Featureless data processing method, device, computer equipment and storage medium

Abstract

The embodiment of the present invention discloses a method, device, computer equipment and storage medium for processing featureless data. The method includes: obtaining data transmitted on an API interface to obtain data to be processed; obtaining a data tag defined by a terminal; obtaining a URL accessed by a user to obtain a URL to be associated; matching the URL to be associated with a corresponding API interface, and performing association analysis on the data tag and the data to be processed to obtain an analysis result; and displaying the analysis result. By implementing the method of the embodiment of the present invention, it is possible to collect data transmitted from an API interface, define tags for featureless data, and automatically identify, classify and grade data, thereby improving data processing efficiency.

Description

Technical Field

[0001] The present invention relates to a data processing method, and more specifically to a featureless data processing method, device, computer equipment and storage medium. Background Art

[0002] In the existing data processing, it is generally necessary to perform data labeling on the data. Data labeling includes data identification, classification and grading. Data includes data in transmission and data relatively statically stored in the database system. For data in transmission, especially through API (Application Programming Interface), Data transmitted through the API interface can currently only be processed for data with data features. Data with data features means that the data to be identified can summarize or abstract one or more features that are clearly distinguished from other data through the data itself. The data can be uniquely identified by using a single feature or a combination of multiple features using regular expressions, keywords, dictionaries, machine learning models, scripts, etc., such as name, gender, mobile phone number, email address, etc. in personal privacy data; however, for data without data features transmitted through the API interface, data processing cannot be performed automatically and quickly. Data without data features means that the data cannot be uniquely identified by using a single feature or a combination of multiple features using regular expressions, keywords, dictionaries, machine learning models, scripts, etc., such as financial-related data, sales-related cost / price / profit..., business data in different industries, etc.; since it is impossible to identify, classify, and grade featureless data, it can only be performed manually, which is inefficient and affects the effect of subsequent data analysis.

[0003] Therefore, it is necessary to design a new method to collect data transmitted from the API interface, define labels for featureless data, and automatically identify, classify and grade the data to improve data processing efficiency. Summary of the invention

[0004] The purpose of the present invention is to overcome the defects of the prior art and provide a method, device, computer equipment and storage medium for processing featureless data.

[0005] To achieve the above object, the present invention adopts the following technical solution: a method for processing featureless data, comprising:

[0006] Get the data transmitted on the API interface to obtain the data to be processed;

[0007] Get the data tags defined by the terminal;

[0008] Get the URL visited by the user to get the URL to be associated;

[0009] Matching the corresponding API interface to the URL to be associated, and performing association analysis on the data tag and the data to be processed to obtain an analysis result;

[0010] The analysis results are presented.

[0011] A further technical solution is: the data tag defined by the acquisition terminal includes:

[0012] The terminal starts a browser plug-in, and uses the browser plug-in to intercept request information or response information of user interaction actions;

[0013] The terminal locates the URL and field corresponding to the user's access to the specified page data based on the intercepted information;

[0014] The terminal defines the data label for the URL and field corresponding to the page data designated by the user to obtain the data label;

[0015] Get the data label.

[0016] A further technical solution is that the terminal locates the URL and field corresponding to the page data designated by the user according to the intercepted information, including:

[0017] The terminal copies the specified data from the page accessed by the user, and performs a two-way fuzzy match with the intercepted information by using keywords or regular expressions. When the data is matched, the fields and URLs corresponding to the matched data are obtained. If the data corresponding to different fields on the page data are different, re-positioning is performed; if the data corresponding to different fields on the page data have the same value, the page interaction and positioning actions are performed again from the previous matching results to obtain the URL and fields corresponding to the page data specified by the user.

[0018] Its further technical solution is: the data label includes definition rules for data identification, classification and grading; the data label can reference preset or customized data identification names, data classification names, data grading names to perform data identification, data classification and data grading on fields corresponding to the customized data identification names, data classification names and data grading names.

[0019] A further technical solution is: matching the corresponding API interface to the URL to be associated, and performing association analysis on the data tag and the data to be processed to obtain an analysis result, including:

[0020] Match the corresponding API interface to the URL to be associated to obtain the target API interface;

[0021] Associating the field corresponding to the URL to be associated with the field corresponding to the target API interface;

[0022] Associating the data tag corresponding to the field corresponding to the to-be-associated URL in the data tag with the field corresponding to the target API interface to obtain an association result;

[0023] A label list and a graph corresponding to the data to be processed collected by the target API interface are generated according to the association result to obtain an analysis result.

[0024] A further technical solution is: matching the corresponding API interface to the URL to be associated to obtain the target API interface includes:

[0025] Segmenting the information of the URL to be associated to obtain an access URL path;

[0026] Segmenting the access URL path to obtain a first ordered array;

[0027] Performing information segmentation and path segmentation on the API interface to obtain a second ordered array;

[0028] Traversing the first ordered array, and comparing the values ​​at the same position of the first ordered array with the values ​​at the second ordered array, to determine the API interface successfully matched by the URL to be associated;

[0029] The API interface successfully matched by the URL to be associated is marked to obtain the target API interface.

[0030] Its further technical solution is: the label list includes the target API interface name, the user access URL, the field name corresponding to the URL and the data label information; the graph includes the statistical results of the number of API interfaces with data labels and without data labels, the percentage statistical results of the number of API interfaces with data labels and without data labels, the data labels of the top 100 API interfaces, a trend chart of the number of API interfaces with newly added data labels drawn daily, and the statistical results of data label category screening.

[0031] The present invention also provides a featureless data processing device, comprising:

[0032] A data acquisition unit is used to acquire data transmitted on the API interface to obtain data to be processed;

[0033] A label acquisition unit, used to acquire a data label defined by a terminal;

[0034] A URL acquisition unit is used to acquire the URL accessed by the user to obtain the URL to be associated;

[0035] An association unit, used to match the URL to be associated with a corresponding API interface, and perform association analysis on the data tag and the data to be processed to obtain an analysis result;

[0036] A display unit is used to display the analysis result.

[0037] The present invention further provides a computer device, which includes a memory and a processor. The memory stores a computer program, and the processor implements the above method when executing the computer program.

[0038] The present invention also provides a storage medium, wherein the storage medium stores a computer program, and the computer program can implement the above method when executed by a processor.

[0039] Compared with the prior art, the beneficial effects of the present invention are as follows: the present invention obtains data transmitted on the API interface, defines data tags on the terminal, obtains the URL accessed by the user, matches the API interface according to the URL accessed by the user, and associates the data tags with the data transmitted on the matching API interface, thereby realizing the collection of data transmitted from the API interface, defining tags for featureless data, and automatically identifying, classifying and grading the data, thereby improving data processing efficiency.

