Baselevel data authority management method and system

Abstract

The invention relates to the technical field of data management and authority control, in particular to a basic-level data authority management method and system, and the method comprises the following steps: introducing four roles: a super administrator, a regional administrator, a data leader and a worker; the super administrator has global setting and supervision authority, including checking all ledgers and establishing department structures and roles; a region administrator manages data in a specified region and has a checking permission of a standing book in the region; the data leader is responsible for creating a machine account, distributing authority and monitoring data use conditions, and can authorize and adjust operation authority and field authority across departments; the base-level data authority management method and system have the beneficial effects that by introducing a role authority system and a large language model technology, the security, the high efficiency and the normalization of base-level data management are remarkably improved. The method not only ensures the integrity and accuracy of the data, but also improves the working efficiency through a flexible authorization mechanism.

Description

Technical Field

[0001] The present invention relates to the technical field of data management and authority control, and in particular to a basic data authority management method and system. Background Art

[0002] With the rapid development of information technology, grassroots data management plays a vital role in various fields. However, in the process of grassroots data management, how to ensure the security, efficiency and standardized use of data to meet the specific needs of grassroots social governance has become an urgent problem to be solved.

[0003] Traditional methods of grassroots data management often have many limitations, mainly including inflexible authority allocation, insufficiently strict data access control, and high risk of data leakage. For authority allocation, most systems currently manage user operation and data permissions through preset roles and permissions. This static authority allocation method has poor flexibility and is difficult to meet the complex and changeable authority requirements in grassroots data management. For data access control, traditional access control methods often rely on fixed rules or simple identity authentication and authorization, and are unable to cope with higher-level access control (such as data modification, deletion, etc.). This method affects the efficiency of data circulation and is difficult to cope with complex and changeable security threats. For data leakage, encryption, auditing and other technical means are currently used. These technical means reduce the risk of data leakage to a certain extent, but for grassroots data with huge amounts of data, encryption and auditing will affect system performance to a certain extent. In addition, auditing technology usually requires manual analysis to identify potential security threats. The above problems may not only lead to a waste of data resources, but also have a serious impact on grassroots social governance. Summary of the invention

[0004] The purpose of the present invention is to provide a grassroots data authority management method and system, which is applied to grassroots data management, aims to solve the problems existing in the prior art and meet the specific needs of grassroots social governance, so as to solve the problems raised in the above-mentioned background technology.

[0005] To achieve the above object, the present invention provides the following technical solution: a basic data rights management method, the method comprising the following steps:

[0006] Introducing four roles: super administrator, regional administrator, data leader, and staff;

[0007] The super administrator has global settings and supervision permissions, including viewing all ledgers and establishing department structures and roles;

[0008] The regional administrator manages the data in the designated area and has the authority to view the ledgers in the area;

[0009] Data leaders are responsible for creating ledgers, assigning permissions, and supervising data usage. They can authorize and adjust operation permissions and field permissions across departments.

[0010] Staff members have the operation permissions and field permissions assigned by data leaders;

[0011] Introduce large language model technology to automatically generate and optimize permission rules, conduct anomaly monitoring, and ensure data security.

[0012] Preferably, the method further comprises the following steps:

[0013] The super administrator creates the department structure and roles;

[0014] The data leader creates the ledger and obtains all operation permissions of the ledger by default. The first-level department to which they belong obtains all operation permissions and data permissions by default. The super administrator and the regional administrator of the area to which the ledger belongs obtain viewing permissions by default.

[0015] Data leaders allocate permissions, including authorization within the department and authorization across departments. For authorization across departments, it is necessary to verify whether the department has been authorized to avoid duplicate authorization;

[0016] The large language model predicts and recommends appropriate permission settings based on user behavior patterns, roles and responsibilities, and ledger attributes, reducing the workload of manual configuration.

[0017] Preferably, the specific steps of cross-departmental authorization include:

[0018] Before data leaders authorize cross-departmental work, they should verify whether the target department has been authorized;

[0019] If not authorized, the authorization is successful, and all data permissions are opened by default, which can be edited and adjusted later;

[0020] After successful authorization, if editing permissions are granted, the permission settings on the entire authorization chain will be updated synchronously. Once authorization is canceled, the entire authorization chain will be revoked.

[0021] Preferably, the specific steps of introducing the large language model technology for abnormal monitoring include:

[0022] The large language model continuously monitors user behavior and data access, including access frequency, access time, and accessed data types;

[0023] Once an abnormal situation is found, a risk assessment is conducted and abnormal handling measures are implemented based on the assessment results, such as canceling the abnormal user's permissions and immediately notifying the data leaders of the relevant departments;

[0024] Record detailed exception handling logs for subsequent auditing and tracing.

