Supply chain graph model construction method and device and storage medium

Abstract

The invention provides a supply chain graph model construction method and device and a storage medium, relates to the technical field of artificial intelligence, and can enable a constructed supply chain graph model to express a complex relationship between nodes in a supply chain. The method comprises the following steps: acquiring supply chain information of target equipment, wherein the supply chain information comprises information of a plurality of nodes related to a supply chain of the target equipment; determining an association relationship among the plurality of nodes based on the supply chain information; and constructing a supply chain graph model of the target equipment based on the association relationship among the plurality of nodes.

Description

Technical Field

[0001] The present application relates to the field of artificial intelligence technology, and in particular to a supply chain graph model construction method, device and storage medium. Background Art

[0002] In order to display and manage the supply dependencies of data centers and build a detailed data center supply chain graph model for enterprises, how to form a complete supply chain graph model becomes a key issue.

[0003] At present, the general supply chain graph model only considers the connection relationship between customers and complete equipment suppliers, and is unable to comprehensively and systematically integrate the multi-source heterogeneous data of the data center. In the process of building the supply chain graph model, data fragmentation is serious, and it is unable to fully express the complex relationship between the nodes in the supply chain, making it difficult to form a complete supply chain view. Summary of the invention

[0004] The present application provides a supply chain graph model construction method, device and storage medium, which can enable the constructed supply chain graph model to express the complex relationship between nodes in the supply chain.

[0005] In order to achieve the above objectives, this application adopts the following technical solutions:

[0006] In a first aspect, the present application provides a method for constructing a supply chain graph model, the method comprising: obtaining supply chain information of a target device, the supply chain information comprising information of multiple nodes related to the supply chain of the target device; based on the supply chain information, determining the association relationship between the multiple nodes; and based on the association relationship between the multiple nodes, constructing a supply chain graph model of the target device.

[0007] In a possible implementation, the node includes at least one of the following: a supplier node; a device node; a component node; a regional node; and a service node.

[0008] In a possible implementation, the association relationship includes at least one of the following: a supply relationship; a composition relationship; a location relationship; and an application relationship.

[0009] In one possible implementation, a supply chain graph model of a target device is constructed based on the association relationship between multiple nodes, including: determining a central node and multiple subordinate nodes of the central node among the multiple nodes according to the association relationship between the multiple nodes; and constructing a supply chain graph model of the target device according to the hierarchical relationship between the central node and the multiple subordinate nodes.

[0010] In a possible implementation, the central node is a device node, and the subordinate nodes include one or more of a supplier node, a component node, a regional node, and a service node.

[0011] In a possible implementation, the method also includes: determining a risk transfer coefficient of a supplier for any one of multiple suppliers of a target device, the risk transfer coefficient being used to reflect the degree of impact on the supply chain of the target device when an abnormality occurs in the supplier; determining monitoring priorities of multiple suppliers based on the risk transfer coefficient of each supplier, and monitoring multiple suppliers according to the monitoring priorities.

[0012] In one possible implementation, determining the risk transfer coefficient of a supplier includes: obtaining the number of transmission paths between the supplier node and the business node corresponding to the supplier in the supply chain graph model, the supplier's risk level weight, and the risk reachability probability; wherein the number of transmission paths is the total number of transmission paths between the supplier node and the business node, and the risk reachability probability is the probability that the supplier's risk will have an actual impact on the business node; determining the supplier's risk transfer coefficient based on the number of transmission paths, the risk level weight, and the risk reachability probability.

[0013] In a second aspect, the present application provides a supply chain graph model construction device, which includes: a communication unit and a processing unit; the communication unit is used to obtain supply chain information of a target device, the supply chain information includes information of multiple nodes related to the supply chain of the target device; the processing unit is used to determine the association relationship between multiple nodes based on the supply chain information; the processing unit is also used to construct a supply chain graph model of the target device based on the association relationship between multiple nodes.

[0014] In a possible implementation, the node includes at least one of the following: a supplier node; a device node; a component node; a regional node; and a service node.

[0015] In a possible implementation, the association relationship includes at least one of the following: a supply relationship; a composition relationship; a location relationship; and an application relationship.

[0016] In one possible implementation, the processing unit is further used to determine a central node among the multiple nodes and multiple subordinate nodes of the central node based on the association relationship between the multiple nodes; the processing unit is further used to construct a supply chain graph model of the target device based on the hierarchical relationship between the central node and the multiple subordinate nodes.

[0017] In a possible implementation, the central node is a device node, and the subordinate nodes include one or more of a supplier node, a component node, a regional node, and a service node.

[0018] In a possible implementation, for any one of the multiple suppliers of the target device, the processing unit is further used to determine the risk transfer coefficient of the supplier, where the risk transfer coefficient is used to reflect the degree of impact on the supply chain of the target device when an abnormality occurs in the supplier; the processing unit is also used to determine the monitoring priority of the multiple suppliers based on the risk transfer coefficient of each supplier, and monitor the multiple suppliers according to the monitoring priority.

[0019] In a possible implementation, the communication unit is further used to obtain the number of transmission paths between the supplier node and the business node corresponding to the supplier in the supply chain graph model, the supplier's risk level weight and the risk reachability probability; wherein the number of transmission paths is the total number of transmission paths between the supplier node and the business node, and the risk reachability probability is the probability that the supplier's risk has an actual impact on the business node; the processing unit is further used to determine the supplier's risk transmission coefficient based on the number of transmission paths, the risk level weight and the risk reachability probability.

[0020] In a third aspect, the present application provides a supply chain graph model building device, the device comprising: a processor and a communication interface; the communication interface and the processor are coupled, and the processor is used to run a computer program or instructions to implement the supply chain graph model building method as described in the first aspect and any possible implementation method of the first aspect.

[0021] In a fourth aspect, the present application provides a computer-readable storage medium, which stores instructions. When the instructions are executed on a terminal, the terminal executes the supply chain graph model construction method described in the first aspect and any possible implementation method of the first aspect.

[0022] In a fifth aspect, the present application provides a computer program product comprising instructions, which, when the computer program product is run on a supply chain graph model building device, enables the supply chain graph model building device to execute the supply chain graph model building method as described in the first aspect and any possible implementation of the first aspect.

[0023] In a sixth aspect, the present application provides a chip, comprising a processor and a communication interface, wherein the communication interface and the processor are coupled, and the processor is used to run a computer program or instructions to implement the supply chain graph model construction method as described in the first aspect and any possible implementation method of the first aspect.

[0024] Specifically, the chip provided in the present application also includes a memory for storing computer programs or instructions.

[0025] The above technical solution brings at least the following beneficial effects: obtaining the supply chain information of the target device, determining the association relationship between multiple nodes based on the supply chain information, and constructing a supply chain graph model of the target device based on the association relationship between multiple nodes. In other words, the supply chain graph model construction method provided by the present application is to construct a supply chain graph model based on the association relationship between multiple nodes, and the supply chain graph model constructed can express the complex relationship between the nodes in the supply chain. BRIEF DESCRIPTION OF THE DRAWINGS

[0026] Figure 1 A schematic diagram of the composition of a supply chain graph model building device provided in an embodiment of the present application;

[0027] Figure 2 A flow chart of a supply chain graph model construction method provided in an embodiment of the present application;

[0028] Figure 3 A flowchart of another supply chain graph model construction method provided in an embodiment of the present application;

[0029] Figure 4 A schematic diagram of a supply chain graph model provided in an embodiment of the present application;

[0030] Figure 5 A flowchart of another supply chain graph model construction method provided in an embodiment of the present application;

[0031] Figure 6 A schematic diagram of another supply chain graph model provided in an embodiment of the present application;

[0032] Figure 7 A schematic diagram of the structure of a supply chain graph model building device provided in an embodiment of the present application. DETAILED DESCRIPTION

[0033] The supply chain graph model construction method, device and storage medium provided in the embodiments of the present application are described in detail below in conjunction with the accompanying drawings.

[0034] The term "and / or" in this article is merely a description of the association relationship of associated objects, indicating that three relationships may exist. For example, A and / or B can mean: A exists alone, A and B exist at the same time, and B exists alone.

[0035] The terms "first" and "second" and the like in the specification and drawings of this application are used to distinguish different objects, or to distinguish different processing of the same object, rather than to describe a specific order of objects.

[0036] In addition, the terms "including" and "having" and any variations thereof mentioned in the description of the present application are intended to cover non-exclusive inclusions. For example, a process, method, system, product or device comprising a series of steps or units is not limited to the listed steps or units, but may optionally include other steps or units that are not listed, or may optionally include other steps or units that are inherent to these processes, methods, products or devices.

[0037] It should be noted that, in the embodiments of the present application, words such as "exemplary" or "for example" are used to indicate examples, illustrations or descriptions. Any embodiment or design described as "exemplary" or "for example" in the embodiments of the present application should not be interpreted as being more preferred or more advantageous than other embodiments or designs. Specifically, the use of words such as "exemplary" or "for example" is intended to present related concepts in a specific way.

[0038] In the description of the present application, unless otherwise specified, “plurality” means two or more.

[0039] In order to display and manage the supply dependencies of data centers and build a detailed data center supply chain graph model for enterprises, how to form a complete supply chain graph model becomes a key issue. The following introduces relevant experiences in other fields.

[0040] In the financial industry, for example, in risk control, marketing, or auditing, by building enterprise association maps or capital flow maps, in-depth analysis and monitoring of complex financial relationships are achieved. In the medical field, for example, in disease diagnosis, drug development, or patient management, by building disease-symptom, drug-disease, or patient-treatment relationship maps, comprehensive integration and intelligent analysis of medical information are achieved. In the manufacturing industry, by building supply chain relationship maps, comprehensive monitoring and management of suppliers, manufacturers, distributors, and other links are achieved.

[0041] The traditional data center supply chain graph model only considers the connection relationship between customers and complete equipment suppliers, ignoring the supply relationship of multiple components of the complete equipment and the dependency of the complete equipment in the customer's usage scenario. It is therefore unable to comprehensively and systematically integrate multi-source heterogeneous data such as data center software and hardware product equipment supply information, data center deployment areas, and business scenarios, and is unable to fully express the complex relationship between complete equipment, components, suppliers, and business scenarios. For example, multi-level and multi-path associations and dependencies.

[0042] In other words, the traditional supply chain graph model construction process suffers from serious data fragmentation, making it difficult to form a complete supply chain view. As a result, the relationships in the supply chain graph model are not fully expressed and the relationship reasoning ability is insufficient, making it impossible to deeply explore the potential value in the graph model.

[0043] In view of this, an embodiment of the present application provides a method for constructing a supply chain graph model, the method comprising: obtaining supply chain information of a target device, determining the association relationship between multiple nodes based on the supply chain information, and constructing a supply chain graph model of the target device based on the association relationship between the multiple nodes. In other words, the supply chain graph model construction method provided by the present application is to construct a supply chain graph model based on the association relationship between multiple nodes, and the supply chain graph model constructed can express the complex relationship between the nodes in the supply chain.

[0044] The application scenarios of the embodiments of the present application are not limited. The business scenarios described in the embodiments of the present application are intended to more clearly illustrate the technical solutions of the embodiments of the present application, and do not constitute a limitation on the technical solutions provided by the embodiments of the present application. It is known to those skilled in the art that with the evolution of network architecture and the emergence of new business scenarios, the technical solutions provided by the embodiments of the present application are also applicable to similar technical problems.

[0045] For example, Figure 1 A schematic diagram of the composition of a supply chain graph model building device 10 provided in an embodiment of the present application, the supply chain graph model building device 10 may include a processor 101 and a bus 102.

[0046] Furthermore, the supply chain graph model building device 10 may also include a communication interface 103 and a memory 104. The processor 101, the memory 104 and the communication interface 103 may be connected via a bus 102.

[0047] The processor 101 is a central processing unit (CPU), a general processor, a network processor (NP), a digital signal processor (DSP), a microprocessor, a microcontroller, a programmable logic device (PLD), or any combination thereof. The processor 101 may also be other devices with processing functions, such as circuits, devices, or software modules, without limitation.

[0048] The bus 102 is used to transmit information between the components included in the supply chain graph model building device 10.

[0049] The communication interface 103 is used to communicate with other devices or other communication networks. The other communication networks may be Ethernet, radio access network (RAN), wireless local area network (WLAN), etc. The communication interface 103 may be a module, a circuit, a communication interface or any device capable of realizing communication.

[0050] The memory 104 is used to store instructions, where the instructions may be computer programs.

[0051] The memory 104 may be a read-only memory (ROM) or other types of static storage devices that can store static information and / or instructions, or a random access memory (RAM) or other types of dynamic storage devices that can store information and / or instructions, or an electrically erasable programmable read-only memory (EEPROM), a compact disc read-only memory (CD-ROM) or other optical disc storage, optical disc storage (including compressed optical disc, laser disc, optical disc, digital versatile disc, Blu-ray disc, etc.), magnetic disk storage media or other magnetic storage devices, etc., without limitation.

[0052] It should be noted that the memory 104 can exist independently of the processor 101, or it can be integrated with the processor 101. The memory 104 can be used to store instructions or program codes or some data, etc. The memory 104 can be located in the supply chain graph model building device 10, or it can be located outside the supply chain graph model building device 10, without limitation. The processor 101 is used to execute the instructions stored in the memory 104 to implement the supply chain graph model building method provided in the following embodiments of the present application.

[0053] In an example, the processor 101 may include one or more CPUs, for example, CPU0 and CPU1 (not shown in the figure).

[0054] As an optional implementation, the supply chain graph model building device 10 includes multiple processors.

[0055] As an optional implementation, the supply chain graph model building device 10 also includes an output device and an input device. For example, the input device is a keyboard, a mouse, a microphone, a joystick, and the output device is a display screen, a speaker, and the like.

[0056] It should be noted that the supply chain graph model building device 10 can be a desktop computer, a portable computer, a network server, a mobile phone, a tablet computer, a wireless terminal, an embedded device, a chip system or a Figure 2 In addition, Figure 2 The composition shown in the Figure 1 as well as Figure 2 The limitations of each device in Figure 2 In addition to the parts shown, Figure 1 as well as Figure 2 The various devices in the drawings may include more or fewer components than shown, or combine certain components, or arrange the components differently.

[0057] In the embodiment of the present application, the chip system may be composed of a chip, or may include a chip and other discrete devices.

[0058] In addition, the actions, terms, etc. involved in the various embodiments of the present application can refer to each other without limitation. The message name or parameter name in the message exchanged between the various devices in the embodiments of the present application is only an example, and other names can also be used in the specific implementation without limitation.

[0059] The following is a description of the supply chain graph model construction method provided by the embodiment of the present application in conjunction with the accompanying drawings. Among them, the actions, terms, etc. involved in the various embodiments of the present application can refer to each other without limitation. The message name or parameter name in the message exchanged between the various devices in the embodiment of the present application is only an example, and other names can also be used in the specific implementation without limitation. The actions involved in the various embodiments of the present application are only an example, and other names can also be used in the specific implementation, such as: "included in" in the embodiment of the present application can also be replaced by "carried on" or "carried in", etc.

[0060] It should be noted that the executing entity of the technical solution of this application is not limited.

[0061] like Figure 2 As shown, the embodiment of the present application proposes a method for constructing a supply chain graph model, the method comprising:

[0062] S201. Obtain supply chain information of a target device.

[0063] The supply chain information includes information of multiple nodes related to the supply chain of the target device. The target device refers to the hardware device in the data center.

[0064] Exemplarily, the type of the target device may be a server, switch, router or firewall, etc. The target device has a device model, that is, a product number of the device, which is specified by the device supplier and may be composed of English letters, numbers and special symbols.

[0065] Exemplarily, the supply chain information of the target device may include supplier information, component information, region information, and business information.

[0066] The supplier information includes the name of the device supplier and the name of the component supplier. The device supplier refers to the sales manufacturer of the target device. The component supplier refers to the provider of the hardware components and software components that make up the target device. The hardware component supplier is an entity supplier. The software component supplier includes two forms: an entity supplier and an open source service provider.

[0067] Component information includes information about the hardware components and software components that make up the target device. Hardware component information includes hardware component type and hardware component model. The hardware component type can be CPU, network card, memory, hard disk or power supply, etc. The hardware component model refers to the product model of the hardware component, which is specified by the supplier of the hardware component and can be composed of English letters, numbers and special symbols. Software component information includes software component type and software component name and version number. The software component type can be operating system or database, etc. The software component name and version number refer to the product name and version number of the software component. For example, the name and version number of the operating system can be CentOS 7.9.2009.

[0068] The regional information includes the deployment area name and regional extension information. The deployment area name refers to the name of the computer room or data center where the target device is located, for example, North China 001 computer room or Langfang data center. Regional extension information may include geographic location information or network environment information. Among them, geographic location information refers to the geographic location of the computer room or data center where the target device is located, for example, the province name or city name. Network environment information refers to key indicator information such as network architecture, bandwidth or latency of the computer room or data center where the target device is located.

[0069] Business information includes business type, business description information, and business system name. Business type refers to the type of business system carried by the computer room or data center where the target device is located, such as office, management, or production. Business description information refers to information such as business requirements, performance indicators, or security requirements of the business system. Business system name refers to the name of a specific software application system. For example, the names of office business systems include unified portal systems, email systems, integrated office systems, or official document management platforms.

[0070] It should be noted that the supply chain information of the above-mentioned target equipment can be obtained from asset management systems, purchase lists, data center architecture deployment design plans, Internet information retrieval results, enterprise business planning plans and enterprise application management platforms.

[0071] Exemplarily, the above-mentioned multiple nodes related to the supply chain of the target device may include at least one of the following: a supplier node, a device node, a component node, a regional node or a business node. Among them, the supplier node includes a device supplier node and a component supplier node. The attribute information of the device supplier node includes the device supplier name. The attribute information of the component supplier node includes the component supplier name. The attribute information of the device node includes the device type and the device model. The component node includes a hardware component node and a software component node. The attribute information of the hardware component node includes the hardware component type and the hardware component model, and the attribute information of the software component node includes the software component type software and the software component name and version number. The attribute information of the regional node includes the deployment area name. The attribute information of the business node includes the business type and the business system name. In addition, each node has a unique node identifier.

[0072] Optionally, the attribute information of the area node may further include area extension information. The attribute information of the service node may further include service description information.

[0073] S202: Determine the association relationship between multiple nodes based on the supply chain information.

[0074] In a possible implementation, supply chain information is identified to obtain multiple nodes and attribute information corresponding to the nodes, and the association relationship between the multiple nodes is determined based on the supply chain information.

