Blacklist processing method, apparatus, device, storage medium, and program product

Abstract

The application provides a black list processing method, device, equipment, storage medium and program product, relates to the technical field of electronic commerce, and the method comprises the steps that a query task request is received, a to-be-checked merchant list and a preset hit threshold are obtained based on the query task request; a thread is configured for each to-be-checked merchant in the to-be-checked merchant list; based on the query task request, the to-be-checked merchant list is processed by using at least one thread to obtain a query result, and the query result is added to a queue; the query result is the result of whether the to-be-checked merchant hits the black list; based on the adding order of the query result in the queue, the number of merchants hitting the black list in the query result is counted in sequence, and when it is determined that the number of merchants is greater than the preset hit threshold, a return result is generated; the return result is used for indicating that all the to-be-checked merchants in the to-be-checked merchant list are black list merchants; in this way, the queuing mode of processing the query result in the first return first processing mode is adopted, the response time is reduced, and the query rate is accelerated.

Description

Technical Field

[0001] This application relates to the field of e-commerce technology, and in particular to a blacklist processing method, apparatus, device, storage medium, and program product. Background Technology

[0002] With the rapid development of electronic payment, online merchants have become an important way of consumption in life. However, in the course of business transactions, if a merchant violates the signed contract to a certain extent, or if a merchant has a certain bad record provided by regulatory agencies, these merchants will be added to a blacklist and restricted from conducting certain businesses.

[0003] In existing technologies, querying blacklisted merchants is usually handled in a serial query and serial processing manner. That is, after receiving a blacklist query request, the merchants to be queried are queried one by one based on the blacklist query request, and compared with the merchant data in the blacklist data source. After all the merchants to be queried have been compared, the comparison result is returned.

[0004] However, the above method requires comparing all the merchants to be queried before returning the results, which results in a long response time, low processing efficiency, and a relatively poor customer experience. Summary of the Invention

[0005] This application provides a blacklist processing method, apparatus, device, storage medium, and program product to solve the problem that existing methods of querying blacklists using serial query and serial processing have long response times, low processing efficiency, and relatively poor customer experience.

[0006] Firstly, this application provides a blacklist processing method, the method comprising:

[0007] Receive a query task request and obtain a list of merchants to be queried and a preset hit threshold based on the query task request; the list of merchants to be queried includes at least one merchant to be queried, and the preset hit threshold is the number of times the query hits the blacklist based on the application scenario.

[0008] Configure one thread for each merchant in the list of merchants to be queried;

[0009] Based on the query task request, at least one thread is used to query the list of merchants to be queried, at least one query result is obtained, and the at least one query result is added to a queue; the query result is the result of whether the merchant to be queried in the list of merchants to be queried is on the blacklist;

[0010] Based on the adding order of the query results in the queue, the number of the hit blacklist merchants in the query results is counted in sequence, and when it is determined that the number of the hit blacklist merchants is greater than a preset hit threshold, a return result is generated; the return result is used to indicate that all the to-be-searched merchants in the to-be-searched merchant list are blacklist merchants.

[0011] Optionally, the to-be-searched merchant list is queried by using at least one thread to obtain at least one query result, including:

[0012] If the number of the to-be-searched merchants in the to-be-searched merchant list is one, the to-be-searched merchant list is queried by using one thread in a serial processing manner to obtain one query result;

[0013] If the number of the to-be-searched merchants in the to-be-searched merchant list is multiple, the to-be-searched merchant list is queried by using multiple threads in a parallel processing manner to obtain multiple query results.

[0014] Optionally, the at least one query result is added to a queue, including:

[0015] The return time of the at least one query result is obtained, the return time being the response time of processing the to-be-searched merchant;

[0016] An adding order is generated based on the size of the return time, and the at least one query result is added to the queue based on the adding order.

[0017] Optionally, when it is determined that the number of the hit blacklist merchants is greater than the preset hit threshold, a return result is generated, including:

[0018] When it is determined that the number of the hit blacklist merchants is greater than the preset hit threshold, the query processing is interrupted, and the attribute information and the transaction relationship information of the to-be-searched merchants in the to-be-searched merchant list are monitored;

[0019] The association relationship of the to-be-searched merchants is determined according to the attribute information and the transaction relationship information, and the risk level of the to-be-searched merchants is determined based on the association relationship;

[0020] A return result is generated based on the risk level, and the return result is visually displayed; wherein the return result is also used to indicate the risk level of each blacklist merchant.

[0021] Optionally, the method further includes:

[0022] When it is determined that the number of the hit blacklist merchants is less than or equal to the preset hit threshold, a processing result is generated, the processing result being used to indicate that the to-be-searched merchants in the to-be-searched merchant list are whitelist merchants.

[0023] Optionally, the method further comprises:

[0024] After determining that the merchant to be checked in the list of merchants to be checked is a blacklisted merchant, intercepting the blacklisted merchant and sending an audit prompt message to the blacklisted merchant to prompt the blacklisted merchant to upload merchant information.

[0025] Optionally, the method further comprises:

[0026] Obtaining merchant information of each blacklisted merchant, and for each blacklisted merchant, sequentially performing an identification operation on the content in the merchant information, auditing the blacklisted merchant, and obtaining an audit result;

[0027] When the audit result is determined to be passed, the blacklisted merchant is deleted from the blacklist library; the blacklist library pre-stores a blacklist for comparison.

[0028] In a second aspect, the application also provides a blacklist processing device, which comprises:

[0029] The acquisition module is configured to receive a query task request and acquire a list of merchants to be checked and a preset hit threshold based on the query task request; the list of merchants to be checked includes at least one merchant to be checked, and the preset hit threshold is the number of times of hitting the blacklist based on the application scenario;

[0030] The configuration module is configured to configure one thread for each merchant to be checked in the list of merchants to be checked;

[0031] The query module is configured to perform query processing on the list of merchants to be checked based on the query task request using at least one thread, obtain at least one query result, and add the at least one query result to a queue; the query result is the result of whether the merchant to be checked in the list of merchants to be checked hits the blacklist;

[0032] The return module is configured to sequentially count the number of merchants hitting the blacklist in the query result based on the addition order of the query result in the queue, and generate a return result when it is determined that the number of merchants hitting the blacklist is greater than the preset hit threshold; the return result is used to indicate that the merchants to be checked in the list of merchants to be checked are all blacklisted merchants.

[0033] In a third aspect, the application also provides an electronic device, which comprises a processor and a memory in communication connection with the processor;

[0034] The memory stores computer execution instructions;

[0035] The processor executes the computer execution instructions stored in the memory to implement the method according to any one of the first aspect.

[0036] In a fourth aspect, the present application provides a computer readable storage medium, which stores computer execution instructions, and the computer execution instructions are used to implement the method according to any one of the first aspect when executed by a processor.

[0037] In a fifth aspect, the present application provides a computer program product, which comprises a computer program, and the computer program is used to implement the method according to any one of the first aspect when executed by a processor.

[0038] In summary, the present application provides a blacklist processing method, device, equipment, storage medium and program product, which can receive a query task request, obtain a list of to-be-checked merchants and query requirements, set the number of core threads of a thread pool according to the number of to-be-checked merchants in the list of to-be-checked merchants, and then construct a query subtask, put the query subtask into the thread pool and execute the query subtask in parallel, that is, each thread processes one to-be-checked merchant, and further, when the query subtask has a query result, the query result is added to a queue, the query result is continuously taken out from the queue for processing, and the number of times of hitting the blacklist is counted; if the number of times of hitting the blacklist satisfies the query requirement, that is, greater than a preset hit threshold, a return result is generated, and the query process ends in advance, thereby accelerating the query efficiency. The present application puts the query result into the queue, processes the query result in the queuing mode of returning first and processing first, and reduces the overall response time. BRIEF DESCRIPTION OF DRAWINGS

[0039] The accompanying drawings, which are incorporated herein and form part of the specification, illustrate embodiments consistent with the present application and, together with the description, further serve to explain the principles of the application.

[0040] Figure 1 An application scenario schematic diagram provided for an embodiment of the present application;

[0041] Figure 2 A flowchart of a blacklist processing method provided for an embodiment of the present application;

[0042] Figure 3 A flowchart of a specific blacklist processing method provided for an embodiment of the present application;

[0043] Figure 4 A structural schematic diagram of a blacklist processing device provided for an embodiment of the present application;

[0044] Figure 5 A structural schematic diagram of an electronic device provided for an embodiment of the present application.

[0045] The specific embodiments of the application will be described in detail below with reference to the drawings. These drawings and the associated description are not intended to limit the scope of the application in any way, but merely to describe certain embodiments of the application in sufficient detail to enable one skilled in the art to make and use the application. DETAILED DESCRIPTION

[0046] The exemplary embodiments will be described in detail below with reference to the drawings. The following description is not intended to limit the scope of the application in any way, but merely to describe certain embodiments of the application in sufficient detail to enable one skilled in the art to make and use the application.

[0047] In order to clearly describe the technical solutions of the embodiments of the application, in the embodiments of the application, the terms "first", "second", and the like are used to distinguish items or objects having substantially the same function and effect. For example, a first device and a second device are merely used to distinguish different devices, and do not limit the order of the devices. Those skilled in the art can understand that the terms "first", "second", and the like do not limit the number and execution order, and the terms "first", "second", and the like do not necessarily mean different.

[0048] It should be noted that the terms "exemplary" or "for example" are used herein to mean "an example of" or "an example, only. Any embodiment or design described herein as "exemplary" or "for example" should not be construed as being more preferred or advantageous than other embodiments or designs. Rather, the term "exemplary" or "for example" is used in this application to present concepts in a concrete manner.

[0049] In this application, "at least one" means one or more, and "multiple" means two or more. The term "and / or" describes the association relationship between the associated objects, which means that there can be three relationships, for example, A and / or B, which can represent the following three cases: A exists alone, A and B exist together, and B exists alone, where A and B can be singular or plural. The character " / " generally represents an "or" relationship between the associated objects. "At least one of the following" or similar expressions means any combination of these items, including any combination of single or multiple items. For example, at least one of a, b, or c can represent a, b, c, a-b, a-c, b-c, or a-b-c, where a, b, and c can be single or multiple.

[0050] It should be noted that the collection, storage, use, processing, transmission, provision and disclosure of the financial data or user data and other information involved in the technical solutions of the present application comply with relevant laws and regulations and do not violate public order and good customs.

[0051] The terms involved in the present application are explained as follows.

[0052] Primary merchant: can refer to a platform, such as a payment program, etc.

[0053] Secondary merchant: can refer to a platform, which opens an account and builds a relationship through the Application Programming Interface (API) of the platform.

[0054] Future: can refer to the result of asynchronous execution, when the asynchronous execution is completed, the returned result will be saved in Future, such as Future in Java 1.5, which can be used for asynchronous result acquisition.

[0055] CompletionService: can refer to the interface newly added in Java 1.8, which is used to solve the problem of Future blocking, specifically, after submitting a task, the return value can be obtained according to the completion order of the task, and the return value of the task can be obtained while processing the task.

[0056] With the rapid development of electronic payment, online merchants have become a very important consumption way in life. However, in the process of business dealings, if the merchant violates the signed contract and reaches a certain degree, or for the merchant with certain bad records provided by the regulatory agency, these merchants will be added to the blacklist, and the blacklisted merchants will be restricted from performing certain businesses.

[0057] The core of the existing finance is risk control, that is, the control of risk and the control of customer fund safety, and the credit card management has very strict requirements for risk control, so usually the credit card system needs to go through complex processing logic and verification rules for authorizing a financial transaction, especially the verification of the blacklist. Especially in the online payment scene of Hui Fu, there may be merchants that produce transaction risks, therefore, it is necessary to quickly and effectively identify the risk merchants that endanger the safety of user accounts and funds.

[0058] In a possible implementation, a risk merchant intelligent identification method can be used to identify a risk merchant. Specifically, historical data is processed, aggregated, and feature extracted, and then model training and model deployment are performed. Further, external data is collected in real time, and the collected real-time data and offline data are merged. Feature calculation is performed on the merged data, and the data after feature calculation is pushed to a message queue. Based on the deployed model, features are obtained from the pushed message queue, and it is determined whether the merchant is a risk merchant based on the model.

[0059] However, the above scheme is based on a model to determine whether a merchant is a risk merchant, and does not use a blacklist identification method to determine a risk user, and the process is complex.

[0060] In another possible implementation, a risk merchant identification method, device, electronic equipment, and storage medium are used. A merchant association graph is constructed, the association relationship between merchants in different scenarios is focused on, and a risk result of the target merchant is obtained. This method is a method for identifying associated risk merchants, and does not reflect how to accelerate the identification of blacklisted merchants.

[0061] In another possible implementation, a transaction data processing method, device, equipment, and storage medium are used. Index operation is performed on transaction data to determine whether a to-be-identified merchant is a suspected risk merchant. If the to-be-identified merchant is a suspected risk merchant, the corresponding funds are frozen. This method is a method for identifying risk transactions, and does not query blacklisted users.

[0062] Therefore, the management and control of risk merchants can be handled by using a blacklist comparison method. Specifically, merchants can be divided into first-level merchants and second-level merchants. The historical transaction data features of the second-level merchants or information of a regulatory agency are analyzed to configure a blacklist of the second-level merchants. The second-level merchants on the blacklist are processed and verified in turn. The long verification and processing logic results in a long response time of transactions, low efficiency, and poor customer experience.

[0063] In another possible implementation, an internet financial blacklist system based on big data and an application method thereof are used. A large amount of internet financial blacklist data is processed offline by an offline data index module, features are extracted and efficiently indexed, when a service request is received, the blacklist data is queried in real time by an online data query module, the online data query module directly uses the results generated by the offline service to perform real-time evaluation and calculation on the service data, and provides a unified interface for querying and giving a response.

[0064] The above method adopts the application method of the blacklist to query the blacklist, but it is resource-consuming to crawl user blacklist data and establish data index, and it takes a long time to clean, integrate, and even analyze data association and establish a data model, and the query rate is slow.

[0065] Therefore, the efficiency of serial query and serial processing is the worst, firstly, the overall response time depends on the processing order, and secondly, time-consuming queries will affect subsequent queries. To solve the problem of serial query, a parallel query can be used to speed up the solution.

[0066] In another possible implementation, a credit card transaction verification method and system are adopted. By obtaining transaction information, a plurality of components related to credit card information are called in parallel to query the credit card information corresponding to the transaction information. According to the credit card information corresponding to the transaction information, verification is also performed in parallel to obtain the verification result of the transaction information. The credit card transaction verification method reduces the response time of credit card transactions and improves verification efficiency.

[0067] However, the above method adopts parallel verification of transaction information, but the result is returned only after all verification processes are completed, that is, the return of the result is still serial, and the improvement effect is limited, and the response time is long.

[0068] To solve the above problems, the present application provides a blacklist processing method, which uses parallel query queuing processing (CompletionService) to query the blacklist, that is, according to the size of the merchant list to be queried, the number of core threads of the thread pool used is set, further, query sub-tasks are constructed to query the blacklist and put into the thread pool for parallel execution. When the sub-task has a query result, the query result is put into the queue according to the order of return, and the query result is continuously taken out from the queue for processing. Without requiring all query results to be obtained, as long as the preset condition is met, the ongoing task query can be interrupted in advance to save resource consumption, reduce resource waste, and speed up the query efficiency.

[0069] The embodiments of the present application will be described below with reference to the accompanying drawings. Figure 1 A schematic diagram of an application scenario provided by the embodiments of the present application is shown in FIG. 1. The blacklist processing method provided by the present application can be applied to, for example, Figure 1The application scenario shown. The application scenario includes: the first terminal device 101, the second terminal device 102 and the third terminal device 103, the query processing system 104 and the cloud 105; wherein, the query processing system 104 provides an interface for the terminal device to query, such as providing interface 1 for the first terminal device 101, providing interface 2 for the second terminal device 102, and providing interface 3 for the third terminal device 103; the cloud 105 is used to provide a blacklist library for the query processing system 104, which is used for blacklist query.

[0070] Specifically, taking the first terminal device 101 as an example, the first terminal device 101 sends a query task request to the query processing system 104, and the query processing system 104 obtains a list of to-be-inquired merchants and query requirements based on the query task request, such as a list of second-level merchants including four second-level merchants A, B, C and D, and a query requirement that the query process is ended in advance as long as one second-level merchant hits the blacklist; further, the query processing system 104 calls threads to query the to-be-inquired merchants in the list of to-be-inquired merchants for the blacklist, and obtains query results, assuming that the query results are: no hit in the blacklist (corresponding to a response time of 80ms), no hit in the blacklist (corresponding to a response time of 40ms), hit in the blacklist (corresponding to a response time of 60ms), and hit in the blacklist (corresponding to a response time of 60ms).

[0071] By using the parallel query queuing processing method for blacklist query, since the query is executed in parallel, the query results are put into the queue according to the return time, that is, at 40ms, the result of the second-level merchant B is found, no hit in the blacklist and continue to query, at 60ms, the result of the second-level merchant C or D is found, hit in the blacklist and the return result is generated and the process is ended in advance, and the corresponding response time of the processing process is 60ms. Correspondingly, the query processing system 104 can send the return result to the first terminal device 101 for visual display.

[0072] It can be understood that if the serial query serial processing method is used for blacklist query, assuming that the second-level merchant C or D is queried last, the maximum response time is 80ms+40ms+60ms=180ms. Assuming that the second-level merchant C or D is queried first, the minimum response time is 60ms, and the response time is determined according to the order of query.

[0073] If the blacklist query is processed in a parallel query serial processing (Future) mode, the corresponding query is parallel, but the processing result is serial. If the result of the second-level merchant C or D is processed last, and the second-level merchant A needs 80 ms to end, the maximum response time is 80 ms; if the result of the second-level merchant C or D is processed first, and the second-level merchant C or D needs a response time of 60 ms, the minimum response time is 60 ms. Although parallel query reduces the response time, there may still be a long response time of 80 ms.

[0074] It should be noted that different terminal devices can send different query task requests, that is, corresponding to different levels of to-be-queried merchant lists and query requirements, and the embodiments of the present application do not make specific limitations thereon. For example, the second terminal device 102 can send a query task request to the query processing system 104, and the second-level to-be-queried merchant list obtained based on the query task request includes 10 to-be-queried merchants, and the query requirement is that 9 second-level merchants hit the blacklist, and the query process is ended in advance, and the corresponding processing process is similar to the above processing process; the third terminal device 103 is also similar, and will not be described here.

[0075] The terminal device can also be referred to as a terminal, a user equipment (UE), a mobile station (MS), a mobile terminal (MT), etc. The terminal device can be a mobile phone, a smart television, a wearable device, a smart speaker, a smart security device, a smart gateway, a tablet computer (Pad), a computer with wireless transceiver function, a virtual reality (VR) terminal device, an augmented reality (AR) terminal device, a wireless terminal in industrial control, a wireless terminal in self-driving, a wireless terminal in remote medical surgery, a wireless terminal in smart grid, a wireless terminal in transportation safety, a wireless terminal in smart city, a wireless terminal in smart home, etc.

[0076] The technical solutions of the present application and how the technical solutions of the present application solve the above technical problems will be described in detail below with specific embodiments. The following specific embodiments can be combined with each other, and the same or similar concepts or processes may not be described again in some embodiments. The embodiments of the present application will be described below with reference to the accompanying drawings.

[0077] Based on Figure 1 The application embodiment provides a black list processing method based on the application scenario shown in the figure. Figure 2 The application embodiment provides a flow chart of a black list processing method. As shown in the figure, the black list processing method comprises the following steps. Figure 2

[0078] S201, receiving a query task request, and obtaining a to-be-checked merchant list and a preset hit threshold based on the query task request; the to-be-checked merchant list comprises at least one to-be-checked merchant, and the preset hit threshold is the number of times of hitting the black list based on the application scenario.

[0079] Each first-level merchant corresponds to a corresponding merchant list, and a first-level merchant can correspond to multiple second-level merchants.

[0080] In the application embodiment, the preset hit threshold can refer to a threshold set in advance for determining whether the number of to-be-checked merchants hitting the black list meets the query requirement. Different application scenarios correspond to different query requirements. For example, in the bank scenario of online payment, the query requirement can be set as that there is one second-level merchant hitting the black list in the first-level merchant, and then the query is ended in advance, and the corresponding preset hit threshold is 1. Because the security level required for bank payment is high, as long as there is one, the first-level merchant can be rejected.

[0081] It should be noted that different application scenarios can set different preset hit thresholds, and the application embodiment does not make specific limitation on this. The preset hit threshold can also be modified artificially.

[0082] S202, configuring one thread for each to-be-checked merchant in the to-be-checked merchant list.

[0083] In this step, the number of core threads of the thread pool used is set according to the number of to-be-checked merchants in the to-be-checked merchant list. For example, if the number of to-be-checked second-level merchants is 4, 4 threads need to be configured.

[0084] S203, based on the query task request, using at least one thread to query and process the to-be-checked merchant list, obtaining at least one query result, and adding the at least one query result to the queue; the query result is the result of whether the to-be-checked merchant in the to-be-checked merchant list hits the black list.

[0085] In this step, for each to-be-checked merchant, a corresponding query subtask is constructed, the query subtask is bound to a thread, put into the thread pool, and concurrent query is started to obtain the query result. Because the response time corresponding to the black list query of different to-be-checked merchants is different, the query result is put into the queue according to the order of return by listening to the query result of each thread. ​

[0086] S204, based on the adding order of the query results in the queue, the number of the query results hitting the blacklist is counted in sequence, and when it is determined that the number of the query results hitting the blacklist is greater than a preset hitting threshold, a return result is generated; the return result is used to indicate that all the to-be-searched merchants in the to-be-searched merchant list are blacklist merchants.

[0087] In the embodiment of the application, the adding order corresponds to the return order of the query results. Alternatively, the adding order can also be determined based on the priority of the to-be-searched merchant. For example, if a to-be-searched merchant has a high priority, the to-be-searched merchant is preferentially added to the first position of the queue. Similarly, other to-be-searched merchants are added to the queue according to the priority from high to low, and there is an adding order. In the case where the to-be-searched merchant does not have a corresponding priority, the return order of the query results can be used, and the embodiment of the application does not make a specific limitation.

[0088] In this step, based on the return order of the query results, the returned query results are obtained from the query result queue in a loop, and the number of times of hitting the blacklist in the query results is counted. If the number of times is greater than a preset hitting threshold, the loop is exited, the query task that has not been completed is cancelled, and a return result is generated to reject the first-level merchant. Because the number of times of hitting the blacklist of the to-be-searched merchants in the second-level merchant list corresponding to the first-level merchant is too large, other to-be-searched merchants can not be queried, and the resource consumption is saved.

[0089] For example, in the application scenario of Figure 1 if there are other query requirements, for example, the to-be-searched merchant hits X blacklists to end, 1<=X<=number of merchants, the response time of the parallel query queuing processing (CompletionService) is the response time of the Xth hit merchant after sorting according to the response time. If X=2, the corresponding response time is 60ms.

[0090] It can be understood that if the response time of the serial query serial processing is greater than or equal to the sum of the response times of the first X hit merchants, that is, the minimum response time is 120ms; if the response time of the parallel query serial processing (Future) is greater than or equal to the maximum response time of the first X hit merchants, that is, the minimum response time is 60ms.

[0091] Specifically, if the processing order of the parallel query serial processing (Future) is the second-level merchants C and D, the corresponding response time is 60ms; assuming that the processing order is the second-level merchants A, C and D, the corresponding response time is 80ms, so the minimum response time is 60ms.

[0092] Different from the way of using parallel query queuing processing (CompletionService), the processing order is the second-level merchants C and D, and the last response time is 60 ms.

[0093] By comparison, it is found that compared with the way of serial query serial processing and parallel query serial processing, the way of parallel query queuing processing can reduce the overall response time.

[0094] Therefore, the application provides a blacklist processing method, which can receive a query task request, obtain a list of to-be-searched merchants and a query requirement, set the number of core threads of a thread pool according to the number of to-be-searched merchants in the list of to-be-searched merchants, and then construct query sub-tasks, put the query sub-tasks into the thread pool for parallel execution, that is, each thread processes one to-be-searched merchant, and further, when the query sub-tasks have query results, the query results are added to a queue, the query results are continuously taken out from the queue for processing, and the number of times of hitting the blacklist is counted; if the number of times of hitting the blacklist satisfies the query requirement, that is, greater than a preset hit threshold, a return result is generated, and the query process ends in advance, thereby accelerating the query efficiency. The application processes the query results by putting the query results into the queue and using the queuing way of returning first and processing first, thereby reducing the overall response time.

[0095] Optionally, at least one thread is used to perform query processing on the list of to-be-searched merchants to obtain at least one query result, including:

[0096] If the number of to-be-searched merchants in the list of to-be-searched merchants is one, one thread is used to perform query processing on the list of to-be-searched merchants in a serial processing manner to obtain one query result.

[0097] If the number of to-be-searched merchants in the list of to-be-searched merchants is multiple, multiple threads are used to perform query processing on the list of to-be-searched merchants in a parallel processing manner to obtain multiple query results.

[0098] In this step, since there is no correlation between the query of the second-level merchants, parallel query can be used, so for a specific query business scenario of multiple to-be-searched merchant blacklists, parallel query is used to improve the query efficiency, but if the number of to-be-searched merchants in the list of to-be-searched merchants is one, one thread can be used to perform query processing on the list of to-be-searched merchants in a serial processing manner, thereby saving resources.

[0099] Therefore, the application embodiment can use different query ways for different business situations, thereby improving the flexibility of query.

[0100] Optionally, the at least one query result is added to a queue, including:

[0101] obtaining a return time of the at least one query result, the return time being a response time of processing the queried merchant;

[0102] generating an adding order based on the size of the return time, and adding the at least one query result into the queue based on the adding order.

[0103] In this step, for different business requirements, the processing of the query result is optimized by the queuing processing mode. Since the response time of processing the queried merchant is different, the return time of the query result corresponding to each queried merchant is also different, that is, the return time of the query result is obtained, the adding order is generated based on the size of the return time, and the query result is added into the queue in turn based on the adding order.

[0104] It should be noted that if the return time of two or more query results is the same, the adding order can be sorted according to the priority of the queried merchant or randomly sorted, which is not limited in the embodiment of the application.

[0105] Therefore, by querying the blacklist of the merchant, the query result is returned first, and the completed query is processed first in the queuing mode, which reduces the overall response time, can adapt to different business requirements, and reduces resource consumption.

[0106] Optionally, when it is determined that the number of the hit blacklist merchants is greater than a preset hit threshold, a return result is generated, including:

[0107] When it is determined that the number of the hit blacklist merchants is greater than a preset hit threshold, the query processing is interrupted, and the attribute information and the transaction relationship information of the queried merchant in the queried merchant list are monitored;

[0108] The association relationship of the queried merchant is determined according to the attribute information and the transaction relationship information, and the risk level of the queried merchant is determined based on the association relationship;

[0109] The return result is generated based on the risk level, and the return result is visually displayed; wherein the return result is also used to indicate the risk level of each blacklist merchant.

[0110] In the embodiment of the application, the attribute information of the merchant includes one or more of the operator information, the operating system information, the contact information and the settlement information of the current merchant, and the interaction information includes one or more of the registration information, the login information, the order information, the payment information and the operation information of the current merchant.

[0111] In this step, the association relationship of the to-be-searched merchant is determined according to the attribute information and transaction relationship information of the merchant, that is, whether the blacklisted merchants have an association relationship. It can be determined that the blacklisted merchants have an association relationship according to whether the attribute information and / or interaction information corresponding to the blacklisted merchants are the same or the number of overlapping information is greater than a threshold value. For example, if the same operator information corresponds to three blacklisted merchants, it is determined that the three blacklisted merchants have an association relationship.

[0112] Further, the risk level can be determined according to whether there is an association relationship and the association degree, that is, the risk level of the blacklisted merchants with an association relationship is higher than that of the blacklisted merchants without an association relationship. For the blacklisted merchants with an association relationship, the higher the association degree, the higher the risk level. The association degree is determined based on the number of overlapping information. For example, the risk level of three blacklisted merchants with an association relationship is higher than that of two blacklisted merchants with an association relationship.

[0113] Further, the return result is generated based on the risk level corresponding to the blacklisted merchant, and the return result is visually displayed to remind the administrator to limit the corresponding permission for the blacklisted merchant with different risk levels.

[0114] It can be understood that the higher the risk level, the fewer the corresponding use permissions, that is, the more the disabled permissions. The application embodiments do not specifically limit the types and numbers of disabled permissions for different risk levels.

[0115] Therefore, under the condition of not requiring to obtain all query results, as long as the preset condition is met, that is, the number of blacklisted merchants is greater than the preset hit threshold, the ongoing time-consuming query can be interrupted in advance to save resource consumption. Further, by determining the blacklist level, the administrator can comprehensively understand the information of the blacklisted user and perform corresponding operations.

[0116] Optionally, the method further comprises:

[0117] When it is determined that the number of blacklisted merchants is less than or equal to the preset hit threshold, a processing result is generated, and the processing result is used to indicate that the to-be-searched merchant in the to-be-searched merchant list is a whitelisted merchant.

[0118] In this step, when it is determined that the number of blacklisted merchants is less than or equal to the preset hit threshold, a processing result is generated. The processing result corresponds to a first-level merchant and a second-level merchant corresponding to the first-level merchant. The second-level merchant can be regarded as a whitelisted user, and the whitelisted user is stored. Correspondingly, the blacklisted merchant in the above-mentioned embodiments can also be stored to enrich the blacklist library.

[0119] Therefore, the application embodiment distinguishes and stores the black list and the white list of the to-be-searched merchant, facilitates subsequent query and use, and improves the flexibility of processing.

[0120] Optionally, the method further comprises:

[0121] After determining that the to-be-searched merchant in the to-be-searched merchant list is a black list merchant, the black list merchant is intercepted and processing, and an audit prompt information is sent to the black list merchant to prompt the black list merchant to upload the merchant information.

[0122] In the application embodiment, the merchant information includes but is not limited to: bank registration information, legal person credit information, tax record information, etc., wherein the bank registration information includes at least one of name information, address information, important personnel information, account information, business scope information, etc., and can also include legal identity card photos or business license photos, etc.

