技术领域Technical Field
本发明实施例涉及电力网络技术领域，尤其涉及一种电力网络空间中实体信任度的评估方法、装置、设备及存储介质。Embodiments of the present invention relate to the field of power network technology, and in particular to a method, device, equipment and storage medium for evaluating the trustworthiness of entities in a power network space.
背景技术Background Art
随着电力系统与网络技术的结合愈发紧密，除了自然灾害、技术故障等因素，可能存在的实体异常或违规行为，通过网络的传播和放大，同样可对系统造成巨大损害。因此，为了防范系统中的异常实体因素导致电力系统问题，进而对社会生产和生活造成影响，迫切需要对电力系统中的实体和群体建立其信任度量系统，以从根本上降低恶意行为的影响。As the integration of power systems and network technologies becomes increasingly close, in addition to factors such as natural disasters and technical failures, possible entity anomalies or violations can also cause huge damage to the system through the spread and amplification of the network. Therefore, in order to prevent abnormal entity factors in the system from causing power system problems and then affecting social production and life, it is urgent to establish a trust measurement system for entities and groups in the power system to fundamentally reduce the impact of malicious behavior.
目前，信任度量系统主要应用在互联网的服务器交互方面，它通过统计实体过去的守信/失信行为记录，以及其他实体对其的历史评估，综合计算得到信誉，用于为网络中的服务提供商建立信用评级以供合作方或客户参考。但在新型电力系统中，大量需要评估的实体往往由于运行位置的限制，在信任度量上高度依赖于其所处的工作群体，从而呈现出分簇的集中分布，而由于传统信任度量的对象一般为网络中的实体而非现实中的自然人、终端设备等，其对考察对象的群体所属往往属于缺失部分。同时，由于考察对象从虚拟实体变为系统中的真实实体，一些对象自然社会的属性也可纳入了考察范围，例如设备的参数信息、运行地点、维护者或是自然人的社交网络、社会声誉和影响力等，这些新的因素理论上与目标信誉存在一定的关联，一个有效的度量系统应该也将其视为考察的部分，而这是传统以互联网为背景的信任度量往往缺失考虑的。At present, the trust measurement system is mainly used in the server interaction of the Internet. It calculates the reputation by counting the entity's past trustworthy/distrustful behavior records and other entities' historical evaluations of it, and uses it to establish a credit rating for the service provider in the network for reference by partners or customers. However, in the new power system, a large number of entities that need to be evaluated are often highly dependent on their work groups in terms of trust measurement due to the limitations of their operating locations, thus showing a clustered centralized distribution. Since the objects of traditional trust measurement are generally entities in the network rather than natural persons, terminal devices, etc. in reality, the group to which the object of investigation belongs is often missing. At the same time, since the object of investigation changes from a virtual entity to a real entity in the system, some natural and social attributes of the object can also be included in the scope of investigation, such as the parameter information of the equipment, the operating location, the social network of the maintainer or natural person, the social reputation and influence, etc. These new factors are theoretically related to the target reputation. An effective measurement system should also regard them as part of the investigation, which is often missing in the traditional trust measurement based on the Internet.
因此，为了更好适应电力网络空间中考察对象的属性变更，需要一种新型的高效实用的信任度量计算方案。Therefore, in order to better adapt to the attribute changes of the objects under investigation in the power network space, a new, efficient and practical trust metric calculation scheme is needed.
发明内容Summary of the invention
本发明实施例提供一种电力网络空间中实体信任度的评估方法、装置、设备及存储介质，可以提高对电力网络空间中的实体的信任度的评估的准确性。The embodiments of the present invention provide a method, device, equipment and storage medium for evaluating the trust of entities in a power network space, which can improve the accuracy of evaluating the trust of entities in a power network space.