[0075] Exemplarily, the above-mentioned association relationship may include at least one of the following: supply relationship, composition relationship, location relationship or application relationship. Among them, the supply relationship refers to the association relationship between the supplier node and the device node or the association relationship between the supplier node and the component node, indicating that the supplier supplies the device or component. The composition relationship refers to the association relationship between the device node and the component node, indicating that the device is composed of components. The location relationship refers to the association relationship between the device node and the regional node, indicating that the device is located in the region. The application relationship refers to the association relationship between the regional node and the business node, indicating that the region carries the operation and maintenance of the business system.

[0076] Illustratively, Table 1 provides an exemplary description of determining supply chain information as multiple nodes and association relationships between the multiple nodes.

[0077] Table 1

[0078]

[0079]

[0080] S203: construct a supply chain graph model of the target device based on the association relationship between multiple nodes.

[0081] In one possible implementation, the device node is determined based on the association relationship between multiple nodes, the device node is used as the central node, and multiple subordinate nodes of the central node are determined. According to the hierarchical relationship between the central node and multiple subordinate nodes, a supply chain graph model of the target device is constructed. For details, please refer to the following Figure 3 The embodiments described are not described in detail here.

[0082] In another possible implementation, easily recognizable icons, shapes or colors are used to represent multiple nodes. According to the association relationship between the multiple nodes, the nodes with the association relationship are connected by lines, and the corresponding relationship type is displayed to obtain a supply chain graph model of the target device.

[0083] In the supply chain graph model construction method provided by the present application, the supply chain information of the target device is obtained, the association relationship between multiple nodes is determined based on the supply chain information, and the supply chain graph model of the target device is constructed based on the association relationship between multiple nodes. In other words, the supply chain graph model construction method provided by the present application is to construct a supply chain graph model based on the association relationship between multiple nodes, and the supply chain graph model constructed can express the complex relationship between the nodes in the supply chain.

[0084] In one embodiment, Figure 3 As shown, the above S203 can be specifically determined through the following S301 to S302.

[0085] S301. Determine a central node among the multiple nodes and multiple subordinate nodes of the central node according to association relationships among the multiple nodes.

[0086] The central node is a device node, and the subordinate nodes include one or more of a supplier node, a component node, a regional node, and a business node.

[0087] In a possible implementation, a central node (i.e., a device node) is determined based on the association relationship between multiple nodes, and subordinate nodes of the device node are determined. The subordinate nodes of the device node include component nodes having a composition relationship with the device node, supplier nodes having a supply relationship with the device node and the component node, regional nodes having a location relationship with the device node, and service nodes having an application relationship with the regional node.

[0088] S302: Construct a supply chain graph model of the target device according to the hierarchical relationship between the central node and multiple subordinate nodes.

[0089] For example, Figure 4 A schematic diagram of a supply chain graph model provided in an embodiment of the present application. Figure 4As shown, a supply chain graph model is constructed with the target device as the server, and the server is deployed in Beijing mainframe room No. 1. The node information and relationship information in the supply chain graph model are described below.

[0090] 1. Node information

[0091] 1-1. Supplier Node

[0092] Figure 4 The six diamonds in the diagram are supplier nodes, including device supplier nodes and component supplier nodes. The text inside the node is the supplier name (i.e. supplier 1 to supplier 6). The supplier of the server and the CPU is the same, and the supplier nodes are merged into one.

[0093] 1-2. Device Node

[0094] Figure 4 The pentagon in the figure is a device node. The device type is server and the device model is ABC1000.

[0095] 1-3. Component Node

[0096] Figure 4 The six ovals in the figure are component nodes, which are divided into hardware component nodes and software component nodes. The text in the hardware component node is the hardware component type and hardware component model, such as Figure 4 The CPUDDD12345, network card EEE12345, memory FFF12345, and hard disk AAA12345 in the software component node are the software component type, software component name, and version number, such as Figure 4 The operating system is BBBV1.0 and the database is CCCV1.0.

[0097] 1-4. Regional Nodes

[0098] Figure 4 The square in the middle is the regional node, and the text inside the node is the deployment area name, i.e. Beijing Host Room No. 1.

[0099] 1-5. Business Node

[0100] Figure 4 The two circles in the middle are business nodes, and the text inside the nodes is the business type and business system name, such as Figure 4 The production big data analysis system and the management comprehensive office system.

[0101] 2. Relationship Information

[0102] 2-1. Supply relationship

[0103] One device node and six component nodes are connected to six supplier nodes respectively, for a total of seven connection relationships.

[0104] 2-2. Composition relationship

[0105] One device node is connected to six component nodes, for a total of six connection relationships.

[0106] 2-3. Position relationship

[0107] 1 device node is connected to 1 regional node, with a total of 1 connection relationship.

[0108] 2-4. Application relationship

[0109] One regional node is connected to two business nodes, with a total of two connections.

[0110] It should be noted that the nodes in the above supply chain graph model can be represented not only by different shapes but also by different colors. For example, supplier nodes are green, equipment nodes are brown, component nodes are yellow, regional nodes are purple, and business nodes are blue.

