CN113935847A - Online process risk processing method, device, server and medium - Google Patents
Online process risk processing method, device, server and medium Download PDFInfo
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Abstract
The application is applicable to the technical field of information security, and particularly relates to a risk processing method, device, server and medium for an online process. According to the method, when a target process node is triggered, N associated risk factors associated with the target process node are determined from a risk factor library, wherein the risk factors are Java method classes for realizing corresponding risk detection, so that each associated risk factor is used for carrying out risk detection on the target process node to obtain a corresponding risk detection result, a corresponding risk processing event is generated according to each risk detection result, and the corresponding risk detection result is processed when the risk processing event is triggered.
Description
Technical Field
The present application belongs to the technical field of information security, and in particular, to a risk processing method, apparatus, server, and medium for an online process.
Background
The investment process requires that the risk be reduced as much as possible to produce greater revenue. At present, an investor generally uses an online investment system to perform investment operation, in order to realize risk detection on the online investment system, the risk detection needs to be fixed on a certain flow node or a certain flow nodes in an investment flow in a hard coding mode, and a corresponding detection result is output when user operation reaches the corresponding flow node.
Disclosure of Invention
In view of this, embodiments of the present application provide a method, an apparatus, a server, and a medium for risk processing of an online process, so as to solve a problem of how to simply and effectively implement risk processing.
In a first aspect, an embodiment of the present application provides a risk processing method for an online process, where the risk processing method includes:
when a target process node is triggered, determining N associated risk factors associated with the target process node from a risk factor library, wherein the risk factor library stores the association relationship between the risk factors and the process node, the risk factors are Java method classes for realizing corresponding risk detection, and N is an integer greater than zero;
performing risk detection on the target process node by using each associated risk factor to obtain a corresponding risk detection result;
generating a corresponding risk processing event according to each risk detection result;
and processing the corresponding risk detection result when each risk processing event is triggered.
In a second aspect, an embodiment of the present application provides a risk processing apparatus for an online process, where the risk processing apparatus includes:
a risk factor determination module, configured to determine, when a target process node is triggered, N associated risk factors associated with the target process node from a risk factor library, where the risk factor library stores an association relationship between risk factors and process nodes, the risk factors are Java method classes for implementing corresponding risk detection, and N is an integer greater than zero;
the risk detection module is used for carrying out risk detection on the target process node by using each associated risk factor to obtain a corresponding risk detection result;
the processing event generating module is used for generating corresponding risk processing events according to each risk detection result;
and the risk processing module is used for processing the corresponding risk detection result when each risk processing event is triggered.
In a third aspect, an embodiment of the present application provides a server, where the server includes a processor, a memory, and a computer program stored in the memory and executable on the processor, and the processor, when executing the computer program, implements the risk processing method according to the first aspect.
In a fourth aspect, an embodiment of the present application provides a computer-readable storage medium, where a computer program is stored, and the computer program, when executed by a processor, implements the risk processing method according to the first aspect.
In a fifth aspect, an embodiment of the present application provides a computer program product, which, when running on a server, causes the server to execute the risk processing method according to the first aspect.
Compared with the prior art, the embodiment of the application has the advantages that: according to the method and the device, when the target process node is triggered, N associated risk factors associated with the target process node are determined from the risk factor library, and the risk factors are Java method classes for realizing corresponding risk detection.
Drawings
In order to more clearly illustrate the technical solutions in the embodiments of the present application, the drawings needed to be used in the embodiments or the prior art descriptions will be briefly described below, and it is obvious that the drawings in the following description are only some embodiments of the present application, and it is obvious for those skilled in the art to obtain other drawings based on these drawings without inventive exercise.
Fig. 1 is a schematic flow chart of a risk processing method of an online process according to an embodiment of the present application;
fig. 2 is a schematic flow chart of a risk processing method of an online process according to a second embodiment of the present application;
fig. 3 is a schematic structural diagram of a risk processing apparatus of an online process according to a third embodiment of the present application;
fig. 4 is a schematic structural diagram of a server according to a fourth embodiment of the present application.
Detailed Description
In the following description, for purposes of explanation and not limitation, specific details are set forth, such as particular system structures, techniques, etc. in order to provide a thorough understanding of the embodiments of the present application. It will be apparent, however, to one skilled in the art that the present application may be practiced in other embodiments that depart from these specific details. In other instances, detailed descriptions of well-known systems, devices, circuits, and methods are omitted so as not to obscure the description of the present application with unnecessary detail.
It will be understood that the terms "comprises" and/or "comprising," when used in this specification and the appended claims, specify the presence of stated features, integers, steps, operations, elements, and/or components, but do not preclude the presence or addition of one or more other features, integers, steps, operations, elements, components, and/or groups thereof.
It should also be understood that the term "and/or" as used in this specification and the appended claims refers to and includes any and all possible combinations of one or more of the associated listed items.
As used in this specification and the appended claims, the term "if" may be interpreted contextually as "when", "upon" or "in response to" determining "or" in response to detecting ". Similarly, the phrase "if it is determined" or "if a [ described condition or event ] is detected" may be interpreted contextually to mean "upon determining" or "in response to determining" or "upon detecting [ described condition or event ]" or "in response to detecting [ described condition or event ]".
Furthermore, in the description of the present application and the appended claims, the terms "first," "second," "third," and the like are used for distinguishing between descriptions and not necessarily for describing or implying relative importance.
Reference throughout this specification to "one embodiment" or "some embodiments," or the like, means that a particular feature, structure, or characteristic described in connection with the embodiment is included in one or more embodiments of the present application. Thus, appearances of the phrases "in one embodiment," "in some embodiments," "in other embodiments," or the like, in various places throughout this specification are not necessarily all referring to the same embodiment, but rather "one or more but not all embodiments" unless specifically stated otherwise. The terms "comprising," "including," "having," and variations thereof mean "including, but not limited to," unless expressly specified otherwise.
The server in the embodiment of the present application may be a palm top computer, a desktop computer, a notebook computer, an ultra-mobile personal computer (UMPC), a netbook, a cloud server, a Personal Digital Assistant (PDA), and the like, and the embodiment of the present application does not limit the specific type of the server.
The embodiment of the application can acquire and process related data based on an artificial intelligence technology. Among them, Artificial Intelligence (AI) is a theory, method, technique and application system that simulates, extends and expands human Intelligence using a digital computer or a machine controlled by a digital computer, senses the environment, acquires knowledge and uses the knowledge to obtain the best result.
The artificial intelligence infrastructure generally includes technologies such as sensors, dedicated artificial intelligence chips, cloud computing, distributed storage, big data processing technologies, operation/interaction systems, mechatronics, and the like. The artificial intelligence software technology mainly comprises a computer vision technology, a robot technology, a biological recognition technology, a voice processing technology, a natural language processing technology, machine learning/deep learning and the like.
It should be understood that, the sequence numbers of the steps in the following embodiments do not mean the execution sequence, and the execution sequence of each process should be determined by the function and the inherent logic of the process, and should not constitute any limitation to the implementation process of the embodiments of the present application.
In order to explain the technical means of the present application, the following description will be given by way of specific examples.
Referring to fig. 1, a schematic flow diagram of a risk processing method for an online process provided in an embodiment of the present application is shown, where the risk processing method is applied to a server, the server provides an online service for a client APP or an applet and the like on a terminal device of a user, and the user can trigger an online process of the online service in the client APP or the applet on the terminal device. And the server monitors corresponding process nodes in the online process in real time, and detects and processes the risks of the process nodes when detecting that the process nodes are triggered. And the server is connected with a corresponding database to acquire corresponding data. As shown in fig. 1, the risk processing method may include the steps of:
step S101, when the target process node is triggered, determining N associated risk factors associated with the target process node from a risk factor library.
The risk factor library stores association relations between the risk factors and the process nodes, is a preset database, and one process node may be associated with one or more risk factors and one risk factor may also be associated with one or more process nodes. When the risk detection of the process node needs to be carried out by adding a certain detection mode, a risk factor corresponding to the detection mode is added in the risk factor library and is associated with the process node, when the risk detection of the process node needs to be carried out by deleting a certain detection mode, the risk factor corresponding to the detection mode can be found in the risk factor library and is deleted or is disconnected from the association relation of the process node, and when the risk detection of the process node needs to be improved for a certain detection mode, the risk factor corresponding to the detection mode in the risk factor library can be modified.
According to the risk detection requirements of each process node, the risk factors are flexibly configured to be associated with the process nodes, namely the flexibility of the risk factors and the flexibility of the process nodes are considered, the risk factors are allowed to be configured at any process node, and all the risk factors are allowed to be configured at any process node.
A risk factor library is created in the server, developers add the developed and tested risk factors into the risk factor library, and configure the process nodes corresponding to the risk factors to form the incidence relation between the risk factors and the process nodes. In one embodiment, the risk factor library is an independent database, and the server is connected to the risk factor library to obtain the corresponding risk factors according to the association relationship in the risk factor library.
The risk factor is a Java method class for realizing corresponding risk detection, the Java method class is used for realizing the function of risk detection, the Java method class is developed and formed by developers based on different risk detection requirements, and the risk detection can be realized and the risk detection result can be output by executing the corresponding Java method class. For example, the risk factor may be a Java method class for detecting a quota on a service, or the risk factor may be a Java method class for detecting whether a user belongs to a blacklist.
The risk factor is developed by splitting the existing risk detection code written by hard coding on the process node and the process node, so that the risk detection and the process node are disconnected in a coding form, and the risk detection is converted into an independent risk factor. And extracting and classifying the risk factors aiming at a certain online process, removing repeated risk factors, and developing and storing each risk factor into a risk factor library according to established business logic through a Java method class. For example, if risk detection is performed for each process node of the process a by using the risk factor 1, the risk factor 1 is developed and added to the risk factor library, and the risk factor 1 is associated with each process node of the process a.
For example, the target process node is a node in the online process service such as the investment process, such as a commit node, and the risk detection required when the node is committed may be an investment upper limit risk, a credit risk, and the like. The target process node is triggered by the last node of the target process node completing or the target process node being submitted.
Optionally, before performing risk detection on the target process node by using each associated risk factor, the method further includes:
outputting an authority prompt to a user triggering a target process node, wherein the authority prompt is used for prompting the user to allow sending basic information of the user to execute risk detection;
accordingly, performing risk detection on the target process node using each associated risk factor includes:
and if the basic information sent by the user is received, performing risk detection on the target process node by using each associated risk factor.
And when the server collects the action instruction for triggering the process node from the terminal equipment of the user, the server executes the step of determining all risk factors associated with the target process node from the risk factor library. After the target process node is triggered, whether a user triggering the target process node allows the server to acquire the basic information of the user or not can be inquired, and the basic information of the user can be sent to the server by the user allowing party for risk detection, otherwise, the risk detection is finished. In one embodiment, if the user does not allow the basic information of the user to be sent to the server, a permission reminding can be output to remind the user that the basic information of the user needs to be allowed to be sent to the server, and the risk detection can be executed. For example, a dialog box of "right-off reminder" is popped up in the client APP on the terminal device of the user, and the user is triggered to perform a selection operation in the dialog box.
For example, for a process node a, a risk detection function of "whether a file is real" needs to be added, so that the risk detection function of "whether a file is real" is packaged as a Java method class, that is, a risk factor 1, the risk factor 1 is stored in a risk factor library, and is configured in the risk factor library to be associated with the process node a, when the process node a is triggered, all risk factors associated with the process node a in the risk factor library are obtained, and all risk factors are called to perform risk detection, so as to obtain a risk detection result.
In the application, the server can also provide risk factor storage service, collect risk factors compiled by developers by providing a risk factor compiling interface, upload the compiled risk factors to a risk factor library through a risk factor uploading interface, the risk factor library can be subjected to services such as inquiry, editing and the like, and the uploaded risk factors can be associated with the process nodes through editing service after the developers upload the risk factors.
And S102, performing risk detection on the target process node by using each associated risk factor to obtain a corresponding risk detection result.
Therefore, each associated risk factor corresponding to the target process node needs to be used, so as to realize corresponding risk detection and obtain a corresponding risk detection result. For example, the service quota of the submitting node is detected through the risk factor 2, the risk detection result is obtained to be within the service quota range, namely no risk or pass, whether the user belongs to the blacklist is detected through the risk factor 3, and the risk detection result is obtained to be that the user belongs to the blacklist, namely risk or fail.
The risk detection results can include types such as pass, warning and fail, and the display modes of the risk detection results are different according to different types, so that different types of risk detection results are distinguished.
Optionally, performing risk detection on the target process node by using each associated risk factor includes:
calling each associated risk factor by using a Java reflection mechanism;
and executing each Java method class to carry out risk detection on the target process node.
The risk factor can be used by calling the risk factor by using a Java reflection technology, namely calling a Java method class, so that risk detection is realized, and a risk detection result is obtained. After a Java method class is executed, a risk detection result is obtained, i.e. one risk factor corresponds to one risk detection result.
The Java reflection technology may dynamically load a specified class from the memory and obtain all contents in the class, and the basic steps of reflection include: obtaining a Class object, namely obtaining a byte code file object with a specified name; instantiating an object to obtain the attribute, method or constructor of a class; accessing attributes, calling methods, calling constructor creating objects.
Optionally, after determining N associated risk factors associated with the target process node from the risk factor library, the method further includes:
detecting the state of the N associated risk factors;
removing the associated risk factors with failure states from the N associated risk factors to obtain M target risk factors, wherein M is an integer which is less than or equal to N and is greater than zero;
correspondingly, the step of performing risk detection on the target process node by using each associated risk factor to obtain a corresponding risk detection result comprises the following steps:
and carrying out risk detection on the target process nodes by using each target risk factor to obtain corresponding risk detection results.
In order to define the usage requirements of the risk factors, after N associated risk factors are determined, the state of each associated risk factor needs to be detected, so as to determine whether the associated risk factors can be used. In one embodiment, each risk factor in the risk factor library corresponds to identification information and the like, the risk factor that cannot be used may be identified as "invalid", the identification number is identified as "0", the risk factor that can be used may be identified as "valid", the identification number is identified as "1", and the detection of "0" and "1" may determine the state of the risk factor. When the identifier of the risk factor is "failure", all process nodes associated with the risk factor cannot use the risk factor to perform risk detection.
And eliminating the risk factors with failure states from the acquired N associated risk factors, and performing risk detection on the target process nodes by using the eliminated remaining associated risk factors.
Optionally, the detecting the states of the N associated risk factors includes:
acquiring the current time and the use time of each associated risk factor;
if the current time is not within the use timeliness of the associated risk factor, the state of the associated risk factor is invalid;
if the current time is within the usage age of the associated risk factor, the status of the associated risk factor is valid.
In one embodiment, the use age and the like are set for each risk factor in the risk factor library, and the state of a risk factor not in the use age is "invalid" and the state of a risk factor in the use age is "valid". And determining the state of the risk factor according to the current time and the use aging corresponding to the risk factor. And eliminating risk factors of which the current time is not in the use time limit from the N associated risk factors, and carrying out risk detection on the target process node by using the residual associated risk factors after elimination.
And step S103, generating corresponding risk processing events according to each risk detection result.
After the risk detection result is obtained, in order to facilitate the user to process the risk detection result, the risk detection result needs to be converted into a corresponding processing event and displayed on the terminal device of the user, so that the risk detection result is used for the user to process. The risk detection result may include a pass type, an alert type, a fail type, and the like, and different types may correspond to different risk processing events. For example, when the risk detection result is "pass", the corresponding risk processing event may be a "review" button, and the user may review the risk detection process by clicking the "review" button, and when the risk detection result is "fail", the corresponding risk processing event may be a "processing" button, and the user may generate a processing interface by clicking the "processing" button.
The risk processing event is used for processing a corresponding risk detection result, when the risk detection result indicates that a risk exists, the generated risk processing event needs to be operated by a user firstly, the online process can be continued after the operation meets the condition, and when the risk detection result indicates that no risk exists or the risk is small, the generated risk processing event does not need to be operated by the user for the risk processing time, but correspondingly can provide a look-up function, so that the user can conveniently look up detailed information.
The risk processing event may be a processing button triggered by a touch click or a mouse click by a user to enter a corresponding processing interface. If the risk processing event is clicked and then the processing interface is popped up, a user can operate in the processing interface, wherein the operation comprises uploading of a certificate, face recognition, password input and the like, so that risks are eliminated, and if the risk processing event is clicked and then the browsing interface is popped up, the user can look up detailed information of risk detection in the browsing interface, wherein the detailed information comprises a risk detection object, a risk detection method, a file used for the risk detection and the like.
When a plurality of risk detection results exist, a plurality of risk processing events are correspondingly generated, so that the risk detection results and the risk processing events thereof can be displayed in a list form when displayed on the terminal equipment of a user, each risk detection result is arranged from top to bottom, and the corresponding risk processing event is correspondingly displayed in the next column of the row where each risk detection result is located.
In the method and the device, all risk detection results can be arranged and displayed for the target process node, and processing operation options are provided for a user, so that the method and the device are beneficial to the user to obtain the risk comprehension of the process node, such as the conditions of high risk, medium risk and low risk, and can effectively guide the user to process.
Optionally, after generating a corresponding risk processing event according to each risk detection result, the method further includes:
acquiring a trigger signal of each risk processing event of a user;
and outputting a processing interface corresponding to the risk processing event according to each trigger signal, wherein the processing interface is used for displaying the detection process information and/or outputting the processing operation component.
Wherein the trigger signal may refer to a signal triggering a risk processing event. For example, when the risk processing time is a button, clicking the button is a signal that triggers a risk processing event. The processing interface may be different according to different risk processing events, for example, when a risk processing event is "pass", the output processing interface after generating the trigger signal is only used for displaying the detection process information, and when a risk processing event is "fail", the output processing interface after generating the trigger signal includes a processing operation component, and the processing operation component may be used for providing a corresponding processing operation.
And step S104, when each risk processing event is triggered, processing a corresponding risk detection result.
The triggering instruction for triggering the risk processing event may refer to clicking the risk processing event, performing a processing operation in the generated processing interface, and the like. And if the risk processing event is a 'look up' button, clicking the 'look up' button to trigger the risk processing event, and processing the corresponding risk detection result to show detailed information in the risk detection process. And if the risk processing event is a 'processing' button, a processing interface is generated after the 'processing' button is clicked, processing operation in the processing interface is to trigger the risk processing event, and processing the corresponding risk detection result is to process the risk detection result according to the processing operation in the processing interface. For example, if the risk detection result is "no pass", and the "ignore" operation is clicked in the processing interface generated after the "process" button is clicked, the risk detection result corresponding to the processing is ignored, and the risk detection result can be considered as pass.
For example, for a process node a, a risk detection function of "whether a file is real" needs to be added, so that, during development, the risk detection function of "whether a file is real" is packaged as a risk factor 4, the risk factor 4 is stored in a risk factor library, and is configured to be associated with the process node a in the risk factor library, when the process node a is triggered, all risk factors (including risk factor 2, risk factor 3, and risk factor 4) associated with the process node a in the risk factor library are acquired, all risk factors are called to perform risk detection, and a risk detection result corresponding to each risk factor is acquired, for example, the risk detection result corresponding to the risk factor 2 is "pass", the risk detection result corresponding to the risk factor 3 is "alert", the risk detection result corresponding to the risk factor 4 is "fail", accordingly, the risk processing event corresponding to the risk factor 2 is "view", the risk processing event corresponding to the risk factor 3 is "view", and the risk processing event corresponding to the risk factor 4 is "process".
According to the method and the device, when the target process node is triggered, N associated risk factors associated with the target process node are determined from the risk factor library, and the risk factors are Java method classes for realizing corresponding risk detection.
Referring to fig. 2, which is a schematic flow chart of a risk processing method of an online flow provided in the second embodiment of the present application, as shown in fig. 2, the risk processing method may include the following steps:
step S201, when the target process node is triggered, N associated risk factors associated with the target process node are determined from the risk factor library.
And S202, performing risk detection on the target process node by using each associated risk factor to obtain a corresponding risk detection result.
The content types of steps S201 to S202 are the same as those of steps S101 to S102, and reference may be made to the description of steps S101 to S102, which is not repeated herein.
Step S203, generating corresponding risk display events according to each risk detection result.
After the risk detection result is obtained, in order to facilitate the user to check the risk detection result, the risk detection result needs to be converted into a corresponding risk display event and displayed on the terminal device of the user. The risk detection result can comprise types of pass, warning, fail and the like, and different types can correspond to different risk display events. For example, when the risk detection result is "pass", no risk is indicated, and thus, the corresponding risk presentation event may be a green mark, and when the risk detection result is "fail", a risk is indicated, and thus, the corresponding risk presentation event may be a red mark.
The risk display event is used for displaying the risk detection results in a distinguishing manner, can be a display rule such as marking operation and rendering operation, and can be used for displaying different risk detection results in a distinguishing manner.
Step S204, each risk display event is combined with the corresponding risk detection result to display each risk detection result.
The combination may refer to displaying the risk detection result according to a display rule corresponding to the risk display event. For example, when the risk detection result is "pass", the ground color of the row in which the risk detection result is located is filled with green using a green marking operation, when the risk detection result is "alert", the ground color of the row in which the risk detection result is located is filled with yellow using a yellow marking operation, and when the risk detection result is "fail", the ground color of the row in which the risk detection result is located is filled with red using a red marking operation.
For example, for a process node a, a risk detection function of "whether a file is real" needs to be added, so that, during development, the risk detection function of "whether a file is real" is packaged as a risk factor 4, the risk factor 4 is stored in a risk factor library, and is configured to be associated with the process node a in the risk factor library, when the process node a is triggered, all risk factors (including risk factor 2, risk factor 3, and risk factor 4) associated with the process node a in the risk factor library are acquired, all risk factors are called to perform risk detection, and a risk detection result corresponding to each risk factor is acquired, for example, the risk detection result corresponding to the risk factor 2 is "pass", the risk detection result corresponding to the risk factor 3 is "alert", the risk detection result corresponding to the risk factor 4 is "fail", correspondingly, the risk detection result corresponding to the risk factor 1 is marked as green, the risk detection result corresponding to the risk factor 2 is marked as yellow, and the risk detection result corresponding to the risk factor 3 is marked as red.
According to the risk detection method and device, the corresponding risk display events are generated according to each risk detection result, each risk display event is combined with the corresponding risk detection result, each risk detection result is displayed, different display aiming at different risk detection results is achieved, and a user can observe conveniently.
Corresponding to the risk processing method of the foregoing embodiment, fig. 3 shows a block diagram of a risk processing apparatus of an online process provided in the third embodiment of the present application, where the risk processing apparatus is applied to a server, the server provides an online service for a client APP or an applet and the like on a terminal device of a user, and the user can trigger the online process of the online service in the client APP or the applet on the terminal device. And the server monitors corresponding process nodes in the online process in real time, and detects and processes the risks of the process nodes when detecting that the process nodes are triggered. And the server is connected with a corresponding database to acquire corresponding data. For convenience of explanation, only portions related to the embodiments of the present application are shown.
Referring to fig. 3, the risk processing apparatus includes:
a risk factor determining module 31, configured to determine, when a target process node is triggered, N associated risk factors associated with the target process node from a risk factor library, where the risk factor library stores association relationships between the risk factors and the process node, where a risk factor is a Java method class for implementing corresponding risk detection, and N is an integer greater than zero;
a risk detection module 32, configured to perform risk detection on the target process node using each associated risk factor to obtain a corresponding risk detection result;
a processing event generating module 33, configured to generate a corresponding risk processing event according to each risk detection result;
and the risk processing module 34 is used for processing the corresponding risk detection result when each risk processing event is triggered.
Optionally, the risk processing apparatus further includes:
the display event generation module is used for carrying out risk detection on the target process node by using each associated risk factor to obtain a corresponding risk detection result, and then generating a corresponding risk display event according to each risk detection result;
and the display module is used for combining each risk display event with the corresponding risk detection result so as to display each risk detection result.
Optionally, the risk processing apparatus further includes:
the state detection module is used for detecting the states of the N associated risk factors after the N associated risk factors associated with the target process node are determined from the risk factor library;
the eliminating module is used for eliminating the associated risk factors with failure states from the N associated risk factors to obtain M target risk factors, wherein M is an integer which is less than or equal to N and is greater than zero;
accordingly, the risk detection module 32 is specifically configured to:
and carrying out risk detection on the target process nodes by using each target risk factor to obtain corresponding risk detection results.
Optionally, the state detection module includes:
the aging acquiring unit is used for acquiring the current time and the use aging of each associated risk factor;
the first state judgment unit is used for judging that the state of the associated risk factor is invalid if the current time is not within the use timeliness of the associated risk factor;
and the second state judgment unit is used for judging that the state of the associated risk factor is valid if the current time is within the use time limit of the associated risk factor.
Optionally, the risk processing apparatus further includes:
the permission prompting module is used for outputting permission prompts to users triggering the target process nodes before risk detection is carried out on the target process nodes by using each associated risk factor, and the permission prompts are used for prompting the users to allow basic information of the users to be sent to execute the risk detection;
accordingly, the risk detection module 32 includes:
and the risk detection unit is used for carrying out risk detection on the target process node by using each associated risk factor if the basic information sent by the user is received.
Optionally, the risk detection module 32 includes:
the calling unit is used for calling each associated risk factor by using a Java reflection mechanism;
and the execution unit is used for executing each Java method class to carry out risk detection on the target process node.
Optionally, the risk processing apparatus further includes:
the trigger signal acquisition module is used for acquiring a trigger signal of each risk processing event from a user after generating a corresponding risk processing event according to each risk detection result;
and the output module is used for outputting a processing interface corresponding to the risk processing event according to each trigger signal, and the processing interface is used for displaying the detection process information and/or outputting the processing operation component.
It should be noted that, because the contents of information interaction, execution process, and the like between the modules are based on the same concept as that of the embodiment of the method of the present application, specific functions and technical effects thereof may be specifically referred to a part of the embodiment of the method, and details are not described here.