[0040] The present invention is further described below in conjunction with the accompanying drawings and specific embodiments. BRIEF DESCRIPTION OF THE DRAWINGS

[0041] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the accompanying drawings required for use in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are some embodiments of the present invention. For ordinary technicians in this field, other accompanying drawings can be obtained based on these accompanying drawings without paying any creative work.

[0042] Figure 1 A schematic diagram of an application scenario of the method for processing featureless data provided by an embodiment of the present invention;

[0043] Figure 2 A schematic diagram of a flow chart of a method for processing featureless data provided by an embodiment of the present invention;

[0044] Figure 3 A schematic diagram of a sub-process of a method for processing featureless data provided by an embodiment of the present invention;

[0045] Figure 4 A schematic diagram of a sub-process of a method for processing featureless data provided by an embodiment of the present invention;

[0046] Figure 5 A schematic diagram of a sub-process of a method for processing featureless data provided by an embodiment of the present invention;

[0047] Figure 6 A schematic block diagram of a featureless data processing device provided by an embodiment of the present invention;

[0048] Figure 7 A schematic block diagram of an association unit of a featureless data processing device provided by an embodiment of the present invention;

[0049] Figure 8 A schematic block diagram of a matching subunit of a featureless data processing device provided by an embodiment of the present invention;

[0050] Fig. 9 A schematic block diagram of a computer device provided in an embodiment of the present invention. DETAILED DESCRIPTION

[0051] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0052] It should be understood that when used in this specification and the appended claims, the terms "include" and "comprises" indicate the presence of described features, integers, steps, operations, elements and / or components, but do not exclude the presence or addition of one or more other features, integers, steps, operations, elements, components and / or combinations thereof.

[0053] It should also be understood that the terms used in this specification of the present invention are only for the purpose of describing specific embodiments and are not intended to limit the present invention. As used in the specification of the present invention and the appended claims, unless the context clearly indicates otherwise, the singular forms "a", "an" and "the" are intended to include plural forms.

[0054] It should be further understood that the term "and / or" used in the present description and the appended claims refers to any and all possible combinations of one or more of the associated listed items, and includes these combinations.

[0055] See also Figure 1 and Figure 2 , Figure 1 A schematic diagram of an application scenario of the featureless data processing method provided in an embodiment of the present invention. Figure 2A schematic flow chart of a featureless data processing method provided by an embodiment of the present invention. The featureless data processing method is applied in a management server. The management server interacts with the terminal and the application server for data, wherein the application server collects data transmitted on the API interface and transmits it to the management server, and the terminal is used to define data tags. The management server performs correlation analysis based on the data transmitted on the API interface and the data tags defined by the terminal, and displays the results of the analysis. In addition, an agent, i.e., an application client, is installed on the application server. The application client communicates with the management end, which is generally a separate server. The collection strategy set in the management end is pushed to the application client in real time, and the actual collection strategy is set in combination with the built-in collection switch of the application client. When data initiated by a user through a user terminal passes through the specified interface of the application client, the application client intercepts the data using byte enhancement technology, and collects the intercepted data using the actual collection strategy, and caches the collected data.

[0056] Figure 2 FIG. 1 is a flow chart of a method for processing featureless data provided by an embodiment of the present invention. Figure 2 As shown, the method includes the following steps S110 to S150.

[0057] S110: Acquire data transmitted on the API interface to obtain data to be processed.

[0058] In this embodiment, the data to be processed refers to data transmitted on the API interface, such as user identification, protocol, request and response data.

[0059] Specifically, the application client on the application server obtains the collection strategy from the management end; the actual collection strategy is set using a switch mode according to the collection strategy; the access data is intercepted using byte enhancement technology; the intercepted data is collected based on the actual collection strategy in combination with the linkage mechanism to collect user behavior data, application transmission data, such as user identification, protocol, request and response data, to obtain data to be processed.

[0060] The collection strategy includes at least one of the following data collection methods: data collection based on user identification configuration, data collection based on application service configuration, data collection based on application interface, data collection according to fields of application interface, data collection based on configured frequency, and data collection based on configured single data collection volume.

[0061] Compared with network traffic collection and application gateway deployment collection, which are limited to specific network areas and deployment locations, and the collection scope is limited, this embodiment is deployed on the application service host in the form of a client, that is, an application client. The deployment is simple, the collection scope is not limited, and there is a unified management end to uniformly configure and manage the application client; on the management end, a single or combined data collection strategy can be configured based on application services, user identifiers, application interfaces, application interface fields, collection frequency, and data collection volume to collect user behavior data, application transmission data, and application asset data, so as to achieve controllability of data collection. By changing the collection strategy on the management end, the application client's data collection strategy can be changed to achieve controllability of data collection. The data collection strategy can be quickly configured without the need for fixed-point data collection development, which saves manpower, greatly shortens the development cycle, and improves work and project efficiency; there is no need to collect user behavior data, application transmission data, and application asset data at buried points and two openings, which reduces the operation and maintenance of the application and the impact on the application system, thereby more guaranteeing the normal operation of the application. During deployment, it is deployed on the application service host in client mode, and a unified management terminal performs unified configuration management on the application client; it has no impact on the application system architecture and has no impact on the existing network architecture.

[0062] Specifically, the above-mentioned data collection method based on user identification configuration refers to whether to collect application transmission data based on user identification configuration, specifying that a single, multiple or all users can or cannot collect user behavior data, application transmission data and application asset data, where the user identification includes the accessed user account, access IP, access mac, access browser, etc.

[0063] The data collection method based on application service configuration refers to whether to collect application transmission data and application asset data based on the application service configuration, and specifies whether a single, multiple, or all application services can or cannot collect application transmission data.

[0064] The data collection method based on application interface data collection refers to whether the application interface collects application transmission data and application asset data, and specifies whether a single, multiple or all application interfaces can or cannot collect application transmission data.

[0065] The data collection method based on the fields of the application interface refers to whether the fields of the application interface configure the collection of application transmission data. It is mainly controlled by the interface field on the interface name, specifying whether a single, multiple or all application interface fields can or cannot collect application transmission data.

[0066] The data collection method based on the configured frequency is controlled by the time period of collecting data.

[0067] The data collection method based on the configured single data collection volume is mainly controlled by the number of data items that need to be collected.

