Secure interaction method and device for reversely screening for derived feature

Abstract

Disclosed are a secure interaction method and device for reversely screening for a derived feature. The method comprises: by means of community discovery, determining a community to which each data transmission apparatus belongs; reversely screening for a target community on the basis of data security indexes of communities; determining a derived feature of a target data transmission apparatus on the basis of an association relationship between the target data transmission apparatus and the target community; and identifying a data transmission security level of the target data transmission apparatus on the basis of the derived feature, and transmitting data on the basis of the data transmission security level. According to the present invention, the target community is reversely screened for in combination with the community discovery and the data security indexes of the communities, the derived feature of the target data transmission apparatus is determined on the basis of the association relationship between the target data transmission apparatus and the target community, and the data transmission security level of the apparatus is identified by means of the derived feature from the perspective of the association with the community, so that the identification accuracy of malicious attacks on the data by the plurality of apparatuses working together is improved, and the security of data exchange is guaranteed.

Description

A secure interactive method and device for reverse screening of derived features Technical Field

[0001] The present invention relates to the field of computer processing technology, and in particular to a secure interaction method, device, electronic device and computer-readable medium for reverse screening of derived features. Background Art

[0002] With the advent of the big data era, increasing amounts of data are being applied across various fields. Therefore, ensuring data security during transmission and exchange is paramount. For example, when using fifth-generation mobile communication networks (5G networks) for data transmission, malicious attackers often disguise themselves as legitimate devices, gaining the trust of network communication services and launching attacks. Furthermore, mobile network applications require the support of smart devices. However, network technology and smart devices are subject to certain malicious attacks in real-world applications, compromising the security of 5G networks during data transmission. Furthermore, data exchange between information systems also presents security issues. For example, a cluster can combine a group of independent terminals (such as computers) into a larger service system using a high-speed communication network. The terminals in the cluster can communicate with each other and collaboratively provide users with applications, system resources, and data. Therefore, these terminals present data security risks during data transmission, such as malicious attacks and data theft.

[0003] In existing technologies, the security of data transmission devices can be identified through machine learning. This method is based solely on the data transmission behavior of a single device and does not take into account the relationship between multiple devices. In reality, malicious attacks and theft of data are often carried out in collaboration with multiple devices.

[0004] Summary of the Invention

[0005] In view of this, the main purpose of the present invention is to propose a secure interaction method, device, electronic device and computer-readable medium for reverse screening of derived features, in order to at least partially solve at least one of the above technical problems.

[0006] In order to solve the above technical problems, the first aspect of the present invention provides a secure interactive method for reverse screening of derived features, the method comprising:

[0007] Determine the community to which each data transmission device belongs through community discovery;

[0008] Reversely screen target communities based on the data security indicators of each community;

[0009] determining a derived feature of the target data transmission device according to an association relationship between the target data transmission device and the target community;

[0010] The data transmission security level of the target data transmission device is identified according to the derived feature, and data interaction is performed according to the data transmission security level.

[0011] According to a preferred embodiment of the present invention, determining the derived features of the target data transmission device based on the association relationship between the target data transmission device and the target community includes:

[0012] Determine the distance between the target data transmission device and each target community respectively;

[0013] The derived characteristics of the target data transmission device are determined according to the distance between the target data transmission device and each target community and the data security index of each target community.

[0014] According to a preferred embodiment of the present invention, determining the distance between the target data transmission device and each target community includes:

[0015] Determine whether the target data transmission device can reach the target community;

[0016] If it is unreachable, the distance between the target data transmission device and the unreachable target community is zero;

[0017] If reachable, the distance between the target data transmission device and the reachable target community is the shortest distance between the target data transmission device and the reachable target community center node.

[0018] According to a preferred embodiment of the present invention, determining the derived features of the target data transmission device based on the association relationship between the target data transmission device and the target community includes:

[0019] Determine whether the target data transmission device exists in the target community;

[0020] If so, determining the derived characteristics of the target data transmission device based on the target community where the target data transmission device is located;

[0021] If it does not exist, the target community that the target data transmission device can reach is searched, and the derived features of the target data transmission device are determined according to the distance between the target data transmission device and the reachable target community.

