Visual network security service large screen automatic arrangement method and system

Abstract

The invention discloses a visual network security service large-screen automatic arrangement method and a visual network security service large-screen automatic arrangement system. The method comprises five steps of data collection, processing, artificial intelligence arrangement, visualization and user interface. Firstly, network traffic, security events and system state data are captured; carrying out data cleaning, conversion and feature extraction; large-screen contents are automatically arranged by using deep learning; converting the data into a visual chart; and finally providing an interactive operation interface. Compared with traditional manual arrangement and arrangement schemes based on templates or rules, the method has higher flexibility and adaptability, network state changes can be intelligently responded, and user experience is improved.

Description

Technical Field

[0001] The present invention relates to the field of network security technology, and in particular to a method and system for automatically arranging a large-screen visualized network security service. Background Art

[0002] In the field of network security, business dashboards are an important tool that can display the network's security status, alerts, and other relevant information, helping network security engineers and decision makers understand the network's status in real time and promptly discover and handle security issues. However, current dashboard orchestration mainly relies on manual operations, which is not only inefficient but also prone to errors. For example, manual dashboard orchestration takes a lot of time and effort, and is prone to errors due to operational errors or omissions. In addition, the results of manual dashboard orchestration may also vary greatly due to differences in the operator's professional level and experience.

[0003] Another problem is that the information display methods of existing network security business large screens often lack intuitiveness and comprehensibility. For example, the data and charts displayed on the large screen may be difficult to understand for non-professional audiences, and may not intuitively reflect the security status of the network. This requires a method that can convert complex network security data into intuitive and easy-to-understand visual representations to improve the efficiency of information transmission on the large screen. Summary of the invention

[0004] Based on this, the embodiment of the present application provides a method and system for automatically arranging a large screen of visualized network security services. By using artificial intelligence technology to automatically arrange the large screen, the arrangement efficiency can be greatly improved and arrangement errors can be reduced. At the same time, by using visualization technology to convert complex network security data into intuitive and easy-to-understand visual representations, the intuitiveness and comprehensibility of the information display on the large screen can be greatly improved.

[0005] In a first aspect, a method for automatically arranging a large screen of a visualized network security service is provided, the method comprising:

[0006] Collect network security data; where network security data includes at least network traffic data, security event data and system status data;

[0007] Processing the collected network security data; the processing process includes data cleaning, data conversion and feature extraction;

[0008] The processed network security data is arranged on the big screen; the processed data is analyzed by deep learning algorithms, the large screen layout is optimized based on user interaction and feedback using reinforcement learning algorithms, and the arrangement of large screen elements is iteratively optimized using genetic algorithms to ensure that the charts, texts, and pictures displayed on the big screen can reflect the security status of the network in real time;

[0009] Visualize the results of the arrangement;

[0010] A user interface is set based on the visualization conversion result; wherein the user interface includes a web page, a mobile application, and virtual reality.

[0011] Optionally, collecting network security data specifically includes:

[0012] Capture network traffic data through network sniffers, obtain security event data through security event management systems, and use system monitoring tools to collect system status data.

[0013] Optionally, processing network security data specifically includes:

[0014] Data cleaning: specifically includes identifying and processing missing values ​​in the data, deleting records with missing values ​​or using statistical methods to fill in missing values; identifying outliers in the data through statistical analysis and deleting them; using filters to identify and reduce noise in the data;

[0015] Data conversion: convert data from different sources into a unified format and normalize or standardize the data;

[0016] Feature extraction: Use the principal component analysis model to extract the latent features of the data.

[0017] Optionally, the result of the arrangement is visualized and converted into a visual format, including:

[0018] According to the output data and large screen element layout instructions, the chart library and data-driven documents are used to convert the data into charts and graphics; among them, the data-driven document is D3.js;

[0019] Use geographic information system to display geographic distribution information and generate direct visual conversion results through color, shape and dynamic effects; the geographic information system is ArcGIS.

