Business data security access system, method and device using third-party large model

Abstract

The application relates to a business data security access system, method and equipment applying a third-party large model, and relates to the field of traffic management safety. The business data security access system and method applying the third-party large model provided by the application realize technical isolation between business data and a third-party public cloud large model based on an intelligent client control carrier, solve the problem of leakage of business data and personal information in the process of developing intelligent services, and realize intelligent application of the third-party public cloud large model in the field of public security government service.

Description

Technical Field

[0001] The present invention relates to the field of traffic management safety technology, and in particular to a business data security access system, method and device using a third-party large model. Background Art

[0002] With the rapid development of information technology, public security and traffic management services are undergoing a comprehensive transformation from informatization to digitization and intelligentization. This transformation not only improves the efficiency of government processing but also significantly enhances the public experience. However, traffic management services are characterized by low frequency and high demand. Most people do not frequently engage with these services and are therefore often unfamiliar with the procedures. This results in public security and traffic management departments devoting considerable time and resources to answering various inquiries from the public. To address this challenge, the application of advanced artificial intelligence technologies, such as large models, to the establishment of online smart service windows for public security and traffic management has become a key means of enhancing the ability of online traffic management services. This smart service window can intelligently and automatically answer common questions and guide users through complex procedures, significantly reducing the burden of manual consultation and improving service quality and efficiency.

[0003] While privately deploying and training large models for public security traffic management government services can provide highly customized solutions, the high cost and technical difficulty make this a prohibitive approach for many local departments. By contrast, leveraging the large model capabilities provided by third-party public clouds offers significant advantages, such as manageable costs and rapid results. Public cloud platforms typically possess powerful computing capabilities and mature technical support, enabling rapid deployment and optimization of large models, enabling them to achieve high service levels in a short period of time. However, the current information security landscape is complex and severe, especially regarding the sensitivity of traffic management business data and personal information. To effectively mitigate the risk of data leakage and ensure secure access to business data, it is imperative to research and propose an efficient and reliable data security access method. This method must not only ensure data security during transmission and storage, but also enable granular data management and access control without compromising user experience. Summary of the Invention

[0004] The purpose of the present invention is to provide a business data security access system, method and equipment using a third-party big model to solve the problem that related technologies cannot effectively protect the security of business data and personal information during deep integration and interaction with third-party systems.

[0005] To achieve the above object, the technical solution adopted by the present invention is:

[0006] In a first aspect, the present invention provides a business data security access system using a third-party large model, the system comprising:

[0007] Business system, which is used to provide user login authentication and business data query interface;

[0008] Third-party public cloud big models, which are used to provide big-model-based intent recognition, knowledge retrieval, and reasoning capabilities for government services;

[0009] Government service clients, which are the vehicles through which users access government services; and

[0010] An intelligent client control, embedded in the government service client, for linking the business system and the third-party public cloud big model;

[0011] The business system and the third-party public cloud big model are both only connected to the smart client control for communication, so as to achieve secure isolation of business data during the application of the third-party public cloud big model.

[0012] In one possible implementation, the smart client control includes:

[0013] An interactive display module, which is used to receive user questions, display the inference results of the third-party public cloud large model, and respond to user operation events;

[0014] A logic processing module, which is used to organize and process question guide words, analyze knowledge question answering results, and process record data query intent; and

[0015] A service integration module is used to integrate the business system and the third-party public cloud big model, manage sessions and access tokens, and implement data communication requests and analysis.

[0016] In a second aspect, the present invention provides a method for securely accessing business data using a third-party large model, the method being applied to any of the above-described systems for securely accessing business data using a third-party large model, the method comprising:

[0017] Obtain user questions and user personalized tag information;

[0018] Sending the user question and user personalized tag information to a third-party public cloud big model through an intelligent client control;

[0019] Based on the third-party public cloud big model, the data query intention is identified in combination with the user's question and the user's personalized tag information, and the question and answer results are generated by reasoning and fed back to the smart client control;

[0020] The question-and-answer results and data query intention are parsed by the intelligent client control, and a business data query request is initiated to the business system based on user needs.

[0021] In a possible implementation, obtaining user questions and user personalized tag information includes:

[0022] Based on the user session, the smart client obtains user questions and user personalized tag information from the business system;

[0023] The user personalized tag information does not include the user's personal identity information.

