Method and system for configuring three-layer network equipment ACL command based on AI technology and medium

Abstract

The invention discloses a method and a system for configuring an ACL command of three-layer network equipment based on an AI technology, and a medium, mainly relates to the technical field of three-layer network equipment, and is used for solving the problems that an existing scheme needs to depend on professional configuration personnel and lacks intelligent means. Comprising the following steps: acquiring three-layer network equipment information and configuration demand information in a text form; identifying a device brand and a device model used by a user from the three-layer network device information, and extracting a demand prompt word from the configuration demand information; obtaining a plurality of pieces of corresponding configuration case information from a preset equipment information database according to the equipment brand and the equipment model; and identifying the configuration case information conforming to the demand cue word from the plurality of pieces of configuration case information, inputting the demand cue word and a preset ACL operation command into a preset AI server, and adjusting to obtain final ACL operation command information.

Description

Technical Field

[0001] This application relates to the technical field of access control lists, and particularly to a method, system and medium for configuring ACL commands for three-layer network devices based on AI technology. Background Art

[0002] With the rapid development of network technology, three-layer network devices (such as enterprise routers, three-layer switches, etc.) play a core role in enterprise network architectures in data forwarding and security control functions. The Access Control List (ACL) is a key technical means for network security protection. By predefining rules to finely control network traffic, it can effectively prevent illegal access and guard against network attacks. Traditional ACL configuration requires network administrators to manually write command-line instructions, which requires the simultaneous possession of network security policy design capabilities, knowledge of device manufacturer syntax specifications, and skills in logical arrangement of operation commands.

[0003] The existing technologies have the following significant defects: First, the ACL command syntax of devices from different manufacturers (such as Cisco, Huawei, H3C, etc.) varies significantly, and configuration personnel must be familiar with the instruction systems of specific device models; second, in complex network environments, ACL rules need to take into account multi-dimensional conditions such as source / destination addresses, protocol types, port numbers, etc., and manual writing is prone to policy conflicts or logical loopholes; third, when facing new network threats or policy change requirements, there is a lack of intelligent means to quickly generate adapted ACL configuration solutions. Summary of the Invention

[0004] This application provides a method, system and medium for configuring ACL commands for three-layer network devices based on AI technology to solve the problems existing in the existing solutions, such as relying on professional configuration personnel and lacking intelligent means.

[0005] In a first aspect, this application provides a method for configuring ACL commands for three-layer network devices based on AI technology, the method comprising: Obtaining three-layer network device information and configuration requirement information in text form; Identifying the device brand and device model used by the user from the three-layer network device information, and extracting requirement prompt words from the configuration requirement information; Obtaining corresponding several configuration case information from a preset device information database according to the device brand and device model; Identifying configuration case information that meets the requirement prompt words from several configuration case information, inputting the requirement prompt words and preset ACL operation commands into a preset AI server, and adjusting to obtain final ACL operation command information; wherein, the final ACL operation command information includes ACL operation commands and parsing information for each command in the ACL operation commands.

[0006] In an implementation manner of the present application, obtaining three-layer network device information and configuration requirement information in text form specifically includes: Obtaining initial three-layer network device information and initial configuration requirement information through a preset text input interface; Obtaining a format check program and a semantic recognition program; Using the format check program to detect whether the initial three-layer network device information and the initial configuration requirement information meet the preset format requirements; When not meeting the preset format requirements, uploading format prompt information to the preset text input interface; When meeting the preset format requirements, using the semantic recognition program to detect whether the initial three-layer network device information and the initial configuration requirement information meet the preset complete semantic requirements; When not meeting the preset complete semantic requirements, uploading semantic prompt information to the preset text input interface; When meeting the preset complete semantic requirements, obtaining three-layer network device information and configuration requirement information.

[0007] In an implementation manner of the present application, identifying the device brand and device model used by the user from the three-layer network device information and extracting requirement prompt words from the configuration requirement information specifically includes: Extracting initial device brand keywords and initial model information from the three-layer network device information; Through natural language processing technology, determining the device brand and device model with the highest similarity to the initial device brand keywords and initial model information from a preset brand-model keyword library as the device brand and device model used by the user; Through natural language processing technology, extracting requirement prompt words from the configuration requirement information.

[0008] In an implementation manner of the present application, before obtaining corresponding several configuration case information from a preset device information database according to the device brand and device model, the method further includes: Storing configuration case information corresponding to different device brands and different device models in the preset device information database; Among them, the configuration case information includes device brand, device model, configuration keywords, and preset ACL operation command names.