第一方面，本发明实施例提供了一种电力网络空间中实体信任度的评估方法，包括：In a first aspect, an embodiment of the present invention provides a method for evaluating the trust of an entity in a power network space, comprising:
基于第一行为序列确定第一基础信用评分以及基于第二行为序列确定第二基础信用评分；其中，所述第一行为序列为实体的行为序列，所述第一基础信用评分为所述实体的基础信用评分，所述第二行为序列为群体的行为序列，所述第二基础信用评分为所述群体的基础信用评分；所述群体中包括多个所述实体；Determine a first basic credit score based on a first behavior sequence and determine a second basic credit score based on a second behavior sequence; wherein the first behavior sequence is a behavior sequence of an entity, the first basic credit score is a basic credit score of the entity, the second behavior sequence is a behavior sequence of a group, the second basic credit score is a basic credit score of the group; the group includes a plurality of the entities;
基于所述群体中两两实体间的协作度确定所述群体的团结度；Determining the solidarity of the group based on the degree of cooperation between two entities in the group;
将所述实体的属性信息输入影响因子预测模型，输出所述实体的影响因子；Inputting the attribute information of the entity into an impact factor prediction model, and outputting the impact factor of the entity;
基于所述第一基础信用评分、所述第二基础信用评分、所述团结度及所述影响因子确定所述实体的信任度；Determining the trustworthiness of the entity based on the first basic credit score, the second basic credit score, the solidarity, and the influencing factor;
根据所述实体的信任度确定所述实体的信任度等级。A trust level of the entity is determined based on the trust of the entity.
第二方面，本发明实施例还提供了一种电力网络空间中实体信任度的评估装置，包括：In a second aspect, an embodiment of the present invention further provides a device for evaluating the trustworthiness of entities in a power network space, comprising:
基础信用评分确定模块，用于基于第一行为序列确定第一基础信用评分以及基于第二行为序列确定第二基础信用评分；其中，所述第一行为序列为实体的行为序列，所述第一基础信用评分为所述实体的基础信用评分，所述第二行为序列为群体的行为序列，所述第二基础信用评分为所述群体的基础信用评分；所述群体中包括多个所述实体；A basic credit score determination module, configured to determine a first basic credit score based on a first behavior sequence and to determine a second basic credit score based on a second behavior sequence; wherein the first behavior sequence is a behavior sequence of an entity, the first basic credit score is a basic credit score of the entity, the second behavior sequence is a behavior sequence of a group, the second basic credit score is a basic credit score of the group; the group includes a plurality of the entities;
团结度确定模块，用于基于所述群体中两两实体间的协作度确定所述群体的团结度；A solidarity determination module, used to determine the solidarity of the group based on the degree of cooperation between any two entities in the group;
影响因子确定模块，用于将所述实体的属性信息输入影响因子预测模型，输出所述实体的影响因子；An impact factor determination module, used for inputting attribute information of the entity into an impact factor prediction model and outputting the impact factor of the entity;
实体信任度确定模块，用于基于所述第一基础信用评分、所述第二基础信用评分、所述团结度及所述影响因子确定所述实体的信任度；an entity trustworthiness determination module, configured to determine the trustworthiness of the entity based on the first basic credit score, the second basic credit score, the solidarity, and the influencing factor;
信任度等级确定模块，用于根据所述实体的信任度确定所述实体的信任度等级。The trust level determination module is used to determine the trust level of the entity according to the trust level of the entity.
第三方面，本发明实施例还提供了一种电子设备，所述电子设备包括：In a third aspect, an embodiment of the present invention further provides an electronic device, the electronic device comprising:
至少一个处理器；以及与所述至少一个处理器通信连接的存储器；其中，at least one processor; and a memory in communication with the at least one processor; wherein,
所述存储器存储有可被所述至少一个处理器执行的计算机程序，所述计算机程序被所述至少一个处理器执行，以使所述至少一个处理器能够执行本发明实施例所述的电力网络空间中实体信任度的评估方法。The memory stores a computer program that can be executed by the at least one processor, and the computer program is executed by the at least one processor so that the at least one processor can execute the method for evaluating the trust of entities in the power network space described in an embodiment of the present invention.
第四方面，本发明实施例还提供了一种计算机可读存储介质，所述计算机可读存储介质存储有计算机指令，所述计算机指令用于使处理器执行时实现本发明实施例所述的电力网络空间中实体信任度的评估方法。In a fourth aspect, an embodiment of the present invention further provides a computer-readable storage medium, wherein the computer-readable storage medium stores computer instructions, and the computer instructions are used to enable a processor to implement the method for evaluating the trust of entities in the power network space described in the embodiment of the present invention when executed.
本发明实施例公开了一种电力网络空间中实体信任度的评估方法、装置、设备及存储介质。基于第一行为序列确定第一基础信用评分以及基于第二行为序列确定第二基础信用评分；其中，第一行为序列为实体的行为序列，第一基础信用评分为实体的基础信用评分，第二行为序列为群体的行为序列，第二基础信用评分为群体的基础信用评分；群体中包括多个实体；基于群体中两两实体间的协作度确定群体的团结度；将实体的属性信息输入影响因子预测模型，输出实体的影响因子；基于第一基础信用评分、第二基础信用评分、团结度及影响因子确定实体的信任度；根据实体的信任度确定实体的信任度等级。本发明实施例提供的电力网络空间中实体信任度的评估方法，可以提高实体信任度评估的准确性。The embodiment of the present invention discloses a method, device, equipment and storage medium for evaluating the trust of entities in an electric power network space. A first basic credit score is determined based on a first behavior sequence, and a second basic credit score is determined based on a second behavior sequence; wherein the first behavior sequence is a behavior sequence of an entity, the first basic credit score is a basic credit score of the entity, the second behavior sequence is a behavior sequence of a group, and the second basic credit score is a basic credit score of the group; the group includes multiple entities; the solidarity of the group is determined based on the degree of cooperation between two entities in the group; the attribute information of the entity is input into an influence factor prediction model, and the influence factor of the entity is output; the trust of the entity is determined based on the first basic credit score, the second basic credit score, the solidarity and the influence factor; the trust level of the entity is determined according to the trust of the entity. The method for evaluating the trust of an entity in an electric power network space provided by the embodiment of the present invention can improve the accuracy of entity trust evaluation.
附图说明BRIEF DESCRIPTION OF THE DRAWINGS
图1是本发明实施例一中的一种电力网络空间中实体信任度的评估方法的流程图；FIG1 is a flow chart of a method for evaluating the trustworthiness of entities in a power network space in a first embodiment of the present invention;
图2是本发明实施例一中的一种图结构的示意图；FIG2 is a schematic diagram of a graph structure in Embodiment 1 of the present invention;
图3是本发明实施例一中的一种影响因子预测模型的结构示意图；FIG3 is a schematic diagram of the structure of an impact factor prediction model in Embodiment 1 of the present invention;
图4是本发明实施例二中的一种电力网络空间中实体信任度的评估装置的结构示意图；4 is a schematic diagram of the structure of an evaluation device for entity trust in a power network space in a second embodiment of the present invention;
图5是本发明实施例三中的一种电子设备的结构示意图。FIG5 is a schematic diagram of the structure of an electronic device in Embodiment 3 of the present invention.
具体实施方式DETAILED DESCRIPTION
下面结合附图和实施例对本发明作进一步的详细说明。可以理解的是，此处所描述的具体实施例仅仅用于解释本发明，而非对本发明的限定。另外还需要说明的是，为了便于描述，附图中仅示出了与本发明相关的部分而非全部结构。The present invention will be further described in detail below in conjunction with the accompanying drawings and embodiments. It is to be understood that the specific embodiments described herein are only used to explain the present invention, rather than to limit the present invention. It should also be noted that, for ease of description, only parts related to the present invention, rather than all structures, are shown in the accompanying drawings.
实施例一Embodiment 1
图1为本发明实施例一提供的一种电力网络空间中实体信任度的评估方法的流程图，本实施例可适用于对电力网络空间中的实体的信任度进行评估的情况，该方法可以由电力网络空间中实体信任度的评估装置来执行，该装置可以通过软件和/或硬件的形式实现，可选的，通过电子设备来实现，该电子设备可以是移动终端、PC端或服务器等。具体包括如下步骤：FIG1 is a flow chart of a method for evaluating the trust of an entity in a power network space provided by Embodiment 1 of the present invention. This embodiment is applicable to the case of evaluating the trust of an entity in a power network space. The method can be executed by an evaluation device for evaluating the trust of an entity in a power network space. The device can be implemented in the form of software and/or hardware. Optionally, it can be implemented by an electronic device, which can be a mobile terminal, a PC or a server, etc. Specifically, the following steps are included:
S110，基于第一行为序列确定第一基础信用评分以及基于第二行为序列确定第二基础信用评分。S110, determining a first basic credit score based on the first behavior sequence and determining a second basic credit score based on the second behavior sequence.
其中，第一行为序列为实体的行为序列，第一基础信用评分为实体的基础信用评分，第二行为序列为群体的行为序列，第二基础信用评分为群体的基础信用评分；群体中包括多个实体。Among them, the first behavior sequence is the behavior sequence of the entity, the first basic credit score is the basic credit score of the entity, the second behavior sequence is the behavior sequence of the group, and the second basic credit score is the basic credit score of the group; the group includes multiple entities.
其中，实体的行为序列可以是按照发生时间升序排序的实体的行为，每个行为有三种取值：-1，0，1，分表表示恶意行为，普通行为和合规行为。示例性的，一个实体的行为序列可以表示为（r1，r2，……，rn）。The behavior sequence of an entity may be the behavior of the entity sorted in ascending order of occurrence time, and each behavior has three values: -1, 0, 1, which represent malicious behavior, common behavior, and compliant behavior. For example, the behavior sequence of an entity may be represented as (r1 , r2 , ..., rn ).
具体的，基于第一行为序列确定第一基础信用评分按照如下公式确定：，其中，为第一基础信用评分，K为第一行为序列包括的行为数量，为可调节参数，为第i个行为的取值。可以是大于0.5的任意值。本实施例中，当第一行为序列中加入新的行为rK+1时，新的第一基础信用评分的计算公式可以表示为：，直接在原第一基础信用评分的基础上确定新的第一基础信用评分，可以降低计算量。Specifically, the first basic credit score is determined based on the first behavior sequence according to the following formula: ,in, is the first basic credit score, K is the number of behaviors included in the first behavior sequence, is an adjustable parameter, is the value of the ith behavior. It can be any value greater than 0.5. In this embodiment, when a new behavior rK+1 is added to the first behavior sequence, the calculation formula of the new first basic credit score can be expressed as: , directly determining a new first basic credit score based on the original first basic credit score can reduce the amount of calculation.
其中，群体的行为序列可以是按照发生时间升序排序的群体的行为，每个行为有三种取值：-1，0，1，分表表示恶意行为，普通行为和合规行为。示例性的，一个群体的行为序列可以表示为（r1，r2，……，rn）。The behavior sequence of a group can be the group's behaviors sorted in ascending order of occurrence time, and each behavior has three values: -1, 0, 1, which represent malicious behavior, common behavior, and compliant behavior. For example, a group's behavior sequence can be represented as (r1 , r2 , ..., rn ).
示例性的，某个群体中包括6个实体，编号为1-6，表1示出了这6个实体的行为序列，每个序列中包括4个行为。Exemplarily, a certain group includes 6 entities, numbered 1-6. Table 1 shows the behavior sequences of these 6 entities, and each sequence includes 4 behaviors.
表1Table 1
按照上述公式计算各个实体的基础信用评分，假设，则计算得到各实体的基础信用评分如表2所示：According to the above formula, the basic credit score of each entity is calculated, assuming , then the basic credit scores of each entity are calculated as shown in Table 2:
表2Table 2
具体的，基于第二行为序列确定第二基础信用评分按照如下公式确定：，其中，为第二基础信用评分，L为第二行为序列包括的行为数量，为可调节参数，为第j个行为的取值。可以是大于0.5的任意值。本实施例中，当第一行为序列中加入新的行为rL+1时，新的第一基础信用评分的计算公式可以表示为：，直接在原第二基础信用评分的基础上确定新的第二基础信用评分，可以降低计算量。Specifically, the second basic credit score is determined based on the second behavior sequence according to the following formula: ,in, is the second basic credit score, L is the number of behaviors included in the second behavior sequence, is an adjustable parameter, is the value of the jth behavior. It can be any value greater than 0.5. In this embodiment, when a new behavior rL+1 is added to the first behavior sequence, the calculation formula of the new first basic credit score can be expressed as: , directly determining a new second basic credit score based on the original second basic credit score can reduce the amount of calculation.
示例性的，表3为某个群体的行为序列，该行为序列中包括6个行为：For example, Table 3 is a behavior sequence of a group, which includes 6 behaviors:
表3Table 3
按照上述公式计算该群体的基础信用评分，假设，则计算得到该群体的基础信用评分C2为0.64352。According to the above formula, the basic credit score of this group is calculated, assuming , then the basic credit score C2 of this group is calculated to be 0.64352.
本实施例中的电力网络空间中包括多个群体，且每个群体中包含多个实体。对于每个群体及每个实体，均按照上述方式确定其基础信用评分。The power network space in this embodiment includes multiple groups, and each group includes multiple entities. For each group and each entity, its basic credit score is determined in the above manner.