[0024] In a possible implementation, parsing the question-and-answer results and data query intent by the smart client control and initiating a business data query request to the business system based on user needs includes:

[0025] Parsing the question-and-answer results and data query intent through the smart client control, converting the data query intent into user-readable operation events, and displaying the question-and-answer results and operation events to the user;

[0026] In response to a user actively triggering an operation event, the smart client control sends a data query request to the business system.

[0027] In a possible implementation, the user personalized tag information includes at least: user location, user age, user vehicle status, user driver's license status, number of user violation records to be processed, user's permitted vehicle type, and user driver's license score.

[0028] In a possible implementation, the data query intention includes at least:

[0029] Business processing intention, which is used to indicate that a specific business function jump entry needs to be provided;

[0030] Offline branch query intent, which is used to indicate the list of service branches and detailed entrances;

[0031] Process query intent, which is used to indicate the need to provide personalized business function processes and required material entry;

[0032] Basic data query intent, which indicates that a query entry for basic data on motor vehicles, driver's licenses, and traffic violations is required; and

[0033] The manual feedback intention is used to indicate that a manual reply is required to handle the feedback entry.

[0034] In a possible implementation, in the process of parsing the question-and-answer results and data query intent by the smart client control and initiating a business data query request to the business system based on user needs:

[0035] Initiate requests based only on the currently logged-in user session, and only return information related to the current user.

[0036] In one possible implementation, based on the third-party public cloud big model, the data query intention is identified in combination with the user question and the user's personalized tag information, and the question-answer result is generated by reasoning and fed back to the smart client control:

[0037] The third-party public cloud big model identifies the preset data query intention type through semantic analysis and model reasoning based on the user questions and user personalized tag information.

[0038] In a third aspect, the present invention provides a computer device comprising a processor and a memory, wherein the memory stores at least one instruction, at least one program, code set or instruction set, and the processor can load and execute at least one instruction, at least one program, code set or instruction set to implement the method for secure access to business data of a third-party large model provided above.

[0039] In a fourth aspect, the present invention provides a computer-readable storage medium, which stores at least one instruction, at least one program, code set or instruction set. The processor can load and execute at least one instruction, at least one program, code set or instruction set to implement the business data security access method of the third-party large model provided above.

[0040] In a fifth aspect, the present invention provides a computer program product or computer program, comprising computer program instructions stored in a computer-readable storage medium. A processor reads the computer instructions from the computer-readable storage medium and executes the computer instructions, causing a computer device to perform the method for securely accessing business data using a third-party large model as provided above.

[0041] The beneficial effects brought about by the technical solution provided by the present invention include at least:

[0042] The business data security access system and method using a third-party big model provided by the present invention realizes the technical isolation between business data and the third-party public cloud big model based on the intelligent client control carrier, solves the problem of leakage of business data and personal information in the process of providing intelligent services, and realizes the intelligent application of the third-party public cloud big model in the field of public security and government services. BRIEF DESCRIPTION OF THE DRAWINGS

[0043] The accompanying drawings are used to provide further understanding of the present invention and constitute a part of the specification. They are used to explain the present invention together with the embodiments of the present invention and do not constitute a limitation of the present invention.

[0044] Figure 1A connection schematic diagram of a business data security access system applying a third-party large model is shown.

[0045] Figure 2 A structure schematic diagram of an intelligent client control of a business data security access system applying a third-party large model is shown.

[0046] Figure 3 A flowchart of a business data security access method applying a third-party large model is shown.

[0047] Figure 4 A question and answer loading flowchart based on user personalized label information of a business data security access method applying a third-party large model is shown.

[0048] Figure 5 A data query intention recognition loading flowchart of a business data security access method applying a third-party large model is shown.

[0049] Figure 6 A structure schematic diagram of a computer device for executing a business data security access method applying a third-party large model is shown. DETAILED DESCRIPTION

[0050] The technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the drawings in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, rather than all the embodiments of the present application. Based on the embodiments in the present application, all other embodiments obtained by those of ordinary skill in the art without creative work fall within the scope of protection of the present application.

[0051] The present application will be further described below with reference to the drawings and embodiments.

[0052] Figure 1 A connection schematic diagram of a business data security access system applying a third-party large model is shown. The business data security access system applying a third-party large model comprises:

[0053] A business system is configured to provide user login authentication and business data query interface. The user login authentication service is responsible for identity authentication of users using government service, and the business data interface is provided for the exchange government service client to access after user login, and only feedbacks the business data information matched with the current user identity.