[0009] In an implementation manner of the present application, identifying configuration case information that meets the requirement prompt words from several configuration case information, inputting the requirement prompt words and a preset ACL operation command into a preset AI server, and adjusting to obtain final ACL operation command information specifically includes: Using natural language processing technology to identify configuration case information that meets the requirement prompt words from several configuration case information; Input the requirement prompt and the preset ACL operation command into the preset AI server to generate an ACL operation command; Parse the parsing information of each command in the ACL operation command; Upload the final ACL operation command information to the preset user interaction interface.

[0010] In a second aspect, the present application provides a system for configuring the ACL commands of a three-layer network device based on AI technology. The system includes: A user interaction module for obtaining the three-layer network device information and configuration requirement information in text form; An AI processing module for identifying the device brand and device model used by the user from the three-layer network device information, and extracting the requirement prompt from the configuration requirement information; A database retrieval module for obtaining corresponding several configuration case information from the preset device information database according to the device brand and device model; A command generation module for identifying the configuration case information that meets the requirement prompt from several configuration case information, inputting the requirement prompt and the preset ACL operation command into the preset AI server, and adjusting to obtain the final ACL operation command information; wherein, the final ACL operation command information includes the ACL operation command and the parsing information of each command in the ACL operation command.

[0011] In an implementation manner of the present application, the user interaction module includes an acquisition unit, for obtaining the initial three-layer network device information and the initial configuration requirement information through a preset text input interface; Obtain a format check program and a semantic recognition program; Use the format check program to detect whether the initial three-layer network device information and the initial configuration requirement information meet the preset format requirements; When it does not meet the preset format requirements, upload the format prompt information to the preset text input interface; When it meets the preset format requirements, use the semantic recognition program to detect whether the initial three-layer network device information and the initial configuration requirement information meet the preset complete semantic requirements; When it does not meet the preset complete semantic requirements, upload the semantic prompt information to the preset text input interface; When it meets the preset complete semantic requirements, obtain the three-layer network device information and the configuration requirement information.

[0012] In an implementation manner of the present application, the AI processing module includes an extraction unit, for extracting the initial device brand keyword and the initial model information from the three-layer network device information; Through natural language processing technology, determine the device brand and device model with the highest similarity between the initial device brand keyword and the initial model information from a preset brand-model keyword library, as the device brand and device model used by the user; Extract demand prompt words from the configuration requirement information through natural language processing technology.

[0013] In an implementation manner of the present application, the system further includes a storage module, for storing configuration case information corresponding to different device brands and different device models in a preset device information database; Among them, the configuration case information includes device brand, device model, configuration keyword, and preset ACL operation command name.

[0014] In a third aspect, the present application provides a non-volatile computer storage medium, on which computer instructions are stored, and when the computer instructions are executed, a method for configuring a three-layer network device ACL command based on AI technology as described in any one of the above is implemented.

[0015] It can be seen from the above technical solutions that the present application has the following advantages: By automatically identifying the device brand and model and calling the case library in the preset database, it is possible to adapt to the ACL command syntax rules of different manufacturers (such as Cisco and Huawei), avoiding the risks of manual memory and adaptation errors. For example, for the differential ACL parameter call logic of "Huawei S5700 switch" and "Cisco Catalyst 9500", the AI model can automatically select a compliant syntax template based on the device information.

[0016] Extract prompt words (such as "prohibit external access to the internal network HTTP service") from the configuration requirement text, and combine the semantic analysis ability of the AI server to convert unstructured requirements into ACL commands containing parameters such as source IP, destination port, and protocol type, reducing the dependence on professional term expressions. Compared with the traditional method of manually writing commands one by one, the efficiency is improved.

[0017] When generating ACL operation commands, the AI model can identify potential rule conflicts (such as duplicate filtering policies or incorrect logical order) by analyzing historical configuration cases and current network device information (such as routing table status and interface security level), and automatically optimize the command permutation and combination based on the priority. For example, when the requirement involves multi-VLAN cross-device access control, the AI can dynamically adjust the command execution order to avoid policy failure.

[0018] By continuously updating the case database in the preset device information database and combining with the real-time input configuration requirements, the AI server can adapt to new types of network threats or topology change scenarios. For example, generating temporary blocking rules for zero-day attack characteristics or automatically adapting the ACL deployment nodes according to the SDN architecture adjustment.