[0111] It can be understood that by adding component nodes and business nodes to the supply chain graph model, the supply relationship of multiple components of the target device and the dependency of the target device in the customer usage scenario can be expressed, which can achieve transparency of each link in the supply chain, making it easier for enterprises to promptly discover and respond to potential supply chain risks.

[0112] Furthermore, after S203, the monitoring priority of any supplier can be determined according to the supply chain graph structure, so that the supplier can be monitored according to the monitoring priority. Figure 5 As shown, the supply chain graph model construction method recorded in the embodiment of the present application may also include the following steps.

[0113] S501. Determine a risk transfer coefficient of any supplier among multiple suppliers of a target device.

[0114] Among them, the risk transfer coefficient is used to reflect the impact of abnormal supplier behavior on the supply chain of the target device.

[0115] In a possible implementation, for any supplier among multiple suppliers of the target device, the number of transmission paths between the supplier node and the business node corresponding to the supplier in the supply chain graph model, the risk level weight of the supplier and the risk reachability probability are obtained, and the risk transmission coefficient of the supplier is determined according to the number of transmission paths, the risk level weight and the risk reachability probability. Among them, the number of transmission paths is the total number of transmission paths between the supplier node and the business node. The risk reachability probability is the probability that the supplier's risk actually affects the business node.

[0116] Optionally, the risk transfer coefficient of the above supplier may satisfy the following formula:

[0117] Supplier's risk transfer coefficient = number of transfer paths × risk level weight × risk reachability probability

[0118] Exemplarily, Table 2 provides a detailed description of the three parameters (ie, the number of transmission paths, the risk level weight, and the risk reachability probability) required to determine the risk transmission coefficient (RTC) of a supplier.

[0119] Table 2

[0120]

[0121]

[0122] Optionally, the above-mentioned risk reachability probability can be obtained based on specific risk information and implemented protective measures. Specifically, professionals (such as security experts or security operation and maintenance personnel, etc.) can evaluate and analyze the specific risk information and implemented protective measures, and calculate and assign the probability of the risk actually affecting the business system to obtain the risk reachability probability.

[0123] It should be noted that the risk transfer coefficient is usually used in the field of risk management to describe the degree of risk transmission or conduction between different stages, different entities or different systems, reflecting the degree of impact of the risk at a certain stage on the subsequent stages or related entities. In the embodiment of the present application, the risk transfer coefficient refers to the degree of impact of abnormalities such as security vulnerabilities, malicious attacks, property rights compliance, or supply and service outages introduced by suppliers on the business system.

[0124] For example, Figure 6 A schematic diagram of another supply chain graph model provided in an embodiment of the present application. Figure 6 As shown in the figure, diamonds are supplier nodes, ovals are component nodes, pentagons are equipment nodes, squares are regional nodes, and circles are business nodes. The meaning of the text in the nodes is the same as Figure 4 Similar, I will not go into details here.

[0125] by Figure 6 Take the supply chain graph model shown in as an example to calculate the risk transfer coefficient of supplier 1. Specifically, Figure 6 The transmission path shown by the dashed line in the middle can obtain TP = 4. In addition, if the risk level weight of supplier 1 is 0.8 (ie, RL = 0.8) and there is no protection measure (ie, RR = 1), then the RTC of supplier 1 = 4 × 0.8 × 1 = 3.2.

[0126] S502. Determine monitoring priorities of multiple suppliers based on the risk transfer coefficient of each supplier, and monitor the multiple suppliers according to the monitoring priorities.

[0127] In a possible implementation, suppliers are ranked according to their risk transfer coefficients, suppliers are divided into different monitoring priorities according to the ranking results, and suppliers are monitored according to the monitoring priorities.

[0128] Exemplarily, taking 6 suppliers as an example, the 6 suppliers are sorted according to the risk transfer coefficient corresponding to each supplier, and the monitoring priority of the first 2 suppliers is determined as high priority, the monitoring priority of the middle 2 suppliers is determined as medium priority, and the monitoring priority of the last 2 suppliers is determined as low priority. For suppliers with high monitoring priority, real-time monitoring is carried out. For suppliers with medium monitoring priority, regular monitoring (for example, once a day) is carried out. For suppliers with low monitoring priority, regular monitoring (for example, once a week) is carried out.

[0129] Furthermore, the risk transfer coefficients of all suppliers can be updated regularly, and the suppliers can be sorted according to the updated risk transfer coefficients of the suppliers to determine the updated monitoring priority of each supplier. Each supplier can be monitored according to the updated monitoring priority of each supplier.

[0130] It is understandable that by determining the monitoring priority of suppliers through their risk transfer coefficients and conducting real-time monitoring of high-priority suppliers, it is possible to accurately assess security risks in the supply chain and provide early warnings, as well as to promptly identify and handle risk issues, thereby improving the overall security level of the enterprise.

