A data transparent transmission cracking system and method based on a strategy mode and a proxy mode

Abstract

The application relates to the technical field of transparent data transmission, and particularly discloses a data transparent transmission cracking system and method based on a strategy mode and a proxy mode, the method comprising the following steps: receiving original transparent data, obtaining the data structure of the original transparent data, and generating a structure record table; based on the structure record table, updating an analysis strategy at a fixed time, converting the original transparent data into unified format data based on the analysis strategy; monitoring the conversion process of the original transparent data in real time, and updating the analysis strategy again according to the monitoring result; and constructing a transparent channel of the analysis strategy based on the data frequency item. Through the use of the strategy mode, the flexibility and the expansibility of data processing are realized. Different data formats can correspond to different strategy classes, so that compatible processing of various data formats is realized.

Description

Technical Field

[0001] This invention relates to the field of transparent data transmission technology, specifically a data transparent transmission brute-force system and method based on strategy and proxy modes. Background Technology

[0002] Existing technologies have certain compatibility limitations when processing transparent data in different formats. Since different upstream systems may use different data formats and communication protocols, additional parsers or format conversions are required, increasing the complexity of system development and maintenance.

[0003] Expanding system functionality and integrating new upstream and downstream data transmission and credential stuffing channels requires significant modifications and adjustments to existing systems, resulting in a large workload and low efficiency. This limits the system's flexibility and scalability in rapidly changing business environments.

[0004] Existing technologies often require writing a large amount of code and logic when dealing with complex pass-through brute-force attack systems, leading to reduced system maintainability. Long-term maintenance and improvement of the system may face difficulties and risks.

[0005] Existing technologies may pose security risks during data pass-through and credential stuffing attacks. Failure to adequately verify and filter the pass-through data may lead to malicious attacks or unauthorized access, resulting in risks such as data leaks or system crashes.

[0006] In summary, existing technologies have objective drawbacks in terms of compatibility, scalability, maintenance difficulties, and security. Summary of the Invention

[0007] The purpose of this invention is to provide a data pass-through credential stuffing system and method based on strategy pattern and proxy pattern, so as to solve the problems mentioned in the background art.

[0008] To achieve the above objectives, the present invention provides the following technical solution:

[0009] A data pass-through credential stuffing method based on strategy and proxy patterns, the method comprising:

[0010] Receive raw transparent data, obtain the data structure of the raw transparent data, and generate a structure record table; the structure record table includes data structure items and data count items.

[0011] Based on the structure record table, a parsing strategy is updated periodically, and the original transparent data is converted into data in a unified format based on the parsing strategy.

[0012] The conversion process of the original transparent data is monitored in real time, and the parsing strategy is updated a second time based on the monitoring results;

[0013] A pass-through channel for constructing a parsing strategy is built based on the data frequency item.

[0014] As a further aspect of the present invention: the steps of receiving the original transparent data, obtaining the data structure of the original transparent data, and generating a structure record table include:

[0015] Establish a connection channel with the downstream system, and insert a data enhancement node into the connection channel; the data enhancement node is used to intercept, record and verify the original transparent data;

[0016] The raw transparent data is received based on the connection channel, and the raw transparent data is processed through the data enhancement node.

[0017] Obtain the data structure of the raw transparent data, record the frequency of occurrence of each data structure, and generate a structure record table;

[0018] During the process of acquiring the data structure of the raw transparent data, the performance parameters of the channel are monitored in real time and logs are generated.

[0019] As a further aspect of the present invention: the step of periodically updating the parsing strategy based on the structure record table, and converting the original transparent data into unified format data based on the parsing strategy, includes:

[0020] Count the number of data points and their intervals of change for each data structure;

[0021] Based on the frequency of the statistical data at the aforementioned variation intervals, a frequency curve is obtained;

[0022] The frequency curves are analyzed to obtain data characteristics, including multi-order derivative characteristics.

[0023] When the data features meet the preset data conditions, the parsing strategy is updated;

[0024] The original transparent data is converted into a unified format data based on the latest parsing strategy.