[0022] According to a preferred embodiment of the present invention, determining the community to which each data transmission device belongs through community discovery includes:

[0023] Establish a network with data transmission equipment as nodes;

[0024] The community to which each data transmission device in the network belongs is determined by a community discovery algorithm.

[0025] According to a preferred embodiment of the present invention, if the target community is not screened out based on the data security indicators of each community, the network and / or community discovery process are adjusted, and then the community to which each data transmission device belongs is determined through community discovery.

[0026] According to a preferred embodiment of the present invention, adjusting the network includes: adjusting the network node type and / or adjusting the association relationship between nodes; adjusting the community discovery process includes: adjusting the community discovery algorithm, or adjusting the training parameters in the community discovery algorithm.

[0027] To solve the above technical problems, the second aspect of the present invention provides a secure interactive device for reverse screening of derived features, the device comprising:

[0028] A first determination module is configured to determine the community to which each data transmission device belongs through community discovery;

[0029] The reverse screening module is used to reversely screen target communities based on the data security indicators of each community;

[0030] a second determining module, configured to determine a derived feature of the target data transmission device according to an association relationship between the target data transmission device and the target community;

[0031] The data transmission module is configured to identify the data transmission security level of the target data transmission device according to the derived characteristics, and perform data interaction according to the data transmission security level.

[0032] According to a preferred embodiment of the present invention, the second determining module includes:

[0033] A first sub-determination module is used to respectively determine the distance between the target data transmission device and each target community;

[0034] The second sub-determination module is configured to determine the derived features of the target data transmission device according to the distance between the target data transmission device and each target community and the data security index of each target community.

[0035] According to a preferred embodiment of the present invention, the first sub-determination module includes:

[0036] The first judgment module is used to judge whether the target data transmission device can reach the target community;

[0037] The third sub-determination module is used to determine that if the target data transmission device is unreachable, the distance between the target data transmission device and the unreachable target community is zero; if the target data transmission device is reachable, the distance between the target data transmission device and the reachable target community is the shortest distance between the target data transmission device and the central node of the reachable target community.

[0038] According to a preferred embodiment of the present invention, the second determining module includes:

[0039] The second judgment module is used to judge whether the target data transmission device exists in the target community;

[0040] The third sub-determination module is used to determine the derived characteristics of the target data transmission device based on the target community where the target data transmission device is located, if it exists; if it does not exist, to search for the target community that the target data transmission device can reach, and determine the derived characteristics of the target data transmission device based on the distance between the target data transmission device and the reachable target community.

[0041] According to a preferred embodiment of the present invention, the first determining module includes:

[0042] Create a module for establishing a network with data transmission devices as nodes;

[0043] The community discovery module is used to determine the community to which each data transmission device in the network belongs through a community discovery algorithm.

[0044] According to a preferred embodiment of the present invention, the present invention further comprises:

[0045] The adjustment module is used to adjust the network and / or the community discovery process if the reverse screening module fails to screen out the target community based on the data security indicators of each community, and then determine the community to which each data transmission device belongs through community discovery.

[0046] According to a preferred embodiment of the present invention, adjusting the network includes: adjusting the network node type and / or adjusting the association relationship between nodes; adjusting the community discovery process includes: adjusting the community discovery algorithm, or adjusting the training parameters in the community discovery algorithm.

[0047] To solve the above technical problems, the present invention provides an electronic device according to a third aspect, including:

[0048] processor; and

[0049] A memory storing computer executable instructions, which, when executed, cause the processor to perform any of the methods described above.

[0050] In order to solve the above technical problems, the fourth aspect of the present invention provides a computer-readable storage medium, wherein the computer-readable storage medium stores one or more programs, and when the one or more programs are executed by a processor, the above method is implemented.

