A method, system, device, and storage medium for mosaic-based network attack.

Abstract

This invention discloses a method, system, device, and storage medium for disrupting mosaic warfare networks, belonging to the technical field of complex network confrontation and combat effectiveness enhancement. The method includes constructing a mosaic warfare network model containing several real nodes based on pre-acquired target defense layout information; determining the stability of the mosaic warfare network model based on the real nodes to obtain a stability determination result; and embedding test nodes into the mosaic warfare network model based on the stability determination result, whereby the test nodes engage with the real nodes to disrupt the mosaic warfare network model. This invention can evaluate the stability of the mosaic warfare network model in real time and accurately, and accurately locate the weak nodes of the mosaic warfare network model. It provides a scientific basis for timely identification of the vulnerability points of the mosaic warfare network model and prediction of the reconstruction effect, effectively guiding the formulation of disruption strategies and ensuring a competitive advantage in complex and ever-changing battlefield environments.

Description

Technical Field

[0001] This invention belongs to the field of complex network countermeasures and combat effectiveness enhancement technology, specifically relating to a mosaic warfare network attack method, system, device and storage medium. Background Technology

[0002] Originally, mosaic referred to small, flat tiles used in architecture to create various decorative patterns. Later, in the computer field, it came to be used as a technique for blurring images or videos.

[0003] Mosaic warfare can coordinate and allocate various combat resources according to the actual battlefield situation, dynamically reorganize and allocate them in real time, and realize the dynamic reorganization of the battlefield network in more combinations to form an optimized adaptive kill network.

[0004] However, the mosaic warfare network adapts to battlefield changes through continuous dynamic reorganization, and this high flexibility makes the network structure difficult to predict. The problem this invention aims to solve is how to determine the stability of the network after each reorganization in a constantly changing network environment, and how to assess the overall functionality when some nodes are damaged, thereby achieving a breakthrough. Summary of the Invention

[0005] The purpose of this invention is to overcome the shortcomings of the prior art and provide a method, system, device and storage medium for breaking mosaic warfare networks. This method can determine the stability of the mosaic warfare network after each reorganization, accurately locate the weak nodes of the mosaic warfare network model, and then break it.

[0006] This invention provides the following technical solution:

[0007] Firstly, a method for disrupting a mosaic warfare network is provided, comprising: constructing a mosaic warfare network model containing several real nodes based on pre-acquired target defense layout information, wherein the real nodes are used to represent the combat elements of the target; determining the stability of the mosaic warfare network model based on the real nodes to obtain a stability determination result; and embedding test nodes in the mosaic warfare network model based on the stability determination result, wherein the test nodes engage in combat against the real nodes to disrupt the mosaic warfare network model.

[0008] As an optional technical solution of the present invention, the mosaic war network model is represented as follows:

[0009] ;

[0010] in, Let represent the mosaic warfare network model, D represent the network layer of the mosaic warfare network model, V represent the real nodes, E represent the edges between real nodes, and P represent attributes. Represents the actual node attributes. The network represents the edge attributes between real nodes, where L represents inter-layer links, M represents mapping relationships, and T represents information flow relationships. The categories of real nodes include command and control nodes, judgment nodes, decision-making nodes, and action nodes. Command and control nodes are used to observe the combat environment to obtain combat environment information; judgment nodes are used to assess the current combat situation; decision-making nodes are used to command operations; and action nodes are used to execute combat plans. The network layers of the mosaic warfare network model include a physical layer, an information layer, and a cognitive layer. The physical layer includes action nodes, the information layer includes command and control nodes, and the cognitive layer includes judgment nodes and decision-making nodes.

[0011] As an optional technical solution of the present invention, the step of determining the stability of the mosaic network model based on real nodes to obtain a stability determination result includes:

[0012] The participation matrix C of the mosaic war network model is constructed as follows:

[0013] ;

[0014] in, This represents the number of shortest cycles containing the i-th and j-th real nodes. This represents the total number of actual nodes;

[0015] Based on the participation matrix C, the node closure degree is calculated and expressed as:

[0016] ;

[0017] in, Let represent the closure degree of the i-th real node. This represents the number of shortest cycles containing only the i-th real node;

[0018] The importance order of each real node is obtained by sorting the closure degree of the nodes.

