Method and system for testing survivability based on dynamic heterogeneous network

Abstract

The embodiment of the invention provides an survivability test method and system based on a dynamic heterogeneous network, and the method comprises the steps: obtaining target data based on a multi-stage target smart grid; determining target survivability according to the target data; when it is determined that the target survivability is smaller than the preset survivability, executing a target operation to enable the target survivability to be larger than or equal to the preset survivability; wherein the target data comprises the target connectivity, the target fault tolerance, the target attack resistance and / or the target death degree of the multi-level target dynamic heterogeneous network. According to the method and the device, the sensing precision of the state of the dynamic heterogeneous network can be improved, so that the precision of the survivability test of the dynamic heterogeneous network is improved, and the robustness and survivability of the dynamic heterogeneous network are improved.

Description

Technical Field

[0001] The embodiments of the present application relate to the field of network security technology, and in particular to a method and system for testing the survivability of a dynamic heterogeneous network. Background Art

[0002] Survivability testing is mainly used to evaluate and improve the stability and recovery capabilities of complex networks in the face of failures, attacks or environmental changes.

[0003] At present, related technologies have problems such as low perception accuracy of dynamic heterogeneous network status, low accuracy of dynamic heterogeneous network invulnerability testing, and low robustness and survivability of dynamic heterogeneous networks.

[0004] Therefore, a new technical solution is urgently needed to solve the above technical problems. Summary of the Invention

[0005] According to an embodiment of the present application, a method and system for survivability testing based on a dynamic heterogeneous network are provided, which can improve the perception accuracy of the dynamic heterogeneous network status, thereby improving the accuracy of the dynamic heterogeneous network survivability test, and further improving the robustness and survivability of the dynamic heterogeneous network.

[0006] In a first aspect of the present application, a method for testing survivability of a dynamic heterogeneous network is proposed, comprising: Obtain target data based on multi-level target smart grid; Determine the target's invulnerability based on target data; When it is determined that the target invulnerability is less than the preset invulnerability, performing a target operation to make the target invulnerability greater than or equal to the preset invulnerability; The target data includes target connectivity, target fault tolerance, target anti-attack degree, and / or target death degree of a multi-level target dynamic heterogeneous network.

[0007] In some feasible implementations, the above method further includes: Obtain target information corresponding to a multi-level target dynamic heterogeneous network; Generate multi-level target smart grid based on target information; The target information includes: target network topology information, target node attribute information, target service and application mapping relationship information, target security configuration information, target network operation status information, target geographical distribution information, and / or target management interface information.

[0008] In some feasible implementations, the multi-level target smart grid is provided with corresponding multi-level target intelligent agents; Among them, the first-level target smart grid sets the first-level target intelligent agent to control the target dynamic heterogeneous network; The secondary target smart grid is equipped with a secondary target agent to control the target dynamic heterogeneous sub-network; The three-level target smart grid is equipped with three-level target intelligent agents to control the target dynamic heterogeneous local area network; And / or, a four-level target smart grid, setting up a four-level target intelligent agent to regulate the target network nodes.

[0009] In some feasible implementations, the multi-level target agent is used to determine corresponding target frequency information according to corresponding target network operation status information; According to the target frequency information, a target test operation is performed to obtain target data.

[0010] In some feasible implementations, determining the target invulnerability based on the target data includes: Determining a first target invulnerability based on a target connectivity of the target dynamic heterogeneous network and a corresponding first weight, a target fault tolerance and a corresponding second weight, a target attack resistance and a corresponding third weight, and / or a target lethality and a corresponding fourth weight; Determining a second target invulnerability based on the target connectivity of the target dynamic heterogeneous subnetwork and the corresponding first weight, the target fault tolerance and the corresponding second weight, the target attack resistance and the corresponding third weight, and / or the target lethality and the corresponding fourth weight; Determining a third target invulnerability based on the target connectivity of the target dynamic heterogeneous local area network and the corresponding first weight, the target fault tolerance and the corresponding second weight, the target attack resistance and the corresponding third weight, and / or the target lethality and the corresponding fourth weight; A fourth target indestructibility is determined based on the target connectivity of the target network node and the corresponding first weight, the target fault tolerance and the corresponding second weight, the target anti-attack degree and the corresponding third weight, and / or the target death degree and the corresponding fourth weight.

[0011] In some feasible implementations, the third weight corresponding to the target dynamic heterogeneous network is greater than the first weight; wherein the first weight, the second weight, and the fourth weight are equal; The first weight and the second weight corresponding to the target dynamic heterogeneous sub-network are equal; the third weight and the fourth weight are equal; wherein the fourth weight is less than the first weight; The first weight corresponding to the target dynamic heterogeneous local area network is equal to the fourth weight; the second weight is equal to the third weight; wherein the third weight is less than the first weight; The fourth weight corresponding to the target network node is greater than the first weight; The first weight is equal to the second weight; The second weight is greater than the third weight.

[0012] In some feasible implementations, when it is determined that the target invulnerability is less than the preset invulnerability, performing the target operation to make the target invulnerability greater than or equal to the preset invulnerability includes: Constructing a target abnormality digital twin model according to the target abnormality dynamic heterogeneous network, the target abnormality dynamic heterogeneous sub-network, the target abnormality dynamic heterogeneous local area network, and / or the target abnormality network node; Generate target fault evolution path based on target abnormal digital twin model; Execute target operations based on the target fault evolution path.

[0013] In some feasible implementations, the following further comprises: When it is determined that the target connectivity is less than the preset connectivity, the target operation includes: target redundant path startup operation, target virtual node introduction operation, and / or target topology reconstruction operation; When it is determined that the target fault tolerance is less than the preset fault tolerance, the target operation includes: a target node backup operation, a target redundant link addition operation, and / or a target containerized microservice startup operation; In the case where it is determined that the target attack resistance is less than the preset attack resistance, the target operation includes: a target firewall startup operation, a target attack source isolation operation, and / or a target honeypot trapping operation; When it is determined that the target death degree is greater than or equal to the preset death degree, the target operation includes: a target edge node construction operation, a target architecture decentralization operation, and / or a target load migration operation.

[0014] In some feasible implementations, the target mortality rate is determined according to the following formula: in, Used to indicate Momentary target dynamic heterogeneous network individuals The corresponding target death degree; Used to indicate the first scaling factor; Used to represent the target dynamic heterogeneous network individuals in the target historical data Basis risk; β Used to represent the second scaling factor; k Used to indicate target threat factors; M Used to indicate target threat factors k the number of Used to indicate target threat factors k The corresponding weight; Used to indicate Momentary target dynamic heterogeneous network individuals Target threat factors faced k Strength; Used to represent the third scaling factor; Used to represent target dynamic heterogeneous network individuals A collection of adjacent or related target dynamic heterogeneous network individuals; Used to indicate ( t -1) Dynamic and heterogeneous network individuals with momentary goals j probability of death.

[0015] In a second aspect of the present application, a survivability testing system based on a dynamic heterogeneous network is proposed, which is applicable to the above method and includes: An acquisition unit, used to acquire target data based on a multi-level target smart grid; A determination unit, configured to determine target invulnerability based on target data; an execution unit, configured to, when determining that the target invulnerability is less than a preset invulnerability, execute a target operation to make the target invulnerability greater than or equal to the preset invulnerability; The target data includes target connectivity, target fault tolerance, target anti-attack degree, and / or target death degree of a multi-level target dynamic heterogeneous network.

[0016] The embodiments of the present application provide a method and system for testing the invulnerability of a dynamic heterogeneous network, wherein the method includes: obtaining target data based on a multi-level target intelligent grid; determining the target invulnerability based on the target data; and, if it is determined that the target invulnerability is less than a preset invulnerability, performing a target operation to make the target invulnerability greater than or equal to the preset invulnerability; wherein the target data includes: target connectivity, target fault tolerance, target anti-attack degree, and / or target death degree of the multi-level target dynamic heterogeneous network. The present application can improve the perception accuracy of the dynamic heterogeneous network status, thereby improving the accuracy of dynamic heterogeneous network invulnerability testing, and further improving the robustness and survivability of the dynamic heterogeneous network.

[0017] It should be understood that the contents described in the Summary of the Invention are not intended to limit the key or important features of the embodiments of the present application, nor are they intended to limit the scope of the present application. Other features of the present application will become readily understood through the following description. BRIEF DESCRIPTION OF THE DRAWINGS

[0018] The above and other features, advantages and aspects of the embodiments of the present application will become more apparent with reference to the following detailed description in conjunction with the accompanying drawings. In the accompanying drawings, the same or similar reference numerals represent the same or similar elements, wherein: Figure 1A flowchart of a method for testing invulnerability based on a dynamic heterogeneous network according to an embodiment of the present application is shown in FIG. 1. Figure 2 A structural diagram of a system for testing invulnerability based on a dynamic heterogeneous network according to an embodiment of the present application is shown in FIG. 2. Figure 3 A structural diagram of an electronic device according to an embodiment of the present application is shown in FIG. 3. DETAILED DESCRIPTION

[0019] To make the objectives, technical solutions, and advantages of the embodiments of the present disclosure clearer, the following will be combined with the accompanying drawings for the embodiments of the present disclosure to make a clear and complete description of the technical solutions in the embodiments of the present disclosure. Obviously, the described embodiments are some but not all of the embodiments of the present disclosure. Based on the embodiments in the present disclosure, all other embodiments obtained by a person of ordinary skill in the art without creative work fall within the protection scope of the present disclosure.

[0020] In addition, the term "and / or" herein is only to describe the association relationship of the associated objects, which means that there can be three relationships, for example, A and / or B can mean that there are three cases of A alone, A and B together, and B alone. In addition, the character " / " herein generally represents an "or" relationship between the front and rear associated objects.

[0021] In a first aspect, the embodiments of the present application provide a method for testing invulnerability based on a dynamic heterogeneous network, which can be applied to the fields of military intelligence, city perception, Internet of Things monitoring, and / or network defense. Figure 1 A flowchart of a method 100 for testing invulnerability based on a dynamic heterogeneous network according to an embodiment of the present application is shown in FIG. 1. Figure 1 As shown in FIG. 1, the method 100 includes the following steps. Step S1: obtaining target data based on a multi-level target wisdom grid; wherein the target data includes target connectivity, target fault tolerance, target attack resistance, and / or target mortality of the multi-level target dynamic heterogeneous network.

[0022] Exemplarily, the target connectivity of the multi-level target dynamic heterogeneous network can be obtained based on the multi-level target wisdom grid, for determining the communication capability of the multi-level target dynamic heterogeneous network.

[0023] Exemplarily, the target fault tolerance of the multi-level target dynamic heterogeneous network can be obtained based on the multi-level target wisdom grid, for determining the capability of the multi-level target dynamic heterogeneous network to maintain basic functions in the presence of partial component failures.

[0024] Exemplarily, based on the above-mentioned multi-level target smart grid, the target anti-attack degree of the multi-level target dynamic heterogeneous network can be obtained to determine the ability of the multi-level target dynamic heterogeneous network to resist external attacks.

[0025] Exemplarily, based on the multi-level target smart grid, the target death degree of the multi-level target dynamic heterogeneous network can be obtained to determine the extent to which the multi-level target dynamic heterogeneous network has failed or been destroyed.

[0026] In some feasible implementations, before executing step S1, the method further includes: Obtain target information corresponding to a multi-level target dynamic heterogeneous network; wherein the target information includes: target network topology information, target node attribute information, target service and application mapping relationship information, target security configuration information, target network operation status information, target geographical distribution information, and / or target management interface information.

[0027] Exemplarily, the above-mentioned target network topology information may include: the number and type information of each network node corresponding to the multi-level target dynamic heterogeneous network, such as: router information, switch information, and / or terminal device information, etc.; link connection relationship information corresponding to the multi-level target dynamic heterogeneous network, such as: adjacency matrix information, and / or graph structure information, etc.; and / or, path weight information between each network node corresponding to the multi-level target dynamic heterogeneous network, such as: delay information, bandwidth information, and / or packet loss rate information, etc.

[0028] Exemplarily, the above-mentioned target node attribute information may include: role information of each network node corresponding to the multi-level target dynamic heterogeneous network, such as: core node information, edge node information, and / or terminal node information, etc.; performance parameter information of each network node, such as: CPU information, memory information, and / or storage information, etc.; redundancy or backup capability information, and / or virtualization information, such as: container information, and / or virtual machine information, etc.

[0029] Exemplarily, the above-mentioned target service and application mapping relationship information may include: service list information running on each network node corresponding to the multi-level target dynamic heterogeneous network, such as: database information, Web service information, and / or control center information, etc.; dependency information between individual services, such as: call chain information in the microservice architecture, etc.; service quality requirement information, such as: delay information, availability information, and / or throughput information.

[0030] Exemplarily, the target security configuration information may include: firewall deployment information, security component information, such as intrusion detection system information; encrypted communication information, identity authentication mechanism information, vulnerability repair information, and / or attack record information, etc.

[0031] Exemplarily, the above-mentioned target network operation status information may include: historical fault record information, such as: downtime information, recovery time information; abnormal event log information, such as: traffic surge information, abnormal access information; and / or, anti-destruction assessment historical value information, etc.

[0032] Exemplarily, the above-mentioned target geographic distribution information may include: geographic location information of each network node corresponding to the multi-level target dynamic heterogeneous network, such as: city information, building information, and / or, computer room information, etc.; network area division information, such as: subnet information, and / or, VLAN information, etc.; and / or, cross-domain or cross-organizational collaboration information, etc.

[0033] Exemplarily, the above-mentioned target management interface information may include: management protocol information, such as SSH information, SNMP information, and / or REST API information, etc.; and / or supported automation tool information, such as Ansible information, Kubernetes information, and / or SDN controller information, etc.

[0034] Generate a multi-level target smart grid based on target information.

[0035] For example, the information on the number and type of network nodes corresponding to the multi-level target dynamic heterogeneous network, the link connection relationship information corresponding to the multi-level target dynamic heterogeneous network, the path weight information between the network nodes corresponding to the multi-level target dynamic heterogeneous network; the role information of the network nodes corresponding to the multi-level target dynamic heterogeneous network, the performance parameter information, redundancy or backup capability information, and virtualization information of the network nodes; the service list information running on the network nodes corresponding to the multi-level target dynamic heterogeneous network, the dependency relationship information between the services, and the service quality requirement information; the firewall deployment information, security component information, encrypted communication information, identity authentication information, etc. Verification mechanism information, vulnerability repair information, attack record information; historical fault record information, abnormal event log information, abnormal access information, anti-destruction assessment historical value information; geographical location information of each network node corresponding to the multi-level target dynamic heterogeneous network, network area division information, cross-domain or cross-organizational collaboration information; management protocol information, and / or supported automation tool information, etc., divide the monitoring area into several grid units to generate the above-mentioned multi-level target smart grid, wherein each grid unit can be used to represent a logical or physical location, and is used to record the status information of the corresponding target dynamic heterogeneous network structure, threat level information, and / or resource distribution information, etc.

[0036] Therefore, the above method can accurately construct a multi-level target smart grid based on the above-mentioned target network topology information, target node attribute information, target service and application mapping relationship information, target security configuration information, target network operation status information, target geographic distribution information, and / or target management interface information, thereby realizing hierarchical acquisition of target data to improve the acquisition accuracy and efficiency of target data; thereby improving the perception accuracy of dynamic heterogeneous network status; hierarchical execution of target operations to achieve hierarchical improvement of the anti-destruction degree based on dynamic heterogeneous networks, thereby improving the accuracy of dynamic heterogeneous network anti-destruction testing and improving the robustness and survivability of dynamic heterogeneous networks.

[0037] In some feasible implementations, the multi-level target smart grid is provided with corresponding multi-level target intelligent agents.

[0038] Among them, the first-level target smart grid sets up a first-level target intelligent body to control the target dynamic heterogeneous network.

[0039] It should be noted that the aforementioned primary target smart grid employs a primary target agent to regulate the target dynamic heterogeneous network, i.e., the global network. This primary target agent is used for comprehensive coordination and / or strategic planning, and possesses high computing power, communication bandwidth, and strong learning capabilities.

[0040] Exemplarily, the above-mentioned first-level target smart grid equipped with a first-level target intelligent body can perceive the global operating status of the target dynamic heterogeneous network based on the geographic information system and / or the Internet of Things system, perform topology and optimization on the target dynamic heterogeneous network as a whole, and / or respond to major events, wherein the above-mentioned major events may include: large-scale network attack events, large-scale network disconnection events, and / or large-scale network failure events, etc.

[0041] Among them, the secondary target smart grid is equipped with a secondary target intelligent agent to control the target dynamic heterogeneous sub-network.

[0042] It should be noted that the aforementioned secondary target smart grid is equipped with a secondary target agent to control the target dynamic heterogeneous sub-network, i.e., the regional network. The secondary target agent is used for sub-network management and / or task allocation, and has medium computing power and strong fault tolerance.

[0043] Exemplarily, the above-mentioned secondary target smart grid with secondary target intelligent bodies can monitor and diagnose the status of the target dynamic heterogeneous sub-network, i.e., the regional network, based on the controller, edge computing, and / or local optimization algorithm, allocate network resources of the target dynamic heterogeneous sub-network, i.e., the regional network to improve load balancing, and / or detect and respond to network threats of the target dynamic heterogeneous sub-network, i.e., the regional network, etc.

[0044] The third target smart grid is provided with a third target agent for regulating the target dynamic heterogeneous local area network.

[0045] It should be noted that the third target smart grid is provided with a third target agent for regulating the target dynamic heterogeneous local area network, i.e., a local LAN or a small-range network. The third target agent is used for fast response and / or local optimization, with low latency and high execution degree.

[0046] Illustratively, the third target smart grid provided with the third target agent can control the target dynamic heterogeneous local area network, i.e., the local LAN or the small-range network, in real time based on a lightweight protocol, an embedded AI chip, and / or a local database cache data, etc., manage the access and authority of the network nodes of the target dynamic heterogeneous local area network, i.e., the local LAN or the small-range network, in real time, and / or evaluate and optimize the network quality of the target dynamic heterogeneous local area network, i.e., the local LAN or the small-range network, in real time, etc.

[0047] And / or, the fourth target smart grid is provided with a fourth target agent for regulating the target network node.

[0048] It should be noted that the fourth target smart grid is provided with a fourth target agent for regulating the target network node, i.e., a single device or terminal. The fourth target agent is used for state monitoring and / or simple repair of the single device or terminal. The fourth target agent is a lightweight agent with low power consumption.

[0049] Illustratively, the fourth target smart grid provided with the fourth target agent can detect the running state of a single target network node based on a low-power communication protocol and / or a microcontroller, etc.; regulate the running state of the single target network node in real time, such as sleep regulation, wake-up regulation, and / or switching communication channel regulation, etc.; and perform local security protection on the single target network node, such as anti-tampering or identity authentication, etc.

[0050] Thus, the above method can make the control instructions and feedbacks between the first target wisdom grid and the fourth target wisdom grid form a closed loop, thereby promoting the vertical information collaboration between the first target wisdom grid and the fourth target wisdom grid; make each level of target dynamic heterogeneous network have autonomous decision-making ability at this level, thereby realizing the horizontal autonomy of the first target wisdom grid to the fourth target wisdom grid; through hierarchical scheduling, the optimal resource allocation of the multi-level target wisdom grid can be realized; reduce the influence of local anomalies of the multi-level target wisdom grid on the whole multi-level target wisdom grid, improve the fault tolerance and anomaly isolation of the multi-level target wisdom grid; make the multi-level target wisdom grid support hierarchical expansion, so as to improve the expansibility of the multi-level target wisdom grid; further improve the construction precision of the multi-level target wisdom grid; thereby further improve the acquisition precision and efficiency of the target data; further improve the perception accuracy of the dynamic heterogeneous network state, and further improve the precision of the dynamic heterogeneous network invulnerability test, and further improve the robustness and survivability of the dynamic heterogeneous network.

[0051] In some possible embodiments, the above multi-level target agent is configured to determine corresponding target frequency information according to corresponding target network running state information; and perform a target test operation to obtain target data according to the target frequency information.

[0052] For example, the first target agent can determine corresponding target frequency information according to the running state information of the target dynamic heterogeneous network, i.e., the global network, to perform a target test operation to obtain the target connectivity, target fault tolerance, target attack resistance, and / or target mortality of the target dynamic heterogeneous network, i.e., the global network.

[0053] For example, the second target agent can determine corresponding target frequency information according to the running state information of the target dynamic heterogeneous sub-network, i.e., the regional network, to perform a target test operation to obtain the target connectivity, target fault tolerance, target attack resistance, and / or target mortality of the target dynamic heterogeneous sub-network, i.e., the regional network.

[0054] Exemplarily, the above-mentioned three-level target intelligent agent can determine the corresponding target frequency information based on the operating status information of the target dynamic heterogeneous local area network, i.e., the local LAN or a small-scale network, to perform target test operations to obtain the target connectivity, target fault tolerance, target anti-attack degree, and / or target death degree corresponding to the target dynamic heterogeneous local area network, i.e., the local LAN or a small-scale network.

[0055] Exemplarily, the above-mentioned four-level target intelligent agent can determine the corresponding target frequency information based on the operating status information of the target network node, i.e., a single device or terminal, to perform target test operations to obtain the target connectivity, target fault tolerance, target anti-attack degree, and / or target death degree corresponding to the target network node, i.e., a single device or terminal.

[0056] It should be noted that the above-mentioned first-level target intelligent agent, second-level target intelligent agent, third-level target intelligent agent, and / or fourth-level target intelligent agent can determine the target dynamic heterogeneous network, target dynamic heterogeneous sub-network, target dynamic heterogeneous local area network, and / or the network load information, service quality information, and / or security threat level information corresponding to the target network node based on the above-mentioned target network operation status information, and determine the above-mentioned target frequency information, so as to perform corresponding target test operations on the target dynamic heterogeneous network, target dynamic heterogeneous sub-network, target dynamic heterogeneous local area network, and / or target network node based on the above-mentioned target frequency information to obtain the corresponding target connectivity, target fault tolerance, target anti-attack degree, and / or target death degree.

[0057] Specifically, the above-mentioned first-level target intelligent agent can perform global network topology detection test, key node reachability detection test, overall bandwidth utilization monitoring test, and / or security policy consistency check test on the target dynamic heterogeneous network based on the above-mentioned target frequency information, so as to obtain the target connectivity, target fault tolerance, target anti-attack degree, and / or target death degree corresponding to the target dynamic heterogeneous network.

[0058] Specifically, the above-mentioned secondary target intelligent agent can perform regional link quality detection tests, subnet internal node communication status tests, service load balancing analysis, and / or regional security incident response mechanism verification tests on the target dynamic heterogeneous subnetwork based on the above-mentioned target frequency information, so as to obtain the target connectivity, target fault tolerance, target anti-attack degree, and / or target death degree corresponding to the target dynamic heterogeneous subnetwork.

[0059] Specifically, the above-mentioned three-level target intelligent agent can perform local area network device connection status testing, local service access testing, network congestion or conflict testing, and / or permission control and access log analysis on the target dynamic heterogeneous local area network based on the above-mentioned target frequency information, so as to obtain the target connectivity, target fault tolerance, target anti-attack degree, and / or target death degree corresponding to the target dynamic heterogeneous local area network.

[0060] Specifically, the above-mentioned four-level target intelligent agent can perform Ping test, port open status scan test, CPU, memory, disk resource usage analysis, application layer interface call test, and / or log analysis and abnormal behavior identification on the target network node based on the above-mentioned target frequency information to obtain the target connectivity, target fault tolerance, target anti-attack degree, and / or target death degree corresponding to the target network node.

[0061] Among them, the above-mentioned target frequency information is positively correlated with the above-mentioned network load information, the above-mentioned service quality information and the above-mentioned security threat level information, that is, the higher the network load, the higher the service quality requirement, and / or the higher the security threat level, the higher the target frequency corresponding to executing the target test operation.

[0062] Therefore, the above method can accurately determine the target frequency information corresponding to the target dynamic heterogeneous network, the target dynamic heterogeneous subnetwork, the target dynamic heterogeneous local area network, and / or the target network node based on the above target network operation status information, so that the above-mentioned first-level target intelligent agent, the second-level target intelligent agent, the third-level target intelligent agent, and / or the fourth-level target intelligent agent can accurately perform target test operations according to the above-mentioned target frequency information to determine the target connectivity, target fault tolerance, target anti-attack degree, and / or target death degree corresponding to the target dynamic heterogeneous network, the target dynamic heterogeneous subnetwork, the target dynamic heterogeneous local area network, and / or the target network node, thereby improving the accuracy of the dynamic heterogeneous network anti-destruction test, and further improving the robustness and survivability of the dynamic heterogeneous network.

[0063] Step S2: Determine the target invulnerability based on the target data.

[0064] Exemplarily, the target survivability corresponding to the above-mentioned target dynamic heterogeneous network, target dynamic heterogeneous subnetwork, target dynamic heterogeneous local area network, and / or target network nodes can be determined based on the target connectivity, target fault tolerance, target anti-attack degree, and / or target death degree corresponding to the above-mentioned target dynamic heterogeneous network, target dynamic heterogeneous subnetwork, target dynamic heterogeneous local area network, and / or target network nodes.

[0065] In some feasible implementations, determining the target invulnerability based on the target data includes: determining the first target invulnerability according to the target connectivity and the corresponding first weight, the target fault tolerance and the corresponding second weight, the target attack resistance and the corresponding third weight, and / or the target death rate and the corresponding fourth weight of the target dynamic heterogeneous network; determining the second target invulnerability according to the target connectivity and the corresponding first weight, the target fault tolerance and the corresponding second weight, the target attack resistance and the corresponding third weight, and / or the target death rate and the corresponding fourth weight of the target dynamic heterogeneous sub-network; determining the third target invulnerability according to the target connectivity and the corresponding first weight, the target fault tolerance and the corresponding second weight, the target attack resistance and the corresponding third weight, and / or the target death rate and the corresponding fourth weight of the target dynamic heterogeneous local network; determining the fourth target invulnerability according to the target connectivity and the corresponding first weight, the target fault tolerance and the corresponding second weight, the target attack resistance and the corresponding third weight, and / or the target death rate and the corresponding fourth weight of the target network node.

[0066] Specifically, the first target invulnerability, the second target invulnerability, the third target invulnerability, and / or the fourth target invulnerability can be determined according to the following formula: wherein, R is used to represent the first target invulnerability, the second target invulnerability, the third target invulnerability, and / or the fourth target invulnerability; is used to represent the first weight; C is used to represent the target connectivity; is used to represent the second weight; F is used to represent the target fault tolerance; is used to represent the third weight; A is used to represent the target attack resistance; is used to represent the fourth weight; D is used to represent the target death rate.

[0067] Therefore, the above method can improve the determination accuracy of the target invulnerability of the target dynamic heterogeneous network, the target dynamic heterogeneous sub-network, the target dynamic heterogeneous local network, and / or the target network node, thereby improving the execution accuracy of the target operation, and further improving the robustness and survivability of the target dynamic heterogeneous network, the target dynamic heterogeneous sub-network, the target dynamic heterogeneous local network, and / or the target network node.

[0068] In some possible implementations, the third weight corresponding to the target dynamic heterogeneous network is greater than the first weight; wherein the first weight, the second weight, and the fourth weight are equal.

[0069] For example, the first weight corresponding to the target dynamic heterogeneous network can be set to 0.2; the second weight to 0.2; the third weight to 0.4; and the fourth weight to 0.2 to improve the security and anti-attack capability of the target dynamic heterogeneous network.

[0070] In some feasible implementations, the first weight and the second weight corresponding to the target dynamic heterogeneous sub-network are equal; the third weight and the fourth weight are equal; wherein the fourth weight is less than the first weight.

[0071] For example, the first weight corresponding to the target dynamic heterogeneous subnetwork may be set to 0.3; the second weight to 0.3; the third weight to 0.2; and the fourth weight to 0.2 to improve the stability and fault tolerance of the target dynamic heterogeneous subnetwork.