[0020] Optionally, the processed network security data is arranged on a large screen, which also includes:

[0021] Predefined large-screen templates, each of which contains specific layout and design elements. Users select the corresponding template based on specific network security monitoring needs, and then fill the collected and processed network security data into the corresponding position of the selected template.

[0022] Optionally, the processed network security data is arranged on a large screen, which also includes:

[0023] The large screen content is automatically arranged according to predefined rules; wherein the predefined rules include highlighting warning information on the large screen when a high-risk security incident is detected.

[0024] Optionally, the processed network security data is arranged on a large screen, which also includes:

[0025] The built-in expert system identifies the patterns of security events and recommends corresponding large-screen display methods based on the identified patterns.

[0026] In a second aspect, a visual network security service large-screen automatic orchestration system is provided, the system comprising:

[0027] A data collection module, used to collect network security data; wherein the network security data at least includes network flow data, security event data and system status data;

[0028] The data processing module is used to process the collected network security data; the processing process includes data cleaning, data conversion and feature extraction;

[0029] The artificial intelligence module is used to arrange the processed network security data on the large screen. The processed data is analyzed by deep learning algorithms, and the large screen layout is optimized based on user interaction and feedback using reinforcement learning algorithms. The arrangement of large screen elements is iteratively optimized using genetic algorithms to ensure that the charts, texts, and pictures displayed on the large screen can reflect the security status of the network in real time.

[0030] Visualization module, used to convert the arrangement results into visual ones;

[0031] The user interface module is used to set the user interface based on the visualization conversion result; wherein the user interface includes a web page, a mobile application, and virtual reality.

[0032] In a third aspect, an electronic device is provided, including a memory and a processor, wherein the memory stores a computer program, and when the processor executes the computer program, the method for automatically arranging a large-screen visual network security service as described in any one of the first aspects above is implemented.

[0033] In a fourth aspect, a computer-readable storage medium is provided, on which a computer program is stored. When the computer program is executed by a processor, the method for automatically arranging a large screen of visual network security services as described in any one of the first aspects above is implemented.

[0034] The beneficial effects brought by the technical solution provided by the embodiment of the present application include at least:

[0035] 1. Improve efficiency: Traditional network security business large screen layout usually needs to be done manually, which is not only inefficient but also prone to errors. However, the present invention uses artificial intelligence technology to achieve automatic layout of the large screen, which greatly improves the efficiency of layout and reduces the possibility of errors.

[0036] 2. Enhanced visual representation: The present invention greatly enhances the visual representation of network security information by using advanced visualization tools and techniques to convert complex network security data into intuitive and easy-to-understand visual representations.

[0037] 3. Improve flexibility and adaptability: The system of the present invention can automatically adjust the layout and content of the large screen according to the state of the network and changes in demand. This greatly improves the flexibility and adaptability of the large screen, so that the large screen can better meet the needs of users.

[0038] 4. Enhanced user experience: The present invention greatly enhances the user experience by providing an easy-to-use and intuitive user interface, allowing users to interactively view and operate the large screen.

[0039] 5. Has broad application prospects: Due to the importance of network security, network security business large screens are widely used in various occasions, such as security operation and maintenance centers, network monitoring centers, security audit centers, etc. Therefore, the system of the present invention has broad application prospects.

[0040] 6. Realizes intelligent management of network security information: Through artificial intelligence technology, the present invention realizes intelligent management of network security information, which can help network security personnel better understand and deal with network security issues and improve the management level of network security.

[0041] The advantages of the present invention are mainly reflected in improving efficiency, enhancing visual representation, improving flexibility and adaptability, enhancing user experience, having broad application prospects, and realizing intelligent management of network security information. BRIEF DESCRIPTION OF THE DRAWINGS

[0042] In order to more clearly illustrate the implementation methods of the present invention or the technical solutions in the prior art, the following briefly introduces the drawings required for the implementation methods or the description of the prior art. Obviously, the drawings in the following description are only exemplary, and for ordinary technicians in this field, other implementation drawings can be derived from the provided drawings without creative work.

