Dynamic data verification method and device based on context awareness
By parsing the context information of the data verification request, dynamically obtaining the verification rules, and matching them in the verification rule registry, the problem of coupling between verification rules and business code is solved, enabling flexible data verification and reducing maintenance difficulty.
Patent Information
- Application Number
- CN202511766913.9
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2025-11-27
- Publication Date
- 2026-03-03
AI Technical Summary
Existing data validation technologies lack flexibility, with validation rules tightly coupled with business code, making them difficult to adapt to multiple context scenarios and maintain.
By receiving data verification requests, parsing the context information of the data object to be verified, dynamically obtaining matching verification rules, and performing rule matching and execution in the verification rule registry center, the verification rules are decoupled from the business code.
It improves the flexibility of verification, enabling dynamic selection of verification rules based on runtime context, reducing maintenance difficulty, and adapting to verification needs in different scenarios.
Smart Images
Figure CN121597544A_ABST
Abstract
Description
Technical Field
[0001] This disclosure relates to the field of data verification technology, and in particular to a context-aware dynamic data verification method and apparatus. Background Technology
[0002] Currently, in modern software development, data validation is a crucial step in ensuring data quality and system reliability. Data validation is the process of checking input or stored data to ensure that it conforms to specific standards or rules. The validation process involves multiple aspects, including but not limited to the data's format, type, range, uniqueness, and correlation with other data.
[0003] With the proliferation of microservice architectures and distributed systems, data typically originates from multiple sources (such as user input, internal databases, partner APIs, etc.), and each source may have different validation requirements for the same data fields. Furthermore, data privacy regulations (such as GDPR) require special handling of sensitive data, further increasing the complexity of validation logic.
[0004] However, existing data validation technologies suffer from at least the following drawbacks: lack of flexibility, meaning validation rules are tightly coupled with business code, requiring code modification and redeployment when business rules change; inability to adapt to multiple contexts, meaning the same data may require different validation rules in different contexts. For example, email formats must be strictly validated during user registration, while more lenient formats may be allowed when importing data internally. Existing technologies struggle to dynamically adjust validation rules based on contextual information such as data source and usage scenario; and maintenance difficulties, meaning that as business grows and validation rules increase and change, the scattered validation code becomes difficult to maintain.
[0005] Therefore, how to decouple data validation rules from business code, improve the flexibility of validation while reducing maintenance difficulty, is a technical problem that urgently needs to be solved. Summary of the Invention
[0006] To address the aforementioned technical issues, this disclosure provides a context-aware dynamic data verification method and apparatus.
[0007] A first aspect of this disclosure provides a context-aware dynamic data verification method, comprising:
[0008] Receive data verification request;
[0009] Parse the data verification request to obtain the data object to be verified and the corresponding verification context information of the data object to be verified.
[0010] The verification rules that match the data object to be verified are obtained by verifying the context information.
[0011] The validation rules are used to execute validation logic on the data objects to be validated, and the corresponding data validation results are obtained.
[0012] A second aspect of this disclosure provides a context-aware dynamic data verification apparatus, comprising:
[0013] The request receiving module is used to receive data verification requests;
[0014] The data parsing module is used to parse the data object to be verified and the corresponding verification context information from the data verification request.
[0015] The rule acquisition module is used to obtain the verification rules that match the data object to be verified by verifying the verification context information;
[0016] The verification execution module is used to execute verification logic on the data object to be verified according to the verification rules, and obtain the corresponding data verification results.
[0017] A third aspect of this disclosure provides an electronic device, including a processor and a memory:
[0018] The memory is used to store program code and transfer the program code to the processor; the processor is used to execute the context-aware dynamic data verification method of the first aspect above according to the instructions in the program code.
[0019] A fourth aspect of this disclosure provides a computer-readable storage medium for storing program code for executing the context-aware dynamic data verification method of the first aspect above.
[0020] The technical solution provided in this disclosure has the following advantages compared with the prior art:
[0021] This disclosure provides a context-aware dynamic data verification method and apparatus. The method involves receiving a data verification request; parsing the request to obtain the data object to be verified and the corresponding verification context information; obtaining verification rules matching the data object using the verification context information; and executing verification logic on the data object to be verified using the verification rules to obtain the corresponding data verification result. This decouples the verification rules from the business code, dynamically selects verification rules based on the runtime context, and allows the verification strategy to flexibly adapt to different scenarios, thereby improving verification flexibility while reducing maintenance difficulty. Attached Figure Description
[0022] The accompanying drawings, which are incorporated in and form a part of this specification, illustrate embodiments consistent with this disclosure and, together with the description, serve to explain the principles of this disclosure.