[0072] In some feasible implementations, the first weight corresponding to the target dynamic heterogeneous local area network is equal to the fourth weight; the second weight is equal to the third weight; wherein the third weight is less than the first weight.

[0073] For example, the first weight corresponding to the target dynamic heterogeneous local area network can be set to 0.4; the second weight to 0.1; the third weight to 0.1; and the fourth weight to 0.4 to improve the communication guarantee capability of the target dynamic heterogeneous local area network and its tolerance to failure of target network nodes.

[0074] In some feasible implementations, the fourth weight corresponding to the target network node is greater than the first weight; the first weight is equal to the second weight; and the second weight is greater than the third weight.

[0075] For example, the first weight corresponding to the target network node can be set to 0.2; the second weight to 0.2; the third weight to 0.1; and the fourth weight to 0.5 to reduce the influence of the failed target network node and increase the death penalty capability to increase the sensitivity to the dead target network node.

[0076] Therefore, the above method can further improve the determination accuracy of the target anti-destruction degree corresponding to the target dynamic heterogeneous network, the target dynamic heterogeneous sub-network, the target dynamic heterogeneous local area network, and / or the target network node through differentiated settings of the first weight, the second weight, the third weight, and / or the fourth weight corresponding to the target dynamic heterogeneous network, the target dynamic heterogeneous sub-network, the target dynamic heterogeneous local area network, and / or the target network node, thereby improving the execution accuracy of the target operation, so as to enhance the robustness and survivability of the target dynamic heterogeneous network, the target dynamic heterogeneous sub-network, the target dynamic heterogeneous local area network, and / or the target network node.

[0077] Step S3: When it is determined that the target invulnerability is less than the preset invulnerability, a target operation is performed to make the target invulnerability greater than or equal to the preset invulnerability.

[0078] Exemplarily, in a case where the primary target intelligent agent determines that the target inviolability of the target dynamic heterogeneous network corresponds to is less than the corresponding preset inviolability, the target operation can be controlled to be executed to make the target inviolability of the target dynamic heterogeneous network correspond to be greater than or equal to the corresponding preset inviolability.

[0079] Exemplarily, in a case where the secondary target intelligent agent determines that the target inviolability of the target dynamic heterogeneous sub-network corresponds to is less than the corresponding preset inviolability, the target operation can be controlled to be executed to make the target inviolability of the target dynamic heterogeneous sub-network correspond to be greater than or equal to the corresponding preset inviolability.

[0080] Exemplarily, in a case where the tertiary target intelligent agent determines that the target inviolability of the target dynamic heterogeneous local area network corresponds to is less than the corresponding preset inviolability, the target operation can be controlled to be executed to make the target inviolability of the target dynamic heterogeneous local area network correspond to be greater than or equal to the corresponding preset inviolability.

[0081] Exemplarily, in a case where the quaternary target intelligent agent determines that the target inviolability of the target network node corresponds to is less than the corresponding preset inviolability, the target operation can be controlled to be executed to make the target inviolability of the target network node correspond to be greater than or equal to the corresponding preset inviolability.

[0082] In some possible implementations, the above-mentioned execution of the target operation to make the target inviolability greater than or equal to the preset inviolability in a case where the target inviolability is determined to be less than the preset inviolability includes: According to the target abnormal dynamic heterogeneous network, the target abnormal dynamic heterogeneous sub-network, the target abnormal dynamic heterogeneous local area network, and / or the target abnormal network node, a target abnormal digital twin model is constructed; a target fault evolution path is generated according to the target abnormal digital twin model; and the target operation is executed according to the target fault evolution path.

[0083] Exemplarily, when the first-level target intelligent agent determines that the target indestructibility corresponding to the target dynamic heterogeneous network is less than the corresponding preset indestructibility, the second-level target intelligent agent determines that the target indestructibility corresponding to the target dynamic heterogeneous subnetwork is less than the corresponding preset indestructibility, the third-level target intelligent agent determines that the target indestructibility corresponding to the target dynamic heterogeneous local area network is less than the corresponding preset indestructibility, and / or the fourth-level target intelligent agent determines that the target indestructibility corresponding to the target network node is less than the corresponding preset indestructibility, a target abnormal digital twin model can be constructed based on the target fault tree, target Bayesian network, and / or target Markov chain, etc., according to the target abnormal dynamic heterogeneous network, target abnormal dynamic heterogeneous subnetwork, target abnormal dynamic heterogeneous local area network, and / or target abnormal network node; based on reinforcement learning, and / or graph neural network, etc., according to the target abnormal digital twin model, a target fault evolution path is generated to predict the fault propagation trend; and according to the target fault evolution path, the target operation is executed.

[0084] Among them, the above-mentioned target operations may include: target resource scheduling operations, target isolation and repair operations, target redundant deployment operations, target topology reconstruction operations, target security protection operations, and / or target early warning notification operations.

[0085] Specifically, the target resource scheduling operation is used to migrate critical tasks to target high-availability nodes. The target isolation and repair operation is used to isolate or restart services of nodes that are about to fail. The target redundancy deployment operation is used to add backup nodes to critical paths. The target topology reconstruction operation is used to re-plan communication paths to bypass high-risk areas. The target security protection operation is used to enhance the security of attacked nodes, such as strengthening firewalls, encryption, and / or access control. The target early warning notification operation is used to send alarm information to target devices, where the target devices may include mobile devices belonging to target operation and maintenance personnel.

[0086] Therefore, the above method can accurately construct a target abnormal digital twin model based on the target abnormal dynamic heterogeneous network, the target abnormal dynamic heterogeneous subnetwork, the target abnormal dynamic heterogeneous local area network, and / or the target abnormal network node; accurately predict and generate the target fault evolution path based on the target abnormal digital twin model; accurately pre-execute the target operation based on the target fault evolution path to ensure that the target anti-destruction degree of the multi-level target dynamic heterogeneous network is greater than or equal to the preset anti-destruction degree, thereby accurately improving the robustness and survivability of the dynamic heterogeneous network.

[0087] In some feasible implementations, it further includes: when it is determined that the target connectivity is less than the preset connectivity, the target operation includes: a target redundant path startup operation, a target virtual node introduction operation, and / or a target topology reconstruction operation.

[0088] Exemplarily, when the first-level target intelligent agent determines that the target connectivity corresponding to the target dynamic heterogeneous network is less than the preset connectivity, the first-level target intelligent agent can control the execution of the corresponding target redundant path startup operation, target virtual node introduction operation, and / or target topology reconstruction operation.

[0089] Exemplarily, when the secondary target agent determines that the target connectivity corresponding to the target dynamic heterogeneous subnetwork is less than the preset connectivity, the secondary target agent can control the execution of the corresponding target redundant path startup operation, target virtual node introduction operation, and / or target topology reconstruction operation.

[0090] Exemplarily, when the third-level target intelligent agent determines that the target connectivity corresponding to the target dynamic heterogeneous local area network is less than the preset connectivity, the third-level target intelligent agent can control the execution of the corresponding target redundant path startup operation, target virtual node introduction operation, and / or target topology reconstruction operation.

[0091] Exemplarily, when the fourth-level target intelligent agent determines that the target connectivity corresponding to the target network node is less than the preset connectivity, the fourth-level target intelligent agent can control the execution of the corresponding target redundant path startup operation, target virtual node introduction operation, and / or target topology reconstruction operation.

[0092] Therefore, the above method can achieve the precise execution of target redundant path startup operation, target virtual node introduction operation, and / or target topology reconstruction operation when it is determined that the target dynamic heterogeneous network, target dynamic heterogeneous subnetwork, target dynamic heterogeneous local area network, and / or the target network node corresponding target connectivity is less than the preset connectivity, so as to ensure that the target dynamic heterogeneous network, target dynamic heterogeneous subnetwork, target dynamic heterogeneous local area network, and / or the target network node corresponding target indestructibility is greater than or equal to the corresponding preset indestructibility, thereby accurately improving the robustness and survivability of the multi-level target dynamic heterogeneous network.

[0093] In some feasible implementations, the method further includes: when it is determined that the target fault tolerance is less than the preset fault tolerance, the target operation includes: a target node backup operation, a target redundant link addition operation, and / or a target containerized microservice startup operation.

[0094] Exemplarily, when the first-level target intelligent agent determines that the target tolerance corresponding to the target dynamic heterogeneous network is less than the preset tolerance, the first-level target intelligent agent can control the execution of the corresponding target node backup operation, target redundant link addition operation, and / or target containerized microservice startup operation.

[0095] Exemplarily, when the secondary target agent determines that the target tolerance corresponding to the target dynamic heterogeneous subnetwork is less than the preset tolerance, the secondary target agent can control the execution of the corresponding target node backup operation, target redundant link addition operation, and / or target containerized microservice startup operation.

[0096] Exemplarily, when the third-level target agent determines that the target tolerance corresponding to the target dynamic heterogeneous local area network is less than the preset tolerance, the third-level target agent can control the execution of the corresponding target node backup operation, target redundant link addition operation, and / or target containerized microservice startup operation.

[0097] Exemplarily, when the fourth-level target agent determines that the target tolerance corresponding to the target network node is less than the preset tolerance, the fourth-level target agent can control the execution of the corresponding target node backup operation, target redundant link addition operation, and / or target containerized microservice startup operation.

[0098] Therefore, the above method can achieve the precise execution of target node backup operations, target redundant link addition operations, and / or target containerized microservice startup operations when it is determined that the target tolerance corresponding to the target dynamic heterogeneous network, target dynamic heterogeneous subnetwork, target dynamic heterogeneous local area network, and / or target network node is less than the preset tolerance, so as to ensure that the target indestructibility corresponding to the target dynamic heterogeneous network, target dynamic heterogeneous subnetwork, target dynamic heterogeneous local area network, and / or target network node is greater than or equal to the corresponding preset indestructibility, thereby accurately improving the robustness and survivability of the multi-level target dynamic heterogeneous network.

[0099] In some feasible implementations, it also includes: when it is determined that the target attack resistance is less than the preset attack resistance, the target operation includes: a target firewall startup operation, a target attack source isolation operation, and / or a target honeypot trapping operation.

[0100] Exemplarily, when the first-level target intelligent agent determines that the target attack degree corresponding to the target dynamic heterogeneous network is less than the preset attack degree, the first-level target intelligent agent can control the execution of the corresponding target firewall startup operation, target attack source isolation operation, and / or target honeypot trapping operation.

[0101] Exemplarily, when the secondary target intelligent agent determines that the target attack degree corresponding to the target dynamic heterogeneous subnetwork is less than the preset attack degree, the secondary target intelligent agent can control the execution of the corresponding target firewall startup operation, target attack source isolation operation, and / or target honeypot trapping operation.

[0102] Exemplarily, when the third-level target intelligent agent determines that the target attack degree corresponding to the target dynamic heterogeneous local area network is less than the preset attack degree, the third-level target intelligent agent can control the execution of the corresponding target firewall startup operation, target attack source isolation operation, and / or target honeypot trapping operation.

[0103] Exemplarily, when the fourth-level target intelligent agent determines that the target attack degree corresponding to the target network node is less than the preset attack degree, the fourth-level target intelligent agent can control the execution of the corresponding target firewall startup operation, target attack source isolation operation, and / or target honeypot trapping operation.

[0104] Therefore, the above method can achieve the precise execution of the target firewall startup operation, the target attack source isolation operation, and / or the target honeypot trapping operation when it is determined that the target dynamic heterogeneous network, the target dynamic heterogeneous subnetwork, the target dynamic heterogeneous local area network, and / or the target network node corresponds to a target anti-attack degree that is less than a preset anti-attack degree, so as to ensure that the target dynamic heterogeneous network, the target dynamic heterogeneous subnetwork, the target dynamic heterogeneous local area network, and / or the target network node corresponds to a target anti-destruction degree that is greater than or equal to the corresponding preset anti-destruction degree, thereby accurately improving the robustness and survivability of the multi-level target dynamic heterogeneous network.

[0105] In some feasible implementations, it also includes: when it is determined that the target death degree is greater than or equal to the preset death degree, the target operation includes: a target edge node construction operation, a target architecture decentralization operation, and / or a target load migration operation.

[0106] Exemplarily, when the first-level target intelligent agent determines that the target death degree corresponding to the target dynamic heterogeneous network is greater than or equal to the preset death degree, the first-level target intelligent agent can control the execution of the corresponding target edge node construction operation, target architecture decentralization operation, and / or target load migration operation.

[0107] Exemplarily, when the secondary target agent determines that the target death degree corresponding to the target dynamic heterogeneous subnetwork is greater than or equal to the preset death degree, the secondary target agent can control the execution of the corresponding target edge node construction operation, target architecture decentralization operation, and / or target load migration operation.

[0108] Exemplarily, when the third-level target agent determines that the target death degree corresponding to the target dynamic heterogeneous local area network is greater than or equal to the preset death degree, the third-level target agent can control the execution of the corresponding target edge node construction operation, target architecture decentralization operation, and / or target load migration operation.

[0109] Exemplarily, when the fourth-level target agent determines that the target death degree corresponding to the target network node is greater than or equal to the preset death degree, the fourth-level target agent can control the execution of the corresponding target edge node construction operation, target architecture decentralization operation, and / or target load migration operation.

[0110] Therefore, the above method can achieve the precise execution of target edge node construction operations, target architecture decentralization operations, and / or target load migration operations when it is determined that the target dynamic heterogeneous network, target dynamic heterogeneous subnetwork, target dynamic heterogeneous local area network, and / or the target network node corresponding to the target death degree is greater than or equal to the preset death degree, so as to ensure that the target dynamic heterogeneous network, target dynamic heterogeneous subnetwork, target dynamic heterogeneous local area network, and / or the target network node corresponding to the target anti-destruction degree is greater than or equal to the corresponding preset anti-destruction degree, thereby accurately improving the robustness and survivability of the multi-level target dynamic heterogeneous network.