[0051] The present invention determines the community to which each data transmission device belongs through community discovery; reversely screens the target community based on the data security indicators of each community; and determines the derived characteristics of the target data transmission device based on the association relationship between the target data transmission device and the target community. The derived characteristics are then used to identify the data transmission security level of the device from the perspective of community association, thereby improving the accuracy of identifying malicious attacks on data by multiple devices in collaboration, thereby ensuring data transmission security. BRIEF DESCRIPTION OF THE DRAWINGS

[0052] In order to make the technical problems solved by the present invention, the technical means adopted, and the technical effects achieved more clearly, specific embodiments of the present invention will be described in detail below with reference to the accompanying drawings. However, it should be noted that the drawings described below are only drawings of exemplary embodiments of the present invention. Those skilled in the art can derive drawings of other embodiments based on these drawings without inventive effort.

[0053] FIG1 is a schematic flow chart of a secure interactive method for reverse screening of derived features according to an embodiment of the present invention;

[0054] FIG2 is a schematic diagram of determining the derived characteristics of the target data transmission device according to an embodiment of the present invention;

[0055] FIG3 is a schematic diagram of the structural framework of a secure interactive device for reverse screening of derived features according to an embodiment of the present invention;

[0056] FIG4 is a block diagram of an exemplary embodiment of an electronic device according to the present invention;

[0057] FIG5 is a schematic diagram of an embodiment of a computer-readable medium according to the present invention. DETAILED DESCRIPTION

[0058] The exemplary embodiments of the present invention will now be described more fully with reference to the accompanying drawings. Although each exemplary embodiment can be implemented in a variety of specific ways, it should not be understood that the present invention is limited to the embodiments set forth herein. Rather, these exemplary embodiments are provided to make the content of the present invention more complete and to more fully convey the inventive concept to those skilled in the art.

[0059] The same reference numerals in the accompanying drawings represent the same or similar elements, components or parts, and thus repeated descriptions of the same or similar elements, components or parts may be omitted below. It should also be understood that although the first, second, third and other numbered adjectives may be used herein to describe various devices, elements, components or parts, these devices, elements, components or parts should not be limited by these adjectives. In other words, these adjectives are only used to distinguish one from another. For example, the first device may also be called the second device, but this does not deviate from the essential technical solution of the present invention. In addition, the terms "and / or" and "and / or" refer to all combinations including any one or more of the listed items.

[0060] Please refer to FIG1 , which is a secure interactive method for reverse screening of derived features provided by the present invention. As shown in FIG1 , the method includes:

[0061] S1. Determine the community to which each data transmission device belongs through community discovery;

[0062] In this embodiment, the data transmission device can be a switching device, transmission device or terminal device in a data communication system, or it can be a data interaction network, such as a microservice architecture, a terminal or server in a cluster. These terminals or servers can communicate with each other, interact with data, and collaboratively provide applications, system resources and data to users.

[0063] In this embodiment, both the data communication system and the data interaction network can be abstracted as a network, and the community structure in the network can be discovered through community discovery. According to graph theory, a community is a subgraph with closely connected internal nodes. Nodes within a community are closely connected, while nodes in different communities are sparsely connected. Nodes within the same community can share common features. The community can reflect the local characteristics of node behavior in the network and their mutual correlation. In this embodiment, determining the community to which each data transmission device belongs through community discovery includes:

[0064] S11. Establish a network with data transmission devices as nodes;

[0065] A network is formed by nodes and edges that describe the relationships between nodes. In this embodiment, the relationships between nodes can include communication relationships, shared address relationships, data exchange relationships, and so on. For example, a network can be established with data transmission devices as nodes and the communication relationships between data transmission devices as edges.

[0066] S12. Determine the community to which each data transmission device in the network belongs by using a community discovery algorithm.

[0067] Among them: the community discovery algorithm can use statistical inference, such as: the stochastic block model (SBM) of the graph generation model, traditional machine learning, such as: spectral clustering, deep learning, such as autoencoder (AutoEncoder), DeepNMF, convolutional neural network (GCN). Preferably, this embodiment uses a modularity-based community discovery algorithm (Louvain algorithm) and a label propagation algorithm (LPA algorithm) to determine the community to which each data transmission device in the network belongs. For example, in Figure 2, the communities 1, 2, and 3 to which the data transmission devices belong are obtained through community discovery.

[0068] S2. Reversely screen target communities based on the data security indicators of each community;

[0069] In this embodiment, the target community is preferably a community with low data transmission security. Of course, the target community can also be a community with high data transmission security, which is not specifically limited in the present invention. The data security index is used to reflect the security of data transmission within the community. For example, the data security index can be a data transmission risk rate. The higher the data transmission risk rate in the community, the lower the data transmission security in the community, and the lower the data transmission risk rate, the higher the data transmission security in the community. Where: q1 is the number of data transmission devices in the community that are at risk of malicious data attacks, data theft, etc. when transmitting data, q0 is the total number of data transmission devices in the community, q0 includes the data transmission devices q1 in the community that have data transmission records. 01 and data transmission equipment with no data transmission records 02 Data security indicators can be measured using risk indexes. The higher the risk index of a community, the lower the security of data transmission in the community, and the lower the risk index, the higher the security of data transmission in the community. Where: q1 is the number of data transmission devices in the community that have risks such as malicious attacks and data theft when transmitting data, q 01 The number of data transfer devices in the community that have data transfer records.

[0070] For example, if the target community is a community with low data transmission security, a threshold can be set in advance. Communities with a data transmission risk rate or community risk index greater than the threshold are designated as target communities; conversely, communities with a data transmission risk rate or community risk index less than the threshold are designated as target communities. For example, in Figure 2, if the threshold is 0.5, the risk index of Community 1 is 0.8, the risk index of Community 2 is 0.6, and the risk index of Community 3 is 0.6, then Communities 1, 2, and 3 are all designated as target communities with low data transmission security.

[0071] Among them, the threshold can be set according to the confidentiality level of the data. For example, multiple thresholds of different sizes can be pre-configured, and the corresponding threshold is selected according to the confidentiality level of the data to be transmitted. For example, the confidentiality level of the data to be transmitted is inversely proportional to the size of the threshold, that is, data with a high confidentiality level uses a threshold with a small value, and data with a low confidentiality level uses a threshold with a large value.

[0072] In this embodiment, if the target community is not identified based on the data security indicators of each community, the process can return to step S1, adjust the network and / or the community discovery process, and then determine the community to which each data transmission device belongs through community discovery. The target community can then be reversely identified based on the data security indicators of each community. Adjusting the network can include adjusting the network node type, such as changing the node type from a data transmission device to a data transmission device with data transmission records. It can also include adjusting the relationships between nodes, such as changing the communication relationship to a shared location relationship. It can also include adjusting both the node type and the relationships between nodes. Adjusting the community discovery process can include adjusting the community discovery algorithm, such as changing the Louvain algorithm to the LPA algorithm. Alternatively, it can include adjusting the training parameters within the community discovery algorithm, such as continuing to use the Louvain algorithm but modifying the termination condition for the number of folds.

[0073] S3. Determine the derived features of the target data transmission device based on the association relationship between the target data transmission device and the target community;

[0074] The target data transmission device may be a data transmission device for data to be transmitted. In one example, the association between the target data transmission device and the target community can be described by the distance between the two. Based on the distance and combined with the target community security index, derived features are obtained. Determining the derived features of the target data transmission device based on the association between the target data transmission device and the target community may include:

[0075] S31, respectively determining the distance between the target data transmission device and each target community;

[0076] In this embodiment, the distance between the target data transmission device and the target community refers to the distance from the target data transmission device to the central node of the target community, which can be determined through the network in step S11. Among them: the target data transmission device may be located in a certain target community, or may reach the target community through an edge, or may not have an edge with the target community, that is, it cannot reach the target community. Then in this step, it is first determined whether the target data transmission device can reach the target community, that is, whether the target data transmission device has a common edge with the target community in the network. If it is unreachable, the distance between the target data transmission device and the unreachable target community is zero; if it is reachable, the distance between the target data transmission device and the reachable target community is the shortest distance between the target data transmission device and the central node of the reachable target community. Among them: the central node can be the node with the largest degree centrality in the community, the node with the smallest total distance to other points in closeness centrality, or the node with the shortest path passing the most in betweenness centrality, and so on.

