Method and system for risk assessment of equipment system of network based on complex network betweenness

Abstract

The application provides an equipment system network risk assessment method and system based on complex network betweenness. The method comprises the following steps: obtaining all effective attack link sets based on the complex hierarchical network of the equipment system network; obtaining the node betweenness of each second node attacking each first node based on all effective attack link sets; obtaining the importance of each second node according to the importance of the first node; and obtaining the risk coefficient of the equipment system network according to the importance of the target second node. The application designs the node betweenness of the second node attacking each first node; and according to the different importance of the first node, the node betweenness of the second node calculated for each first node is weighted and summed to obtain the importance of each second node of the complex hierarchical network of the equipment system network; and the importance value of the target second node with the highest importance in all second nodes is selected as the risk coefficient of the equipment system network, thereby improving the risk assessment accuracy of the equipment system network.

Description

Technical Field

[0001] This invention relates to the field of risk assessment technology, and in particular to a method and system for assessing the network risk of equipment systems based on complex network betweenness. Background Technology

[0002] Existing risk assessment methods for equipment system networks include node removal methods, which simply calculate the decline in the equipment system network capability index before and after node removal. The drawback of this method is that the construction of the equipment system network capability index is controversial. The calculation method based on the reconnaissance or strike range of each piece of equipment is too one-sided and unrealistic. The actual equipment capability varies depending on the type and intelligence of each piece of equipment, making it difficult to uniformly construct it in the equipment system network. Another risk calculation method is to compare the size of the node degree as the pivotal role of the node. This type of method does not consider the connectivity between the layers of the entire equipment system network and can only represent the importance of the node in its own layer.

[0003] Therefore, there is an urgent need for a more effective risk assessment method to improve the accuracy of risk assessment for equipment system networks. Summary of the Invention

[0004] The present invention provides a method and system for assessing the network risk of equipment systems based on the betweenness of complex networks, which is used to solve the technical problem that there is an urgent need for a more effective risk assessment method in the prior art and to improve the accuracy of risk assessment of equipment system networks.

[0005] This invention provides a method for assessing the network risk of equipment systems based on complex network betweenness, comprising:

[0006] Based on the complex hierarchical network corresponding to the equipment system network, a set of all effective strike links generated for each first node is obtained. The complex hierarchical network is obtained based on the capability base map of the equipment system network. The first node is determined according to the target of the node strike in the capability base map of the equipment system network.

[0007] Based on the set of all effective strike links, the node betweenness number of each second node striking each first node is obtained, where the second node is a node in the network capability base map of the equipment system.

[0008] Based on the importance of the first node, the betweenness numbers of the nodes are weighted and summed to obtain the importance of each second node. The importance of the first node is obtained based on the betweenness numbers of the nodes.

[0009] The risk coefficient of the equipment system network is obtained based on the importance of the target second node, where the target second node is the second node with the highest importance among all second nodes.

[0010] According to the present invention, a method for assessing the network risk of an equipment system based on the betweenness of complex networks is provided, wherein the method for obtaining the complex hierarchical network includes:

[0011] Based on the equipment system network capability base map, the type of equipment corresponding to each second node is obtained;

[0012] Based on the type of equipment, a complex hierarchical network corresponding to the equipment system network and the connection relationships between nodes in each hierarchical network are obtained. The complex hierarchical network includes four layers: reconnaissance, communication, command and control, and strike.

[0013] According to the present invention, a method for assessing the network risk of an equipment system based on the betweenness of complex networks is provided. The method, based on the complex hierarchical network corresponding to the equipment system network, obtains a set of all effective strike links generated for each first node, including:

[0014] Based on the edge relationships between nodes in each layer of the complex layered network, a cyclic traversal method is used to calculate the set of all effective attack links in the complex layered network.

[0015] According to the present invention, a method for assessing the network risk of an equipment system based on the betweenness of complex networks is provided. The method involves calculating the set of all effective strike links in the complex hierarchical network using a iterative traversal method based on the edge relationships between nodes in each layer of the complex hierarchical network.

[0016] The first node of the first layer of the complex hierarchical network is taken as the current node;

[0017] Repeat the following search process until the node obtained after the last execution of the search process that has an edge relationship with the updated current node is the first node of the last layer of the complex hierarchical network, and obtain all strike links;

[0018] The strike links corresponding to the nodes whose last node in all strike links is the same as the first node of the first layer network are taken as valid strike links, and the set of all valid strike links is obtained.

[0019] The search process includes:

[0020] Based on the edge relationships between nodes in each layered network, find the nodes in the next layer of the complex layered network that are connected to the current node;

[0021] The current node is updated based on the nodes of the next-layer network. According to the method for assessing the network risk of an equipment system based on the betweenness of complex networks provided by the present invention, obtaining the betweenness of each second node striking each first node based on the set of all effective strike links includes:

[0022] Based on the set of all valid strike links, calculate the number of all strike links constructed when striking each first node;

[0023] The number of strike links passing through each second node is obtained from the strike links constructed when each first node is attacked;

[0024] The node betweenness number is obtained based on the total number of all strike links and the number of strike links.

[0025] According to the present invention, a method for assessing the network risk of an equipment system based on complex network betweenness numbers is provided. The method involves calculating the weighted sum of the betweenness numbers of the nodes based on the importance of the first node to obtain the importance of each second node, including:

[0026] Based on the importance of the first node, the importance coefficient of each first node is obtained;

[0027] Based on the importance coefficient, the betweenness numbers of the nodes are weighted and summed to obtain the importance of each second node.

[0028] This invention also provides a network risk assessment system for equipment systems based on complex network betweenness, comprising:

[0029] The first acquisition module is used to obtain a set of all effective strike links generated for each first node based on the complex hierarchical network corresponding to the equipment system network. The complex hierarchical network is obtained based on the capability map of the equipment system network. The first node is determined according to the target of the node strike in the capability map of the equipment system network.

[0030] The second acquisition module is used to obtain the node betweenness number of each second node that strikes each first node based on the set of all effective strike links, where the second node is a node in the network capability base map of the equipment system.

[0031] The third acquisition module is used to perform a weighted summation calculation on the node betweenness numbers based on the importance of the first node to obtain the importance of each second node, wherein the importance of the first node is obtained based on the node betweenness numbers.

[0032] The risk assessment module is used to obtain the risk coefficient of the equipment system network based on the importance of the target second node, wherein the target second node is the second node with the highest importance among all second nodes.

[0033] The present invention also provides an electronic device, including a processor and a memory storing a computer program, wherein the processor executes the program to implement the equipment system network risk assessment method based on complex network betweenness as described above.

[0034] The present invention also provides a non-transitory computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the equipment system network risk assessment method based on complex network betweenness as described above.

[0035] The present invention also provides a computer program product, including a computer program that, when executed by a processor, implements the equipment system network risk assessment method based on complex network betweenness as described above.

[0036] The present invention provides a method and system for assessing the network risk of an equipment system based on the betweenness of complex networks. It designs the betweenness of a second node in attacking each first node; and, based on the different importance of the first nodes, performs a weighted summation of the betweenness of the second nodes calculated for each first node to obtain the importance of each second node in the complex hierarchical network of the equipment system; and selects the importance value of the target second node with the highest importance among all second nodes as the risk coefficient of the equipment system network, thereby improving the accuracy of risk assessment of the equipment system network. Attached Figure Description

[0037] To more clearly illustrate the technical solutions in this invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of this invention. For those skilled in the art, other drawings can be obtained from these drawings without creative effort.

[0038] Figure 1 This is one of the flowcharts illustrating the network risk assessment method for equipment systems based on complex network betweenness provided by the present invention;

[0039] Figure 2 This is the second flowchart of the equipment system network risk assessment method based on complex network betweenness provided by the present invention;

[0040] Figure 3 This is a schematic diagram of the structure of the equipment system network risk assessment system based on complex network betweenness provided by the present invention;

[0041] Figure 4 This is a schematic diagram of the physical structure of the electronic device provided by the present invention. Detailed Implementation

[0042] To make the objectives, technical solutions, and advantages of this invention clearer, the technical solutions of this invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some, not all, of the embodiments of this invention. All other embodiments obtained by those skilled in the art based on the embodiments of this invention without creative effort are within the scope of protection of this invention.

