Data processing method and device, equipment and storage medium

Abstract

The embodiment of the invention discloses a data processing method and device, equipment and a storage medium. The method comprises the steps of obtaining behavior data of a target object; performing feature extraction processing on the behavior data to obtain behavior features; performing permission allocation processing on the behavior characteristics through a permission allocation model to obtain pre-allocated permissions; the pre-distribution permission is used for representing the behavior permission owned by the target object. By adopting the method, the distribution efficiency of social application program permission distribution can be improved.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of Internet, and particularly relates to a data processing method and device, equipment and storage medium. BACKGROUND

[0002] At present, with the development of Internet technology, the frequency of using various social application programs for data processing is higher and higher. In the existing data processing technology, the management of permissions is usually based on preset rules or user roles. These traditional methods mostly rely on manual setting, which is not only time-consuming and laborious, but also has poor flexibility and cannot perform personalized permission allocation according to the specific behavior characteristics of users. In addition, the scalability of the traditional permission management system is poor, and when the behavior data volume is large or the behavior types are many, it is difficult to efficiently and accurately perform permission allocation, which can easily lead to permission configuration errors or security vulnerabilities. Therefore, the consumption of system resources is increased, and the permission configuration efficiency is reduced. SUMMARY

[0003] The embodiments of the present application provide a data processing method, device, equipment and storage medium, which can improve the allocation efficiency of social application program permission allocation.

[0004] The embodiments of the present application provide a data processing method, device, equipment and storage medium, which can improve the allocation efficiency of social application program permission allocation. The embodiments of the present application provide a data processing method, device, equipment and storage medium, which can improve the allocation efficiency of social application program permission allocation. The embodiments of the present application provide a data processing method, device, equipment and storage medium, which can improve the allocation efficiency of social application program permission allocation. The embodiments of the present application provide a data processing method, device, equipment and storage medium, which can improve the allocation efficiency of social application program permission allocation. The embodiments of the present application provide a data processing method, device, equipment and storage medium, which can improve the allocation efficiency of social application program permission allocation.

[0005] The embodiments of the present application provide a data processing method, device, equipment and storage medium, which can improve the allocation efficiency of social application program permission allocation. The embodiments of the present application provide a data processing method, device, equipment and storage medium, which can improve the allocation efficiency of social application program permission allocation. The embodiments of the present application provide a data processing method, device, equipment and storage medium, which can improve the allocation efficiency of social application program permission allocation. The embodiments of the present application provide a data processing method, device, equipment and storage medium, which can improve the allocation efficiency of social application program permission allocation. The embodiments of the present application provide a data processing method, device, equipment and storage medium, which can improve the allocation efficiency of social application program permission allocation.

[0006] The embodiments of the present application provide a data processing method, device, equipment and storage medium, which can improve the allocation efficiency of social application program permission allocation. The embodiments of the present application provide a data processing method, device, equipment and storage medium, which can improve the allocation efficiency of social application program permission allocation.

[0007] The permission allocation module is further configured to perform function permission allocation processing on the behavior feature through the permission allocation model to obtain function permissions, perform field permission allocation processing on the behavior feature through the permission allocation model to obtain field permissions, perform data permission allocation processing on the behavior feature through the permission allocation model to obtain data permissions, and perform main entity setting permission allocation processing on the behavior feature through the permission allocation model to obtain main entity setting permissions. The function permissions, the field permissions, the data permissions, and the main entity setting permissions are determined as the pre-allocated permissions.

[0008] The feature extraction module is further configured to perform noise filtering processing on the behavior data based on the obtained abnormal behavior rules to obtain filtered data, and extract a feature vector of the filtered data through a convolutional neural network to obtain the behavior feature.

[0009] The permission allocation module is further configured to optimize a model loss value by using a gradient descent algorithm to obtain an updated loss value, and adjust parameters of an initial permission model by using the updated loss value to obtain the permission allocation model.

[0010] The permission allocation module is further configured to perform primary permission allocation processing on the behavior feature through the permission allocation model to obtain primary allocation permissions, perform secondary permission allocation processing on the behavior feature through the permission allocation model to obtain secondary allocation permissions, and determine the primary allocation permissions and the secondary allocation permissions as the pre-allocated permissions.