[0019] Non-professionals can describe the configuration requirements in natural language (such as "only allow the finance department to access the ERP system"), and the system automatically generates command-line codes with parsing information, reducing the dependence on senior network engineers. At the same time, the parsing information of each command (such as "deny tcp 192.168.1.0 / 24 any eq 80") can assist the operation and maintenance personnel to quickly understand the policy logic and reduce the complexity of later maintenance. BRIEF DESCRIPTION OF THE DRAWINGS

[0020] In order to more clearly illustrate the technical solutions of the present invention, the drawings required for description will be briefly introduced below. Obviously, the drawings in the following description are only some embodiments of the present invention. For those of ordinary skill in the art, other drawings can be obtained based on these drawings without creative efforts.

[0021] Figure 1 It is a flowchart of a method for configuring ACL commands for three-layer network devices based on AI technology provided by an embodiment of the present application.

[0022] Figure 2 It is a schematic diagram of the internal structure of a system for configuring ACL commands for three-layer network devices based on AI technology provided by an embodiment of the present application. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0023] The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all the embodiments. All other embodiments obtained by those of ordinary skill in the art based on the embodiments of the present invention without creative efforts shall fall within the protection scope of the present invention.

[0024] Those skilled in the art should understand that the embodiments described below are only the preferred embodiments of the present disclosure, and do not mean that the present disclosure can only be implemented through the preferred embodiments. The preferred embodiments are only used to explain the technical principles of the present disclosure and are not used to limit the protection scope of the present disclosure. Based on the preferred embodiments provided by the present disclosure, all other embodiments obtained by those of ordinary skill in the art without creative efforts should still fall within the protection scope of the present disclosure.

[0025] It should also be noted that the term "including", "comprising" or any other variant thereof is intended to cover non-exclusive inclusion, such that a process, method, commodity or device comprising a series of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such process, method, commodity or device. Without further limitation, an element defined by the statement "comprising an..." does not exclude the presence of additional identical elements in the process, method, commodity or device comprising the element.

[0026] The technical problem to be solved by this application is to simplify the configuration of three-layer network devices (enterprise routers or three-layer switches). According to the user's problem, corresponding prompt information can be generated to guide the user to locate the problem, and then based on the user's current configuration requirements (such as the brand model of the network device and the content of the user's requirements), corresponding ACL command recommendations can be generated. The present invention can not only assist the user in locating the problem, but also generate relevant commands to solve the user's problem to improve the efficiency of configuring network devices.

[0027] In general, network troubleshooting is an operation that relies relatively heavily on experience and is highly professional. However, not everyone is a professional in actual projects. This application uses AI natural language understanding technology and retrieval technology. Through a pre-set fault knowledge base, it can assist non-professional users in locating problems existing in the network and generating command lines for configuring corresponding ACL policies to assist users in quickly solving network access problems in their work.

[0028] The technical solutions proposed in the embodiments of this application will be described in detail below with reference to the accompanying drawings.

[0029] The embodiment provides a method for configuring ACL commands for three-layer network devices based on AI technology, as Figure 1 shown, the method provided in the embodiment of this application mainly includes the following steps: Step 110, obtain three-layer network device information and configuration requirement information in text form.

[0030] In some embodiments, obtaining three-layer network device information and configuration requirement information in text form can specifically be: Obtain initial three-layer network device information and initial configuration requirement information through a pre-set text input interface; Obtain a format check program and a semantic recognition program; Use the format check program to detect whether the initial three-layer network device information and the initial configuration requirement information meet the pre-set format requirements; When they do not meet the pre-set format requirements, upload format prompt information to the pre-set text input interface; When meeting the requirements of the preset format, use a semantic recognition program to detect whether the initial three-layer network device information and the initial configuration requirement information meet the preset complete semantic requirements; When not meeting the preset complete semantic requirements, upload semantic prompt information to the preset text input interface; When meeting the preset complete semantic requirements, obtain the three-layer network device information and the configuration requirement information.

[0031] It should be noted that this step is responsible for receiving the relevant information about the three-layer network device (enterprise router or three-layer switch) input by the user, including the device brand, device model, and the description of the current problem scenario, etc. Subsequently, these input information are analyzed and processed, combined with the problem scenario data and material data in the knowledge base, to provide data support for the ACL command generation module, and finally the command generation module generates ACL operation recommendations suitable for the user's current situation.

