Tenant identification method for multi-system

Abstract

This application relates to the fields of system integration and data mining technology, and provides a method for tenant identification in multiple systems. The method includes: receiving a first business request from a target tenant; intercepting the first business request through an integrated interceptor; and identifying the tenant identity of the first business request according to a preset tenant identification rule embedded in the integrated interceptor. If the identification is successful, the first business request is allowed to continue processing. This achieves the goal of intercepting business requests through an integrated interceptor, reducing the need to develop interceptors for each system, ensuring unified identification of tenant information, and improving the efficiency and accuracy of tenant identification across multiple systems.

Description

Technical Field

[0001] This application relates to the fields of system integration and data mining technology, and in particular to a tenant identification method for multi-system systems. Background Technology

[0002] With the rapid development of information technology and the diversification of business operations, multi-system environments have become the norm for enterprise operations. Traditional tenant identification methods often rely on simple username / password verification or static tenant identifiers, which may be sufficient in a single-system or small multi-system environment, but become inadequate in large or complex multi-system environments. As business operations continue to expand and data volumes explode, the limitations of this traditional method become increasingly apparent, such as insufficient security, management difficulties, and difficulty in tracking.

[0003] Against this backdrop, a tenant identification method for multiple systems has emerged, aiming to intercept business requests by integrating interceptors, thereby avoiding the need to develop separate interceptors for each system and solving the technical problems of the inability to uniformly identify tenant information and the low efficiency and accuracy of tenant identification across multiple systems. Summary of the Invention

[0004] This application provides a tenant identification method for multiple systems, which aims to intercept business requests by integrating interceptors, thereby avoiding the need to develop separate interceptors for each system and solving the technical problems of inconsistent tenant information identification and low efficiency and accuracy of tenant identification across multiple systems.

[0005] In view of the above problems, this application provides a tenant identification method for multiple systems.

[0006] The first aspect disclosed in this application provides a tenant identification method for multiple systems, the method comprising: receiving a first service request from a target tenant; intercepting the first service request through an integrated interceptor, and identifying the tenant identity of the first service request according to a preset tenant identification rule, the preset tenant identification rule being embedded in the integrated interceptor; if the identification is successful, allowing the first service request to continue processing.

[0007] Another aspect of this application discloses a tenant identification system for multiple systems, the system being used in the above-described method, the system comprising: a receiving module 1, the receiving module 1 being used to receive a first service request from a target tenant; an identity identification module 2, the identity identification module 2 being used to intercept the first service request through an integrated interceptor, and to identify the tenant identity of the first service request according to a preset tenant identification rule, the preset tenant identification rule being embedded in the integrated interceptor; and an identification judgment module 3, the identification judgment module 3 being used to allow the first service request to continue processing if the identification is successful.

[0008] One or more technical solutions provided in this application have at least the following technical effects or advantages:

[0009] The aforementioned tenant identification method for multiple systems operates in a multi-system environment. When a target tenant sends a business request, the system first intercepts it through an integrated interceptor. This interceptor has a set of preset tenant identification rules used to identify the tenant's identity. If the request matches the preset identification rules, the system will continue processing the request. This ensures both processing efficiency and data security and accuracy. In summary, this method intercepts business requests through an integrated interceptor, reducing the need to develop interceptors for each system, ensuring unified identification of tenant information, and improving the efficiency and accuracy of tenant identification across multiple systems.

[0010] The above description is merely an overview of the technical solution of this application. In order to better understand the technical means of this application and to implement it in accordance with the contents of the specification, and to make the above and other objects, features and advantages of this application more obvious and understandable, specific embodiments of this application are given below. Attached Figure Description

[0011] To more clearly illustrate the technical solutions in the embodiments of the present invention, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0012] Figure 1 This is a flowchart illustrating a tenant identification method for multiple systems in one embodiment;

[0013] Figure 2 This is a schematic diagram illustrating the tenant identity recognition process in a tenant identification method for multiple systems, as shown in one embodiment.