[0068] Any combination of the above data collection methods configures whether to collect application transmission data, such as allowing the collection of behavior data of a certain user accessing a certain interface or not allowing the collection of behavior data of a specified or all users accessing a specified application service; thereby forming a collection strategy.

[0069] In this embodiment, the actual collection strategy refers to the strategy actually used to collect data, which is a combination of the collection strategy transmitted by the client and the set switch mode to form a variety of data collection strategies, and these data collection strategies are executed in sequence according to the set priority.

[0070] In this embodiment, the switch mode includes at least one of a switch for setting data collection based on application services, a switch for setting data collection based on user identification, a switch for setting data collection based on application interfaces, and a switch for setting data collection based on fields of application interfaces; the switch mode also includes a periodic threshold for data collection and filtering rules based on the amount of data collected for a single time.

[0071] Specifically, the mode of setting the switch for data collection based on the application service means that when the status is enabled, the application client will turn on the data collection function of the application service, which is a prerequisite for the collection function to work normally; when the status is closed, the application client will turn off the collection function of the application service, and all collection functions under this application service will be turned off.

[0072] The mode of setting the switch for data collection based on user identification means that when the status is enabled, the application client turns on the data collection function based on user identification; when the status is disabled, the application client turns off the data collection function based on user identification, but other collection switches and data collection are not affected, and data is no longer collected based on user identification.

[0073] The mode of setting the switch for data collection based on the application interface means that when the status is enabled, data collection is performed on all application interfaces by default, and the data of the specified interface can be defined for collection or non-collection, where the specified interface can be a single, multiple, or all interface names combined with a label for collection or non-collection; when the status is closed, the data collection function based on the application interface under this application service will be closed by default, but data of the specified interface, such as a single, multiple, or all interface names combined with a label for collection, can be collected. At this time, other collection switches and data collection are not affected.

[0074] The mode of setting the switch of data collection based on the fields of the application interface means that when the status is enabled, data collection is performed on all interfaces and all fields by default, and data of specified interfaces and specified fields, such as single, multiple or all interface names plus the field names of the corresponding interfaces and the data marked as not to be collected, will not be collected; when the status is closed, the data collection function based on the application interface fields will be closed, but other collection switches and data collection will not be affected. It is just that application transmission data will no longer be collected based on the application interface fields, but data of specified interfaces and specified fields, such as single, multiple or all interface names plus the field names of the corresponding interfaces and the data marked for collection will be collected. At this time, other collection switches and data collection will not be affected.

[0075] The periodic threshold of data collection controls the data that needs to be collected by counting the time period of data collection. The main body of the collected data is a single application service, the application interface in the service, and the interface field. The filtering rule based on the collection volume of a single data is to extract and filter the number of data items for a single application service, the application interface in the service, and the interface field. When filtering, methods such as pre-data extraction, post-data extraction, random extraction, and data extraction from a specific data point will be adopted.

[0076] The management end establishes a two-way communication channel with the application client, and can send instructions to the application client at any time. The application client can also execute according to the instructions and return the execution results. The application client can also actively send information such as the status of the application client to the management end through this two-way communication channel. During the initial installation, after the application client and the management end establish communication, the management end can push the collection strategy according to the application client group or according to a single application client. When the data collection strategy is updated, the strategy will also be pushed in real time. The application client executes different data collection logic according to the different collection instructions in the collection strategy based on the received data strategy, thereby achieving the function of manageable and controllable data collection.

[0077] In this embodiment, the access data refers to data initiated by the user terminal; the intercepted data refers to data passing through a designated interface of the application client.

[0078] Specifically, after the Java bytecode is generated, the generated Java bytecode is dynamically modified when loaded by the JVM according to the rules defined in the Java bytecode, and the content of the enhanced function is added to intercept the access data according to the content of the enhanced function to obtain the intercepted data.

[0079] Using bytecode enhancement technology, after Java bytecode is generated, according to the rules defined in the Java bytecode, the generated Java bytecode is dynamically modified when it is loaded by the JVM (Java Virtual Machine), adding required fields or method functions, or inheriting and implementing new classes and interfaces, etc. These dynamically added fields, or method functions, or inheriting and implementing new classes and interfaces are all enhanced functions, which mainly refer to the function of automatically extracting the request parameters and return results of the method function.

[0080] Before extracting relevant data, first determine the method functions of the class that the data of interest must pass through during a user's access. After determining these method functions, the logic of collecting data before and after calling these method functions is enhanced by bytecode technology. At this time, the application system that needs to be collected can be collected according to actual needs. The above method functions include Object first = methodd (String paramer) and / or Object second = first.methond (String paramer);

[0081] First, the main content of the method method (String paramer) is extracted into a function with a method name of a random string, such as sdfsdfsd (paramer); then the method method (String paramer) is modified to:

[0082]

[0083] Finally, the data collected in before() and after() will be stored in a variable in the first object, which is enhanced. In this way, the value in this variable can be passed to the before and after methods in first.methond(Stringparamer), so that the user's data can be linked together throughout the life cycle of a visit.

[0084] The extracted data includes different types of data, user identification information such as user account, IP, mac, browser, etc., user access time, access results, access interface, access data and access times, etc. However, these data are scattered in different places during the user access process. Through the above method functions, these data can be gathered together and aggregated to any data access party, that is, bytecode enhancement technology is used to intercept and aggregate all data.

[0085] When the access data flow and interface calls of user access and task scheduling pass through the Agent of the application client, the application client will use bytecode enhancement technology to intercept the data passing through. The data obtained based on the bytecode enhancement technology is also the transmission data after the application layer protocol is parsed, so there is no need to parse the protocol and restore the content, so it is not affected by encryption protocols and private protocols when collecting data. There is no need to collect user behavior data, application transmission data, and application asset data at the same time, which reduces the operation and maintenance of the application and the impact on the application system, thereby ensuring the normal operation of the application; it has no impact on the application system architecture and has no impact on the existing network architecture.

[0086] Since the application client is deployed on the application server, application components, application host IP, and application instances can be collected directly on the application system. Combining the above two types of data collection, the application asset data that can be collected include application name, application service name, application interface, application component, application host IP, application instance, database name, database IP, database port, database category, etc.

[0087] Specifically, the intercepted data stream is parsed according to the actual collection strategy to collect the required user behavior data, application transmission data and application asset data.

[0088] In this embodiment, the intercepted data is collected according to different data collection logics in the actual collection strategy, including user behavior data, application transmission data and application asset data; wherein different data collection logics perform data collection according to set priorities.