[0019] The degree is defined as the number of neighboring nodes of any real node.

[0020] ;

[0021] in, This represents the degree of the i-th real node. This represents the edge weight between the i-th and j-th real nodes. When the i-th and j-th real nodes are not connected, ... ;

[0022] The average degree of all real nodes is expressed as:

[0023] ;

[0024] in, This represents the average degree of all real nodes.

[0025] The difference in degree among the real nodes is taken as the degree value distribution, and expressed as:

[0026] ;

[0027] in, Indicates the distribution of degree values. Represents the original distribution of the degree of any real node;

[0028] Calculate the edge probability with weight w, expressed as the edge weight distribution. :

[0029] ;

[0030] in, This represents the number of edges with weight w in the mosaic network model;

[0031] Calculate the sum of edge weights connected to the i-th real node in the mosaic war network model, and express it as the node weight value. :

[0032] ;

[0033] The closure degree of the mosaic warfare network model is expressed as:

[0034] ;

[0035] in, This indicates the closure degree of the mosaic war network model;

[0036] The stability state of the mosaic war network model is obtained by comparing the closure degree of the mosaic war network model with a set threshold.

[0037] As an optional technical solution of the present invention, the step of embedding test nodes in the mosaic warfare network model based on the stability determination result, and having the test nodes fight against real nodes to break the mosaic warfare network model, includes:

[0038] The test node attacks the real node. When the i-th real node is damaged, the load is distributed to its neighboring nodes, as shown in the following:

[0039] ;

[0040] in, This represents the load distributed to the r-th neighbor node. Let i represent the set of neighboring nodes of the i-th real node. This represents the load of the i-th real node. This represents the load capacity of the r-th neighboring node. This represents the load capacity of the k-th neighbor node;

[0041] like If the value is 0, it means that the r-th neighbor node is overloaded and has failed.

[0042] Damaged real nodes and invalid neighbor nodes are considered as weak nodes in the mosaic war network model.

[0043] As an optional technical solution of the present invention, after the real nodes are destroyed, the mosaic war network model is dynamically reorganized; the stability of the dynamically reorganized mosaic war network model is determined, and a test node is embedded according to the determination result, and the test node fights against the remaining real nodes.

[0044] As an optional technical solution of the present invention, the step of embedding test nodes in the mosaic warfare network model based on the stability determination result, and having the test nodes fight against real nodes to break the mosaic warfare network model, further includes:

[0045] The real nodes that are difficult to fight against in the test nodes are taken as the difficult points of the fight. If there are difficult points of the fight, the test nodes are combined with conventional attack methods.

[0046] The source capacity of the mosaic warfare network model is represented as:

[0047] ;

[0048] in, Let M represent the source capacity of the mosaic network model, and M represent the number of edges in the mosaic network model. Let m represent the source capacity of the m-th edge;

[0049] The source capacity of the mosaic war network model The attack coefficient received by each edge in the mosaic warfare network model is evenly distributed across M edges. Represented as:

[0050] ;

[0051] After combining conventional attack methods, all edges in the mosaic warfare network model are sorted from largest to smallest according to their load, and the source capacity of the mosaic warfare network model is determined. Assigned to the front On each edge of the mosaic warfare network model, the breaching coefficient received by each edge is... Represented as:

[0052] ;

[0053] in, This represents the load of the m-th connection. This represents the load of the s-th connection;

[0054] The total penetration coefficient is expressed as:

[0055] ;

[0056] in, Indicates the total penetration coefficient;

[0057] when At that time, it disrupts the key to the confrontation;

[0058] Where C represents the edge capacity of the mosaic war network model.

[0059] As an optional technical solution of the present invention, it also includes:

[0060] The effectiveness of the attack is determined by the network efficiency F, whereby the network efficiency F is expressed as:

[0061] ;

[0062] Where N represents the total number of real nodes. This represents the shortest path distance between the i-th real node and the j-th real node;

[0063] If the i-th real node and the j-th real node are not connected, it is represented as:

[0064] ;

[0065] The smaller the network efficiency F, the better the attack effect.