[0011] In an aspect, the present application provides a computer device, comprising: a processor, a memory, and a network interface. The processor is connected to the memory and the network interface. The network interface is configured to provide a data communication function. The memory is configured to store a computer program. The processor is configured to call the computer program, so that the computer device executes the method in the embodiments of the present application.

[0012] In an aspect, the present application provides a computer readable storage medium, which stores a computer program. The computer program is suitable for being loaded by a processor and executed to execute the method in the embodiments of the present application.

[0013] In an aspect, the present application provides a computer program product or a computer program. The computer program product or the computer program comprises 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. The processor executes the computer instructions, so that the computer device executes the method in the embodiments of the present application.

[0014] This application embodiment obtains the behavioral data of the target object; performs feature extraction processing on the behavioral data to obtain behavioral features; performs permission allocation processing on the behavioral features through a permission allocation model to obtain pre-allocated permissions; the pre-allocated permissions are used to represent the behavioral permissions possessed by the target object.

[0015] This application obtains behavioral data of a target object; performs feature extraction processing on the behavioral data to obtain behavioral features; and applies a permission allocation model to the behavioral features to obtain pre-assigned permissions. These pre-assigned permissions represent the behavioral permissions possessed by the target object. Using this application can improve the efficiency of permission allocation in social applications. It enhances system security by granting different permissions to different objects, reducing the risk of unauthorized access. Furthermore, it reduces the workload of administrators and improves the efficiency and accuracy of permission management. Ultimately, it improves the user experience, allowing users to more easily obtain the necessary permissions. Attached Figure Description

[0016] To more clearly illustrate the technical solutions in the embodiments of this application or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0017] Figure 1 This is a schematic diagram of a network architecture provided in an embodiment of this application; Figure 2 This is a flowchart illustrating a data processing method provided in an embodiment of this application; Figure 3a This is a schematic diagram of an interface regarding function permissions provided in an embodiment of this application; Figure 3b This is a schematic diagram of an interface regarding field permissions provided in an embodiment of this application; Figure 3c This is a schematic diagram of an interface related to data permissions provided in an embodiment of this application; Figure 3d This is a schematic diagram of an interface for setting permissions for a main entity, provided in an embodiment of this application. Figure 4 This is a schematic diagram of the structure of a data processing device provided in an embodiment of this application; Figure 5 This is a schematic diagram of the structure of a computer device provided in an embodiment of this application. Detailed Implementation

[0018] The technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, and not all embodiments. Based on the embodiments of this application, all other embodiments obtained by those of ordinary skill in the art without creative effort are within the scope of protection of this application.

[0019] It is understood that in the specific implementation of this application, data related to objects or users (such as permission data) is involved. When the following embodiments of this application are applied to specific products or technologies, user permission or consent is required, and the collection, use and processing of related data must comply with the relevant laws, regulations and standards of the relevant regions.

[0020] The terms "first," "second," etc., in the specification, claims, and accompanying drawings of this application are used to distinguish different objects, not to describe a specific order. Furthermore, the terms "comprising" and "having," and any variations thereof, are intended to cover non-exclusive inclusion. For example, a process, method, system, product, or apparatus that includes a series of steps or units is not limited to the listed steps or units, but may optionally include steps or units not listed, or may optionally include other steps or units inherent to these processes, methods, products, or apparatuses.

[0021] In this document, the term "embodiment" means that a particular feature, structure, or characteristic described in connection with an embodiment may be included in at least one embodiment of this application. The appearance of this phrase in various places throughout the specification does not necessarily refer to the same embodiment, nor is it a separate or alternative embodiment mutually exclusive with other embodiments. It will be explicitly and implicitly understood by those skilled in the art that the embodiments described herein can be combined with other embodiments.

[0022] This application provides a video rendering scheme involving video encoding and decoding technology, and the specific process is illustrated in the following embodiments.

[0023] Please see Figure 1 , Figure 1This is a schematic diagram of a network architecture provided in an embodiment of this application. The network interaction architecture may include a server 100 and a terminal cluster. The terminal cluster may include terminal devices 200a, 200b, 200c, ..., 200n. Communication connections may exist between terminal devices in the cluster; for example, there is a communication connection between terminal devices 200a and 200b, and between terminal devices 200a and 200c. Simultaneously, any terminal device in the terminal cluster may have a communication connection with the server 100; for example, there is a communication connection between terminal device 200a and server 100. The communication connection method is not limited; it can be established directly or indirectly through wired communication, wireless communication, or other methods. This application does not impose any restrictions on this method.