[0089] In addition, the user behavior data mentioned above includes user identification, collection time, user access behavior, access interface, number of access data and access data volume. The user identification includes user account, access IP, access mac and access browser; the application transmission data includes user identification, data transmission time, all fields in the protocol, the content corresponding to all fields in the protocol, all request data transmitted and all response data transmitted; the application transmission data includes user identification, data transmission time, protocol fields such as all fields of http and RPC (Remote Procedure Call) and other protocols, protocol content such as all contents of http and RPC (Remote Procedure Call) and other protocol fields, all request data transmitted and all response data transmitted. The application asset data mentioned above includes user identification, application name, application service name, application interface, application component, application host IP, application instance, data transmission time, database name, database IP, database port, database category, etc.

[0090] In this embodiment, the above priorities are:

[0091] When multiple policies are executed, they are processed from high to low priority, and are processed from high to low according to the data collection method based on application service configuration, the data collection method based on the configured frequency, the data collection method based on the configured single data collection volume, the data collection method based on the application interface, the data collection method based on the fields of the application interface, and the data collection method based on the user identification configuration.

[0092] When multiple policies conflict, they are handled according to the high priority, and are processed from high to low according to the data collection method based on application service configuration, the data collection method based on the configured frequency, the data collection method based on the configured single data collection amount, the data collection method based on the application interface, the data collection method based on the fields of the application interface, and the data collection method based on the user identification configuration.

[0093] When a problem occurs in the executed data collection strategy logic, the application client will not execute the data collection instruction and return a failure result to the management end.

[0094] Compared with preset embedding points and fixed-point dual-opening, the data that can be collected by this embodiment is more comprehensive, and only simple configuration is required during collection, thus making the collection of user behavior data, application transmission data, and application asset data simpler and more flexible.

[0095] After receiving the collected data from the client, the management server starts the following processing:

[0096] API interface asset sorting: sort out the related asset information with API interface as the primary key. The related asset information includes but is not limited to the application, service, host, instance, components used, etc.

[0097] API interface data combing: Use API interface as the primary key to comb the data transmitted on the interface. The transmitted data includes but is not limited to the protocol and its field information, interface request data, interface response data, etc.

[0098] Stores assets and data information of API interfaces.

[0099] S120: Acquire a data tag defined by the terminal.

[0100] In this embodiment, the data label refers to the definition rules for identifying, classifying and grading data; the data label can reference preset or customized data identification names, data classification names, and data classification names to identify, classify and grade the fields corresponding to the customized data identification names, data classification names and data classification names.

[0101] In one embodiment, see Figure 3 , the above-mentioned step S120 may include steps S121 to S124.

[0102] S121. The terminal starts a browser plug-in, and uses the browser plug-in to intercept request information or response information of a user interaction action.

[0103] In this embodiment, a browser plug-in is installed and started on the terminal, specifically, the browser plug-in is installed and started on the browser through which the user accesses the application; when the user accesses the application system and performs interactive actions, the browser plug-in can be used to intercept the request information or response information of the user's interactive actions.

[0104] The core functions of the browser plug-in are as follows: authentication management through the management server; intercepting the request and response data when the user accesses the application by rewriting the request and receiving methods of the browser's underlying API, such as XML Http Request, and locating and analyzing the data. Currently, it supports ajax, fetch request and response types; performing data label operations on the browser plug-in and synchronizing the label data to the management platform; supported browser types: Google, Firefox, 360, QQ, Sogou.

[0105] Install the plug-in through the extension program on the terminal's browser; start the browser plug-in; based on the interactive interface that pops up on the browser, authentication and login are required before operation: the browser plug-in requires login authentication, which comes from the user management and role management of the management server. Only users who are authorized to use the browser plug-in can log in and use it.

[0106] The user logs in to the application system on the browser and performs request and response interactions based on the access page. The following example illustrates the use of requests and responses:

[0107] Requesting information means registering an account and entering personal information, such as name, mobile phone number, address, and email address, and performing a submission action;

[0108] The response information refers to querying the user's mobile phone number and obtaining list information, such as name and mobile phone number.

[0109] In addition, when intercepting request information, the specific operations are as follows: take the example of registering an account and entering personal information, such as user account, name, mobile phone number, age, and submitting it. At this time, the plug-in will intercept the URL (Uniform Resource Locator) accessed by the user. The URL format is 'protocol type: / / server address[:port number] / path / file name[parameter=value]', and obtain the data in the request information, such as name, mobile phone number, address, email, and the fields corresponding to the data.

[0110] When intercepting response information, the specific operations are as follows: take the user account query and obtain the user list information, such as user account, name, mobile phone number, and age, as an example. At this time, the plug-in will intercept the URL accessed by the user. The URL format is 'protocol type: / / server address[:port number] / path / file name[parameter=value]', and obtain the data in the response information, such as name, mobile phone number, and the fields corresponding to the data.

[0111] S122: The terminal locates the URL and field corresponding to the page data designated by the user according to the intercepted information.

[0112] In this embodiment, the terminal copies the specified data from the page accessed by the user, and performs a two-way fuzzy match with the intercepted information by using keywords or regular expressions. When the data is matched, the fields and URLs corresponding to the matched data are obtained. If the data corresponding to different fields on the page data are different, re-positioning is performed; if the data corresponding to different fields on the page data have the same value, the page interaction and positioning action is performed again from the previous matching result to obtain the URL and field corresponding to the page data specified by the user.

[0113] Specifically, for the matching of request information and the positioning of access fields and URLs, the specified submission data is copied from the user access page, such as input data in text boxes / drop-down boxes / radio boxes / check boxes, etc. The 'user account' submission data when registering an account is used as an example. The 'user account' information data entered by the user and the request data intercepted by the plug-in are fuzzily matched in both directions using keywords or regular expressions, that is, the user account will be fuzzily matched with the intercepted data, and the intercepted data will be fuzzily matched with the user account. If the data is matched, the fields and URLs corresponding to the matched request data are obtained. If the data corresponding to different fields on the page are not the same, they can generally be located at one time. Most of the time, a URL and a field will be located. If there are data corresponding to different fields on the page with the same value, the user can perform page interaction and positioning actions again in the last matching result. The number of fields to be located should not be the same as the number of other fields as much as possible until the field and URL positioning are completed.

