Full-link transaction risk control real-time monitoring method, system, equipment and medium

Abstract

The invention relates to a general web crawler technology and a financial science and technology, and discloses a full-link transaction risk control real-time monitoring method, which comprises the following steps: obtaining an access permission of an external application channel, obtaining multi-channel full-link data according to the access permission, performing data analysis on the multi-channel full-link data to obtain full-link data, and sending the full-link data to a server; the method comprises the following steps: receiving full-link data, performing data channel verification on the full-link data to obtain verified full-link data, performing data filtering processing on the verified full-link data to obtain filtered full-link data, performing format conversion processing on the filtered full-link data to obtain standard message data, and sending the standard message data to a server; and carrying out transaction risk analysis according to the standard message data to obtain a transaction risk analysis result, and carrying out safety early warning according to the transaction risk analysis result. The invention further provides a full-link transaction risk control real-time monitoring system, electronic equipment and a storage medium. According to the invention, the quality and efficiency of full-link transaction data acquisition can be improved.

Description

Technical Field

[0001] The present invention relates to the fields of general web crawler technology and financial technology, and in particular to a full-link transaction risk control real-time monitoring method, system, equipment and medium. Background Art

[0002] With the rapid development of information technology and the widespread popularity of e-commerce, full-link transactions occupy a vital position in modern business activities. Full-link transactions cover every link from product display, user selection, payment settlement to logistics distribution, involving many participants and complex business processes. This transaction model provides consumers with a convenient and efficient shopping experience, and also brings huge business opportunities to enterprises.

[0003] However, the existing transaction risk control collection system is unable to collect full-link data for all transaction links at the same time. In addition, the lack of an integrated collection solution makes it difficult to integrate different data sources, making it difficult to achieve comprehensive and accurate analysis of full-link transaction data, thereby reducing the quality and efficiency of full-link transaction data collection. Summary of the invention

[0004] The present invention provides a full-link transaction risk control real-time monitoring method, system, device and medium, the main purpose of which is to solve the problems of low quality and low efficiency of existing full-link transaction data collection methods.

[0005] To achieve the above purpose, the present invention provides a full-link transaction risk control real-time monitoring method, comprising:

[0006] Obtain access rights to external application channels, and obtain multi-channel full-link data based on the access rights;

[0007] Performing data analysis on the multi-channel full-link data to obtain full-link data;

[0008] Performing data channel verification on the full-link data to obtain verified full-link data;

[0009] Performing data filtering on the verified full-link data to obtain filtered full-link data;

[0010] Performing format conversion processing on the filtered full-link data to obtain standard message data;

[0011] A transaction risk analysis is performed based on the standard message data to obtain a transaction risk analysis result, and a security warning is issued based on the transaction risk analysis result.

[0012] In order to solve the above problems, the present invention also provides a full-link transaction risk control real-time monitoring system, the system comprising:

[0013] A data acquisition module is used to obtain access rights of external application channels and obtain multi-channel full-link data according to the access rights;

[0014] A parsing and verification module, used to perform data parsing on the multi-channel full-link data to obtain full-link data, perform data channel verification on the full-link data to obtain verified full-link data;

[0015] A filtering and conversion module is used to perform data filtering processing on the verified full-link data to obtain filtered full-link data, and perform format conversion processing on the filtered full-link data to obtain standard message data;

[0016] The security warning module is used to perform transaction risk analysis based on the standard message data, obtain transaction risk analysis results, and issue a security warning based on the transaction risk analysis results.

[0017] The data acquisition module is used to obtain the code change record data after the preset software version is successfully deployed.

[0018] In order to solve the above problem, the present invention further provides an electronic device, the electronic device comprising:

[0019] at least one processor;

[0020] and, a memory communicatively coupled to the at least one processor;

[0021] Among them, the memory stores a computer program that can be executed by the at least one processor, and the computer program is executed by the at least one processor so that the at least one processor can execute the above-mentioned full-link transaction risk control real-time monitoring method.

[0022] In order to solve the above problems, the present invention also provides a computer-readable storage medium, in which at least one computer program is stored. The at least one computer program is executed by a processor in an electronic device to implement the above-mentioned full-link transaction risk control real-time monitoring method.

[0023] The embodiment of the present invention obtains access rights of external application channels, obtains multi-channel full-link data according to the access rights, performs data analysis on the multi-channel full-link data to obtain full-link data, performs data channel verification on the full-link data to obtain verified full-link data, performs data filtering on the verified full-link data to obtain filtered full-link data, performs format conversion on the filtered full-link data to obtain standard message data, performs transaction risk analysis according to the standard message data to obtain transaction risk analysis results, and issues security warnings according to the transaction risk analysis results. This ensures that the changed code is tested, avoids missed tests, and can solve the problem of insufficient reliability of existing software testing methods after code changes. BRIEF DESCRIPTION OF THE DRAWINGS

[0024] Figure 1 Schematic diagram of an application environment of a full-link transaction risk control real-time monitoring method in one embodiment of the present invention;

[0025] Figure 2 A schematic diagram of a process for a full-link transaction risk control real-time monitoring method provided by an embodiment of the present invention;

[0026] Figure 3 A functional module diagram of a full-link transaction risk control real-time monitoring system provided by an embodiment of the present invention;

[0027] Figure 4 A schematic diagram of the structure of an electronic device for implementing the full-link transaction risk control real-time monitoring method provided by an embodiment of the present invention.