[0043] Figure 1 This is one of the flowcharts illustrating the network risk assessment method for equipment systems based on complex network betweennesses provided by this invention, such as... Figure 1 As shown, the method includes:

[0044] Step 110: Based on the complex hierarchical network corresponding to the equipment system network, obtain a set of all effective strike links generated for each first node. The complex hierarchical network is obtained based on the capability map of the equipment system network. The first node is determined according to the target of the node strike in the capability map of the equipment system network.

[0045] Step 120: Based on the set of all effective strike links, obtain the node betweenness number of each second node striking each first node, where the second node is a node in the network capability base map of the equipment system.

[0046] Step 130: Based on the importance of the first node, perform a weighted summation of the node betweenness numbers to obtain the importance of each second node. The importance of the first node is obtained based on the node betweenness numbers.

[0047] Step 140: Based on the importance of the target second node, obtain the risk coefficient of the equipment system network, wherein the target second node is the second node with the highest importance among all second nodes.

[0048] It should be noted that the above method can be implemented by computer equipment.

[0049] Optionally, an Equipment System Network (ESN) is a networked architecture used for managing and controlling equipment systems. It connects various equipment, sensors, actuators, and related subsystems to enable data exchange, communication, and collaborative operation within the equipment system.

[0050] An equipment system network capability base map is a graphical representation that describes the capabilities and functions of each node in an equipment system network. It can be used to illustrate the connections and interactions between different nodes in an equipment system network, and to label the specific functions and capabilities of each node.

[0051] In the equipment system network capability map, each node represents a specific piece of equipment, sensor, actuator, or subsystem, while the lines connecting nodes represent their connections and communication relationships. Labels and symbols on nodes are used to identify the specific functions, capabilities, or characteristics of those nodes.

[0052] The network capability map of this equipment system is a collection of all combat equipment resources possessed by the second node (corresponding to our node), including but not limited to equipment type, capabilities, and coverage. The first node corresponds to the enemy node, i.e., the target of our node's attack.

[0053] A complex hierarchical network is constructed based on the location and relationships of the nodes corresponding to each piece of equipment in the equipment system network capability base map.

[0054] For the above complex hierarchical network, calculate the set of all effective strike links corresponding to each enemy node, and store the node numbers passed through by each effective strike link in sequence.

[0055] Drawing inspiration from the definitions of betweenness centrality in complex networks and graph theory statistics, we calculate the betweenness of our nodes when attacking each enemy node.

[0056] Specifically, betweenness considers the proportion of all shortest paths in a network, thus betweenness centrality can well reflect the importance of a node or edge in the entire network. Node betweenness refers to the number of shortest paths passing through a node in a network, and the betweenness centrality of a node is BC. i The calculation formula is as follows:

[0057]

[0058] in, This represents the number of paths connecting s and t that pass through node i and are the shortest paths. st Represents the number of shortest paths connecting s and t; normalization (let BC) i After <1), we have:

[0059]

[0060] Where N represents that there are N combinations of s and t, and each combination has multiple paths.

[0061] Based on the varying importance of enemy nodes, the above node betweenness calculation results are weighted and summed to obtain the node centrality of our nodes in the complex hierarchical network corresponding to the equipment system network, i.e., the importance of each second node.

[0062] The importance value of the highest-importance node among all our nodes (i.e., the target's second node) represents the risk coefficient of the equipment system network.

[0063] The present invention provides a method for assessing the network risk of an equipment system based on the betweenness of complex networks. This method designs the betweenness of a second node in attacking each first node; and, based on the different importance of the first nodes, performs a weighted summation of the betweenness of the second nodes calculated for each first node, obtaining the importance of each second node in the complex hierarchical network of the equipment system; finally, it selects the importance value of the target second node with the highest importance among all second nodes as the risk coefficient of the equipment system network, thereby improving the accuracy of risk assessment of the equipment system network.

[0064] Furthermore, in one embodiment, the method of obtaining the complex hierarchical network may include:

[0065] Based on the equipment system network capability base map, the type of equipment corresponding to each second node is obtained;

[0066] Based on the type of equipment, a complex hierarchical network corresponding to the equipment system network and the connection relationships between nodes in each hierarchical network are obtained. The complex hierarchical network includes four layers: reconnaissance, communication, command and control, and strike.

[0067] Optionally, the type of equipment corresponding to our nodes can be obtained based on the equipment system network capability base map.

[0068] Single node x i It can be described from three aspects: node attributes, node activity status, and node performance, represented by a triple x. i = <ATRB,STAT,CAP > In this context, ATRB represents node attributes, STAT represents node activity status, and CAP represents node performance.

[0069] The set B of enemy target nodes in the equipment system network can be represented as:

[0070] B = {b} i i = 1, 2, ..., N B}

[0071] Based on the type of equipment, the equipment system network is divided into a complex layered network M, which includes four layers: reconnaissance, communication, command and control, and strike. This can be represented as:

[0072] M = (G, E)

[0073] Where E represents the set of edges connecting nodes in each layer of a complex hierarchical network, and G represents a multi-layer network consisting of multiple single-layer networks, which can be represented as:

[0074] G = {G α :α∈{1,2,...,M}}

[0075] G α =(X α E α )

[0076]

[0077]

[0078] In each layer of network G α In the middle, X α E represents the set of nodes active in this layer of the network. α This represents the set of edges connecting active nodes within this layer of the network. All nodes in each layer of the network originate from the same set of nodes X. This represents the i-th node in layer a. N represents the j-th node in layer a. α It represents the set of all nodes in a certain layer of a network.

[0079] In some embodiments, the node representation order of the strike link is "target (i.e. enemy node) → reconnaissance → (communication) → command and control → (communication) → strike".

[0080] Furthermore, in one embodiment, the process of obtaining a set of all effective strike links generated for each first node based on the complex hierarchical network corresponding to the equipment system network may include:

[0081] Based on the edge relationships between nodes in each layer of the complex layered network, a cyclic traversal method is used to calculate the set of all effective attack links in the complex layered network.

[0082] Optionally, the set of all valid attack links can be calculated by starting from an enemy node and iterating through all the edges based on the connection relationships between nodes in different hierarchical networks, until the same enemy node is reached.

[0083] Further, in one embodiment, the step of calculating the set of all effective strike links of the complex hierarchical network using a loop traversal method based on the edge relationships between nodes in each layer of the complex hierarchical network may include:

[0084] The first node of the first layer of the complex hierarchical network is taken as the current node;

[0085] Repeat the following search process until the node obtained after the last execution of the search process that has an edge relationship with the updated current node is the node of the last layer of the complex hierarchical network, and obtain all strike links;

[0086] The strike links corresponding to the nodes whose last node in all strike links is the same as the first node of the first layer network are taken as valid strike links, and the set of all valid strike links is obtained.

[0087] The search process includes:

[0088] Based on the edge relationships between nodes in each layered network, find the nodes in the next layer of the complex layered network that are connected to the current node;

[0089] The current node is updated based on the nodes of the next layer network.

[0090] Optionally, in step 1, the enemy node in the first layer of the complex hierarchical network is set as the current node. Specifically, the pointer of the enemy node in the first layer of the network is set to the current node and stored in the list queue. In actual execution, each layer of the complex hierarchical network has different functions, and the association between different layers of the network can be set according to the requirements. In addition, the node attributes in each layer of the network are different.

[0091] Perform the search process corresponding to steps 2 through 4.

[0092] Step 2: Starting from the current node, calculate the nodes in the next layer of the network that are connected to the current node. Specifically, calculate the connection relationships E between nodes in the complex hierarchical network. α Use Python to find nodes in the next layer of the network that are connected to the current node and their positions;

[0093] Step 3: The current node is transferred to a node in the next layer of the network, and the current node is updated based on the nodes in the next layer of the network obtained in Step 2.