[0014] Figure 3 This is a system architecture diagram for a tenant identification method for multiple systems in one embodiment.

[0015] Explanation of reference numerals in the attached diagram: Receive module 1, Identity recognition module 2, Identification and judgment module 3. Detailed Implementation

[0016] This application provides a multi-label arrhythmia discrimination method based on a multi-scale neural network model, which solves the technical problems of classification difficulties caused by the nonlinearity and complexity of arrhythmia signals, as well as low classification accuracy and prediction accuracy.

[0017] 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 a part of the embodiments of this application, and not all of them. All other embodiments obtained by those skilled in the art based on the embodiments of this application without creative effort are within the scope of protection of this application.

[0018] It should be noted that the terms "comprising" and "having," and any variations thereof, are intended to cover non-exclusive inclusion. For example, a process, method, system, product, or server that includes a series of steps or units is not necessarily limited to those steps or units that are explicitly listed, but may include other steps or modules that are not explicitly listed or that are inherent to such process, method, product, or device.

[0019] Example 1

[0020] like Figure 1 As shown, this application provides a tenant identification method for multiple systems, the method comprising:

[0021] Receive the first business request from the target tenant;

[0022] With the rapid development of cloud computing technology, multi-tenancy technology has also been further improved and enhanced. Modern multi-tenant systems typically adopt a microservice architecture, where each tenant can have its own application instance while sharing some common services and infrastructure. This architecture allows each tenant to have greater flexibility and scalability, while also reducing maintenance costs and improving resource utilization.

[0023] In this embodiment, when multiple systems receive the first business request from a target tenant, quickly and accurately identifying the tenant's identity becomes crucial. The first business request refers to the first or specific business request sent by the target tenant. The system terminal collects and summarizes the first business requests sent by the target tenant to the multiple systems through the system interface, network requests, or other means. The received first business request data is then cleaned, handling missing values, outliers, and duplicate values. Missing values ​​are filled, deleted, or imputed using methods such as global constants or the mean. Outliers are identified using univariate scatter plots, and deletion or other processing is performed based on the actual situation. Duplicate values ​​are deleted or merged. The cleaned data is then JSON-ified for subsequent operations and transmission. Through the above processing, the integrity and security of tenant data are ensured, improving the efficiency and accuracy of tenant identification across multiple systems.

[0024] The first service request is intercepted by an integrated interceptor, and the tenant identity of the first service request is identified according to a preset tenant identification rule, which is embedded in the integrated interceptor.

[0025] In one embodiment, to ensure accurate identification and management of multiple system tenants, an integrated interceptor is used to intercept the first business request. The integrated interceptor is a component or tool used to intercept and process the first business request from the target tenant. The preset tenant identification rules are a set of preset rules or conditions used to identify and verify tenant identity. These rules are embedded in the integrated interceptor and are used to process the first business request from the target tenant. The system terminal first starts the integrated interceptor and puts it in a listening state, waiting to receive requests. When a first business request from the target tenant is received, the request is passed to the integrated interceptor for processing. After receiving the request, the integrated interceptor performs preliminary analysis and judgment. According to the preset tenant identification rules embedded in the interceptor, the request is intercepted, relevant information such as tenant number and tenant identifier is extracted, and this information is compared with the preset tenant identification rules. Based on the comparison result, the integrated interceptor determines whether the tenant identity in the request matches the preset rules. In this way, the system terminal can quickly and accurately determine the tenant identity of the request, ensuring data security and isolation, while improving the efficiency of tenant management. This approach simplifies the tenant identification process, avoids the need for each system to develop its own interceptors, and ensures that tenant information can be identified uniformly.

[0026] Furthermore, this application provides an integrated interceptor, and the method further includes:

[0027] The integrated interceptor includes at least an HTTP information acquisition interface, an RPC information acquisition interface, and a WebFlux information acquisition interface.

