculation, the practicability is further improved, and further, the network node security quality estimation coefficient when the network node data are subjected to power grid parameter data transmission is obtained by comprehensively calculating according to the working parameters and the test results of the network node and the model, so that the calculation result is more reasonable and objective, and the practicability and the stability are further improved.
The foregoing is only a preferred embodiment of the present invention, but the scope of the present invention is not limited thereto, and any person skilled in the art, who is within the scope of the present invention, should be covered by the protection scope of the present invention by making equivalents and modifications to the technical solution and the inventive concept thereof.
Claims (10)
1. The network node evaluation system based on the power grid information parameter analysis is characterized in that: comprising the following steps:
the power grid parameter processing unit is used for acquiring power grid information parameters, constructing a power grid parameter classification model based on the power grid information parameters, and simultaneously inputting the power grid information parameters into the power grid parameter classification model for classification to acquire a plurality of sub-power grid parameter data;
the network node analysis unit is used for acquiring each data receiving terminal from the data transmission link corresponding to the sub-grid parameter data, acquiring the interaction record of the network layer of each data receiving terminal when receiving the data, and extracting the network node;
the network node evaluation unit is used for constructing a network node evaluation model, inputting the network node into the network node evaluation model for calculation, determining a maximum risk evaluation value of a data transmission link of the power grid information parameter, and screening the network node for qualification according to the maximum risk evaluation value.
2. The network node evaluation system based on grid information parameter analysis according to claim 1, wherein: the power grid parameter processing unit comprises:
the data acquisition module is used for acquiring the power grid information parameters from the power grid, determining a standard data format of the power grid information parameters, and carrying out data standardization on 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:
inputting the standard power grid information parameters into a power grid parameter classification model for classification, and acquiring parameter data labels corresponding to the data based on the power grid parameter classification model;
and clustering the standard power grid information parameters based on the parameter data labels to obtain a plurality of sub-power grid parameter data.
3. The network node evaluation system based on grid information parameter analysis according to claim 2, wherein: after the power grid parameter data are obtained, the method further comprises the following steps:
integrating and mapping the power grid parameter data into a vector space with a fixed dimension according to a label for classified storage;
determining classification characteristics corresponding to the power grid parameter data, acquiring a data format of the power grid parameter data based on the classification characteristics, and converting the data format of the power grid parameter data based on the data format to generate a target data transmission file.
4. A network node assessment system based on grid information parameter analysis according to claim 3, wherein: the network node analysis unit comprises:
the information synchronization module is used for determining a data transmission link between the target data transmission file and the data receiving terminal, receiving the target data transmission file based on the data receiving terminal, reading a plurality of sub-grid parameter data in the target data transmission file, and determining whether the plurality of sub-grid parameter data are complete;
the network node extraction module is used for determining a data acquisition rule of the data receiving terminal, generating a data transmission network protocol between the data acquisition rule and the classification characteristic of the target data transmission file according to the data acquisition rule and the classification characteristic of the target data transmission file, and acquiring a network node of each target data transmission file in a data transmission link based on the data transmission network protocol.
5. The network node evaluation system based on grid information parameter analysis as set forth in claim 4, wherein: the network node extraction module is further configured to:
searching a standard network flow of a network node in a network flow table, and determining initial data characteristics of the network node according to the standard network flow;
The data receiving terminal invokes a data resource sample, runs the data transmission network protocol based on the data resource sample, and obtains a running result;
acquiring a network node between a data receiving terminal and a target data transmission file according to the operation result, generating an interaction record, and acquiring data transmission characteristic parameters of a data transmission network protocol according to the interaction record;
and generating a grid chain between each data receiving terminal and the target data transmission file based on the data transmission characteristic parameters.
6. The network node evaluation system based on grid information parameter analysis according to claim 5, wherein: the network node evaluation unit comprises:
the evaluation model construction module is used for constructing a network node data calculation formula based on the network node data, constructing a power grid parameter data calculation formula based on the power grid parameter data, combining the network node data calculation formula and the power grid parameter data calculation formula, and constructing a network node evaluation model;
the node evaluation module is used for inputting the network node into the network node evaluation model for calculation, obtaining a network node safety quality evaluation coefficient, and judging whether the network node is qualified or not based on the network node safety quality evaluation coefficient.