[0094] Step 4: Starting from the current node, repeat the search process steps 2 and 3 until the last search process is completed and the node with an edge relationship to the updated current node is the enemy node of the last layer of the complex hierarchical network, thus obtaining all attack links.

[0095] Step 5: Only retain the strike links in which the last node of all strike links is the same as the first node in the first layer network as valid strike links.

[0096] Step 6: Represent all effective strike links in the complex hierarchical network in sequence. The node representation order of the strike links is "target → reconnaissance → command and control → communication → strike → target".

[0097] Further, in one embodiment, obtaining the node betweenness number of each second node striking each first node based on the set of all valid strike links may include:

[0098] Based on the set of all valid strike links, calculate the number of all strike links constructed when striking each first node;

[0099] The number of attack links passing through each second node is obtained from the attack links constructed when each first node is attacked;

[0100] The node betweenness number is obtained based on the total number of all strike links and the number of strike links.

[0101] Optionally, based on the set of all effective strike links obtained from the complex hierarchical network of the equipment system network described above, the strike target (i.e., enemy node) b is calculated respectively. i The total number of all strike links constructed when (i = 1, 2, ... m) SSL i Calculate the target b. i In all attack links constructed when (i = 1, 2, ..., m), the one that passes through our node r j Number of strike links (j = 1, 2, ..., n) Specifically, Python's built-in functions can be used to directly count the number of targets hit (b). i The number of nodes (our nodes) in the list corresponding to all strike links constructed when (i = 1, 2, ... m).

[0102] Calculate our node r j (j = 1, 2, ..., n) targeting b i Betweenness (i.e., betweenness centrality) of nodes (i = 1, 2, ..., m)

[0103]

[0104] Among them, SSL i In order to target b i The total number of all strike links for (i = 1, 2, ..., m) To strike target b i In all attack links constructed when (i = 1, 2, ..., m), the one that passes through our node r j The number of strike links (j = 1, 2, ..., n).

[0105] The closer the calculated betweenness centrality value is to 1, the more important node i is, the weaker its substitutability, and the higher its risk.

[0106] Further, in one embodiment, the step of calculating the weighted sum of the betweenness factors of the nodes based on the importance of the first node to obtain the importance of each second node includes:

[0107] Based on the importance of the first node, the importance coefficient of each first node is obtained;

[0108] Based on the importance coefficient, the betweenness numbers of the nodes are weighted and summed to obtain the importance of each second node.

[0109] Optionally, the node centrality, i.e., node importance, of each node in the complex multi-layered network corresponding to the computational equipment system network is calculated, and the importance of each node r on our side is determined. j The Importance of (j=1,2,...,n) in the Equipment System Network Kimr j For each enemy target b i Weighted sum of importance for (i = 1, 2, ..., m):

[0110]

[0111] Among them, due to the different importance of enemy nodes, for each enemy node (i.e., target) b i (i = 1, 2, ..., m) Set an importance coefficient α i And there are:

[0112]

[0113] In this example, there are 5 enemy nodes, and their initial importance coefficients are set proportionally to 0.2.

[0114] In one embodiment of the present invention, the risk coefficient of the equipment system network is calculated by selecting r from all our nodes. j The importance value of the node with the highest importance (j=1,2,...,n) represents the risk coefficient of the equipment system network:

[0115] Srisk = max{Kimr j ,j=0,1,...n}

[0116] Where Srisk represents r among all our nodes j (j=1,2,...,n) The importance value of the node with the highest importance.

[0117] Figure 2 This is the second flowchart of the equipment system network risk assessment method based on complex network betweenness provided by the present invention, referred to... Figure 2The process includes: Step S1, constructing a complex hierarchical network based on the location and relationships of each equipment node in the equipment system network capability map; Step S2, calculating the set of all effective strike links corresponding to each enemy node in the complex hierarchical network, storing the node numbers passed through each strike link in sequence; Step S3, drawing on the definition of betweenness centrality from complex networks and graph theory statistics, calculating the betweenness of our nodes in striking each enemy node; Step S4, calculating the weighted sum of the above betweenness calculation results based on the different importance of enemy nodes, obtaining the node centrality, i.e., node importance, of each node in the complex multi-layer network corresponding to the equipment system network; Step S5, selecting the importance value of the node with the highest importance among all our nodes to represent the node importance of the equipment system network.