[0032] The user inputs the information about the three-layer network device in text form. For example, input "Currently using a three-layer switch of a certain brand and model, and need to configure a network policy to block the IP of a certain network segment from accessing another certain network segment. Please assist in setting up ACL". This step will conduct a preliminary format check and semantic recognition on the text input by the user to ensure the integrity and accuracy of the input information. If the input information is incomplete or in the wrong format, the user will be prompted to re-enter or supplement the relevant information.

[0033] Step 120: Identify the device brand and model used by the user from the three-layer network device information, and extract demand prompt words from the configuration requirement information.

[0034] This step can be specifically as follows: Extract the initial device brand keyword and the initial model information from the three-layer network device information; Through natural language processing technology, determine the device brand and model with the highest similarity to the initial device brand keyword and the initial model information from the preset brand-model keyword library as the device brand and model used by the user; Through natural language processing technology, extract demand prompt words from the configuration requirement information.

[0035] Those skilled in the art can understand that in this step, the device brand and model information are first extracted from the user input. Through natural language processing (NLP) technology and a predefined brand and model keyword library, the device brand and model used by the user are accurately identified. The problem scenario described by the user is deeply analyzed to extract key information. For example, from "a certain department network segment cannot access a specific server at a certain IP", the key problem point of "a certain network segment cannot access a certain specific one" is extracted. The NLP technology is used to semantically understand the problem scenario and convert it into a form that can be understood by a computer for subsequent matching and analysis with the data in the device information database.

[0036] Step 130: Obtain corresponding several configuration case information from a preset device information database according to the device brand and model.

[0037] Before obtaining corresponding several configuration case information from a preset device information database according to the device brand and model, the method further includes: Store the configuration case information corresponding to different device brands and different device models in the preset device information database; wherein, the configuration case information includes device brand, device model, configuration keywords, and the name of the preset ACL operation command.

[0038] Those skilled in the art can understand that in this step, relevant technical parameters of the device, supported ACL features, and existing configuration case information, etc. can be queried from the preset device information database according to the identified device brand and model. The device information database stores detailed information of various common three-layer network devices, including ACL command syntax, applicable scenarios, configuration examples, etc. of devices of different brands and models. For example, for a certain brand of router, the database stores various ACL types supported by it (such as basic ACL, advanced ACL, etc.) and their corresponding command formats and usage instructions.

[0039] Step 140: Identify the configuration case information that meets the requirement prompt words from several configuration case information, input the requirement prompt words and the preset ACL operation command into a preset AI server, and adjust to obtain the final ACL operation command information.

[0040] Among them, the final ACL operation command information includes the ACL operation command and the parsing information of each command in the ACL operation command.

[0041] In some embodiments, identifying the configuration case information that meets the requirement prompt words from several configuration case information, inputting the requirement prompt words and the preset ACL operation command into a preset AI server, and adjusting to obtain the final ACL operation command information specifically includes: Using natural language processing technology, identify configuration case information that meets the requirement prompt words from several configuration case information; Input the requirement prompt words and the preset ACL operation commands into the preset AI server to generate ACL operation commands; Analyze the parsing information of each command in the ACL operation commands; Upload the final ACL operation command information to the preset user interaction interface.

[0042] For example, for a certain brand of router, in the case of basic ACL, the following commands may be generated: acl number 2000; rule permit source ; interface <the interface name connecting to the server>; traffic-filter outbound acl 2000.

[0043] For the advanced ACL scenario, considering that more precise access control may be required, such as restricting access time, etc., the following commands may be generated: acl number 3000; rule permit tcp source destination <server IP> destination-port eq <server port number> time-range [access time period name]; interface [the interface name connecting to the server]; traffic-filter outbound acl 3000; The generated ACL commands can be further optimized and verified. The optimization process includes checking the syntax correctness of the commands, ensuring that the commands comply with the best practice configuration principles of the device, and avoiding possible configuration conflicts.

[0044] The ACL operation recommendation commands generated and verified through the above steps will be presented to the user through a preset user interface. The output results not only include specific ACL commands but also come with brief parsing information to explain the function of each command and how to apply it to the user's current network environment. For example, for the ACL commands generated above, the system will explain to the user: "The first command creates a basic ACL numbered 2000 and allows traffic with the source address of to pass through; the second command applies this ACL to the interface connecting to the server, achieving control over access to the server by specific departments." The user can perform configuration operations on actual layer-3 network devices according to the commands and instructions provided by the system.