[0023] To more clearly illustrate the technical solutions in the embodiments of this disclosure or the prior art, the accompanying drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, for those skilled in the art, other drawings can be obtained based on these drawings without creative effort.
[0024] Figure 1 This is one of the flowcharts illustrating a context-aware dynamic data verification method provided in this disclosure.
[0025] Figure 2 This is a second schematic flowchart of a context-aware dynamic data verification method provided in this embodiment of the present disclosure;
[0026] Figure 3 This is a structural block diagram of the context-aware dynamic data verification device provided in the embodiments of this disclosure;
[0027] Figure 4 This is a structural block diagram of an electronic device provided in an embodiment of this disclosure;
[0028] Figure 5 This is a structural block diagram of a computer-readable storage medium provided in an embodiment of this disclosure. Detailed Implementation
[0029] To better understand the above-mentioned objectives, features, and advantages of this disclosure, the solutions disclosed herein will be further described below. It should be noted that, unless otherwise specified, the embodiments and features described herein can be combined with each other.
[0030] Numerous specific details are set forth in the following description in order to provide a full understanding of this disclosure, but this disclosure may also be implemented in other ways different from those described herein; obviously, the embodiments in the specification are only some, and not all, of the embodiments of this disclosure.
[0031] It should be understood that the steps described in the embodiments of this disclosure may be performed in different orders and / or in parallel. Furthermore, method embodiments may include additional steps and / or omit the steps shown. The scope of this disclosure is not limited in this respect.
[0032] It should be noted that, in this document, relational terms such as "first" and "second" are used merely to distinguish one entity or operation from another, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Furthermore, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Unless otherwise specified, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes the element.
[0033] It should be noted that the terms "a" and "a plurality of" used in this disclosure are illustrative rather than restrictive, and those skilled in the art should understand that, unless otherwise expressly indicated in the context, they should be understood as "one or more".
[0034] Existing data validation technologies typically result in tight coupling between validation rules and business code. When business rules change, code modification and redeployment are required. They also fail to adapt to multiple contexts, meaning the same data may require different validation rules in different contexts. For example, email addresses must be strictly validated during user registration, while a more lenient format may be allowed when importing data internally. Existing technologies struggle to dynamically adjust validation rules based on contextual information such as data source and usage scenario. Furthermore, maintenance is difficult; as business grows and validation rules increase and change, the scattered validation code becomes difficult to maintain. To address these issues, this disclosure provides a context-aware dynamic data validation method, which is described below with specific embodiments.
[0035] Figure 1 This is a flowchart illustrating a context-aware dynamic data verification method provided in this embodiment of the disclosure. The data verification method specifically includes the following steps:
[0036] Step 101: Receive data verification request.
[0037] In this embodiment of the invention, the data verification request can be in various formats, including but not limited to JSON, XML, etc. The method of receiving the data verification request can also be varied, and no further specific limitations are made here.
[0038] Step 102: Parse the data verification request to obtain the data object to be verified and the verification context information corresponding to the data object to be verified.
[0039] In this embodiment of the invention, by parsing the acquired data verification request, the data object to be verified and the verification context information corresponding to the data object to be verified in the data verification request are obtained.
[0040] Optionally, the type of the data object to be verified can take many forms, without further specific limitations here. The verification context information corresponding to the data object to be verified refers to the processing environment used to describe the data object to be verified.
[0041] Optionally, the verification context information may include one or more combinations of dimensions such as data source, privacy level, and user risk level.
[0042] For example, the data source refers to the origin of the data object to be verified, including but not limited to user web applications, mobile applications, internal databases, etc. Privacy level refers to the privacy level of the data object to be verified, including but not limited to public data, internal data, sensitive data, etc. User risk level refers to the potential risk level posed by the data object to be verified, including but not limited to low, medium, and high, used to dynamically adjust the verification strictness.
[0043] Optionally, depending on the actual business scenario, different combinations of dimensions can be customized to achieve an accurate description of the processing environment of the data object to be verified, thereby providing a basis for dynamic verification.