[0123] It should be noted that the merchant information can also be obtained from multiple different data sources, for example, the bank registration information, tax record information of the merchant stored in the server of some administrative organ, and the legal person credit information of the merchant stored in the server of the bank, etc. The application does not make specific limitations on the specific content and source of the merchant information, which can represent the valid identity of the merchant and be used to verify the security of the merchant.

[0124] In this step, after determining that a certain to-be-searched merchant is a black list merchant, the black list merchant can be intercepted and processed, and an audit prompt information can be sent to the black list merchant to prompt the black list merchant to upload the merchant information, which is used to verify whether the identity of the merchant is safe and real. The audit prompt information can be sent to the terminal device corresponding to the merchant in the form of a short message or a display prompt box. The application embodiment does not make specific limitations on the content and sending form of the audit prompt information. The content of the audit prompt information can include the risk level and some processing operations of the system on the merchant.

[0125] Therefore, the application embodiment can intercept and process the black list merchant, and improve the security of the system.

[0126] Optionally, the method further comprises:

[0127] The merchant information of each black list merchant is obtained, and for each black list merchant, the identification operation of the content in the merchant information is sequentially performed to audit the black list merchant and obtain an audit result.

[0128] When the audit result is determined to be passed, the black list merchant is deleted from the black list library; the black list library pre-stores a black list for comparison.

[0129] In the embodiments of the present application, the identification operation can include character recognition operation, keyword recognition operation, and face recognition operation, etc., for judging whether the merchant information of the blacklisted merchant is real and correct. The specific operation of the identification operation is not limited in the embodiments of the present application, which can also be manually identified, and the identification result is uploaded.

[0130] In this step, for each blacklisted merchant, the merchant information corresponding to the blacklisted merchant is sequentially subjected to an identification operation, such as identifying the legal person credit information, account information, bank registration information, and identifying the legal person ID photo or business license photo, etc., and then the blacklisted merchant is audited to obtain an audit result. The identification method can be input into a machine model or a pre-defined algorithm. The machine model and the pre-defined algorithm are not limited in the embodiments of the present application. The machine model can be a convolutional neural network model based on deep learning.

[0131] When it is determined that the audit result is passed, the blacklisted merchant can be deleted from the blacklist library to update the pre-stored blacklist in the blacklist library. The blacklist library can be obtained by crawling the merchant blacklist data on the Internet, or obtained from model training, cloud, etc. The embodiments of the present application are not limited in this regard.

[0132] Therefore, the embodiments of the present application can audit the identified blacklisted merchant to determine whether it meets the blacklist, i.e., perform identity authentication, and improve the accuracy of execution.

[0133] In combination with the above embodiments, Figure 3 A specific flowchart of a blacklist processing method provided by the embodiments of the present application is shown in Figure 3 The blacklist processing method includes the following steps:

[0134] Step A: information acquisition, i.e., the secondary merchant list and the hit frequency threshold (preset hit threshold) can be obtained based on the input parameters corresponding to the query task request, and step B is executed.

[0135] Step B: concurrent query, i.e., the thread pool size is set according to the size of the merchant list, i.e., the number of threads is set to the number of secondary merchants to be searched, and for each secondary merchant to be searched, a corresponding query subtask is constructed, and the thread is bound and added to the thread pool for concurrent calling. During the query process, it is judged whether the subtask is completed. If yes, step C is executed, otherwise, the subtask is waited to be completed.

[0136] Step C: a queuing process is performed, that is, a query result returned by each thread is listened to, if a subtask is completed, that is, there is a query result corresponding to it, the query result is added to a result queue, and a loop is performed to obtain the returned query result from the result queue, the hit number is counted, and it is judged whether the user list is processed completely, if yes, a missed return result (processing result) is generated, if not, step D is executed.

[0137] Step D: it is judged whether the hit blacklist number is greater than the hit number threshold, if yes, a hit return result is generated, and the loop is exited, the query subtask not completed is cancelled, and the process is ended in advance, if not, step C is executed.

[0138] Therefore, the application not only uses a parallel mode to execute a subquery task, but also uses a queue to store a query result of the subtask, and for processing the query result, the query result can be processed in sequence according to the return order of the subtask, the processing of the query result is optimized, the efficiency is improved, the blacklisted merchant is quickly processed, and the response time is reduced.

[0139] In the foregoing embodiment, the black list processing method provided by the embodiment of the application is introduced, and in order to realize each function in the method provided by the embodiment of the application, the electronic device as an execution subject can include a hardware structure and / or a software module, and each function is realized in the form of a hardware structure, a software module, or a hardware structure plus a software module. Whether a certain function in the foregoing functions is executed in the form of a hardware structure, a software module, or a hardware structure plus a software module depends on the specific application of the technical solution and the design constraint conditions.

[0140] For example, Figure 4 A structure diagram of a black list processing device provided by the embodiment of the application, the device includes an acquisition module 410, a configuration module 420, a query module 430, and a return module 440; wherein the acquisition module 410 is configured to receive a query task request, and acquire a to-be-searched merchant list and a preset hit threshold based on the query task request; the to-be-searched merchant list includes at least one to-be-searched merchant, and the preset hit threshold is a number of times of hitting a blacklist based on an application scenario;

[0141] The configuration module 420 is configured to configure one thread for each to-be-searched merchant in the to-be-searched merchant list;

[0142] The query module 430 is configured to perform query processing on the to-be-searched merchant list based on the query task request by using at least one thread, obtain at least one query result, and add the at least one query result to a queue; the query result is a result of whether a to-be-searched merchant in the to-be-searched merchant list hits a blacklist;

[0143] The return module 440 is configured to: sequentially count the number of hit blacklist merchants in the query results based on an adding order of the query results in a queue; and generate a return result when it is determined that the number of hit blacklist merchants is greater than a preset hit threshold; the return result is used to indicate that all the to-be-searched merchants in the to-be-searched merchant list are blacklist merchants.

[0144] Optionally, the query module 430 includes a query unit and an adding unit; the query unit is configured to:

[0145] If the number of to-be-searched merchants in the to-be-searched merchant list is one, the to-be-searched merchant list is processed by using one thread in a serial processing manner to obtain one query result;

[0146] If the number of to-be-searched merchants in the to-be-searched merchant list is more than one, the to-be-searched merchant list is processed by using multiple threads in a parallel processing manner to obtain multiple query results.