[0045] Based on the above-defined and semantically clear Q&A scenarios provided by the user, this application can give relevant configuration commands. For example, in some relatively complex network troubleshooting scenarios where it is impossible to determine specific ACL commands solely based on the description of the problem. It can also assist the user in troubleshooting. For example, if the user's problem is: "There is special flooding traffic in the current network, and I can't determine the problem, and there is no basis for configuring ACL commands." Then the application can prompt the user to first disconnect the network connection between the current switch and the upper level to assist the user in confirming the source of the flooding. Furthermore, it can assist the user in determining the problem to write appropriate ACL commands.

[0046] In addition, this application Figure 2 is a system for configuring ACL commands for layer-3 network devices based on AI technology provided by an embodiment of this application. As Figure 2 shown, the system provided by the embodiment of this application mainly includes: A user interaction module 210, which is used to obtain layer-3 network device information and configuration requirement information in text form.

[0047] The user interaction module 210 includes an acquisition unit, which is used to obtain initial layer-3 network device information and initial configuration requirement information through a preset text input interface; An acquisition format checker and a semantic recognition program; Use the format checker to detect whether the initial layer-3 network device information and initial configuration requirement information meet the preset format requirements; When they do not meet the preset format requirements, upload format prompt information to the preset text input interface; When they meet the preset format requirements, use the semantic recognition program to detect whether the initial layer-3 network device information and initial configuration requirement information meet the preset complete semantic requirements; When they do not meet the preset complete semantic requirements, upload semantic prompt information to the preset text input interface; When meeting the requirements of the preset complete semantics, obtain the three-layer network device information and the configuration requirement information.

[0048] The AI processing module 220 is used to identify the device brand and device model used by the user from the three-layer network device information, and extract the requirement prompt words from the configuration requirement information.

[0049] The AI processing module 220 includes an extraction unit. It is used to extract the initial device brand keyword and the initial model information from the three-layer network device information. Through natural language processing technology, from the preset brand-model keyword library, determine the device brand and device model with the highest similarity to the initial device brand keyword and the initial model information as the device brand and device model used by the user. Through natural language processing technology, extract the requirement prompt words from the configuration requirement information.

[0050] The database retrieval module 230 is used to obtain the corresponding several configuration case information from the preset device information database according to the device brand and device model.

[0051] The command generation module 240 is used to identify the configuration case information that meets the requirement prompt words from the several configuration case information, input the requirement prompt words and the preset ACL operation commands into the preset AI server, and adjust to obtain the final ACL operation command information; wherein, the final ACL operation command information includes the ACL operation command and the parsing information of each command in the ACL operation command.

[0052] The system further includes a storage module. It is used to store the configuration case information corresponding to different device brands and different device models in the preset device information database. Wherein, the configuration case information includes the device brand, the device model, the configuration keyword, and the preset ACL operation command name.

[0053] In addition, the embodiment of the present application also provides a non-volatile computer storage medium, on which executable instructions are stored, and when the executable instructions are executed, the method for configuring the three-layer network device ACL command based on AI technology as described above is implemented.

[0054] The above description of the disclosed embodiments enables those skilled in the art to implement or use the present invention. Various modifications to these embodiments will be apparent to those skilled in the art, and the general principles defined herein can be implemented in other embodiments without departing from the spirit or scope of the present invention. Therefore, the present invention will not be limited to the embodiments shown herein, but is to be accorded the widest scope consistent with the principles and novel features disclosed herein.

Claims

1. A method for configuring ACL commands for a layer 3 network device based on AI technology, characterized in that: The method comprises: Obtain the three-layer network device information and configuration requirement information in text form; Identify the device brand and model used by the user from the Layer 3 network device information, and extract the requirement prompt words from the configuration requirement information; According to the device brand and device model, corresponding configuration case information is obtained from the preset device information database; Identify configuration case information that meets the requirement prompt word from a number of configuration case information, input the requirement prompt word and the preset ACL operation command into the preset AI server, and adjust to obtain final ACL operation command information; wherein the final ACL operation command information includes the ACL operation command and parsing information of each command in the ACL operation command.

2. The method for configuring ACL commands for a layer 3 network device based on AI technology according to claim 1, characterized in that: Obtain the three-layer network device information and configuration requirement information in text form, including: Obtain initial three-layer network device information and initial configuration requirement information through a preset text input interface; Get format checkers and semantic recognition programs; Use the format checker to check whether the initial three-layer network device information and initial configuration requirement information meet the preset format requirements; When the preset format requirements are not met, the format prompt information is uploaded to the preset text input interface; When the preset format requirements are met, a semantic recognition program is used to detect whether the initial three-layer network device information and the initial configuration requirement information meet the preset complete semantic requirements; When the preset complete semantic requirements are not met, the semantic prompt information is uploaded to the preset text input interface; When the preset complete semantic requirements are met, obtain the three-layer network device information and configuration requirement information.