[0028] Preferably, the integrated interceptor is a powerful tool for multi-system tenant management. It includes at least three information retrieval interfaces: an HTTP information retrieval interface, an RPC information retrieval interface, and a WebFlux information retrieval interface. Each of these interfaces plays a crucial role. The HTTP information retrieval interface is specifically designed to handle HTTP requests, extracting key information such as tenant identifiers. Through this interface, the interceptor can gain a deeper understanding of the details of each request, thereby better performing tasks such as tenant authentication and permission checks. The RPC information retrieval interface is designed to handle requests based on the RPC protocol. RPC (Remote Procedure Call) is a technology that allows communication and data exchange between different processes or computers. This interface enables the integrated interceptor to handle requests from RPC, further extending its ability to handle different types of requests. The WebFlux information retrieval interface is for asynchronous web requests based on the Spring WebFlux framework. WebFlux is a module of the Spring framework that provides a reactive way to build web applications. Through this interface, the interceptor can easily handle asynchronous requests, improving the system's flexibility and scalability. In summary, the three interfaces of the integrated interceptor provide it with powerful information acquisition capabilities, enabling it to adapt to various types of tenant requests, thereby playing a key role in multi-system tenant management and improving the efficiency of multi-system tenant identification.

[0029] Furthermore, such as Figure 2 As shown, this application provides a method for identifying the tenant identity of the first service request according to a preset tenant identification rule, which further includes:

[0030] Based on the business-system database, the first business request is matched with the relevant system to obtain the matching associated system;

[0031] Optionally, the first business request is tenant-identified according to preset tenant identification rules. The business-system database refers to a database integrating various business and system information, containing various entities, relationships, and rules within the business domain, as well as related system information and attributes. Request system matching refers to the process of searching and determining the associated system matching the business requirement in the business-system database based on the business requirement and system attributes. The goal of this process is to ensure that each business request can be correctly routed to the most suitable system for processing it. The matched associated system refers to the specific system that matches and is selected for the first business request, including deposit systems, loan systems, and risk control systems. Specifically, the built-in rule name for the deposit system is "matching tenantCode" in HTTP requests; the built-in rule name for the loan system is "matching orgIdcom" in RPC requests; and the built-in rule name for the risk control system is "matching legal entity ID" in WebFlux requests. The system terminal's request system matching based on the business-system database is an intelligent matching mechanism. It utilizes the business and system information stored in the database to comprehensively analyze each business request to find the most matching associated system. First, after user authentication is successful, the integrated interceptor uses the business-system database to perform system matching on the first business request. During the system matching process, the integrated interceptor comprehensively considers multiple factors, such as processing capacity, historical performance, and business rules. Then, through comparison and analysis, the integrated interceptor identifies the relevant system that matches the first business request. Finally, the integrated interceptor routes the first business request to the selected relevant system and passes it to subsequent processing flows. This matching method, by quickly and accurately matching relevant systems, ensures that business requests are processed efficiently and accurately, improving overall operational efficiency. Simultaneously, it provides enterprises with a comprehensive, real-time view, supporting business decision-making and system optimization. This intelligent matching mechanism provides powerful support for enterprise business processing.

[0032] The matching and association system is identified according to the preset tenant identification rules to determine the data type to be identified and the data association path;