[0044] For example, the verification context information could be: (1) Data source: Web application; (2) Privacy level: Internal data; (3) Risk level: High. Alternatively, the verification context information could be: (1) Data source: Mobile application; (2) Privacy level: Public data; (3) Risk level: Low.
[0045] Optionally, when performing data validation, it is necessary to pass in both the data object to be validated and the validation context information of the data object to be validated, for subsequent matching of validation rules.
[0046] Optionally, the verification context information of the data object to be verified can be predefined. This verification context information is used to describe the processing environment of the data object to be verified, and then the corresponding data verification rules can be obtained based on the verification context information to achieve dynamic data verification.
[0047] Optionally, the verification context information of the data object to be verified can be added at any time to meet the dynamic data verification needs of various data objects to be verified, thereby improving the flexibility of verification.
[0048] Step 103: Obtain the verification rules that match the data object to be verified by verifying the context information.
[0049] Specifically, by dynamically obtaining validation rules that match the data object to be validated based on its validation context information, the accuracy of data validation can be improved. In other words, dynamically matching appropriate data validation rules to data in different processing environments is crucial for improving the accuracy of data validation.
[0050] Optionally, when the same data has different validation context information, that is, when the same data is in different processing environments, the required validation rules are different.
[0051] For example, for multi-channel user registration verification requirements, website registration environment type requires strict format verification rules; mobile registration environment type requires device fingerprint verification rules; partner import environment type requires data encryption verification rules.
[0052] Optionally, different validation rules apply to different validation contexts, that is, to different data processing environments, and the corresponding validation logic is also different.
[0053] Step 104: Execute the validation logic on the data object to be validated according to the validation rules to obtain the corresponding data validation results.
[0054] Specifically, the validation logic is executed on the data object to be validated according to the validation rules, and the corresponding data validation result is obtained by executing the validation logic in the order of the rules. If it passes, valid data is output; if it fails, error data is output.
[0055] This embodiment of the disclosure receives a data verification request; parses the data verification request to obtain the data object to be verified and the verification context information corresponding to the data object to be verified; obtains the verification rule matching the data object to be verified through the verification context information; and executes the verification logic on the data object to be verified using the verification rule to obtain the corresponding data verification result. Thus, the verification rule can be decoupled from the business code, and the verification rule can be dynamically selected according to the runtime context, so that the verification strategy can flexibly adapt to different scenarios.
[0056] Based on the above embodiments, Figure 2 This is a flowchart illustrating a context-aware dynamic data verification method provided in an embodiment of this disclosure. Figure 2 As shown, the data verification method specifically includes the following steps:
[0057] Step 201: Receive data verification request.
[0058] Step 202: Parse the data verification request to obtain the data object to be verified and the verification context information corresponding to the data object to be verified.
[0059] The technical principles of steps 201 and 202 above are the same as those of the corresponding steps in the previous embodiment, and will not be repeated here.
[0060] Step 203: Send the verification context information corresponding to the data object to be verified to the verification rule registry center; receive the verification rule returned by the verification rule registry center in response to the verification context information, the verification rule including the corresponding verification logic.
[0061] Specifically, the validation rule registry is the central hub for managing various validation rules, and it can be predefined. The validation rule registry includes multiple validation rules for data validation. Each validation rule includes rule description information, which may include one or more of the following: context description, rule identifier, rule description, validation logic, and error message. The validation rule registry enables dynamic matching of validation rules by associating them with the validation context conditions of the data object to be validated.
[0062] For example, the applicable conditions, or context description, define the contexts in which the validation rule applies, including conditions such as data source and privacy level. The rule identifier is the unique identifier for each validation rule. The rule description describes the purpose of each validation rule. The validation logic is the specific validation function that accepts field values and context as parameters and returns the validation result. The error message is the error message returned when validation fails.
[0063] Optionally, different verification rules can be composed of different rule descriptions. For example, the context description for verification rule one is: applicable data source is a web application; privacy level is internal data; risk level is high. The context description for verification rule two is: applicable data source is a mobile application; privacy level is internal data. The context description for verification rule three is: applicable risk level is high. The above are just some examples of verification rules, and are not listed individually.
[0064] Optionally, the step of receiving the verification rules returned by the verification rule registry center in response to the verification context information further includes: matching the context description of the rule description information of each verification rule in the verification rule registry center with the verification context information of the data object to be verified; when the match is consistent, obtaining the corresponding verification rule from the verification rule registry center.