[0024] It is understood that the methods provided in this application embodiment can be executed by computer devices, including but not limited to the aforementioned network nodes (which can be terminal devices or servers in this application embodiment). In this application embodiment, the server can be an independent physical server, a server cluster or distributed system composed of multiple physical servers, or a cloud server providing basic cloud computing services such as cloud databases, cloud services, cloud computing, cloud functions, cloud storage, network services, cloud communication, middleware services, domain name services, security services, CDN, and big data and artificial intelligence platforms. The terminal devices mentioned above can be electronic devices, including but not limited to mobile phones, tablets, desktop computers, laptops, PDAs, in-vehicle devices, augmented reality / virtual reality (AR / VR) devices, head-mounted displays, smart TVs, wearable devices, smart speakers, digital cameras, webcams, and other mobile internet devices (MIDs) with network access capabilities, or terminal devices in scenarios such as trains, ships, and flights. In this application embodiment, the terminal device may include a video client.

[0025] It is understood that the embodiments of this application can be applied to various scenarios, including but not limited to cloud technology, artificial intelligence, and smart transportation. The computer equipment mentioned in this application can be a server or terminal device (such as a social application client), or a system composed of a server and terminal devices.

[0026] It is understood that, in a specific embodiment, for example, when an application (such as a social application) needs to allocate permissions, the permission allocation method of this application can be used for permission allocation. Specifically, the permission allocation method of this application involves the following steps: A computer device can acquire behavioral data of a target object; the behavioral data is processed to extract features to obtain behavioral features; the behavioral features are then processed to allocate permissions using a permission allocation model to obtain pre-allocated permissions; the pre-allocated permissions represent the behavioral permissions possessed by the target object.

[0027] Further, please see Figure 2 , Figure 2 This is a flowchart illustrating a data processing method provided in an embodiment of this application. Figure 2 As shown, this method can be executed by a server, which can be configured to perform the above-mentioned actions. Figure 1 The server 100 shown is not limited here. For ease of understanding, this application embodiment uses the method executed by the server as an example for illustration. This data processing method may include at least the following steps S101-S104: Step S101: Obtain the behavior data of the target object.

[0028] Step S102: Perform feature extraction processing on the behavioral data to obtain behavioral features.

[0029] Specifically, the server can perform noise filtering on the acquired abnormal behavior rules to obtain filtered data; and extract the feature vector of the filtered data through a convolutional neural network to obtain behavioral features.

[0030] Step S103: The behavior features are processed by the permission allocation model to obtain pre-allocated permissions; the pre-allocated permissions are used to represent the behavior permissions that the target object has.

[0031] Specifically, the server can use a permission allocation model to allocate functional permissions to behavioral features, thereby obtaining functional permissions; use the same permission allocation model to allocate field permissions to behavioral features, thereby obtaining field permissions; use the same permission allocation model to allocate data permissions to behavioral features, thereby obtaining data permissions; use the same permission allocation model to allocate main entity setting permissions to behavioral features, thereby obtaining main entity setting permissions; and then determine the functional permissions, field permissions, data permissions, and main entity setting permissions as pre-allocated permissions.

[0032] Furthermore, the server can perform primary permission allocation processing on behavioral characteristics through the permission allocation model to obtain primary allocation permissions; perform secondary permission allocation processing on behavioral characteristics through the permission allocation model to obtain secondary allocation permissions; and determine the primary allocation permissions and the secondary allocation permissions as pre-allocated permissions.

[0033] For easier understanding, please refer to Figure 3a , Figure 3a This is a schematic diagram of an interface regarding function permissions provided in an embodiment of this application. For example... Figure 3a The diagram shown is a schematic representation of a function permission interface 31A provided in this application embodiment. This function permission interface 31A can display associated information about function permissions in the information display area 301A. For example, the company to which the target object corresponding to the function permission belongs, "XXX Group". Another example is the role corresponding to the target object (e.g., "General Manager"). Yet another example is the job category to which the target object belongs (e.g., manager, salesperson, production staff, or quality control staff). Furthermore, the function permission interface 31A can respond to trigger operations on the function permission control 302X, displaying the corresponding display content 303A. Specifically, the display content 303A corresponding to the function permission control 302X can include browsing permissions for corresponding purchase orders. Specifically, it can also be further subdivided into secondary menus such as "Supplier Management" and "Create Purchase Order".