[0033] Optionally, the data type to be identified refers to the data type that needs to be determined and identified when identifying the matching associated systems according to preset tenant identification rules, including but not limited to tenant information, business data, system configuration, etc. The data association path refers to the relationship and path between data types determined when identifying the matching associated systems according to preset tenant identification rules. These relationships and paths describe the connections and flow between different data types, helping to understand the flow and usage of data in the system. When a business request is received and an associated system has been matched through the business-system database, the system terminal triggers the identification process. First, the validity of the tenant identifier is checked according to preset tenant identification rules, and the existence of the tenant in the system's tenant list is verified. Then, it is confirmed whether the tenant has permission to access the requested resource. Once the tenant identifier is verified as valid, the system will query the tenant information repository to obtain detailed information about the tenant, such as tenant name, subscribed service level, configuration preferences, etc. After obtaining the detailed information of the tenant, the system will again check the associated systems previously matched through the business-system database to ensure that the system can meet the tenant's needs and permissions. Simultaneously, after confirming the applicability of the associated system, the system will determine the data type that needs to be identified when processing the tenant's request. These data types include tenant information, business data, and system configurations, depending on business needs and tenant permissions. By identifying and classifying these data types, the system can better understand tenant needs and business scenarios, providing a foundation for subsequent data processing and business operations. The system then establishes data association paths by setting data query parameters and specifying data sources and destinations. This ensures that the required data is correctly retrieved and associated when processing requests, better integrating and managing data from different sources and types, and achieving standardized data management and use. This not only improves data processing efficiency but also identifies potential data problems or bottlenecks, providing a basis for system optimization and improvement. In summary, identifying matching and associating systems based on preset tenant identification rules, and determining the data types to be identified and data association paths, is a comprehensive process. It helps improve data processing efficiency and accuracy, as well as system stability and reliability. Through this process, enterprises can better utilize data to support decision-making and business development.

[0034] The first information acquisition interface is invoked based on the data type to be identified;

[0035] Based on the first information acquisition interface and the data association path, the first business request is used to extract tenant information to obtain the first tenant information;

[0036] Tenant identification is performed on the first tenant information based on the tenant identification database.

[0037] Optionally, the first information acquisition interface refers to the interface used to obtain the required information when called based on the data type to be identified. The tenant identification database refers to a database used to store and manage tenant identity information. This database contains detailed tenant information, authentication credentials, and other relevant data, used for tenant identification and management in a multi-tenant system. The system terminal calls the first information acquisition interface according to the data type to be identified to communicate with the relevant data source. The interface sends a data request to the data source according to preset rules and parameters to obtain the required data. When the data source receives the request, it performs corresponding processing and returns the result to the interface. After receiving the data response, the interface parses and processes it to extract the tenant information contained therein. Then, based on the obtained data association path, the system determines the position and flow direction of the tenant information in the data stream and extracts relevant tenant information, such as tenant ID, name, and description, from the data response. Finally, the system verifies the extracted tenant information to ensure its accuracy and completeness, and integrates the extracted and verified tenant information to form a complete tenant information set, i.e., the first tenant information. Finally, this tenant information is compared with the data in the tenant identification database to identify the tenant's identity. The goal of this process is to ensure that the system can accurately identify and verify the identity of tenants, providing them with appropriate services and resources. In this way, multi-tenant systems can provide a secure and isolated environment that meets the needs and business logic of different tenants. At the same time, this process also helps improve the system's data processing capabilities and service quality, enhancing the enterprise's competitiveness and market position.

[0038] Furthermore, this application provides a method for constructing preset tenant identification rules, which also includes:

[0039] The system retrieves multiple business requests.

[0040] Randomly select a first business request system from among the multiple business request systems, and obtain the first identification data type and the first data association path corresponding to the first business request system;

[0041] Optionally, preset tenant identification rules also need to be constructed. The business request system refers to a system or platform that receives and processes business requests. These systems are typically used to handle business requests from different sources, such as user interfaces, API interfaces, and external data sources. The system terminal acquires multiple business request systems, all of which are used to receive and process various business requests. One of these systems is then randomly selected and designated as the first business request system. Subsequently, the first identification data type and the first data association path corresponding to this first business request system are obtained. This information is crucial for subsequent data processing and business logic.

[0042] Based on the decision tree principle, the preset tenant identification rule is constructed by taking the preset tenant identification rule as the root node, the first business request system as the child node, and the first identification data type and the first data association path as the leaf nodes of the child node.