[0118] The present invention provides a method for assessing the network risk of an equipment system based on the betweenness of complex networks. The method for calculating the betweenness of nodes used to assess the importance of nodes considers the proportion of paths passing through the node. In the equipment system network model, the path category is set as the strike link passing through the node, which is more in line with the business scenario and business objectives of the present invention. Furthermore, the order of each path is set according to the order of the layered network, and each path covers each layer of the network in the model. This not only considers the hub function of the node itself, but also the connection between layers, making the indicators more reasonable and scientific. This helps to more accurately assess the performance of the equipment system network, which is beneficial to the subsequent construction and optimization of the equipment system network, thereby improving combat capabilities and efficiency.

[0119] The following describes the equipment system network risk assessment system based on complex network betweenness provided by the present invention. The equipment system network risk assessment system based on complex network betweenness described below can be referred to in correspondence with the equipment system network risk assessment method based on complex network betweenness described above.

[0120] Figure 3 This is a schematic diagram of the equipment system network risk assessment system based on complex network betweenness, provided by the present invention. Figure 3 As shown, it includes:

[0121] The first acquisition module 310 is used to obtain a set of all effective strike links generated for each first node based on the complex hierarchical network corresponding to the equipment system network. The complex hierarchical network is obtained based on the capability map of the equipment system network. The first node is determined according to the target of the node strike in the capability map of the equipment system network.

[0122] The second acquisition module 311 is used to obtain the node betweenness number of each second node striking each first node based on the set of all effective strike links, wherein the second node is a node in the equipment system network capability base map.

[0123] The third acquisition module 312 is used to perform a weighted summation calculation on the node betweenness numbers based on the importance of the first node to obtain the importance of each second node, wherein the importance of the first node is obtained based on the node betweenness numbers.

[0124] The risk assessment module 313 is used to obtain the risk coefficient of the equipment system network based on the importance of the target second node, wherein the target second node is the second node with the highest importance among all second nodes.

[0125] The present invention provides a network risk assessment system for equipment systems based on complex network betweenness numbers. It designs the betweenness number of a second node in attacking each first node; and, based on the different importance of the first nodes, performs a weighted summation of the betweenness numbers calculated by the second node for each first node to obtain the importance of each second node in the complex hierarchical network of the equipment system; and selects the importance value of the target second node with the highest importance among all second nodes as the risk coefficient of the equipment system network, thereby improving the accuracy of risk assessment of the equipment system network.

[0126] Figure 4 This is a schematic diagram of the physical structure of an electronic device provided by the present invention, such as... Figure 4 As shown, the electronic device may include: a processor 410, a communication interface 411, a memory 412, and a communication bus 413, wherein the processor 410, the communication interface 411, and the memory 412 communicate with each other via the communication bus 413. The processor 410 can call logical instructions in the memory 412 to execute the following methods:

[0127] Based on the complex hierarchical network corresponding to the equipment system network, a set of all effective strike links generated for each first node is obtained. The complex hierarchical network is obtained based on the capability base map of the equipment system network. The first node is determined according to the target of the node strike in the capability base map of the equipment system network.

[0128] Based on the set of all effective strike links, the node betweenness number of each second node striking each first node is obtained, where the second node is a node in the network capability base map of the equipment system.

[0129] Based on the importance of the first node, the betweenness numbers of the nodes are weighted and summed to obtain the importance of each second node. The importance of the first node is obtained based on the betweenness numbers of the nodes.

[0130] The risk coefficient of the equipment system network is obtained based on the importance of the target second node, where the target second node is the second node with the highest importance among all second nodes.