[0111] In some feasible implementations, the target mortality rate is determined according to the following formula: in, Used to indicate Momentary target dynamic heterogeneous network individuals The corresponding target death degree; Used to indicate the first scaling factor; Used to represent the target dynamic heterogeneous network individuals in the target historical data Basis risk; β Used to represent the second scaling factor; k Used to indicate target threat factors; M Used to indicate target threat factors k the number of Used to indicate target threat factors k The corresponding weight; Used to indicate Momentary target dynamic heterogeneous network individuals Target threat factors faced k Strength; Used to represent the third scaling factor; Used to represent target dynamic heterogeneous network individuals A collection of adjacent or related target dynamic heterogeneous network individuals; Used to indicate ( t -1) Dynamic and heterogeneous network individuals with momentary goals j probability of death.

[0112] It should be noted that the above formula It is used to determine the historical death risk baseline of individuals in the target dynamic heterogeneous network; Used to determine the risk of multiple real-time threat factors superimposed; Used to determine the maximum risk from neighboring individuals or systematically connected individuals at the previous moment.

[0113] It should be noted that the above-mentioned target dynamic heterogeneous network individuals may include: target dynamic heterogeneous network individuals, target dynamic heterogeneous sub-network individuals, target dynamic heterogeneous local area network individuals, and / or target network node individuals.

[0114] Therefore, based on the above formula, the above method can accurately determine the historical death risk baseline, real-time threat superposition risk and cascade transmission risk corresponding to the target dynamic heterogeneous network individual, target dynamic heterogeneous sub-network individual, target dynamic heterogeneous local area network individual, and / or the target network node individual, so as to improve the determination accuracy of the death degree corresponding to the target dynamic heterogeneous network individual, target dynamic heterogeneous sub-network individual, target dynamic heterogeneous local area network individual, and / or the target network node individual, thereby further improving the determination accuracy of the target indestructibility. When it is determined that the target indestructibility corresponding to the target dynamic heterogeneous network individual, target dynamic heterogeneous sub-network individual, target dynamic heterogeneous local area network individual, and / or the target network node individual is less than the preset indestructibility, the target operation is accurately executed to make the target indestructibility greater than or equal to the preset indestructibility, thereby accurately improving the robustness and survivability of the multi-level target dynamic heterogeneous network.

[0115] Based on this, the present application provides an embodiment of the present application, which provides a method for testing the invulnerability of a dynamic heterogeneous network, including: obtaining target data based on a multi-level target smart grid; determining the target invulnerability based on the target data; and, if it is determined that the target invulnerability is less than a preset invulnerability, performing a target operation to make the target invulnerability greater than or equal to the preset invulnerability; wherein the target data includes: target connectivity, target fault tolerance, target anti-attack degree, and / or target death degree of the multi-level target dynamic heterogeneous network. The present application can improve the perception accuracy of the dynamic heterogeneous network status, thereby improving the accuracy of the dynamic heterogeneous network invulnerability test, and further improving the robustness and survivability of the dynamic heterogeneous network.

[0116] It should be noted that for the aforementioned method embodiments, for the sake of simplicity, they are all expressed as a series of action combinations, but those skilled in the art should be aware that this application is not limited by the order of the actions described, because according to this application, certain steps can be performed in other orders or simultaneously. Secondly, those skilled in the art should also be aware that the embodiments described in this specification are all optional embodiments, and the actions and modules involved are not necessarily required by this application.

[0117] The above is an introduction to the method embodiment. The following is a device embodiment to further illustrate the solution described in this application.

[0118] In a second aspect of the embodiments of the present application, a survivability testing system based on a dynamic heterogeneous network is proposed, which is applicable to the method described above. Figure 2 This is a structural diagram of a vehicle identification system 200 based on millimeter wave radar provided in an embodiment of the present application. Figure 2 The illustrated dynamic heterogeneous network-based invulnerability testing system 200 includes an acquisition unit 210 , a determination unit 220 , and an execution unit 230 .

[0119] An acquisition unit 210 is configured to acquire target data based on a multi-level target smart grid; A determination unit 220, configured to determine target invulnerability based on target data; An execution unit 230 is configured to, when determining that the target invulnerability is less than a preset invulnerability, execute a target operation to make the target invulnerability greater than or equal to the preset invulnerability; The target data includes target connectivity, target fault tolerance, target anti-attack degree, and / or target death degree of a multi-level target dynamic heterogeneous network.

[0120] Figure 3 This is a structural diagram of an electronic device 300 provided in an embodiment of the present application. Figure 3 As shown, the electronic device 300 includes a central processing unit (CPU) 301, which can perform various appropriate actions and processes according to the program stored in the read-only memory (ROM) 302 or the program loaded from the storage part 308 into the random access memory (RAM) 303. In the RAM 303, various programs and data required for the operation of the terminal device or server are also stored. The CPU 301, ROM 302 and RAM 303 are connected to each other via a bus 304. An input / output (I / O) interface 305 is also connected to the bus 304.

[0121] The following components are connected to the I / O interface 305: an input section 306 including a keyboard, a mouse, and the like; an output section 307 including devices such as a cathode ray tube (CRT), a liquid crystal display (LCD), and a speaker; a storage section 308 including a hard disk; and a communication section 309 including a network interface card such as a LAN card or a modem. The communication section 309 performs communication processing via a network such as the Internet. A drive 310 is also connected to the I / O interface 305 as needed. Removable media 311, such as a magnetic disk, an optical disk, a magneto-optical disk, or a semiconductor memory, is installed in the drive 310 as needed, so that computer programs read therefrom can be installed into the storage section 308 as needed.

[0122] In particular, according to an embodiment of the present application, the above method flow steps can be implemented as a computer software program. For example, an embodiment of the present application includes a computer program product, which includes a computer program carried on a machine-readable medium, and the computer program includes program code for executing the method shown in the flowchart. In such an embodiment, the computer program can be downloaded and installed from the network via the communication part 309, and / or installed from the removable medium 311. When the computer program is executed by the central processing unit (CPU) 301, the above-mentioned functions defined in the system of the present application are executed.

[0123] It should be noted that the computer-readable medium described in this application may be a computer-readable signal medium or a computer-readable storage medium, or any combination of the two. A computer-readable storage medium may be, for example, but not limited to, an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, device, or component, or any combination of the above. More specific examples of computer-readable storage media may include, but are not limited to: an electrical connection with one or more wires, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the above. In this application, a computer-readable storage medium may be any tangible medium that contains or stores a program that can be used by or in conjunction with an instruction execution system, device, or component. In this application, a computer-readable signal medium may include a data signal propagated in baseband or as part of a carrier wave, which carries computer-readable program code. This propagated data signal may take a variety of forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination of the above. A computer-readable signal medium may also be any computer-readable medium other than a computer-readable storage medium that can transmit, propagate, or transport a program for use by or in conjunction with an instruction execution system, apparatus, or device. Program code embodied on a computer-readable medium may be transmitted using any suitable medium, including but not limited to wireless, wireline, optical fiber cable, RF, or any suitable combination thereof.

[0124] The flowcharts and block diagrams in the accompanying drawings illustrate the possible architecture, functions and operations of the systems, methods and computer program products according to various embodiments of the present application. In this regard, each box in the flowchart or block diagram can represent a module, program segment, or a part of code, and the aforementioned module, program segment, or a part of code contains one or more executable instructions for realizing the specified logical function. It should also be noted that in some alternative implementations, the functions marked in the box can also occur in a different order than that marked in the accompanying drawings. For example, two boxes represented in succession can actually be executed substantially in parallel, and they can sometimes be executed in the opposite order, depending on the functions involved. It should also be noted that each box in the block diagram and / or flowchart, and the combination of the boxes in the block diagram and / or flowchart, can be implemented by a dedicated hardware-based system that performs the specified function or operation, or can be implemented by a combination of dedicated hardware and computer instructions.