[0066] Secondly, a mosaic warfare network breaching system is provided, comprising: a model building module, used to build a mosaic warfare network model containing several real nodes based on pre-acquired target defense layout information, wherein the real nodes are used to represent the combat elements of the target; a stability determination module, used to determine the stability of the mosaic warfare network model based on the real nodes, and obtain a stability determination result; and a breaching module, used to embed test nodes in the mosaic warfare network model based on the stability determination result, wherein the test nodes confront the real nodes to breach the mosaic warfare network model.

[0067] Thirdly, a mosaic warfare network attack device is provided, including a processor and a storage medium;

[0068] The storage medium is used to store instructions;

[0069] The processor is configured to operate according to the instructions to execute the steps of the mosaic warfare network breaching method described in the first aspect.

[0070] Fourthly, a computer-readable storage medium is provided, on which a computer program is stored, characterized in that, when executed by a processor, the program implements the steps of the mosaic warfare network breaking method described in the first aspect.

[0071] Compared with the prior art, the beneficial effects of the present invention are:

[0072] The mosaic warfare network breaching method provided by this invention analyzes the stability of the constructed mosaic warfare network model and embeds test nodes, enabling real-time and accurate evaluation of the model's stability. This allows for precise location of weak nodes in the mosaic warfare network model, providing a scientific basis for timely identification of vulnerabilities and prediction of reorganization effects. It effectively guides the formulation of breaching strategies, ensuring a competitive advantage in complex and ever-changing battlefield environments. Attached Figure Description

[0073] Figure 1 This is a flowchart of the mosaic warfare network breaching method in an embodiment of the present invention;

[0074] Figure 2 This is a schematic diagram illustrating the calculation process of node closure in an embodiment of the present invention;

[0075] Figure 3 This is a schematic diagram of the initial state of the mosaic network model in an embodiment of the present invention;

[0076] Figure 4 This is a schematic diagram of the damage state of the mosaic warfare network model in an embodiment of the present invention;

[0077] Figure 5 This is a schematic diagram of the breach state of the mosaic warfare network model in an embodiment of the present invention. Detailed Implementation

[0078] The present invention will be further described below with reference to the accompanying drawings. The following embodiments are only used to more clearly illustrate the technical solution of the present invention, and should not be used to limit the scope of protection of the present invention.

[0079] Example 1

[0080] This embodiment provides a method for dismantling mosaic-based networks. For example... Figure 1 As shown, the method includes the following steps:

[0081] Step 1: Construct a mosaic warfare network model containing several real nodes based on the pre-acquired target defense layout information.

[0082] Specifically, the mosaic war network model is represented as follows:

[0083] ;

[0084] in, Let represent the mosaic warfare network model, D represent the network layer of the mosaic warfare network model, V represent the real nodes, E represent the edges between real nodes, and P represent attributes. Represents the actual node attributes. The attributes represent the connection between real nodes: L represents inter-layer links, M represents mapping relationships, and T represents information flow relationships.

[0085] In this embodiment, the mosaic warfare network model includes several real nodes and edges connecting them. The real nodes represent operational elements of the target, such as various sensors, command and control stations, weapon platforms, and troop formations. The real nodes are categorized into command and control nodes, judgment nodes, decision-making nodes, and action nodes. Command and control nodes observe the operational environment to obtain operational information; judgment nodes assess the current operational situation; decision-making nodes command operations; and action nodes execute operational plans. The mosaic warfare network model's network layers include a physical layer, an information layer, and a cognitive layer. The physical layer includes action nodes, the information layer includes command and control nodes, and the cognitive layer includes judgment and decision-making nodes.

[0086] Furthermore, there are mapping and flow relationships between the physical layer, information layer, and cognitive layer. The physical layer includes business execution nodes, support nodes, and their connections. The information layer includes communication nodes, detection nodes, information fusion nodes, and their connections. The cognitive layer includes evaluation nodes, command nodes, control nodes, and their connections.

[0087] Step 2: Determine the stability of the mosaic network model and obtain the stability determination result.

[0088] (1) Calculate the closure degree of the nodes, as follows:

[0089] like Figure 2 As shown, the shortest cycles extracted from the mosaic network model include both the shortest cycles formed by connecting edges E within the same network layer and the shortest cycles formed by information flow relationships T between different network layers.

[0090] Construct the participation matrix C of the mosaic warfare network model to represent the circle information in the mosaic warfare network model. It is represented as:

[0091] ;

[0092] in, This represents the number of shortest cycles containing the i-th and j-th real nodes. This represents the total number of actual nodes.