[0034] For easier understanding, please refer to Figure 3b , Figure 3b This is a schematic diagram of an interface regarding field permissions provided in an embodiment of this application. For example... Figure 3b The diagram shown is a schematic representation of a field permission interface 32A provided in this embodiment of the application. The field permission interface 32A can display associated information about field permissions in the information display area 321A. For example, the target object corresponding to the field permission belongs to the company "XXX Group". Another example is the role corresponding to the target object (e.g., "General Manager"). Yet another example is the job category to which the target object belongs (e.g., manager, salesperson, production staff, or quality control personnel). Furthermore, the field permission interface 32A can respond to trigger operations on the field permission control 322X, displaying the corresponding display content 323A. Specifically, the display content 323A corresponding to the field permission control 322X can include different field information, such as supplier name, supplier category, address, source path, office phone number, and supplier level. In essence, field permissions can be seen as the target object's viewing permissions for that field. In short, for the target object, fields selected by the permission administrator who manages the permissions will be displayed, while fields not selected by the permission administrator will not be displayed.

[0035] For easier understanding, please refer to Figure 3c , Figure 3c This is a schematic diagram of an interface related to data permissions provided in an embodiment of this application. For example... Figure 3c The diagram shown is a schematic representation of a data permission interface 33A provided in this embodiment of the application. The data permission interface 33A can display associated information about data permissions in the information display area 331A. For example, the company to which the target object corresponding to the data permission belongs, such as "XXX Group". Another example is the role corresponding to the target object (e.g., "General Manager"). Yet another example is the job category to which the target object belongs (e.g., manager, salesperson, production staff, or quality control personnel). Furthermore, the data permission interface 33A can respond to trigger operations on the data permission control 332X, displaying the corresponding display content 333A. Specifically, the display content 333A corresponding to the function permission control 332X can include the corresponding browsing data permissions. Specifically, the computer device can select the data field and the filtering method. The filtering method can include equal to, greater than, less than, etc. Furthermore, in response to the input "filter value", the system responds to the "Add" control, completing the creation of a data permission rule. For example, if the "Purchase Unit Price" field in the "New Purchase Order" of the target object is filtered by "less than" and "100", then users with that role can only see data rows with purchase unit prices less than 100 in the purchase order list, while those greater than or equal to 100 will not be visible. As another example, if the "Purchaser" field in "New Purchase Order" is set to "equal to" and filtered by "Zhang San", then users with that role can only see purchase data initiated by "Zhang San" in "Purchase Management", while purchase orders created by other users will not be visible.

[0036] For easier understanding, please refer to Figure 3d , Figure 3d This is a schematic diagram of an interface for setting permissions for a main entity, provided in an embodiment of this application. For example... Figure 3dThe diagram shown is a schematic of a main entity setting permission interface 34A provided in an embodiment of this application. The main entity setting permission interface 34A can display associated information about the main entity setting permissions in the display information area 341A. For example, the company to which the target object corresponding to the main entity setting permission belongs, "XXX Group". Another example is the role corresponding to the target object (e.g., "General Manager"). Yet another example is the job category to which the target object belongs (e.g., manager, salesperson, production staff, or quality control staff). Furthermore, the main entity setting permission interface 34A can respond to a trigger operation on the main entity setting permission control 342X, displaying the corresponding display content 343A. Specifically, the display content 343A corresponding to the main entity setting permission control 342X can include settings for different aspects of the corresponding main entity (e.g., salary or attendance). For example, if the target object simultaneously works in multiple subsidiaries or different departments of a head office, the main entity setting permission for salary management can be set to a specific subsidiary or department for that target object. For example, if the target person works in multiple subsidiaries or different departments of a parent company, the main entity for attendance management can be configured to set permissions for that target person to specify which subsidiary or department.

[0037] The training process of the permission allocation model can be as follows: The server can obtain tag permission data and tag behavior data; obtain sample behavior data, perform feature extraction processing on the sample behavior data to obtain sample behavior features; input the sample behavior features into the initial permission model for permission allocation processing to obtain sample allocation permissions; generate model loss values ​​based on the sample allocation permissions and the tag permission data, and adjust the model parameters of the initial permission model based on the model loss values ​​to obtain the permission allocation model.