[0065] Specifically, by matching the context description of the rule description information of each verification rule in the verification rule registry with the verification context information of the data object to be verified, the corresponding verification rule can be accurately obtained from the verification rule registry only when the match is consistent.
[0066] Optionally, when the verification context information of the data object to be verified is the same as the context description of the rule description information of the verification rule in the verification rule registry, it is considered that the context description of the rule description information of the verification rule matches the verification context information of the data object to be verified.
[0067] Specifically, there are several ways to implement matching. One method is to consider a match achieved when the context description of the rule description information of the validation rule matches every dimension of the validation context information of the data object to be validated.
[0068] For example, when the verification context information of the data object to be verified is: data source is a web application; privacy level is internal data; risk level is high, it can be matched with rules one and three as shown above. Specifically, the context description of verification rule one is: applicable data source is a web application; privacy level is internal data; risk level is high. The context description of verification rule three is: applicable risk level is high.
[0069] Optionally, regarding the data source dimension: if the rule defines an applicable set of data sources (not empty), then the data sources in the current context must be within that set; if the rule is not defined (an empty set), then all data sources are considered to be matched. The same applies to privacy level and risk level.
[0070] Optionally, the matching here is based on the set inclusion relationship of each dimension, and all dimensions must match simultaneously.
[0071] Step 204: Execute the validation logic on the data object to be validated according to the validation rules. Execute the validation logic in the order of rule execution. If it passes, output valid data; if it fails, output error data.
[0072] Specifically, the verification logic for each verification rule is pre-defined. After obtaining the verification rule corresponding to the data object to be verified, the corresponding verification logic is obtained, and then the verification logic is executed sequentially according to the rule execution order. If it passes, valid data is output; if it fails, error data is output, thus completing the data verification and obtaining the verification result.
[0073] This embodiment of the disclosure receives a data verification request; parses the data verification request to obtain the data object to be verified and the verification context information corresponding to the data object; sends the verification context information corresponding to the data object to be verified to the verification rule registration center; receives the verification rule returned by the verification rule registration center in response to the verification context information, the verification rule including the corresponding verification logic; and executes the verification logic on the data object to be verified using the verification rule to obtain the corresponding data verification result. Thus, the verification rule can be decoupled from the business code, and the verification rule can be dynamically selected according to the runtime context, so that the verification strategy can flexibly adapt to different scenarios.
[0074] Correspondingly, this application also provides a context-aware dynamic data verification device. Figure 3 This is a structural block diagram of a context-aware dynamic data verification device according to an embodiment of this application. Figure 3 As shown, a context-aware dynamic data verification device may include:
[0075] The request receiving module 301 is used to receive data verification requests;
[0076] The data parsing module 302 is used to parse the data verification request to obtain the data object to be verified and the verification context information corresponding to the data object to be verified.
[0077] The rule acquisition module 303 is used to acquire the verification rules that match the data object to be verified by means of the verification context information;
[0078] The verification execution module 304 is used to execute verification logic on the data object to be verified according to the verification rules, and obtain the corresponding data verification results.
[0079] In summary, this application achieves the following: receiving a data verification request; parsing the data verification request to obtain the data object to be verified and the corresponding verification context information; sending the verification context information corresponding to the data object to be verified to the verification rule registry; receiving the verification rules returned by the verification rule registry in response to the verification context information, wherein the verification rules include the corresponding verification logic; and executing the verification logic on the data object to be verified using the verification rules to obtain the corresponding data verification result. This decouples the verification rules from the business code and dynamically selects the verification rules based on the runtime context, enabling the verification strategy to flexibly adapt to different scenarios.
[0080] Those skilled in the art will clearly understand that, for the sake of convenience and brevity, the above-described division of functional units and modules is merely an example. In practical applications, the above functions can be assigned to different functional units and modules as needed, that is, the internal structure of the device can be divided into different functional units or modules to complete all or part of the functions described above. The functional units and modules in the embodiments can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated unit can be implemented in hardware or as a software functional unit. Furthermore, the specific names of the functional units and modules are only for easy differentiation and are not intended to limit the scope of protection of this application. The specific working process of the units and modules in the above system can be referred to the corresponding process in the foregoing method embodiments, and will not be repeated here.