[0025] Preferably, a login user authority system is also included, which ensures:

[0026] Super administrators can make global settings, access all ledgers, and fully monitor data dynamics;

[0027] The regional administrator is responsible for supervising all ledgers within a specific area and ensuring the integrity and accuracy of the data within the area;

[0028] Data leaders have the ability to create new ledgers and authorize operations on authorized ledgers to achieve flexible data management;

[0029] Staff members operate the ledger according to existing authority to ensure the smooth progress of daily work;

[0030] Except for the creator of the ledger, all users must obtain corresponding authorization before filling in, exporting or approving operations to enhance data security and improve the standardization and efficiency of the workflow.

[0031] A basic data rights management system, the system comprising:

[0032] The super administrator module is used to set up and supervise the entire system globally, including viewing all ledgers and establishing department structures and roles;

[0033] The regional administrator module is used to manage data in a specified area and has the authority to view the ledgers in the area;

[0034] The data leadership module is responsible for creating ledgers, assigning permissions, and supervising data usage under the respective first-level departments. It has cross-departmental authorization functions and can flexibly select operation permissions. Field permissions are fully open by default and can be adjusted through editing;

[0035] The staff module, as a common user, has the operation permissions and field permissions assigned by the data leader;

[0036] The large language model auxiliary module uses deep learning algorithms to learn historical data access records and permission configuration information, automatically generate and optimize permission rules, predict and recommend appropriate permission settings, reduce manual configuration workload, and monitor abnormal behavior.

[0037] Preferably, the following modules are also included:

[0038] The authority allocation module includes the following: after the data leader creates a ledger, the corresponding authority is granted to the ledger creator, the first-level department to which it belongs, the super administrator, and the regional administrator by default;

[0039] The cross-department authorization verification module ensures that when cross-department authorization is made, if the target department has already been authorized, it cannot be authorized again;

[0040] In the permission adjustment synchronization module, any permission adjustment by the data leader will directly affect the entire authorization chain. Once the authorization of a department is revoked, the relevant authorization synchronization will become invalid.

[0041] Preferably, a login user authority system is also included, which includes:

[0042] The super administrator can make global settings, access all ledgers, and fully monitor data dynamics;

[0043] The regional administrator is responsible for overseeing all ledgers within a specific region to ensure data integrity and accuracy;

[0044] Data leaders have the ability to create new ledgers and authorize data to achieve flexible data management;

[0045] Staff members operate the ledger according to existing authority to ensure smooth progress of daily work;

[0046] All users must obtain corresponding authorization before performing specific operations to enhance data security and improve the standardization and efficiency of work processes.

[0047] Preferably, an authorization module is also included:

[0048] Data leaders perform authorization operations in the accounts they have permissions for, which are divided into department authorization and cross-department authorization;

[0049] When the department authorizes, the data leader grants his / her operation authority to all members of the first-level department, and the members automatically inherit the department's data authority;

[0050] When cross-department authorization is performed, the target department is checked to see if it has been authorized to avoid duplicate authorization, and flexible selection of operation permissions is allowed. Data permissions are fully open by default and can be adjusted through editing.

[0051] Use big language model technology to analyze ledger attributes and user behavior patterns, roles and responsibilities, predict and recommend appropriate permission settings, generate permission allocation plans, and after review and modification by data leaders, perform one-click authorization operations.

[0052] Preferably, it also includes an abnormality monitoring module and a processing module, which continuously monitor user behavior and data access through a large language model and identify abnormal behavior, including:

[0053] Monitor user access frequency, access time, and accessed data types;

[0054] Once an abnormal situation is found, risk assessment is carried out and abnormal handling measures are automatically executed, such as canceling the abnormal user's permissions and immediately notifying the data leaders of relevant departments;

[0055] Record detailed exception handling logs for subsequent auditing and tracing.

