A method and system for processing card binding business

Abstract

This specification discloses a method and system for processing card binding services. In the embodiments of this specification, for each bank, a simulated card binding request is sent to the bank server of the bank through the cloud real machine according to the detection frequency corresponding to the bank. The bank server returns a response result, and the cloud real machine reports the response information to the payment platform server based on the response result. The payment platform server determines whether there is an abnormality in the bank server of the bank based on the response information. If there is an abnormality, the card binding entrance corresponding to the bank is closed. If there is no abnormality, the card binding entrance corresponding to the bank is opened. In this method, it is possible to timely determine whether there is an abnormality in the bank server from the response result obtained by continuously sending the card binding request to the bank server by the cloud real machine, and close or open the card binding entrance of the corresponding bank based on the judgment result. In this way, the bank card binding entrances displayed to the user can all perform the card binding service, thereby improving the user experience.

Description

Technical Field

[0001] The present invention relates to the field of payment technology, and in particular to a method and system for processing card binding services. Background Art

[0002] In the payment field, payment platforms usually set up a one-click card binding business module, so that users can quickly bind their bank cards without entering the card number.

[0003] When users bind their bank cards, the payment platform only provides binding entries for each bank card. After users click on the binding entry of a designated bank, they will go through a series of identity authentication and be redirected to the card binding page of the designated bank. Users will then perform the card binding operation on the card binding page.

[0004] However, since the payment platform system is not connected to the bank system, when a bank system fails, the payment platform cannot promptly close the card binding entrance of the bank with the system failure, causing the payment platform to still provide the card binding entrance of the bank with the system failure to users, thereby reducing the user experience. Summary of the invention

[0005] The embodiments of this specification provide a method and system for processing a card binding service to partially solve the problems existing in the above-mentioned prior art.

[0006] The embodiments of this specification adopt the following technical solutions:

[0007] This specification provides a system for processing card binding business, the system comprising: a payment platform server, a cloud real machine, and a bank server;

[0008] The payment platform server is used to send a detection instruction to the cloud real machine for each bank according to the detection frequency corresponding to the bank;

[0009] The cloud real machine is used to simulate a card binding request corresponding to the bank according to the received detection instruction, and send the card binding request to a bank server corresponding to the bank;

[0010] The bank server is used to return a response result to the cloud real machine according to the received card binding request;

[0011] The cloud real machine is further used to report response information to the payment platform server based on the received response result;

[0012] The payment platform server is also used to determine whether there is an abnormality in the bank server of the bank based on the received response information; if there is an abnormality, close the card binding entrance corresponding to the bank; if there is no abnormality, open the card binding entrance corresponding to the bank.

[0013] Optionally, the cloud real machine is also used for:

[0014] At least one of a response status corresponding to the response result, text information in a response page corresponding to the response result, and a session status currently saved by the cloud real machine is obtained as response information.

[0015] Optionally, when the payment platform server determines whether there is an abnormality in the bank server of the bank according to the received response information, it is specifically used to:

[0016] According to the received response information, a failure coefficient corresponding to the bank server of the bank is determined, and according to the failure coefficient, it is judged whether there is an abnormality in the bank server of the bank.

[0017] Optionally, when the payment platform server determines the failure coefficient corresponding to the bank server of the bank and judges whether there is an abnormality in the bank server of the bank according to the failure coefficient, it is specifically used to:

[0018] Based on the failure coefficient corresponding to the bank server of the bank determined each time within a preset detection cycle, the comprehensive failure coefficient corresponding to the bank server of the bank within the detection cycle is determined, and based on the historical comprehensive failure coefficients within the same detection cycle in history and the comprehensive failure coefficient, it is judged whether there is an abnormality in the bank server of the bank within the detection cycle.

[0019] Optionally, the payment platform server is further used to: if it is determined that there is an abnormality in the bank server of the bank, update the detection frequency corresponding to the bank to obtain an updated detection frequency, wherein the updated detection frequency is greater than the detection frequency.

[0020] This specification provides a method for processing a card binding service, including:

[0021] The payment platform server sends a detection instruction to the cloud real machine for each bank according to the detection frequency corresponding to the bank, so that the cloud real machine simulates the card binding request corresponding to the bank according to the received detection instruction, sends the card binding request to the bank server corresponding to the bank, and reports response information to the payment platform server based on the received response result, wherein the response result is generated by the bank server according to the card binding request sent by the cloud real machine;

[0022] The payment platform server receives the response information reported by the cloud real machine, and determines whether there is an abnormality in the bank server of the bank according to the response information;

[0023] If there is an abnormality, the payment platform server closes the card binding entrance corresponding to the bank;

[0024] If there is no abnormality, the payment platform server opens the card binding entrance corresponding to the bank.

[0025] Optionally, the payment platform server determines whether there is an abnormality in the bank server of the bank according to the response information, specifically including:

[0026] The payment platform server determines the failure coefficient corresponding to the bank server of the bank according to the received response information, and judges whether there is an abnormality in the bank server of the bank according to the failure coefficient.