[0043] Figure 1 A flowchart of the steps of a method for automatically arranging a large screen of visual network security services provided in an embodiment of the present application;

[0044] Figure 2 A flowchart of the system business architecture provided for the embodiment of the present application;

[0045] Figure 3 A system workflow diagram provided for an embodiment of the present application. DETAILED DESCRIPTION

[0046] In order to make the purpose, technical solution and advantages of the present application more clearly understood, the present application is further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present application and are not used to limit the present application.

[0047] In the description of the present invention, the terms "comprises", "has" and any variations thereof are intended to cover non-exclusive inclusions. For example, a process, method, system, product or apparatus comprising a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may also include other steps or units that are not explicitly listed but are inherent to these processes, methods, products or apparatuses, or steps or units added based on further optimization schemes conceived by the present invention.

[0048] The network security business screen is an important part of network security management. It can display the network's security status, alarms and other related information in real time, helping network security engineers and decision makers understand the real-time status of the network and discover and deal with security issues. However, the traditional screen arrangement method mainly relies on manual operation, which is not only inefficient but also prone to errors.

[0049] To solve these problems, some existing solutions try to introduce automation technology. For example, some systems use preset templates for large screen layout. This method can improve the layout efficiency and reduce the layout errors to a certain extent. However, the flexibility and adaptability of the preset template method are limited. For example, if the status or demand of the network changes, the preset template may not meet the new demand. In addition, the preset template method cannot solve the problem of intuitiveness and comprehensibility of information display.

[0050] Another existing solution is the rule-based automatic orchestration method. This method uses predefined rules to orchestrate the big screen. For example, you can define some rules such as "if a certain type of security event occurs, display a certain type of chart on the big screen." However, the flexibility and adaptability of this method are also limited. For example, the predefined rules may not cover all situations and it is difficult to cope with the rapid changes in network status. In addition, the definition and update of rules also require a lot of manual operations, which increases the complexity and workload of management.

[0051] Therefore, the technical problems to be solved by the present invention include:

[0052] 1. How to improve the efficiency of the network security business screen and reduce the errors in the arrangement;

[0053] 2. How to improve the intuitiveness and comprehensibility of information display on the network security business screen.

[0054] The current network security business screen orchestration mainly relies on manual operation or preset templates and rule-based automatic orchestration methods. These methods have some obvious shortcomings.

[0055] First, the manual operation of the arrangement method is inefficient and prone to errors. Manual arrangement of the large screen takes a lot of time and energy, and is prone to errors due to operational errors or omissions. In addition, the results of manual arrangement of the large screen may also vary greatly due to the different professional levels and experience of the operators.

[0056] Secondly, the flexibility and adaptability of preset templates and rule-based automatic orchestration methods are limited. If the state or needs of the network change, the preset templates or rules may not meet the new needs. In addition, the preset template method and rule-based method cannot solve the problem of intuitiveness and comprehensibility of information display.

[0057] Finally, existing solutions cannot meet the needs of automatic orchestration of network security business large screens, especially in terms of orchestration efficiency, orchestration errors, information intuitiveness and comprehensibility.

[0058] Therefore, the purpose of the present invention is to propose a large-screen automatic arrangement system for visualized network security services based on artificial intelligence to solve the above problems. Specifically, the objectives of the present invention include:

[0059] 1. Improve the efficiency of network security business screen arrangement and reduce arrangement errors. By using artificial intelligence technology to automatically arrange the screen, the efficiency of arrangement can be greatly improved and the errors can be reduced.

[0060] 2. Improve the intuitiveness and comprehensibility of information display on the network security business large screen. By using visualization technology to convert complex network security data into intuitive and easy-to-understand visual representations, the intuitiveness and comprehensibility of information display on the large screen can be greatly improved.

[0061] 3. Improve the flexibility and adaptability of the network security business screen. By using artificial intelligence technology to automatically arrange the screen, the screen can better adapt to changes in network status and needs.

[0062] By achieving these goals, the present invention can greatly improve the efficiency and effect of the network security business large screen, thereby improving the effect of network security management.

