Mosaic battle network breaking method, system and device and storage medium

Abstract

The invention discloses a mosaic battle network breaking method, system and device and a storage medium, and belongs to the technical field of complex network confrontation and battle effectiveness improvement. The method comprises the following steps: constructing a mosaic battle network model containing a plurality of real nodes according to pre-acquired target defense layout information; judging the stability of the mosaic battle network model according to the real node to obtain a stability judgment result; and based on a stability determination result, embedding a test node in the mosaic battle network model, and enabling the test node to confront the real node so as to break the mosaic battle network model. The stability of the mosaic warfare network model can be accurately evaluated in real time, the weak nodes of the mosaic warfare network model are accurately positioned, a scientific basis is provided for identifying the weak points of the mosaic warfare network model in time and pre-judging the recombination effect, making of a breaking strategy is effectively guided, and the reliability of the system is improved. It is ensured that a precedent is occupied in a complex and changeable battlefield environment.

Description

Technical Field

[0001] The present invention belongs to the technical field of complex network confrontation and combat effectiveness improvement, and specifically relates to a mosaic warfare network breaking method, system, device and storage medium. Background Art

[0002] The original meaning of mosaic refers to small tiles used to form various decorative patterns in buildings. Later, it was extended to a means of blurring images or videos in the computer field.

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

[0004] However, the mosaic warfare network is constantly and dynamically reorganized to cope with battlefield changes. This high flexibility makes the network structure difficult to predict. How to judge the stability of the network after each reorganization in a constantly changing network environment, and how to judge the overall functionality of the network when some nodes are damaged, and then achieve attack, is a problem that the present invention needs to solve. Summary of the invention

[0005] The purpose of the present invention is to overcome the deficiencies in the prior art and to provide a mosaic warfare network attack method, system, device and storage medium, which 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 attack it.

[0006] The present invention provides the following technical solutions:

[0007] In a first aspect, a mosaic warfare network attack method is provided, comprising: constructing a mosaic warfare network model including a plurality of real nodes according to pre-acquired target defense layout information, wherein the real nodes are used to represent combat elements of the target; judging the stability of the mosaic warfare network model according to the real nodes to obtain a stability judgment result; based on the stability judgment result, embedding a test node in the mosaic warfare network model, and using the test node to fight against the real node to attack the mosaic warfare network model.

[0008] As an optional technical solution of the present invention, the mosaic warfare network model is expressed as:

[0009] ;

[0010] in, represents the mosaic warfare network model, D represents the network layer of the mosaic warfare network model, V represents the real node, E represents the edge between the real nodes, P represents the attribute, Represents the real node attributes, represents the edge attributes between real nodes, L represents the inter-layer link, M represents the mapping relationship, and T represents the information flow relationship; the categories of the real nodes include command nodes, judgment nodes, decision nodes and action nodes; the command nodes are used to observe the combat environment to obtain combat environment information, the judgment nodes are used to evaluate the current combat situation, the decision nodes are used to command operations, and the action nodes are used to execute combat plans; the network layers of the mosaic warfare network model include the physical layer, the information layer and the cognitive layer, wherein the physical layer includes action nodes, the information layer includes command nodes, and the cognitive layer includes judgment nodes and decision nodes.

[0011] As an optional technical solution of the present invention, the stability of the mosaic warfare network model is determined according to the real nodes to obtain the stability determination result, including:

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

[0013] ;

[0014] in, represents the number of shortest cycles containing the ith real node and the jth real node, Indicates the total number of real nodes;

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

[0016] ;

[0017] in, represents the closure degree of the i-th real node, represents the number of shortest cycles that only contain the i-th real node;

[0018] Sorting the node closure degrees to obtain the importance order of each real node;

[0019] The number of adjacent nodes of any real node is taken as the degree, expressed as:

[0020] ;

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

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

[0023] ;

[0024] in, Represents the average degree of all real nodes;