[0038] Furthermore, the server can use the gradient descent algorithm to optimize the model loss value and obtain an updated loss value; the updated loss value can then be used to adjust the parameters of the initial permission model to obtain a permission allocation model.

[0039] It is understood that, in the specific embodiments of this application, data such as permission-related data is involved. When the above and below embodiments of this application are applied to specific products or technologies, the collection and processing of related data should strictly comply with the requirements of relevant regional laws and regulations, obtain the informed consent or separate consent of the personal information subject (or have a legal basis), and carry out subsequent data use and processing within the scope of laws and regulations and the authorization of the personal information subject. When facial (or other biometric) recognition technology is involved, the collection, use, and processing of related data should comply with the requirements of relevant regional laws and regulations. Before collecting facial information, the information processing rules should be informed and the separate consent of the target object should be obtained (or have a legal basis). Facial information should be processed in strict accordance with the requirements of laws and regulations and personal information processing rules, and technical measures should be taken to ensure the security of related data.

[0040] This application obtains behavioral data of a target object; performs feature extraction processing on the behavioral data to obtain behavioral features; and applies a permission allocation model to the behavioral features to obtain pre-assigned permissions. These pre-assigned permissions represent the behavioral permissions possessed by the target object. Using this application can improve the efficiency of permission allocation in social applications. It enhances system security by granting different permissions to different objects, reducing the risk of unauthorized access. Furthermore, it reduces the workload of administrators and improves the efficiency and accuracy of permission management. Ultimately, it improves the user experience, allowing users to more easily obtain the necessary permissions.

[0041] Further, please see Figure 4 , Figure 4 This is a schematic diagram of the structure of a data processing apparatus provided in an embodiment of this application. The aforementioned data processing apparatus can be a computer program (including program code) running on a computer device; for example, the data processing apparatus is application software. This apparatus can be used to execute corresponding steps in the methods provided in the embodiments of this application. Figure 4 As shown, the data processing device 1 may include: a data acquisition module 11, a feature extraction module 12, and a permission allocation module 13.

[0042] Data acquisition module 11 is used to acquire behavioral data of the target object; Feature extraction module 12 is used to perform feature extraction processing on behavioral data to obtain behavioral features; The permission allocation module 13 is used to process the permission allocation of behavioral features through the permission allocation model to obtain pre-allocated permissions; the pre-allocated permissions are used to represent the behavioral permissions possessed by the target object.

[0043] The specific functional implementation methods of the data acquisition module 11, feature extraction module 12, and permission allocation module 13 can be found in the above description.Figure 2 Steps S101-S103 in the corresponding embodiment will not be described again here.

[0044] The permission allocation module 13 is also used to obtain tag permission data and tag behavior data; obtain sample behavior data, perform feature extraction processing on the sample behavior data to obtain sample behavior features; input the sample behavior features into the initial permission model for permission allocation processing to obtain sample allocation permissions; generate model loss values ​​based on sample allocation permissions and tag permission data, and adjust the model parameters of the initial permission model based on the model loss values ​​to obtain the permission allocation model.

[0045] The specific implementation of the permission allocation module 13 can be found in the above description. Figure 2 Step S103 in the corresponding embodiment will not be described again here.

[0046] The permission allocation module 13 is further used to perform functional permission allocation processing on behavioral features through the permission allocation model to obtain functional permissions; to perform field permission allocation processing on behavioral features through the permission allocation model to obtain field permissions; to perform data permission allocation processing on behavioral features through the permission allocation model to obtain data permissions; and to perform main entity setting permission allocation processing on behavioral features through the permission allocation model to obtain main entity setting permissions. The functional permissions, field permissions, data permissions, and main entity setting permissions are determined as pre-allocated permissions.

[0047] The specific implementation of the permission allocation module 13 can be found in the above description. Figure 2 Step S103 in the corresponding embodiment will not be described again here.

[0048] The feature extraction module 12 is also used to perform noise filtering on the behavior data based on the acquired abnormal behavior rules to obtain filtered data; and to extract the feature vector of the filtered data through a convolutional neural network to obtain behavior features.

[0049] The specific implementation of the feature extraction module 12 can be found in the above description. Figure 2 Step S102 in the corresponding embodiment will not be described again here.