[0054] Third-party public cloud big models, which are used to provide big-model-based intent recognition, knowledge retrieval, and reasoning capabilities for government services;

[0055] Government service clients, which are the vehicles for users to access government services and can be in various forms such as apps, mini-programs, and H5 pages; and

[0056] The intelligent client control is embedded in the government service client and is used to link the business system and the third-party public cloud big model. During services such as intelligent question and answer, operations involving sensitive data, such as loading user personalized tag information and querying business data, are all completed by this control agent. It is the core component for isolating third-party public cloud big model data requests and protecting business data.

[0057] It can be understood that secure access to business data relies on smart client controls. Business systems and third-party public cloud big models only communicate and connect with smart client controls to achieve secure isolation of business data during the application of third-party public cloud big models.

[0058] In an embodiment of the present application, the smart client control runs in the government service client and relies on the user login authentication session environment to achieve trusted communication with the business system. The smart client control is triggered autonomously by the user and does not actively initiate data query operations.

[0059] Figure 2 A schematic diagram of the structure of a smart client control of a business data security access system using a third-party large model provided by an exemplary embodiment of the present invention is shown. The smart client control includes:

[0060] The interactive display module is used to receive user questions, display the inference results of the third-party public cloud large model, and respond to user operation events;

[0061] A logic processing module, which is used to organize and process question guide words, analyze knowledge question answering results, and process record data query intent; and

[0062] The service integration module is used to integrate business systems and third-party public cloud models, manage sessions and access tokens, and implement data communication requests and parsing.

[0063] In the embodiment of the present application, the interactive display module provides users with an operation interface such as intelligent Q&A and guidance services. It includes the ability to collect user intelligent Q&A information, render intelligent Q&A results, and jump to events in the Q&A results. The event jump capability corresponds to the business data query intent identified by the third-party public cloud big model, providing users with personalized data query events. Users can choose to click to trigger events through the interactive display module. The events supported by the interactive display module include:

[0064] Business handling events, click to jump to the business handling function;

[0065] Check events at offline outlets and click to jump to the outlet information interface;

[0066] View events in the business process and click to jump to the business process details interface;

[0067] Information query events: based on the user's specific intent, click to jump to view motor vehicle, driver's license or traffic violation information;

[0068] Manual feedback event, click to jump to the manual feedback link entrance.

[0069] It is worth mentioning that the interactive display module supports multiple operating environments such as APP, mini-programs, H5, etc.

[0070] In the embodiment of the present application, the logic processing module is the core component of the intelligent client control that connects the business system and the third-party public cloud model. It specifically includes the following functions:

[0071] Drive the service integration module to synchronize user personalized tag information and authorization tokens to the business system;

[0072] Obtain user intelligent question and answer guidance words, assemble user personalized tag information, drive the service integration module, and initiate intelligent question and answer requests to third-party large model services;

[0073] Analyze the intelligent question-answering reasoning results, drive the exchange display module to display the question-answering results, and provide data query event drive;

[0074] Capture user operation events, drive the service integration module, and initiate data query requests to the business system;

[0075] In this embodiment, the service integration module integrates the communication protocols of the business system and the third-party public cloud model, manages sessions and access tokens, and implements network data communication. The smart client control communicates with the business system based on user sessions, and with the third-party public cloud model based on authorization tokens, ensuring data access security. The authorization tokens are dynamically issued to the business system by the third-party public cloud model.

[0076] Figure 3 A flowchart of a method for securely accessing business data using a third-party large model provided by an exemplary embodiment of the present invention is shown. Figure 4 A flowchart of a question-and-answer loading method based on user personalized tag information for secure access to business data using a third-party large model provided by an exemplary embodiment of the present invention is shown. Figure 5A flowchart for identifying data query intent in a method for securely accessing business data using a third-party large model, provided by an exemplary embodiment of the present invention, is shown. The method is applied to the secure access system for business data using a third-party large model as described above. The method is applied to a scenario of intelligent government services. The method specifically includes the following steps:

[0077] Step 301: Obtain user questions and user personalized tag information.

[0078] In an embodiment of the present application, the intelligent client obtains user questions and user personalized tag information from the business system based on the user session; wherein, the user personalized tag information does not include the user's personal identity information, and the third-party public cloud big model does not participate in the process of obtaining the user personalized tag information.

[0079] In an embodiment of the present application, the user's personalized tag information includes at least: the user's location, the user's age, the user's vehicle status, the user's driver's license status, the number of pending violations of the user, the user's permitted vehicle type, and the user's driver's license score.