[0025] The difference between the degrees of each real node is taken as the degree distribution, which is expressed as:

[0026] ;

[0027] in, represents the degree distribution, represents the original distribution of the degree of any real node;

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

[0029] ;

[0030] in, Represents the number of edges with weight w in the Mosaic Warfare network model;

[0031] Calculate the sum of the edge weights connected to the i-th real node in the Mosaic Warfare network model, expressed as the node weight value :

[0032] ;

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

[0034] ;

[0035] in, Indicates the closure of the Mosaic Warfare network model;

[0036] The closedness of the mosaic warfare network model is compared with a set threshold to obtain the stability state of the mosaic warfare network model.

[0037] As an optional technical solution of the present invention, based on the stability determination result, a test node is embedded in the mosaic warfare network model, and the test node is used to fight against the real node to break the mosaic warfare network model, including:

[0038] The test node fights against the real node. When the i-th real node is destroyed, the load is distributed to its neighboring nodes, which is expressed as:

[0039] ;

[0040] in, represents the load distributed to the rth neighbor node, represents the set of neighbor nodes of the ith real node, represents the real node load of the ith node, represents the load capacity of the rth neighbor node, represents the load capacity of the kth neighbor node;

[0041] like , it means that the rth neighbor node is overloaded and fails;

[0042] The damaged real nodes and failed neighbor nodes serve as weak nodes in the mosaic warfare network model.

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

[0044] As an optional technical solution of the present invention, based on the stability determination result, a test node is embedded in the mosaic warfare network model, and the test node is used to fight against the real node to break the mosaic warfare network model, and further includes:

[0045] The real nodes that are difficult for the test nodes to counter are used as the countermeasure difficulties. If there are countermeasure difficulties, the test nodes are combined with conventional attack methods;

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

[0047] ;

[0048] in, represents the source capacity of the mosaic warfare network model, M represents the number of edges in the mosaic warfare network model, represents the source capacity of the mth edge;

[0049] Source capacity of mosaic warfare network model Evenly distributed to M links, the attack coefficient received by each link in the mosaic warfare network model It is expressed as:

[0050] ;

[0051] After combining conventional attack methods, all the links in the mosaic warfare network model are sorted from large to small according to the link load, and the source capacity of the mosaic warfare network model is Assign to front The attack coefficient received by each link in the mosaic warfare network model It is expressed as:

[0052] ;

[0053] in, represents the load of the mth edge, represents the load of the sth edge;

[0054] The total breaking coefficient is expressed as;

[0055] ;

[0056] in, It represents the total breaking coefficient;

[0057] when When, it destroys the difficulty of confrontation;

[0058] Among them, C represents the edge capacity of the mosaic warfare network model.

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

[0060] The attack effect is determined by the network efficiency F, which is expressed as:

[0061] ;

[0062] Where N represents the total number of real nodes. 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 can be expressed as:

[0064] ;

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

[0066] In a second aspect, a mosaic warfare network attack system is provided, comprising: a model construction module, for constructing a mosaic warfare network model including a number of real nodes according to pre-acquired target defense layout information, wherein the real nodes are used to represent combat elements of the target; a stability determination module, for determining the stability of the mosaic warfare network model according to the real nodes to obtain a stability determination result; and an attack module, for embedding a test node in the mosaic warfare network model based on the stability determination result, and having the test node fight against the real node to attack the mosaic warfare network model.

[0067] In a third aspect, 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 used to operate according to the instructions to execute the steps of the mosaic warfare network breaking method described in the first aspect.

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

[0071] Compared with the prior art, the present invention has the following beneficial effects:

[0072] The mosaic warfare network breaking method provided by the present invention can evaluate the stability of the mosaic warfare network model in real time and accurately by performing stability analysis on the constructed mosaic warfare network model and embedding test nodes, and realize the precise positioning of the weak nodes of the mosaic warfare network model, thereby providing a scientific basis for timely identifying the vulnerable points of the mosaic warfare network model and predicting the reorganization effect, effectively guiding the formulation of breaking strategies, and ensuring taking the initiative in complex and changeable battlefield environments. BRIEF DESCRIPTION OF THE DRAWINGS

[0073] Figure 1 is a flow chart of a mosaic warfare network attack method according to an embodiment of the present invention;

[0074] Figure 2 Schematic diagram of the calculation process of node closure degree in an embodiment of the present invention;

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

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

[0077] Figure 5 It is a schematic diagram of the attack state of the mosaic warfare network model in an embodiment of the present invention. DETAILED DESCRIPTION

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

[0079] Example 1

[0080] This embodiment provides a mosaic warfare network attack method. Figure 1 As shown, the method comprises 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 warfare network model is expressed as:

[0083] ;

[0084] in, represents the mosaic warfare network model, D represents the network layer of the mosaic warfare network model, V represents the real node, E represents the edge between the real nodes, P represents the attribute, Represents the real node attributes, It represents the edge attribute between real nodes, L represents the inter-layer link, M represents the mapping relationship, and T represents the information flow relationship.

[0085] In this embodiment, the mosaic warfare network model includes a number of real nodes and edges between the real nodes. The real nodes are used to represent the combat elements of the target, such as various sensors, command and control sites, weapon platforms, force formations, etc. The categories of the real nodes include command and control nodes, judgment nodes, decision 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 evaluate the current combat situation, the decision nodes are used to command operations, and the action nodes are used to execute combat plans. The network layer of the mosaic warfare network model includes a physical layer, an information layer and a cognitive layer, wherein the physical layer includes action nodes, the information layer includes command and control nodes, and the cognitive layer includes judgment nodes and decision nodes.

[0086] Furthermore, there is a mapping and flow relationship between the physical layer, information layer and cognitive layer. The physical layer includes business execution nodes, assurance nodes and their edges. The information layer includes communication nodes, detection nodes, information fusion nodes and their edges. The cognitive layer includes evaluation nodes, command nodes, control nodes and their edges.

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

[0088] (1) Calculate the node closure degree as follows:

[0089] like Figure 2 As shown, the shortest circle in the mosaic warfare network model is extracted, including both the shortest circle formed by the edge E in the same network layer and the shortest circle formed by the information flow relationship T between different network layers.

[0090] The participation matrix C of the mosaic warfare network model is constructed to characterize the circle information in the mosaic warfare network model. It is expressed as:

[0091] ;

[0092] in, represents the number of shortest cycles containing the ith real node and the jth real node, Indicates the total number of real nodes.

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

[0094] ;

[0095] in, represents the closure degree of the i-th real node, represents the number of shortest cycles that only contain the i-th real node.

[0096] The node closure degrees are sorted to obtain the importance order of each real node.

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

[0098] The number of adjacent nodes of any real node is taken as the degree, expressed as:

[0099] ;

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

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

[0102] ;

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

[0104] The degree of a real node is positively correlated with the importance or influence of the real node in the Mosaic Warfare network model. The larger the degree of a real node, the more real nodes are connected to it, and the higher its importance in the network. In the Mosaic Warfare network, the higher the degree value, the higher the connectivity of the node, which means it is likely to be a key node in the Mosaic Warfare network model.

[0105] The difference between the degrees of each real node is taken as the degree distribution, which is expressed as:

[0106] ;

[0107] in, represents the degree distribution, Represents the raw distribution of the degree of any real node.

[0108] Calculate the edge probability with weight w, expressed as edge weight distribution , which is used to indicate the uniformity of the edge resource distribution in the mosaic warfare network model, and is expressed as:

[0109] ;

[0110] in, Represents the number of edges with weight w in the Mosaic Warfare network model.

[0111] Calculate the sum of the edge weights connected to the i-th real node in the Mosaic Warfare network model, expressed as the node weight value :

[0112] ;

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

[0114] ;

[0115] in, Indicates the degree of closure of the Mosaic Warfare network model.

[0116] The closedness of the mosaic warfare network model is compared with a set threshold to obtain the stability state of the mosaic warfare network model.

[0117] Step 2 is implemented during the attack process of the Mosaic Warfare Network Model. After each dynamic reorganization of the Mosaic Warfare Network Model, a stability judgment is performed to evaluate the stability of the Mosaic Warfare Network Model during the dynamic reorganization process and the overall functionality of the Mosaic Warfare Network Model when some real nodes are damaged in real time. The key nodes and weak nodes in the current Mosaic Warfare Network Model are preliminarily determined to provide data support for embedding test nodes.

[0118] Step 3: Based on the stability determination result, a test node is embedded in the mosaic warfare network model to break the mosaic warfare network model. Specifically, it includes:

[0119] (1) The test node uses random attacks and deliberate attacks to fight against real nodes. Random attacks refer to the test node randomly removing real nodes in the mosaic network model without distinction, and deliberate attacks refer to removing real nodes in order of importance. The test node fights against real nodes. When the i-th real node is destroyed, the load is distributed to its neighboring nodes, expressed as:

[0120] ;

[0121] in, represents the load distributed to the rth neighbor node, represents the set of neighbor nodes of the ith real node, represents the real node load of the ith node, represents the load capacity of the rth neighbor node, Represents the load capacity of the kth neighbor node.

[0122] like , it means that the rth neighbor node is overloaded and fails.

[0123] The damaged real nodes and failed neighbor nodes are used as weak nodes of the mosaic warfare network model. After the real nodes are damaged, the mosaic warfare network model is dynamically reorganized. The stability of the dynamically reorganized mosaic warfare network model is determined, and the test nodes are embedded according to the determination results, and the test nodes fight against the remaining real nodes.

[0124] Repeat the above process continuously to disconnect the links of the real nodes in the Mosaic Warfare network model, so that the real nodes are isolated, contained or removed as much as possible, and finally the purpose of breaking the Mosaic Warfare network model is achieved. Figure 3 As shown in the figure, the initial state of the mosaic network model is achieved. After the test node confrontation, the edges between the real nodes are partially disconnected, reaching the following Figure 4 Damage status shown.

[0125] (2) The real nodes that are difficult for the test nodes to counter are taken as the countermeasure difficulties. If there are countermeasure difficulties, the test nodes are combined with conventional attack methods.

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

[0127] ;

[0128] in, represents the source capacity of the mosaic warfare network model, M represents the number of edges in the mosaic warfare network model, Represents the source capacity of the mth edge.

[0129] Source capacity of mosaic warfare network model Evenly distributed to M links, the attack coefficient received by each link in the mosaic warfare network model It is expressed as:

[0130] ;

[0131] After combining conventional attack methods, all the links in the mosaic warfare network model are sorted from large to small according to the link load, and the source capacity of the mosaic warfare network model is Assign to front The attack coefficient received by each link in the mosaic warfare network model It is expressed as:

[0132] ;

[0133] in, represents the load of the mth edge, represents the load of the sth edge;

[0134] The total breaking coefficient is expressed as;

[0135] ;

[0136] in, Indicates the total breaking coefficient;

[0137] when When , the difficulty of confrontation is destroyed, where C represents the edge capacity of the mosaic warfare network model.

[0138] like Figure 5 As shown, this is the state of the Mosaic Warfare network model after it was broken. Most of the edges in the initial state are disconnected, and some real nodes become invalid nodes.

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

[0140] The attack effect is determined by the network efficiency F, which is expressed as:

[0141] ;

[0142] Where N represents the total number of real nodes. 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 can be expressed as:

[0144] ;

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

[0146] Furthermore, the difficult-to-confront part of the enemy mosaic warfare network model is copied to our combat network model, and the network efficiency of our combat network model is recorded as .