[0050] The permission allocation module 13 is also used to optimize the model loss value using the gradient descent algorithm to obtain the updated loss value; and to adjust the parameters of the initial permission model using the updated loss value to obtain the permission allocation model.

[0051] The specific implementation of the permission allocation module 13 can be found in the above description. Figure 2 Step S103 in the corresponding embodiment will not be described again here.

[0052] The permission allocation module 13 is further used to perform primary permission allocation processing on the behavior features through the permission allocation model to obtain primary allocation permissions; to perform secondary permission allocation processing on the behavior features through the permission allocation model to obtain secondary allocation permissions; and to determine the primary allocation permissions and secondary allocation permissions as pre-allocated permissions.

[0053] The specific implementation of the permission allocation module 13 can be found in the above description. Figure 2 Step S103 in the corresponding embodiment will not be described again here.

[0054] Further, please see Figure 5 , Figure 5 This is a schematic diagram of the structure of a computer device provided in an embodiment of this application. Figure 5 As shown, the computer device 1000 may include: at least one processor 1001, such as a CPU; at least one network interface 1004; a user interface 1003; a memory 1005; and at least one communication bus 1002. The communication bus 1002 is used to enable communication between these components. The user interface 1003 may include a display screen and a keyboard. The network interface 1004 may optionally include a standard wired interface or a wireless interface (such as a Wi-Fi interface). The memory 1005 may be high-speed RAM or non-volatile memory, such as at least one disk drive. Optionally, the memory 1005 may also be at least one storage device located remotely from the aforementioned processor 1001. Figure 5 As shown, the memory 1005, which serves as a computer storage medium, may include an operating system, a network communication module, a user interface module, and a device control application program.

[0055] exist Figure 5 In the computer device 1000 shown, the network interface 1004 provides network communication functionality; the user interface 1003 is mainly used to provide an input interface for the user; and the processor 1001 can be used to call the device control application stored in the memory 1005 to achieve: Obtain behavioral data of the target object; perform feature extraction processing on the behavioral data to obtain behavioral features; perform permission allocation processing on the behavioral features through a permission allocation model to obtain pre-assigned permissions; the pre-assigned permissions are used to represent the behavioral permissions possessed by the target object.

[0056] It should be understood that the computer device 1000 described in the embodiments of this application can execute the foregoing text. Figure 2 The data processing method described in the embodiment corresponding to Figure 3 can also be executed as described above. Figure 4The description of the data processing device 1 in the corresponding embodiments will not be repeated here. Furthermore, the beneficial effects of using the same method will also not be repeated here.

[0057] This application also provides a computer-readable storage medium storing a computer program, the computer program including program instructions, which are implemented when executed by a processor. Figure 2 The data processing methods provided in each step of Figure 3 can be found in the above description. Figure 2 The implementation methods provided for each step in Figure 3 will not be repeated here. Furthermore, the beneficial effects of using the same method will also not be elaborated upon.

[0058] The aforementioned computer-readable storage medium can be an internal storage unit of the data processing apparatus or computer device provided in any of the foregoing embodiments, such as a hard disk or memory of the computer device. The computer-readable storage medium can also be an external storage device of the computer device, such as a plug-in hard disk, smart media card (SMC), secure digital (SD) card, flash card, etc., provided on the computer device. Furthermore, the computer-readable storage medium can include both internal storage units and external storage devices of the computer device. The computer-readable storage medium is used to store the computer program and other programs and data required by the computer device. The computer-readable storage medium can also be used to temporarily store data that has been output or will be output.

[0059] This application 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 aforementioned... Figure 2 The description of the data processing method in the embodiment corresponding to Figure 3 will not be repeated here. Furthermore, the beneficial effects of using the same method will also not be repeated here.

[0060] The term "comprising," and any variations thereof, in the specification, claims, and drawings of this application are intended to cover non-exclusive inclusion. For example, a process, method, apparatus, product, or device that includes a series of steps or units is not limited to the steps or modules listed, but may optionally include steps or modules not listed, or may optionally include other steps or units inherent to such processes, methods, apparatus, products, or devices.

[0061] Those skilled in the art will recognize that the units and algorithm steps of the various examples described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, computer software, or a combination of both. To clearly illustrate the interchangeability of hardware and software, the components and steps of the various examples have been generally described in terms of functionality in the foregoing description. Whether these functions are implemented in hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementations should not be considered beyond the scope of this application.