[0080] Step 302: Send the user's question and personalized tag information to a third-party public cloud big model through the smart client control to achieve accurate intent recognition and reasoning based on the personalized tag information.

[0081] In a specific implementation process, the user should first log in to the business system, complete identity authentication, and then establish a session between the government service client and the business system; in the session state, the user initiates an intelligent dialogue through the smart client control, and the smart client control requests the business system to load the user's personalized tag information and call the access token of the third-party public cloud big model; the business system obtains the access token through the third-party public cloud big model authorization and authentication interface, and returns it to the smart client control together with the user's personalized tag information; the smart client control submits an intelligent question and answer request to the third-party public cloud big model based on the question guide words and the user's personalized tag information; the third-party public cloud big model authenticates the access token and accepts the question and answer request.

[0082] Step 303: Based on the third-party public cloud big model, the data query intention is identified in combination with the user's question and the user's personalized tag information, and the question and answer results are generated by reasoning and fed back to the smart client control without directly requesting the business system to implement the data query.

[0083] In an embodiment of the present application, data query intentions include at least: business processing intentions, which are used to indicate that a specific business function jump entry needs to be provided; offline outlet query intentions, which are used to indicate that a service outlet list and a details entry need to be provided; processing procedure query intentions, which are used to indicate that a personalized business function process and a required material entry need to be provided; basic data query intentions, which are used to indicate that a motor vehicle, driver's license, and traffic violation basic data query entry needs to be provided; and manual feedback intentions, which are used to indicate that a manual reply and handling feedback entry needs to be provided.

[0084] In an embodiment of the present application, based on a third-party public cloud big model, the data query intention is identified in combination with user questions and user personalized tag information, question and answer results are generated by reasoning, and feedback is given to the intelligent client control process: the third-party public cloud big model identifies the preset data query intention type based on user questions and user personalized tag information through semantic analysis and model reasoning, without being aware of the identity information of the current questioning user and without relying on the business system data interface.

[0085] Step 304: parse the question-and-answer results and data query intent through the intelligent client control, and initiate a business data query request to the business system based on user needs.

[0086] In an embodiment of the present application, the question-and-answer results and data query intentions are parsed by an intelligent client control, and the data query intentions are translated into user-readable operation events, and the question-and-answer results and operation events are displayed to the user; in response to the user actively triggering the operation event, the intelligent client control sends a data query request to the business system to enhance the question-and-answer guidance effect.

[0087] In this embodiment, the intelligent client control analyzes question-and-answer results and data query intent, and initiates business data query requests to the business system based on user needs. The request is initiated only based on the currently logged-in user session, and only information related to the current user is returned. Data communication occurs only between the intelligent client control and the business system, and is unrelated to the third-party public cloud model.

[0088] In a specific implementation, after receiving the inference results, the smart client control parses the question-and-answer results and data query intent. If the inference results do not contain data query intent, the answer result is directly rendered to the user. If the inference results contain data query intent, the query intent is converted into an action event that the user can understand, and the actionable event is displayed under the user's question-and-answer results. If the user actively triggers an action event, the smart client control initiates a data query request to the business system based on the user session and jumps to the specific function or page. Business data queries are initiated by users and completed between the smart client control and the business system. The third-party public cloud big model does not participate in the data query, parsing, and rendering process, and the smart client control does not actively initiate queries.

[0089] To sum up, the business data security access system and method using a third-party big model provided by the present invention realizes the technical isolation between business data and the third-party public cloud big model based on the intelligent client control carrier, solves the problem of leakage of business data and personal information in the process of providing intelligent services, and realizes the intelligent application of the third-party public cloud big model in the field of public security and government services.

[0090] Figure 6 A schematic diagram of the structure of a computer device for executing a method for securely accessing business data using a third-party large model provided by an exemplary embodiment of the present invention is shown. The computer device includes:

[0091] The processor 601 includes one or more processing cores. The processor 601 executes various functional applications and data processing by running software programs and modules.

[0092] Receiver 602 and transmitter 603 can be implemented as a communication component, which can be a communication chip. Optionally, the communication component can include signal transmission functionality. That is, transmitter 603 can be used to transmit control signals to the image acquisition device and scanning device, and receiver 602 can be used to receive corresponding feedback instructions.

[0093] The memory 604 is connected to the processor 601 via a bus 605 .

[0094] The memory 604 may be used to store at least one instruction, and the processor 601 may be used to execute the at least one instruction to implement each step in the above method embodiment.