7. The network node evaluation system based on grid information parameter analysis as claimed in claim 6, wherein: the method for obtaining the network node security quality assessment coefficient specifically comprises the following steps:
respectively deducting the network node data and the power grid parameter data, determining the load of the network node data in the power grid parameter data, and determining the maximum risk assessment value of the network node according to the network node safety quality assessment coefficient;
acquiring historical transmission success data of each data receiving terminal, analyzing the historical transmission success data to determine the integrity and the safety of the data receiving terminal, and evaluating threat risk indexes and vulnerability risk indexes of the data receiving terminal according to the integrity and the safety;
and inputting the maximum risk evaluation value, the threat risk index and the vulnerability risk index of the network node into a network node evaluation model to calculate a network node safety quality evaluation coefficient when carrying out power grid parameter data transmission on the network node data.
8. The network node evaluation system based on grid information parameter analysis as claimed in claim 7, wherein: the node evaluation module is further configured to:
determining a security assessment value of the network node based on the network node security quality assessment coefficient, comparing the security assessment value with a preset security assessment threshold value, and judging whether the network node is in a security operation range;
When the security assessment score is equal to or greater than the score threshold, judging that the network node has risk, and meanwhile, when the network node has risk, generating an early warning report and acquiring a data transmission link corresponding to the network node;
determining a data receiving terminal based on a data transmission link corresponding to the network node, and simultaneously transmitting the early warning report to the data receiving terminal based on the Internet of things;
otherwise, judging the security of the network node.
9. The network node evaluation system based on grid information parameter analysis according to claim 2, wherein: the data acquisition module acquires the power grid information parameters from a power grid, determines a standard data format of the power grid information parameters, performs data standardization on the power grid information parameters according to the standard data format to obtain standard power grid information parameters, and comprises the following steps:
dividing the core data of the power grid information parameters, and determining the associated data distribution of each core data according to the division result;
acquiring a data structure corresponding to the power grid information parameter based on the associated data distribution of each core data;
generating a protocol configuration file corresponding to the power grid information parameters according to the data structure;
Decomposing the power grid information parameters into a plurality of types of power grid sub-information according to the protocol configuration file;
determining a data structure object of each type of power grid sub-information according to information data distribution conditions in the power grid sub-information;
carrying out serialization processing on the data structure object of each type of power grid sub-information to obtain a byte sequence containing all information contents in the type of power grid sub-information;
inputting byte sequences of all information contents in each type of power grid sub-information into a standardized dictionary library to determine a matched standardized dictionary of the type of power grid sub-information;
acquiring a preset matching model corresponding to a matching standardized dictionary of each type of power grid sub-information;
determining a standard data format of the power grid information parameters based on a preset matching model corresponding to a matching standardized dictionary of each type of power grid sub-information;
converting all the power grid sub-information in the power grid information parameters into the standard data format, and acquiring a standardized differential data set of each power grid sub-information according to a conversion result;
acquiring the current field of abnormal data in the standardized differential data set of each power grid sub-information;
A standardized component corresponding to the current field is called from a preset database, and the current field of abnormal data in the standardized differential data set of each power grid sub-information is converted into a standard field by utilizing the standardized component;
and generating standard power grid information parameters according to the converted abnormal data and the converted normal data.
10. The network node evaluation system based on grid information parameter analysis as claimed in claim 7, wherein: the calculating the network node security quality evaluation coefficient when the network node data is transmitted with the power grid parameter data based on the network node maximum risk evaluation value, the threat risk index and the vulnerability risk index is input to a network node evaluation model comprises the following steps:
determining the self risk attitude of the network node according to the maximum risk evaluation value of the network node;
determining an active external risk attitude of the network node based on the threat risk index, and determining a passive risk attitude of the network node based on the vulnerability risk index;
calculating the comprehensive security situation index of the network node by using a preset security situation assessment function on the self risk situation degree, the active external risk situation degree and the passive external risk situation degree of the network node:
Wherein Q is expressed as an integrated security situation index of the network node, f () is expressed as a preset security situation assessment function, A 1 Expressed as a first weight value, the value is 0.5, B is expressed as the self risk attitude of the network node, A 2 Expressed as a second weight value, the value is 0.25, C is expressed as the active external risk attitude of the network node, A 3 The value is expressed as a third weight value, the value is 0.25, D is expressed as the passive risk attitude of the network node, e is expressed as a natural constant, the value is 2.72, and alpha is expressed as the network security assurance coefficient of the network and the node;
judging the belonging grade of the security quality of the network node according to the comprehensive security situation index of the network node, judging the security of the network node when the belonging grade of the security quality is medium grade or high grade, and judging the unsafe of the network node when the belonging grade of the security quality is low grade;
inputting the network node maximum risk assessment value, the threat risk index and the vulnerability risk index into a network node assessment model to calculate a network node safety quality assessment coefficient when carrying out power grid parameter data transmission on the network node data:
wherein F is represented as a network node safety quality evaluation coefficient when the network node data are subjected to power grid parameter data transmission, and G is represented as a network node safety quality evaluation coefficient when the network node data are subjected to power grid parameter data transmission 1 Expressed as a network node maximum risk assessment value, G 2 Represented as network node risk reference threshold, K, under standard conditions entered in the network node assessment model 1 Expressed as threat risk index, K 2 Expressed as threat risk index reference threshold, L under standard state entered in the network node assessment model 1 Expressed as vulnerability risk index, L 2 The vulnerability risk index reference threshold value under the standard state recorded in the network node evaluation model is represented, beta is represented as the utilization rate of the network node when the network node data is subjected to power grid parameter data transmission, and delta is represented as the time delay rate of the network node when the network node data is subjected to power grid parameter data transmission.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202310178043.8A CN116346637A (en) | 2023-02-28 | 2023-02-28 | Network node evaluation system based on power grid information parameter analysis |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202310178043.8A CN116346637A (en) | 2023-02-28 | 2023-02-28 | Network node evaluation system based on power grid information parameter analysis |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN116346637A true CN116346637A (en) | 2023-06-27 |
Family
ID=86890682
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202310178043.8A Pending CN116346637A (en) | 2023-02-28 | 2023-02-28 | Network node evaluation system based on power grid information parameter analysis |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN116346637A (en) |
Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN116797267A (en) * | 2023-08-23 | 2023-09-22 | 深空间发展投资控股(湖北)有限公司 | Distributed market data acquisition management system for equity investment |
-
2023
- 2023-02-28 CN CN202310178043.8A patent/CN116346637A/en active Pending
Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN116797267A (en) * | 2023-08-23 | 2023-09-22 | 深空间发展投资控股(湖北)有限公司 | Distributed market data acquisition management system for equity investment |
| CN116797267B (en) * | 2023-08-23 | 2023-11-24 | 深空间发展投资控股(湖北)有限公司 | Distributed market data acquisition management system for equity investment |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN110909811B (en) | OCSVM (online charging management system) -based power grid abnormal behavior detection and analysis method and system | |
| CN112910859B (en) | Internet of things equipment monitoring and early warning method based on C5.0 decision tree and time sequence analysis | |
| CN116154900B (en) | Active safety three-stage prevention and control system and method for battery energy storage power station | |
| CN112087334B (en) | Alarm root cause analysis method, electronic device and storage medium | |
| CN114386537B (en) | Lithium battery fault diagnosis method and device based on Catboost and electronic equipment | |
| CN107679734A (en) | It is a kind of to be used for the method and system without label data classification prediction | |
| CN116346637A (en) | Network node evaluation system based on power grid information parameter analysis | |
| CN108111361A (en) | Transmission network fault locating analysis method and system based on big data analysis | |
| CN116366374B (en) | Security assessment method, system and medium for power grid network management based on big data | |
| CN115037559B (en) | Data safety monitoring system based on flow, electronic equipment and storage medium | |
| CN116628554B (en) | Industrial Internet data anomaly detection method, system and equipment | |
| CN114885334B (en) | High-concurrency short message processing method | |
| CN118094531B (en) | Safe operation and maintenance real-time early warning integrated system | |
| CN117749409A (en) | Large-scale network security event analysis system | |
| CN117172753A (en) | Intelligent hydropower station inspection system and method based on mobile internet | |
| CN117201203B (en) | Block chain-based supply chain data secure sharing system and method | |
| CN118041587A (en) | Network security test evaluation system and method | |
| CN113641667A (en) | Data abnormity monitoring system and method of distributed big data acquisition platform | |
| CN117118665A (en) | Power system data interaction security threat information analysis method | |
| CN111815137A (en) | Comprehensive assessment method for vulnerability of power system | |
| CN117034149A (en) | Fault processing strategy determining method and device, electronic equipment and storage medium | |
| CN115169234B (en) | Power network reliability assessment method based on big data analysis | |
| CN111143763A (en) | Method and device for evaluating state of power equipment and storage medium thereof | |
| JP6858798B2 (en) | Feature generator, feature generator and program | |
| CN112579436B (en) | Micro-service software architecture identification and measurement method |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination |