Data processing method and device, equipment and storage medium

Abstract

The invention provides a data processing method and device, equipment and a storage medium, and relates to the field of financial science and technology or other related fields. The method comprises the following steps: acquiring a business event performed by a user in a browser, extracting user behavior characteristics according to the business event, performing risk judgment on the user behavior characteristics based on a binary module deployed in the browser to generate a judgment result, and controlling the business operation process of the business event in the browser according to the judgment result. Risk judgment is executed locally in the browser, network transmission is avoided, the real-time response capacity of risk control judgment is effectively improved, the high-timeliness service scene requirement is met, risk control logic is packaged in an irreversible binary module, rule confidentiality is enhanced, user behavior characteristics are locally processed by the browser, uploading to a server is not needed, and user experience is improved. And the data minimization principle is met, and the privacy protection capability is improved.

Description

Technical Field

[0001] This application relates to the field of financial technology or other related fields, and in particular to a data processing method, apparatus, device and storage medium. Background Technology

[0002] In the financial sector, for high-risk business scenarios such as user identity verification, payment transactions, and loan applications, current mainstream financial risk control systems are generally deployed on the backend. The main process includes: the frontend page collects user behavior data such as IP address, device fingerprint, and input content, and sends the collected data to the backend server through an HTTP interface. The backend risk control engine parses the data and performs risk assessment based on preset rules or models, and then returns the judgment result for the frontend page to provide prompts or restrict operations, such as refusing login or blocking transactions.

[0003] While backend risk control offers the advantage of centralized and unified management, it also has several shortcomings. For example, user actions must be transmitted over the network, leading to delays in judgment and an inability to immediately intercept malicious behavior, resulting in poor real-time performance and failing to meet some business needs. Furthermore, data collected by the frontend may be tampered with or hijacked during transmission, resulting in low security. Additionally, uploading all behavioral data to the server may involve user privacy information, violating the principle of data minimization and demonstrating insufficient privacy protection capabilities.

[0004] It is evident that a risk control method is urgently needed to overcome the aforementioned shortcomings of existing technologies in high-risk business scenarios within the financial industry. Summary of the Invention

[0005] This application provides a data processing method, apparatus, device, and storage medium to solve the technical problems of poor real-time performance, low security, and insufficient privacy protection capabilities in existing back-end risk control systems.

[0006] Firstly, this application provides a data processing method, including:

[0007] Obtain the business events performed by the user in the browser, and extract user behavior features based on the business events;

[0008] The binary module deployed in the browser performs risk assessment on the user behavior characteristics and generates assessment results. The binary module includes risk control rules and risk assessment algorithms.

[0009] Based on the judgment result, the browser controls the business operation process of the business event.

[0010] Secondly, this application provides a data processing apparatus, comprising:

[0011] The acquisition module is used to acquire business events performed by the user in the browser and extract user behavior features based on the business events.

[0012] The risk assessment module is used to assess the user's behavioral characteristics based on a binary module deployed in the browser and generate a assessment result. The binary module includes risk control rules and risk assessment algorithms.

[0013] The business control module is used to control the business operation process of the business event in the browser based on the judgment result.

[0014] Thirdly, this application provides an electronic device, including: a processor, and a memory communicatively connected to the processor;

[0015] The memory stores computer-executed instructions;

[0016] The processor executes computer execution instructions stored in the memory to implement the method described in the first aspect.

[0017] Fourthly, this application provides a computer-readable storage medium storing computer-executable instructions, which, when executed by a processor, are used to implement the method described in the first aspect.

[0018] Fifthly, this application provides a computer program product, including a computer program that, when executed by a processor, implements the method described in the first aspect.

