CN116614407A - Risk control method and device - Google Patents

Abstract

One or more embodiments of the present disclosure provide a risk control method and apparatus, where the method includes: firstly, acquiring a plurality of single-point quality evaluation information of a plurality of service nodes in a target call chain, wherein each single-point quality evaluation information comprises quality evaluation information of service data generated by any service node aiming at a service processing call request, and different service data are acquired based on a target call request identifier; and then, carrying out full-link evaluation processing based on the plurality of single-point quality evaluation information to obtain full-link quality evaluation information corresponding to the target call request identifier, and carrying out risk prevention and control on the target call chain based on the full-link quality evaluation information.

Description

A risk control method and device

technical field

This document relates to the field of Internet technology, in particular to a risk control method and device.

Background technique

At present, with the rapid development of Internet technology, back-end servers that provide services for front-end applications are facing more and more network risks. Therefore, risk assessment of back-end servers is required to improve their anti-risk capabilities , to ensure the stability and efficiency of its service capabilities.

However, with the development of risk control technology, more and more risk control technologies are applied to the field of risk control, more and more systems are connected to the risk control link, and more and more nodes are used for data transfer , the proportion of cross-network and long-link transfer business is getting higher and higher. However, in the process of risk assessment, it is analyzed on a single node, and the situation of other nodes is often unknown, which leads to its risk Control has relatively large limitations, often resulting in misjudgments and missed judgments, affecting the smooth progress of business and data security.

It can be seen from this that it is necessary to provide a more comprehensive risk control method to reduce misjudgments and missed judgments and improve the accuracy of risk control.

Contents of the invention

The purpose of one or more embodiments of this specification is to provide a risk control method. The risk control method includes:

Obtain multiple single-point quality evaluation information of multiple service nodes in the target call chain; wherein, each of the single-point quality evaluation information includes the quality evaluation information of the service data generated by any of the service nodes for the service processing call request The service data corresponding to different service nodes is obtained based on the same target invocation request identifier corresponding to the service processing invocation request.

A full-link evaluation process is performed based on the multiple single-point quality evaluation information to obtain full-link quality evaluation information corresponding to the target invocation request identifier.

Risk prevention and control is performed on the target call chain based on the full link quality assessment information.

The purpose of one or more embodiments of this specification is to provide a risk control device. The risk control device includes:

A single-point evaluation information acquisition module, which obtains multiple single-point quality evaluation information of multiple service nodes in the target call chain; wherein, each of the single-point quality evaluation information includes any of the service nodes for the service processing call request. The generated service data quality evaluation information, and the service data corresponding to different service nodes are obtained based on the same target invocation request identifier corresponding to the service processing invocation request.

A full-link evaluation information determination module, which performs full-link evaluation processing based on the multiple single-point quality evaluation information, and obtains full-link quality evaluation information corresponding to the target invocation request identifier.

A call chain risk control module, which implements risk prevention and control on the target call chain based on the full link quality assessment information.

An object of one or more embodiments of the present specification is to provide a risk control device comprising: a processor; and a memory arranged to store computer-executable instructions.

When the computer-executable instructions are executed, the processor acquires multiple single-point quality assessment information of multiple service nodes in the target call chain, wherein each single-point quality assessment information includes any one of the service The quality evaluation information of the business data generated by the node for the service processing call request. The service data corresponding to different service nodes is obtained based on the same target call request identifier corresponding to the service process call request; based on the multiple The single-point quality evaluation information is processed for full link evaluation to obtain the full link quality evaluation information corresponding to the target call request identifier; based on the full link quality evaluation information, risk prevention and control is performed on the target call chain.

An object of one or more embodiments of the present specification is to provide a storage medium for storing computer-executable instructions. The executable instructions are executed by the processor to implement the following method: obtain multiple single-point quality assessment information of multiple service nodes in the target call chain; wherein, each of the single-point quality assessment information includes any one of the service node For the quality evaluation information of the service data generated by the service processing call request, the service data corresponding to the different service nodes is obtained based on the same target call request identifier corresponding to the service process call request; based on the multiple The single-point quality assessment information is subjected to full-link assessment processing to obtain full-link quality assessment information corresponding to the target call request identifier; based on the full-link quality assessment information, risk prevention and control is performed on the target call chain.

Description of drawings

In order to more clearly illustrate one or more embodiments of this specification or the technical solutions in the prior art, the following will briefly introduce the drawings that need to be used in the description of the embodiments or the prior art. Obviously, in the following description The accompanying drawings are only some embodiments described in one or more of the present specification, and those skilled in the art can also obtain other drawings according to these drawings without any creative effort.

FIG. 1 is a schematic diagram of an application scenario of a risk control system provided by one or more embodiments of this specification;

Fig. 2 is a schematic flow chart of the first risk control method provided by one or more embodiments of this specification;

Fig. 3 is a second schematic flow chart of the risk control method provided by one or more embodiments of this specification;

Fig. 4 is a schematic diagram of the module composition of the risk control device provided by one or more embodiments of this specification;

Fig. 5 is a schematic structural diagram of a risk control device provided by one or more embodiments of this specification.

Detailed ways

In order to enable those skilled in the art to better understand the technical solutions in one or more embodiments of this specification, the technical solutions in one or more embodiments of this specification will be described below in conjunction with the drawings in one or more embodiments of this specification To describe clearly and completely, it is obvious that the described embodiments are only one or more partial embodiments in this specification, rather than all the embodiments. All other embodiments obtained by persons of ordinary skill in the art based on one or more embodiments in this specification without creative efforts shall fall within the scope of protection of this document.

It should be noted that, in the case of no conflict, one or more embodiments in this specification and features in the embodiments can be combined with each other. One or more embodiments of this specification will be described in detail below with reference to the drawings and in combination with the embodiments.

Some terms in one or more embodiments of this specification are explained as follows:

A data transfer node, also known as a service node, is an abstract concept that represents a system or an interface through which data passes.

Data transfer full link, referred to as full link and full call link, refers to the combination of transfer relationships between data transfer nodes to form a complete data transfer link.

One or more embodiments of this specification provide a risk control method and device, by obtaining multiple single-point quality assessment information of multiple service nodes in the target call chain, wherein each single-point quality assessment information includes any business The quality evaluation information of the business data generated by the node for the business processing call request. Different business data are obtained based on the target call request identifier; Request the full link quality assessment information corresponding to the identification, and then based on the above full link quality assessment information, carry out risk prevention and control on the target call chain, so that the quality assessment information of each business node can be collected from the perspective of the full link for comprehensive risk assessment Prevention and control, avoiding missed judgments and misjudgments caused by the limitations of single-node risk control, and improving the accuracy of risk control.