[0025] As a further aspect of the present invention: the step of real-time monitoring of the conversion process of the original transparent transmission data and updating the parsing strategy a second time based on the monitoring results includes:

[0026] Real-time monitoring of the conversion process of raw transparent data, and calculation of resource consumption;

[0027] Based on the similarity of the data structures, compare the resource consumption and calculate the consumption difference.

[0028] The anomaly conversion process is based on the consumption difference and similarity markers;

[0029] The parsing strategy for the abnormal conversion process is updated a second time.

[0030] As a further aspect of the present invention: the step of constructing the pass-through channel of the parsing strategy based on the data frequency item includes:

[0031] Read the number of data items within a preset time period;

[0032] When the number of data transmissions reaches a preset threshold, a pass-through channel corresponding to the parsing strategy is constructed, with one pass-through channel corresponding to one parsing strategy.

[0033] The present invention also provides a data pass-through credential stuffing system based on strategy pattern and proxy pattern, the system comprising:

[0034] The record table generation module is used to receive raw transparent data, obtain the data structure of the raw transparent data, and generate a structured record table; the structured record table includes data structure items and data count items.

[0035] The format unification module is used to periodically update the parsing strategy based on the structure record table, and convert the original transparent data into unified format data based on the parsing strategy.

[0036] The strategy update module is used to monitor the conversion process of the original transparent data in real time and update the parsing strategy a second time based on the monitoring results.

[0037] The channel creation module is used to construct a transparent channel for the parsing strategy based on the data count item.

[0038] As a further aspect of the present invention: the record table generation module includes:

[0039] A node insertion unit is used to establish a connection channel with the downstream system and insert a data enhancement node into the connection channel; the data enhancement node is used to intercept, record and verify the original transparent data;

[0040] The data processing unit is used to receive raw transparent data based on the connection channel and process the raw transparent data through the data enhancement node;

[0041] The frequency statistics unit is used to obtain the data structure of the raw transparent data, record the occurrence frequency of various data structures, and generate a structure record table.

[0042] During the process of acquiring the data structure of the raw transparent data, the performance parameters of the channel are monitored in real time and logs are generated.

[0043] As a further aspect of the present invention: the format unification module includes:

[0044] Statistical unit, used to count the number of data points and their intervals of change in each data structure;

[0045] The frequency analysis unit is used to obtain a frequency curve based on the frequency of the statistical data according to the variation interval;

[0046] The curve analysis unit is used to analyze the exponential curve to obtain data features; the data features include multi-order derivative features.

[0047] The strategy update unit is used to update the parsing strategy when the data features meet the preset data conditions;

[0048] An execution unit is used to convert the original transparent data into unified format data based on the latest parsing strategy.

[0049] As a further aspect of the present invention: the strategy update module includes:

[0050] The monitoring and computing unit is used to monitor the conversion process of the raw transparent data in real time and calculate the resource consumption.

[0051] The comparison calculation unit is used to compare resource consumption based on the similarity of data structures and calculate the consumption difference.

[0052] A process marking unit is used to mark abnormal conversion processes based on consumption differences and similarity.

[0053] The update execution unit is used to perform a secondary update on the parsing strategy for the exception conversion process.

[0054] As a further aspect of the present invention: the channel creation module includes:

[0055] The data reading unit is used to read the number of data items within a preset time period;

[0056] An execution unit is constructed to construct a transparent transmission channel corresponding to the parsing strategy when the number of data transmissions reaches a preset threshold. One transparent transmission channel corresponds to one parsing strategy.

[0057] Compared with existing technologies, the beneficial effects of this invention are as follows: This invention achieves flexibility and scalability in data processing by using the strategy pattern. Different data formats can correspond to different strategy classes, thus achieving compatible processing of various data formats. By using the proxy pattern, proxy management of system functions is achieved. Proxy objects can insert new functions, add restrictions, etc., to better control access to and operation of real system functions. By using the template method pattern, the data pass-through process is unified and standardized. The data pass-through process is defined in the abstract class, and some methods that need to be implemented by subclasses are left out to ensure the sequence and consistency of the process. By using the factory pattern, the ability to quickly connect to new upstream and downstream pass-through and credential stuffing channels is achieved. Concrete factory classes can create corresponding channel objects according to different upstream channels and uniformly manage the upstream channels and the process of connecting to new channels. Attached Figure Description

[0058] To more clearly illustrate the technical solutions in the embodiments of the present invention, the accompanying drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of the present invention.

[0059] Figure 1 This is a flowchart of a data pass-through credential stuffing method based on the strategy pattern and the proxy pattern.

[0060] Figure 2 This is the data pass-through process.

[0061] Figure 3 This is a block diagram of the structure of a data pass-through brute-force attack system based on the strategy pattern and the proxy pattern. Detailed Implementation

[0062] To make the technical problems to be solved, the technical solutions, and the beneficial effects of the present invention clearer, the present invention will be further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative of the present invention and are not intended to limit the present invention.

[0063] Please see Figure 1 In this embodiment of the invention, a data pass-through credential stuffing method based on strategy pattern and proxy pattern is provided, the method comprising:

[0064] Receive raw transparent data, obtain the data structure of the raw transparent data, and generate a structure record table; the structure record table includes data structure items and data count items.

[0065] Based on the structure record table, a parsing strategy is updated periodically, and the original transparent data is converted into data in a unified format based on the parsing strategy.

[0066] The conversion process of the original transparent data is monitored in real time, and the parsing strategy is updated a second time based on the monitoring results;

[0067] A pass-through channel for constructing a parsing strategy is built based on the data frequency item.

[0068] Existing solutions are typically designed for data pass-through brute-force attack systems, and mainly include the following steps:

[0069] 1. Data Reception: The system receives data pass-through requests from upstream sources through different communication protocols (such as HTTP, TCP / IP, etc.). These requests may be encoded in different formats (such as JSON, XML, etc.).

[0070] 2. Data Parsing: The received data needs to be parsed to extract key information and then organized and stored according to the system's internal data model. This step typically requires writing parsers for different data formats or using specialized parsing tools.

[0071] 3. Data Processing: The parsed data needs to undergo a series of processing operations, including data cleaning, validation, transformation, and calculation. Depending on business needs, data filtering, screening, or aggregation may also be required.

[0072] 4. Data Storage: The processed data needs to be stored in a database or other persistent storage medium for subsequent query and analysis operations. Storage solutions can be selected based on the specific scenario, such as relational databases or NoSQL databases.

[0073] 5. Data Transmission: The system may need to transmit processed data to downstream systems or other business modules. This step typically involves data format conversion and data exchange protocol adaptation to ensure that the data can be correctly received and processed by the downstream system.

[0074] Existing technologies have been widely used in the field of data pass-through and brute-force attacks, but they also have some limitations. For example, different parsers or specialized parsing tools are needed for data pass-through in different formats, increasing the difficulty of development and maintenance. Expanding system functions and connecting to new upstream and downstream data pass-through and brute-force attack channels require extensive modifications to system processes, resulting in a large workload and low efficiency. Therefore, the technical solution provided in this patent aims to overcome these limitations and reach the top level in the industry.

[0075] In one embodiment of the technical solution of the present invention, it includes a transparent data receiving module, a transparent data processing module, and an upstream data transparent channel docking module, as detailed below:

[0076] The transparent data receiving module possesses unified system function enhancement capabilities, employing a design combining policy and proxy patterns. This combined design makes the system's data reception and processing more flexible, scalable, and secure. Through unified system function enhancement, we can provide efficient and reliable transparent data processing capabilities, meeting diverse business needs and ensuring stable system operation.

[0077] The pass-through data processing module employs a design combining the strategy pattern and the template method pattern to process pass-through data in different formats. This design minimizes changes when adding new pass-through types. The combination of these patterns enables the module to efficiently and flexibly handle various pass-through data formats with minimal modifications. This facilitates system scalability and maintainability while ensuring the uniformity and standardization of the pass-through data processing procedure.

[0078] The upstream data pass-through channel integration module employs a design combining the strategy and factory patterns. It integrates with different pass-through channels and can select the appropriate strategy for processing as needed. This combined approach allows the module to choose the appropriate strategy for different pass-through channels and achieves unified management of strategy objects. Thus, when adding, modifying, or deleting pass-through channels, only the corresponding strategy classes and configurations need to be added, modified, or deleted, without modifying other parts of the code. This design improves the system's scalability and maintainability, making the pass-through channel integration process more flexible and controllable.