[0019] This application provides a data processing method, apparatus, device, and storage medium. First, it acquires business events performed by a user in a browser, extracts user behavioral features based on these events, and then performs risk assessment on these user behavioral features using a binary module deployed in the browser, generating a assessment result. This binary module is irreversible and includes risk control rules and a risk assessment algorithm. Finally, based on the assessment result, it controls the business operation process of the business events within the browser. The process involves acquiring user business events in the browser, extracting user behavioral features, and then performing risk assessment on these features using a risk control engine built in the browser based on an irreversible binary module. The assessment result is then returned to control the corresponding business operation process. Performing risk assessment locally in the browser avoids network transmission, effectively improving the real-time response capability of risk control assessment to meet the needs of high-efficiency business scenarios. Furthermore, encapsulating the risk control logic in an irreversible binary module enhances rule confidentiality. In addition, processing user behavioral features locally in the browser eliminates the need to upload to a server, conforming to the principle of data minimization and improving privacy protection capabilities. Attached Figure Description

[0020] The accompanying drawings, which are incorporated in and form part of this specification, illustrate embodiments consistent with this application and, together with the description, serve to explain the principles of this application.

[0021] Figure 1 This application provides an illustration of the application scenario.

[0022] Figure 2 Flowchart of the data processing method provided in this application Figure 1 ;

[0023] Figure 3 Flowchart of the data processing method provided in this application Figure 2 ;

[0024] Figure 4 Schematic diagram of the data processing apparatus provided in this application Figure 1 ;

[0025] Figure 5 Schematic diagram of the data processing apparatus provided in this application Figure 2 ;

[0026] Figure 6 A schematic diagram of the electronic device structure provided in this application.

[0027] The accompanying drawings have illustrated specific embodiments of this application, which will be described in more detail below. These drawings and descriptions are not intended to limit the scope of the concept in any way, but rather to illustrate the concept of this application to those skilled in the art through reference to specific embodiments. Detailed Implementation

[0028] Exemplary embodiments will now be described in detail, examples of which are illustrated in the accompanying drawings. When the following description relates to the drawings, unless otherwise indicated, the same numbers in different drawings denote the same or similar elements. The embodiments described in the following exemplary embodiments do not represent all embodiments consistent with this application. Rather, they are merely examples of apparatuses and methods consistent with some aspects of this application as detailed in the appended claims.

[0029] It should be noted that the user information (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data used for analysis, data stored, data displayed, etc.) involved in this application are all information and data authorized by the user or fully authorized by all parties. Furthermore, the collection, storage, use, processing, transmission, provision, disclosure, and application of the relevant data all comply with the relevant laws, regulations, and standards of the relevant countries and regions, have taken necessary confidentiality measures, do not violate public order and good morals, and provide corresponding operation access points for users to choose to authorize or refuse.

[0030] Furthermore, the technical solution involved in this application, which involves big data analysis of user information (including but not limited to personal biometrics, identity data, consumption data, asset data, electronic terminal operation data, etc.) and the use of artificial intelligence technology for automated decision-making, and makes decisions that have a significant impact on personal rights based on the results of automated decision-making, provides users with corresponding operation entry points for users to choose to agree to or reject the results of automated decision-making; if the user chooses to reject, the process will proceed to the expert decision-making process.

[0031] It should be noted that the data processing methods, apparatus, devices and storage media provided in this application can be used in the field of fintech or other related fields, or in any field other than fintech or other related fields. The application fields of the data processing methods, apparatus, devices and storage media in this application are not limited.

[0032] Figure 1 The application scenario diagram provided in this application is as follows: Figure 1 As shown, in business scenarios such as user authentication, payment transactions, and loan applications at financial institutions 10, users perform business operations on the browser side 20 through web pages, mobile H5 pages, etc. The financial risk control system needs to analyze user behavior characteristics in real time to determine whether there are abnormal behaviors, such as automated script operations, fake identity registration, and malicious payments. Currently, most mainstream financial risk control systems are deployed on the backend. Although backend risk control has the advantage of centralized and unified management, its reliance on network communication architecture leads to high response latency and makes it difficult to handle scenarios that require local real-time judgment, such as intercepting the immediate operation of malicious scripts. In addition, data collected on the frontend may be tampered with or hijacked during transmission, resulting in high rule transparency but low security. Furthermore, all user behavior data is uploaded to the server, which may involve user privacy information, does not comply with the principle of data minimization, and has insufficient privacy protection capabilities.