[0093] Based on the participation matrix C, the node closure degree is calculated and expressed as:

[0094] ;

[0095] in, Let represent the closure degree of the i-th real node. This represents the number of shortest cycles containing only the i-th real node.

[0096] The importance order of each real node is obtained by sorting the closure degree of the nodes.

[0097] (2) Calculate the closure degree of the mosaic war network model, as follows:

[0098] The degree is defined as the number of neighboring nodes of any real node.

[0099] ;

[0100] in, This represents the degree of the i-th real node. This represents the edge weight between the i-th and j-th real nodes. When the i-th and j-th real nodes are not connected, ... .

[0101] The average degree of all real nodes is expressed as:

[0102] ;

[0103] in, This represents the average degree of all real nodes.

[0104] The degree of a real node is positively correlated with its importance or influence in the mosaic warfare network model. The higher the degree of a real node, the more real nodes it is connected to, and the higher its importance in the network. In the mosaic warfare network, a higher degree value indicates higher node connectivity, meaning it is more likely to be a key node in the mosaic warfare network model.

[0105] The difference in degree among the real nodes is taken as the degree value distribution, and expressed as:

[0106] ;

[0107] in, Indicates the distribution of degree values. This represents the original distribution of the degree of any real node.

[0108] Calculate the edge probability with weight w, expressed as the edge weight distribution. , used to represent the uniformity of edge resource distribution in a mosaic network model, is expressed as:

[0109] ;

[0110] in, This represents the number of edges with weight w in the mosaic network model.

[0111] Calculate the sum of edge weights connected to the i-th real node in the mosaic war network model, and express it as the node weight value. :

[0112] ;

[0113] The closure degree of the mosaic warfare network model is expressed as:

[0114] ;

[0115] in, This indicates the closure degree of the mosaic war network model.

[0116] The stability state of the mosaic war network model is obtained by comparing the closure degree of the mosaic war network model with a set threshold.

[0117] Step two is implemented during the attack on the mosaic warfare network model. After each dynamic reorganization of the mosaic warfare network model, a stability assessment is performed to evaluate the stability of the mosaic warfare network model during the dynamic reorganization process in real time and accurately, as well as the overall functionality of the mosaic warfare network model when some real nodes are damaged. The key nodes and weak nodes in the current mosaic warfare network model are preliminarily identified to provide data support for embedding test nodes.

[0118] Step 3: Based on the stability assessment results, embed test nodes into the mosaic warfare network model to attack it. Specifically, this includes:

[0119] (1) The test node employs both random and deliberate attacks against real nodes. A random attack refers to the test node indiscriminately removing real nodes from the mosaic network model, while a deliberate attack refers to removing real nodes sequentially according to their importance. When the i-th real node is damaged, the test node distributes the load to its neighboring nodes, as follows:

[0120] ;

[0121] in, This represents the load distributed to the r-th neighbor node. Let i represent the set of neighboring nodes of the i-th real node. This represents the load of the i-th real node. This represents the load capacity of the r-th neighboring node. This represents the load capacity of the k-th neighbor node.

[0122] like If , it means that the r-th neighbor node is overloaded and has failed.

[0123] Damaged real nodes and their failed neighbor nodes are considered weak nodes in the mosaic war network model. After a real node is damaged, the mosaic war network model dynamically reorganizes. The stability of the dynamically reorganized mosaic war network model is determined, and a test node is embedded based on the determination result. The test node then competes against the remaining real nodes.

[0124] By repeatedly performing the above process, the edges connecting real nodes in the mosaic warfare network model are broken, isolating, restraining, or removing real nodes as much as possible, ultimately achieving the goal of breaking the mosaic warfare network model. For example... Figure 3 As shown, this is the initial state of the mosaic war network model. After testing node adversarial scenarios, the edges between real nodes are partially broken, achieving the desired state. Figure 4 The damage condition shown.

[0125] (2) The real nodes that are difficult to fight against are taken as the difficult points of the fight. If there are difficult points of the fight, the test nodes are combined with conventional attack methods.

[0126] The source capacity of the mosaic warfare network model is represented as:

[0127] ;

[0128] in, Let M represent the source capacity of the mosaic network model, and M represent the number of edges in the mosaic network model. This represents the source capacity of the m-th edge.

[0129] The source capacity of the mosaic war network model The attack coefficient received by each edge in the mosaic warfare network model is evenly distributed across M edges. Represented as:

[0130] ;

[0131] After combining conventional attack methods, all edges in the mosaic warfare network model are sorted from largest to smallest according to their load, and the source capacity of the mosaic warfare network model is determined. Assigned to the front On each edge of the mosaic warfare network model, the breaching coefficient received by each edge is... Represented as:

[0132] ;

[0133] in, This represents the load of the m-th connection. This represents the load of the s-th connection;

[0134] The total penetration coefficient is expressed as:

[0135] ;

[0136] in, Indicates the total penetration coefficient;

[0137] when When this occurs, it disrupts the difficulty of the confrontation, where C represents the edge capacity of the mosaic war network model.

[0138] like Figure 5 As shown, this is the state of the mosaic network model after it has been compromised. In the initial state, most of the edges are broken, and some real nodes become invalid nodes.

[0139] Step 4: Evaluate the effectiveness of the attack.

[0140] The effectiveness of the attack is determined by the network efficiency F, whereby the network efficiency F is expressed as:

[0141] ;

[0142] Where N represents the total number of real nodes. This represents the shortest path distance between the i-th real node and the j-th real node.

[0143] If the i-th real node and the j-th real node are not connected, it is represented as:

[0144] ;

[0145] The smaller the network efficiency F, the better the attack effect. When there are no connected nodes in the mosaic warfare network model, then... The larger the network efficiency F, the more difficult it is for some real nodes and their edges in the mosaic war network model to fight against.

[0146] Furthermore, the parts of the enemy's mosaic warfare network model that are difficult to counter are copied into our own combat network model. The network efficiency of our own combat network model is denoted as... .

[0147] when At that time, it was believed that our operational network model could effectively counter the enemy, creating a "counteracting" effect. The network efficiency of our operational network model was then assessed. The difference between the network efficiency F of the network model and that of the enemy's mosaic warfare network model is taken as the surplus, denoted as . , represented as:

[0148] ;

[0149] Surplus The higher the value, the stronger our combat network's ability to break through the strong parts of the enemy's mosaic warfare network. Therefore, by replicating the difficult-to-counter parts of the mosaic warfare network model, we can enhance the robustness of our combat network.

[0150] Example 2

[0151] This embodiment provides a mosaic-based network attack system, including:

[0152] The model building module is used to construct a mosaic warfare network model containing several real nodes based on pre-acquired target defense layout information, wherein the real nodes are used to represent the combat elements of the target.

[0153] The stability determination module is used to determine the stability of the mosaic war network model based on the real nodes and obtain the stability determination result.

[0154] The attack module is used to embed test nodes into the mosaic warfare network model based on the stability determination result. The test nodes then engage real nodes to attack the mosaic warfare network model.

[0155] Example 3

[0156] This embodiment provides a mosaic warfare network breaching device, including a processor and a storage medium; the storage medium is used to store instructions; the processor is used to operate according to the instructions to execute the steps of the mosaic warfare network breaching method described in Embodiment 1.

[0157] Example 4

[0158] This embodiment provides a computer-readable storage medium storing a computer program that, when executed by a processor, implements the steps of the mosaic warfare network breaching method described in Embodiment 1.

[0159] Those skilled in the art will understand that embodiments of this application can be provided as methods, systems, or computer program products. Therefore, this application can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, this application can take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0160] This application is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of this application. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, generate instructions for implementing the flowchart... Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

[0161] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing device to function in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process Figure 1 One or more processes and / or boxes Figure 1 The function specified in one or more boxes.

[0162] These computer program instructions may also be loaded onto a computer or other programmable data processing equipment to cause a series of operational steps to be performed on the computer or other programmable equipment to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable equipment for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 The steps of the function specified in one or more boxes.

[0163] The above description is only a preferred embodiment of the present invention. It should be noted that for those skilled in the art, several improvements and modifications can be made without departing from the technical principles of the present invention, and these improvements and modifications should also be considered within the scope of protection of the present invention.