[0079] like Figure 2 As shown, the interaction relationships between the three modules are as follows:

[0080] 1. The transparent data receiving module transmits the received transparent data to the transparent data processing module.

[0081] 2. The transparent data processing module further processes the transparent data before transmitting it to the upstream data transparent channel interface module.

[0082] 3. The upstream data pass-through channel docking module calls the specific channel to complete the data pass-through.

[0083] As a preferred embodiment of the technical solution of the present invention, the steps of receiving the original transparent data, obtaining the data structure of the original transparent data, and generating the structure record table include:

[0084] Establish a connection channel with the downstream system, and insert a data enhancement node into the connection channel; the data enhancement node is used to intercept, record and verify the original transparent data;

[0085] The raw transparent data is received based on the connection channel, and the raw transparent data is processed through the data enhancement node.

[0086] Obtain the data structure of the raw transparent data, record the frequency of occurrence of each data structure, and generate a structure record table;

[0087] During the process of acquiring the data structure of the raw transparent data, the performance parameters of the channel are monitored in real time and logs are generated.

[0088] In one example of the technical solution of this invention, the function of the transparent data receiving module is described as follows:

[0089] Data Reception: The transparent data receiving module establishes a connection with the downstream system to acquire raw transparent data. Through the application of a proxy mode, this module can enhance the data reception process by intercepting, recording, and verifying data, ensuring data security and reliability.

[0090] Data parsing strategy: The transparent data receiving module defines a series of parsing strategies based on different data formats. These strategies include parsing algorithms and rules. By applying the strategy pattern, the system can select an appropriate parsing strategy at runtime based on configuration or parameters, flexibly processing transparent data of different formats.

[0091] Parsing Result Conversion: The transparent data receiving module converts the parsed data into a unified internal data structure. In this process, the use of a proxy pattern enhances system functionality, enabling operations such as data format validation, data conversion, and data merging.

[0092] System Functionality Enhancement: The transparent data receiving module intercepts and enhances the data receiving process through a proxy model, allowing the addition of extra functional modules such as logging, performance monitoring, and exception handling. This enables unified system functionality enhancement while receiving data, improving system maintainability and scalability.

[0093] Furthermore, regarding the transparent data processing module, the specific details are as follows:

[0094] Strategy Pattern: The pass-through data processing module uses the strategy pattern to handle pass-through data of different formats. It defines an abstract strategy interface, and each concrete data processing strategy class implements this interface and is responsible for processing pass-through data of a specific format. Based on the required processing strategy, the module can select the appropriate strategy for processing according to the data format. Processing a new pass-through type only requires adding a new concrete strategy class and specifying the strategy in the configuration; no modification to existing code is necessary.

[0095] Template Method Pattern: The pass-through data processing module uses the Template Method pattern to control the data pass-through process. It defines an abstract template method that standardizes and encapsulates the entire process of processing pass-through data, and defines some variable steps or hook methods for concrete strategy classes to implement. In this way, during data processing, the template method calls the various steps or hook methods in a predefined order, ensuring that the processing flow of pass-through data remains consistent.

[0096] Minimal Modification Principle: The design of the pass-through data processing module takes into account the principle of minimal modification when adding different pass-through types. By adopting the strategy pattern and template method pattern, adding a new pass-through type only requires implementing the corresponding processing strategy class and specifying the strategy in the configuration. Since the module has already defined the processing flow and specifications, adding different pass-through types does not require modifying the core code of the module, thus achieving the goal of minimal modification.

[0097] The design of the pass-through data processing module, which combines the strategy pattern and the template method pattern, enables the module to efficiently and flexibly process pass-through data of different formats, with minimal modifications when adding new pass-through types. This facilitates the system's scalability and maintainability, while also ensuring the uniformity and standardization of the pass-through data processing procedure.