[0131] In summary, the supply chain graph model constructed by the embodiment of the present application can clearly and intuitively reflect the dependencies between components, equipment and services. The supply chain graph model constructed by the embodiment of the present application can effectively resist the risk of supply and service outage and speed up the response and response when the risk occurs. For example, a certain complete machine equipment has a risk of supply and service outage due to a specific component, and the complete machine equipment cannot be delivered on time, causing customers to postpone deployment or fail to expand capacity in time, resulting in business damage. The supply chain graph model constructed by the embodiment of the present application, combined with the analysis of factors such as market fluctuations, can help enterprises to carry out strategic reserves of key components or complete equipment in advance, and thus can effectively resist the risk of supply and service outage. For another example, when a component has a major security vulnerability or the risk of being maliciously attacked, it can quickly locate which complete equipment uses the component and which business systems use the affected complete equipment, and then quickly respond, formulate targeted risk protection measures, and minimize the loss to the business system. In other words, by adopting the supply chain graph model construction method provided by the embodiment of the present application, enterprises can optimize supply chain management, thereby reducing costs, improving efficiency and enhancing innovation capabilities.

[0132] It is understandable that the above-mentioned supply chain graph model construction method can be implemented by a supply chain graph model construction device. In order to realize the above-mentioned functions, the supply chain graph model construction device includes hardware structures and / or software modules corresponding to the execution of each function. Those skilled in the art should easily realize that, in combination with the modules and algorithm steps of each example described in the embodiments disclosed herein, the embodiments disclosed in this application can be implemented in the form of hardware or a combination of hardware and computer software. Whether a function is executed in the form of hardware or computer software driving hardware depends on the specific application and design constraints of the technical solution. Professional and technical personnel can use different methods to implement the described functions for each specific application, but such implementation should not be considered to exceed the scope of the embodiments disclosed in this application.

[0133] The embodiments disclosed in the present application can divide the functional modules according to the supply chain graph model construction device generated by the above method example. For example, each functional module can be divided according to each function, or two or more functions can be integrated into one processing module. The above integrated modules can be implemented in the form of hardware or in the form of software functional modules. It should be noted that the division of modules in the embodiments disclosed in the present application is schematic and is only a logical functional division. There may be other division methods in actual implementation.

[0134] Figure 7 This is a schematic diagram of the structure of a supply chain graph model building device provided in an embodiment of the present application. Figure 7 As shown, the supply chain graph model building device 70 can be used to execute Figure 2 , Figure 3 as well as Figure 5 The supply chain graph model construction method shown in the figure. The supply chain graph model construction device 70 includes: a communication unit 701 and a processing unit 702.

[0135] The communication unit 701 is used to obtain the supply chain information of the target device, and the supply chain information includes information of multiple nodes related to the supply chain of the target device; the processing unit 702 is used to determine the association relationship between the multiple nodes based on the supply chain information; the processing unit 702 is also used to construct a supply chain graph model of the target device based on the association relationship between the multiple nodes.

[0136] In a possible implementation, the node includes at least one of the following: a supplier node; a device node; a component node; a regional node; and a service node.

[0137] In a possible implementation, the association relationship includes at least one of the following: a supply relationship; a composition relationship; a location relationship; and an application relationship.

[0138] In one possible implementation, the processing unit 702 is also used to determine a central node among the multiple nodes and multiple subordinate nodes of the central node based on the association relationship between the multiple nodes; the processing unit 702 is also used to construct a supply chain graph model of the target device based on the hierarchical relationship between the central node and the multiple subordinate nodes.

[0139] In a possible implementation, the central node is a device node, and the subordinate nodes include one or more of a supplier node, a component node, a regional node, and a service node.

[0140] In one possible implementation, for any one of the multiple suppliers of the target device, the processing unit 702 is further used to determine the risk transfer coefficient of the supplier, where the risk transfer coefficient is used to reflect the degree of impact on the supply chain of the target device when an abnormality occurs in the supplier; the processing unit 702 is also used to determine the monitoring priority of the multiple suppliers based on the risk transfer coefficient of each supplier, and monitor the multiple suppliers according to the monitoring priority.

[0141] In one possible implementation, the communication unit 701 is further used to obtain the number of transmission paths between the supplier node corresponding to the supplier in the supply chain graph model and the business node, the supplier's risk level weight and the risk reachability probability; wherein the number of transmission paths is the total number of transmission paths between the supplier node and the business node, and the risk reachability probability is the probability that the supplier's risk has an actual impact on the business node; the processing unit 702 is further used to determine the supplier's risk transmission coefficient based on the number of transmission paths, the risk level weight and the risk reachability probability.