[0095] An embodiment of the present invention also provides a computer-readable storage medium, which stores at least one instruction, at least one program, code set or instruction set, which is loaded and executed by a processor to implement the above-mentioned method for securely accessing business data using a third-party large model.

[0096] The present invention also provides a computer program product or computer program, which includes computer instructions stored in a computer-readable storage medium. A processor of a computer device reads the computer instructions from the computer-readable storage medium and executes the computer instructions, causing the computer device to perform the method for securely accessing business data using a third-party large model as described in any of the above embodiments.

[0097] Optionally, the computer-readable storage medium may include: read-only memory (ROM), random access memory (RAM), solid-state drives (SSDs), or optical disks. The random access memory may include resistance random access memory (ReRAM) and dynamic random access memory (DRAM). The serial numbers of the above embodiments of the present invention are for descriptive purposes only and do not represent the superiority or inferiority of the embodiments.

[0098] It should be understood that the specific examples herein are only intended to help those skilled in the art better understand the present disclosure, rather than to limit the scope of the present invention.

[0099] It can be understood that in the various implementations of this specification, the size of the sequence number of each process does not mean the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of this disclosure.

[0100] It can be understood that the various embodiments described in this specification can be implemented individually or in combination, and the present disclosure is not limited thereto.

[0101] Unless otherwise indicated, all technical and scientific terms used in this disclosure have the same meaning as commonly understood by those skilled in the art in the technical field of this specification. The terms used in this specification are only for the purpose of describing specific embodiments and are not intended to limit the scope of this specification. The term "and / or" used in this specification includes any and all combinations of one or more related listed items. The singular forms "a", "above", and "the" used in this disclosure and the appended claims are also intended to include the plural forms unless the context clearly indicates otherwise.

[0102] It is understood that the processor of the present disclosure can be an integrated circuit chip with signal processing capabilities. During implementation, each step of the above-mentioned method embodiment can be completed by hardware integrated logic circuits in the processor or software instructions. The above-mentioned processor can be a general-purpose processor, a digital signal processor (DSP), an application-specific integrated circuit (ASIC), a field programmable gate array (FPGA), or other programmable logic devices, discrete gate or transistor logic devices, or discrete hardware components. The various methods, steps, and logic block diagrams disclosed in this disclosure can be implemented or executed. The general-purpose processor can be a microprocessor or any conventional processor. The steps of the method disclosed in this disclosure can be directly implemented and executed by a hardware decoding processor, or by a combination of hardware and software modules in the decoding processor. The software module can be located in a storage medium mature in the art, such as random access memory, flash memory, read-only memory, programmable read-only memory, electrically erasable programmable memory, registers, etc. The storage medium is located in the memory, and the processor reads the information in the memory and, in conjunction with its hardware, completes the steps of the above-mentioned method.

[0103] It will be understood that the memory in the present disclosure may be volatile memory or non-volatile memory, or may include both volatile and non-volatile memory. Among them, the non-volatile memory may be read-only memory (ROM), programmable read-only memory (programmable ROM, PROM), erasable programmable read-only memory (erasable PROM, EPROM), electrically erasable programmable read-only memory (EEPROM) or flash memory. The volatile memory may be random access memory (RAM). It should be noted that the memory of the systems and methods described herein is intended to include, but is not limited to, these and any other suitable types of memory.

[0104] Those skilled in the art will appreciate that the units and algorithm steps of each example described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Professionals and technicians can use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of this specification.

[0105] Those skilled in the art will clearly understand that, for the convenience and brevity of description, the specific working processes of the above-described systems, devices and units can refer to the corresponding processes in the aforementioned method implementation methods and will not be repeated here.

[0106] In the several embodiments provided in this specification, it should be understood that the disclosed systems, devices, and methods can be implemented in other ways. For example, the device embodiments described above are merely illustrative. For example, the division of the units is merely a logical function division. In actual implementation, there may be other division methods, such as multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some interfaces, indirect coupling or communication connection of devices or units, which can be electrical, mechanical or other forms.

[0107] The units described as separate components may or may not be physically separate, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed across multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of this embodiment.

[0108] In addition, each functional unit in each embodiment of this specification may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit.

[0109] If the functions are implemented in the form of software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of this specification, or the part that contributes to the prior art, or the part of the technical solution can be embodied in the form of a software product. The computer software product is stored in a storage medium and includes several instructions for enabling a computer device (which can be a personal computer, server, or network device, etc.) to execute all or part of the steps of the method described in each embodiment of this specification. The aforementioned storage medium includes various media that can store program codes, such as a USB flash drive, a mobile hard disk, a read-only memory (ROM), a random access memory (RAM), a magnetic disk, or an optical disk.