[0062] The methods and related apparatuses provided in this application are described with reference to the method flowcharts and / or structural diagrams provided in this application. Specifically, each block of the method flowchart and / or structural diagram, as well as combinations of blocks in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing device to create a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing device, generate instructions for implementing the process. Figure One A schematic diagram of one or more processes and / or structures. Figure One The computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing device to operate in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process Figure One A schematic diagram of one or more processes and / or structures. Figure One The functions specified in one or more boxes. These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable apparatus for implementing the process. Figure One A process or multiple processes and / or structures illustrate the steps of the functions specified in one or more boxes.

[0063] The above-disclosed embodiments are merely preferred embodiments of this application and should not be construed as limiting the scope of this application. Therefore, any equivalent variations made in accordance with the claims of this application shall still fall within the scope of this application.

Claims

1. A data processing method, characterized by, The method comprises: obtaining behavior data of a target object; performing feature extraction processing on the behavior data to obtain behavior features; performing permission allocation processing on the behavior features through a permission allocation model to obtain pre-allocated permissions; the pre-allocated permissions are used to represent the behavior permissions possessed by the target object.

2. The method of claim 1, wherein, Further comprising: obtaining label permission data and label behavior data; obtaining sample behavior data, performing feature extraction processing on the sample behavior data to obtain sample behavior features; inputting the sample behavior features into an initial permission model to perform permission allocation processing, to obtain sample allocated permissions; generating a model loss value according to the sample allocated permissions and the label permission data, adjusting model parameters of the initial permission model according to the model loss value, to obtain a permission allocation model.

3. The method of claim 1, wherein, The permission allocation processing on the behavior features through the permission allocation model to obtain pre-allocated permissions comprises: performing function permission allocation processing on the behavior features through the permission allocation model to obtain function permissions; performing field permission allocation processing on the behavior features through the permission allocation model to obtain field permissions; performing data permission allocation processing on the behavior features through the permission allocation model to obtain data permissions; performing main entity setting permission allocation processing on the behavior features through the permission allocation model to obtain main entity setting permissions; determining the function permissions, the field permissions, the data permissions, and the main entity setting permissions as the pre-allocated permissions.

4. The data processing method of claim 1, wherein, The feature extraction processing on the behavior data to obtain behavior features comprises: performing noise filtering processing on the behavior data based on obtained abnormal behavior rules to obtain filtered data; extracting a feature vector of the filtered data through a convolutional neural network to obtain behavior features.

5. The data processing method according to claim 2, characterized in that, Further comprising: optimizing a model loss value using a gradient descent algorithm to obtain an updated loss value; adjusting parameters of the initial permission model using the updated loss value to obtain a permission allocation model.

6. The data processing method of claim 1, wherein, The permission allocation processing on the behavior features through the permission allocation model to obtain pre-allocated permissions comprises: performing primary permission allocation processing on the behavior features through the permission allocation model to obtain primary allocated permissions; performing secondary permission allocation processing on the behavior features through the permission allocation model to obtain secondary allocated permissions; determining the primary allocated permissions and the secondary allocated permissions as the pre-allocated permissions.

7. A data processing apparatus, characterized by, The data processing apparatus comprises: a data acquisition module configured to obtain behavior data of a target object; a feature extraction module configured to perform feature extraction processing on the behavior data to obtain behavior features; a permission allocation module configured to perform permission allocation processing on the behavior features through a permission allocation model to obtain pre-allocated permissions; the pre-allocated permissions are used to represent the behavior permissions possessed by the target object.

8. A computer device, comprising: The apparatus comprises: a processor, a memory, and a network interface; the processor is connected with the memory and the network interface, wherein the network interface is configured to provide data communication function, the memory is configured to store computer programs, and the processor is configured to call the computer programs to enable the computer device to execute the method according to any one of claims 1-6.

9. A computer-readable storage medium, characterized in that, The computer program is stored in the computer readable storage medium and is adapted to be loaded and executed by the processor to enable the computer device having the processor to perform the method of any one of claims 1-6.

10. A computer program product, characterised in that, The computer program product comprises the computer program stored in the computer readable storage medium and adapted to be read and executed by the processor to enable the computer device having the processor to perform the steps of the data processing method of any one of claims 1-6.

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