[0056] Compared with the prior art, the present invention has the following beneficial effects:

[0057] The grassroots data authority management method and system proposed in this invention significantly improve the security, efficiency and standardization of grassroots data management by introducing a role authority system and large language model technology. This method not only ensures the integrity and accuracy of the data, but also improves work efficiency through a flexible authorization mechanism. At the same time, the introduction of large language model technology makes authority allocation more scientific and intelligent, effectively prevents security risks, and provides strong technical support for grassroots social governance. BRIEF DESCRIPTION OF THE DRAWINGS

[0058] Figure 1 is a flow chart of the method of the present invention;

[0059] Figure 2 Authorization flow chart for the present invention;

[0060] Figure 3 This is the abnormal monitoring flow chart of the present invention. DETAILED DESCRIPTION

[0061] In order to make the purpose and technical solution of the present invention clearly and completely described, and the advantages more clearly understood, the embodiments of the present invention are further described in detail with reference to the accompanying drawings. It should be understood that the specific embodiments described herein are part of the embodiments of the present invention, rather than all of the embodiments, and are only used to explain the embodiments of the present invention, and are not used to limit the embodiments of the present invention. All other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0062] For example, see Figures 1 to 3 The present invention provides a technical solution: a basic data rights management method, the method comprising the following steps:

[0063] Applied to grassroots data management, it meets the specific needs of grassroots social governance and ensures the safe, efficient and standardized use of grassroots data. It is characterized in that four roles are introduced in this method: super administrator, regional administrator, data leader and staff. The super administrator has the authority to globally set and supervise the entire grassroots data management system, including the authority to view all ledgers, and can establish departmental structures and roles. The regional administrator manages the data in the specified area and has the authority to view the ledgers in the area. Under each first-level department, there is one and only one data leader, who is responsible for creating ledgers, assigning permissions and supervising data usage. The staff is an ordinary user in the grassroots data management system and has the operation permissions and field permissions assigned by the data leader.

[0064] According to the needs of the ledger task, the data leader can grant the ledger to anyone under the first-level department to which he belongs. The individual who obtains the permission automatically inherits the data permissions of the first-level department to which he belongs. At the same time, cross-departmental authorization can be performed to grant permissions to other departments. When cross-departmental authorization is performed, you can flexibly choose to grant operation permissions, and field permissions are fully open by default. After authorization is completed, operation permissions and field permissions can be adjusted through editing. Through the data leader of each department, the ledger can be authorized to each grassroots staff member.

[0065] In addition, data leaders can use advanced big language model technology in the authorization process, use the deep learning algorithm of the big language model, learn historical data access records and permission configuration information, and automatically generate and optimize permission rules. In this method, the big language model predicts and recommends appropriate permission settings based on the user's behavior patterns, roles and responsibilities, and the attributes of the corresponding ledger, reducing the authorization links of data leaders in various departments. The ledger creator can perform authorization with one click after fine-tuning the permission configuration plan, which can reduce the workload of manual configuration. At the same time, big model technology can also perform anomaly monitoring. Through deep learning, it analyzes user access behavior, such as access frequency, access time, access data type, etc., to identify abnormal behavior. For any abnormal user, the system will immediately revoke the person's authority and notify the data leader of the department while recording the abnormal log, thereby effectively preventing security risks.

[0066] As the highest decision-maker of authority management, any authority adjustment by the data leader will directly affect the entire authorization chain. Once the authorization of a department is revoked, all related authorizations will also become invalid.

[0067] The main steps of this method are as follows:

[0068] Step S1: Super administrator creates department structure

[0069] Step S2: Super administrator creates a role

[0070] Step S3: Data leader creates ledger

[0071] Step S4: The creator of the ledger obtains all operation permissions of the ledger by default, the first-level department to which it belongs obtains all operation permissions and data permissions by default, and the super administrator and the regional administrator of the area to which the ledger belongs obtain viewing permissions by default.

[0072] Step S5: Data leadership assigns permissions

[0073] Step S6: Cross-departmental authorization checks whether the department has been authorized. If it has been authorized, it cannot be authorized again and the authorization failure is displayed. If it has not been authorized, the authorization is successful.

[0074] Step S7: Large language model detects user behavior and assists data leaders in allocating authority

[0075] Step S8: The large language model performs anomaly detection and exception handling to prevent security issues

[0076] As a preferred implementation, this method designs a login user authority system to ensure data security and efficient management. In this system, user roles are divided into super administrators, regional administrators, data leaders, and staff, and each role is given a specific scope of authority. Super administrators can access all ledgers and fully monitor data dynamics. Regional administrators are responsible for supervising all ledgers in a specific area to ensure the integrity and accuracy of data in the area. Data leaders have the ability to create new ledgers and can authorize operations on authorized ledgers, which provides the possibility for flexible data management. Staff can operate ledgers according to existing permissions to ensure the smooth progress of daily work. In addition, except for the creator of the ledger, all other users must obtain corresponding authorization before filling, exporting or approving operations. This mechanism not only enhances data security, but also improves the standardization and efficiency of the workflow. Through such permission settings, this method ensures the orderly flow of information flow, and at the same time gives different roles appropriate permissions, which not only ensures data security, but also optimizes management processes.