[0114] When matching response data and locating access fields and URLs, copy the response return data from the user access page, such as list fields, summary statistics, graphic statistics and other corresponding data. Take the user account query and obtain the user's 'age' data information as an example. For example, for a one-way precise match of numeric types, use the 'age' data returned by the query and the response data intercepted by the plug-in for a one-way precise match using regular expressions, that is, the returned 'age' data will be accurately matched with the intercepted response data. If the data is matched, the fields and URLs corresponding to the matched request data are obtained. If the data corresponding to different fields on the page are not the same, they can generally be located at one time. Most of the time, a URL and a field will be located. If there are data corresponding to different fields on the page with the same value, the user can perform page interaction and positioning actions again. The number of fields to be located should not be the same as that of other fields until the field and URL positioning are completed.

[0115] S123: The terminal defines a data tag for the URL and field corresponding to the page data designated by the user to obtain a data tag.

[0116] In this embodiment, after the specified data on the application system page is located, data labeling operations can be performed on the located URL field. Data labeling mainly includes data identification, data classification, and data grading. The data identification name, data classification name, and data grading name preset or customized by the management platform can be directly referenced on the interactive page to perform data identification, data classification, and data grading on this field. After completing the data labeling of the field, submit and synchronize the data label information to the management server.

[0117] S124: Obtain the data label.

[0118] S130: Acquire the URL visited by the user to obtain the URL to be associated.

[0119] In this embodiment, the URL to be associated refers to the URL accessed by the user.

[0120] The management server obtains the URL accessed by the user from the browser plug-in, and matches the corresponding API interface according to the URL accessed by the user based on the API interface data stored on the management server.

[0121] S140: Match the corresponding API interface to the URL to be associated, and perform association analysis on the data tag and the data to be processed to obtain an analysis result.

[0122] In this embodiment, the analysis result refers to the label list and graphics corresponding to the data to be processed collected by the API interface matched by the user's access URL. Customized labels can include types such as telephone and finance, and can be processed according to priority levels. When marking, personal privacy data, name, address, and each company can be customized to automatically manage classification and grading.

[0123] In one embodiment, see Figure 4 , the above-mentioned step S140 may include steps S141 to S144.

[0124] S141. Match the corresponding API interface to the URL to be associated to obtain a target API interface.

[0125] In this embodiment, the target API interface refers to an array generated based on the URL to be associated and an array generated based on the API interface in which the number and value of strings are equal; the number of strings in the two arrays is a variable, and the corresponding position in the array generated based on the API interface is a variable, which is an API interface that meets these two conditions.

[0126] In one embodiment, see Figure 5 , the above-mentioned step S141 may include steps S1411 to S1416.

[0127] S1411. Segment the information of the URL to be associated to obtain an access URL path.

[0128] In this embodiment, the access URL path refers to information of a designated location in the access URL information.

[0129] Separate the protocol information from the access URL according to " / / ". Take the access URL 'https: / / host:port / system / user / getPage' as an example. In this example, it is https. Then, according to " / ", the URL is separated to obtain 'host, port and / system / user / getPage', where ' / system / user / getPage' is the path.

[0130] S1412: Segment the access URL path to obtain a first ordered array.

[0131] In this embodiment, the first ordered array refers to an array obtained by dividing the access URL path into individual fields.

[0132] The path / system / user / getPage is further split into / system, / user, / getPage according to " / " level by level to obtain an ordered array A, thereby obtaining the first ordered array.

[0133] S1413. Perform information segmentation and path segmentation on the API interface to obtain a second ordered array.

[0134] The API interface can also be segmented according to the above steps S1411 to S1412 to obtain an ordered array B, ie, a second ordered array; details will not be repeated here.

[0135] S1415. Traverse the first ordered array, and compare the values ​​at the same position of the first ordered array with those of the second ordered array to determine the API interface that is successfully matched by the URL to be associated.

[0136] Traverse ordered array A and compare them one by one with the values ​​at the same position in ordered array B. In the following two cases, it is considered that the user's access URL matches the API interface successfully: one is that the number and value of strings in ordered array A and ordered array B are the same; the other is that the number of strings in ordered array A and ordered array B is a variable, and the corresponding position in ordered array B is a variable.

[0137] S1416: Mark the API interface that is successfully matched by the URL to be associated to obtain a target API interface.

[0138] The API interface that the user access URL successfully matches is marked with a corresponding label, indicating that the user access URL is equivalent to the successfully matched API interface.

[0139] S142: Associate the field corresponding to the URL to be associated with the field corresponding to the target API interface.

[0140] In this embodiment, when the user access URL is associated with the target API interface, the field names are compared and the field names under the user access URL are associated with the field names under the API interface. If the values ​​of the field names are the same, they are associated.

[0141] S143. Associate the data tag corresponding to the field corresponding to the to-be-associated URL in the data tag with the field corresponding to the target API interface to obtain an association result.

[0142] In this embodiment, the association result refers to the result obtained by associating the data tag corresponding to the field corresponding to the to-be-associated URL in the data tag with the field corresponding to the target API interface.

[0143] According to the data tags previously defined by the user for the fields under the access URL, such as data identification, data classification, and data classification, the data tags are associated with the corresponding fields under the target API interface.

[0144] S144. Generate a label list and a graph corresponding to the data to be processed collected by the target API interface according to the association result to obtain an analysis result.

[0145] The tag list includes the target API interface name, user access URL, field name corresponding to the URL, and data tag information; the graph includes statistics on the number of API interfaces with data tags and without data tags, percentage statistics on the number of API interfaces with data tags and without data tags, data tags of the top 100 API interfaces, a trend chart of the number of API interfaces with newly added data tags drawn daily, and statistics on data tag category screening.

[0146] Specifically, the statistical results of data label category filtering refer to setting specific filtering sub-items for data identification, data classification, and data grading, and counting the number of API interfaces and the overall proportion.

[0147] S150: Display the analysis results.

[0148] Based on the application system access page, the API interface is used to transmit featureless data for data identification, data classification and data grading. First, based on the bytecode enhancement technology, the agent is installed on the service on the application server to realize the collection of data transmitted on the API interface. Then, based on the plug-in developed for the browser application, the user can directly define data labels for visible data on the application system access page, realizing the function of defining labels for visible data, and can be extended to various business systems to allow users to define data labels.

[0149] This embodiment collects API interface data based on bytecode enhancement technology, performs data tag operations on featureless data of access pages based on browser plug-ins, and performs data association analysis in combination with API interface data and data tag operation information, associates and maps data tag information defined on the application access page with API interface fields, thereby achieving the goal of data tag management of transmitted API interface field data, solving the industry's problem of being unable to perform data tagging on featureless data transmitted via API interfaces; solving the problem of difficulty in implementing data classification and data grading in data tags: directly defining data tags for visible data on the application system page, which can be defined as long as it is visible, without the need for professional security personnel or developers to identify and operate, with simple operation and convenient implementation; the same applies to data tag definitions for feature data.