[0043] Optionally, the system terminal uses a decision tree principle, with a preset tenant identification rule as the root node. This root node is the starting point of the entire decision tree and represents the core rule for tenant identification. The first business request system is then added as a child node to the decision tree. This child node represents the identification branch related to the business request system. To improve the decision tree, the first identification data type and the first data association path are further used as leaf nodes of the child nodes. These leaf nodes provide specific data basis and paths to guide the actual operation of tenant identification. Then, based on the preset tenant identification rule, the first business request system, the first identification data type, and the first data association path, a complete decision logic is constructed. This logic will be used in the subsequent tenant identity identification process. Finally, the constructed decision tree is verified to ensure its logical correctness, structural integrity, and accurate tenant identity identification. This completes the construction of the preset tenant identification rule. By constructing a hierarchical and structurally complete decision tree, the accuracy and efficiency of tenant identification can be improved.

[0044] Furthermore, this application provides a method for identifying tenants based on the first tenant information using a tenant identification database, which further includes:

[0045] The tenant identification database is matched according to the data type to be identified to determine the first tenant identification database;

[0046] The first tenant information is input into the first tenant identification database for traversal and comparison, and the tenant identity is identified based on the information comparison results.

[0047] Optionally, the system terminal analyzes the data type to be identified to understand its characteristics, structure, and requirements. It then performs a preliminary scan of the tenant identification database to understand its data types, fields, and structure. Based on the data type to be identified, corresponding matching rules and conditions are formulated. These rules are used to search the database for tenant identification databases that match the data type to be identified. The system then performs searches and matching operations in the tenant identification database according to the formulated matching rules. The matching results are then filtered to exclude irrelevant or non-compliant records, confirming the first tenant identification database, which is the database that best matches the data type to be identified. Further, the system terminal organizes and formats the first tenant information to ensure its accuracy and completeness. A connection is then established with the first tenant identification database to ensure the stability and security of data transmission. The first tenant information is imported into the first tenant identification database to prepare for subsequent comparison operations. Then, pre-written query statements are used to traverse and compare the data in the first tenant identification database to ensure that the tenant ID, name, description, and other information completely match the records in the database. During the traversal and comparison process, if abnormal or non-compliant records are found, appropriate processing is required, such as deleting abnormal data. Finally, the tenant's identity is determined based on the comparison results. In summary, this series of operations aims to ensure accurate tenant identification and improve the system's data processing capabilities and service quality.

[0048] Furthermore, this application provides a method for tenant identification based on information comparison results, which further includes:

[0049] If the first tenant identification database contains data identical to the first tenant information, then the tenant identification is successful.

[0050] If no data matching the first tenant information exists in the first tenant identification database, then tenant identification fails.

[0051] Optionally, when the system terminal performs tenant identification based on the information comparison results, if the first tenant information completely matches the data in the first tenant identification database, it means that the tenant identification has passed and the system has confirmed the tenant's identity. Conversely, if there is no data in the database that matches the first tenant information, the tenant identification fails, and the system cannot confirm the tenant's identity. This process ensures the accuracy and reliability of tenant identification and helps improve the system's data processing capabilities and service quality.

[0052] If the identification is successful, the first service request is allowed to continue processing.

[0053] In one embodiment, if tenant identification is successful—that is, if the first tenant's information matches the data in the first tenant identification database—then the system will allow the first business request to continue processing. This means the tenant has been confirmed as legitimate, and their request will be processed and executed. This process ensures the security and isolation of the multi-tenant system, meeting the needs of tenants and business logic.

[0054] Furthermore, this application provides results for identifying failures, and the method also includes:

[0055] If identification fails, the first service request will be prevented from being processed.

[0056] Preferably, if tenant identification fails—that is, if the first tenant information does not match the data in the first tenant identification database—the system will prevent the first business request from continuing to be processed. This means that the tenant is considered illegitimate or unauthorized, and their request will not be processed or executed. This process helps protect the security and isolation of the multi-tenant system, preventing unauthorized access and operations.