[0028] The realization of the purpose, functional features and advantages of the present invention will be further explained in conjunction with embodiments and with reference to the accompanying drawings. DETAILED DESCRIPTION

[0029] It should be understood that the specific embodiments described herein are only used to explain the present invention, and are not used to limit the present invention.

[0030] The embodiment of the present application provides a method for real-time monitoring of full-link transaction risk control. The execution subject of the method for real-time monitoring of full-link transaction risk control includes but is not limited to at least one of the electronic devices such as the server and the terminal that can be configured to execute the method provided by the embodiment of the present application. In other words, the method for real-time monitoring of full-link transaction risk control can be executed by software or hardware installed on a terminal device or a server device, and the software can be a blockchain platform. The server includes but is not limited to: a single server, a server cluster, a cloud server or a cloud server cluster, etc. The server can be an independent server, or it can be a cloud server that provides basic cloud computing services such as cloud services, cloud databases, cloud computing, cloud functions, cloud storage, network services, cloud communications, middleware services, domain name services, security services, content delivery networks (Content Delivery Network, CDN), and big data and artificial intelligence platforms.

[0031] The intelligent question-answering processing method based on artificial intelligence provided by the embodiment of the present invention can be applied in Figure 1 In an application environment, the client communicates with the server through a network. The server can obtain access rights of external application channels through the client, obtain multi-channel full-link data according to the access rights, perform data analysis on the multi-channel full-link data to obtain full-link data, perform data channel verification on the full-link data to obtain the verified full-link data, perform data filtering on the verified full-link data to obtain filtered full-link data, perform format conversion on the filtered full-link data to obtain standard message data, perform transaction risk analysis based on the standard message data to obtain transaction risk analysis results, and perform security warnings based on the transaction risk analysis results. It can effectively improve the quality and efficiency of full-link transaction data collection. Among them, the client can be but is not limited to various personal computers, laptops, smart phones, tablet computers and portable wearable devices. The server can be implemented with an independent server or a server cluster consisting of multiple servers. The present invention is described in detail below through specific embodiments.

[0032] Reference Figure 2 FIG. 1 is a flow chart of a method for real-time monitoring of full-link transaction risk control provided by an embodiment of the present invention. In this embodiment, the method for real-time monitoring of full-link transaction risk control includes:

[0033] S1. Obtain access rights to external application channels, and obtain multi-channel full-link data based on the access rights.

[0034] In the embodiment of the present invention, obtaining access rights to the external application channel refers to setting an access verification mechanism for the external application channel (a specific access code is required for access), and then using the preset access code as a parameter to make a parameter request.

[0035] In detail, the external application channels include but are not limited to open banking, cash registers, China UnionPay, POS machines and pocket banks.

[0036] In detail, the request with parameters may be a request with parameters using a post request.

[0037] In detail, the post request is a request method in the HTTP protocol, which is mainly used to submit data to the server for processing. Compared with the commonly used get request, the data obtained by the post request cannot be cached and is difficult to be stolen or tampered with during transmission, thereby improving data security.

[0038] In the embodiment of the present invention, in obtaining access rights to external application channels and obtaining multi-channel full-link data based on the access rights, it is necessary to clarify the specific needs of full-link collection, determine the key transaction links, and clarify which external application channels are required to obtain access rights. If the external channel provides an application programming interface (API), access rights can be obtained by integrating these APIs. Understand the documentation and usage specifications of each channel API, and carry out development and debugging to ensure that the required data can be obtained stably. If the external channel does not provide an API, legal data capture tools can be used to obtain data with the permission of the channel party.

[0039] In the embodiment of the present invention, the step of obtaining access rights of an external application channel and obtaining multi-channel full-link data according to the access rights includes:

[0040] Access the external application channel using a preset access code to obtain access rights to the external application channel;

[0041] Identify the rated system programming language for each external application channel;

[0042] Determining whether the system programming language of the external application channel is a standardized system programming language;

[0043] If the system programming language of the external application channel is a standardized system programming language, a standardized queue message method is used to collect data from the external application channel to obtain multi-channel full-link data;

[0044] If the system programming language of the external application channel is not a standardized system programming language, a unified SDK is used to collect data from the external application channel to obtain multi-channel full-link data.

[0045] In detail, the identification of the rated system programming language of each external application channel is to identify the programming language corresponding to the external application channel by identifying the data interface of each external application channel.

[0046] In detail, the standardized system programming language is set in advance according to the requirements, for example, programming languages ​​such as Python, Java and C++ can be set as the standardized system programming language according to the usage rate of the programming language.

[0047] In detail, the standardized MQ approach refers to using message queue technology in accordance with a series of standards and best practices in system design and implementation. This includes selecting appropriate MQ (Message Queue) products, designing reasonable message formats and routing strategies, ensuring reliable transmission and processing of messages, and defining a unified message format so that different systems and components can correctly parse and process messages. For example, JSON or XML format can be used to represent message content.

[0048] In detail, the MQ product can ensure that messages are not lost or duplicated in various situations. For example, it has a persistent storage mechanism, a message confirmation mechanism, etc. The MQ product can monitor the number of messages in the queue to promptly detect queue backlogs; understand the message sending and receiving speed of the MQ and evaluate the performance of the system; monitor errors in the message transmission and processing process to promptly detect and solve problems; and measure the time interval from the message being sent to being processed to ensure the response speed of the system.

[0049] In the embodiment of the present invention, the MQ product may be RocketMQ, Kafka, and Pulsar.

[0050] In the embodiment of the present invention, the collected data is adapted to Pulsar+Kafka. Both Pulsar and Kafka have powerful message processing capabilities. By adapting the collected data to these two message queues, appropriate queues can be selected for data storage and processing according to different business needs. For example, for scenarios with high real-time requirements, Kafka can be used first for fast data transmission and processing; for scenarios that require long-term storage and multi-tenant support, Pulsar can be selected.

[0051] In detail, Pulsar and Kafka are both distributed message queue systems with good scalability. The processing capacity of the system can be expanded by adding nodes to cope with the growing amount of data and business needs. When the amount of data in the non-standard system increases, the cluster size of the message queue can be easily expanded without causing too much impact on the existing system.

[0052] In detail, both Pulsar and Kafka support persistent storage of data, which can ensure that data is not lost when the system fails or restarts. This is very critical for important business data, which can improve the reliability of the system. You can configure the persistence strategy of the message queue, such as storage time, number of copies, etc., to meet different business needs.

[0053] In an embodiment of the present invention, when it is determined that the system programming language of the external application channel is not a standardized system programming language, due to the diversity of non-standard system programming languages, compatibility issues may arise. Therefore, it is necessary to generate SDKs according to different programming languages ​​to ensure the efficiency of data collection and the consistency of data formats.

[0054] In detail, the SDK (Software Development Kit) refers to a collection of tools provided to software developers for developing a certain type of software. SDK usually includes a compiler, debugger, documentation, code library, development tools, function library, API interface, development environment, etc., which enables developers to develop software applications more efficiently.

[0055] In the embodiment of the present invention, by obtaining access rights of external application channels and obtaining multi-channel full-link data according to the access rights, the efficiency of subsequent data analysis is improved.

[0056] S2. parse the multi-channel full-link data to obtain full-link data.

[0057] In the embodiment of the present invention, a key step in processing multi-channel full-link data is to parse the data so that it can be further processed and analyzed. Since the multi-channel full-link data is stored and transmitted in JSON (JavaScript Object Notation) format, a specific data parsing method is required to ensure that the data can be correctly read and understood.

[0058] In the embodiment of the present invention, the data parsing of the multi-channel full-link data to obtain the full-link data refers to parsing the multi-channel full-link data into easy-to-read data to improve the efficiency of data processing.

[0059] In the embodiment of the present invention, the step of parsing the multi-channel full-link data to obtain the full-link data includes:

[0060] Determining whether the multi-channel full-link data has been encrypted;

[0061] If the multi-channel full-link data is encrypted, decrypting the multi-channel full-link data;

[0062] If the multi-channel full-link data is not encrypted, the multi-channel full-link data is parsed using a preset JSON parsing library.

[0063] In detail, different programming languages ​​have corresponding JSON parsing libraries. For example, in Java, the JSON parsing library is a Java JSON processing library, which can convert JSON data to and from Java objects.

[0064] In the embodiment of the present invention, after the multi-channel full-link data is parsed to obtain the full-link data, it is necessary to check the accuracy, completeness and consistency of the full-link data.

[0065] In the embodiment of the present invention, by performing data analysis on the multi-channel full-link data, the full-link data is obtained, thereby improving the efficiency of subsequent data channel verification.

[0066] S3. Perform data channel verification on the full-link data to obtain verified full-link data.

[0067] In the embodiment of the present invention, the data channel verification of the full-link data to obtain the verified full-link data refers to verifying whether the data source channel of the full-link data is related to the financial field, and eliminating the full-link data from irrelevant channels.

[0068] In the embodiment of the present invention, the step of verifying the data channel of the full-link data is crucial to ensure the accuracy and relevance of the data. The verification process involves a strict review of the source channels of the full-link data to verify whether it has a direct connection with the financial field. The purpose of this step is to filter out truly valuable data from a large number of possible data sources, thereby laying a solid foundation for subsequent data processing and analysis.

[0069] In detail, we first need to identify which channels are related to the financial sector. This may include banking transaction systems, payment platforms, financial market data, etc., and then track each data point of the entire link data to determine its source channel. By designing and implementing a set of verification mechanisms to automatically detect whether the data source meets the predefined financial relevance standards, channel data that does not meet the financial relevance standards will be eliminated to ensure the purity of the data set, and the quality of the verified data will be evaluated, including the integrity, consistency and accuracy of the data.

[0070] In the embodiment of the present invention, the step of performing data channel verification on the full-link data to obtain the verified full-link data includes:

[0071] Obtaining channel information of the full-link data;

[0072] Performing irrelevant channel verification on the channel information to obtain irrelevant channel information;

[0073] Annotate irrelevant data according to the irrelevant channel information to obtain irrelevant data information;

[0074] The irrelevant data in the full-link data is removed according to the irrelevant data information to obtain the verified full-link data.

[0075] In the embodiment of the present invention, by performing data channel verification on the full-link data, the verified full-link data is obtained, thereby improving the efficiency of subsequent data filtering processing.

[0076] S4. Perform data filtering on the verified full-link data to obtain filtered full-link data.

[0077] In the embodiment of the present invention, the data filtering processing is performed on the verified full-link data to obtain the filtered full-link data, which refers to filtering the data whose format or content does not meet the requirements in the verified full-link data.

[0078] In the embodiment of the present invention, the step of performing data filtering on the verified full-link data to obtain filtered full-link data includes:

[0079] Identifying the format attributes of the verified full-link data;

[0080] Marking illegal format data according to the format attributes and preset standard format attributes to obtain illegal data;

[0081] Determining whether the illegal data conforms to a preset standard format attribute;

[0082] If the illegal data conforms to the preset standard format attributes, returning to the step of identifying the format attributes of the verified full-link data;

[0083] If the illegal data does not conform to the preset standard format attributes, the illegal data is removed from the verified full-link data to obtain filtered full-link data.

[0084] In the embodiment of the present invention, the data filtering process is performed on the verified full-link data to obtain the filtered full-link data in order to further improve the quality and reliability of the data. This process involves a detailed review of the verified full-link data to ensure that the data items therein not only pass the basic verification, but also that their format and content fully comply with the preset standards and requirements.

[0085] In the embodiment of the present invention, illegal data filtering is performed on the verified full-link data to obtain filtered full-link data, thereby improving the efficiency of subsequent format conversion processing.

[0086] S5. Perform format conversion processing on the filtered full-link data to obtain standard message data.

[0087] In the embodiment of the present invention, the format conversion processing is performed on the filtered full-link data to obtain standard message data, which means that the filtered full-link data is converted into a unified format to improve the efficiency of subsequent data processing.

[0088] In the embodiment of the present invention, the format conversion processing of the filtered full-link data to obtain standard message data is to further optimize the data processing process and ensure the consistency and readability of the data. This process involves converting the cleaned data into a standardized format so that subsequent data processing, analysis and transmission can be carried out more efficiently.

[0089] Specifically, the target format of the standard message data needs to be determined first. This may include defining the data structure, field order, data type, and encoding method, etc. Based on the target format, a set of detailed format conversion rules are designed. These rules will guide how to map the filtered data to the standard format.

[0090] In the embodiment of the present invention, after the filtered full-link data is format-converted to obtain standard message data, the method further includes:

[0091] The standard message data is encrypted using an AES encryption algorithm to obtain encrypted message data;

[0092] Performing data annotation processing on the encrypted message data to obtain data annotation information;

[0093] The encrypted message data is stored in a corresponding label database according to the data annotation information.

[0094] In the embodiment of the present invention, the AES encryption algorithm is a widely used symmetric encryption algorithm with the characteristics of high efficiency and security.

[0095] In detail, the AES encryption is a symmetric encryption algorithm, which means that the same key is used for encryption and decryption. This makes it relatively fast in encryption speed and suitable for encryption of large amounts of data.

[0096] In the embodiment of the present invention, by performing format conversion processing on the filtered full-link data, standard message data is obtained, thereby improving the efficiency of subsequent payment risk analysis.

[0097] S6. Perform transaction risk analysis based on the standard message data to obtain a transaction risk analysis result, and issue a security warning based on the transaction risk analysis result.

[0098] In the embodiment of the present invention, the transaction risk analysis is performed according to the standard message data to obtain the transaction risk analysis result, which is performed according to the standard message data using a pre-trained risk analysis model.

[0099] In detail, the risk analysis model is a convolutional neural network model.

[0100] In the embodiment of the present invention, the step of performing transaction risk analysis according to the standard message data to obtain a transaction risk analysis result includes:

[0101] Normalizing the standard message data to obtain normalized message data;

[0102] Performing one-hot encoding on the normalized message data to obtain message data features;

[0103] A pre-trained risk analysis model is used to perform transaction risk analysis based on the message data characteristics to obtain a transaction risk analysis result.

[0104] In detail, the normalizing the standard message data to obtain normalized message data refers to mapping the numerical value-related data in the standard message data to a range between 0 and 1, so as to improve the recognition effect of the subsequent model on the data.

[0105] In detail, the one-hot encoding refers to converting data into a binary vector representation, where each category corresponds to one dimension, thereby expressing the characteristics of the data.

[0106] In an embodiment of the present invention, the risk analysis model is obtained by acquiring a large amount of message data, extracting features from the large amount of message data as training data, and annotating data according to the actual transaction risk level corresponding to each message data. The risk analysis model is used to predict risks based on the training data, and the difference between the predicted result and the actual result is calculated. The back propagation algorithm is then used to perform hyperparameter optimization on the risk analysis model based on the difference value until the performance of the model meets the requirements or the model training is confirmed to be completed after a preset number of iterations.

[0107] In detail, the hyperparameters include weight parameters, bias terms, and learning rates.

[0108] In detail, the weight parameters are an important component of machine learning and neural network models. In the model, the weight parameters connect different neurons or features and are used to measure the influence of each input feature on the output result. The value of the weight parameter determines the transmission and processing method of the input signal in the model. By continuously adjusting the weight parameters, the model can learn the complex relationship between different features, thereby achieving accurate prediction and classification of data.

[0109] Furthermore, the weight parameters usually need to be initialized at the beginning of model training, which can be done by random initialization, zero initialization or specific initialization methods (such as Xavier initialization, He initialization, etc.). During the training process, the weight parameters are continuously adjusted through optimization algorithms (such as gradient descent) to minimize the loss function of the model. The optimization algorithm determines the update direction and amplitude of the weight parameters based on the gradient information of the loss function to the weight parameters. Appropriate weight parameters can make the model better fit the training data and improve the accuracy and generalization ability of the model.

[0110] In detail, the bias term plays a role in adjusting the output results in the model, similar to adding a constant term in a linear equation. It can help the model better adapt to different data distributions and improve the flexibility and robustness of the model. The value of the bias term determines the output value of the model when there is no input, or the contribution to the output result when the input feature is weak. The bias term also needs to be initialized at the beginning of model training, and can usually be set to a small random value or a specific value. Similar to the weight parameter, the bias term is also adjusted by the optimization algorithm during the training process to minimize the loss function of the model. Reasonable setting of the bias term can improve the performance of the model, especially when dealing with nonlinear data and complex tasks.

[0111] In detail, the learning rate determines the amplitude of each parameter update, that is, the step size that the model takes in the direction of minimizing the loss function during the optimization process. A suitable learning rate can enable the model to quickly converge to the optimal solution during training while avoiding falling into local optimality or oscillation.

[0112] Furthermore, the choice of learning rate usually needs to be adjusted according to the specific problem and data set. Generally speaking, a larger learning rate can make the model update parameters quickly in the early stage of training, but may cause instability or failure to converge; a smaller learning rate can make the model converge more stably, but may require a longer training time. During the training process, fixed learning rate and dynamic learning rate adjustment strategies (such as learning rate decay, adaptive learning rate, etc.) can be used to optimize the performance of the model. Learning rate decay is to gradually reduce the learning rate as the training progresses to balance the convergence speed and stability of the model; the adaptive learning rate automatically adjusts the learning rate according to the training situation of the model to improve the training efficiency.

[0113] In the embodiment of the present invention, the transaction risk analysis result is a numerical value, and issuing a security warning according to the transaction risk analysis result refers to determining whether to issue a security warning according to a relationship between the numerical value and a preset risk threshold.

[0114] In the embodiment of the present invention, by performing transaction risk analysis according to the standard message data to obtain a transaction risk analysis result, a security warning is issued according to the transaction risk analysis result, thereby improving the security of the transaction.

[0115] It can be seen that in the embodiment of the present invention, by collecting the full-link transaction data of each external channel and performing data verification, data filtering and data conversion according to unified standards, standardized collection of full-link transaction data of multiple external channels is achieved, thereby improving the quality and efficiency of full-link transaction data collection.

[0116] like Figure 3 , which is a functional module diagram of a full-link transaction risk control real-time monitoring system provided by an embodiment of the present invention.

[0117] The full-link transaction risk control real-time monitoring system 100 of the present invention can be installed in an electronic device. According to the functions implemented, the full-link transaction risk control real-time monitoring system 100 can include a data acquisition module 101, a parsing and verification module 102, a filtering and conversion module 103, and a security warning module 104. The module of the present invention can also be called a unit, which refers to a series of computer program segments that can be executed by an electronic device processor and can complete fixed functions, which are stored in the memory of the electronic device.

[0118] In this embodiment, the functions of each module / unit are as follows:

[0119] The data acquisition module 101 is used to obtain access rights of external application channels and obtain multi-channel full-link data according to the access rights;

[0120] The parsing and verification module 102 is used to perform data parsing on the multi-channel full-link data to obtain full-link data, and perform data channel verification on the full-link data to obtain verified full-link data;

[0121] The filtering and conversion module 103 is used to perform data filtering processing on the verified full-link data to obtain filtered full-link data, and perform format conversion processing on the filtered full-link data to obtain standard message data;

[0122] The security warning module 104 is used to perform transaction risk analysis based on the standard message data, obtain transaction risk analysis results, and issue a security warning based on the transaction risk analysis results.

[0123] In one embodiment, the data acquisition module 101 is specifically used for:

[0124] Access the external application channel using a preset access code to obtain access rights to the external application channel;

[0125] Identify the rated system programming language for each external application channel;

[0126] Determining whether the system programming language of the external application channel is a standardized system programming language;

[0127] If the system programming language of the external application channel is a standardized system programming language, a standardized queue message method is used to collect data from the external application channel to obtain multi-channel full-link data;

[0128] If the system programming language of the external application channel is not a standardized system programming language, a unified SDK is used to collect data from the external application channel to obtain multi-channel full-link data.