Claims

1. A method for disrupting mosaic-based networks, characterized in that, include: Based on pre-acquired target defense layout information, a mosaic warfare network model containing several real nodes is constructed, wherein the real nodes represent the target's combat elements; the mosaic warfare network model is represented as follows: ； in, Let represent the mosaic warfare network model, D represent the network layer of the mosaic warfare network model, V represent the real nodes, E represent the edges between real nodes, and P represent attributes. Represents the actual node attributes. The attributes represent the connections between real nodes: L represents inter-layer links, M represents mapping relationships, and T represents information flow relationships. The categories of real nodes include command and control nodes, judgment nodes, decision-making nodes, and action nodes; the command and control nodes are used to observe the combat environment to obtain combat environment information, the judgment nodes are used to assess the current combat situation, the decision-making nodes are used to command combat, and the action nodes are used to execute combat plans. The network layers of the mosaic warfare network model include a physical layer, an information layer, and a cognitive layer. The physical layer includes action-type nodes, the information layer includes command and control-type nodes, and the cognitive layer includes judgment-type nodes and decision-type nodes. The stability of the mosaic warfare network model is determined based on the actual nodes, and the stability determination result is obtained, including: constructing the participation matrix C of the mosaic warfare network model, expressed as: ； in, This represents the number of shortest cycles containing the i-th and j-th real nodes. This represents the total number of actual nodes; Based on the participation matrix C, the node closure degree is calculated and expressed as: ； in, Let represent the closure degree of the i-th real node. This represents the number of shortest cycles containing only the i-th real node; The importance order of each real node is obtained by sorting the closure degree of the nodes. The degree is defined as the number of neighboring nodes of any real node. ； in, This represents the degree of the i-th real node. This represents the edge weight between the i-th and j-th real nodes. When the i-th and j-th real nodes are not connected, ... ; The average degree of all real nodes is expressed as: ； in, This represents the average degree of all real nodes. The difference in degree among the real nodes is taken as the degree value distribution, and expressed as: ； in, Indicates the distribution of degree values. Represents the original distribution of the degree of any real node; Calculate the edge probability with weight w, expressed as the edge weight distribution. : ； in, This represents the number of edges with weight w in the mosaic network model; Calculate the sum of edge weights connected to the i-th real node in the mosaic war network model, and represent it as the node weight value. : ； The closure degree of the mosaic warfare network model is expressed as: ； in, This indicates the closure degree of the mosaic war network model; The stability state of the mosaic warfare network model is obtained by comparing the closure degree of the mosaic warfare network model with a set threshold. Based on the stability determination result, test nodes are embedded in the mosaic warfare network model. These test nodes then engage real nodes to disrupt the mosaic warfare network model. This includes: when the i-th real node is destroyed, the test node distributes load to its neighboring nodes, as shown below: ； in, This represents the load distributed to the r-th neighbor node. Let i represent the set of neighboring nodes of the i-th real node. This represents the load of the i-th real node. This represents the load capacity of the r-th neighboring node. This represents the load capacity of the k-th neighbor node; like If the value is 0, it means that the r-th neighbor node is overloaded and has failed. Damaged real nodes and invalid neighbor nodes are considered as weak nodes in the mosaic war network model.

2. The mosaic warfare network attack method according to claim 1, characterized in that, After the real nodes are destroyed, the mosaic war network model is dynamically reorganized. The stability of the dynamically reorganized mosaic war network model is determined, and test nodes are embedded based on the determination results. The test nodes then compete against the remaining real nodes.

3. The mosaic warfare network attack method according to claim 1, characterized in that, The method of embedding test nodes into the mosaic warfare network model based on the stability determination result, whereby the test nodes compete against real nodes to disrupt the mosaic warfare network model, also includes: The real nodes that are difficult to fight against in the test nodes are taken as the difficult points of the fight. If there are difficult points of the fight, the test nodes are combined with conventional attack methods. The source capacity of the mosaic warfare network model is represented as: ； in, Let M represent the source capacity of the mosaic network model, and M represent the number of edges in the mosaic network model. Let m represent the source capacity of the m-th edge; The source capacity of the mosaic war network model The attack coefficient received by each edge in the mosaic warfare network model is evenly distributed across M edges. Represented as: ； After combining conventional attack methods, all edges in the mosaic warfare network model are sorted from largest to smallest according to their load, and the source capacity of the mosaic warfare network model is determined. Assigned to the front On each edge of the mosaic warfare network model, the breaching coefficient received by each edge is... Represented as: ； in, This represents the load of the m-th connection. This represents the load of the s-th connection; The total penetration coefficient is expressed as: ； in, Indicates the total penetration coefficient; when At that time, it disrupts the key to the confrontation; Where C represents the edge capacity of the mosaic war network model.

