Information security intelligent interaction cooperation method and device based on large language model
Through intelligent interactive collaboration methods based on large language models, SQL statement performance problems are solved, database performance is improved, data leakage is avoided, and development efficiency is improved.
Patent Information
- Application Number
- CN202311735956.1
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2023-12-15
- Publication Date
- 2025-07-22
AI Technical Summary
In the prior art, performance problems of SQL statements are difficult to quickly and accurately diagnose and optimize, resulting in low database performance and error-prone, and traditional methods are inefficient and complex.
The intelligent interaction collaboration method based on the large language model is adopted. By establishing intelligent interaction collaboration requests, intelligent interaction language information and table structure information are extracted, encrypted, input the large language model to generate response information, and decrypted and displayed to achieve secure information interaction, assisting developers to write high-quality intelligent interaction language files.
It realizes automatic generation, diagnosis and optimization of intelligent interactive languages, improves database performance, avoids data leakage, and improves developer work efficiency and accuracy.
Smart Images
Figure CN120353774A_ABST
Abstract
Description
Technical Field
[0001] This application relates to the field of computer information processing. Specifically, it relates to an information security intelligent interaction and collaboration method, device, electronic device, and computer-readable medium based on a large language model. Background Art
[0002] In a real development environment, developers cannot directly interact with a database, and various intelligent interaction languages serve as the bridge between developers and the database. The most common intelligent interaction language is SQL (Structured Query Language). SQL is an intelligent interaction language with multiple functions such as data manipulation and data definition. This language has an interactive feature, which provides great convenience for users. The database management system should make full use of the SQL language to improve the working quality and efficiency of computer application systems. The SQL language can not only be independently applied to terminals but also serve as a sub-language to provide effective assistance for other programming. In this program application, SQL can optimize program functions together with other programming languages, thereby providing users with more comprehensive information.
[0003] Since SQL is a structured query language, this language requires developers to specify a specific interaction scheme for a specific problem, that is, to write SQL statements. However, in the actual development process, performance problems of SQL statements are widespread. Some performance problems only occur when the data volume reaches a certain level or a certain condition is triggered. Once they occur, how to quickly and accurately diagnose the cause of the problem and how to quickly optimize the SQL statements to avoid the same problem from occurring again have always been difficult problems that every developer needs to face. Traditional SQL diagnosis and optimization methods usually require manual analysis of SQL statements. For complex SQL statements, problems such as high complexity, low efficiency, and easy errors are often encountered. Therefore, a new intelligent interaction and collaboration method, device, electronic device, and computer-readable medium based on a large language model are needed.
[0004] The above information disclosed in the background art section is only used to enhance the understanding of the background of this application. Therefore, it may include information that does not constitute the prior art known to those of ordinary skill in the art. Summary of the Invention
[0005] In view of this, this application provides an information security intelligent interaction and collaboration method, device, electronic device, and computer-readable medium based on a large language model, which can automatically generate, diagnose, and optimize intelligent interaction languages, assist developers in writing high-quality intelligent interaction language files, quickly analyze intelligent interaction languages with problems and propose optimization solutions, improve database performance, and avoid data leakage.
[0006] Other features and advantages of the present application will become apparent from the following detailed description, or will be learned in part through the practice of the present application.
[0007] According to one aspect of the present application, an intelligent interaction and collaboration method based on a large language model is proposed. The method includes: establishing an intelligent interaction and collaboration request, where the intelligent interaction and collaboration request is: a first request and / or a second request and / or a third request; extracting intelligent interaction language information from the intelligent interaction and collaboration request; obtaining table structure information related to the intelligent interaction and collaboration request; encrypting the intelligent interaction language information and the table structure information to generate a collaborative processing problem; inputting the collaborative processing problem into the large language model to generate a response information; decrypting the response information and displaying it to achieve information - secure interaction.
[0008] Optionally, when the intelligent interaction and collaboration request is the first request, establishing the intelligent interaction and collaboration request includes: establishing an intelligent interaction language file; based on natural language, inputting functional data and a target table of the intelligent interaction language to be generated; establishing the intelligent interaction and collaboration request according to the functional data and the target table.
[0009] Optionally, when the intelligent interaction and collaboration request is the second request and / or the third request, establishing the intelligent interaction and collaboration request includes: selecting the intelligent interaction language file; determining the intelligent interaction language file as a diagnosis or optimization; determining the target table corresponding to the intelligent interaction language file; establishing the intelligent interaction and collaboration request according to the intelligent interaction language file and the target table.