[0147] Optionally, the adding unit is configured to:

[0148] obtain a return time of the at least one query result, the return time being a response time of processing a to-be-searched merchant;

[0149] generate an adding order based on the size of the return time, and add the at least one query result into the queue based on the adding order.

[0150] Optionally, the return module 440 is specifically configured to:

[0151] when it is determined that the number of hit blacklist merchants is greater than the preset hit threshold, interrupt the query processing, and monitor attribute information and transaction relationship information of the to-be-searched merchants in the to-be-searched merchant list;

[0152] determine an association relationship of the to-be-searched merchants according to the attribute information and the transaction relationship information, and determine a risk level of the to-be-searched merchants based on the association relationship;

[0153] generate a return result based on the risk level, and visually display the return result; the return result is also used to indicate the risk level of each blacklist merchant.

[0154] Optionally, the apparatus further includes a generation module, the generation module is configured to:

[0155] when it is determined that the number of hit blacklist merchants is less than or equal to the preset hit threshold, generate a processing result, the processing result is used to indicate that the to-be-searched merchants in the to-be-searched merchant list are whitelist merchants.

[0156] Optionally, the apparatus further comprises an intercepting module, configured to:

[0157] After determining that the merchant to be checked in the list of merchants to be checked is a blacklisted merchant, intercepting the blacklisted merchant, and sending an audit prompt information to the blacklisted merchant to prompt the blacklisted merchant to upload merchant information.

[0158] Optionally, the apparatus further comprises an audit module, configured to:

[0159] Obtaining merchant information of each blacklisted merchant, and performing, for each blacklisted merchant, an identification operation on the content in the merchant information in sequence to audit the blacklisted merchant and obtain an audit result.

[0160] When the audit result is determined to be passed, the blacklisted merchant is deleted from a blacklist library; the blacklist library pre-stores a blacklist for comparison.

[0161] The specific implementation principles and effects of the blacklisted processing apparatus provided by the embodiments of the present application can be referred to the related descriptions and effects of the corresponding embodiments described above, and will not be described in detail here.

[0162] For example, the embodiments of the present application also provide a structural schematic diagram of an electronic device, Figure 5 For the structural schematic diagram of an electronic device provided by the embodiments of the present application, as Figure 5 shown, the electronic device can include a processor 501 and a memory 502 in communication with the processor; the memory 502 stores a computer program; the processor 501 executes the computer program stored in the memory 502, so that the processor 501 executes the method described in any of the above embodiments.

[0163] The memory 502 and the processor 501 can be connected through a bus 503.

[0164] The embodiments of the present application also provide a computer readable storage medium, which stores computer program execution instructions, and the computer program execution instructions are executed by a processor to implement the method in any of the preceding embodiments of the present application.

[0165] The embodiments of the present application also provide a chip running instruction, which is used to execute the method described in any of the preceding embodiments executed by the electronic device in any of the preceding embodiments of the present application.

[0166] The embodiments of the present application also provide a computer program product, which includes a computer program, and the computer program is executed by a processor to implement the method described in any of the preceding embodiments executed by the electronic device in any of the preceding embodiments of the present application.

[0167] In several embodiments provided in the present application, it should be understood that the disclosed apparatus and method can be implemented by other manners. For example, the apparatus embodiments described above are merely illustrative, for example, the division of the modules is merely a logical function division, and actual implementation can have another division manner, for example, a plurality of modules or components can be combined or integrated into another system, or some features can be ignored or not executed. In addition, the coupling or direct coupling or communication connection between the displayed or discussed modules can be indirect coupling or communication connection between the modules through some interfaces, apparatuses or modules, and can be electrical, mechanical or other forms.

[0168] The modules illustrated as separate components can or can not be physically separated, and the components illustrated as modules can or can not be physical units, that is, can be located in one place, or can be distributed to a plurality of network units. Part or all of the modules can be selected to implement the embodiment scheme according to actual needs.

[0169] In addition, the function modules in each embodiment of the present application can be integrated in one processing unit, or each module can be physically present alone, or two or more modules can be integrated in one unit. The unit formed by the above modules can be realized in the form of hardware or in the form of hardware plus software function unit.

[0170] The integrated modules realized in the form of software function modules can be stored in a computer readable storage medium. The software function modules stored in the storage medium include a plurality of instructions for causing a computer device (which can be a personal computer, a server, or a network device, etc.) or a processor to execute part of the steps of the method described in each embodiment of the present application.

[0171] It should be understood that the processor can be a central processing unit (CPU), and can also be other general-purpose processors, digital signal processors (DSP), application specific integrated circuits (ASIC), etc. The general-purpose processor can be a microprocessor or the processor can also be any conventional processor and the like. The steps of the method disclosed in the present application can be directly embodied as hardware processor execution, or executed by a combination of hardware and software modules in the processor.

[0172] The memory can include a high-speed Random Access memory (RAM) and can also include a Non-volatile Memory (NVM), such as at least one disk memory, and can also be a U disk, a mobile hard disk, a read-only memory, a magnetic disk or an optical disk, etc.

[0173] The bus can be an Industry Standard Architecture (ISA) bus, a Peripheral Component Interconnect (PCI) bus, or an Extended Industry Standard Architecture (EISA) bus, etc. The bus can be divided into an address bus, a data bus, a control bus, etc. For the sake of representation, the bus in the drawings of the present application does not limit to only one bus or one type of bus.

[0174] The storage medium described above can be realized by any type of volatile or non-volatile storage device or a combination thereof, such as Static Random-Access Memory (SRAM), Electrically Erasable Programmable Read Only Memory (EEPROM), Erasable Programmable Read-Only Memory (EPROM), Programmable Read-Only Memory (PROM), Read-Only Memory (ROM), magnetic storage, flash memory, magnetic disk or optical disk. The storage medium can be any available medium that can be accessed by a general-purpose or special-purpose computer.

[0175] An exemplary storage medium is coupled to the processor, so that the processor can read information from the storage medium and can write information to the storage medium. Of course, the storage medium can also be an integral part of the processor. The processor and the storage medium can be located in an Application Specific Integrated Circuit (ASIC). Of course, the processor and the storage medium can also exist as discrete components in an electronic device or a host device.