3. The method for configuring ACL commands for a layer 3 network device based on AI technology according to claim 1, characterized in that: Identify the brand and model of the device used by the user from the Layer 3 network device information, and extract the requirement prompt words from the configuration requirement information, including: Extracting initial device brand keywords and initial model information from Layer 3 network device information; By using natural language processing technology, the device brand and device model with the highest similarity between the initial device brand keyword and the initial model information are determined from a preset brand-model keyword library, and used as the device brand and device model used by the user; Through natural language processing technology, demand prompt words are extracted from configuration requirement information.

4. The method for configuring ACL commands for a layer 3 network device based on AI technology according to claim 1, characterized in that: Before acquiring corresponding configuration case information from a preset device information database according to the device brand and device model, the method further includes: Storing configuration case information corresponding to different device brands and different device models in a preset device information database; The configuration case information includes the device brand, device model, configuration keywords, and preset ACL operation command name.

5. The method for configuring ACL commands for a layer 3 network device based on AI technology according to claim 1, characterized in that: Identify configuration case information that meets the requirement prompt word from a number of configuration case information, input the requirement prompt word and the preset ACL operation command into the preset AI server, and adjust to obtain the final ACL operation command information, specifically including: Using natural language processing technology, identify configuration case information that meets the requirement prompt words from a number of configuration case information; Input the required prompt words and the preset ACL operation command into the preset AI server to generate the ACL operation command; Analyze the parsing information of each command in the ACL operation command; The final ACL operation command information is uploaded to the preset user interaction interface.

6. A system for configuring ACL commands for layer 3 network devices based on AI technology, characterized in that: The system comprises: A user interaction module is used to obtain the three-layer network device information and configuration requirement information in text form; The AI ​​processing module is used to identify the device brand and model used by the user from the Layer 3 network device information and extract the requirement prompt words from the configuration requirement information; A database retrieval module is used to obtain corresponding configuration case information from a preset device information database according to the device brand and device model; The command generation module is used to identify configuration case information that meets the requirement prompt word from a number of configuration case information, input the requirement prompt word and the preset ACL operation command into the preset AI server, and adjust to obtain the final ACL operation command information; wherein the final ACL operation command information includes the ACL operation command and the parsing information of each command in the ACL operation command.

7. The system for configuring ACL commands for layer 3 network devices based on AI technology according to claim 6, characterized in that: The user interaction module includes an acquisition unit, Used to obtain initial three-layer network device information and initial configuration requirement information through a preset text input interface; Get format checkers and semantic recognition programs; Use the format checker to check whether the initial three-layer network device information and initial configuration requirement information meet the preset format requirements; When the preset format requirements are not met, the format prompt information is uploaded to the preset text input interface; When the preset format requirements are met, a semantic recognition program is used to detect whether the initial three-layer network device information and the initial configuration requirement information meet the preset complete semantic requirements; When the preset complete semantic requirements are not met, the semantic prompt information is uploaded to the preset text input interface; When the preset complete semantic requirements are met, obtain the three-layer network device information and configuration requirement information.

8. The system for configuring ACL commands for layer-3 network devices based on AI technology according to claim 6, characterized in that: The AI ​​processing module includes an extraction unit, Used to extract initial device brand keywords and initial model information from Layer 3 network device information; By using natural language processing technology, the device brand and device model with the highest similarity between the initial device brand keyword and the initial model information are determined from a preset brand-model keyword library, and used as the device brand and device model used by the user; Through natural language processing technology, demand prompt words are extracted from configuration requirement information.

9. The system for configuring ACL commands for layer-3 network devices based on AI technology according to claim 6, characterized in that: The system also includes a storage module, Used to store configuration case information corresponding to different device brands and different device models in the preset device information database; The configuration case information includes the device brand, device model, configuration keywords, and preset ACL operation command name.

10. A non-volatile computer storage medium, characterized in that: Computer instructions are stored thereon, and when the computer instructions are executed, the method for configuring ACL commands of a three-layer network device based on AI technology as described in any one of claims 1-5 is implemented.

Images