[0131] Furthermore, the logical instructions in the aforementioned memory can be implemented as software functional units and sold or used as independent products, and can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, or the part that contributes to the prior art, or a part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer power supply (which may be a personal computer, server, or network power supply, etc.) to execute all or part of the steps of the methods described in the various embodiments of the present invention. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0132] Furthermore, this invention discloses a computer program product, which includes a computer program stored on a non-transitory computer-readable storage medium. The computer program includes program instructions, and when these instructions are executed by a computer, the computer can execute the equipment system network risk assessment method based on complex network betweenness provided in the above-described method embodiments, for example including:

[0133] Based on the complex hierarchical network corresponding to the equipment system network, a set of all effective strike links generated for each first node is obtained. The complex hierarchical network is obtained based on the capability base map of the equipment system network. The first node is determined according to the target of the node strike in the capability base map of the equipment system network.

[0134] Based on the set of all effective strike links, the node betweenness number of each second node striking each first node is obtained, where the second node is a node in the network capability base map of the equipment system.

[0135] Based on the importance of the first node, the betweenness numbers of the nodes are weighted and summed to obtain the importance of each second node. The importance of the first node is obtained based on the betweenness numbers of the nodes.

[0136] The risk coefficient of the equipment system network is obtained based on the importance of the target second node, where the target second node is the second node with the highest importance among all second nodes.

[0137] On the other hand, the present invention also provides a non-transitory computer-readable storage medium storing a computer program thereon, which, when executed by a processor, is implemented to perform the equipment system network risk assessment method based on complex network betweennesses provided in the above embodiments, for example including:

[0138] Based on the complex hierarchical network corresponding to the equipment system network, a set of all effective strike links generated for each first node is obtained. The complex hierarchical network is obtained based on the capability base map of the equipment system network. The first node is determined according to the target of the node strike in the capability base map of the equipment system network.

[0139] Based on the set of all effective strike links, the node betweenness number of each second node striking each first node is obtained, where the second node is a node in the network capability base map of the equipment system.

[0140] Based on the importance of the first node, the betweenness numbers of the nodes are weighted and summed to obtain the importance of each second node. The importance of the first node is obtained based on the betweenness numbers of the nodes.

[0141] The risk coefficient of the equipment system network is obtained based on the importance of the target second node, where the target second node is the second node with the highest importance among all second nodes.

[0142] The system embodiments described above are merely illustrative. The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the modules can be selected to achieve the purpose of this embodiment according to actual needs. Those skilled in the art can understand and implement this without any creative effort.

[0143] Through the above description of the embodiments, those skilled in the art can clearly understand that each embodiment can be implemented by means of software plus necessary general-purpose hardware platforms, and of course, it can also be implemented by hardware. Based on this understanding, the above technical solutions, in essence or the part that contributes to the prior art, can be embodied in the form of a software product. This computer software product can be stored in a computer-readable storage medium, such as ROM / RAM, magnetic disk, optical disk, etc., including several instructions to cause a computer power supply (which may be a personal computer, server, or network power supply, etc.) to execute the methods described in various embodiments or some parts of the embodiments.

[0144] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, and not to limit them; although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features; and these modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A method for assessing the network risk of equipment systems based on the betweenness of complex networks, characterized in that, include: Based on the complex hierarchical network corresponding to the equipment system network, a set of all effective strike links generated for each first node is obtained. The complex hierarchical network is obtained based on the capability base map of the equipment system network. The first node is determined according to the target of the node strike in the capability base map of the equipment system network. Based on the set of all effective strike links, the node betweenness number of each second node striking each first node is obtained, where the second node is a node in the network capability base map of the equipment system. Based on the importance of the first node, the betweenness numbers of the nodes are weighted and summed to obtain the importance of each second node. The importance of the first node is obtained based on the betweenness numbers of the nodes. The risk coefficient of the equipment system network is obtained based on the importance of the target second node, where the target second node is the second node with the highest importance among all second nodes; The methods for obtaining the complex hierarchical network include: Based on the equipment system network capability base map, the type of equipment corresponding to each second node is obtained; Based on the type of equipment, a complex hierarchical network corresponding to the equipment system network and the connection relationships between nodes in each layer of the complex hierarchical network are obtained. The complex hierarchical network includes four layers: reconnaissance, communication, command and control, and strike. The weighted summation of the betweenness factors of the nodes based on the importance of the first node, to obtain the importance of each second node, includes: Based on the importance of the first node, the importance coefficient of each first node is obtained; Based on the importance coefficient, the betweenness numbers of the nodes are weighted and summed to obtain the importance of each second node.