[0063] Existing solutions cannot meet the needs of automatic arrangement of network security business large screens, especially in terms of arrangement efficiency, arrangement errors, information intuitiveness and comprehensibility. In order to solve these problems, the present invention proposes a method and system for automatic arrangement of visual network security business large screens based on artificial intelligence. By using artificial intelligence technology to automatically arrange large screens, not only can the arrangement efficiency be greatly improved and arrangement errors be reduced, but also complex network security data can be converted into intuitive and easy-to-understand visual representations through visualization technology, thereby greatly improving the intuitiveness and comprehensibility of information display on the large screen. Please refer to Figure 1 , which shows a flowchart of a method for automatically arranging a large screen of visual network security services provided by an embodiment of the present application, which may include the following steps:

[0064] S1, collect network security data.

[0065] Among them, network security data at least includes network flow data, security event data and system status data. This step is responsible for collecting data related to network security. These data include network flow data, security event data, system status data, etc. These data can be collected in various ways, for example, collecting network flow data through a network sniffer, collecting security event data through a security event management system, and collecting system status data through a system monitoring tool.

[0066] S2, processes the collected network security data.

[0067] The processing process includes data cleaning, data conversion and feature extraction. This step is responsible for processing the collected data and extracting useful information. The data processing process includes various data processing algorithms, such as data cleaning algorithms, data conversion algorithms, feature extraction algorithms, etc. The goal of the data processing process is to convert the raw data into a format suitable for artificial intelligence algorithm processing.

[0068] Data cleaning implementation details include:

[0069] Missing value handling: Identify and handle missing values ​​in the data. This may include deleting records with missing values ​​or filling in missing values ​​using statistical methods (such as mean, median, mode).

[0070] Outlier detection: Identify outliers in the data through statistical analysis or machine learning algorithms. These outliers may be caused by errors or security attacks. Outliers can be removed, replaced, or corrected using models.

[0071] Noise filtering: Identify and reduce noise in the data, which may include smoothing techniques or filters to improve data quality.

[0072] Consistency check: Ensure that data remains consistent across different sources and formats, for example, timestamp format, naming conventions, etc.

[0073] Data conversion implementation details include:

[0074] Format unification: Convert data from different sources into a unified format for easy processing and analysis.

[0075] Normalization / Standardization: Normalizing or standardizing the data to make the scales of different features consistent helps improve the performance of the algorithm.

[0076] Encoding conversion: Convert categorical data into numerical data, for example, using One-Hot Encoding or Label Encoding.

[0077] Feature construction: construct new features from raw data that may be more useful for cybersecurity analysis, for example, extracting the time of day from the timestamp.

[0078] Feature extraction implementation details include:

[0079] Statistical feature extraction: Extract statistical features from data, such as mean, variance, maximum value, minimum value, etc. These features help describe the distribution characteristics of the data.

[0080] Frequency Domain Feature Extraction: Extract frequency domain features from data using methods such as Fourier transform, which is particularly useful for identifying periodic patterns.

[0081] Time series feature extraction: For time series data, extract time series features such as trends and seasonality, which helps predict and identify network security incidents.

[0082] Model-based feature extraction: Use machine learning models (such as principal component analysis PCA, autoencoders) to extract latent features of the data that can capture the complex structure and relationships of the data.

[0083] S3, arranges the processed network security data on a large screen.

[0084] Among them, the data processed by deep learning algorithm analysis is used, the reinforcement learning algorithm is used to optimize the large-screen layout based on user interaction and feedback, and the genetic algorithm is applied to iteratively optimize the arrangement of large-screen elements to ensure that the charts, texts and picture elements displayed on the large screen can reflect the security status of the network in real time.

[0085] This step is responsible for automatically arranging the large screen according to the processed data. Specifically, it includes various artificial intelligence algorithms, such as deep learning algorithms, reinforcement learning algorithms, genetic algorithms, etc. The goal of this step is to automatically select and arrange the elements of the large screen, including charts, text, pictures, etc., according to the status and needs of the network.

[0086] S4, visualizes the results of the arrangement.