4. The mosaic warfare network attack method according to claim 1, characterized in that, Also includes: The effectiveness of the attack is determined by the network efficiency F, whereby the network efficiency F is expressed as: ； Where N represents the total number of real nodes. This represents the shortest path distance between the i-th real node and the j-th real node; If the i-th real node and the j-th real node are not connected, it is represented as: ； The smaller the network efficiency F, the better the attack effect.

5. A mosaic-based network attack system, characterized in that, include: The model building module is used to construct a mosaic warfare network model containing several real nodes based on pre-acquired target defense layout information. The real nodes represent the operational elements of the target. The mosaic warfare network model is represented as follows: ； in, Let represent the mosaic warfare network model, D represent the network layer of the mosaic warfare network model, V represent the real nodes, E represent the edges between real nodes, and P represent attributes. Represents the actual node attributes. The attributes represent the connections between real nodes: L represents inter-layer links, M represents mapping relationships, and T represents information flow relationships. The categories of real nodes include command and control nodes, judgment nodes, decision-making nodes, and action nodes; the command and control nodes are used to observe the combat environment to obtain combat environment information, the judgment nodes are used to assess the current combat situation, the decision-making nodes are used to command combat, and the action nodes are used to execute combat plans. The network layers of the mosaic warfare network model include a physical layer, an information layer, and a cognitive layer. The physical layer includes action-type nodes, the information layer includes command and control-type nodes, and the cognitive layer includes judgment-type nodes and decision-type nodes. The stability determination module is used to determine the stability of the mosaic warfare network model based on the real nodes, and obtain the stability determination result, including: constructing the participation matrix C of the mosaic warfare network model, represented as: ； in, This represents the number of shortest cycles containing the i-th and j-th real nodes. This represents the total number of actual nodes; Based on the participation matrix C, the node closure degree is calculated and expressed as: ； in, Let represent the closure degree of the i-th real node. This represents the number of shortest cycles containing only the i-th real node; The importance order of each real node is obtained by sorting the closure degree of the nodes. The degree is defined as the number of neighboring nodes of any real node. ； in, This represents the degree of the i-th real node. This represents the edge weight between the i-th and j-th real nodes. When the i-th and j-th real nodes are not connected, ... ; The average degree of all real nodes is expressed as: ； in, This represents the average degree of all real nodes. The difference in degree among the real nodes is taken as the degree value distribution, and expressed as: ； in, Indicates the distribution of degree values. Represents the original distribution of the degree of any real node; Calculate the edge probability with weight w, expressed as the edge weight distribution. : ； in, This represents the number of edges with weight w in the mosaic network model; Calculate the sum of edge weights connected to the i-th real node in the mosaic war network model, and represent it as the node weight value. : ； The closure degree of the mosaic warfare network model is expressed as: ； in, This indicates the closure degree of the mosaic war network model; The stability state of the mosaic warfare network model is obtained by comparing the closure degree of the mosaic warfare network model with a set threshold. The attack module, based on the stability determination result, embeds test nodes into the mosaic warfare network model. These test nodes then engage real nodes to attack the mosaic warfare network model. This includes: when the i-th real node is destroyed, the test node distributes load to its neighboring nodes, as shown below: ； in, This represents the load distributed to the r-th neighbor node. Let i represent the set of neighboring nodes of the i-th real node. This represents the load of the i-th real node. This represents the load capacity of the r-th neighboring node. This represents the load capacity of the k-th neighbor node; like If the value is 0, it means that the r-th neighbor node is overloaded and has failed. Damaged real nodes and invalid neighbor nodes are considered as weak nodes in the mosaic war network model.

6. A mosaic warfare network breaching device, characterized in that, Including processor and storage media; The storage medium is used to store instructions; The processor is configured to operate according to the instructions to perform the steps of the mosaic warfare network breaching method according to any one of claims 1 to 4.

7. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the program is executed by the processor, it implements the steps of the mosaic warfare network breaching method according to any one of claims 1 to 4.

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