[0057] In summary, the embodiments of this application have at least the following technical effects:

[0058] This application embodiment combines preset tenant identification rules, multiple business request systems, and a tenant identification database to construct a hierarchical and logically rigorous decision tree for accurate tenant identification. The method first randomly selects one of the multiple business request systems as the first business request system and obtains its corresponding first identification data type and first data association path. Then, this information is used as the leaf nodes of the child nodes to construct a complete preset tenant identification rule. By matching the data type to be identified with the tenant identification database, the first tenant identification database is found. Next, the first tenant information is input into this database for traversal and comparison, and the tenant identity is identified based on the comparison results. If the identification is successful, the corresponding business request is allowed to continue processing; if the identification fails, the processing of the business request is blocked. This method improves the accuracy and efficiency of tenant identification, meeting the security and isolation requirements of multi-tenant systems. Simultaneously, this method also has strong flexibility and scalability, and can be applied to multi-tenant systems of different types and sizes. These technical effects collectively achieve efficient and reliable tenant identification in a multi-system environment, providing strong support for enterprise data processing and services.

[0059] Example 2

[0060] Based on the same inventive concept as the multi-label arrhythmia discrimination method based on a multi-scale neural network model in the foregoing embodiments, such as Figure 3 As shown, this application provides a tenant identification system for multiple systems, the system comprising:

[0061] Receiving module 1, the receiving module 1 is used to receive the first service request of the target tenant;

[0062] The identity recognition module 2 is used to intercept the first service request through an integrated interceptor and to identify the tenant identity of the first service request according to a preset tenant identification rule, wherein the preset tenant identification rule is embedded in the integrated interceptor.

[0063] The identification and judgment module 3 is used to allow the first service request to continue processing if the identification is successful.

[0064] Furthermore, the identity recognition module 2 is used to perform the following method:

[0065] The integrated interceptor includes at least an HTTP information acquisition interface, an RPC information acquisition interface, and a WebFlux information acquisition interface.

[0066] Furthermore, the identity recognition module 2 is used to perform the following method:

[0067] Based on the business-system database, the first business request is matched with the relevant system to obtain the matching associated system;

[0068] The matching and association system is identified according to the preset tenant identification rules to determine the data type to be identified and the data association path;

[0069] The first information acquisition interface is invoked based on the data type to be identified;

[0070] Based on the first information acquisition interface and the data association path, the first business request is used to extract tenant information to obtain the first tenant information;

[0071] Tenant identification is performed on the first tenant information based on the tenant identification database.

[0072] Furthermore, the identity recognition module 2 is used to perform the following method:

[0073] The system retrieves multiple business requests.

[0074] Randomly select a first business request system from among the multiple business request systems, and obtain the first identification data type and the first data association path corresponding to the first business request system;

[0075] Based on the decision tree principle, the preset tenant identification rule is constructed by taking the preset tenant identification rule as the root node, the first business request system as the child node, and the first identification data type and the first data association path as the leaf nodes of the child node.

[0076] Furthermore, the identity recognition module 2 is used to perform the following method:

[0077] The tenant identification database is matched according to the data type to be identified to determine the first tenant identification database;

[0078] The first tenant information is input into the first tenant identification database for traversal and comparison, and the tenant identity is identified based on the information comparison results.

[0079] Furthermore, the identity recognition module 2 is used to perform the following method:

[0080] If the first tenant identification database contains data identical to the first tenant information, then the tenant identification is successful.

[0081] If no data matching the first tenant information exists in the first tenant identification database, then tenant identification fails.

[0082] Furthermore, the identification and judgment module 3 is used to perform the following method:

[0083] If identification fails, the first service request will be prevented from being processed.

[0084] It should be noted that the order of the embodiments described above is merely for descriptive purposes and does not represent the superiority or inferiority of the embodiments. Furthermore, specific embodiments have been described above. Other embodiments are within the scope of the appended claims. In some cases, the actions or steps described in the claims can be performed in a different order than that shown in the embodiments and still achieve the desired results. Additionally, the processes depicted in the drawings do not necessarily require a specific and sequential order to achieve the desired results. In some embodiments, multitasking and parallel processing are also possible or may be advantageous.