[0081] This application also provides an electronic device 400, such as... Figure 4 As shown, it includes one or more processors 401, communication interface 402, memory 403 and communication bus 404, wherein the processor 401, communication interface 402 and memory 403 communicate with each other through communication bus 404.
[0082] Memory 403 is used to store computer programs;
[0083] When processor 401 executes the program stored in memory 403, it implements the steps of the aforementioned context-aware dynamic data verification method. For example, when processor 401 executes the program stored in memory 403, it implements the following steps:
[0084] Receive data verification request;
[0085] Parse the data verification request to obtain the data object to be verified and the corresponding verification context information of the data object to be verified.
[0086] The verification rules that match the data object to be verified are obtained by verifying the context information.
[0087] The validation rules are used to execute validation logic on the data objects to be validated, and the corresponding data validation results are obtained.
[0088] Processor 401 can be a general-purpose processor, including a central processing unit (CPU), a network processor (NP), etc.; it can also be a digital signal processor (DSP), an application-specific integrated circuit (ASIC), a field-programmable gate array (FPGA), or other programmable logic devices, discrete gate or transistor logic devices, or discrete hardware components.
[0089] Memory 403 may include mass storage for data or instructions. For example, and not limitingly, memory 403 may include a hard disk drive (HDD), a floppy disk drive, flash memory, optical disk, magneto-optical disk, magnetic tape, or a Universal Serial Bus (USB) drive, or a combination of two or more of these. Where suitable, memory 403 may include removable or non-removable (or fixed) media. In a particular embodiment, memory 403 is a non-volatile solid-state memory. In a particular embodiment, memory 403 includes read-only memory (ROM). Where suitable, the ROM may be a mask-programmed ROM, a programmable ROM (PROM), an erasable PROM (EPROM), an electrically erasable PROM (EEPROM), an electrically rewritable ROM (EAROM), or flash memory, or a combination of two or more of these.
[0090] Communication bus 404 includes hardware, software, or both, for coupling the aforementioned components together. For example, the bus may include an Accelerated Graphics Port (AGP) or other graphics bus, an Enhanced Industry Standard Architecture (EISA) bus, a Front Side Bus (FSB), HyperTransport (HT) interconnect, an Industry Standard Architecture (ISA) bus, an Infinite Bandwidth Interconnect, a Low Pin Count (LPC) bus, a memory bus, a Microchannel Architecture (MCA) bus, a Peripheral Component Interconnect (PCI) bus, a PCI-Express (PCI-X) bus, a Serial Advanced Technology Attachment (SATA) bus, a Video Electronics Standards Association Local (VLB) bus, or other suitable buses, or combinations of two or more of these. Where appropriate, the bus may include one or more buses. Although specific buses are described and illustrated in embodiments of this application, this application contemplates any suitable bus or interconnect.
[0091] This application also provides a computer-readable storage medium 500, such as... Figure 5As shown, a computer-readable storage medium 500 stores a computer program that, when executed by a processor, implements the steps of the aforementioned context-aware dynamic data verification method. For example, the computer program is configured to store program code 501, which is used to perform the following steps:
[0092] Receive data verification request;
[0093] Parse the data verification request to obtain the data object to be verified and the corresponding verification context information of the data object to be verified.
[0094] The verification rules that match the data object to be verified are obtained by verifying the context information.
[0095] The validation rules are used to execute validation logic on the data objects to be validated, and the corresponding data validation results are obtained.
[0096] If an integrated module / unit is implemented as a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, all or part of the processes in the methods of the above embodiments can also be implemented by a computer program instructing related hardware. The computer program can be stored in a computer-readable storage medium, and when executed by a processor, it can implement the steps of the various method embodiments described above. The computer program includes computer program code, which can be in the form of source code, object code, executable files, or certain intermediate forms. Computer-readable media can include: any entity or device capable of carrying computer program code, recording media, USB flash drives, portable hard drives, magnetic disks, optical disks, computer memory, read-only memory (ROM), random access memory (RAM), electrical carrier signals, telecommunication signals, and software distribution media, etc. Of course, there are other types of readable storage media, such as quantum memories, graphene memories, etc. It should be noted that the content contained in computer-readable media may be appropriately added to or subtracted from the requirements of legislation and patent practice in a jurisdiction. For example, in some jurisdictions, computer-readable media may not include electrical carrier signals and telecommunication signals, in accordance with legislation and patent practice.