[0087] This step is responsible for converting the output of S3 into a visual representation. Visualization includes various visualization tools and technologies, such as chart libraries, data-driven documents (D3.js), geographic information systems (ArcGIS), etc. The goal of visualization is to convert complex network security data into intuitive and easy-to-understand visual representations.

[0088] S5, setting a user interface based on the visualized conversion result.

[0089] Wherein, the user interface includes web pages, mobile applications, and virtual reality.

[0090] This step is responsible for providing a user interface so that users can interactively view and operate the large screen. This step includes setting up various user interface technologies, such as web pages, mobile applications, virtual reality, etc. The goal is to provide an easy-to-use and intuitive user interface so that users can easily view and operate the large screen.

[0091] In an optional embodiment of the present application, S3 may arrange the processed network security data on a large screen by the following method:

[0092] 1. Template-based layout solution: This solution usually includes a series of predefined large screen templates. Users can select the appropriate template according to their needs and then fill in the corresponding data. The advantage of this solution is that it is simple to implement and users can quickly create large screens. However, this solution has poor flexibility and adaptability and may not meet complex and changing needs.

[0093] 2. Rule-based orchestration scheme: This scheme usually includes a series of predefined rules, and the system automatically arranges the large screen according to these rules. The advantage of this scheme is that it can achieve a certain degree of automation and reduce manual operations. However, this scheme is also less flexible and adaptable, requires manual pre-definition of rules, and is difficult to handle complex and unknown situations.

[0094] 3. Expert system-based arrangement solution: This solution usually includes an expert system, which contains a large amount of expert knowledge and experience, and can automatically arrange the large screen based on this knowledge and experience. The advantage of this solution is that it can use the expert knowledge and experience to improve the quality of arrangement. However, this solution is difficult to implement, requiring the collection and processing of a large amount of expert knowledge and experience, and it is difficult to handle new and unknown situations.

[0095] Although these alternative technical solutions have their own advantages and disadvantages, in comparison, the artificial intelligence-based automatic orchestration system of the present invention has significant advantages in terms of efficiency, accuracy, visual representation, user experience, and handling of complex and changing requirements.

[0096] Please refer to Figure 2 , which shows a system business architecture flow chart of a visual network security business large-screen automatic orchestration system provided by an embodiment of the present application, including:

[0097] A data collection module, used to collect network security data; wherein the network security data at least includes network flow data, security event data and system status data;

[0098] The data processing module is used to process the collected network security data; the processing process includes data cleaning, data conversion and feature extraction;

[0099] The artificial intelligence module is used to arrange the processed network security data on the large screen. The processed data is analyzed by deep learning algorithms, and the large screen layout is optimized based on user interaction and feedback using reinforcement learning algorithms. The arrangement of large screen elements is iteratively optimized using genetic algorithms to ensure that the charts, texts, and pictures displayed on the large screen can reflect the security status of the network in real time.

[0100] Visualization module, used to convert the arrangement results into visual ones;

[0101] The user interface module is used to set the user interface based on the visualization conversion result; wherein the user interface includes a web page, a mobile application, and virtual reality.

[0102] like Figure 3 The system workflow diagram is given. In this system, first, the data collection module collects network security related data. Then, the data processing module processes the collected data and extracts useful information. Next, the artificial intelligence module automatically arranges the large screen according to the processed data. Then, the visualization module converts the output of the artificial intelligence module into a visual representation. Finally, the user interface module provides a user interface so that users can interactively view and operate the large screen.

[0103] In this way, the system can realize the automatic arrangement of the network security business screen, improve efficiency, reduce errors, and enhance the visual representation of network security information. In addition, the system can also automatically adjust the layout and content of the screen according to the changes in network status and needs, improving the flexibility and adaptability of the screen.

[0104] The key points and points to be protected of the present invention mainly include the following aspects:

[0105] 1. Automatic arrangement method based on artificial intelligence: A key point of the present invention is to use artificial intelligence technology to achieve automatic arrangement of large screens. This includes using artificial intelligence algorithms such as deep learning, reinforcement learning, and genetic algorithms to automatically select and arrange elements of large screens according to the status and needs of the network. This is the core of the present invention and an important protection point of the present invention.