[0010] Optionally, extracting intelligent interaction language information from the intelligent interaction and collaboration request includes: extracting functional data from the intelligent interaction and collaboration request as the intelligent interaction language information; or extracting the intelligent interaction language file from the intelligent interaction and collaboration request as the intelligent interaction language information.
[0011] Optionally, obtaining table structure information related to the intelligent interaction and collaboration request includes: extracting the target table from the intelligent interaction and collaboration request; obtaining the table name, table field information, type information, index information, and storage engine information corresponding to the target table.
[0012] Optionally, encrypting the intelligent interaction language information and the table structure information to generate a collaborative processing problem includes: decomposing the table structure information to generate elements; performing name mapping on the intelligent interaction language information and the elements based on a mapping dictionary for encryption; generating the collaborative processing problem through the encryption result.
[0013] Optionally, it further includes: extracting all table structure information in the database; decomposing all the table structure information to generate multiple elements; assigning mapping names to the multiple elements respectively; and generating the mapping dictionary through the multiple elements and their corresponding mapping names.
[0014] Optionally, generating the collaborative processing problem from the encryption result includes: determining a problem template according to the intelligent interaction collaboration request; and filling the encryption result into the problem template to generate the collaborative processing problem.
[0015] Optionally, decrypting and then displaying the response information to achieve information - secure interaction includes: decrypting the response information through the mapping dictionary; and displaying the decryption result on the user side.
[0016] Optionally, displaying the decryption result on the user side includes: displaying the decryption result in the form of chat language on the platform page.
[0017] According to one aspect of the present application, an intelligent interaction collaboration device based on a large - language model is proposed. The device includes: a request module for establishing an intelligent interaction collaboration request, where the intelligent interaction collaboration request is: a first request and / or a second request and / or a third request; a language module for extracting intelligent interaction language information from the intelligent interaction collaboration request; a structure module for obtaining table structure information related to the intelligent interaction collaboration request; an encryption module for encrypting the intelligent interaction language information and the table structure information to generate a collaborative processing problem; a response module for inputting the collaborative processing problem into the large - language model to generate a response information; and a decryption module for decrypting and then displaying the response information to achieve information - secure interaction.
[0018] According to one aspect of the present application, an electronic device is proposed. The electronic device includes: one or more processors; a storage device for storing one or more programs; when the one or more programs are executed by the one or more processors, the one or more processors implement the method as described above.
[0019] According to one aspect of the present application, a computer - readable medium is proposed, on which a computer program is stored, and when the program is executed by a processor, it implements the method as described above.
[0020] Based on the large language model, the information security intelligent interaction and collaboration method, device, electronic device and computer-readable medium of the present application establish an intelligent interaction and collaboration request, where the intelligent interaction and collaboration request is: the first request and / or the second request and / or the third request; extract intelligent interaction language information from the intelligent interaction and collaboration request; obtain table structure information related to the intelligent interaction and collaboration request; encrypt the intelligent interaction language information and the table structure information to generate a collaborative processing problem; input the collaborative processing problem into the large language model to generate response information; decrypt and display the response information to achieve information security interaction. In this way, it can automatically generate, diagnose and optimize intelligent interaction languages, assist developers in writing high-quality intelligent interaction language files, quickly analyze existing intelligent interaction languages and propose optimization solutions, improve database performance, and avoid data leakage.
[0021] It should be understood that the above general description and the following detailed description are only exemplary and do not limit the present application. Brief Description of the Drawings
[0022] By referring to the accompanying drawings and describing their exemplary embodiments in detail, the above and other objectives, features and advantages of the present application will become more apparent. The following described drawings are only some embodiments of the present application. For those of ordinary skill in the art, other drawings can be obtained based on these drawings without creative efforts.
[0023] Figure 1 It is a flowchart of a method for information security intelligent interaction and collaboration based on a large language model shown according to an exemplary embodiment.
[0024] Figure 2 It is a schematic diagram of a method for information security intelligent interaction and collaboration based on a large language model shown according to another exemplary embodiment.
[0025] Figure 3 It is a flowchart of a method for information security intelligent interaction and collaboration based on a large language model shown according to another exemplary embodiment.
[0026] Figure 4 It is a flowchart of a method for information security intelligent interaction and collaboration based on a large language model shown according to another exemplary embodiment.