[0129] In one embodiment, the parsing and verification module 102 is specifically used to:

[0130] Determining whether the multi-channel full-link data has been encrypted;

[0131] If the multi-channel full-link data is encrypted, decrypting the multi-channel full-link data;

[0132] If the multi-channel full-link data is not encrypted, the multi-channel full-link data is parsed using a preset JSON parsing library.

[0133] In one embodiment, the parsing and verification module 102 is specifically used to:

[0134] Obtaining channel information of the full-link data;

[0135] Performing irrelevant channel verification on the channel information to obtain irrelevant channel information;

[0136] Annotate irrelevant data according to the irrelevant channel information to obtain irrelevant data information;

[0137] The irrelevant data in the full-link data is removed according to the irrelevant data information to obtain the verified full-link data.

[0138] In one embodiment, the filtering conversion module 103 is specifically used to:

[0139] Identifying the format attributes of the verified full-link data;

[0140] Marking illegal format data according to the format attributes and preset standard format attributes to obtain illegal data;

[0141] Determining whether the illegal data conforms to a preset standard format attribute;

[0142] If the illegal data conforms to the preset standard format attributes, returning to the step of identifying the format attributes of the verified full-link data;

[0143] If the illegal data does not conform to the preset standard format attributes, the illegal data is removed from the verified full-link data to obtain filtered full-link data.

[0144] In one embodiment, the filtering conversion module 103 is specifically used to:

[0145] The standard message data is encrypted using an AES encryption algorithm to obtain encrypted message data;

[0146] Performing data annotation processing on the encrypted message data to obtain data annotation information;

[0147] The encrypted message data is stored in a corresponding label database according to the data annotation information.

[0148] In one embodiment, the security warning module 104 is specifically used to:

[0149] Normalizing the standard message data to obtain normalized message data;

[0150] Performing one-hot encoding on the normalized message data to obtain message data features;

[0151] A pre-trained risk analysis model is used to perform transaction risk analysis based on the message data characteristics to obtain a transaction risk analysis result.

[0152] In detail, each module described in the full-link transaction risk control real-time monitoring system 100 described in the embodiment of the present invention is used in the same manner as described above. Figure 2 The same technical means are used as the real-time monitoring method for full-link transaction risk control described in the text, and can produce the same technical effects, so I will not go into details here.

[0153] like Figure 4 , which is a schematic diagram of the structure of an electronic device of a full-link transaction risk control real-time monitoring method provided by an embodiment of the present invention.

[0154] The electronic device 1 may include a processor 10, a memory 11, a communication bus 12 and a communication interface 13, and may also include a computer program stored in the memory 11 and executable on the processor 10, such as a full-link transaction risk control real-time monitoring program.

[0155] In some embodiments, the processor 10 may be composed of an integrated circuit, for example, a single packaged integrated circuit, or a plurality of integrated circuits with the same or different functions, including one or more central processing units (CPUs), microprocessors, digital processing chips, graphics processors, and combinations of various control chips. The processor 10 is the control core (ControlUnit) of the electronic device, and uses various interfaces and lines to connect the various components of the entire electronic device, and executes or executes the programs or modules stored in the memory 11 (such as the full-link transaction risk control real-time monitoring program, etc.), and calls the data stored in the memory 11 to execute various functions of the electronic device and process data.

[0156] The memory 11 includes at least one type of readable storage medium, and the readable storage medium includes flash memory, mobile hard disk, multimedia card, card-type memory (for example: SD or DX memory, etc.), magnetic memory, disk, optical disk, etc. In some embodiments, the memory 11 may be an internal storage unit of an electronic device, such as a mobile hard disk of the electronic device. In other embodiments, the memory 11 may also be an external storage device of an electronic device, such as a plug-in mobile hard disk, a smart memory card (Smart Media Card, SMC), a secure digital (Secure Digital, SD) card, a flash card (Flash Card), etc. equipped on the electronic device. Further, the memory 11 may also include both an internal storage unit of the electronic device and an external storage device. The memory 11 can not only be used to store application software and various types of data installed in the electronic device, such as the code of the full-link transaction risk control real-time monitoring program, but also can be used to temporarily store data that has been output or is to be output.

[0157] The communication bus 12 may be a peripheral component interconnect (PCI) bus or an extended industry standard architecture (EISA) bus, etc. The bus may be divided into an address bus, a data bus, a control bus, etc. The bus is configured to realize connection and communication between the memory 11 and at least one processor 10, etc.