[0150] The above-mentioned method for processing featureless data obtains the data transmitted on the API interface, defines data tags on the terminal, obtains the URL accessed by the user, matches the API interface according to the URL accessed by the user, and associates the data tags with the data transmitted on the matching API interface, thereby realizing the collection of data transmitted from the API interface, defining tags for featureless data, and automatically identifying, classifying and grading the data, thereby improving data processing efficiency.

[0151] Figure 6 is a schematic block diagram of a featureless data processing device 300 provided in an embodiment of the present invention. Figure 6 As shown, corresponding to the above featureless data processing method, the present invention also provides a featureless data processing device 300. The featureless data processing device 300 includes a unit for executing the above featureless data processing method, and the device can be configured in a server. Figure 6 The featureless data processing device 300 includes a data acquisition unit 301, a tag acquisition unit 302, a URL acquisition unit 303, an association unit 304 and a display unit 305.

[0152] The data acquisition unit 301 is used to acquire data transmitted on the API interface to obtain data to be processed; the tag acquisition unit 302 is used to acquire the data tag defined by the terminal; the URL acquisition unit 303 is used to acquire the URL visited by the user to obtain the URL to be associated; the association unit 304 is used to match the corresponding API interface for the URL to be associated, and perform association analysis on the data tag and the data to be processed to obtain an analysis result; the display unit 305 is used to display the analysis result.

[0153] In one embodiment, the tag acquisition unit 302 is used to start a browser plug-in by the terminal, and use the browser plug-in to intercept the request information or response information of the user interaction action; the terminal locates the URL and field corresponding to the user's access to the specified page data based on the intercepted information; the terminal defines the data tag for the URL and field corresponding to the user's access to the specified page data to obtain the data tag; and obtains the data tag.

[0154] Specifically, the tag acquisition unit 302 is used for the terminal to copy the specified data from the user access page, and perform two-way fuzzy matching with the intercepted information by using keywords or regular expressions. When the data is matched, the fields and URLs corresponding to the matched data are obtained. If the data corresponding to different fields on the page data are different, re-positioning is performed; if the data corresponding to different fields on the page data have the same value, the page interaction and positioning action is performed again from the previous matching result to obtain the URL and field corresponding to the page data specified by the user.

[0155] In one embodiment, if Figure 7 As shown, the association unit 304 includes a matching subunit 3041 , a field association subunit 3042 , a tag association subunit 3043 and an analysis subunit 3044 .

[0156] The matching subunit 3041 is used to match the API interface corresponding to the URL to be associated to obtain the target API interface; the field association subunit 3042 is used to associate the field corresponding to the URL to be associated with the field corresponding to the target API interface; the tag association subunit 3043 is used to associate the data tag corresponding to the field corresponding to the URL to be associated in the data tag to the field corresponding to the target API interface to obtain an association result; the analysis subunit 3044 is used to generate a tag list and a graph corresponding to the data to be processed collected by the target API interface according to the association result to obtain an analysis result.

[0157] In one embodiment, if Figure 8 As shown, the matching subunit 3041 includes a first segmentation module 30411 , a second segmentation module 30412 , a third segmentation module 30413 , a traversal module 30414 and an identification processing module 30415 .

[0158] The first segmentation module 30411 is used to perform information segmentation on the URL to be associated to obtain the access URL path; the second segmentation module 30412 is used to segment the access URL path to obtain a first ordered array; the third segmentation module 30413 is used to perform information segmentation and path segmentation on the API interface to obtain a second ordered array; the traversal module 30414 is used to traverse the first ordered array and compare the values ​​at the same position of the first ordered array with the second ordered array to determine the API interface that is successfully matched by the URL to be associated; the identification processing module 30415 is used to mark the API interface that is successfully matched by the URL to be associated to obtain the target API interface.

[0159] It should be noted that those skilled in the art can clearly understand that the specific implementation process of the above-mentioned featureless data processing device 300 and each unit can refer to the corresponding description in the aforementioned method embodiment, and for the convenience and brevity of description, it will not be repeated here.

[0160] The featureless data processing device 300 can be implemented in the form of a computer program. The computer program can be implemented in the form of a computer program. Fig. 9 Runs on the computer device shown.

[0161] See also Fig. 9 , Fig. 95 is a schematic block diagram of a computer device provided in an embodiment of the present application. The computer device 500 may be a server, wherein the server may be an independent server or a server cluster composed of multiple servers.

[0162] See also Fig. 9 The computer device 500 includes a processor 502 , a memory and a network interface 505 connected via a system bus 501 , wherein the memory may include a non-volatile storage medium 503 and an internal memory 504 .

[0163] The non-volatile storage medium 503 can store an operating system 5031 and a computer program 5032. The computer program 5032 includes program instructions, and when the program instructions are executed, the processor 502 can execute a featureless data processing method.

[0164] The processor 502 is used to provide computing and control capabilities to support the operation of the entire computer device 500 .

[0165] The internal memory 504 provides an environment for the operation of the computer program 5032 in the non-volatile storage medium 503. When the computer program 5032 is executed by the processor 502, the processor 502 can execute a featureless data processing method.

[0166] The network interface 505 is used to communicate with other devices over the network. Fig. 9 The structure shown in the figure is merely a block diagram of a portion of the structure related to the solution of the present application, and does not constitute a limitation on the computer device 500 to which the solution of the present application is applied. The specific computer device 500 may include more or fewer components than those shown in the figure, or combine certain components, or have a different arrangement of components.

[0167] The processor 502 is used to run the computer program 5032 stored in the memory to implement the following steps:

[0168] Acquire the data transmitted on the API interface to obtain the data to be processed; acquire the data tag defined by the terminal; acquire the URL visited by the user to obtain the URL to be associated; match the corresponding API interface to the URL to be associated, and perform association analysis on the data tag and the data to be processed to obtain the analysis result; and display the analysis result.

[0169] Among them, the data label includes definition rules for data identification, classification and grading; the data label can reference preset or customized data identification names, data classification names, data classification names, to perform data identification, data classification, and data grading on fields corresponding to the customized data identification names, data classification names, and data classification names.

[0170] In one embodiment, when the processor 502 implements the step of obtaining the data tag defined by the terminal, the processor 502 specifically implements the following steps:

[0171] The terminal starts a browser plug-in and uses the browser plug-in to intercept request information or response information of user interaction actions; the terminal locates the URL and field corresponding to the user's access to the specified page data based on the intercepted information; the terminal defines data tags for the URL and field corresponding to the user's access to the specified page data to obtain data tags; and obtains the data tags.