[0147] when When the network efficiency of our combat network model is The difference between the network efficiency F of the enemy mosaic warfare network model is taken as the surplus part and is recorded as , expressed as:

[0148] ;

[0149] Surplus The larger the value, the stronger the ability of our combat network to break the strong part of the enemy's mosaic warfare network. Therefore, by copying the difficult-to-fight parts of the mosaic warfare network model, the robustness of our combat network can be enhanced.

[0150] Example 2

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

[0152] The model building module is used to build a mosaic warfare network model containing a number of real nodes according to 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 warfare network model according to the real nodes to obtain a stability determination result.

[0154] The attack module is used to embed a test node in the mosaic warfare network model based on the stability judgment result, and the test node fights against the real node to attack the mosaic warfare network model.

[0155] Example 3

[0156] This embodiment provides a mosaic warfare network cracking 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 cracking method described in Example 1.

[0157] Example 4

[0158] This embodiment provides a computer-readable storage medium on which a computer program is stored. When the program is executed by a processor, the steps of the mosaic warfare network cracking method described in Example 1 are implemented.

[0159] Those skilled in the art will appreciate that the embodiments of the present application may be provided as methods, systems, or computer program products. Therefore, the present application may take the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware. Moreover, the present application may take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program codes.

[0160] The present application is described with reference to the flowcharts and / or block diagrams of the methods, devices (systems), and computer program products according to the embodiments of the present application. It should be understood that each process and / or box in the flowchart and / or block diagram, as well as the combination of the processes and / or boxes in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to generate a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 A process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0161] These computer program instructions may also be stored in a computer-readable memory capable of directing a computer or other programmable data processing device to operate in a specific manner, so that the instructions stored in the computer-readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 A process or multiple processes and / or boxes Figure 1 A function specified in one or more boxes.

[0162] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operating steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing instructions for implementing the process. Figure 1 A process or multiple processes and / or boxes Figure 1 The steps for the functions specified in one or more boxes.

[0163] The above is only a preferred embodiment of the present invention. It should be pointed out that for ordinary technicians in this technical field, several improvements and modifications can be made without departing from the technical principles of the present invention. These improvements and modifications should also be regarded as the scope of protection of the present invention.

Claims

1. A mosaic warfare network attack method, characterized in that: include: Constructing a mosaic warfare network model including a plurality of real nodes according to the 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 according to the real nodes to obtain a stability determination result; Based on the stability determination result, a test node is embedded in the mosaic warfare network model, and the test node is used to fight against the real node to break the mosaic warfare network model.

2. The mosaic warfare network attack method according to claim 1, characterized in that: The mosaic warfare network model is expressed as: ； in, represents the mosaic warfare network model, D represents the network layer of the mosaic warfare network model, V represents the real node, E represents the edge between the real nodes, P represents the attribute, Represents the real node attributes, It represents the edge attribute between real nodes, L represents the inter-layer link, M represents the mapping relationship, and T represents the information flow relationship; The categories of the real nodes include accusation nodes, judgment nodes, decision nodes and action nodes; the accusation nodes are used to observe the combat environment to obtain combat environment information, the judgment nodes are used to evaluate the current combat situation, the decision nodes are used to command operations, 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, wherein the physical layer includes action nodes, the information layer includes accusation nodes, and the cognitive layer includes judgment nodes and decision nodes.