2. The method for assessing the network risk of equipment systems based on complex network betweenness as described in claim 1, characterized in that, The complex hierarchical network corresponding to the equipment system network yields a set of all effective strike links generated for each first node, including: Based on the edge relationships between nodes in each layer of the complex layered network, a cyclic traversal method is used to calculate the set of all effective attack links in the complex layered network.

3. The method for assessing the network risk of equipment systems based on complex network betweenness as described in claim 2, characterized in that, The step of calculating the set of all effective attack links in the complex hierarchical network by using a loop traversal method based on the edge relationships between nodes in each layer of the complex hierarchical network includes: The first node of the first layer of the complex hierarchical network is taken as the current node; Repeat the following search process until the node obtained after the last execution of the search process that has an edge relationship with the updated current node is the first node of the last layer of the complex hierarchical network, and obtain all strike links; The strike links corresponding to the nodes whose last node in all strike links is the same as the first node of the first layer network are taken as valid strike links, and the set of all valid strike links is obtained. The search process includes: Based on the edge relationships between nodes in each layered network, find the nodes in the next layer of the complex layered network that are connected to the current node; The current node is updated based on the nodes of the next layer network.

4. The method for assessing the network risk of equipment systems based on complex network betweenness as described in claim 1, characterized in that, The process of obtaining the node betweenness number of each second node attacking each first node based on the set of all valid attack links includes: Based on the set of all valid strike links, calculate the number of all strike links constructed when striking each first node; The number of attack links passing through each second node is obtained from the attack links constructed when each first node is attacked; The node betweenness number is obtained based on the total number of all strike links and the number of strike links.

5. A network risk assessment system for equipment systems based on complex network betweenness, characterized in that, include: The first acquisition module is used to obtain a set of all effective strike links generated for each first node based on the complex hierarchical network corresponding to the equipment system network. The complex hierarchical network is obtained based on the capability map of the equipment system network. The first node is determined according to the target of the node strike in the capability map of the equipment system network. The second acquisition module is used to obtain the node betweenness number of each second node that strikes each first node based on the set of all effective strike links, where the second node is a node in the network capability base map of the equipment system. The third acquisition module is used to perform a weighted summation calculation on the node betweenness numbers based on the importance of the first node to obtain the importance of each second node, wherein the importance of the first node is obtained based on the node betweenness numbers. The risk assessment module is used to obtain the risk coefficient of the equipment system network based on the importance of the target second node, wherein the target second node is the second node with the highest importance among all second nodes; It also includes a fourth acquisition module, which is specifically used for: Based on the equipment system network capability base map, the type of equipment corresponding to each second node is obtained; Based on the type of equipment, a complex hierarchical network corresponding to the equipment system network and the connection relationships between nodes in each layer of the complex hierarchical network are obtained. The complex hierarchical network includes four layers: reconnaissance, communication, command and control, and strike. The third acquisition module is specifically used for: Based on the importance of the first node, the importance coefficient of each first node is obtained; Based on the importance coefficient, the betweenness numbers of the nodes are weighted and summed to obtain the importance of each second node.

6. An electronic device comprising a processor and a memory storing a computer program, characterized in that, When the processor executes the computer program, it implements the network risk assessment method for equipment systems based on complex network betweenness as described in any one of claims 1 to 4.

7. A non-transitory computer-readable storage medium having a computer program stored thereon, characterized in that, When executed by a processor, the computer program implements the network risk assessment method for equipment systems based on complex network betweenness as described in any one of claims 1 to 4.

8. A computer program product, comprising a computer program, characterized in that, When the computer program is executed by the processor, it implements the equipment system network risk assessment method based on complex network betweenness as described in any one of claims 1 to 4.

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