[0027] Figure 5 It is a block diagram of a device for information security intelligent interaction and collaboration based on a large language model shown according to an exemplary embodiment.
[0028] Figure 6 It is a block diagram of an electronic device shown according to an exemplary embodiment. Detailed Description of the Specific Embodiment
[0029] Example embodiments will now be described more fully with reference to the accompanying drawings. However, the example embodiments can be implemented in various forms and should not be construed as limited to the embodiments set forth herein; rather, these embodiments are provided so that this application will be thorough and complete, and will fully convey the concept of the example embodiments to those skilled in the art. Like reference numerals in the figures denote like or similar parts, and thus their repeated description will be omitted.
[0030] Abbreviations and Definitions of Key Terms
[0031] 1. AI (Artificial Intelligence): Artificial Intelligence.
[0032] 2. GPT (Generative Pre-trained Transformer): Generative Pre-trained Transformer model.
[0033] 3. SQL (Structured Query Language): Structured Query Language, a standard query language for managing relational databases, which can be used to store, retrieve, modify, and manage data in a database.
[0034] 4. IDEA (IntelliJ IDEA): An integrated development tool for the Java programming language.
[0035] 5. SQL Diagnosis and Tuning: Analyze existing SQL to find out whether there are problems that may affect database performance or data security, etc., and propose optimization solutions for these problems, and optimize and adjust the problematic SQL.
[0036] 6. Data Masking: Transform certain sensitive information through masking rules to achieve reliable protection of sensitive privacy data.
[0037] Figure 1 is a flowchart of an information security intelligent interaction and collaboration method based on a large language model shown according to an exemplary embodiment. The information security intelligent interaction and collaboration method 10 based on a large language model includes at least steps S102 to S112.
[0038] As Figure 1 shown, in S102, an intelligent interaction and collaboration request is established, and the intelligent interaction and collaboration request is: the first request and / or the second request and / or the third request.
[0039] In a specific embodiment, a plugin can be installed on the user side, and this plugin monitors the operation instructions of the user side on the database. When the user operates the intelligent interaction language, it monitors the user actions to trigger subsequent auxiliary steps.
[0040] In subsequent embodiments of the present application, taking SQL language as an example, the intelligent interaction and collaboration method of the present application will be described. It can be understood that the method of the present application can also be applied to other database processing languages, and the present application is not limited thereto.
[0041] In one embodiment, when the intelligent interaction language is SQL language, the first request may be a writing request for SQL language. The SQL writing request provides SQL for developers to implement specified functions and assists in development. When the intelligent interaction and collaboration request is the first request, establishing the intelligent interaction and collaboration request includes: based on natural language, inputting the function data and target table of the intelligent interaction language to be generated; establishing the intelligent interaction and collaboration request according to the function data and the target table.
[0042] In one embodiment, the second request may be a diagnostic request for an existing SQL instruction, and the third request may be a tuning request for an existing SQL instruction. The diagnostic request diagnoses a certain SQL statement to check whether there are defects or analyze the reason for a certain new phenomenon (such as a long query time). The tuning request refers to proposing a feasible optimization plan for the content of the SQL diagnosis. When the intelligent interaction and collaboration request is the second request and / or the third request, establishing the intelligent interaction and collaboration request includes: selecting the intelligent interaction language file; determining the intelligent interaction language file for diagnosis or tuning; determining the target table corresponding to the intelligent interaction language file; establishing the intelligent interaction and collaboration request according to the intelligent interaction language file and the target table.
[0043] In S104, intelligent interaction language information is extracted from the intelligent interaction and collaboration request. Different data contents are extracted to generate intelligent interaction language information according to different processing requests.
[0044] In one embodiment, when the intelligent interaction and collaboration request is the first request, the function data is extracted from the intelligent interaction and collaboration request as the intelligent interaction language information. When the intelligent interaction and collaboration request is the first request, the function data of the natural language input above is used as the intelligent interaction language information.
[0045] In one embodiment, when the intelligent interaction and collaboration request is the second request and / or the third request, the intelligent interaction language file is extracted from the intelligent interaction and collaboration request as the intelligent interaction language information. When the intelligent interaction and collaboration request is the second request and / or the third request, the selected SQL statement above is used as the intelligent interaction language information.
[0046] In S106, obtain the table structure information related to the intelligent interaction collaboration request. The target table can be extracted from the intelligent interaction collaboration request; obtain the table name, table field information, type information, index information, and storage engine information corresponding to the target table.
[0047] In a specific embodiment, the table structure information involved in the SQL can be extracted, such as the table name, table field information, type information, index information, storage engine information, etc.
[0048] Furthermore, developers can freely formulate a specific extraction scheme for the table structure information. Taking MYSQL as an example, developers can, for example, specify using the desc command to obtain the table structure information, and developers can, for example, specify using the show create table command to obtain the table structure information.
[0049] In S108, encrypt the intelligent interaction language information and the table structure information to generate a collaborative processing problem. The table structure information can be decomposed to generate elements; based on the mapping dictionary, perform name mapping on the intelligent interaction language information and the elements for encryption; generate the collaborative processing problem through the encryption result.
[0050] In one embodiment, for example, determine a problem template according to the intelligent interaction collaboration request; fill the encryption result into the problem template to generate the collaborative processing problem.
[0051] In S110, input the collaborative processing problem into a large language model to generate response information. Input the collaborative processing problem into the large language model generated by GPT. In this application, the large language model can specifically be ChatGPT (Chat Generative Pre-trained Transformer).
[0052] In S112, decrypt and display the response information to achieve information - secure interaction. Decrypt the response information through the mapping dictionary; display the decryption result on the user side.
[0053] In one embodiment, for example, display the decryption result in the form of chat language on the platform page.
[0054] Figure 2 The schematic diagram describes the encryption - decryption process. As Figure 2 described, the intelligent interaction collaboration request of the user can be encrypted through a dedicated encryption - decryption algorithm service and then sent to the large language model server. After the large language model generates the response information, it is decrypted through the encryption - decryption algorithm service and then displayed on the user side.
[0055] In this application, the encryption and decryption algorithm service can be set on the user side or on the server side. The large language model can be set on the server side or on a third-party platform. Since the data transmitted to the large language model is encrypted data, data security can be guaranteed and the problem of data leakage will not occur.
[0056] According to the information security intelligent interaction and collaboration method based on a large language model of the present application, by establishing an intelligent interaction and collaboration request, the intelligent interaction and collaboration request is: a first request and / or a second request and / or a third request; extracting intelligent interaction language information from the intelligent interaction and collaboration request; obtaining table structure information related to the intelligent interaction and collaboration request; encrypting the intelligent interaction language information and the table structure information to generate a collaborative processing problem; inputting the collaborative processing problem into the large language model to generate a response information; decrypting and displaying the response information to achieve information security interaction, which can automatically generate, diagnose, and optimize intelligent interaction languages, assist developers in writing high-quality intelligent interaction language files, quickly analyze existing intelligent interaction languages and propose optimization solutions, improve database performance, and avoid data leakage.
[0057] It should be clearly understood that the present application describes how to form and use specific examples, but the principles of the present application are not limited to any details of these examples. Instead, based on the teachings of the content disclosed in the present application, these principles can be applied to many other embodiments.
[0058] Figure 3 It is a flowchart of an information security intelligent interaction and collaboration method based on a large language model shown according to another exemplary embodiment. Figure 3 The shown process 30 is for Figure 1 a detailed description of S108 "encrypting the intelligent interaction language information and the table structure information to generate a collaborative processing problem" in the shown process.
[0059] As Figure 3 shown, in S302, a mapping dictionary is generated through the multiple elements and their corresponding mapping names. For example, all table structure information in the database can be extracted; all table structure information is decomposed to generate multiple elements; mapping names are respectively assigned to the multiple elements; and the mapping dictionary is generated through the multiple elements and their corresponding mapping names.
[0060] The encryption and decryption algorithm in the present application mainly performs name mapping, that is, the table structure remains unchanged, but the specific use of the table is hidden through mapping, that is, the business attributes and functional attributes in the data are blurred, and only its structural attributes are retained.
[0061] First, the corresponding relationship between elements and their mapping names is generated from all table structure information in the database to generate a mapping dictionary.
[0062] In S304, the table structure information is decomposed to generate elements. The key elements in the table structure information are decomposed into table names, field names, index names, field remarks, table remarks, etc.
[0063] In S306, based on the mapping dictionary, name mapping is performed on the intelligent interaction language information and the elements for encryption. The mapping relationship is obtained from the mapping dictionary to map and encrypt SQL statements and table structures.
[0064] More specifically, name mapping can be performed on each element, and it can be mapped to a name without business meaning.
[0065] For example, the table name: student can be mapped to table_name;
[0066] The field name is mapped to column1, column2...
[0067] The index name is mapped to idx1, idx2...
[0068] For some elements with business information but not affecting the generation of responses by the large language model, they can be directly hidden or replaced. For example, field remarks or table remarks can be hidden or replaced with information without business meaning.
[0069] In S308, the collaborative processing problem is generated through the encryption result.
[0070] In S310, the problem template is determined according to the intelligent interaction collaboration request. Problem templates corresponding to different intelligent interaction collaboration requests can be generated.
[0071] In one embodiment, the problem template corresponding to the first request can be, for example:
[0072] "Generate the SQL language corresponding to A and C";
[0073] Wherein, A can be the intelligent interaction language information corresponding to the first request, and C can be the data table structure.
[0074] In one embodiment, the problem template corresponding to the second request can be, for example:
[0075] "Track and diagnose the SQL language related to B in the database and return the corresponding problems";
[0076] Wherein, B can be the intelligent interaction language information corresponding to the second request, and C can be the data table structure.
[0077] In S312, the encrypted result is filled into the problem template to generate the collaborative processing problem. The intelligent interaction language information and the data table structure are respectively encrypted, and the encrypted data is filled into positions A, B, and C, thereby generating a problem template.
[0078] Figure 4 It is a flowchart of an information security intelligent interaction collaboration method based on a large language model shown according to another exemplary embodiment. Figure 4 The process 40 shown is a detailed description of Figure 1 the process shown.
[0079] As Figure 4 shown, in S402, right-click on the blank space in the SQL file and select "Generate Instruction". Right-click on the blank space in the SQL file, and in the pop-up input window, enter the specific requirements for the SQL that needs to be written by AI.
[0080] In S402, enter the specific requirements for the SQL statement to be generated in natural language in the pop-up input box.
[0081] In S406, select the SQL statement, right-click, and select "Diagnostic Instruction" or "Optimization Instruction". Select the SQL statement in the SQL file that needs to be diagnosed or optimized, right-click, and select the SQL diagnosis or SQL optimization menu in the pop-up menu list.
[0082] In S408, extract the table structure information.
[0083] In S410, the table structure information and the SQL data are desensitized and / or encrypted. Developers can freely choose whether to desensitize the data and can customize more flexible desensitization methods.
[0084] Encrypt the table structure and SQL statement in the user's request content. Considering that the AI service provider may be an external institution, directly sending internal information such as the table structure and SQL statement to a third party may pose a risk of data leakage. To protect data security, the table structure and SQL need to be encrypted.
[0085] In S412, generate a collaborative processing problem.
[0086] In S414, call the large language model to obtain the response information. Send the encrypted request content to the large language model server, and the large language model server makes a response to the specific request.
[0087] In one embodiment, the GPT model can be selected as the large language model service. The large language model can perform SQL writing, SQL diagnosis, and SQL tuning. For SQL writing, specific SQL statements do not need to be given, but text descriptions need to be provided for the large language model to generate specific SQL. For SQL diagnosis and SQL tuning, specific SQL statements need to be given to facilitate the large language model to give diagnosis results and tuning suggestions.
[0088] In practical applications, developers can freely choose different large language model services provided internally or externally.
[0089] In S416, the response information is decrypted and displayed in the interaction window. Developers can freely choose the display method. In one embodiment, the IDEA chat plugin can be set to display the request content put forward by the developer and the response content of the large language model in a suitable format on the chat plugin page, facilitating developers to browse, use, and interact.
[0090] The intelligent interaction and collaboration method based on the large language model of the present application can greatly facilitate developers to develop high-quality SQL, diagnose existing SQL, discover potential problematic SQL in advance, and optimize it. Considering data security issues, the intelligent interaction and collaboration method based on the large language model of the present application also proposes a data encryption scheme for intelligent interaction language to achieve the protection of privacy data.
[0091] Those skilled in the art can understand that all or part of the steps to implement the above embodiments are realized as a computer program executed by the CPU. When the computer program is executed by the CPU, the above functions defined by the above method provided by the present application are executed. The program can be stored in a computer-readable storage medium, which can be a read-only memory, a disk, an optical disc, etc.
[0092] In addition, it should be noted that the above drawings are only schematic illustrations of the processes included in the method according to the exemplary embodiments of the present application, rather than for limiting purposes. It is easy to understand that the processes shown in the above drawings do not indicate or limit the time sequence of these processes. Additionally, it is also easy to understand that these processes can be executed synchronously or asynchronously in multiple modules, for example.
[0093] The following is an embodiment of the device of the present application, which can be used to execute the method embodiment of the present application. For details not disclosed in the device embodiment of the present application, please refer to the method embodiment of the present application.
[0094] Figure 5 is a block diagram of an information security intelligent interaction and collaboration device based on a large language model shown according to another exemplary embodiment. As Figure 5As shown, the intelligent interaction and collaboration device 50 based on the large language model includes: a request module 502, a language module 504,
[0095] The request module 502 is used to establish an intelligent interaction and collaboration request, and the intelligent interaction and collaboration request is: a first request and / or a second request and / or a third request;
[0096] When the intelligent interaction and collaboration request is the first request, the request module 502 is further used to establish an intelligent interaction language file; based on the function data and the target table of the intelligent interaction language to be generated from natural language input; establish the intelligent interaction and collaboration request according to the function data and the target table.
[0097] When the intelligent interaction and collaboration request is the second request and / or the third request, the request module 502 is further used to select an intelligent interaction language file; determine the intelligent interaction language file as diagnosis or optimization; determine the target table corresponding to the intelligent interaction language file; establish the intelligent interaction and collaboration request according to the intelligent interaction language file and the target table.
[0098] The language module 504 is used to extract intelligent interaction language information from the intelligent interaction and collaboration request; the language module 504 is further used to extract function data as the intelligent interaction language information from the intelligent interaction and collaboration request; the language module 504 is further used to extract the intelligent interaction language file as the intelligent interaction language information from the intelligent interaction and collaboration request.
[0099] The structure module 506 is used to obtain the table structure information related to the intelligent interaction and collaboration request; the structure module 506 is further used to extract the target table from the intelligent interaction and collaboration request; obtain the table name, table field information, type information, index information, and storage engine information corresponding to the target table.
[0100] The encryption module 508 is used to encrypt the intelligent interaction language information and the table structure information to generate a collaborative processing problem; the encryption module 508 is further used to decompose the table structure information to generate elements; perform name mapping on the intelligent interaction language information and the elements based on the mapping dictionary for encryption; generate the collaborative processing problem through the encryption result.
[0101] The response module 510 is used to input the collaborative processing problem into the large language model to generate response information;
[0102] The decryption module 512 is used to decrypt the response information and display it to achieve information - secure interaction. The decryption module 512 is further used to decrypt the response information through the mapping dictionary; display the decryption result on the user side.
[0103] The information security intelligent interaction and collaboration device based on a large language model according to the present application establishes an intelligent interaction and collaboration request, where the intelligent interaction and collaboration request is: a first request and / or a second request and / or a third request; extracts intelligent interaction language information from the intelligent interaction and collaboration request; obtains table structure information related to the intelligent interaction and collaboration request; encrypts the intelligent interaction language information and the table structure information to generate a collaborative processing problem; inputs the collaborative processing problem into the large language model to generate a response message; decrypts and displays the response message to achieve information security interaction. In this way, it can automatically generate, diagnose, and optimize intelligent interaction languages, assist developers in writing high-quality intelligent interaction language files, quickly analyze existing intelligent interaction languages, and propose optimization solutions, improving database performance and avoiding data leakage.
[0104] As Figure 6 shown, an embodiment of the present application provides an electronic device, including a processor 610, a communication interface 620, a memory 630, and a communication bus 640. Among them, the processor 610, the communication interface 620, and the memory 630 communicate with each other through the communication bus 640;
[0105] The memory 630 is used to store a computer program;
[0106] When the processor 610 executes the program stored on the memory 630, it implements the intelligent interaction and collaboration method based on the large language model in any of the above embodiments.
[0107] The communication interface 620 is used for communication between the above electronic device and other devices.
[0108] The memory 630 may include a random access memory 630 (Random Access Memory, abbreviated as RAM), or may also include a non-volatile memory 630 (non-volatile memory), such as at least one disk memory 630. Optionally, the memory 630 may also be at least one storage device located far from the aforementioned processor 610.