[0176] The above merely illustrates the specific implementation of the embodiments of the present application, but the protection scope of the embodiments of the present application is not limited to this. Any change or replacement within the technical scope disclosed by the embodiments of the present application should be covered in the protection scope of the embodiments of the present application. Therefore, the protection scope of the embodiments of the present application should be subject to the protection scope of the claims.

Claims

1. A black list processing method characterized by comprising: The method comprises: receiving a query task request and obtaining a list of to-be-checked merchants and a preset hit threshold based on the query task request; the list of to-be-checked merchants comprises at least one to-be-checked merchant, and the preset hit threshold is the number of query hits of a blacklist based on an application scenario; configuring one thread for each to-be-checked merchant in the list of to-be-checked merchants; based on the query task request, using at least one thread to perform query processing on the list of to-be-checked merchants to obtain at least one query result, and adding the at least one query result to a queue; the query result is the result of whether a to-be-checked merchant in the list of to-be-checked merchants hits a blacklist; based on the order of adding the query result to the queue, sequentially counting the number of merchants that hit the blacklist in the query result, and when it is determined that the number of merchants that hit the blacklist is greater than the preset hit threshold, generating a return result; the return result is used to indicate that all to-be-checked merchants in the list of to-be-checked merchants are blacklist merchants and the risk level of each blacklist merchant; when it is determined that the number of merchants that hit the blacklist is greater than the preset hit threshold, generating a return result, comprising: when it is determined that the number of merchants that hit the blacklist is greater than the preset hit threshold, interrupting the query processing, determining that all to-be-checked merchants in the list of to-be-checked merchants are blacklist merchants, and monitoring the attribute information and transaction relationship information of the blacklist merchants; if the attribute information and / or interaction information corresponding to the blacklist merchants are the same, or the number of overlapping information corresponding to the attribute information and / or interaction information of the blacklist merchants is greater than a preset threshold, it is determined that there is an association relationship between the blacklist merchants; determining the risk level of the blacklist merchants according to the association relationship and the association degree; wherein the association degree is determined based on the number of overlapping information, and the association degree is positively correlated with the risk level; the risk level of blacklist merchants with an association relationship is higher than that of blacklist merchants without an association relationship; generating the return result based on the risk level, and visually displaying the return result.

2. The method of claim 1, wherein, using at least one thread to perform query processing on the list of to-be-checked merchants to obtain at least one query result, comprising: if the number of to-be-checked merchants in the list of to-be-checked merchants is one, using one thread to perform query processing on the list of to-be-checked merchants in a serial processing manner to obtain one query result; if the number of to-be-checked merchants in the list of to-be-checked merchants is multiple, using multiple threads to perform query processing on the list of to-be-checked merchants in a parallel processing manner to obtain multiple query results.

3. The method of claim 1, wherein, adding the at least one query result to the queue, comprising: obtaining the return time of the at least one query result, the return time being the response time of processing a to-be-checked merchant; generating an adding order based on the size of the return time, and adding the at least one query result to the queue based on the adding order.

4. The method of claim 3, wherein, The method further comprises: when it is determined that the number of merchants that hit the blacklist is less than or equal to the preset hit threshold, generating a processing result, the processing result being used to indicate that the to-be-checked merchants in the list of to-be-checked merchants are whitelist merchants.

5. The method according to any one of claims 1 to 4, characterized in that, The method further comprises: After determining that a blacklisted merchant in the list of merchants to be checked, intercepting the blacklisted merchant and sending an audit prompt to the blacklisted merchant to prompt the blacklisted merchant to upload merchant information.

6. The method of claim 5, wherein, The method further comprises: Obtaining merchant information of each blacklisted merchant, and sequentially performing an identification operation on the content in the merchant information for each blacklisted merchant to audit the blacklisted merchant and obtain an audit result; When the audit result is determined to be passed, the blacklisted merchant is deleted from the blacklist library; the blacklist library pre-stores a blacklist for comparison.

7. A black list processing apparatus characterized by comprising: The device comprises: An acquisition module configured to receive a query task request and acquire a list of merchants to be checked and a preset hit threshold based on the query task request; the list of merchants to be checked comprises at least one merchant to be checked, and the preset hit threshold is the number of hits of a blacklist based on an application scenario; A configuration module configured to configure a thread for each merchant to be checked in the list of merchants to be checked; A query module configured to perform query processing on the list of merchants to be checked based on the query task request using at least one thread, obtain at least one query result, and add the at least one query result to a queue; the query result is a result of whether a merchant to be checked in the list of merchants to be checked hits a blacklist; A return module configured to sequentially count the number of merchants hitting a blacklist in the query result based on the order of addition of the query result in the queue, and generate a return result when the number of merchants hitting a blacklist is determined to be greater than the preset hit threshold; the return result is used to indicate that all merchants to be checked in the list of merchants to be checked are blacklisted merchants and the risk level of each blacklisted merchant; The return module is specifically configured to interrupt query processing when the number of merchants hitting a blacklist is determined to be greater than the preset hit threshold, determine that all merchants to be checked in the list of merchants to be checked are blacklisted merchants, and monitor attribute information and transaction relationship information of the blacklisted merchants; if the attribute information and / or interaction information corresponding to the blacklisted merchants are the same or the number of overlapping information corresponding to the attribute information and / or interaction information of the blacklisted merchants is greater than a preset threshold, it is determined that the blacklisted merchants have an association relationship; the risk level of the blacklisted merchants is determined according to the association relationship and the association degree; the association degree is determined based on the number of overlapping information, the association degree is positively correlated with the risk level, the risk level of blacklisted merchants with an association relationship is higher than that of blacklisted merchants without an association relationship, the return result is generated based on the risk level, and the return result is visually displayed.

8. An electronic device, comprising: Comprise: A processor and a memory connected in communication with the processor; The memory stores computer execution instructions; The processor executes the computer execution instructions stored in the memory to implement the method of any one of claims 1-6.

9. A computer-readable storage medium, characterized in that, The computer readable storage medium stores computer-executable instructions that, when executed by a processor, implement the method of any one of claims 1-6.

10. A computer program product, characterised in that, A computer program that, when executed by a processor, implements the method of any one of claims 1-6.

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