Fig. 4 is a schematic structural diagram of a server according to a fourth embodiment of the present application. As shown in fig. 4, the server 4 of this embodiment includes: at least one processor 40 (only one shown in fig. 4), a memory 41, and a computer program 42 stored in the memory 41 and executable on the at least one processor 40, the steps in any of the various risk processing method embodiments described above being implemented when the computer program 42 is executed by the processor 40.
The server 4 may include, but is not limited to, a processor 40, a memory 41. Those skilled in the art will appreciate that fig. 4 is merely an example of the server 4 and does not constitute a limitation of the server 4, and may include more or less components than those shown, or combine certain components, or different components, such as input output devices, network access devices, etc.
The Processor 40 may be a CPU, and the Processor 40 may also be other general purpose processors, Digital Signal Processors (DSPs), Application Specific Integrated Circuits (ASICs), Field-Programmable Gate arrays (FPGAs) or other Programmable logic devices, discrete Gate or transistor logic devices, discrete hardware components, etc. A general purpose processor may be a microprocessor or the processor may be any conventional processor or the like.
The storage 41 may in some embodiments be an internal storage unit of the server 4, such as a hard disk or a memory of the server 4. The memory 41 may be an external storage device of the server 4 in other embodiments, such as a plug-in hard disk, a Smart Media Card (SMC), a Secure Digital (SD) Card, a Flash memory Card (Flash Card), and the like, provided on the server 4. Further, the memory 41 may also include both an internal storage unit of the server 4 and an external storage device. The memory 41 is used for storing an operating system, an application program, a BootLoader (BootLoader), data, and other programs, such as program codes of a computer program. The memory 41 may also be used to temporarily store data that has been output or is to be output.
It will be apparent to those skilled in the art that, for convenience and brevity of description, only the above-mentioned division of the functional units and modules is illustrated, and in practical applications, the above-mentioned function distribution may be performed by different functional units and modules according to needs, that is, the internal structure of the apparatus is divided into different functional units or modules, so as to perform all or part of the functions described above. Each functional unit and module in the embodiments may be integrated in one processing unit, or each unit may exist alone physically, or two or more units are integrated in one unit, and the integrated unit may be implemented in a form of hardware, or in a form of software functional unit. In addition, specific names of the functional units and modules are only for convenience of distinguishing from each other, and are not used for limiting the protection scope of the present application. The specific working processes of the units and modules in the above-mentioned apparatus may refer to the corresponding processes in the foregoing method embodiments, and are not described herein again. The integrated unit, if implemented in the form of a software functional unit and sold or used as a stand-alone product, may be stored in a computer readable storage medium. Based on such understanding, all or part of the flow of the method of the embodiments described above can be implemented by a computer program, which can be stored in a computer readable storage medium and can implement the steps of the embodiments of the methods described above when the computer program is executed by a processor. Wherein the computer program comprises computer program code, which may be in the form of source code, object code, an executable file or some intermediate form, etc. The computer readable medium may include at least: any entity or device capable of carrying computer program code, recording medium, computer Memory, Read-Only Memory (ROM), Random Access Memory (RAM), electrical carrier wave signals, telecommunications signals, and software distribution media. Such as a usb-disk, a removable hard disk, a magnetic or optical disk, etc. In certain jurisdictions, computer-readable media may not be an electrical carrier signal or a telecommunications signal in accordance with legislative and patent practice.
When the computer program product runs on a server, the steps in the method embodiments can be implemented when the server executes the computer program product.
In the above embodiments, the descriptions of the respective embodiments have respective emphasis, and reference may be made to the related descriptions of other embodiments for parts that are not described or illustrated in a certain embodiment.
Those of ordinary skill in the art will appreciate that the various illustrative elements and algorithm steps described in connection with the embodiments disclosed herein may be implemented as electronic hardware or combinations of computer software and electronic hardware. Whether such functionality is implemented as hardware or software depends upon the particular application and design constraints imposed on the implementation. Skilled artisans may implement the described functionality in varying ways for each particular application, but such implementation decisions should not be interpreted as causing a departure from the scope of the present application.
In the embodiments provided in the present application, it should be understood that the disclosed apparatus/server and method may be implemented in other ways. For example, the above-described apparatus/server embodiments are merely illustrative, and for example, a division of modules or units is merely a logical division, and an actual implementation may have another division, for example, a plurality of units or components may be combined or integrated into another system, or some features may be omitted, or not executed. In addition, the shown or discussed mutual coupling or direct coupling or communication connection may be an indirect coupling or communication connection through some interfaces, devices or units, and may be in an electrical, mechanical or other form.