[0106] 2. Data processing and feature extraction: In order to enable the artificial intelligence algorithm to effectively process network security data, the present invention includes a data processing module for processing the collected data and extracting useful information. This includes methods such as data cleaning, data conversion, and feature extraction. This is an important supporting technology of the present invention and also a protection point of the present invention.

[0107] 3. Visualization: To enhance the visualization of network security information, the present invention includes a visualization module for converting the output of the artificial intelligence module into a visualization. This includes the use of various visualization tools and techniques, which is an important feature of the present invention and a protection point of the present invention.

[0108] 4. User interaction interface: In order to allow users to interactively view and operate the large screen, the present invention includes a user interface module that provides an easy-to-use and intuitive user interface. This includes the use of various user interface technologies, which is an important feature of the present invention and also a protection point of the present invention.

[0109] 5. Overall architecture and workflow of the system: The system of the present invention includes a data collection module, a data processing module, an artificial intelligence module, a visualization module and a user interface module. The design and organization of these modules, as well as the workflow between them, constitute the overall architecture of the present invention. This is an important feature of the present invention and also a protection point of the present invention.

[0110] The key points and points to be protected of the present invention mainly include automatic arrangement method based on artificial intelligence, data processing and feature extraction, visual representation, user interaction interface and the overall architecture and workflow of the system.

[0111] For the specific limitations of the visual network security business large-screen automatic orchestration system, please refer to the limitations of the visual network security business large-screen automatic orchestration system above, which will not be repeated here. Each module in the above-mentioned visual network security business large-screen automatic orchestration system can be implemented in whole or in part through software, hardware and a combination thereof. The above-mentioned modules can be embedded in or independent of the processor in the computer device in the form of hardware, or can be stored in the memory of the computer device in the form of software, so that the processor can call and execute the operations corresponding to the above modules.

[0112] In one embodiment, an electronic device is provided, which may be a computer. The electronic device includes a processor, a memory, and a network interface connected via a system bus. The processor of the device is used to provide computing and control capabilities. The memory of the device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system, a computer program, and a database. The internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The database of the computer device is used to automatically arrange data on a large screen of visual network security services. The network interface of the computer device is used to communicate with an external terminal via a network connection. When the computer program is executed by the processor, a method for automatically arranging a large screen of visual network security services is implemented.

[0113] In one embodiment of the present application, a computer-readable storage medium is provided, on which a computer program is stored. When the computer program is executed by a processor, the steps of the above-mentioned visual network security business large-screen automatic arrangement method are implemented.

[0114] The computer-readable storage medium and computer program product provided in this embodiment have similar implementation principles and technical effects to those of the above method embodiments, and are not described in detail here.

[0115] Those of ordinary skill in the art can understand that all or part of the processes in the above-mentioned embodiment methods can be completed by instructing related hardware through a computer program, and the computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the embodiments of the above-mentioned methods. Among them, any reference to memory, storage, database or other media used in the embodiments provided in this application may include non-volatile and / or volatile memory. Non-volatile memory may include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM) or flash memory. Volatile memory may include random access memory (RAM) or external cache memory. By way of illustration and not limitation, RAM is available in M ​​forms, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double data rate SDRAM (DDRSDRAM), enhanced SDRAM (ESDRAM), synchronous link (SyMchliMk) DRAM (SLDRAM), memory bus (RaMbus) direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM), etc.

[0116] The technical features of the above-described embodiments may be arbitrarily combined. To make the description concise, not all possible combinations of the technical features in the above-described embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0117] The above-described embodiments only express several implementation methods of the present application, and the descriptions thereof are relatively specific and detailed, but they cannot be construed as limiting the scope of the patent application. It should be pointed out that, for a person of ordinary skill in the art, several variations and improvements can be made without departing from the concept of the present application, and these all belong to the protection scope of the present application. Therefore, the protection scope of the patent application shall be subject to the attached claims.