Figure 1 is a schematic diagram of the application scenario of the risk control system provided by one or more embodiments of this specification. As shown in Figure 1, the system includes: a client and a server, where the client can be a smart phone, a tablet, etc. Mobile terminal, the client can also be a terminal device such as a personal computer, the server can be a business server for processing the business initiated by the client, the server can be an independent server, or it can be composed of multiple A server cluster composed of servers. In the microservice architecture, the server can be a service node in the microservice architecture, and can also be called a business node.

Among them, the risk control method provided by one or more embodiments of this specification can be applied to the server, and the server can be located at any risk control node, for example, it can be any business node in the business link of the microservice architecture, The specific process of the risk control method is as follows: firstly obtain multiple single-point quality assessment information of multiple service nodes in the target call chain, wherein each single-point quality assessment information includes Requesting the quality evaluation information of the business data generated, different business data is obtained based on the target invocation request identification, and then performing full-link evaluation processing based on the multiple single-point quality evaluation information to obtain the target invocation request identification The corresponding full-link quality assessment information, and then based on the full-link quality assessment information, carry out risk prevention and control on the target call chain, so that the quality assessment information of each service node can be collected from the perspective of the full link for comprehensive Risk prevention and control, avoiding missed judgments and misjudgments caused by the limitations of single-node risk control, and improving the accuracy of risk control.

In the above application scenario, referring to Figure 1, the client can initiate the target business according to the user's operation. The processing of the target business requires the joint participation of multiple business nodes in the microservice architecture. After connecting to A, server A needs to continue to call servers B, C, and D. Among them, server D also needs to call server E. When each called server returns data, server A returns business to the client Respond to the data and complete the business process. The set of a series of invocation relationships initiated from the server constitutes the invocation link corresponding to the business request, referred to as the invocation chain. The above-mentioned servers A, B, C, D, and E are business nodes. In related technologies, the above multiple business nodes may be separated due to at least one of network domain, geographic location, management authority, function, and database category, so that only any one of the nodes can be used for single-node risk prevention and control , but it is impossible to know the risk status of other nodes and carry out targeted prevention and control. Therefore, the risk prevention and control methods provided by related technologies mainly focus on the data quality assessment of a single node, and carry out risk prevention and control methods and system upgrades from the following two aspects Among them, on the one hand, it can be to reduce the human cost of combing and configuring and judging the data quality level, for example, using machine learning to automatically determine the threshold of data quality early warning using historical data; on the other hand, it can be to increase the data quality evaluation. In different ways, for example, power grid companies focus on writing different formulas to evaluate data quality in electricity bill scenarios.

It is not difficult to see that the existing data quality detection and systems are all centered on the quality analysis of data in a single point system. However, the quality of the entire link formed by the flow of data in multiple systems is not involved. The risk control method provided by one or more embodiments of this specification is based on the background of the risk control field, creatively locates the flow links of data in different nodes, and performs quality inspection and early warning.

Specifically, the risk control method in one or more embodiments of this specification can be applied to any of the business nodes, and each business node in the above-mentioned microservice architecture can apply the above-mentioned risk control method, wherein any application of the above-mentioned The business nodes of the risk control method can obtain multiple single-point quality evaluation information of multiple business nodes in the target call chain, wherein each of the single-point quality evaluation information includes any service node's call request for business processing. The quality evaluation information of the generated business data, different business data is obtained based on the target invocation request identifier, and then the whole link evaluation process is performed based on the multiple single-point quality evaluation information to obtain the corresponding target invocation request identifier Based on the full link quality assessment information, risk prevention and control is performed on the target invocation chain based on the full link quality assessment information, so that the quality assessment information of each service node can be collected from the perspective of the full link for comprehensive risk prevention Control, avoid missed judgments and misjudgments caused by the limitations of single-node risk control, and improve the accuracy of risk control.

It should be noted that the business nodes are described above using the microservice architecture as an example, but it should not be understood as limiting the scope of protection of one or more embodiments of the description. In practical applications, the above business nodes can also be other distributed A node in the service architecture, and participate in the multi-node-based service invocation process, all of them can apply the risk control method provided by one or more embodiments of this specification to evaluate the data quality of the whole link and carry out corresponding risk prevention. control.

Fig. 2 is a schematic flowchart of the first risk control method provided by one or more embodiments of this specification. The method in Fig. 2 can be executed by the server in Fig. 1, and the server can be any one of the service nodes, As shown in Figure 2, the method at least includes the following steps:

S102. Obtain multiple single-point quality assessment information of multiple service nodes in the target call chain; wherein, each service node corresponds to a single-point quality assessment information, and each single-point quality assessment information includes any service node for business processing The quality evaluation information of the service data generated by the invocation request, and the service data corresponding to different service nodes are obtained based on the same target invocation request identifier corresponding to the above service processing invocation request.

Specifically, considering that the above multiple business nodes may be separated due to at least one of the reasons of network domain, geographical location, management authority, function, and database category, how to sort out the single-point quality evaluation information of multiple business nodes and summary become the first technical problems to be faced. Based on this, by using the call chain tracking technology in the microservice architecture, the call chain in the microservice architecture is used to realize the tracking and concatenation of business data, and the same target call request identifier (such as traceID) corresponds to Multiple business data of the target call chain are used as the associated business data, so that a target call chain is determined based on the business nodes to which the multiple business data corresponding to the same target call request identifier belong, that is, multiple business nodes in the target call chain are based on the same The target call request identifies multiple data generation nodes corresponding to the service data, and further calculates the full link quality evaluation information based on this. These will be further explained in the subsequent description, and will not be repeated here.

It should be noted that the significance of assessing data quality lies in being able to perceive changes in source data and generated dirty data in the first place, automatically intercept problematic tasks, effectively prevent dirty data from spreading downstream, and avoid problems where task output does not meet expectations Data, affecting normal use and business decisions. At the same time, it can also significantly reduce the time cost of problem handling and avoid the waste of resource costs caused by task rerunning. Therefore, it can be used as one of the main basis for risk prevention and control.

S104. Perform full-link evaluation processing based on the above-mentioned multiple single-point quality evaluation information, and obtain full-link quality evaluation information corresponding to the target invocation request identifier.

Specifically, after obtaining the single-point quality assessment information corresponding to multiple service nodes, it can be fused to obtain the full-link quality assessment information to reflect the data quality of the entire call chain, so as to facilitate further risk prevention from the perspective of the entire link. control.

It should be noted that, in some implementations, a target invocation request identifier corresponds to a service processing invocation request, and a target invocation request identifier corresponds to a full link quality assessment information. Therefore, the target invocation request identifier, service processing invocation request, There is a one-to-one correspondence of full link quality evaluation information, wherein the above full link quality evaluation information may be a score, such as a full link quality score.

S106. Perform risk prevention and control on the target invocation chain based on the above-mentioned full-link quality assessment information.

The risk control method provided by one or more embodiments of this specification obtains multiple single-point quality assessment information of multiple service nodes in the target call chain, wherein each single-point quality assessment information includes The quality evaluation information of the business data generated by the invocation request. Different business data are obtained based on the target invocation request identifier; then, based on the above-mentioned multiple single-point quality assessment information, the whole link evaluation process is performed to obtain the corresponding value of the target invocation request identifier. Based on the above-mentioned full-link quality assessment information, the risk prevention and control of the target call chain can be carried out, so that the quality assessment information of each service node can be collected from the perspective of the whole link for comprehensive risk prevention and control, avoiding Due to the limitations of single-node risk control, missed judgments and misjudgments, etc., improve the accuracy of risk control.

In the above step S102, there are at least two ways to obtain single-point quality assessment information, one is to obtain service data from other service nodes, and then calculate and obtain single-point quality assessment information according to the service data; the other is to obtain the single-point quality assessment information directly from other service nodes Nodes obtain their single-point quality evaluation information, and those skilled in the art can flexibly choose or change the implementation according to actual needs. The above two methods are further described below with examples.

In the first way, in one or more embodiments of this specification, the above step S102 acquires multiple single-point quality evaluation information of multiple service nodes in the target call chain, including:

Based on the target call request identifier generated for the service processing call request of the target call chain, query the service data corresponding to the target call request identifier from the call chain log corresponding to each service node of the target call chain;

For each of the above business nodes, based on the target quality assessment method, perform quality assessment on the business data corresponding to the service node, and obtain the single-point quality assessment information corresponding to the service node; wherein, the above target quality assessment method is for generating the above business data The quality evaluation method configured by the business node.

Wherein, the above-mentioned business data obtained may include business data corresponding to the target invocation request identifier and business data corresponding to multiple historical invocation request identifiers, or may be multiple records corresponding to multiple target invocation request identifiers within a certain unit time period. Business data is not limited by one or more embodiments of this specification.

Through this embodiment, the corresponding service data can be queried directly from the call chain log, and then the current service node performs quality assessment based on the quality assessment method corresponding to each service data, so as to obtain the single-point quality assessment information corresponding to each service node. In this way, the content and format recorded in the call chain log can continue to use the existing technology without changing, and the calculation of the single-point quality evaluation information is all implemented by the current service node, which has little impact on the existing call chain architecture. In the case of few changes to the existing architecture, the single-point quality assessment information of each service node is collected from the perspective of the whole link and integrated for comprehensive risk prevention and control.

In the second way, in other modified implementations of this specification, the above step S102 acquires multiple single-point quality evaluation information of multiple service nodes in the target call chain, including:

Based on the target call request identifier generated for the service processing call request of the target call chain, query the single-point quality evaluation information corresponding to the target call request identifier from the call chain log corresponding to each business node of the target call chain; wherein, each Each business node evaluates the quality of the business data generated by itself according to the target quality evaluation method, and writes the respective call chain logs after binding the single-point quality evaluation information obtained by the evaluation with the target call request identifier;

The single-point quality assessment information corresponding to the same target call request identifier is determined as multiple single-point quality assessment information of multiple service nodes in the target call chain.

Through this implementation mode, it is necessary to add the record of single-point quality assessment information of service nodes in the existing call chain log. The advantage is that each service node calculates the local single-point quality assessment information by itself, and any service node needs to execute this When describing the above-mentioned risk control method provided by one or more embodiments, the single-point quality evaluation information of other service nodes can be directly queried from the call chain log and integrated to carry out comprehensive risk prevention and control, eliminating the need for this The process of any service node calculating the single-point quality evaluation information of other business nodes, in other words, the evaluation process of the single-point quality evaluation information of each service node is distributed to each service node for execution. Through this "decentralization" , "Distributed" calculation method, make full use of the computing resources of each service node, improve the evaluation efficiency of single-point quality evaluation information as a whole, thereby improving the calculation efficiency of full-link quality evaluation information, and then improve the quality evaluation based on full-link The real-time and sensitivity of information for risk prevention and control.

On the basis of any of the above-mentioned embodiments, in some modified implementation manners, the above-mentioned single-point quality evaluation information may be obtained through at least one of the following quality evaluation methods:

Quality evaluation method 1: Based on the matching result of the service data and the data compliance determination rule configured for the above service node, generate single-point quality evaluation information corresponding to the above service node.

Quality assessment method 2: input the above service data into a quality assessment model configured for the above service node to perform quality assessment, and obtain single-point quality assessment information corresponding to the above service node.

Quality assessment method 3: use the quality assessment algorithm configured for the above service nodes to perform quality assessment on the above service data, and obtain single-point quality assessment information corresponding to the above service nodes.

The following takes the above-mentioned quality evaluation method 1 as an example for illustration. In some examples, it is assumed that the data message on a certain node X1, that is, the service data C1 is as follows:

[

{

"key1": 1,

"key2": 2

},

{

"key1": 11,

"key2":22

}

]

Assume that the data message on a node X2, that is, the business data C2 is as follows

[

{

"key1": null,

"key2": null

},

{

"key1": null,

"key2": null

}

]

Assume that the configured data compliance determination rule R1 is key1 and the corresponding length is [0,1] (indicating 0 to 1), and the configured data compliance determination rule R2 is key2 and the corresponding result is not empty.

After passing the data compliance determination rule R1, the single-point quality evaluation information RES1 of the data message C1 is 1/2=0.5, indicating that half of the data hits the rule R1; after passing the data compliance determination rule R2, the data message C1 this time The single-point quality assessment information RES2 of C2 is 0/2=0, indicating that no data matches the rule R2.

Above, the data compliance determination rule is taken as an example to illustrate. In addition, the instruction evaluation model and instruction evaluation algorithm are currently more commonly used methods for evaluating single-point quality evaluation information. Those skilled in the art can flexibly choose the appropriate one based on actual needs. The above-mentioned quality assessment method performs real-time calculation of single-point quality assessment information, which can be implemented with reference to existing technologies, and will not be repeated here.

Through the above-mentioned implementation, those skilled in the art can flexibly select the appropriate above-mentioned quality assessment method to perform real-time calculation of single-point quality assessment information, enrich the implementation means of one or more embodiments of this specification, and satisfy users' liberalization and diversification. need.

It should be noted that, in some implementations, the determination process of single-point quality evaluation information may not be based on the business data corresponding to one call request, but may also be calculated based on multiple pieces of business data corresponding to multiple call requests, for example , for a certain business node, take 1000 pieces of business data before the business data corresponding to the target invocation request identifier (including the business data corresponding to the target invocation request identifier), if there are 20 pieces that do not match rule 1, then, after rule 1 The subsequent scoring is 980/1000=0.98, which is also one of the changeable implementations of one or more embodiments of this specification, and should also be within the scope of protection of one or more embodiments of this specification; in addition, in specific During implementation, the full link quality assessment information may be calculated once for each service processing call request, or the full link quality assessment information may be calculated once at intervals of a certain number of service processing requests.

For the calculation of full link quality evaluation information, in one or more embodiments of this specification, the above step S104 performs full link evaluation processing based on multiple single-point quality evaluation information, and obtains the full link corresponding to the target call request identifier. Quality assessment information, including:

Obtain the quality impact weight corresponding to each business node in the target call chain;

Based on the above quality impact weights, the single-point quality evaluation information corresponding to each of the above service nodes is weighted and fused to obtain the full link quality evaluation information corresponding to the target call request identifier.

Through this embodiment, different quality impact weights can be set for different business nodes. For more important business nodes, the corresponding quality impact weights can be set to a larger value, while for non-important business nodes, the corresponding quality impact weights can be set to a larger value. The corresponding quality impact weight can be set to a smaller value, so that the full-link quality evaluation information obtained by weighted fusion can more accurately reflect the quality evaluation of the entire call chain, facilitating more targeted risk prevention and control .

On the basis of the above embodiments, in some modified implementation manners, the obtaining the quality impact weight corresponding to each of the service nodes in the target call chain includes:

According to the service category of the service processing call request corresponding to the above target call request identifier, determine the quality weight distribution information corresponding to the above target call chain; wherein, the quality weight distribution conditions corresponding to different service categories are different;

Based on the above quality weight distribution information, determine the quality impact weight corresponding to each service node in the above target call chain.

Considering different business processing call requests, the call links they pass through are generally different, which are generally divided according to business categories in practical applications. For example, the service links of payment requests and transfer requests are different, and In different links, the weight distribution of each service node can also be preset to be different according to actual needs. Therefore, in this case, one or more embodiments of this specification need to determine the corresponding The weight of the quality impact, so that the corresponding full-link quality evaluation information can be calculated for different business categories, and then the full-link quality tracking and targeted risk prevention and control can be carried out for different business categories, further improving risk prevention and control. level.

Among them, for the method of risk prevention and control, in one or more embodiments of this specification, the above step S106, based on the above-mentioned full link quality evaluation information, performs risk prevention and control on the target call chain, which may include:

Based on the full-link quality evaluation information corresponding to multiple target call request identifiers in the unit time period, the normalized quality evaluation information of the above unit time period is generated;

Determining normalized quality level change information based on the normalized quality evaluation information corresponding to multiple unit time periods;

Based on the above normalized quality level change information, risk prevention and control is carried out on the target call chain.

Considering that the single-point quality assessment methods deployed by different service nodes are not the same, the calculated single-point quality assessment information may have a large difference in value, which affects the judgment of the risk situation. Therefore, firstly, the full-link quality assessment information Perform normalization processing, and consider that in the case of a large amount of business data, if the quality fluctuations are analyzed one by one, on the one hand, the large amount of data is difficult to observe, and on the other hand, a sudden change in a certain data will interfere with the risk situation. Judgment, therefore, the normalized quality evaluation information after normalization processing is further counted according to the unit time period, such as averaging or weighted average, so as to obtain the comprehensive normalized quality evaluation information per unit time period, and then according to The change trend of the comprehensive normalized quality evaluation information corresponding to multiple unit time periods (that is, the normalized quality level change information) can prevent and control the risk of the target call chain, so that the quality fluctuation of the whole link can be more accurately analyzed Conduct detection and carry out targeted risk prevention and control.

In some variable implementations, the full link quality evaluation information corresponding to multiple target call request identifiers within a unit time period can be normalized to obtain the corresponding Normalized quality evaluation information; then, based on the normalized quality evaluation information corresponding to multiple target call request identifiers in a unit time period, the normalized quality level change information can be determined, that is, multiple normalized quality evaluation information in a unit time period can be obtained. The fluctuation of the quality assessment information over time; specifically, the above-mentioned unit time period may correspond to a quality assessment time window, for example, the unit time period is 1 hour, then, based on the above-mentioned implementation method, it is possible to obtain the Multiple normalized quality evaluation information in any one hour reflects the time fluctuation of the full link quality evaluation information, that is, the quality level change information; however, in order to improve the accuracy of the normalized quality level change information, The normalized quality assessment information corresponding to multiple unit time periods may be considered; specifically, the normalized quality level change information may include multiple normalized quality assessment information in each unit time period of the multiple unit time periods, It may also include comprehensive normalized quality evaluation information corresponding to each unit time period in multiple unit time periods, and the comprehensive normalized quality assessment information may be the mean value or weighted value of multiple normalized quality assessment information within a unit time period mean.

Among them, the above-mentioned normalized quality level change information can be presented in the form of charts, so that users can take targeted risk prevention and control measures after viewing. In addition, the above-mentioned normalized quality level change information can also be presented in numerical form. Compared with the risk prevention and control conditions set by the user, and selecting the appropriate risk prevention and control rules for risk prevention and control, all of them should be within the scope of protection of one or more embodiments of this specification, and will not be described here; optionally, the above The normalized quality level change information is used to display in the form of a trend graph on the visual interface.

Taking the above-mentioned risk prevention and control conditions as the early warning conditions as an example, on the basis of the above-mentioned embodiments, in some modification implementation methods, the above-mentioned risk prevention and control of the target call chain based on the normalized quality level change information includes:

If the above-mentioned normalized quality level change information meets the preset early warning conditions, a full link risk early warning information for the target call chain is issued;

If the above-mentioned normalized quality level change information does not meet the preset warning conditions, continue to determine the full link quality evaluation information of the target call chain for the next service processing call request.

Through this embodiment, the early warning conditions can be set in advance, and after the normalized quality level change information is obtained, it is compared with the preset early warning conditions, and if the early warning conditions are met, a full link risk for the target call chain is issued Early warning information reminds risk control personnel to carry out targeted risk prevention and control. If the warning condition is not met, continue to determine the full link quality evaluation information of the target call chain for the next service processing call request, so as to avoid the risk of missing the full link judgment.

In addition, in one or more embodiments of this specification, multiple service nodes are distributed across domains; the above step S106, based on the above-mentioned full-link quality evaluation information, performs risk prevention and control on the target call chain, which may include:

Based on the above-mentioned full-link quality assessment information and the single-point quality assessment information of the current service node among multiple service nodes, determine the risk identification information of the target service node; wherein, the above-mentioned current service node is a service node located in the current network domain, and the above-mentioned target The service node includes the current service node, the upstream service node of the current service node, or the downstream service node of the current service node;

Based on the above risk identification information, carry out risk prevention and control on the target call chain.

Considering that the above-mentioned cross-domain distribution means that multiple business nodes are located in different network domains, which are generally managed by different risk control personnel. Due to at least Separated by one reason, the current service node cannot know the quality changes of other service nodes. Based on this, based on the above-mentioned full-link quality assessment information and the single-point quality assessment information of the current service node, the current service node can Based on this, it is inferred that the upstream business node, downstream business node, or the current business node itself has risks. The specific inference strategy can be flexibly set according to actual needs, so as to realize the automatic detection of risks and automatically determine the corresponding risk prevention and control measures for risk prevention. control, such as sending early warning information to upstream business nodes or downstream business nodes that are inferred to be at risk, to help them carry out targeted risk prevention and control, and give full play to the advantages of full-link risk prevention and control, thereby improving the entire service architecture as a whole level of risk control.

For ease of understanding, the above risk control method will be further described with reference to a specific example.

Please refer to FIG. 3 , which shows a second schematic flowchart of the risk control method provided by one or more embodiments of this specification. In a specific example, the quality score of a single service node can be calculated by configuring the data compliance determination rule, namely Single-point quality assessment information, and then use the target call request identifier traceId in the whole link to determine the full link of a single business data flow, and then calculate the quality assessment information of the whole link, and then according to the data in the process of passing through multiple service nodes Risk control is carried out on the quality changes represented by the quality assessment information of the whole link in the network.

At the same time, for the evaluation method of the full link quality evaluation information, high-level evaluation rules can be configured to modify the quality impact weight of a single service node in the full link, reducing or ignoring the impact of certain service nodes on the full link quality evaluation information. , the main process is as follows:

(1) Obtain service nodes (x1, x2, x3, ...) and data packets, namely business data (c1, c2, c3, ...) by embedding points in the business system of the business data flow path.

(2) When the data packet c passes through the first service node x, generate the traceId of the data flow.

(3) For the service nodes (x1, x2, x3, ...), configure the data compliance determination rules (R1, R2, R3, ...) corresponding to the data packets (c1, c2, c3, ...).

(4) After the data packets (c1, c2, c3, ...) pass the data standard determination rules (R1, R2, R3, ...), the ratio of hit rules, that is, the single-point quality evaluation information (RES1, RES2, RES3, ...), wherein, the range of each RES is (0-1).

(5) Configure the weight of the service node in the full data link (Q1, Q2, Q3, ...), and the data quality score of the full link, that is, the full link quality evaluation information S, can be obtained as:

S = Q1 x RES1 + Q2 x RES2 + Q3 x RES3 . . .

The following uses a specific example to illustrate the process of calculating the full link quality assessment information S after configuring the data compliance determination rule R and the quality impact weight Q. Among them, the calculation example of single-point quality assessment information RES results:

Assume that the data message on a node X1, that is, the business data C1, is as follows:

[

{

"key1": 1,

"key2": 2

},

{

"key1": 11,

"key2":22

}

]

Assume that the data message on a certain node X2, that is, the business data C2, is as follows:

[

{

"key1": null,

"key2": null

},

{

"key1": null,

"key2": null

}

]

The configuration data compliance determination rule R1 is key1 and the corresponding length is [0,1] (indicating 0 to 1), and the configuration data compliance determination rule R2 is key2 and the corresponding result is not empty.

After passing the data compliance determination rule R1, the single-point quality evaluation information RES1 of the data message C1 is 0.5, indicating that half of the data meets the rule R1;

After passing the data compliance determination rule R2, the single-point quality evaluation information RES2 of the data message C2 is 0, indicating that no data matches the rule R2.

Configure the weight Q1 of the business node X1 to be 0.3, indicating that the importance of this node in the entire link of the data transfer is 30%, and configure the weight Q2 of the node X2 to be 0.7, indicating the importance of the node in the entire link of the data transfer. The degree is 70%.

After calculation, the full-link data quality S of this data is 0.15.

After a period of time, multiple data qualities (S1, S2, S3, . . . ) of the target call chain can be obtained.

The normalized display of (S1, S2, S3, ...) in the time period can represent the change of the whole data link in a period of time.

Based on the above specific examples, it can be seen that by adding the weight Q of the full link node, according to the target call request identifier traceId to connect the full link of a single data flow in series, and then normalize and display its score S after time accumulation, the data flow can be achieved From the perspective of the whole link, the quality of the evaluation data can improve the accuracy of the risk control of the target call chain in the risk control scenario.

The risk control method in one or more embodiments of this specification obtains multiple single-point quality assessment information of multiple service nodes in the target call chain, wherein each single-point quality assessment information includes The quality evaluation information of the business data generated by the invocation request. Different business data are obtained based on the target invocation request identifier; then, based on the above-mentioned multiple single-point quality assessment information, the whole link evaluation process is performed to obtain the corresponding value of the target invocation request identifier. Based on the above-mentioned full-link quality assessment information, the risk prevention and control of the target call chain can be carried out, so that the quality assessment information of each service node can be collected from the perspective of the whole link for comprehensive risk prevention and control, avoiding Due to the limitations of single-node risk control, missed judgments and misjudgments, etc., improve the accuracy of risk control.

Corresponding to the risk control methods described above in Figures 2 to 3, based on the same technical concept, one or more embodiments of this specification also provide a risk control device, and Figure 4 shows the risk control method provided by one or more embodiments of this specification. A schematic diagram of a module composition of a control device, which is used to implement the risk control method described in Figure 2, as shown in Figure 4, the device includes:

A single-point evaluation information acquisition module 402, configured to obtain multiple single-point quality evaluation information of multiple service nodes in the target call chain; wherein, each of the single-point quality evaluation information includes any one of the service nodes for business processing calls The quality evaluation information of the generated service data is requested, and the service data corresponding to different service nodes is obtained based on the same target invocation request identifier corresponding to the service processing invocation request.

The full link evaluation information determination module 404 is configured to perform full link evaluation processing based on the multiple single point quality evaluation information, and obtain the full link quality evaluation information corresponding to the target call request identifier.

The call chain risk control module 406 is configured to perform risk prevention and control on the target call chain based on the full link quality evaluation information.

Optionally, the single-point evaluation information acquisition module 402 is specifically used for:

Based on the target call request identifier generated for the service processing call request of the target call chain, query the service data corresponding to the target call request identifier from the call chain log corresponding to each service node of the target call chain;

For each of the service nodes, based on a target quality assessment method, perform quality assessment on the service data corresponding to the service node, and obtain single-point quality assessment information corresponding to the service node; wherein, the target quality assessment method is for The quality evaluation mode configured by the service node that generates the service data.

Optionally, the single-point evaluation information acquisition module 402 is also specifically used for:

Based on the target call request identifier generated for the service processing call request of the target call chain, query the single-point quality evaluation information corresponding to the target call request identifier from the call chain log corresponding to each service node of the target call chain ; Wherein, each said service node performs quality assessment on the service data generated by itself according to the target quality assessment method, and writes the respective call chain log after binding the single-point quality assessment information obtained by the assessment with the target call request identifier;

The single-point quality assessment information corresponding to the same target call request identifier is determined as multiple single-point quality assessment information of multiple service nodes in the target call chain.

Optionally, the single-point quality assessment information is obtained through at least one of the following quality assessment methods:

generating single-point quality evaluation information corresponding to the service node based on the matching result of the service data and the data compliance determination rule configured for the service node;

inputting the service data into a quality assessment model configured for the service node for quality assessment, and obtaining single-point quality assessment information corresponding to the service node;

Using the quality assessment algorithm configured for the service node to perform quality assessment on the service data to obtain single-point quality assessment information corresponding to the service node.