[0033] To address the aforementioned problems in existing technologies, this application provides a data processing method, apparatus, device, and storage medium. The inventive concept of the data processing method provided in this application lies in: constructing a localized, real-time, and secure risk control engine on the browser side 20; by encapsulating the risk control logic into an irreversible binary module, local processing and risk assessment of user behavior characteristics are achieved, solving problems such as reliance on the backend, high response latency, high rule transparency, and insufficient privacy protection capabilities in existing technologies. Risk assessment can be performed locally on the browser side 20, avoiding network transmission, effectively improving the real-time response capability of risk control assessment to meet the needs of high-efficiency business scenarios. Furthermore, encapsulating the risk control logic in an irreversible binary module enhances rule confidentiality. In addition, user behavior characteristics are processed locally in the browser, without uploading to a server, conforming to the principle of data minimization and improving privacy protection capabilities.

[0034] The technical solution of this application and how the technical solution of this application solves the above-mentioned technical problems are described in detail below with specific embodiments. These specific embodiments can be combined with each other, and the same or similar concepts or processes may not be described again in some embodiments. The embodiments of this application will now be described with reference to the accompanying drawings.

[0035] It should be noted that the browser-side 20 can be deployed on electronic devices such as computers, laptops, tablets, smartphones, and smart wearable devices, allowing users to perform business operations through the browser. Figure 1 The browser client 20 in this application is illustrated using a computer as an example. This application does not limit the type of electronic device.

[0036] in addition, Figure 1 The application scenarios of the data processing methods provided in this application are shown only as illustrative purposes and are not intended to limit the application scenarios.

[0037] Figure 2 Flowchart of the data processing method provided in this application Figure 1 ,like Figure 2 As shown, the method includes:

[0038] S101. Obtain the business events performed by the user in the browser, and extract user behavior features based on the business events.

[0039] Users perform relevant business events in the browser, such as user login and registration, payment transactions, or loan applications on interfaces provided by financial institutions. These business events can be collected, and user behavior data can be extracted to obtain user behavior characteristics.

[0040] In one possible design, step S101 could be implemented in the following ways:

[0041] For example, the browser's data acquisition unit can be used to monitor user interactions with business events. These interactions may include, but are not limited to, at least one of the following: mouse movement, clicks, keyboard input, page dwell time, and focus switching.

[0042] Furthermore, behavioral features are extracted from the interaction on the browser locally to obtain user behavior features, which may include, but are not limited to, at least one of trajectory length, input interval, and typing rhythm.

[0043] Among them, the browser's data collection unit can transmit data between binary modules. For example, it can collect user business events through JavaScript code to obtain user behavior characteristics.

[0044] In some embodiments, the data acquisition unit can uniformly encode user behavior feature data and transmit it to the binary module for risk assessment.

[0045] The data processing method provided in this application processes user behavior characteristics locally in the browser, without uploading complete data to servers or the cloud, thus complying with data compliance requirements and enhancing privacy protection capabilities. Furthermore, it reduces data transmission volume, optimizes system resource utilization, and improves the processing efficiency of the risk control engine.

[0046] In one possible design, before listening to user interactions with business events through the browser's data acquisition unit, a separate thread can be started in the browser to execute the binary module. The separate thread is used to isolate the risk control rules and risk judgment algorithms from the browser's main thread, avoiding blocking user operations, improving page response smoothness, and allocating browser-side computing resources through multiple threads to improve overall performance and optimize resource utilization.

[0047] S102. Based on the binary module deployed in the browser, perform risk assessment on user behavior characteristics and generate assessment results.

[0048] The binary module is irreversible and includes risk control rules and risk assessment algorithms.

[0049] Based on an irreversible binary module deployed in the browser, risk assessment is performed on user behavior characteristics, and corresponding assessment results are generated. The irreversible binary module cannot be debugged, which can improve security and rule confidentiality.