Units described as separate parts may or may not be physically separate, and parts displayed as units may or may not be physical units, may be located in one place, or may be distributed on a plurality of network units. Some or all of the units can be selected according to actual needs to achieve the purpose of the solution of the embodiment.
The above embodiments are only used to illustrate the technical solutions of the present application, and not to limit the same; although the present application has been described in detail with reference to the foregoing embodiments, it should be understood by those of ordinary skill in the art that: the technical solutions described in the foregoing embodiments may still be modified, or some technical features may be equivalently replaced; such modifications and substitutions do not substantially depart from the spirit and scope of the embodiments of the present application and are intended to be included within the scope of the present application.
Claims (10)
1. A risk processing method for an online process, the risk processing method comprising:
when a target process node is triggered, determining N associated risk factors associated with the target process node from a risk factor library, wherein the risk factor library stores the association relationship between the risk factors and the process node, the risk factors are Java method classes for realizing corresponding risk detection, and N is an integer greater than zero;
performing risk detection on the target process node by using each associated risk factor to obtain a corresponding risk detection result;
generating a corresponding risk processing event according to each risk detection result;
and processing the corresponding risk detection result when each risk processing event is triggered.
2. The risk processing method according to claim 1, wherein after performing risk detection on the target process node by using each associated risk factor to obtain a corresponding risk detection result, the method further comprises:
generating a corresponding risk display event according to each risk detection result;
and combining each risk display event with the corresponding risk detection result to display each risk detection result.
3. The risk processing method of claim 1, further comprising, after determining the N associated risk factors associated with the target process node from the risk factor library:
detecting the state of the N associated risk factors;
removing the associated risk factors with failure states from the N associated risk factors to obtain M target risk factors, wherein M is an integer which is less than or equal to N and is greater than zero;
correspondingly, the performing risk detection on the target process node by using each associated risk factor to obtain a corresponding risk detection result includes:
and carrying out risk detection on the target process nodes by using each target risk factor to obtain corresponding risk detection results.
4. The risk processing method of claim 3, wherein the detecting the state of the N associated risk factors comprises:
acquiring the current time and the use time of each associated risk factor;
if the current time is not within the use timeliness of the associated risk factor, the state of the associated risk factor is invalid;
and if the current time is within the use time limit of the associated risk factor, the state of the associated risk factor is valid.
5. The risk processing method of claim 1, wherein before the risk probing the target process node using each associated risk factor, further comprising:
outputting an authority prompt to a user triggering the target process node, wherein the authority prompt is used for prompting the user to allow sending basic information of the user to execute risk detection;
correspondingly, the risk detection of the target process node by using each associated risk factor includes:
and if the basic information sent by the user is received, performing risk detection on the target process node by using each associated risk factor.
6. The risk processing method of claim 1, wherein the risk probing the target process node using each associated risk factor comprises:
calling each associated risk factor by using a Java reflection mechanism;
executing each Java method class to carry out risk detection on the target process node.
7. The risk processing method according to any one of claims 1 to 6, further comprising, after the generating a corresponding risk processing event according to each risk detection result:
acquiring a trigger signal of the user for each risk processing event;
and outputting a processing interface corresponding to the risk processing event according to each trigger signal, wherein the processing interface is used for displaying the detection process information and/or outputting the processing operation component.
8. A risk processing apparatus of an online process, the risk processing apparatus comprising:
a risk factor determination module, configured to determine, when a target process node is triggered, N associated risk factors associated with the target process node from a risk factor library, where the risk factor library stores an association relationship between risk factors and process nodes, the risk factors are Java method classes for implementing corresponding risk detection, and N is an integer greater than zero;
the risk detection module is used for carrying out risk detection on the target process node by using each associated risk factor to obtain a corresponding risk detection result;
the processing event generating module is used for generating corresponding risk processing events according to each risk detection result;
and the risk processing module is used for processing the corresponding risk detection result when each risk processing event is triggered.
9. A server, characterized in that the server comprises a processor, a memory and a computer program stored in the memory and executable on the processor, the processor implementing the risk processing method according to any one of claims 1 to 7 when executing the computer program.
10. A computer-readable storage medium, in which a computer program is stored, which, when being executed by a processor, carries out the risk processing method according to any one of claims 1 to 7.
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