[0172] In one embodiment, when the processor 502 implements the step of locating the URL and field corresponding to the user accessing the specified page data according to the intercepted information, the processor 502 specifically implements the following steps:

[0173] The terminal copies the specified data from the page accessed by the user, and performs a two-way fuzzy match with the intercepted information by using keywords or regular expressions. When the data is matched, the fields and URLs corresponding to the matched data are obtained. If the data corresponding to different fields on the page data are different, re-positioning is performed; if the data corresponding to different fields on the page data have the same value, the page interaction and positioning actions are performed again from the previous matching results to obtain the URL and fields corresponding to the page data specified by the user.

[0174] In one embodiment, when the processor 502 implements the step of matching the URL to be associated with the corresponding API interface and performing association analysis on the data tag and the data to be processed to obtain the analysis result, the processor 502 specifically implements the following steps:

[0175] Match the corresponding API interface to the URL to be associated to obtain the target API interface; associate the field corresponding to the URL to be associated with the field corresponding to the target API interface; associate the data tags corresponding to the fields corresponding to the URL to be associated in the data tags to the fields corresponding to the target API interface to obtain an association result; generate a label list and a graph corresponding to the data to be processed collected by the target API interface based on the association result to obtain an analysis result.

[0176] Among them, the label list includes the target API interface name, user access URL, field name corresponding to the URL and data label information; the graph includes statistics on the number of API interfaces with data labels and without data labels, percentage statistics on the number of API interfaces with data labels and without data labels, data labels of the top 100 API interfaces, a trend chart of the number of API interfaces with newly added data labels drawn daily, and statistics on data label category screening.

[0177] In one embodiment, when the processor 502 implements the step of matching the corresponding API interface to the URL to be associated to obtain the target API interface, the processor 502 specifically implements the following steps:

[0178] Perform information segmentation on the URL to be associated to obtain an access URL path; perform segmentation on the access URL path to obtain a first ordered array; perform information segmentation and path segmentation on the API interface to obtain a second ordered array; traverse the first ordered array, and compare the values ​​at the same position of the first ordered array with the second ordered array to determine the API interface that is successfully matched by the URL to be associated; mark the API interface that is successfully matched by the URL to be associated to obtain a target API interface.

[0179] It should be understood that in the embodiment of the present application, the processor 502 may be a central processing unit (CPU), and the processor 502 may also be other general-purpose processors, digital signal processors (DSP), application-specific integrated circuits (ASIC), field-programmable gate arrays (FPGA) or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. Among them, the general-purpose processor may be a microprocessor or the processor may also be any conventional processor, etc.

[0180] It can be understood by those skilled in the art that all or part of the processes in the method for implementing the above embodiment can be completed by instructing the relevant hardware through a computer program. The computer program includes program instructions, and the computer program can be stored in a storage medium, which is a computer-readable storage medium. The program instructions are executed by at least one processor in the computer system to implement the process steps of the embodiment of the above method.

[0181] Therefore, the present invention also provides a storage medium. The storage medium may be a computer-readable storage medium. The storage medium stores a computer program, wherein when the computer program is executed by a processor, the processor executes the following steps:

[0182] Acquire the data transmitted on the API interface to obtain the data to be processed; acquire the data tag defined by the terminal; acquire the URL visited by the user to obtain the URL to be associated; match the corresponding API interface to the URL to be associated, and perform association analysis on the data tag and the data to be processed to obtain the analysis result; and display the analysis result.

[0183] Among them, the data label includes definition rules for data identification, classification and grading; the data label can reference preset or customized data identification names, data classification names, data classification names, to perform data identification, data classification, and data grading on fields corresponding to the customized data identification names, data classification names, and data classification names.

[0184] In one embodiment, when the processor executes the computer program to implement the step of obtaining the data tag defined by the terminal, the processor specifically implements the following steps:

[0185] The terminal starts a browser plug-in and uses the browser plug-in to intercept request information or response information of user interaction actions; the terminal locates the URL and field corresponding to the user's access to the specified page data based on the intercepted information; the terminal defines data tags for the URL and field corresponding to the user's access to the specified page data to obtain data tags; and obtains the data tags.

[0186] In one embodiment, when the processor executes the computer program to implement the step of locating, by the terminal, the URL and field corresponding to the user accessing the designated page data according to the intercepted information, the processor specifically implements the following steps:

[0187] The terminal copies the specified data from the page accessed by the user, and performs a two-way fuzzy match with the intercepted information by using keywords or regular expressions. When the data is matched, the fields and URLs corresponding to the matched data are obtained. If the data corresponding to different fields on the page data are different, re-positioning is performed; if the data corresponding to different fields on the page data have the same value, the page interaction and positioning actions are performed again from the previous matching results to obtain the URL and fields corresponding to the page data specified by the user.

[0188] In one embodiment, when the processor executes the computer program to implement the step of matching the URL to be associated with the corresponding API interface and performing association analysis on the data tag and the data to be processed to obtain the analysis result, the processor specifically implements the following steps:

[0189] Match the corresponding API interface to the URL to be associated to obtain the target API interface; associate the field corresponding to the URL to be associated with the field corresponding to the target API interface; associate the data tags corresponding to the fields corresponding to the URL to be associated in the data tags to the fields corresponding to the target API interface to obtain an association result; generate a label list and a graph corresponding to the data to be processed collected by the target API interface based on the association result to obtain an analysis result.

[0190] Among them, the label list includes the target API interface name, user access URL, field name corresponding to the URL and data label information; the graph includes statistics on the number of API interfaces with data labels and without data labels, percentage statistics on the number of API interfaces with data labels and without data labels, data labels of the top 100 API interfaces, a trend chart of the number of API interfaces with newly added data labels drawn daily, and statistics on data label category screening.

[0191] In one embodiment, when the processor executes the computer program to implement the step of matching the URL to be associated with the corresponding API interface to obtain the target API interface, the processor specifically implements the following steps:

[0192] Perform information segmentation on the URL to be associated to obtain an access URL path; perform segmentation on the access URL path to obtain a first ordered array; perform information segmentation and path segmentation on the API interface to obtain a second ordered array; traverse the first ordered array, and compare the values ​​at the same position of the first ordered array with the second ordered array to determine the API interface that is successfully matched by the URL to be associated; mark the API interface that is successfully matched by the URL to be associated to obtain a target API interface.