[0027] Optionally, the payment platform server determines whether there is an abnormality in the bank server of the bank according to the failure coefficient, specifically including:

[0028] The payment platform server determines the comprehensive failure coefficient corresponding to the bank server of the bank within the detection period according to the failure coefficient corresponding to the bank server of the bank determined each time within the preset detection period;

[0029] The payment platform server determines whether there is an abnormality in the bank server of the bank within the detection cycle based on the historical comprehensive failure coefficient within the same detection cycle in history and the comprehensive failure coefficient.

[0030] Optionally, the method further comprises:

[0031] If it is determined that the bank server of the bank is abnormal, the payment platform server updates the detection frequency corresponding to the bank to obtain an updated detection frequency, wherein the updated detection frequency is greater than the detection frequency.

[0032] This specification provides a method for processing a card binding service, including:

[0033] The cloud real machine simulates the card binding request corresponding to the bank according to the detection instruction sent by the payment platform server to each bank; wherein the detection instruction is sent by the payment platform server to the cloud real machine according to the detection frequency corresponding to each bank;

[0034] The cloud real machine sends the card binding request to the bank server corresponding to the bank, so that the bank server returns a response result to the cloud real machine according to the received card binding request;

[0035] The cloud real machine receives the response result returned by the bank server, and based on the response result, reports response information to the payment platform server, so that the payment platform server determines whether there is an abnormality in the bank server of the bank according to the received response information. If there is an abnormality, the card binding entrance corresponding to the bank is closed; if there is no abnormality, the card binding entrance corresponding to the bank is opened.

[0036] Optionally, the cloud real machine reports response information to the payment platform server based on the response result, specifically including:

[0037] The cloud real machine obtains at least one of the response status corresponding to the response result, the text information in the response page corresponding to the response result, and the current session state saved by the cloud real machine for sending the card binding request as response information, and reports the response information to the payment platform server.

[0038] This specification provides a device for processing a card binding service, including:

[0039] A response result determination module is used for the payment platform server to send a detection instruction to the cloud real machine for each bank according to the detection frequency corresponding to the bank, so that the cloud real machine simulates the card binding request corresponding to the bank according to the received detection instruction, sends the card binding request to the bank server corresponding to the bank, and reports response information to the payment platform server based on the received response result, wherein the response result is generated by the bank server according to the card binding request sent by the cloud real machine;

[0040] The abnormality judgment module is used for the payment platform server to receive the response information reported by the cloud real machine, and judge whether there is an abnormality in the bank server of the bank based on the response information; if there is an abnormality, the payment platform server closes the card binding entrance corresponding to the bank; if there is no abnormality, the payment platform server opens the card binding entrance corresponding to the bank.

[0041] This specification provides a device for processing a card binding service, including:

[0042] A simulation request module is used for the cloud real machine to simulate the card binding request corresponding to each bank according to the detection instruction sent by the payment platform server to each bank; wherein the detection instruction is sent by the payment platform server to the cloud real machine according to the detection frequency corresponding to each bank;

[0043] A response result determination module is used for the cloud real machine to send the card binding request to the bank server corresponding to the bank, so that the bank server returns a response result to the cloud real machine according to the received card binding request;

[0044] The abnormality judgment module is used for the cloud real machine to receive the response result returned by the bank server, and based on the response result, report the response information to the payment platform server, so that the payment platform server can judge whether there is an abnormality in the bank server of the bank according to the received response information. If there is an abnormality, the card binding entrance corresponding to the bank is closed; if there is no abnormality, the card binding entrance corresponding to the bank is opened.

[0045] This specification provides a computer-readable storage medium, which stores a computer program. When the computer program is executed by a processor, the method for processing the card binding service is implemented.

[0046] The present specification provides an electronic device, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor implements the above-mentioned method for processing a card binding service when executing the program.

[0047] At least one of the above technical solutions adopted in the embodiments of this specification can achieve the following beneficial effects:

[0048] In the embodiment of this specification, for each bank, the payment platform server sends a detection instruction to the cloud real machine according to the detection frequency corresponding to the bank, so that the cloud real machine sends a simulated card binding request to the bank server of the bank. The bank server returns a response result, and the cloud real machine reports the response information to the payment platform server based on the response result. The payment platform server determines whether there is an abnormality in the bank server of the bank based on the response information. If there is an abnormality, the card binding entrance corresponding to the bank is closed. If there is no abnormality, the card binding entrance corresponding to the bank is opened. In this method, it is possible to timely determine whether there is an abnormality in the bank server from the response result obtained by the cloud real machine continuously sending the card binding request to the bank server, and close or open the card binding entrance of the corresponding bank based on the judgment result. In this way, the bank card binding entrances displayed to the user can all perform the card binding business, thereby improving the user experience. BRIEF DESCRIPTION OF THE DRAWINGS

[0049] The drawings described herein are used to provide a further understanding of this specification and constitute a part of this specification. The illustrative embodiments and descriptions of this specification are used to explain this specification and do not constitute an improper limitation on this specification. In the drawings:

[0050] Figure 1 An interaction diagram of a system for processing card binding services provided in an embodiment of this specification;

[0051] Figure 2 A flowchart of a method for processing a card binding service provided in an embodiment of this specification;

[0052] Figure 3A structural diagram of another method for processing a card binding service is provided for the embodiment of this specification;

[0053] Figure 4 A schematic diagram of the structure of a device for processing a card binding service provided in an embodiment of this specification;

[0054] Figure 5 A schematic diagram of another device structure for processing card binding services provided in an embodiment of this specification;

[0055] Figure 6 This is a schematic diagram of the structure of an electronic device provided in an embodiment of this specification. DETAILED DESCRIPTION

[0056] In order to make the purpose, technical solutions and advantages of this specification more clear, the technical solutions of this specification will be clearly and completely described below in combination with the specific embodiments of this specification and the corresponding drawings. Obviously, the described embodiments are only part of the embodiments of this specification, not all of them. Based on the embodiments in this specification, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of this specification.

[0057] The technical solutions provided by the embodiments of this specification are described in detail below in conjunction with the accompanying drawings.

[0058] Figure 1 This is an interactive diagram of a system for processing card binding services provided in an embodiment of this specification. The system may include: a payment platform server, a cloud real machine, and a bank server. Among them, the payment platform server may be a payment platform backend server, and the cloud real machine may be built on the cloud server of the payment platform. In addition, the cloud real machine is a real mobile phone that can be remotely controlled.

[0059] In the embodiment of this specification, the payment platform server can send a detection instruction to the cloud real machine, and the detection instruction is used to trigger the cloud real machine to send a card binding request to the bank server. After the bank server returns a response result to the cloud real machine, the cloud real machine reports the response information to the payment platform server based on the response result. The payment platform server determines whether there is an abnormality in the bank server based on the response information. If there is an abnormality, the card binding entrance corresponding to the bank server with the abnormality is closed. If there is no abnormality (that is, normal), the card binding entrance corresponding to the normal bank server is opened.

[0060] Specifically, the payment platform server can determine the detection period corresponding to each bank as the initial detection period, and determine the detection frequency corresponding to each bank as the initial detection frequency, based on the number of requests for card binding services corresponding to each bank in history. Generally, banks with a relatively large number of requests for card binding services have a shorter detection period and a faster detection frequency than banks with a relatively small number of card services. In addition, the payment platform server can also determine the peak time period for card binding corresponding to each bank based on the time when the card binding service request was sent by each bank user in history.

[0061] When the payment platform server starts the detection process, the payment platform server can obtain the initial detection cycle and initial detection frequency corresponding to each bank for each bank. Then, according to the current time and the corresponding card binding peak period of the bank, it is determined whether the current time is in the corresponding card binding peak period of the bank. If so, the payment platform server adjusts the initial detection cycle and / or initial detection frequency corresponding to the bank, and obtains the adjusted detection cycle and / or adjusted detection frequency corresponding to the bank when it is in the corresponding card binding peak period of the bank. That is, shorten the initial detection cycle corresponding to the bank and / or increase the initial detection frequency corresponding to the bank, and obtain the adjusted detection cycle and / or adjusted detection frequency corresponding to the bank when it is in the corresponding card binding peak period of the bank. Then, the payment platform server sends a detection instruction to the cloud real machine according to the adjusted detection cycle and / or adjusted detection frequency corresponding to the bank. Among them, the detection instruction is used to trigger the cloud real machine to send a card binding request to the bank server of the bank, and the detection instruction carries the card binding entry identifier of the bank.

[0062] The reason for shortening the initial detection cycle or increasing the initial detection frequency during the bank's card binding peak period is to promptly detect whether there are any abnormalities in the bank's server, so that the bank's card binding entrance can be closed or restored in time.

[0063] If not, the payment platform server sends a detection instruction to the cloud real machine according to the initial detection period and / or initial detection frequency corresponding to the bank.

[0064] After receiving the detection instruction sent by the payment platform server, the cloud machine simulates the bank's corresponding card binding request according to the bank's card binding entry identifier. Then, the cloud machine opens the payment platform's corresponding card binding page through the browser, and sends a card binding request to the bank server of the bank according to the bank's corresponding card binding entry and the bank's corresponding card binding request on the card binding page.

[0065] Since the cloud real machine sends the card binding request to the bank's bank server based on the cloud server, and the ordinary user sends the card binding request to the bank's bank server based on the payment platform server, the cloud real machine sending the card binding request will not occupy the service resources of the ordinary user sending the card binding request.

[0066] The bank server of the bank receives the card binding request sent by the cloud real machine, and returns a response result to the cloud real machine according to the device identification of the cloud real machine carried in the card binding request and the detection account number for logging into the payment platform. The response result may include: response status, response page, etc.

[0067] The cloud real machine receives the response result returned by the bank server of the bank, then obtains the response information based on the response result, and reports the response information to the payment platform server.

[0068] When the cloud machine obtains the response information, it can obtain the response status in the response result, where the response status may include: http request failure (for example, return 404 status code), http request success, etc. And the text information in the response page in the response result can be obtained through image recognition technology (for example, OCR technology). In addition, the cloud machine can also obtain the current session status saved by the cloud machine for the card binding request sent. The session status can represent the data interaction status between the cloud machine and the bank server, and the session status may include: session failure, session success, etc.

[0069] Since the method and source of the cloud real machine to obtain the response information are inconsistent, the cloud real machine can obtain the response information through at least one of the above three methods. That is, the response information can be at least one of the response status, text information, and current session status.

[0070] The payment platform server receives the response information reported by the cloud real machine, and determines whether there is any abnormality in the bank server of the bank based on the response information. If there is an abnormality, the card binding entrance corresponding to the bank is closed; if there is no abnormality, the card binding entrance corresponding to the bank is opened.