Optionally, the full link evaluation information determination module 404 is specifically configured to:

Acquiring the quality impact weight corresponding to each of the service nodes in the target call chain;

Based on the quality impact weight, the single-point quality evaluation information corresponding to each of the service nodes is weighted and fused to obtain the full-link quality evaluation information corresponding to the target call request identifier.

Optionally, the above-mentioned full-link evaluation information determination module 404 is further specifically used for:

Determine the quality weight distribution information corresponding to the target call chain according to the service category of the service processing call request corresponding to the target call request identifier; wherein, the quality weight distribution conditions corresponding to different service categories are different;

Based on the quality weight allocation information, determine the quality impact weight corresponding to each of the service nodes in the target call chain.

Optionally, the call chain risk control module 406 is specifically used for:

Generate normalized quality assessment information for the unit time period based on the full-link quality assessment information corresponding to the plurality of target invocation request identifiers in the unit time period;

Determining normalized quality level change information based on the normalized quality assessment information respectively corresponding to the plurality of unit time periods;

Risk prevention and control is performed on the target call chain based on the normalized quality level change information.

Optionally, the call chain risk control module 406 is further specifically used to:

If the normalized quality level change information meets the preset early warning condition, then issue full link risk early warning information for the target call chain;

If the normalized quality level change information does not meet the preset warning condition, continue to determine the full link quality evaluation information of the target call chain for the next service processing call request.

Optionally, multiple service nodes are distributed across domains; the call chain risk control module 406 is specifically used for:

Determine the risk identification information of the target service node based on the full-link quality assessment information and the single-point quality assessment information of the current service node among the plurality of service nodes; wherein, the current service node is a service located in the current network domain A node, where the target service node includes the current service node, an upstream service node of the current service node, or a downstream service node of the current service node;

Perform risk prevention and control on the target call chain based on the risk identification information.

The risk control device in one or more embodiments of this specification obtains multiple single-point quality assessment information of multiple service nodes in the target call chain, wherein each single-point quality assessment information includes The quality evaluation information of the business data generated by the invocation request. Different business data are obtained based on the target invocation request identifier; then, based on the above-mentioned multiple single-point quality assessment information, the whole link evaluation process is performed to obtain the corresponding value of the target invocation request identifier. The whole link quality assessment information, and then based on the above full link quality assessment information, carry out risk prevention and control on the target call chain. Therefore, it is possible to collect the quality assessment information of each business node from the perspective of the whole link for comprehensive risk prevention and control, avoiding missed judgments and misjudgments caused by the limitations of single-node risk control, and improving the accuracy of risk control .

It should be noted that the embodiment of the risk control device in this specification and the embodiment of the risk control method in this specification are based on the same inventive concept, so the specific implementation of this embodiment can refer to the implementation of the corresponding risk control method mentioned above, repeat The place will not be repeated.

Further, corresponding to the above methods shown in Figures 2 to 3, based on the same technical concept, one or more embodiments of this specification also provide a risk control device, which is used to implement the above risk control method, such as Figure 5 shows.

The risk control device may have relatively large differences due to different configurations or performances, and may include one or more processors 501 and memory 502, and one or more storage applications or data may be stored in the memory 502. Wherein, the storage 502 may be a short-term storage or a persistent storage. The application program stored in the memory 502 may include one or more modules (not shown), and each module may include a series of computer-executable instructions to the risk control device. Furthermore, the processor 501 may be configured to communicate with the memory 502, and execute a series of computer-executable instructions in the memory 502 on the risk control device. The risk control device may also include one or more power sources 503, one or more wired or wireless network interfaces 504, one or more input and output interfaces 505, one or more keyboards 506, and the like.

In a specific embodiment, the risk control device includes a memory, and one or more programs, wherein one or more programs are stored in the memory, and one or more programs may include one or more modules, and each Each module may include a series of computer-executable instructions in the risk control device, and configured to be executed by one or more processors. The one or more programs include computer-executable instructions for performing the following:

Obtain multiple single-point quality evaluation information of multiple service nodes in the target call chain; wherein, each of the single-point quality evaluation information includes the quality evaluation information of the service data generated by any of the service nodes for the service processing call request , the service data corresponding to the different service nodes is obtained based on the same target invocation request identifier corresponding to the service processing invocation request;

performing full-link assessment processing based on the plurality of single-point quality assessment information, and obtaining full-link quality assessment information corresponding to the target invocation request identifier;

Risk prevention and control is performed on the target call chain based on the full link quality assessment information.

The risk control device in one or more embodiments of this specification first obtains multiple single-point quality assessment information of multiple service nodes in the target call chain, where each single-point quality assessment information includes The quality evaluation information of the business data generated by the invocation request. Different business data are obtained based on the target invocation request identifier; then, based on the above-mentioned multiple single-point quality assessment information, the whole link evaluation process is performed to obtain the corresponding value of the target invocation request identifier. The whole link quality assessment information, and then based on the above full link quality assessment information, carry out risk prevention and control on the target call chain. It can be seen that, through the risk control device in one or more embodiments of this specification, the quality assessment information of each service node can be collected from the perspective of the whole link to carry out comprehensive risk prevention and control, avoiding the risk caused by the limitations of single node risk control. Omissions, misjudgments, etc., to improve the accuracy of risk control.

It should be noted that the embodiment of risk control equipment in this specification and the embodiment of risk control method in this specification are based on the same inventive concept, so the specific implementation of this embodiment can refer to the implementation of the corresponding risk control method mentioned above, repeat The place will not be repeated.

Further, corresponding to the methods shown in FIGS. 2 to 3 above, based on the same technical concept, one or more embodiments of this specification also provide a storage medium for storing computer-executable instructions. A specific implementation In an example, the storage medium can be a USB flash drive, an optical disc, a hard disk, etc., and the computer-executable instructions stored in the storage medium can realize the following process when executed by the processor:

Obtain multiple single-point quality evaluation information of multiple service nodes in the target call chain; wherein, each of the single-point quality evaluation information includes the quality evaluation information of the service data generated by any of the service nodes for the service processing call request , the service data corresponding to the different service nodes is obtained based on the same target invocation request identifier corresponding to the service processing invocation request;

performing full-link assessment processing based on the plurality of single-point quality assessment information, and obtaining full-link quality assessment information corresponding to the target invocation request identifier;

Risk prevention and control is performed on the target call chain based on the full link quality assessment information.