[0077] As a preferred implementation, this method designs an authorization method that allows data leaders to perform authorization operations in the ledgers they have permissions to. Authorization is divided into department authorization and cross-department authorization. Department authorization means that the data leader can grant his operation permissions to all members of the first-level department to which he belongs, and the members automatically inherit the department data permissions. Cross-department authorization is to grant the department operation permissions and data permissions. The operation permissions can be flexibly selected. The data permissions are all authorized by default for the first time, and can be adjusted later. When the data leader edits the cross-department authorization, the permission settings on the entire authorization chain will be updated synchronously. Once the authorization is canceled, the entire authorization chain will be completely revoked. In addition, this method integrates advanced large language model technology, uses the deep learning algorithm of the large language model, learns historical data access records and permission configuration information, and automatically generates and optimizes permission rules. When authorizing, the data leader can use the large language model technology to analyze the ledger attributes and user behavior patterns, roles and responsibilities, predict and recommend appropriate permission settings, generate permission allocation plans, and the data leader reviews and modifies the plan, and can perform one-click authorization operations. The application of this technology can reduce the authorization links of data leaders in various departments in the middle and greatly reduce the workload of manual configuration. The specific steps are as follows:

[0078] Step A1: Data leader creates ledger

[0079] Step A2: The creator of the ledger obtains all operation permissions of the ledger by default, the first-level department to which it belongs obtains all operation permissions and data permissions by default, and the super administrator and the regional administrator of the area to which the ledger belongs obtain viewing permissions by default.

[0080] Step A3: Data leadership assigns authority

[0081] Step A4: If it is the department, the data leader grants operation permissions to the department personnel, and the department personnel inherit the department data permissions

[0082] Step A5: If it is cross-department authorization, check whether the department has been authorized. If it has been authorized, return authorization failure. If not, authorization is successful.

[0083] Step A6: After successful cross-department authorization, edit data permissions

[0084] Step A7: Ledger attribute analysis

[0085] Step A8: User behavior analysis

[0086] Step A9: Generate a permission allocation plan

[0087] Step A10: Data leader modifies and reviews the authority allocation plan

[0088] Step A11: One-click authorization

[0089] As a preferred implementation, this method introduces advanced large language model technology, which analyzes user access behaviors, such as access frequency, access time, accessed data types, etc. through deep learning, so as to identify abnormal behaviors and achieve efficient security monitoring. The large language model continuously monitors user behavior and data access. Once an abnormal situation occurs, a risk assessment will be conducted. Based on the assessment results, the system automatically executes exception handling measures, including revoking the permissions of abnormal users and immediately notifying the data leaders of relevant departments. Once the exception handling is completed, the system will record a detailed exception handling log. The specific steps are as follows:

[0090] Step B1: Large language model continuously monitors user behavior and data access

[0091] Step B2: If there is no abnormality, return to B1 to continue monitoring. If there is an abnormality, execute B3 to conduct risk assessment.

[0092] Step B3: Automated risk assessment

[0093] Step B4: Exception handling measures

[0094] Step B5: Record the exception handling log.

[0095] Embodiment 2, based on embodiment 1, proposes a basic data rights management system, the system comprising:

[0096] The super administrator module is used to set up and supervise the entire system globally, including viewing all ledgers and establishing department structures and roles;

[0097] The regional administrator module is used to manage data in a specified area and has the authority to view the ledgers in the area;

[0098] The data leadership module is responsible for creating ledgers, assigning permissions, and supervising data usage under the respective first-level departments. It has cross-departmental authorization functions and can flexibly select operation permissions. Field permissions are fully open by default and can be adjusted through editing;

[0099] The staff module, as a common user, has the operation permissions and field permissions assigned by the data leader;

[0100] The large language model auxiliary module uses deep learning algorithms to learn historical data access records and permission configuration information, automatically generate and optimize permission rules, predict and recommend appropriate permission settings, reduce manual configuration workload, and monitor abnormal behavior.

[0101] Also includes the following modules:

[0102] The authority allocation module includes the following: after the data leader creates a ledger, the corresponding authority is granted to the ledger creator, the first-level department to which it belongs, the super administrator, and the regional administrator by default;

[0103] The cross-department authorization verification module ensures that when cross-department authorization is made, if the target department has already been authorized, it cannot be authorized again;

[0104] In the permission adjustment synchronization module, any permission adjustment by the data leader will directly affect the entire authorization chain. Once the authorization of a department is revoked, the relevant authorization synchronization will become invalid.