[0098] As a preferred embodiment of the technical solution of the present invention, the step of converting the original transparent data into unified format data based on the parsing strategy of the structure record table periodically updating the parsing strategy includes:

[0099] Count the number of data points and their intervals of change for each data structure;

[0100] Based on the frequency of the statistical data at the aforementioned variation intervals, a frequency curve is obtained;

[0101] The frequency curves are analyzed to obtain data characteristics, including multi-order derivative characteristics.

[0102] When the data features meet the preset data conditions, the parsing strategy is updated;

[0103] The original transparent data is converted into a unified format data based on the latest parsing strategy.

[0104] In one example of the technical solution of the present invention, the updating process of the parsing strategy is specifically described. The parsing strategy corresponds to each data structure. When the data of a certain data structure appears many times and its changes are relatively drastic (reflected by the derivative characteristics), the parsing strategy is updated.

[0105] As a preferred embodiment of the technical solution of the present invention, the step of real-time monitoring of the conversion process of the original transparent transmission data and updating the parsing strategy a second time based on the monitoring results includes:

[0106] Real-time monitoring of the conversion process of raw transparent data, and calculation of resource consumption;

[0107] Based on the similarity of the data structures, compare the resource consumption and calculate the consumption difference.

[0108] The anomaly conversion process is based on the consumption difference and similarity markers;

[0109] The parsing strategy for the abnormal conversion process is updated a second time.

[0110] The above content further defines the update process of the parsing strategy. The principle is that by monitoring the conversion process of the original transparent data in real time, the amount of resources consumed can be calculated, which is called resource consumption. Based on this, if the data structures of two data are similar, then under the same superior parsing strategy, the resource consumption of the two should be similar. If the resource consumption of any parsing strategy is high, it means that the corresponding parsing strategy is not "good" enough, and at this time, it needs to be updated.

[0111] As a preferred embodiment of the technical solution of the present invention, the step of constructing a transparent transmission channel based on the data frequency item includes:

[0112] Read the number of data items within a preset time period;

[0113] When the number of data transmissions reaches a preset threshold, a pass-through channel corresponding to the parsing strategy is constructed, with one pass-through channel corresponding to one parsing strategy.

[0114] The above content imposes limitations on the upstream data pass-through module, as follows:

[0115] The upstream data pass-through channel integration module is designed using a combination of strategy and factory patterns to integrate with different pass-through channels and select the appropriate strategy for processing as needed. The following is a description of this module:

[0116] Strategy Pattern: The upstream data pass-through channel integration module uses the strategy pattern to handle different pass-through channels. It defines an abstract strategy interface, and each concrete strategy class implements this interface and is responsible for integrating with the specific pass-through channel. Based on the required pass-through channel, the module can select the appropriate integration method according to the strategy. In this way, adding, modifying, or deleting pass-through channels only requires adding, modifying, or deleting the corresponding strategy class, without affecting other parts of the code.

[0117] Factory Pattern: The upstream data pass-through channel integration module uses the factory pattern to uniformly manage the creation of strategy objects. It defines a factory class responsible for selecting the appropriate strategy object based on configuration or parameters and returning it to the caller. The factory class can dynamically create different strategy objects as needed, thereby achieving unified management and flexible switching of strategies.

[0118] By employing a design combining the strategy and factory patterns, the upstream data pass-through channel integration module can select the appropriate strategy for processing different pass-through channels and achieve unified management of strategy objects. Thus, when adding, modifying, or deleting pass-through channels, only the corresponding strategy classes and configurations need to be added, modified, or deleted, without modifying other parts of the code. This design improves the system's scalability and maintainability, making the pass-through channel integration process more flexible and controllable.

[0119] Please see Figure 3 In this embodiment of the invention, a data pass-through credential stuffing system 10 based on strategy pattern and proxy pattern is provided. The system 10 includes:

[0120] The record table generation module 11 is used to receive raw transparent data, obtain the data structure of the raw transparent data, and generate a structure record table; the structure record table includes data structure items and data count items.

[0121] The format unification module 12 is used to periodically update the parsing strategy based on the structure record table and convert the original transparent data into unified format data based on the parsing strategy.

[0122] The strategy update module 13 is used to monitor the conversion process of the original transparent data in real time and update the parsing strategy a second time based on the monitoring results.

[0123] The channel creation module 14 is used to construct a transparent channel for the parsing strategy based on the data count item.