[0097] The foregoing has described specific embodiments of this specification. Other embodiments are within the scope of the appended claims. In some cases, the actions or steps recited in the claims may be performed in a different order than that shown in the embodiments and may still achieve the desired result. Furthermore, the processes depicted in the drawings do not necessarily require the specific or sequential order shown to achieve the desired result. In some embodiments, multitasking and parallel processing are possible or may be advantageous.
[0098] While this application provides method operation steps as shown in the embodiments or flowcharts, more or fewer operation steps may be included based on conventional or non-inventive labor. The order of steps listed in the embodiments is merely one possible execution order among many and does not represent the only execution order. In actual device or client product execution, the method can be executed sequentially as shown in the embodiments or drawings, or in parallel (e.g., in a parallel processor or multi-threaded processing environment).
[0099] This application is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of this application. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, 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 apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, generate instructions for implementing the flowchart... Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.
[0100] This application uses specific embodiments to illustrate the principles and implementation methods of this application. The description of the above embodiments is only for the purpose of helping to understand the method and core ideas of this application. At the same time, for those skilled in the art, there will be changes in the specific implementation methods and application scope based on the ideas of this application. Therefore, the content of this specification should not be construed as a limitation of this application.
Claims
1. A context-aware dynamic data verification method, characterized in that, include: Receive data verification request; The data object to be verified and the verification context information corresponding to the data object to be verified are obtained by parsing the data verification request. The verification rules that match the data object to be verified are obtained through the verification context information; The verification logic is executed on the data object to be verified using the verification rules to obtain the corresponding data verification results.
2. The context-aware dynamic data verification method according to claim 1, characterized in that, The step of obtaining the verification rule matching the data object to be verified through the verification context information further includes: Send the verification context information corresponding to the data object to be verified to the verification rule registration center; The verification rule is received from the verification rule registration center in response to the verification context information. The verification rule includes the corresponding verification logic.
3. The context-aware dynamic data verification method according to claim 2, characterized in that, The step of receiving the verification rule returned by the verification rule registration center in response to the verification context information further includes: The context description of the rule description information of each verification rule in the verification rule registry is matched with the verification context information of the data object to be verified. When the match is consistent, the corresponding verification rule is obtained from the verification rule registry. The rule description information of the verification rule includes one or more of the following: context description, rule identifier, rule description, verification logic, error information, etc.
4. The context-aware dynamic data verification method according to claim 3, characterized in that, The step of matching the context description of the rule description information of each verification rule in the verification rule registration center with the verification context information of the data object to be verified, and obtaining the corresponding verification rule from the verification rule registration center when a match is found, further includes: When the verification context information of the data object to be verified is the same as the context description of the rule description information of the verification rule in the verification rule registry, it is considered that the context description of the rule description information of the verification rule matches the verification context information of the data object to be verified.
5. The context-aware dynamic data verification method according to claim 1, characterized in that, The step of performing verification logic on the data object to be verified using the verification rules to obtain the corresponding data verification result further includes: The verification logic is executed sequentially according to the rule execution order. If it passes, valid data is output; if it fails, error data is output.
6. The context-aware dynamic data verification method according to claim 1, characterized in that, The method further includes: predefining verification context information, which describes the processing environment of the data object to be verified, and includes one or more of the following: data source, privacy level, and user risk.
7. The context-aware dynamic data verification method according to claim 1, characterized in that, The method further includes: pre-defining a verification rule registration center, wherein the verification rule registration center includes multiple verification rules for data verification, each of the verification rules includes rule description information, and the rule description information of the verification rule includes one or more of the following: context description, rule identifier, rule description, verification logic, and error information.
8. A context-aware dynamic data verification device, characterized in that, include: The request receiving module is used to receive data verification requests; The data parsing module is used to parse the data verification request to obtain the data object to be verified and the verification context information corresponding to the data object to be verified. The rule acquisition module is used to acquire the verification rules that match the data object to be verified through the verification context information; The verification execution module is used to perform verification logic on the data object to be verified using the verification rules, and obtain the corresponding data verification results.
9. An electronic device, characterized in that, The device includes a memory and a processor: The memory is used to store program code and transmit the program code to the processor; The processor is configured to execute the context-aware dynamic data verification method according to any one of claims 1-7 according to the instructions in the program code.
10. A computer-readable storage medium, characterized in that, The computer-readable storage medium is used to store program code for executing the context-aware dynamic data verification method according to any one of claims 1-7.