[0109] An embodiment of the present application provides a computer-readable storage medium storing one or more programs, which can be executed by one or more processors to implement the intelligent interaction and collaboration method based on a large language model in any of the above embodiments. For example, an intelligent interaction and collaboration request is established, and the intelligent interaction and collaboration request is: a first request and / or a second request and / or a third request; intelligent interaction language information is extracted from the intelligent interaction and collaboration request; table structure information related to the intelligent interaction and collaboration request is obtained; the intelligent interaction language information and the table structure information are encrypted to generate a collaborative processing problem; the collaborative processing problem is input into a large language model to generate response information; and the response information is decrypted and displayed to achieve secure information interaction.
[0110] The exemplary embodiments of the present application have been specifically illustrated and described above. It should be understood that the present application is not limited to the detailed structures, settings or implementation methods described herein; on the contrary, the present application is intended to cover various modifications and equivalent settings included within the spirit and scope of the appended claims.
Claims
1. An information security intelligent interaction method based on a large language model, characterized in that, Including: Establish an intelligent interaction collaboration request; Extract intelligent interaction language information from the intelligent interaction collaboration request; Obtain the table structure information corresponding to the intelligent interaction collaboration request; Encrypt the intelligent interaction language information and the table structure information through a mapping dictionary to generate a collaborative processing problem; Input the collaborative processing problem into a large language model to generate response information; Decrypt the response information and display it to achieve information - secure interaction.
2. The method according to claim 1, characterized in that, Encrypt the intelligent interaction language information and the table structure information to generate a collaborative processing problem, including: Decompose the table structure information to generate elements; Perform name mapping on the intelligent interaction language information and the elements based on the mapping dictionary for encryption; Generate the collaborative processing problem through the encryption result.
3. The method according to claim 2, wherein Also including: Extract all table structure information in the database; Decompose all table structure information to generate multiple elements; Assign mapping names to the multiple elements respectively; Generate the mapping dictionary through the multiple elements and their corresponding mapping names.
4. The method according to claim 2, wherein Generate the collaborative processing problem through the encryption result, including: Determine a problem template according to the intelligent interaction collaboration request; Fill the encryption result into the problem template to generate the collaborative processing problem.
5. The method according to claim 1, characterized in that, When the intelligent interaction collaboration request is a first request, establishing the intelligent interaction collaboration request includes: Based on natural language, input the functional data and the target table of the intelligent interaction language to be generated; Establish the intelligent interaction collaboration request according to the functional data and the target table.
6. The method according to claim 1, characterized in that, When the intelligent interaction collaboration request is a second request and / or a third request, establishing the intelligent interaction collaboration request includes: Select an intelligent interaction language file; Determine the intelligent interaction language file as for diagnosis or tuning; Determine the target table corresponding to the intelligent interaction language file; Establish the intelligent interaction collaboration request according to the intelligent interaction language file and the target table.
7. The method according to claim 1, wherein Extract intelligent interaction language information from the intelligent interaction collaboration request, including: Extract functional data from the intelligent interaction collaboration request as the intelligent interaction language information; or Extract the intelligent interaction language file from the intelligent interaction collaboration request as the intelligent interaction language information.
8. The method according to claim 1, wherein Obtain the table structure information corresponding to the intelligent interaction collaboration request, including: Extract the target table from the intelligent interaction collaboration request; Obtain the table name, table field information, type information, index information, storage engine information corresponding to the target table.
9. The method according to claim 1, characterized in that, Decrypt the response information and display it to achieve information - secure interaction, including: Decrypt the response information through the mapping dictionary; Display the decryption result on the user side to achieve information - secure interaction.
10. The method according to claim 9, wherein Display the decryption result on the user side to achieve information - secure interaction, including: Display the decryption result in the form of chat language on the platform page.
11. An information security intelligent interaction and collaboration device based on a large language model, characterized in that, Including: A request module for establishing an intelligent interaction collaboration request; A language module for extracting intelligent interaction language information from the intelligent interaction collaboration request; A structure module for obtaining the table structure information corresponding to the intelligent interaction collaboration request; An encryption module, configured to encrypt the intelligent interaction language information and the table structure information to generate a collaborative processing problem; A response module, configured to input the collaborative processing problem into a large language model to generate response information; A decryption module, configured to decrypt the response information and display it to achieve information security interaction.
12. An electronic device, characterized in that, Comprising: One or more processors; A storage device, configured to store one or more programs; When the one or more programs are executed by the one or more processors, the one or more processors implement the method according to any one of claims 1 to 10.
13. A computer-readable medium having a computer program stored thereon, characterized in that, When the program is executed by the processor, the method according to any one of claims 1 to 10 is implemented.