[0158] The communication interface 13 is used for communication between the above-mentioned electronic device and other devices, including a network interface and a user interface. Optionally, the network interface may include a wired interface and / or a wireless interface (such as a WI-FI interface, a Bluetooth interface, etc.), which is generally used to establish a communication connection between the electronic device and other electronic devices. The user interface may be a display (Display), an input unit (such as a keyboard (Keyboard)), and optionally, the user interface may also be a standard wired interface, a wireless interface. Optionally, in this embodiment, the display may be an LED display, a liquid crystal display, a touch-sensitive liquid crystal display, and an OLED (Organic Light-Emitting Diode, organic light-emitting diode) touch device, etc. Among them, the display may also be appropriately referred to as a display screen or a display unit, which is used to display information processed in the electronic device and to display a visual user interface.

[0159] The figure only shows an electronic device with components. Those skilled in the art will understand that the structure shown in the figure does not constitute a limitation on the electronic device, and may include fewer or more components than shown in the figure, or combine certain components, or arrange the components differently.

[0160] For example, although not shown, the electronic device may also include a power source (such as a battery) for supplying power to each component. Preferably, the power source may be logically connected to the at least one processor 10 through a power management device, so that the power management device can realize functions such as charging management, discharging management, and power consumption management. The power source may also include one or more DC or AC power sources, recharging devices, power failure detection circuits, power converters or inverters, power status indicators, and other arbitrary components. The electronic device may also include a variety of sensors, Bluetooth modules, Wi-Fi modules, etc., which will not be repeated here.

[0161] It should be understood that the embodiment is for illustration only and the scope of the patent application is not limited to this structure.

[0162] The full-link transaction risk control real-time monitoring program stored in the memory 11 of the electronic device 1 is a combination of multiple instructions. When running in the processor 10, it can achieve:

[0163] Obtain access rights to external application channels, and obtain multi-channel full-link data based on the access rights;

[0164] Performing data analysis on the multi-channel full-link data to obtain full-link data;

[0165] Performing data channel verification on the full-link data to obtain verified full-link data;

[0166] Performing data filtering on the verified full-link data to obtain filtered full-link data;

[0167] Performing format conversion processing on the filtered full-link data to obtain standard message data;

[0168] A transaction risk analysis is performed based on the standard message data to obtain a transaction risk analysis result, and a security warning is issued based on the transaction risk analysis result.

[0169] Specifically, the specific implementation method of the processor 10 for the above instructions can refer to the description of the relevant steps in the corresponding embodiment of the accompanying drawings, which will not be repeated here.

[0170] Furthermore, if the module / unit integrated in the electronic device 1 is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. The computer-readable storage medium can be volatile or non-volatile. For example, the computer-readable medium can include: any entity or device capable of carrying the computer program code, a recording medium, a USB flash drive, a mobile hard disk, a magnetic disk, an optical disk, a computer memory, and a read-only memory (ROM).

[0171] The present invention further provides a computer-readable storage medium, wherein the computer-readable storage medium stores a computer program, and when the computer program is executed by a processor of an electronic device, the computer program can implement:

[0172] Obtain access rights to external application channels, and obtain multi-channel full-link data based on the access rights;

[0173] Performing data analysis on the multi-channel full-link data to obtain full-link data;

[0174] Performing data channel verification on the full-link data to obtain verified full-link data;

[0175] Performing data filtering on the verified full-link data to obtain filtered full-link data;

[0176] Performing format conversion processing on the filtered full-link data to obtain standard message data;

[0177] A transaction risk analysis is performed based on the standard message data to obtain a transaction risk analysis result, and a security warning is issued based on the transaction risk analysis result.

[0178] In the embodiments provided by the present invention, it should be understood that the disclosed devices, systems and methods can be implemented in other ways. For example, the system embodiments described above are only schematic, for example, the division of the modules is only a logical function division, and there may be other division methods in actual implementation.

[0179] The modules described as separate components may or may not be physically separated, and the components shown as modules may or may not be physical units, that is, they may be located in one place or distributed on multiple network units. Some or all of the modules may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0180] In addition, each functional module in each embodiment of the present invention may be integrated into one processing unit, each unit may exist physically separately, or two or more units may be integrated into one unit. The above-mentioned integrated unit may be implemented in the form of hardware or in the form of hardware plus software functional modules.

[0181] It is obvious to those skilled in the art that the present invention is not limited to the details of the above exemplary embodiments, and that the present invention can be implemented in other specific forms without departing from the spirit or essential characteristics of the present invention.

[0182] Therefore, no matter from which point of view, the embodiments should be regarded as illustrative and non-restrictive, and the scope of the present invention is limited by the appended claims rather than the above description, so it is intended that all changes falling within the meaning and scope of the equivalent elements of the claims are included in the present invention. Any attached figure mark in the claims should not be regarded as limiting the claims involved.

[0183] The embodiments of the present application can acquire and process relevant data based on artificial intelligence technology. Among them, artificial intelligence (AI) is the theory, method, technology and application system that uses digital computers or machines controlled by digital computers to simulate, extend and expand human intelligence, perceive the environment, acquire knowledge and use knowledge to obtain the best results.

[0184] In addition, it is clear that the word "comprising" does not exclude other units or steps, and the singular does not exclude the plural. Multiple units or devices stated in the system claim can also be implemented by one unit or device through software or hardware. The words first, second, etc. are used to indicate names, and do not indicate any particular order.