[0050] In one possible design, prior to step S102, the following may also be included:

[0051] The risk control rules and risk assessment algorithms are compiled into binary modules. The binary modules have a built-in sandbox environment, which is used to isolate the binary modules from the browser's host resources and restrict their access to browser host resources such as the file system and network interfaces.

[0052] Compiling risk control rules and risk assessment algorithms into binary modules makes them undebuggable and irreversible. Furthermore, running in a sandbox environment prevents access to external resources or modification of internal logic such as risk control rules and risk assessment algorithms, thus enhancing rule security. The sandbox environment also prevents external code from interfering with the risk control logic and prevents malicious code injection.

[0053] In one possible design, step S102 could be implemented in the following ways:

[0054] User behavior characteristics are obtained from the data acquisition unit through the data input interface of the binary module. The data input interface supports cross-language interaction with the data acquisition unit.

[0055] The data acquisition unit and the data input interface have a communication bridge, enabling cross-language interaction. Therefore, the binary module's data input interface interfaces with the data acquisition unit to obtain user behavior characteristics.

[0056] In some embodiments, a unified evaluate() interface can be provided to receive user behavior data and return judgment results. The unified evaluate() interface includes a data input interface.

[0057] After obtaining user behavior characteristics, the binary module integrates risk control rules and risk judgment algorithms. The binary module executes the risk control rules and risk judgment algorithms to judge whether the user behavior characteristics have risky behaviors and obtain the corresponding judgment results. The judgment results are determined by the specific content of the risk control rules and risk judgment algorithms, which are not limited in this embodiment.

[0058] In some embodiments, risk control rules and risk assessment algorithms may include at least two or more of decision trees, threshold judgment, rule matching algorithms and scoring cards, supporting free combination and dynamic switching of multiple algorithms, which may be embedded in the binary module.

[0059] The data processing method provided in this application generates a judgment result by performing risk assessment on user behavior characteristics based on a binary module deployed in the browser. The binary module integrates risk control rules and risk assessment algorithms, which support multiple algorithm strategy combinations and dynamic switching, thereby improving the flexibility of risk control strategies. Furthermore, this lightweight risk control algorithm is also suitable for low-performance terminals, effectively reducing resource consumption and adapting to complex business scenarios.

[0060] S103. Based on the judgment result, control the business operation process of business events in the browser.

[0061] Based on the judgment results, the business process is dynamically controlled, such as blocking button submissions, pop-up prompts, and page redirects.

[0062] In one possible design, step S103 could be implemented in the following ways:

[0063] The judgment result is transmitted to the data acquisition unit through the data output interface of the binary module, so that the browser can control the business operation process based on the judgment result. Specifically, the data acquisition unit triggers the business operation instruction corresponding to the judgment result, so that the browser executes the business operation process corresponding to the business operation instruction in the business event. The business operation process includes one or more of the following: blocking button submission, pop-up prompt, and page redirection.

[0064] The business operation instructions correspond to the business operation process and the judgment result. For example, if there is no risky behavior, the business process proceeds normally. If there is risky behavior, interception buttons, pop-ups, page jumps, etc. are generated according to risk control rules and risk judgment algorithms to intercept abnormal user behavior and maintain the security of the financial system.

[0065] In some embodiments, if risky behavior is found in the generated judgment result, the risk judgment can be recorded through existing data collection channels, such as a data tracking system, for subsequent analysis, auditing, and system optimization.

[0066] The data processing method provided in this application first acquires business events performed by users in their browsers, extracts user behavior features based on these events, and then performs risk assessment on these user behavior features using a binary module deployed in the browser, generating a judgment result. This binary module is irreversible and includes risk control rules and risk assessment algorithms. Finally, based on the judgment result, the browser controls the business operation process of the business events. The method involves acquiring user business events in the browser, extracting user behavior features, and then performing risk assessment on these features using a risk control engine built in the browser based on an irreversible binary module, returning the judgment result to control the corresponding business operation process. Performing risk assessment locally in the browser avoids network transmission, effectively improving the real-time response capability of risk control judgment to meet the needs of high-efficiency business scenarios. Furthermore, encapsulating the risk control logic in an irreversible binary module enhances rule confidentiality. In addition, processing user behavior features locally in the browser eliminates the need to upload to a server, conforming to the principle of data minimization and improving privacy protection capabilities.