[0077] For example, in Figure 2, the solid origins represent the central nodes of each target community, and the hollow origins represent nodes within the target community. Target data transmission device 3 has no shared edges with target communities 1, 2, and 3. Therefore, the distances from target data transmission device 3 to target communities 1, 2, and 3 are all zero. The shortest distance from target data transmission device 2 to the central node of target community 1 is 4, the shortest distance to the central node of target community 2 is 3, and the shortest distance to the central node of target community 3 is 2. Therefore, the distances from target data transmission device 3 to target communities 1, 2, and 3 are 4, 3, and 2, respectively. Target data transmission device 1 is located within target community 1, and the shortest distances to the central node of target community 1 are 1, 3, and 3, respectively.

[0078] S32. Determine the derived characteristics of the target data transmission device based on the distance between the target data transmission device and each target community and the data security index of each target community.

[0079] For example, the target community's data security index can be used as a weight, and the distances between the target data transmission device and each target community can be weighted and summed to obtain the derived characteristics of the target data transmission device. In Figure 2, using the risk index as the data security index, the derived characteristics of target data transmission device 3 are 0, the derived characteristics of target data transmission device 2 are: 0.8 / 4 + 0.6 / 3 + 0.6 / 2 = 0.7, and the derived characteristics of target data transmission device 3 are: 0.8 / 1 + 0.6 / 3 + 0.6 / 3 = 1.2.

[0080] In another example, the association between the target data transmission device and the target community can be described by their location relationship. Based on the location relationship and combined with the target community security indicator, derived features are obtained. Determining the derived features of the target data transmission device based on the association between the target data transmission device and the target community may include:

[0081] S301, determining whether the target data transmission device exists in the target community;

[0082] S302. If so, determine the derived characteristics of the target data transmission device according to the target community where the target data transmission device is located;

[0083] Specifically, the derived characteristics of a data transmission device can be determined based on the distance between the target data transmission device and the target community's central node and the security index of the target community where the target data transmission device is located. For example, in Figure 2, target data transmission device 1 is located in target community 1, and the shortest distance to the central node of target community 1 is 1. The risk index of target community 1 is 0.8, so the derived characteristics of target data transmission device 1 are 0.8.

[0084] S303: If the target community does not exist, search for a target community that the target data transmission device can reach, and determine the derived features of the target data transmission device according to the distance between the target data transmission device and the reachable target community.

[0085] For example, the target community's data security index can be used as a weight, and the distances between the target data transmission device and each target community can be weighted and summed to obtain the derived characteristics of the target data transmission device. For example, in Figure 2, target data transmission device 2 can reach target communities 1, 2, and 3. Using the risk index as the data security index, the derived characteristics of target data transmission device 2 are: 0.8 / 4 + 0.6 / 3 + 0.6 / 2 = 0.7.

[0086] S4. Identify the data transmission security level of the target data transmission device according to the derived characteristics, and perform data interaction according to the data transmission security level.

[0087] For example, the derived features of the target data transmission device can be input into a trained recognition model to obtain the data transmission security level of the target data transmission device. The trained recognition model can analyze the derived features to identify the data transmission security level of the target data transmission device. If the data transmission security level is greater than or equal to a preset level, data transmission is performed through the target data transmission device. If the data transmission security level is less than the preset level, data transmission is not performed through the target data transmission device.

[0088] Furthermore, to improve the accuracy of data transmission security level identification, the derived features and data transmission features of the target data transmission device can be input into a trained second recognition model to obtain the data transmission security level of the target data transmission device. The trained second recognition model can analyze the derived features and data transmission features to identify the data transmission security level of the target data transmission device. Data transmission features may include transmission time, transmission channel, transmission protocol, and device information of the data transmission device. The device information may be attribute information that the terminal chooses to disclose, such as device location information, device communication information, device model, and device user attribute information.

[0089] FIG3 is a secure interactive device for reverse screening of derived features according to the present invention. As shown in FIG3 , the device includes:

[0090] A first determining module 31 is configured to determine the community to which each data transmission device belongs through community discovery;

[0091] A reverse screening module 32 is used to reversely screen target communities based on the data security indicators of each community;

[0092] A second determining module 33 is configured to determine a derived feature of the target data transmission device according to an association relationship between the target data transmission device and the target community;

[0093] The data transmission module 34 is configured to identify the data transmission security level of the target data transmission device according to the derived characteristics, and perform data exchange according to the data transmission security level.