[0071] Specifically, the payment platform server determines the failure coefficient corresponding to the bank server of the bank under this detection according to at least one of the response information reported by each detection within the detection cycle of the bank.

[0072] Further, for the response status, if the response status is http request failure, determine the failure coefficient corresponding to the bank server of the bank under this detection. When the response status is http request failure, the failure coefficient can be 1; when the response status is http request success, the failure coefficient can be 0.

[0073] For the current session state, if the current session state is a session failure, determine the failure coefficient corresponding to the bank server of the bank under this detection. When the current session state is a session failure, the failure coefficient may be 1; when the current session state is a session success, the failure coefficient may be 0.

[0074] For text information, the payment platform server can match the pre-saved matching text with the text information reported in this detection to determine whether there are keywords matching the matching text in the text information. Among them, the matching text may include keywords such as error and failure. If so, determine the failure coefficient corresponding to the bank server of the bank under this detection. Since the matching algorithm between the text information and the matching text may have mismatches, resulting in low matching accuracy, the failure coefficient is not a fixed value, but a numerical range, such as: 0~1. When the number of keywords matching the matching text in the text information is greater than the preset threshold, it is determined that the failure coefficient corresponding to the bank server of the bank under this detection is greater than 0.5. When the number of keywords matching the matching text in the text information is not greater than the preset threshold, it is determined that the failure coefficient corresponding to the bank server of the bank under this detection is not greater than 0.5.

[0075] In order to improve the matching accuracy, when there are keywords matching the matching text in the text information, the semantic recognition technology can be used to determine whether the text information indicates that the response is abnormal. If so, the failure coefficient corresponding to the bank server of the bank under this detection is determined to be 1. If not, the failure coefficient corresponding to the bank server of the bank under this detection is determined to be 0.

[0076] After determining the failure coefficient corresponding to the bank server of the bank under this detection, the payment platform server determines the comprehensive failure coefficient of the bank within the detection cycle according to the failure coefficient determined each time within the detection cycle.

[0077] Specifically, based on the failure coefficient corresponding to the bank server of the bank determined each time within the preset detection cycle, the comprehensive failure coefficient of the bank server corresponding to the bank within the detection cycle is determined, and based on the historical comprehensive failure coefficient and the comprehensive failure coefficient within the same detection cycle in history, it is judged whether there is any abnormality in the bank server of the bank within the detection cycle.

[0078] In order to avoid periodic changes in faults, the historical comprehensive fault coefficient in the same detection cycle in history can be compared with the comprehensive fault coefficient in the current detection cycle. If the comprehensive fault coefficient in the current detection cycle is greater than the historical comprehensive fault coefficient, it is determined that there is an abnormality in the bank server of the bank in the current detection cycle. If the comprehensive fault coefficient in the current detection cycle is not greater than the historical comprehensive fault coefficient, it is determined that there is no abnormality in the bank server of the bank in the current detection cycle.

[0079] Furthermore, when determining the comprehensive failure coefficient of the bank server corresponding to the bank within the detection period, the failure coefficients corresponding to the bank server of the bank determined by each detection within the detection period can be summed to obtain the comprehensive failure coefficient corresponding to the bank server of the bank within the detection period. Alternatively, the failure coefficients corresponding to the bank server of the bank determined by each detection within the detection period can be weighted averaged to obtain the comprehensive failure coefficient corresponding to the bank server of the bank within the detection period.

[0080] In addition, if the payment platform server determines that the bank server of the bank is abnormal, it updates the detection frequency and / or detection period corresponding to the detection instruction sent to obtain an updated detection frequency and / or an updated detection period, wherein the updated detection frequency is greater than the detection frequency and the updated detection period is less than the detection period.

[0081] The reason for updating the detection frequency and / or detection period corresponding to sending the detection instruction is to detect in time that the bank server has returned to normal, so as to restore the abnormal card binding entrance of the bank server in time, thereby improving the user experience.

[0082] In addition, when the payment platform server closes or opens the card binding entrance for each bank, the following situations may occur:

[0083] For each bank, if the payment platform server determines that there is an abnormality in the bank's bank server, the state of the card binding entrance corresponding to the bank is set to closed. That is, if the state of the card binding entrance of the bank is originally open, the card binding entrance corresponding to the bank is closed; if the state of the card binding entrance of the bank is originally closed, the state of the card binding entrance corresponding to the bank is maintained.

[0084] If the payment platform server determines that there is no abnormality in the bank server of the bank, the state of the card binding entrance corresponding to the bank is set to open. That is, if the state of the card binding entrance of the bank is originally open, the state of the card binding entrance corresponding to the bank is maintained; if the state of the card binding entrance of the bank is originally closed, the card binding entrance corresponding to the bank is opened, that is, the card binding entrance corresponding to the bank is restored.

[0085] It should be noted that after the payment platform server closes the card binding entrance corresponding to the bank with abnormalities, the card binding page displayed by the payment platform server to ordinary users are all card binding entrances that can execute card binding services, that is, they can be bound as soon as they are visible.

[0086] In addition, in order to restore the card binding entry corresponding to the bank with abnormalities, the cloud machine needs to send a card binding request to the bank server corresponding to the bank with abnormalities to obtain a response result. Therefore, the payment platform server adds the detection account of the cloud machine sending the card binding request to the bank server to the whitelist. The detection account in the whitelist can send card binding requests to the servers of all normal and all abnormal banks.

[0087] Based on the above description of the interaction between the payment platform server, the cloud real machine and the bank server in the card binding business system, a flow chart of a method for processing a card binding business provided in an embodiment of this specification is as follows: Figure 2 As shown. Among them, Figure 2 The method for processing the card binding service shown is applied to the payment platform server. The specific method for processing the card binding service includes:

[0088] S200: The payment platform server sends a detection instruction to the cloud real machine for each bank according to the detection frequency corresponding to the bank, so that the cloud real machine simulates the card binding request corresponding to the bank according to the received detection instruction, sends the card binding request to the bank server corresponding to the bank, and reports response information to the payment platform server based on the received response result, wherein the response result is generated by the bank server according to the card binding request sent by the cloud real machine.

[0089] S202: The payment platform server receives the response information reported by the cloud real machine, and determines whether there is an abnormality in the bank server of the bank based on the response information; if there is an abnormality, close the card binding entrance corresponding to the bank; if there is no abnormality, open the card binding entrance corresponding to the bank.

[0090] Based on the above description of the interaction between the payment platform server, the cloud real machine and the bank server in the card binding service system, another method flow chart for processing the card binding service provided in the embodiment of this specification is as follows: Figure 3 As shown. Among them, Figure 3 The method for processing the card binding service shown is applied to the cloud real machine. The specific method for processing the card binding service includes:

[0091] S300: The cloud real machine simulates a card binding request corresponding to the bank according to the detection instruction sent by the payment platform server to each bank; wherein the detection instruction is sent to the cloud real machine by the payment platform server according to the detection frequency corresponding to each bank.

[0092] S302: The cloud real machine sends the card binding request to the bank server corresponding to the bank, so that the bank server returns a response result to the cloud real machine according to the received card binding request.

[0093] S304: The cloud real machine receives the response result returned by the bank server, and based on the response result, reports response information to the payment platform server, so that the payment platform server determines whether there is an abnormality in the bank server of the bank according to the received response information. If there is an abnormality, the card binding entrance corresponding to the bank is closed; if there is no abnormality, the card binding entrance corresponding to the bank is opened.

[0094] Through the above Figure 1 The system shown, Figure 2 and Figure 3 As can be seen from the method shown, this manual sends a detection instruction to the cloud real machine for each bank on the payment platform server according to the detection frequency corresponding to the bank, so that the cloud real machine sends a simulated card binding request to the bank server of the bank. The bank server returns a response result, and the cloud real machine reports the response information to the payment platform server based on the response result. The payment platform server determines whether there is an abnormality in the bank server of the bank based on the response information. If there is an abnormality, close the card binding entrance corresponding to the bank; if there is no abnormality, open the card binding entrance corresponding to the bank. In this method, it is possible to timely determine whether there is an abnormality in the bank server from the response result obtained by the cloud real machine continuously sending the card binding request to the bank server, and close or open the card binding entrance of the corresponding bank based on the judgment result, so that the bank card binding entrance displayed to the user can perform the card binding business, thereby improving the user experience.

[0095] The above is a method for processing a card binding service provided in an embodiment of this specification. Based on the same idea, this specification also provides a corresponding device, a storage medium, and an electronic device.

[0096] Figure 4 A schematic diagram of a structure of a device for processing a card binding service provided in an embodiment of this specification, the device comprising:

[0097] Determine response result module 401, for the payment platform server to send a detection instruction to the cloud real machine for each bank according to the detection frequency corresponding to the bank, so that the cloud real machine simulates the card binding request corresponding to the bank according to the received detection instruction, sends the card binding request to the bank server corresponding to the bank, and reports response information to the payment platform server based on the received response result, wherein the response result is generated by the bank server according to the card binding request sent by the cloud real machine;

[0098] The abnormality judgment module 402 is used for the payment platform server to receive the response information reported by the cloud real machine, and judge whether there is an abnormality in the bank server of the bank based on the response information; if there is an abnormality, the payment platform server closes the card binding entrance corresponding to the bank; if there is no abnormality, the payment platform server opens the card binding entrance corresponding to the bank.

[0099] Optionally, the abnormality judgment module 402 is specifically used for the payment platform server to determine the failure coefficient corresponding to the bank server of the bank according to the received response information, and to judge whether there is an abnormality in the bank server of the bank according to the failure coefficient.

[0100] Optionally, the abnormality judgment module 402 is specifically used for the payment platform server to determine the comprehensive failure coefficient corresponding to the bank server of the bank within the detection period according to the failure coefficient corresponding to the bank server of the bank determined each time within the preset detection period; and to judge whether there is an abnormality in the bank server of the bank within the detection period according to the historical comprehensive failure coefficients within the same detection period in history and the comprehensive failure coefficient.

[0101] The device further includes: an updating module 403;

[0102] The updating module 403 is used for, if it is determined that the bank server of the bank is abnormal, the payment platform server updates the detection frequency corresponding to the bank to obtain an updated detection frequency, wherein the updated detection frequency is greater than the detection frequency.

[0103] Figure 5 A schematic diagram of the structure of another device for processing a card binding service provided in an embodiment of this specification, the device comprising:

[0104] The simulation request module 501 is used for the cloud real machine to simulate the card binding request corresponding to each bank according to the detection instruction sent by the payment platform server to each bank; wherein the detection instruction is sent by the payment platform server to the cloud real machine according to the detection frequency corresponding to each bank;

[0105] Determine response result module 502, used for the cloud real machine to send the card binding request to the bank server corresponding to the bank, so that the bank server returns a response result to the cloud real machine according to the received card binding request;

[0106] The abnormality judgment module 503 is used for the cloud real machine to receive the response result returned by the bank server, and based on the response result, report the response information to the payment platform server, so that the payment platform server can judge whether there is an abnormality in the bank server of the bank according to the received response information. If there is an abnormality, the card binding entrance corresponding to the bank is closed; if there is no abnormality, the card binding entrance corresponding to the bank is opened.

[0107] Optionally, the exception judgment module 503 is specifically used for the cloud real machine to obtain at least one of the response status corresponding to the response result, the text information in the response page corresponding to the response result, and the current session state saved by the cloud real machine for sending the card binding request as response information, and report the response information to the payment platform server.

[0108] This specification also provides a computer-readable storage medium, wherein the storage medium stores a computer program, and when the computer program is executed by a processor, it can be used to perform the above Figure 2 and Figure 3 Provides methods for processing card binding services.

[0109] based on Figure 2 and Figure 3 The method for processing the card binding service shown in the specification also provides Figure 6 The structural diagram of the electronic device shown in FIG. Figure 6 At the hardware level, the electronic device includes a processor, an internal bus, a network interface, a memory, and a non-volatile memory, and may also include other hardware required for the business. The processor reads the corresponding computer program from the non-volatile memory into the memory and then runs it to achieve the above Figure 2 and Figure 3 The method for processing the card binding service.

[0110] Of course, in addition to software implementation, this specification does not exclude other implementation methods, such as logic devices or a combination of software and hardware, etc., that is to say, the executor of the following processing flow is not limited to each logic unit, but can also be hardware or logic devices.

[0111] In the 1990s, improvements to a technology could be clearly distinguished as hardware improvements (for example, improvements to the circuit structure of diodes, transistors, switches, etc.) or software improvements (improvements to the method flow). However, with the development of technology, many improvements to the method flow today can be regarded as direct improvements to the hardware circuit structure. Designers almost always obtain the corresponding hardware circuit structure by programming the improved method flow into the hardware circuit. Therefore, it cannot be said that an improvement in a method flow cannot be implemented using a hardware entity module. For example, a programmable logic device (PLD) (such as a field programmable gate array (FPGA)) is such an integrated circuit whose logical function is determined by the user's programming of the device. Designers can "integrate" a digital system on a PLD by programming it themselves, without having to ask a chip manufacturer to design and produce a dedicated integrated circuit chip. Moreover, nowadays, instead of manually making integrated circuit chips, this kind of programming is mostly implemented by "logic compiler" software, which is similar to the software compiler used when developing and writing programs, and the original code before compilation must also be written in a specific programming language, which is called hardware description language (HDL). There is not only one HDL, but many kinds, such as ABEL (Advanced Boolean Expression Language), AHDL (Altera Hardware Description Language), Confluence, CUPL (Cornell University Programming Language), HDCal, JHDL (Java Hardware Description Language), Lava, Lola, MyHDL, PALASM, RHDL (Ruby Hardware Description Language), etc. The most commonly used ones are VHDL (Very-High-Speed ​​Integrated Circuit Hardware Description Language) and Verilog. Those skilled in the art should also know that it is only necessary to program the method flow slightly in the above-mentioned hardware description languages ​​and program it into the integrated circuit, and then it is easy to obtain the hardware circuit that implements the logic method flow.

[0112] The controller can be implemented in any appropriate manner, for example, the controller can take the form of a microprocessor or processor and a computer-readable medium storing a computer-readable program code (such as software or firmware) that can be executed by the (micro)processor, a logic gate, a switch, an application-specific integrated circuit (ASIC), a programmable logic controller, and an embedded microcontroller. Examples of controllers include, but are not limited to, the following microcontrollers: ARC 625D, Atmel AT91SAM, Microchip PIC18F26K20, and Silicone Labs C8051F320. The memory controller can also be implemented as part of the control logic of the memory. Those skilled in the art also know that in addition to implementing the controller in a purely computer-readable program code manner, the controller can be implemented in the form of a logic gate, a switch, an application-specific integrated circuit, a programmable logic controller, and an embedded microcontroller by logically programming the method steps. Therefore, this controller can be considered as a hardware component, and the devices included therein for implementing various functions can also be regarded as structures within the hardware component. Or even, the devices for implementing various functions can be regarded as both software modules for implementing the method and structures within the hardware component.

[0113] The systems, devices, modules or units described in the above embodiments may be implemented by computer chips or entities, or by products with certain functions. A typical implementation device is a computer. Specifically, the computer may be, for example, a personal computer, a laptop computer, a cellular phone, a camera phone, a smart phone, a personal digital assistant, a media player, a navigation device, an email device, a game console, a tablet computer, a wearable device, or a combination of any of these devices.

[0114] For the convenience of description, the above device is described in various units according to their functions. Of course, when implementing this specification, the functions of each unit can be implemented in the same or multiple software and / or hardware.

[0115] Those skilled in the art will appreciate that the embodiments of this specification may be provided as methods, systems, or computer program products. Therefore, this specification may take the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware. Moreover, this specification may take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) that contain computer-usable program code.

[0116] This specification is described with reference to the flowcharts and / or block diagrams of the methods, devices (systems), and computer program products according to the embodiments of this specification. It should be understood that each process and / or box in the flowchart and / or block diagram, as well as the combination of the processes and / or boxes in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 A process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0117] These computer program instructions may also be stored in a computer-readable memory capable of directing a computer or other programmable data processing device to operate in a specific manner, so that the instructions stored in the computer-readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 A process or multiple processes and / or boxes Figure 1 A function specified in one or more boxes.

[0118] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operating steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing instructions for implementing the process. Figure 1 A process or multiple processes and / or boxes Figure 1 The steps for the functions specified in one or more boxes.

[0119] In a typical configuration, a computing device includes one or more processors (CPU), input / output interfaces, network interfaces, and memory.

[0120] The memory may include non-permanent storage in a computer-readable medium, random access memory (RAM) and / or non-volatile memory in the form of read-only memory (ROM) or flash RAM. The memory is an example of a computer-readable medium.

[0121] Computer readable media include permanent and non-permanent, removable and non-removable media that can be implemented by any method or technology to store information. Information can be computer readable instructions, data structures, program modules or other data. Examples of computer storage media include, but are not limited to, phase change memory (PRAM), static random access memory (SRAM), dynamic random access memory (DRAM), other types of random access memory (RAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), flash memory or other memory technology, compact disk read-only memory (CD-ROM), digital versatile disk (DVD) or other optical storage, magnetic cassettes, magnetic tape magnetic disk storage or other magnetic storage devices or any other non-transmission media that can be used to store information that can be accessed by a computing device. As defined herein, computer readable media does not include temporary computer readable media (transitory media), such as modulated data signals and carrier waves.

[0122] It should also be noted that the terms "include", "comprises" or any other variations thereof are intended to cover non-exclusive inclusion, so that a process, method, commodity or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, commodity or device. In the absence of more restrictions, the elements defined by the sentence "comprises a ..." do not exclude the existence of other identical elements in the process, method, commodity or device including the elements.

[0123] Those skilled in the art will appreciate that the embodiments of this specification may be provided as methods, systems or computer program products. Therefore, this specification may take the form of a complete hardware embodiment, a complete software embodiment or an embodiment combining software and hardware. Moreover, this specification may take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0124] This specification may be described in the general context of computer-executable instructions executed by a computer, such as program modules. Generally, program modules include routines, programs, objects, components, data structures, etc. that perform specific tasks or implement specific abstract data types. This specification may also be practiced in distributed computing environments where tasks are performed by remote processing devices connected through a communication network. In a distributed computing environment, program modules may be located in local and remote computer storage media, including storage devices.

[0125] Each embodiment in this specification is described in a progressive manner, and the same or similar parts between the embodiments can be referred to each other, and each embodiment focuses on the differences from other embodiments. In particular, for the system embodiment, since it is basically similar to the method embodiment, the description is relatively simple, and the relevant parts can be referred to the partial description of the method embodiment.

[0126] The above description is only an embodiment of the present specification and is not intended to limit the present specification. For those skilled in the art, the present specification may have various changes and variations. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present specification shall be included in the scope of the claims of the present specification.

Claims

1. A system for processing card binding services, characterized in that: The system includes: a payment platform server, a cloud real machine, and a bank server; The payment platform server is used to send a detection instruction to the cloud real machine for each bank according to the detection frequency corresponding to the bank; The cloud real machine is used to simulate a card binding request corresponding to the bank according to the received detection instruction, and send the card binding request to a bank server corresponding to the bank; The bank server is used to return a response result to the cloud real machine according to the received card binding request; The cloud real machine is further used to report response information to the payment platform server based on the received response result; The payment platform server is also used to determine whether there is an abnormality in the bank server of the bank based on the received response information; if there is an abnormality, close the card binding entrance corresponding to the bank; if there is no abnormality, open the card binding entrance corresponding to the bank.

2. The system according to claim 1, characterized in that The cloud real machine is also used for: Obtain at least one of a response status corresponding to the response result, text information in a response page corresponding to the response result, and a current session state saved by the cloud real machine for sending the card binding request as response information.

3. The system according to claim 1, characterized in that When the payment platform server determines whether there is an abnormality in the bank server of the bank according to the received response information, it is specifically used to: According to the received response information, a failure coefficient corresponding to the bank server of the bank is determined, and according to the failure coefficient, it is judged whether there is an abnormality in the bank server of the bank.

4. The system according to claim 3, characterized in that When the payment platform server determines the failure coefficient corresponding to the bank server of the bank and judges whether there is an abnormality in the bank server of the bank according to the failure coefficient, it is specifically used to: Based on the failure coefficient corresponding to the bank server of the bank determined each time within the preset detection cycle, the comprehensive failure coefficient corresponding to the bank server of the bank within the detection cycle is determined, and the historical comprehensive failure coefficients within the historical detection cycle are compared with the comprehensive failure coefficient within the current detection cycle to determine whether there is any abnormality in the bank server of the bank in the current detection cycle.