[0067] In one possible design, the data processing method provided in this application further includes, for example: Figure 3 The strategy shown is a hot update mechanism. Figure 3 Flowchart of the data processing method provided in this application Figure 2 ,like Figure 3 As shown, the method includes:

[0068] S201, periodically or in response to an update command, initiates a policy data update query to the remote interface.

[0069] S202. If the strategy data is updated, obtain the updated risk control rules and risk assessment algorithm through the remote interface.

[0070] The strategy data includes updated risk control rules and risk assessment algorithms.

[0071] S203. Load the updated risk control rules and risk assessment algorithm into the binary module.

[0072] In existing technologies, when risk control rules are adjusted, front-end or back-end services need to be redeployed, resulting in high update costs and slow response times. Therefore, the data processing method provided in this application proposes a hot-update mechanism for strategies.

[0073] For example, the system can actively poll periodically or passively receive update commands to initiate a strategy data update query signal to the remote interface, thereby requesting an update. If the strategy data is updated, the system retrieves the updated strategy data, such as the updated risk control rules and risk assessment algorithms, from the remote server via the remote interface and loads them into the binary module to achieve dynamic updates of the risk control logic. If the strategy is not updated, the system continues with step S201.

[0074] In some embodiments, the data format of the risk control rules and risk judgment algorithms before and after the update can be an efficient data format, such as JSON format and / or Protobuf format, which makes the update package small in size, fast in transmission speed, and facilitates efficient data exchange.

[0075] In some embodiments, when obtaining updated risk control rules and risk assessment algorithms, the updated risk control rules and risk assessment algorithms can also be transmitted in encrypted form via a remote interface to ensure rule security.

[0076] The data processing method provided in this application can proactively poll or push to trigger policy data updates without redeploying the front-end page. If an update occurs, the policy data serialized in JSON or Protobuf format is obtained through a remote interface, and the binary module is hot-loaded. This enables real-time dynamic updates and rapid iterations of risk control logic, quickly responds to changes in risk business scenarios, improves the agility of risk control, and ensures business continuity and a seamless user experience.

[0077] Figure 4 Schematic diagram of the data processing apparatus provided in this application Figure 1 ,like Figure 4 As shown, the data processing apparatus 400 provided in this application includes:

[0078] The acquisition module 401 is used to acquire business events performed by the user in the browser and extract user behavior features based on the business events.

[0079] The risk assessment module 402 is used to assess the risk of user behavior characteristics based on the binary module deployed in the browser and generate assessment results. The binary module includes risk control rules and risk assessment algorithms.

[0080] The business control module 403 is used to control the business operation process of business events in the browser based on the judgment result.

[0081] In one possible design, the data processing apparatus 400 provided in this application further includes: a compilation module, which is used for:

[0082] The risk control rules and risk assessment algorithms are compiled into binary modules. The binary modules have a built-in sandbox environment, which is used to isolate the binary modules from the browser's host resources.

[0083] exist Figure 4 On this basis, Figure 5 Schematic diagram of the data processing apparatus provided in this application Figure 2 ,like Figure 5 As shown, the data processing apparatus 400 provided in this application further includes: an update module 404, which is used for:

[0084] Periodically or in response to update commands, initiate policy data update queries to the remote interface;

[0085] If it is determined that the strategy data has been updated, the updated risk control rules and risk assessment algorithms are obtained through the remote interface. The strategy data includes the updated risk control rules and risk assessment algorithms.