[0105] It also includes a login user authority system, which includes:

[0106] The super administrator can make global settings, access all ledgers, and fully monitor data dynamics;

[0107] The regional administrator is responsible for overseeing all ledgers within a specific region to ensure data integrity and accuracy;

[0108] Data leaders have the ability to create new ledgers and authorize data to achieve flexible data management;

[0109] Staff members operate the ledger according to existing authority to ensure smooth progress of daily work;

[0110] All users must obtain corresponding authorization before performing specific operations to enhance data security and improve the standardization and efficiency of work processes.

[0111] Also includes authorization module:

[0112] Data leaders perform authorization operations in the accounts they have permissions for, which are divided into department authorization and cross-department authorization;

[0113] When the department authorizes, the data leader grants his / her operation authority to all members of the first-level department, and the members automatically inherit the department's data authority;

[0114] When cross-department authorization is performed, the target department is checked to see if it has been authorized to avoid duplicate authorization, and flexible selection of operation permissions is allowed. Data permissions are fully open by default and can be adjusted through editing.

[0115] Use big language model technology to analyze ledger attributes and user behavior patterns, roles and responsibilities, predict and recommend appropriate permission settings, generate permission allocation plans, and after review and modification by data leaders, perform one-click authorization operations.

[0116] It also includes anomaly monitoring and processing modules, which continuously monitor user behavior and data access through a large language model and identify abnormal behavior, including:

[0117] Monitor user access frequency, access time, and accessed data types;

[0118] Once an abnormal situation is found, risk assessment is carried out and abnormal handling measures are automatically executed, such as canceling the abnormal user's permissions and immediately notifying the data leaders of relevant departments;

[0119] Record detailed exception handling logs for subsequent auditing and tracing.

[0120] It aims to solve the problems of inflexible authority allocation, insufficiently strict data access control, and high risk of data leakage in grassroots data management. The method ensures the safe, efficient and standardized use of grassroots data by introducing four roles (super administrator, regional administrator, data leader and staff) and refined authority settings. After creating the ledger, the data leader obtains all operating permissions by default, and the first-level department, super administrator and regional administrator also obtain permissions accordingly. Data leaders can flexibly authorize across departments or within departments according to the requirements of ledger tasks, and use large language model technology to assist in authority allocation and abnormal monitoring to effectively prevent security risks. The method also designs a set of login user authority system to clarify the authority scope of each role, enhance data security and improve management efficiency. The present invention is applicable to data management needs in the process of digital transformation of grassroots social governance, and provides a safe and efficient authority management method for grassroots data management.

[0121] Although embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that various changes, modifications, substitutions and variations may be made to the embodiments without departing from the principles and spirit of the present invention, and that the scope of the present invention is defined by the appended claims and their equivalents.

Claims

1. A basic data rights management method, characterized by: The method comprises the following steps: Introducing four roles: super administrator, regional administrator, data leader, and staff; The super administrator has global settings and supervision permissions, including viewing all ledgers and establishing department structures and roles; The regional administrator manages the data in the designated area and has the authority to view the ledgers in the area; Data leaders are responsible for creating ledgers, assigning permissions, and supervising data usage. They can authorize and adjust operation permissions and field permissions across departments. Staff members have the operation permissions and field permissions assigned by data leaders; Introduce large language model technology to automatically generate and optimize permission rules, conduct anomaly monitoring, and ensure data security.

2. A grass-roots data rights management method according to claim 1, characterized in that: The following steps are also included: The super administrator creates the department structure and roles; The data leader creates the ledger and obtains all operation permissions of the ledger by default. The first-level department to which they belong obtains all operation permissions and data permissions by default. The super administrator and the regional administrator of the area to which the ledger belongs obtain viewing permissions by default. Data leaders allocate permissions, including authorization within the department and authorization across departments. For authorization across departments, it is necessary to verify whether the department has been authorized to avoid duplicate authorization; The large language model predicts and recommends appropriate permission settings based on user behavior patterns, roles and responsibilities, and ledger attributes, reducing the workload of manual configuration.