[0193] The storage medium may be a USB flash drive, a mobile hard disk, a read-only memory (ROM), a magnetic disk, or an optical disk, etc., which are computer-readable storage media that can store program codes.

[0194] Those of ordinary skill in the art will appreciate that the units and algorithm steps of each example described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, computer software, or a combination of the two. In order to clearly illustrate the interchangeability of hardware and software, the composition and steps of each example have been generally described in terms of function in the above description. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Professional and technical personnel can use different methods to implement the described functions for each specific application, but such implementation should not be considered to be beyond the scope of the present invention.

[0195] In the several embodiments provided by the present invention, it should be understood that the disclosed devices and methods can be implemented in other ways. For example, the device embodiments described above are only schematic. For example, the division of each unit is only a logical function division, and there may be other division methods in actual implementation. For example, multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed.

[0196] The steps in the method of the embodiment of the present invention can be adjusted in order, combined and deleted according to actual needs. The units in the device of the embodiment of the present invention can be combined, divided and deleted according to actual needs. In addition, the functional units in the various embodiments of the present invention 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.

[0197] If the integrated unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a storage medium. Based on this understanding, the technical solution of the present invention is essentially or the part that contributes to the prior art, or all or part of the technical solution can be embodied in the form of a software product, and the computer software product is stored in a storage medium, including a number of instructions for a computer device (which can be a personal computer, terminal, or network device, etc.) to perform all or part of the steps of the method described in each embodiment of the present invention.

[0198] The above is only a specific embodiment of the present invention, but the protection scope of the present invention is not limited thereto. Any technician familiar with the technical field can easily think of various equivalent modifications or replacements within the technical scope disclosed by the present invention, and these modifications or replacements should be included in the protection scope of the present invention. Therefore, the protection scope of the present invention shall be based on the protection scope of the claims.

Claims

1. A method for processing featureless data, characterized in that: include: Get the data transmitted on the API interface to obtain the data to be processed; Get the data tags defined by the terminal; Get the URL visited by the user to get the URL to be associated; Matching the corresponding API interface to the URL to be associated, and performing association analysis on the data tag and the data to be processed to obtain an analysis result; presenting the analysis results; The data tag defined by the acquisition terminal includes: The terminal starts a browser plug-in, and uses the browser plug-in to intercept request information or response information of user interaction actions; The terminal locates the URL and field corresponding to the user's access to the specified page data based on the intercepted information; The terminal defines the data label for the URL and field corresponding to the page data designated by the user to obtain the data label; Obtaining the data label; The matching of the to-be-associated URL to a corresponding API interface and the association analysis of the data tag and the to-be-processed data to obtain an analysis result include: Match the corresponding API interface to the URL to be associated to obtain the target API interface; Associating the field corresponding to the URL to be associated with the field corresponding to the target API interface; Associating the data tag corresponding to the field corresponding to the to-be-associated URL in the data tag with the field corresponding to the target API interface to obtain an association result; A label list and a graph corresponding to the data to be processed collected by the target API interface are generated according to the association result to obtain an analysis result.

2. The method for processing featureless data according to claim 1, characterized in that: The terminal locates the URL and field corresponding to the page data designated by the user according to the intercepted information, including: The terminal copies the specified data from the page accessed by the user, and performs a two-way fuzzy match with the intercepted information by using keywords or regular expressions. When the data is matched, the fields and URLs corresponding to the matched data are obtained. If the data corresponding to different fields on the page data are different, re-positioning is performed; if the data corresponding to different fields on the page data have the same value, the page interaction and positioning actions are performed again from the previous matching results to obtain the URL and fields corresponding to the page data specified by the user.

3. The method for processing featureless data according to claim 1, characterized in that: The data tag includes definition rules for data identification, classification and grading; the data tag can reference preset or customized data identification names, data classification names, and data grading names to identify, classify and grade the fields corresponding to the customized data identification names, data classification names and data grading names.

4. The method for processing featureless data according to claim 1, characterized in that: The step of matching the corresponding API interface to the URL to be associated to obtain the target API interface includes: Segmenting the information of the URL to be associated to obtain an access URL path; Segmenting the access URL path to obtain a first ordered array; Performing information segmentation and path segmentation on the API interface to obtain a second ordered array; Traversing the first ordered array, and comparing the values ​​at the same position of the first ordered array with the values ​​at the second ordered array, to determine the API interface successfully matched by the URL to be associated; The API interface successfully matched by the URL to be associated is marked to obtain the target API interface.

5. The method for processing featureless data according to claim 1, characterized in that: The tag list includes the target API interface name, user access URL, field name corresponding to the URL, and data tag information; the graph includes statistics on the number of API interfaces with data tags and without data tags, percentage statistics on the number of API interfaces with data tags and without data tags, data tags of the top 100 API interfaces, a trend chart of the number of API interfaces with newly added data tags drawn daily, and statistics on data tag category screening.

6. A featureless data processing device, characterized in that: include: A data acquisition unit is used to acquire data transmitted on the API interface to obtain data to be processed; A label acquisition unit, used to acquire a data label defined by a terminal; A URL acquisition unit is used to acquire the URL accessed by the user to obtain the URL to be associated; An association unit, used to match the URL to be associated with a corresponding API interface, and perform association analysis on the data tag and the data to be processed to obtain an analysis result; A display unit, used to display the analysis result; A tag acquisition unit, used to start the browser plug-in by the terminal, and use the browser plug-in to intercept the request information or response information of the user interaction action; The terminal locates the URL and field corresponding to the user's access to the specified page data based on the intercepted information; The terminal defines the data label for the URL and field corresponding to the page data designated by the user to obtain the data label; Obtaining the data label; The association unit includes a matching subunit, a field association subunit, a tag association subunit and an analysis subunit; A matching subunit, used to match the corresponding API interface to the URL to be associated, so as to obtain a target API interface; A field association subunit, used to associate the field corresponding to the URL to be associated with the field corresponding to the target API interface; The tag association subunit is used to associate the data tag corresponding to the field corresponding to the to-be-associated URL in the data tag with the field corresponding to the target API interface to obtain an association result; The analysis subunit is used to generate a label list and a graph corresponding to the data to be processed collected by the target API interface according to the association result to obtain the analysis result.

7. A computer device, characterized in that: The computer device comprises a memory and a processor, the memory stores a computer program, and the processor implements the method according to any one of claims 1 to 5 when executing the computer program.

8. A storage medium, characterized in that: The storage medium stores a computer program, and when the computer program is executed by a processor, the method according to any one of claims 1 to 5 can be implemented.

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