[0086] The updated risk control rules and risk assessment algorithms are loaded into the binary module. The data formats of the updated risk control rules and risk assessment algorithms include JSON and / or Protobuf formats.

[0087] In one possible design, update module 404 is also used for:

[0088] The updated risk control rules and risk assessment algorithms are transmitted in encrypted form via a remote interface.

[0089] In one possible design, module 401 is specifically used for:

[0090] The browser's data acquisition unit listens to user interactions with business events, including at least one of mouse movement, clicks, keyboard input, page dwell time, and focus switching.

[0091] The user behavior features are obtained by extracting behavioral features from the interaction on the browser local. These features include at least one of the following: trajectory length, input interval, and typing rhythm.

[0092] In one possible design, the risk assessment module 402 is specifically used for:

[0093] User behavior characteristics are obtained from the data acquisition unit through the data input interface of the binary module. The data input interface supports cross-language interaction with the data acquisition unit.

[0094] The risk control rules and risk judgment algorithms are executed by the binary module to judge the risk of user behavior characteristics and obtain the corresponding judgment results. The risk control rules and risk judgment algorithms include at least two of the following: decision tree, threshold judgment, rule matching algorithm and scorecard.

[0095] In one possible design, the business control module 403 is specifically used for:

[0096] The judgment result is transmitted to the data acquisition unit through the data output interface of the binary module;

[0097] The data collection unit triggers the business operation instruction corresponding to the judgment result, causing the browser to execute the business operation process corresponding to the business operation instruction in the business event. The business operation process includes one or more of the following: intercepting button submission, pop-up prompt, and page redirection.

[0098] In one possible design, the data processing apparatus 400 provided in this application further includes: a thread control module, which is used for:

[0099] The binary module is executed in a separate thread in the browser. The separate thread is used to isolate the risk control rules and risk assessment algorithms from the browser's main thread.

[0100] The data processing apparatus provided in this application can execute the methods provided in the above-described method embodiments. Its implementation principle and technical effects are similar, and will not be described in detail here.

[0101] Figure 6 This is a schematic diagram of the electronic device structure provided in this application. Figure 6 As shown, the electronic device 50 provided in this application includes at least one processor 501 and a memory 502. Optionally, the device 50 further includes a communication component 503. The processor 501, memory 502, and communication component 503 are connected via a bus.

[0102] In a specific implementation, at least one processor 501 executes computer execution instructions stored in memory 502, causing at least one processor 501 to perform the above-described method.

[0103] The specific implementation process of processor 501 can be found in the above method embodiments, and its implementation principle and technical effect are similar. It will not be repeated here.

[0104] In the above embodiments, it should be understood that the processor can be a Central Processing Unit (CPU), or other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), etc. The general-purpose processor can be a microprocessor or any conventional processor. The steps of the method disclosed in this invention can be directly implemented by a hardware processor, or implemented by a combination of hardware and software modules within the processor.

[0105] The memory may include random access memory (RAM) and may also include non-volatile memory (NVM), such as at least one disk storage device.

[0106] The bus can be an Industry Standard Architecture (ISA) bus, a Peripheral Component Interconnect (PCI) bus, or an Extended Industry Standard Architecture (EISA) bus, etc. Buses can be categorized as address buses, data buses, control buses, etc. For ease of illustration, the buses shown in the accompanying drawings are not limited to a single bus or a single type of bus.

[0107] This application also provides a computer program product, including a computer program that, when executed by a processor, implements the above-described method.

[0108] This application also provides a computer-readable storage medium storing computer-executable instructions, which, when executed by a processor, implement the above-described method.

[0109] The aforementioned readable storage medium can be implemented by any type of volatile or non-volatile storage device or a combination thereof, such as static random access memory (SRAM), electrically erasable programmable read-only memory (EEPROM), erasable programmable read-only memory (EPROM), programmable read-only memory (PROM), read-only memory (ROM), magnetic storage, flash memory, magnetic disk, or optical disk. The readable storage medium can be any available medium accessible to a general-purpose or special-purpose computer.