[0142] Through the description of the above implementation methods, technicians in the relevant field can clearly understand that for the convenience and simplicity of description, only the division of the above functional modules is used as an example. In actual applications, the above functions can be assigned to different functional modules as needed, that is, the internal structure of the device is divided into different functional modules to complete all or part of the functions described above. The specific working process of the system, device and unit described above can refer to the corresponding process in the aforementioned method embodiment, and will not be repeated here.

[0143] The present disclosure also provides a computer-readable storage medium having instructions stored thereon. When the instructions in the storage medium are executed by a processor of an electronic device, the electronic device is enabled to execute the supply chain graph model construction method provided by the above-mentioned embodiment of the present disclosure.

[0144] The embodiments of the present disclosure also provide a computer program product containing instructions, which, when executed on an electronic device, enables the electronic device to execute the supply chain graph model construction method provided by the embodiments of the present disclosure.

[0145] Among them, the computer readable storage medium can be, for example, but not limited to, an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, device or device, or any combination of the above. More specific examples of computer readable storage media (a non-exhaustive list) include: an electrical connection with one or more wires, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM), a register, a hard disk, an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the above, or any other form of computer readable storage medium known in the art. An exemplary storage medium is coupled to a processor so that the processor can read information from the storage medium and write information to the storage medium. Of course, the storage medium can also be a component of the processor. The processor and the storage medium can be located in an application-specific integrated circuit (ASIC). In the embodiments of the present application, a computer-readable storage medium may be any tangible medium that contains or stores a program, which may be used by or in conjunction with an instruction execution system, apparatus, or device.

[0146] The above are only specific implementations of the present application, but the protection scope of the present application is not limited thereto. Any changes or substitutions within the technical scope disclosed in the present application should be included in the protection scope of the present application. Therefore, the protection scope of the present application should be based on the protection scope of the claims.

Claims

1. A supply chain graph model construction method, characterized in that: The method comprises: Acquire supply chain information of a target device, wherein the supply chain information includes information of a plurality of nodes related to the supply chain of the target device; Based on the supply chain information, determining the association relationship between the multiple nodes; Based on the association relationship between the multiple nodes, a supply chain graph model of the target device is constructed.

2. The method according to claim 1, characterized in that The node includes at least one of the following: Supplier Node; Device nodes; Component nodes; Regional nodes; Business node.

3. The method according to claim 1 or 2, characterized in that: The association relationship includes at least one of the following: Supply relationships; composition relationship; Positional relationship; Application relationship.

4. The method according to claim 2, characterized in that: The step of constructing a supply chain graph model of the target device based on the association relationship between the multiple nodes includes: Determine a central node among the multiple nodes and multiple subordinate nodes of the central node according to the association relationship between the multiple nodes; A supply chain graph model of the target device is constructed according to the hierarchical relationship between the central node and the plurality of subordinate nodes.

5. The method according to claim 4, characterized in that The central node is the device node, and the subordinate nodes include one or more of the supplier node, the component node, the regional node, and the service node.

6. The method according to claim 2, characterized in that The method further comprises: For any supplier among the multiple suppliers of the target device, determine a risk transfer coefficient of the supplier, where the risk transfer coefficient is used to reflect the degree of impact on the supply chain of the target device when an abnormality occurs to the supplier; Based on the risk transfer coefficient of each supplier, the monitoring priorities of the multiple suppliers are determined, and the multiple suppliers are monitored according to the monitoring priorities.

7. The method according to claim 6, characterized in that Determining the risk transfer coefficient of the supplier includes: Obtain the number of transmission paths between the supplier node corresponding to the supplier in the supply chain graph model and the business node, the risk level weight of the supplier, and the risk reachability probability; wherein the number of transmission paths is the total number of transmission paths between the supplier node and the business node, and the risk reachability probability is the probability that the risk of the supplier has an actual impact on the business node; The risk transfer coefficient of the supplier is determined according to the number of transfer paths, the risk level weight and the risk reachability probability.

8. A supply chain graph model construction device, characterized in that: The device comprises: a communication unit and a processing unit; The communication unit is used to obtain supply chain information of the target device, wherein the supply chain information includes information of multiple nodes related to the supply chain of the target device; The processing unit is used to determine the association relationship between the multiple nodes based on the supply chain information; The processing unit is further used to construct a supply chain graph model of the target device based on the association relationship between the multiple nodes.

9. A supply chain graph model construction device, characterized in that: include: Memory and processor; The memory is coupled to the processor; The memory is used to store instructions executable by the processor; When the processor executes the instructions, it performs the supply chain graph model construction method as described in any one of claims 1-7.

10. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores computer instructions, and when the computer instructions are executed on a computer, the computer executes the supply chain graph model construction method according to any one of claims 1 to 7.

11. A computer program product, characterized in that The computer program product includes computer program instructions, and when the computer program instructions are executed by a processor, the supply chain graph model construction method according to any one of claims 1 to 7 is implemented.

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