[0124] Furthermore, the record table generation module 11 includes:

[0125] A node insertion unit is used to establish a connection channel with the downstream system and insert a data enhancement node into the connection channel; the data enhancement node is used to intercept, record and verify the original transparent data;

[0126] The data processing unit is used to receive raw transparent data based on the connection channel and process the raw transparent data through the data enhancement node;

[0127] The frequency statistics unit is used to obtain the data structure of the raw transparent data, record the occurrence frequency of various data structures, and generate a structure record table.

[0128] During the process of acquiring the data structure of the raw transparent data, the performance parameters of the channel are monitored in real time and logs are generated.

[0129] Specifically, the format unification module 12 includes:

[0130] Statistical unit, used to count the number of data points and their intervals of change in each data structure;

[0131] The frequency analysis unit is used to obtain a frequency curve based on the frequency of the statistical data according to the variation interval;

[0132] The curve analysis unit is used to analyze the exponential curve to obtain data features; the data features include multi-order derivative features.

[0133] The strategy update unit is used to update the parsing strategy when the data features meet the preset data conditions;

[0134] An execution unit is used to convert the original transparent data into unified format data based on the latest parsing strategy.

[0135] In addition, the policy update module 13 includes:

[0136] The monitoring and computing unit is used to monitor the conversion process of the raw transparent data in real time and calculate the resource consumption.

[0137] The comparison calculation unit is used to compare resource consumption based on the similarity of data structures and calculate the consumption difference.

[0138] A process marking unit is used to mark abnormal conversion processes based on consumption differences and similarity.

[0139] The update execution unit is used to perform a secondary update on the parsing strategy for the exception conversion process.

[0140] Furthermore, the channel creation module 14 includes:

[0141] The data reading unit is used to read the number of data items within a preset time period;

[0142] An execution unit is constructed to construct a transparent transmission channel corresponding to the parsing strategy when the number of data transmissions reaches a preset threshold. One transparent transmission channel corresponds to one parsing strategy.

[0143] The beneficial effects of the technical solution of this invention are as follows:

[0144] Flexibility and scalability in data processing: By applying the strategy pattern, appropriate strategies can be selected for processing based on different data formats, thus achieving compatibility with various data formats. This allows the system to adapt to constantly changing data formats and can be quickly expanded to support more data formats by adding new strategy classes.

[0145] Proxy management of system functions: By applying the proxy pattern, proxy objects can manage system functions on behalf of others, allowing for the insertion of new functions, the addition of restrictions, and so on. This provides better control and scalability over system functions, while also enhancing system security and maintainability.

[0146] Unified and standardized data pass-through process: By applying the template method pattern, the data pass-through process is defined, and some methods that need to be implemented by subclasses are left as examples. This ensures that the data pass-through process has a unified sequence and consistency, simplifies the development and maintenance process, and improves the stability and reliability of the system.

[0147] Rapidly integrates with new upstream and downstream channels: By applying the factory pattern, the system achieves rapid integration with upstream and downstream channels. The specific factory class creates corresponding channel objects based on different upstream channels, uniformly managing the upstream channels and the process of integrating with new channels. This allows the system to quickly adapt to different channel requirements, reduces sensitivity to changes in external systems, and improves the system's scalability and flexibility.

[0148] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of the present invention should be included within the protection scope of the present invention.

Claims

1. A data pass-through credential stuffing method based on strategy pattern and proxy pattern, characterized in that, The method includes: Receive raw transparent data, obtain the data structure of the raw transparent data, and generate a structure record table; the structure record table includes data structure items and data count items. Based on the structure record table, a parsing strategy is updated periodically, and the original transparent data is converted into data in a unified format based on the parsing strategy. The conversion process of the original transparent data is monitored in real time, and the parsing strategy is updated a second time based on the monitoring results; Based on the data frequency item, a pass-through channel for constructing the parsing strategy is built; The step of converting the original transparent data into unified format data based on the parsing strategy of the structure record table periodically updating the parsing strategy includes: Count the number of data points and their intervals of change for each data structure; Based on the frequency of the statistical data at the aforementioned variation intervals, a frequency curve is obtained; The frequency curves are analyzed to obtain data characteristics, including multi-order derivative characteristics. When the data features meet the preset data conditions, the parsing strategy is updated; The original transparent data is converted into a unified format data based on the latest parsing strategy; The steps for constructing the parsing strategy based on the data frequency item include: Read the number of data items within a preset time period; When the number of data transmissions reaches a preset threshold, a pass-through channel corresponding to the parsing strategy is constructed, with one pass-through channel corresponding to one parsing strategy.