[0110] An exemplary readable storage medium is coupled to a processor, enabling the processor to read information from and write information to the readable storage medium. Of course, the readable storage medium can also be a component of the processor. The processor and the readable storage medium can reside in an Application Specific Integrated Circuit (ASIC). Alternatively, the processor and the readable storage medium can exist as discrete components in the device.

[0111] It should be noted that, for the sake of simplicity, the foregoing method embodiments are all described as a series of actions. However, those skilled in the art should understand that this application is not limited to the described order of actions, as some steps may be performed in other orders or simultaneously according to this application. Furthermore, those skilled in the art should also understand that the embodiments described in the specification are all optional embodiments, and the actions and modules involved are not necessarily essential to this application.

[0112] It should be further noted that although the steps in the flowchart are shown sequentially according to the arrows, these steps are not necessarily executed in the order indicated by the arrows. Unless explicitly stated herein, there is no strict order restriction on the execution of these steps, and they can be executed in other orders. Moreover, at least some steps in the flowchart may include multiple sub-steps or multiple stages. These sub-steps or stages are not necessarily completed at the same time, but can be executed at different times. The execution order of these sub-steps or stages is not necessarily sequential, but can be performed alternately or in turn with other steps or at least some of the sub-steps or stages of other steps.

[0113] It should be understood that the above-described device embodiments are merely illustrative, and the device of this application can also be implemented in other ways. For example, the division of units / modules in the above embodiments is only a logical functional division, and there may be other division methods in actual implementation. For example, multiple units, modules, or components may be combined, or integrated into another system, or some features may be ignored or not executed.

[0114] Furthermore, unless otherwise specified, the functional units / modules in the various embodiments of this application can be integrated into one unit / module, or each unit / module can exist physically separately, or two or more units / modules can be integrated together. The integrated units / modules described above can be implemented in hardware or as software program modules.

[0115] When integrated units / modules are implemented in hardware, the hardware can be digital circuits, analog circuits, etc. The physical implementation of the hardware structure includes, but is not limited to, transistors, memristors, etc. Unless otherwise specified, the processor can be any suitable hardware processor, such as a CPU, GPU, FPGA, DSP, and ASIC, etc. Unless otherwise specified, the storage unit can be any suitable magnetic or magneto-optical storage medium, such as Resistive Random Access Memory (RRAM), Dynamic Random Access Memory (DRAM), Static Random Access Memory (SRAM), Enhanced Dynamic Random Access Memory (EDRAM), High-Bandwidth Memory (HBM), Hybrid Memory Cube (HMC), etc.

[0116] If the integrated unit / module is implemented as a software program module and sold or used as an independent product, it can be stored in a computer-readable storage device (CMD). Based on this understanding, the technical solution of this application, in essence, 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. This computer software product is stored in a memory and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods of the various embodiments of this application. The aforementioned memory includes various media capable of storing program code, such as a USB flash drive, read-only memory (ROM), random access memory (RAM), portable hard drive, magnetic disk, or optical disk.

[0117] In the above embodiments, the descriptions of each embodiment have their own emphasis. For parts not described in detail in a certain embodiment, please refer to the relevant descriptions of other embodiments. The technical features of the above embodiments can be combined arbitrarily. For the sake of brevity, not all possible combinations of the technical features in the above embodiments are described. However, as long as the combination of these technical features does not contradict each other, it should be considered within the scope of this specification.

[0118] Other embodiments of this application will readily occur to those skilled in the art upon consideration of the specification and practice of the invention disclosed herein. This application is intended to cover any variations, uses, or adaptations of this application that follow the general principles of this application and include common knowledge or customary techniques in the art not disclosed herein. The specification and examples are to be considered exemplary only, and the true scope and spirit of this application are indicated by the following claims.

[0119] It should be understood that this application is not limited to the precise structure described above and shown in the accompanying drawings, and various modifications and changes can be made without departing from its scope. The scope of this application is limited only by the appended claims.