[0125] The units or modules involved in the embodiments described in this application may be implemented in software or hardware. The units or modules described may also be provided in a processor. The names of these units or modules do not, in certain circumstances, constitute limitations on the units or modules themselves.

[0126] The above description is merely a preferred embodiment of the present application and an illustration of the technical principles employed. Those skilled in the art should understand that the scope of application involved in this application is not limited to the technical solutions formed by a specific combination of the above-mentioned technical features, but should also cover other technical solutions formed by any combination of the above-mentioned technical features or their equivalents without departing from the aforementioned application concept. For example, a technical solution formed by replacing the above-mentioned features with (but not limited to) technical features with similar functions applied for in this application.

Claims

1. A method for testing the invulnerability of a dynamic heterogeneous network, characterized in that: include: Obtain target data based on multi-level target smart grid; determining target invulnerability based on the target data; If it is determined that the target invulnerability is less than a preset invulnerability, performing a target operation to make the target invulnerability greater than or equal to the preset invulnerability; The target data includes: target connectivity, target fault tolerance, target anti-attack degree, and / or target death degree of a multi-level target dynamic heterogeneous network.

2. The invulnerability testing method based on a dynamic heterogeneous network according to claim 1, characterized in that: The method further comprises: Obtaining target information corresponding to the multi-level target dynamic heterogeneous network; Generating the multi-level target smart grid according to the target information; The target information includes: target network topology information, target node attribute information, target service and application mapping relationship information, target security configuration information, target network operation status information, target geographical distribution information, and / or target management interface information.

3. The method for testing the invulnerability of a dynamic heterogeneous network according to claim 2, wherein: The multi-level target smart grid is provided with corresponding multi-level target intelligent agents; Among them, the first-level target smart grid sets a first-level target intelligent agent to regulate the target dynamic heterogeneous network; The secondary target smart grid is equipped with a secondary target agent to control the target dynamic heterogeneous sub-network; The three-level target smart grid is equipped with three-level target intelligent agents to control the target dynamic heterogeneous local area network; And / or, a four-level target smart grid, setting up a four-level target intelligent agent to regulate the target network nodes.

4. The method for testing the invulnerability of a dynamic heterogeneous network according to claim 3, wherein: The multi-level target agent is used to determine the corresponding target frequency information according to the corresponding target network operation status information; According to the target frequency information, a target test operation is performed to obtain the target data.

5. The method for testing survivability of a dynamic heterogeneous network according to claim 3, wherein: Determining the target invulnerability according to the target data includes: Determining a first target invulnerability based on the target connectivity of the target dynamic heterogeneous network and the corresponding first weight, the target fault tolerance and the corresponding second weight, the target attack resistance and the corresponding third weight, and / or the target lethality and the corresponding fourth weight; Determining a second target invulnerability based on the target connectivity of the target dynamic heterogeneous subnetwork and the corresponding first weight, the target fault tolerance and the corresponding second weight, the target attack resistance and the corresponding third weight, and / or the target lethality and the corresponding fourth weight; Determining a third target survivability based on the target connectivity of the target dynamic heterogeneous local area network and the corresponding first weight, the target fault tolerance and the corresponding second weight, the target attack resistance and the corresponding third weight, and / or the target lethality and the corresponding fourth weight; A fourth target invulnerability is determined based on the target connectivity of the target network node and the corresponding first weight, the target fault tolerance and the corresponding second weight, the target anti-attack degree and the corresponding third weight, and / or the target death degree and the corresponding fourth weight.

6. The method for testing survivability of a dynamic heterogeneous network according to claim 5, wherein: The third weight corresponding to the target dynamic heterogeneous network is greater than the first weight; wherein the first weight, the second weight, and the fourth weight are equal; The first weight and the second weight corresponding to the target dynamic heterogeneous sub-network are equal; the third weight and the fourth weight are equal; wherein the fourth weight is less than the first weight; The first weight corresponding to the target dynamic heterogeneous local area network is equal to the fourth weight; the second weight is equal to the third weight; wherein the third weight is smaller than the first weight; The fourth weight corresponding to the target network node is greater than the first weight; The first weight is equal to the second weight; The second weight is greater than the third weight.

7. The invulnerability testing method based on a dynamic heterogeneous network according to any one of claims 1 to 5, characterized in that: The step of performing a target operation to make the target survivability greater than or equal to the preset survivability when it is determined that the target survivability is less than the preset survivability includes: Constructing a target abnormality digital twin model according to the target abnormality dynamic heterogeneous network, the target abnormality dynamic heterogeneous sub-network, the target abnormality dynamic heterogeneous local area network, and / or the target abnormality network node; Generate a target fault evolution path according to the target abnormal digital twin model; Execute the target operation according to the target fault evolution path.

8. The method for testing the invulnerability of a dynamic heterogeneous network according to claim 7, wherein: Also includes: When it is determined that the target connectivity is less than the preset connectivity, the target operation includes: target redundant path startup operation, target virtual node introduction operation, and / or target topology reconstruction operation; In the case where it is determined that the target fault tolerance is less than a preset fault tolerance, the target operation includes: a target node backup operation, a target redundant link addition operation, and / or a target containerized microservice startup operation; In the case where it is determined that the target attack resistance is less than a preset attack resistance, the target operation includes: a target firewall startup operation, a target attack source isolation operation, and / or a target honeypot trapping operation; When it is determined that the target death degree is greater than or equal to the preset death degree, the target operation includes: a target edge node construction operation, a target architecture decentralization operation, and / or a target load migration operation.

9. The method for testing survivability of a dynamic heterogeneous network according to claim 8, wherein: The target death degree is determined according to the following formula: in, Used to indicate Momentary target dynamic heterogeneous network individuals The corresponding target death degree; Used to indicate the first scaling factor; Used to represent the target dynamic heterogeneous network individuals in the target historical data Basis risk; β Used to represent the second scaling factor; k Used to indicate target threat factors; M Used to indicate target threat factors k the number of Used to indicate target threat factors k The corresponding weight; Used to indicate Momentary target dynamic heterogeneous network individuals Target threat factors faced k Strength; Used to represent the third scaling factor; Used to represent target dynamic heterogeneous network individuals A collection of adjacent or related target dynamic heterogeneous network individuals; Used to indicate ( t -1) Dynamic and heterogeneous network individuals with momentary goals j probability of death.

10. A survivability test system based on a dynamic heterogeneous network, applicable to the method of claim 1, characterized in that: include: An acquisition unit, used to acquire target data based on a multi-level target smart grid; a determination unit, configured to determine target invulnerability based on the target data; an execution unit, configured to, if it is determined that the target invulnerability is less than a preset invulnerability, execute a target operation to make the target invulnerability greater than or equal to the preset invulnerability; The target data includes: target connectivity, target fault tolerance, target anti-attack degree, and / or target death degree of a multi-level target dynamic heterogeneous network.

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