When the computer-executable instructions stored in the storage medium in one or more embodiments of this specification are executed by the processor, firstly obtain multiple single-point quality evaluation information of multiple service nodes in the target call chain, wherein each single-point The quality evaluation information includes the quality evaluation information of the business data generated by any business node for the business processing call request. Different business data is obtained based on the target call request identification; Through the road evaluation process, the full link quality assessment information corresponding to the target call request identifier is obtained, and then based on the above full link quality assessment information, the risk prevention and control of the target call chain is carried out. It can be seen that, through the storage medium in one or more embodiments of this specification, the quality evaluation information of each service node can be collected from the perspective of the whole link to carry out comprehensive risk prevention and control, and avoid single-node risk control due to limitations. Missed judgments, misjudgments, etc., to improve the accuracy of risk control.

It should be noted that the embodiment of the storage medium in this specification and the embodiment of the risk control method in this specification are based on the same inventive concept, so the specific implementation of this embodiment can refer to the implementation of the corresponding risk control method described above, and repeat I won't repeat them here.

The foregoing describes specific embodiments of this specification. Other implementations are within the scope of the following claims. In some cases, the actions or steps recited in the claims can be performed in an order different from that in the embodiments and still achieve desirable results. In addition, the processes depicted in the accompanying figures do not necessarily require the particular order shown, or sequential order, to achieve desirable results. Multitasking and parallel processing are also possible or may be advantageous in certain embodiments.

In the 1990s, the improvement of a technology can be clearly distinguished as an improvement in hardware (for example, improvements in circuit structures such as diodes, transistors, and switches) or improvements in software (improvement in method flow). However, with the development of technology, the improvement of many current method flows can be regarded as the direct improvement of the hardware circuit structure. Designers almost always get the corresponding hardware circuit structure by programming the improved method flow into the hardware circuit. Therefore, it cannot be said that the improvement of a method flow cannot be realized by hardware physical modules. For example, a Programmable Logic Device (Programmable Logic Device, PLD) (such as a Field Programmable Gate Array (Field Programmable GateArray, FPGA)) is such an integrated circuit, and its logic function is determined by programming the device by a user. It is programmed by the designer to "integrate" a digital system on a PLD, instead of asking a chip manufacturer to design and make a dedicated integrated circuit chip. Moreover, nowadays, instead of making integrated circuit chips by hand, this kind of programming is mostly realized by "logic compiler (logic compiler)" software, which is similar to the software compiler used when writing programs. The original code of the computer must also be written in a specific programming language, which is called a hardware description language (Hardware Description Language, HDL), and there is not only one kind of HDL, but many kinds, such as ABEL (Advanced Boolean Expression Language) , AHDL (Altera Hardware Description Language), Confluence, CUPL (Cornell University Programming Language), HD Cal, JHDL (Java Hardware Description Language), Lava, Lola, My HDL, PALASM, RHDL (Ruby Hardware Description Language), etc., are currently the most commonly used The most popular are VHDL (Very-High-Speed Integrated Circuit Hardware Description Language) and Verilog. It should also be clear to those skilled in the art that only a little logical programming of the method flow in the above-mentioned hardware description languages and programming into an integrated circuit can easily obtain a hardware circuit for realizing the logic method flow.

The controller may be implemented in any suitable way, for example the controller may take the form of a microprocessor or processor and a computer readable medium storing computer readable program code (such as software or firmware) executable by the (micro)processor , logic gates, switches, Application Specific Integrated Circuit (ASIC), programmable logic controllers, and embedded microcontrollers, 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 memory's control logic. Those skilled in the art also know that, in addition to realizing the controller in a purely computer-readable program code mode, it is entirely possible to make the controller use logic gates, switches, application-specific integrated circuits, programmable logic controllers, and embedded The same function can be realized in the form of a microcontroller or the like. Therefore, such a controller can be regarded as a hardware component, and the devices included in it for realizing various functions can also be regarded as structures within the hardware component. Or even, means for realizing various functions can be regarded as a structure within both a software module realizing a method and a hardware component.

The systems, devices, modules, or units described in the above embodiments can be specifically implemented by computer chips or entities, or by products with certain functions. A typical implementing 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 Combinations of any of these devices.

For the convenience of description, when describing the above devices, functions are divided into various units and described separately. Of course, the functions of each unit can be implemented in one or more software and/or hardware when implementing one or more of the present description.

Those skilled in the art should understand that one or more embodiments of the present specification may be provided as a method, system, or computer program product. Accordingly, one or more of the present descriptions may take the form of an entirely hardware embodiment, an entirely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, one or more of the present description may take the form of a computer program product embodied on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) having computer-usable program code embodied therein. form.

One or more of this specification is described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems), and computer program products according to one or more embodiments of this specification. It should be understood that each procedure and/or block in the flowchart and/or block diagram, and a combination of procedures and/or blocks in the flowchart and/or block diagram can be realized by computer program instructions. These computer program instructions may be provided to a general purpose computer, special purpose computer, embedded processor, or processor of other programmable data processing equipment to produce a machine such that the instructions executed by the processor of the computer or other programmable data processing equipment produce a An apparatus for realizing the functions specified in one or more procedures of the flowchart and/or one or more blocks of the block diagram.

These computer program instructions may also be stored in a computer-readable memory capable of directing a computer or other programmable data processing apparatus to operate in a specific manner, such that the instructions stored in the computer-readable memory produce an article of manufacture comprising instruction means, the instructions The device realizes the function specified in one or more procedures of the flowchart and/or one or more blocks of the block diagram.

These computer program instructions can also be loaded onto a computer or other programmable data processing device, causing a series of operational steps to be performed on the computer or other programmable device to produce a computer-implemented process, thereby The instructions provide steps for implementing the functions specified in the flow chart or blocks of the flowchart and/or the block or blocks of the block diagrams.

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

Memory may include non-permanent storage in computer readable media, in the form of random access memory (RAM) and/or nonvolatile memory such as read only memory (ROM) or flash RAM. Memory is an example of computer readable media.

Computer-readable media, including both permanent and non-permanent, removable and non-removable media, can be implemented by any method or technology for storage of information. Information may be computer readable instructions, data structures, modules of a program, 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 Disc Read-Only Memory (CD-ROM), Digital Versatile Disc (DVD) or other optical storage, Magnetic tape cartridge, tape disk storage or other magnetic storage device or any other non-transmission medium that can be used to store information that can be accessed by a computing device. As defined herein, computer-readable media excludes transitory computer-readable media, such as modulated data signals and carrier waves.

It should also be noted that the term "comprises", "comprises" or any other variation thereof is intended to cover a non-exclusive inclusion such that a process, method, article, or apparatus comprising a set of elements includes not only those elements, but also includes Other elements not expressly listed, or elements inherent in the process, method, commodity, or apparatus are also included. Without further limitations, an element defined by the phrase "comprising a ..." does not exclude the presence of additional identical elements in the process, method, article or apparatus comprising said element.

Those skilled in the art should understand that one or more embodiments of the present specification may be provided as a method, system or computer program product. Accordingly, one or more of the present descriptions may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, one or more of the present description may take the form of a computer program product embodied on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) having computer-usable program code embodied therein. form.