Claims

1. A data processing method, characterized by, The method comprises the following steps: acquiring a user's business event in a browser and extracting user behavior features according to the business event; judging the user behavior features based on a binary module deployed in the browser to generate a judgment result, the binary module being irreversible and comprising risk control rules and risk judgment algorithms; controlling a business operation process of the business event in the browser according to the judgment result.

2. The method of claim 1, wherein, Before the step of judging the user behavior features based on the binary module deployed in the browser, the method further comprises the following steps: compiling the risk control rules and risk judgment algorithms into a binary module, the binary module comprising a sandbox environment, and the sandbox environment being used to isolate the binary module and host resources of the browser.

3. The method of claim 1, wherein, The method further comprises the following steps: periodically or in response to an update instruction, initiating a policy data update query to a remote interface; if it is determined that the policy data is updated, acquiring the updated risk control rules and risk judgment algorithms through the remote interface, the policy data comprising the updated risk control rules and risk judgment algorithms; loading the updated risk control rules and risk judgment algorithms into the binary module, the data format of the updated risk control rules and risk judgment algorithms comprising a JSON format and / or a Protobuf format.

4. The method of claim 3, wherein, The step of acquiring the updated risk control rules and risk judgment algorithms through the remote interface comprises the following step: performing encrypted transmission of the updated risk control rules and risk judgment algorithms through the remote interface.

5. The method according to any one of claims 1 to 4, characterized in that, The step of acquiring a user's business event in a browser and extracting user behavior features according to the business event comprises the following steps: listening to interactive operations of the user for the business event through a data collection unit of the browser, the interactive operations comprising at least one of mouse movement, clicking, keyboard input, page dwell time, and focus switching; extracting behavior features of the interactive operations locally in the browser to obtain the user behavior features, the user behavior features comprising at least one of track length, input interval, and typing rhythm.

6. The method of claim 5, wherein, The step of judging the user behavior features based on a binary module deployed in the browser to generate a judgment result comprises the following steps: acquiring the user behavior features from the data collection unit through a data input interface of the binary module, the data input interface supporting cross-language interaction with the data collection unit; performing the risk control rules and risk judgment algorithms through the binary module to judge the user behavior features and obtain the corresponding judgment result, the risk control rules and risk judgment algorithms comprising at least two of decision tree, threshold judgment, rule matching algorithm, and scoring card.

7. The method of claim 6, wherein, The step of controlling a business operation process of the business event in the browser according to the judgment result comprises the following step: transmitting the judgment result to the data collection unit through a data output interface of the binary module. Trigger a business operation instruction corresponding to the judgment result through the data acquisition unit, so that the browser executes a business operation process corresponding to the business operation instruction in the business event, and the business operation process includes one or more of intercepting button submission, pop-up window prompt, and page jump.

8. The method of claim 6, wherein, Before the data acquisition unit of the browser listens to the interactive operation of the user for the business event, it further includes: Starting an independent thread in the browser to execute the binary module, and the independent thread is used to isolate the risk control rule and risk judgment algorithm from the main thread of the browser.

9. A data processing apparatus, characterized by, It includes: An acquisition module is configured to acquire a business event performed by a user in a browser and extract user behavior features according to the business event; A risk judgment module is configured to perform risk judgment on the user behavior features based on a binary module deployed in the browser, generate a judgment result, and the binary module includes a risk control rule and a risk judgment algorithm; A business control module is configured to control a business operation process of the business event in the browser according to the judgment result.

10. An electronic device, comprising: It includes: A processor and a memory connected with the processor in communication; The memory stores computer execution instructions; The processor executes the computer execution instructions stored in the memory to realize the method of any one of claims 1 to 9.

11. A computer readable storage medium, characterized in that, The computer readable storage medium stores computer execution instructions, and the computer execution instructions are executed by the processor to realize the method of any one of claims 1 to 9.

12. A computer program product, characterised in that, It includes a computer program, which is executed by the processor to realize the method of any one of claims 1 to 9.

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