[0110] The above description is merely a specific embodiment of this specification, but the scope of protection of the present invention is not limited thereto. Any changes or substitutions that can be easily conceived by a person skilled in the art within the technical scope disclosed in this specification should be included in the scope of protection of this specification. Therefore, the scope of protection of the present invention should be based on the scope of protection of the claims.

Claims

1. A business data security access system using a third-party large model, characterized in that: The system comprises: Business system, which is used to provide user login authentication and business data query interface; Third-party public cloud big models, which are used to provide big-model-based intent recognition, knowledge retrieval, and reasoning capabilities for government services; Government service clients, which are the vehicles through which users access government services; and An intelligent client control, embedded in the government service client, for linking the business system and the third-party public cloud big model; The business system and the third-party public cloud big model are only connected to the smart client control to achieve secure isolation of business data during the application of the third-party public cloud big model; The smart client control includes: An interactive display module, which is used to receive user questions, display the inference results of the third-party public cloud large model, and respond to user operation events; A logic processing module, which is used to organize and process question guide words, analyze knowledge question answering results, and process record data query intent; and A service integration module is used to integrate the business system and the third-party public cloud big model, manage sessions and access tokens, and implement data communication requests and analysis.

2. A method for securely accessing business data using a third-party large model, the method being applied to the system for securely accessing business data using a third-party large model as claimed in claim 1, characterized in that: The method comprises: Obtain user questions and user personalized tag information; Sending the user question and user personalized tag information to a third-party public cloud big model through an intelligent client control; Based on the third-party public cloud big model, the data query intention is identified in combination with the user's question and the user's personalized tag information, and the question and answer results are generated by reasoning and fed back to the smart client control; The question-and-answer results and data query intention are parsed by the intelligent client control, and a business data query request is initiated to the business system based on user needs.

3. The method for securely accessing business data using a third-party large model according to claim 2, characterized in that: The obtaining of user questions and user personalized tag information includes: Based on the user session, the smart client obtains user questions and user personalized tag information from the business system; The user personalized tag information does not include the user's personal identity information.

4. The method for securely accessing business data using a third-party large model according to claim 2, characterized in that: The step of parsing the question-and-answer results and data query intentions by the smart client control and initiating a business data query request to the business system based on user needs includes: Parsing the question-and-answer results and data query intent through the smart client control, converting the data query intent into user-readable operation events, and displaying the question-and-answer results and operation events to the user; In response to a user actively triggering an operation event, the smart client control sends a data query request to the business system.

5. The method for securely accessing business data using a third-party large model according to claim 2, characterized in that: The user personalized tag information includes at least: user location, user age, user vehicle status, user driver's license status, number of user violation records to be processed, user's permitted vehicle type, and user driver's license points.

6. The method for securely accessing business data using a third-party large model according to claim 2, characterized in that: The data query intention at least includes: Business processing intention, which is used to indicate that a specific business function jump entry needs to be provided; Offline branch query intent, which is used to indicate the list of service branches and detailed entrances; Process query intent, which is used to indicate the need to provide personalized business function processes and required material entry; Basic data query intent, which indicates that a query entry for basic data on motor vehicles, driver's licenses, and traffic violations is required; and The manual feedback intention is used to indicate that a manual reply is required to handle the feedback entry.

7. The method for securely accessing business data using a third-party large model according to claim 2, characterized in that: In the process of parsing the question-and-answer results and data query intentions through the smart client control, and initiating a business data query request to the business system based on user needs: Initiate requests based only on the currently logged-in user session, and only return information related to the current user.

8. The method for securely accessing business data using a third-party large model according to claim 2, characterized in that: Based on the third-party public cloud big model, the data query intention is identified by combining the user's question and the user's personalized tag information, and the question-answer results are generated by reasoning and fed back to the smart client control process: The third-party public cloud big model identifies the preset data query intention type through semantic analysis and model reasoning based on the user questions and user personalized tag information.

9. A computer device, characterized in that: The computer device includes a processor and a memory, wherein the memory stores at least one instruction, at least one program, code set or instruction set, and the at least one instruction, at least one program, code set or instruction set is loaded and executed by the processor to implement the business data security access method using a third-party large model as described in any one of claims 2 to 8.

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