One or more of the present description may be described in the general context of computer-executable instructions, such as program modules, being executed by a computer. Generally, program modules include routines, programs, objects, components, data structures, etc. that perform particular tasks or implement particular abstract data types. One or more of the present description may also be practiced in distributed computing environments where tasks are performed by remote processing devices that are linked through a communications network. In a distributed computing environment, program modules may be located in both local and remote computer storage media including storage devices.

Each embodiment in this specification is described in a progressive manner, the same and similar parts of each embodiment 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 for relevant parts, refer to part of the description of the method embodiment.

The above descriptions are only one or more embodiments of this specification, and are not intended to limit one or more of this specification. Various modifications and changes will occur to one or more of this description for those skilled in the art. Any modification, equivalent replacement, improvement, etc. made within one or more spirits and principles of this specification shall be included within the scope of one or more claims of this specification.

Claims (12)

1. A risk control method, comprising:

acquiring a plurality of single-point quality evaluation information of a plurality of service nodes in a target call chain; wherein, each single-point quality evaluation information comprises quality evaluation information of service data generated by any service node aiming at a service processing call request, and the service data corresponding to different service nodes are acquired based on the same target call request identifier corresponding to the service processing call request;

performing full link evaluation processing based on the plurality of single point quality evaluation information to obtain full link quality evaluation information corresponding to the target call request identifier;

and performing risk prevention and control on the target call chain based on the full link quality evaluation information.

2. The method of claim 1, wherein the obtaining the plurality of single point quality assessment information for the plurality of service nodes in the target call chain comprises:

inquiring service data corresponding to a target call request identifier from a call chain log corresponding to each service node of a target call chain based on the target call request identifier generated by a service processing call request aiming at the target call chain;

for each service node, performing quality evaluation on service data corresponding to the service node based on a target quality evaluation mode to obtain single-point quality evaluation information corresponding to the service node; the target quality evaluation mode is a quality evaluation mode configured for a service node generating the service data.

3. The method of claim 1, wherein the obtaining the plurality of single point quality assessment information for the plurality of service nodes in the target call chain comprises:

inquiring single-point quality evaluation information corresponding to a target call request identifier from a call chain log corresponding to each service node of a target call chain based on the target call request identifier generated by a service processing call request aiming at the target call chain; each service node carries out quality evaluation on service data generated by the service node according to a target quality evaluation mode, and writes single-point quality evaluation information obtained by evaluation into respective call chain logs after binding with a target call request identifier;

and determining the single-point quality evaluation information corresponding to the same target call request identifier as a plurality of single-point quality evaluation information of a plurality of service nodes in a target call chain.

4. A method according to claim 2 or 3, wherein the single point quality assessment information is obtained by means of at least one of the following quality assessment methods:

generating single-point quality evaluation information corresponding to the service node based on a matching result of the service data and a data standard reaching judgment rule configured for the service node;

Inputting the service data into a quality evaluation model configured for the service node for quality evaluation to obtain single-point quality evaluation information corresponding to the service node;

and carrying out quality evaluation on the service data by using a quality evaluation algorithm configured for the service node to obtain single-point quality evaluation information corresponding to the service node.

5. The method of claim 1, wherein the performing the full link quality assessment process based on the plurality of single point quality assessment information to obtain full link quality assessment information corresponding to the target call request identifier comprises:

acquiring a quality influence weight corresponding to each service node in the target call chain;

and carrying out weighted fusion on the single-point quality evaluation information corresponding to each service node based on the quality influence weight to obtain the full-link quality evaluation information corresponding to the target call request identifier.

6. The method of claim 5, wherein the obtaining the quality impact weight corresponding to each service node in the target call chain comprises:

determining quality weight distribution information corresponding to the target call chain according to the service class of the service processing call request corresponding to the target call request identifier; wherein, the quality weight distribution conditions corresponding to different service categories are different;

And determining the quality influence weight corresponding to each service node in the target call chain based on the quality weight distribution information.

7. The method of claim 1, wherein the risk prevention of the target call chain based on the full link quality assessment information comprises:

generating normalized quality evaluation information of a unit time period based on all link quality evaluation information respectively corresponding to a plurality of target call request identifiers in the unit time period;

determining normalized quality level change information based on normalized quality assessment information corresponding to each of the plurality of unit time periods;

and performing risk prevention and control on the target call chain based on the normalized quality level change information.

8. The method of claim 7, wherein the risk prevention of the target call chain based on the normalized quality level change information comprises:

if the normalized quality level change information accords with a preset early warning condition, sending out full-link risk early warning information aiming at the target call chain;

if the normalized quality level change information does not meet the preset early warning condition, continuing to determine the full link quality evaluation information of the target call chain for the next service processing call request.

9. The method of claim 1, wherein a plurality of the service nodes are distributed across a domain; the risk prevention and control of the target call chain based on the full link quality evaluation information comprises:

determining risk identification information of a target service node based on the full link quality evaluation information and single-point quality evaluation information of a current service node in the plurality of service nodes; the target service node comprises the current service node, an upstream service node of the current service node or a downstream service node of the current service node;

and performing risk prevention and control on the target call chain based on the risk identification information.

10. A risk control device comprising:

the single-point evaluation information acquisition module acquires a plurality of single-point quality evaluation information of a plurality of service nodes in a target call chain; wherein, each single-point quality evaluation information comprises quality evaluation information of service data generated by any service node aiming at a service processing call request, and the service data corresponding to different service nodes are acquired based on the same target call request identifier corresponding to the service processing call request;

The full link evaluation information determining module is used for carrying out full link evaluation processing based on the plurality of single-point quality evaluation information to obtain full link quality evaluation information corresponding to the target call request identifier;

and calling a chain wind control module, which is used for performing risk prevention and control on the target calling chain based on the full link quality evaluation information.

11. A risk control device comprising:

a processor; and

a memory arranged to store computer executable instructions that, when executed, cause the processor to:

acquiring a plurality of single-point quality evaluation information of a plurality of service nodes in a target call chain; wherein, each single-point quality evaluation information comprises quality evaluation information of service data generated by any service node aiming at a service processing call request, and the service data corresponding to different service nodes are acquired based on the same target call request identifier corresponding to the service processing call request;

performing full link evaluation processing based on the plurality of single point quality evaluation information to obtain full link quality evaluation information corresponding to the target call request identifier;

and performing risk prevention and control on the target call chain based on the full link quality evaluation information.

12. A storage medium storing computer executable instructions that when executed by a processor implement the method of:

acquiring a plurality of single-point quality evaluation information of a plurality of service nodes in a target call chain; wherein, each single-point quality evaluation information comprises quality evaluation information of service data generated by any service node aiming at a service processing call request, and the service data corresponding to different service nodes are acquired based on the same target call request identifier corresponding to the service processing call request;

performing full link evaluation processing based on the plurality of single point quality evaluation information to obtain full link quality evaluation information corresponding to the target call request identifier;

and performing risk prevention and control on the target call chain based on the full link quality evaluation information.