[0185] Finally, it should be noted that if software tools or components other than those of the Company appear in the application embodiments, they are only used for illustration and do not represent actual use. The above embodiments are only used to illustrate the technical solutions of the present invention and are not intended to limit them. Although the present invention is described in detail with reference to the preferred embodiments, those skilled in the art should understand that the technical solutions of the present invention may be modified or replaced by equivalents without departing from the spirit and scope of the technical solutions of the present invention.

Claims

1. A full-link transaction risk control real-time monitoring method, characterized in that: The method comprises: Obtain access rights to external application channels, and obtain multi-channel full-link data based on the access rights; Performing data analysis on the multi-channel full-link data to obtain full-link data; Performing data channel verification on the full-link data to obtain verified full-link data; Performing illegal data filtering on the verified full-link data to obtain filtered full-link data; Performing format conversion processing on the filtered full-link data to obtain standard message data; A transaction risk analysis is performed based on the standard message data to obtain a transaction risk analysis result, and a security warning is issued based on the transaction risk analysis result.

2. The full-link transaction risk control real-time monitoring method according to claim 1, characterized in that: The obtaining of access rights for external application channels and obtaining multi-channel full-link data according to the access rights include: Access the external application channel using a preset access code to obtain access rights to the external application channel; Identify the rated system programming language for each external application channel; Determining whether the system programming language of the external application channel is a standardized system programming language; If the system programming language of the external application channel is a standardized system programming language, a standardized queue message method is used to collect data from the external application channel to obtain multi-channel full-link data; If the system programming language of the external application channel is not a standardized system programming language, a unified software development toolkit is used to collect data from the external application channel to obtain multi-channel full-link data.

3. The full-link transaction risk control real-time monitoring method according to claim 2, characterized in that: The performing data parsing on the multi-channel full-link data to obtain the full-link data includes: Determining whether the multi-channel full-link data has been encrypted; If the multi-channel full-link data is encrypted, decrypting the multi-channel full-link data; If the multi-channel full-link data is not encrypted, the multi-channel full-link data is parsed using a preset JSON parsing library.

4. The full-link transaction risk control real-time monitoring method according to claim 1, characterized in that: The performing data channel verification on the full-link data to obtain the verified full-link data includes: Obtaining channel information of the full-link data; Performing irrelevant channel verification on the channel information to obtain irrelevant channel information; Annotate irrelevant data according to the irrelevant channel information to obtain irrelevant data information; The irrelevant data in the full-link data is removed according to the irrelevant data information to obtain the verified full-link data.

5. The full-link transaction risk control real-time monitoring method according to claim 1, characterized in that: The performing data filtering processing on the verified full-link data to obtain filtered full-link data includes: Identifying the format attributes of the verified full-link data; Marking illegal format data according to the format attributes and preset standard format attributes to obtain illegal data; Determining whether the illegal data conforms to a preset standard format attribute; If the illegal data conforms to the preset standard format attributes, returning to the step of identifying the format attributes of the verified full-link data; If the illegal data does not conform to the preset standard format attributes, the illegal data is removed from the verified full-link data to obtain filtered full-link data.

6. The full-link transaction risk control real-time monitoring method according to claim 1, characterized in that: After the filtered full-link data is format-converted to obtain standard message data, the method further includes: The standard message data is encrypted using an AES encryption algorithm to obtain encrypted message data; Performing data annotation processing on the encrypted message data to obtain data annotation information; The encrypted message data is stored in a corresponding label database according to the data annotation information.

7. The full-link transaction risk control real-time monitoring method according to claim 1, characterized in that: The performing transaction risk analysis according to the standard message data to obtain a transaction risk analysis result includes: Normalizing the standard message data to obtain normalized message data; Performing one-hot encoding on the normalized message data to obtain message data features; A pre-trained risk analysis model is used to perform transaction risk analysis based on the message data characteristics to obtain a transaction risk analysis result.

8. A full-link transaction risk control real-time monitoring system, characterized in that: The system comprises: A data acquisition module is used to obtain access rights of external application channels and obtain multi-channel full-link data according to the access rights; A parsing and verification module, used to perform data parsing on the multi-channel full-link data to obtain full-link data, perform data channel verification on the full-link data to obtain verified full-link data; A filtering and conversion module is used to perform data filtering processing on the verified full-link data to obtain filtered full-link data, and perform format conversion processing on the filtered full-link data to obtain standard message data; The security warning module is used to perform transaction risk analysis based on the standard message data, obtain transaction risk analysis results, and issue a security warning based on the transaction risk analysis results. The data acquisition module is used to obtain the code change record data after the preset software version is successfully deployed.

9. An electronic device, characterized in that: The electronic device comprises: at least one processor; and, a memory communicatively coupled to the at least one processor; In which, the memory stores a computer program that can be executed by the at least one processor, and the computer program is executed by the at least one processor so that the at least one processor can execute the real-time monitoring method for full-link transaction risk control as described in any one of claims 1 to 7.

10. A computer-readable storage medium storing a computer program, characterized in that: When the computer program is executed by the processor, the full-link transaction risk control real-time monitoring method as described in any one of claims 1 to 7 is implemented.

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