5. The system according to any one of claims 1 to 4, characterized in that: The payment platform server is also used for: If it is determined that an abnormality exists in the bank server of the bank, the detection frequency corresponding to the bank is updated to obtain an updated detection frequency, wherein the updated detection frequency is greater than the detection frequency before the update.

6. A method for processing a card binding service, characterized in that: include: The payment platform server sends a detection instruction to the cloud real machine for each bank according to the detection frequency corresponding to the bank, so that the cloud real machine simulates the card binding request corresponding to the bank according to the received detection instruction, sends the card binding request to the bank server corresponding to the bank, and reports response information to the payment platform server based on the received response result, wherein the response result is generated by the bank server according to the card binding request sent by the cloud real machine; The payment platform server receives the response information reported by the cloud real machine, and determines whether there is an abnormality in the bank server of the bank according to the response information; If there is an abnormality, the payment platform server closes the card binding entrance corresponding to the bank; If there is no abnormality, the payment platform server opens the card binding entrance corresponding to the bank.

7. The method according to claim 6, characterized in that The payment platform server determines whether there is an abnormality in the bank server of the bank according to the response information, specifically including: The payment platform server determines the failure coefficient corresponding to the bank server of the bank according to the received response information, and judges whether there is an abnormality in the bank server of the bank according to the failure coefficient.

8. The method according to claim 7, characterized in that The payment platform server determines whether there is an abnormality in the bank server of the bank according to the failure coefficient, specifically including: The payment platform server determines the comprehensive failure coefficient corresponding to the bank server of the bank within the detection period according to the failure coefficient corresponding to the bank server of the bank determined each time within the preset detection period; The payment platform server compares the historical comprehensive failure coefficients in the historical detection cycle with the comprehensive failure coefficients in the current detection cycle to determine whether there is an abnormality in the bank server of the bank in the current detection cycle.

9. The method according to claim 6, characterized in that The method further comprises: If it is determined that the bank server of the bank is abnormal, the payment platform server updates the detection frequency corresponding to the bank to obtain an updated detection frequency, wherein the updated detection frequency is greater than the detection frequency before the update.

10. A method for processing a card binding service, characterized in that: include: The cloud real machine simulates the card binding request corresponding to the bank according to the detection instruction sent by the payment platform server to each bank; wherein the detection instruction is sent by the payment platform server to the cloud real machine according to the detection frequency corresponding to each bank; The cloud real machine sends the card binding request to the bank server corresponding to the bank, so that the bank server returns a response result to the cloud real machine according to the received card binding request; The cloud real machine receives the response result returned by the bank server, and based on the response result, reports response information to the payment platform server, so that the payment platform server determines whether there is an abnormality in the bank server of the bank according to the received response information. If there is an abnormality, the card binding entrance corresponding to the bank is closed; if there is no abnormality, the card binding entrance corresponding to the bank is opened.

11. The method according to claim 10, characterized in that The cloud real machine reports response information to the payment platform server based on the response result, specifically including: The cloud real machine obtains at least one of the response status corresponding to the response result, the text information in the response page corresponding to the response result, and the current session state saved by the cloud real machine for sending the card binding request as response information, and reports the response information to the payment platform server.

12. A device for processing card binding service, characterized in that: include: A response result determination module is used for the payment platform server to send a detection instruction to the cloud real machine for each bank according to the detection frequency corresponding to the bank, so that the cloud real machine simulates the card binding request corresponding to the bank according to the received detection instruction, sends the card binding request to the bank server corresponding to the bank, and reports response information to the payment platform server based on the received response result, wherein the response result is generated by the bank server according to the card binding request sent by the cloud real machine; The abnormality judgment module is used for the payment platform server to receive the response information reported by the cloud real machine, and judge whether there is an abnormality in the bank server of the bank based on the response information; if there is an abnormality, the payment platform server closes the card binding entrance corresponding to the bank; if there is no abnormality, the payment platform server opens the card binding entrance corresponding to the bank.

13. A device for processing card binding service, characterized in that: include: A simulation request module is used for the cloud real machine to simulate the card binding request corresponding to each bank according to the detection instruction sent by the payment platform server to each bank; wherein the detection instruction is sent by the payment platform server to the cloud real machine according to the detection frequency corresponding to each bank; A response result determination module is used for the cloud real machine to send the card binding request to the bank server corresponding to the bank, so that the bank server returns a response result to the cloud real machine according to the received card binding request; The abnormality judgment module is used for the cloud real machine to receive the response result returned by the bank server, and based on the response result, report the response information to the payment platform server, so that the payment platform server can judge whether there is an abnormality in the bank server of the bank according to the received response information. If there is an abnormality, the card binding entrance corresponding to the bank is closed; if there is no abnormality, the card binding entrance corresponding to the bank is opened.

14. A computer-readable storage medium, characterized in that: The storage medium stores a computer program, and when the computer program is executed by a processor, the method described in any one of claims 6 to 11 is implemented.

15. An electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that: When the processor executes the program, the method described in any one of claims 6 to 11 is implemented.

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