[0085] The above description is only a preferred embodiment of this application and is not intended to limit this application. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of this application should be included within the protection scope of this application.

[0086] This specification and accompanying drawings are merely illustrative examples of this application and are intended to cover any and all modifications, variations, combinations, or equivalents within the scope of this application. Clearly, those skilled in the art can make various alterations and modifications to this application without departing from its scope. Therefore, if such modifications and modifications fall within the scope of this application and its equivalents, this application intends to include such modifications and modifications.

Claims

1. A method for tenant identification for multi-systems, characterized in that, The method comprises: receiving a first service request of a target tenant, and performing data cleaning and JSON processing on the first service request; intercepting the first service request through an integrated interceptor, wherein the integrated interceptor comprises a plurality of types of information acquisition interfaces, and is embedded with a preset tenant identification rule constructed based on a decision tree principle, and the construction of the preset tenant identification rule comprises: obtaining a plurality of service request systems, randomly selecting a first service request system therefrom, and obtaining a first identification data type and a first data association path corresponding to the first service request system; taking the preset tenant identification rule as a root node, taking the first service request system as a child node, and taking the first identification data type and the first data association path as leaf nodes of the child node, to complete the construction of the preset tenant identification rule; and identifying the tenant identity of the first service request according to the preset tenant identification rule; if the identification is passed, the first service request is allowed to continue processing; the tenant identity identification of the first service request according to the preset tenant identification rule comprises: matching the first service request with a request system based on a service-system database, and obtaining a matching associated system; identifying the matching associated system according to the preset tenant identification rule, and determining a to-be-identified data type and a data association path; calling a first information acquisition interface based on the to-be-identified data type; extracting tenant information from the first service request based on the first information acquisition interface and the data association path, and obtaining first tenant information; identifying the tenant identity of the first tenant information according to a tenant identification database.

2. The method of claim 1, wherein, The method further comprises: if the identification fails, the first service request is prevented from continuing processing.

3. The method of claim 1, wherein, The method further comprises: The integrated interceptor at least comprises an http information acquisition interface, an rpc information acquisition interface and a webFlux information acquisition interface.

4. The method of claim 3, wherein, The tenant identity identification of the first tenant information according to the tenant identification database comprises: matching the tenant identification database according to the to-be-identified data type, and determining a first tenant identification database; inputting the first tenant information into the first tenant identification database for traversal comparison, and identifying the tenant identity according to the information comparison result.

5. The method of claim 4, wherein, The tenant identity identification according to the information comparison result comprises: when the first tenant identification database contains the same data as the first tenant information, the tenant identity identification is passed; when the first tenant identification database does not contain the same data as the first tenant information, the tenant identity identification fails.

6. A tenant identification system for multi-systems, characterized in that, The system comprises: a receiving module that receives a first service request of a target tenant, and performs data cleaning and JSON processing on the first service request; an identity identification module that intercepts the first service request through an integrated interceptor, wherein the integrated interceptor comprises a plurality of types of information acquisition interfaces, and is embedded with a preset tenant identification rule constructed based on a decision tree principle, and the construction of the preset tenant identification rule comprises: Obtaining a plurality of service request systems, randomly selecting a first service request system from them, and obtaining the first identification data type and the first data association path corresponding to the first service request system, and taking the preset tenant identification rule as the root node, the first service request system as the child node, and the first identification data type and the first data association path as the leaf node of the child node, completing the construction of the preset tenant identification rule; and identifying the tenant identity of the first service request according to the preset tenant identification rule; If the identification is passed, the first service request is allowed to continue processing, wherein the first service request is matched with the request system based on the business-system database to obtain a matching association system; the matching association system is identified according to the preset tenant identification rule to determine the to-be-identified data type and the data association path; Based on the to-be-identified data type, a first information acquisition interface is called; Based on the first information acquisition interface and the data association path, tenant information is extracted from the first service request to obtain first tenant information; and the first tenant information is identified according to the tenant identification database.

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