3. A grass-roots data rights management method according to claim 2, characterized in that: The specific steps for cross-departmental authorization include: Before data leaders authorize cross-departmental work, they should verify whether the target department has been authorized; If not authorized, the authorization is successful, and all data permissions are opened by default, which can be edited and adjusted later; After successful authorization, if editing permissions are granted, the permission settings on the entire authorization chain will be updated synchronously. Once authorization is canceled, the entire authorization chain will be revoked.

4. A grass-roots data rights management method according to claim 3, characterized in that: The specific steps of introducing large language model technology for anomaly monitoring include: The large language model continuously monitors user behavior and data access, including access frequency, access time, and accessed data types; Once an abnormal situation is found, a risk assessment is conducted and abnormal handling measures are implemented based on the assessment results, such as canceling the abnormal user's permissions and immediately notifying the data leaders of the relevant departments; Record detailed exception handling logs for subsequent auditing and tracing.

5. A grass-roots data rights management method according to claim 1, characterized in that: It also includes a login user permissions system that ensures: Super administrators can make global settings, access all ledgers, and fully monitor data dynamics; The regional administrator is responsible for supervising all ledgers within a specific area and ensuring the integrity and accuracy of the data within the area; Data leaders have the ability to create new ledgers and authorize operations on authorized ledgers to achieve flexible data management; Staff members operate the ledger according to existing authority to ensure the smooth progress of daily work; Except for the creator of the ledger, all users must obtain corresponding authorization before filling in, exporting or approving operations to enhance data security and improve the standardization and efficiency of the workflow.

6. A grassroots data rights management system according to the grassroots data rights management method according to any one of claims 1 to 5, characterized in that: The system comprises: The super administrator module is used to set up and supervise the entire system globally, including viewing all ledgers and establishing department structures and roles; The regional administrator module is used to manage data in a specified area and has the authority to view the ledgers in the area; The data leadership module is responsible for creating ledgers, assigning permissions, and supervising data usage under the respective first-level departments. It has cross-departmental authorization functions and can flexibly select operation permissions. Field permissions are fully open by default and can be adjusted through editing; The staff module, as a common user, has the operation permissions and field permissions assigned by the data leader; The large language model auxiliary module uses deep learning algorithms to learn historical data access records and permission configuration information, automatically generate and optimize permission rules, predict and recommend appropriate permission settings, reduce manual configuration workload, and monitor abnormal behavior.

7. A grass-roots data rights management system according to claim 6, characterized in that: Also includes the following modules: The authority allocation module includes the following: after the data leader creates a ledger, the corresponding authority is granted to the ledger creator, the first-level department to which it belongs, the super administrator, and the regional administrator by default; The cross-department authorization verification module ensures that when cross-department authorization is made, if the target department has been authorized, it cannot be authorized again; In the permission adjustment synchronization module, any permission adjustment by the data leader will directly affect the entire authorization chain. Once the authorization of a department is revoked, the relevant authorization synchronization will become invalid.

8. A grass-roots data rights management system according to claim 6, characterized in that: It also includes a login user authority system, which includes: The super administrator can make global settings, access all ledgers, and fully monitor data dynamics; The regional administrator is responsible for overseeing all ledgers within a specific region to ensure data integrity and accuracy; Data leaders have the ability to create new ledgers and authorize data to achieve flexible data management; Staff members operate the ledger according to existing authority to ensure smooth progress of daily work; All users must obtain corresponding authorization before performing specific operations to enhance data security and improve the standardization and efficiency of work processes.

9. A grass-roots data rights management system according to claim 6, characterized in that: Also includes authorization module: Data leaders perform authorization operations in the accounts they have permissions for, which are divided into department authorization and cross-department authorization; When the department authorizes, the data leader grants his / her operation authority to all members of the first-level department, and the members automatically inherit the department's data authority; When cross-department authorization is performed, the target department is checked to see if it has been authorized to avoid duplicate authorization, and flexible selection of operation permissions is allowed. Data permissions are fully open by default and can be adjusted through editing. Use big language model technology to analyze ledger attributes and user behavior patterns, roles and responsibilities, predict and recommend appropriate permission settings, generate permission allocation plans, and after review and modification by data leaders, perform one-click authorization operations.

10. A grass-roots data rights management system according to claim 6, characterized in that: It also includes anomaly monitoring and processing modules, which continuously monitor user behavior and data access through a large language model and identify abnormal behavior, including: Monitor user access frequency, access time, and accessed data types; Once an abnormal situation is found, risk assessment is carried out and abnormal handling measures are automatically executed, such as canceling the abnormal user's permissions and immediately notifying the data leaders of relevant departments; Record detailed exception handling logs for subsequent auditing and tracing.

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