Claims

1. A method for automatically arranging a large-screen visual network security service, characterized in that: The method comprises: Collect network security data; where network security data includes at least network traffic data, security event data and system status data; Processing the collected network security data; the processing process includes data cleaning, data conversion and feature extraction; The processed network security data is arranged on the big screen; the processed data is analyzed by deep learning algorithms, the large screen layout is optimized based on user interaction and feedback using reinforcement learning algorithms, and the arrangement of large screen elements is iteratively optimized using genetic algorithms to ensure that the charts, texts, and pictures displayed on the big screen can reflect the security status of the network in real time; Visualize the results of the arrangement; A user interface is set based on the visualization conversion result; wherein the user interface includes a web page, a mobile application, and virtual reality.

2. The method for automatically arranging a large-screen visual network security service according to claim 1 is characterized in that: The collection of network security data specifically includes: Capture network traffic data through network sniffers, obtain security event data through security event management systems, and use system monitoring tools to collect system status data.

3. The method for automatically arranging a large-screen visual network security service according to claim 1 is characterized in that: The processing of network security data specifically includes: Data cleaning: specifically includes identifying and processing missing values ​​in the data, deleting records with missing values ​​or using statistical methods to fill in missing values; identifying outliers in the data through statistical analysis and deleting them; using filters to identify and reduce noise in the data; Data conversion: convert data from different sources into a unified format and normalize or standardize the data; Feature extraction: Use the principal component analysis model to extract the latent features of the data.

4. The method for automatically arranging a large-screen visual network security service according to claim 1 is characterized in that: The visual transformation of the arrangement results specifically includes: According to the output data and large screen element layout instructions, the chart library and data-driven documents are used to convert the data into charts and graphics; among them, the data-driven document is D3.js; Use geographic information system to display geographic distribution information and generate direct visual conversion results through color, shape and dynamic effects; the geographic information system is ArcGIS.

5. The method for automatically arranging a large-screen visual network security service according to claim 1 is characterized in that: The processed network security data is arranged on a large screen, including: Predefined large-screen templates, each of which contains specific layout and design elements. Users select the corresponding template based on specific network security monitoring needs, and then fill the collected and processed network security data into the corresponding position of the selected template.

6. The method for automatically arranging a large-screen visual network security service according to claim 1 is characterized in that: The processed network security data is arranged on a large screen, including: The large screen content is automatically arranged according to predefined rules; wherein the predefined rules include highlighting warning information on the large screen when a high-risk security incident is detected.

7. The method for automatically arranging a large-screen visual network security service according to claim 1 is characterized in that: The processed network security data is arranged on a large screen, including: The built-in expert system identifies the patterns of security events and recommends corresponding large-screen display methods based on the identified patterns.

8. A visual network security business large screen automatic arrangement system, characterized in that: The system comprises: A data collection module, used to collect network security data; wherein the network security data at least includes network flow data, security event data and system status data; The data processing module is used to process the collected network security data; the processing process includes data cleaning, data conversion and feature extraction; The artificial intelligence module is used to arrange the processed network security data on the large screen. The processed data is analyzed by deep learning algorithms, and the large screen layout is optimized based on user interaction and feedback using reinforcement learning algorithms. The arrangement of large screen elements is iteratively optimized using genetic algorithms to ensure that the charts, texts, and pictures displayed on the large screen can reflect the security status of the network in real time. Visualization module, used to convert the arrangement results into visual ones; The user interface module is used to set the user interface based on the visualization conversion result; wherein the user interface includes a web page, a mobile application, and virtual reality.

9. An electronic device, characterized in that: It includes a memory and a processor, the memory stores a computer program, and when the computer program is executed by the processor, it implements the method for automatic arrangement of a large-screen visualized network security business as described in any one of claims 1 to 7.

10. A computer-readable storage medium, characterized in that: A computer program is stored thereon, and when the computer program is executed by a processor, the method for automatically arranging a large-screen visual network security service is implemented as described in any one of claims 1 to 7.

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