2. The data pass-through credential stuffing method based on strategy pattern and proxy pattern according to claim 1, characterized in that, The steps of receiving raw transparent data, obtaining the data structure of the raw transparent data, and generating a structure record table include: Establish a connection channel with the downstream system, and insert a data enhancement node into the connection channel; the data enhancement node is used to intercept, record and verify the original transparent data; The raw transparent data is received based on the connection channel, and the raw transparent data is processed through the data enhancement node. Obtain the data structure of the raw transparent data, record the frequency of occurrence of each data structure, and generate a structure record table; During the process of acquiring the data structure of the raw transparent data, the performance parameters of the channel are monitored in real time and logs are generated.

3. The data pass-through credential stuffing method based on strategy pattern and proxy pattern according to claim 1, characterized in that, The real-time monitoring process of converting raw transparent data, and the step of updating the parsing strategy based on the monitoring results, includes: Real-time monitoring of the conversion process of raw transparent data, and calculation of resource consumption; Based on the similarity of the data structures, compare the resource consumption and calculate the consumption difference. The anomaly conversion process is based on the consumption difference and similarity markers; The parsing strategy for the abnormal conversion process is updated a second time.

4. A data pass-through credential stuffing system based on strategy pattern and proxy pattern, characterized in that, The system includes: The record table generation module is used to receive raw transparent data, obtain the data structure of the raw transparent data, and generate a structured record table; the structured record table includes data structure items and data count items. The format unification module is used to periodically update the parsing strategy based on the structure record table, and convert the original transparent data into unified format data based on the parsing strategy. The strategy update module is used to monitor the conversion process of the original transparent data in real time and update the parsing strategy a second time based on the monitoring results. The channel creation module is used to construct a transparent channel for parsing strategies based on the data frequency item; The format unification module includes: Statistical unit, used to count the number of data points and their intervals of change in each data structure; The frequency analysis unit is used to obtain a frequency curve based on the frequency of the statistical data according to the variation interval; The curve analysis unit is used to analyze the exponential curve to obtain data features; the data features include multi-order derivative features. The strategy update unit is used to update the parsing strategy when the data features meet the preset data conditions; An execution unit is used to convert the original transparent data into unified format data based on the latest parsing strategy; The channel creation module includes: The data reading unit is used to read the number of data items within a preset time period; An execution unit is constructed to construct a transparent transmission channel corresponding to the parsing strategy when the number of data transmissions reaches a preset threshold. One transparent transmission channel corresponds to one parsing strategy.

5. The data pass-through credential stuffing system based on strategy pattern and proxy pattern according to claim 4, characterized in that, The record table generation module includes: A node insertion unit is used to establish a connection channel with the downstream system and insert a data enhancement node into the connection channel; the data enhancement node is used to intercept, record and verify the original transparent data; The data processing unit is used to receive raw transparent data based on the connection channel and process the raw transparent data through the data enhancement node; The frequency statistics unit is used to obtain the data structure of the raw transparent data, record the occurrence frequency of various data structures, and generate a structure record table. During the process of acquiring the data structure of the raw transparent data, the performance parameters of the channel are monitored in real time and logs are generated.

6. The data pass-through credential stuffing system based on strategy pattern and proxy pattern according to claim 4, characterized in that, The policy update module includes: The monitoring and computing unit is used to monitor the conversion process of the raw transparent data in real time and calculate the resource consumption. The comparison calculation unit is used to compare resource consumption based on the similarity of data structures and calculate the consumption difference. A process marking unit is used to mark abnormal conversion processes based on consumption differences and similarity. The update execution unit is used to perform a secondary update on the parsing strategy for the exception conversion process.

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