3. The mosaic warfare network attack method according to claim 1, characterized in that: The determining of the stability of the mosaic warfare network model according to the real nodes to obtain a stability determination result includes: The participation matrix C of the mosaic warfare network model is constructed as follows: ； in, represents the number of shortest cycles containing the ith real node and the jth real node, Indicates the total number of real nodes; Based on the participation matrix C, the node closure is calculated, which is expressed as: ； in, represents the closure degree of the i-th real node, represents the number of shortest cycles that only contain the i-th real node; Sorting the node closure degrees to obtain the importance order of each real node; The number of adjacent nodes of any real node is taken as the degree, expressed as: ； in, represents the degree of the i-th real node, represents the edge weight between the ith real node and the jth real node. When the ith real node and the jth real node are not connected, ; The average degree of all real nodes is expressed as: ； in, Represents the average degree of all real nodes; The difference between the degrees of each real node is taken as the degree distribution, which is expressed as: ； in, represents the degree distribution, represents the original distribution of the degree of any real node; Calculate the edge probability with weight w, expressed as edge weight distribution : ； in, Represents the number of edges with weight w in the Mosaic Warfare network model; Calculate the sum of the edge weights connected to the i-th real node in the Mosaic Warfare network model, expressed as the node weight value : ； The closure degree of the mosaic warfare network model is expressed as: ； in, Indicates the closure of the Mosaic Warfare network model; The closedness of the mosaic warfare network model is compared with a set threshold to obtain the stability state of the mosaic warfare network model.

4. The mosaic warfare network attack method according to claim 1, characterized in that: Based on the stability determination result, a test node is embedded in the mosaic warfare network model, and the test node is used to fight against the real node to break the mosaic warfare network model, including: The test node fights against the real node. When the i-th real node is destroyed, the load is distributed to its neighboring nodes, which is expressed as: ； in, represents the load distributed to the rth neighbor node, represents the set of neighbor nodes of the ith real node, represents the real node load of the ith node, represents the load capacity of the rth neighbor node, represents the load capacity of the kth neighbor node; like , it means that the rth neighbor node is overloaded and fails; The damaged real nodes and failed neighbor nodes serve as weak nodes in the mosaic warfare network model.

5. The mosaic warfare network attack method according to claim 4 is characterized in that: After the said real nodes are destroyed, the Mosaic Warfare network model is dynamically reorganized; The stability of the dynamically reorganized mosaic warfare network model is determined, and test nodes are embedded based on the determination results, and the test nodes are used to fight against the remaining real nodes.

6. The mosaic warfare network attack method according to claim 4, characterized in that: Based on the stability determination result, a test node is embedded in the mosaic warfare network model, and the test node is used to fight against the real node to break the mosaic warfare network model, and further includes: The real nodes that are difficult for the test nodes to counter are used as the countermeasure difficulties. If there are countermeasure difficulties, the test nodes are combined with conventional attack methods; The source capacity of the mosaic warfare network model is expressed as: ； in, represents the source capacity of the mosaic warfare network model, M represents the number of edges in the mosaic warfare network model, represents the source capacity of the mth edge; The source capacity of the mosaic warfare network model Evenly distributed to M links, the attack coefficient received by each link in the mosaic warfare network model It is expressed as: ； After combining conventional attack methods, all the links in the mosaic warfare network model are sorted from large to small according to the link load, and the source capacity of the mosaic warfare network model is Assign to front The attack coefficient received by each link in the mosaic warfare network model It is expressed as: ； in, represents the load of the mth edge, represents the load of the sth edge; The total breaking coefficient is expressed as; ； in, Indicates the total breaking coefficient; when When, it destroys the difficulty of confrontation; Among them, C represents the edge capacity of the mosaic warfare network model.

7. The mosaic warfare network attack method according to claim 1, characterized in that: Also includes: The attack effect is determined by the network efficiency F, which is expressed as: ； Where N represents the total number of real nodes. 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 can be expressed as: ； The smaller the network efficiency F is, the better the attack effect is.

8. A mosaic warfare network attack system, characterized in that: include: A model building module, used to build a mosaic warfare network model including a plurality of real nodes according to the 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 according to the real nodes to obtain a stability determination result; The attack module is used to embed a test node in the mosaic warfare network model based on the stability judgment result, and the test node fights against the real node to attack the mosaic warfare network model.

9. A mosaic warfare network attack device, characterized in that: including processor and 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 cracking method described in any one of claims 1 to 7.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the program is executed by a processor, the steps of the mosaic warfare network cracking method described in any one of claims 1 to 7 are implemented.

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