[0094] In one embodiment, the second determining module 33 includes:

[0095] A first sub-determination module is used to respectively determine the distance between the target data transmission device and each target community;

[0096] The second sub-determination module is configured to determine the derived features of the target data transmission device according to the distance between the target data transmission device and each target community and the data security index of each target community.

[0097] Furthermore, the first sub-determination module includes:

[0098] The first judgment module is used to judge whether the target data transmission device can reach the target community;

[0099] The third sub-determination module is used to determine that if the target data transmission device is unreachable, the distance between the target data transmission device and the unreachable target community is zero; if the target data transmission device is reachable, the distance between the target data transmission device and the reachable target community is the shortest distance between the target data transmission device and the central node of the reachable target community.

[0100] In another embodiment, the second determining module 33 includes:

[0101] The second judgment module is used to judge whether the target data transmission device exists in the target community;

[0102] The third sub-determination module is used to determine the derived characteristics of the target data transmission device based on the target community where the target data transmission device is located, if it exists; if it does not exist, to search for the target community that the target data transmission device can reach, and determine the derived characteristics of the target data transmission device based on the distance between the target data transmission device and the reachable target community.

[0103] The first determining module 31 includes:

[0104] Create a module for establishing a network with data transmission devices as nodes;

[0105] The community discovery module is used to determine the community to which each data transmission device in the network belongs through a community discovery algorithm.

[0106] Furthermore, the device further comprises:

[0107] The adjustment module is configured to, if the reverse screening module fails to identify the target community based on the data security indicators of each community, adjust the network and / or the community discovery process, and then determine the community to which each data transmission device belongs through community discovery. Adjusting the network includes adjusting network node types and / or relationships between nodes; adjusting the community discovery process includes adjusting the community discovery algorithm or training parameters within the community discovery algorithm.

[0108] Those skilled in the art will appreciate that the modules in the above device embodiments may be distributed in the device as described, or may be modified accordingly and distributed in one or more devices different from the above embodiments. The modules in the above embodiments may be combined into one module or further split into multiple submodules.

[0109] The following describes an electronic device embodiment of the present invention. This electronic device can be considered a physical implementation of the method and apparatus embodiments of the present invention described above. Details described in the electronic device embodiment of the present invention should be considered supplementary to the above-described method or apparatus embodiments; details not disclosed in the electronic device embodiment of the present invention can be implemented with reference to the above-described method or apparatus embodiments.

[0110] Figure 4 is a block diagram of an exemplary embodiment of an electronic device according to the present invention. The electronic device shown in Figure 4 is only an example and should not limit the functions and scope of use of the embodiments of the present invention.

[0111] As shown in FIG4 , the electronic device 400 of this exemplary embodiment is implemented as a general-purpose data processing device. Components of the electronic device 400 may include, but are not limited to, at least one processing unit 410, at least one storage unit 420, a bus 430 connecting various electronic device components (including the storage unit 420 and the processing unit 410), a display unit 440, and the like.

[0112] The storage unit 420 stores a computer-readable program, which may be a source program or a read-only program. The program may be executed by the processing unit 410, causing the processing unit 410 to perform the steps of various embodiments of the present invention. For example, the processing unit 410 may perform the steps shown in FIG1 .

[0113] Bus 430 may represent one or more of several types of bus structures, including a memory bus or memory controller, a peripheral bus, an accelerated graphics port, a processing unit, or a local bus using any of a variety of bus architectures.

[0114] The electronic device 400 may also communicate with one or more external devices 100 (e.g., a keyboard, a display, a network device, a Bluetooth device, etc.), allowing a user to interact with the electronic device 400 via these external devices 100, and / or allowing the electronic device 400 to communicate with one or more other data processing devices (e.g., a router, a modem, etc.). Such communication may be performed through an input / output (I / O) interface 450, and may also be performed through a network adapter 460 to communicate with one or more networks (e.g., a local area network (LAN), a wide area network (WAN), and / or a public network). The network adapter 460 may communicate with other modules of the electronic device 400 via the bus 430.

[0115] Figure 5 is a schematic diagram of an embodiment of a computer-readable medium of the present invention. As shown in Figure 5, the computer program can be stored on one or more computer-readable media. The computer-readable medium can be a readable signal medium or a readable storage medium. When the computer program is executed by one or more data processing devices, the computer-readable medium is enabled to implement the above-mentioned method of the present invention, namely: determining the community to which each data transmission device belongs through community discovery; reversely screening out the target community based on the data security indicators of each community; determining the derived characteristics of the target data transmission device based on the association relationship between the target data transmission device and the target community; identifying the data transmission security level of the target data transmission device based on the derived characteristics, and performing data interaction based on the data transmission security level.

[0116] The specific embodiments described above further illustrate the objectives, technical solutions, and beneficial effects of the present invention. It should be understood that the present invention is not inherently related to any specific computer, virtual device, or electronic device, and various general-purpose devices can also implement the present invention. The above description is only a specific embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present invention shall be included in the scope of protection of the present invention.

Claims

1. A secure interactive method for reverse screening of derived features, characterized in that: The method comprises: Determine the community to which each data transmission device belongs through community discovery; Reversely screen the target communities based on the data security indicators of each community; Determining a derived feature of the target data transmission device according to an association relationship between the target data transmission device and the target community; The data transmission security level of the target data transmission device is identified according to the derived feature, and data interaction is performed according to the data transmission security level.

2. The method according to claim 1, characterized in that The step of determining the derived features of the target data transmission device according to the association relationship between the target data transmission device and the target community includes: Determine the distance between the target data transmission device and each target community respectively; The derived characteristics of the target data transmission device are determined according to the distance between the target data transmission device and each target community and the data security index of each target community.

3. The method according to claim 2, characterized in that Determining the distance between the target data transmission device and each target community includes: Determine whether the target data transmission device can reach the target community; If it is unreachable, the distance between the target data transmission device and the unreachable target community is zero; If reachable, the distance between the target data transmission device and the reachable target community is the shortest distance between the target data transmission device and the reachable target community center node.

4. The method according to claim 1, characterized in that: The step of determining the derived features of the target data transmission device according to the association relationship between the target data transmission device and the target community includes: Determine whether the target data transmission device exists in the target community; If so, determining the derived characteristics of the target data transmission device according to the target community where the target data transmission device is located; If it does not exist, the target community that the target data transmission device can reach is searched, and the derived features of the target data transmission device are determined according to the distance between the target data transmission device and the reachable target community.

5. The method according to claim 1, characterized in that Determining the community to which each data transmission device belongs through community discovery includes: Establish a network with data transmission equipment as nodes; The community to which each data transmission device in the network belongs is determined by a community discovery algorithm.

6. The method according to claim 5, characterized in that If the target community is not screened out based on the data security indicators of each community, the network and / or the community discovery process is adjusted, and then the community to which each data transmission device belongs is determined through community discovery.

7. The method according to claim 6, characterized in that The adjusting the network includes: adjusting the network node type and / or adjusting the association relationship between nodes; the adjusting the community discovery process includes: adjusting the community discovery algorithm or adjusting the training parameters in the community discovery algorithm.

8. A secure interactive device for reverse screening of derived features, characterized in that: The device comprises: A first determination module is used to determine the community to which each data transmission device belongs through community discovery; The reverse screening module is used to reversely screen out target communities based on the data security indicators of each community; A second determination module, configured to determine a derivative feature of the target data transmission device according to an association relationship between the target data transmission device and the target community; A data transmission module is used to identify the data transmission security level of the target data transmission device according to the derived characteristics, and to perform data interaction according to the data transmission security level.

9. An electronic device, comprising: processor; as well as A memory storing computer executable instructions which, when executed, cause the processor to perform a method according to any one of claims 1 to 7.

10. A computer-readable storage medium, wherein: The computer-readable storage medium stores one or more programs, and when the one or more programs are executed by a processor, the method according to any one of claims 1 to 7 is implemented.

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