S120，基于群体中两两实体间的协作度确定群体的团结度。S120, determining the solidarity of the group based on the degree of cooperation between any two entities in the group.
其中，实体间的协作度是基于已有信息评估获取到的，可以表征两个实体的协同能力，可以由0-1之间的值表示，协作度越接近于1，表示两个实体间的协同能力越好，反之越接近于0，表示两个实体间的协同能力越差。The degree of collaboration between entities is obtained based on the evaluation of existing information, which can characterize the collaborative ability of two entities and can be represented by a value between 0 and 1. The closer the degree of collaboration is to 1, the better the collaborative ability between the two entities. Conversely, the closer the degree of collaboration is to 0, the worse the collaborative ability between the two entities.
具体的，基于群体中两两实体间的协作度确定群体的团结度的方式可以是：对协作度进行降序排序，获得排序后的协作度；基于群体中的实体构建一不含边的图结构；按照排序后的协作度依次在图结构中对应的两两实体间添加边；在图结构中每添加一条边，确定图结构中两两节点间的距离；若所有两两节点间的距离均小于或等于设定阈值，则将当前协作度作为群体的团结度；若两两节点间的距离中的一个或多个大于设定阈值，则继续按照排序后的协作度在图结构中对应的两两实体间添加边，直到所有两两节点间的距离均小于或等于设定阈值。Specifically, the method of determining the solidarity of a group based on the degree of cooperation between pairs of entities in the group can be: sorting the cooperation degrees in descending order to obtain the sorted cooperation degrees; constructing a graph structure without edges based on the entities in the group; adding edges between the corresponding pairs of entities in the graph structure in sequence according to the sorted cooperation degrees; determining the distance between pairs of nodes in the graph structure each time an edge is added to the graph structure; if the distances between all pairs of nodes are less than or equal to a set threshold, taking the current degree of cooperation as the solidarity of the group; if one or more of the distances between pairs of nodes are greater than the set threshold, continuing to add edges between the corresponding pairs of entities in the graph structure according to the sorted cooperation degrees until the distances between all pairs of nodes are less than or equal to the set threshold.
其中，图结构中包括多个节点，节点与实体一一对应。两两节点间的距离可以是连通两个节点的最短路径（即最少的边的数量），若两个节点中无连通的路径，则这两个节点的距离为无穷大。设定阈值为设定的一可调节的阈值参数。The graph structure includes multiple nodes, and the nodes correspond to entities one by one. The distance between two nodes can be the shortest path connecting the two nodes (that is, the minimum number of edges). If there is no connecting path between the two nodes, the distance between the two nodes is infinite. The threshold is set to an adjustable threshold parameter.
本实施例中，一个协作度对应两个实体。假设群体中的实体个数为L，排序后的协作度表示为：P1、P2、……Pn，n=（L-1）L/2。具体的，确定群体团结度的过程可以是：In this embodiment, one degree of cooperation corresponds to two entities. Assuming that the number of entities in the group is L, the degree of cooperation after sorting is expressed as: P1 , P2 , ... Pn , n = (L-1) L/2. Specifically, the process of determining the degree of group solidarity can be:
步骤1，令计数器q=1。Step 1, set counter q=1.
步骤2，在图结构中Pq对应的两个实体间添加一条边。Step 2: Add an edge between the two entities corresponding toPq in the graph structure.
步骤3，令计数器k1=1，k2=2。Step 3, set counter k1=1, k2=2.
步骤4，计算图中节点k1与k2之间的距离D。Step 4: Calculate the distance D between nodes k1 and k2 in the graph.
步骤5，若D＞Dist，则跳转至步骤8，否则跳转至步骤6。Step 5: If D＞Dist, jump to step 8; otherwise, jump to step 6.
步骤6，计数器k2加1，若k2＞L，则跳转至步骤7，否则返回执行步骤4。Step 6, add 1 to counter k2. If k2>L, jump to step 7, otherwise return to step 4.
步骤7，计数器k1加1，若k1≥L，则跳转至步骤9，否则返回执行步骤4。Step 7, add 1 to counter k1. If k1≥L, jump to step 9, otherwise return to step 4.
步骤8，令计数器q加1，并返回执行2。Step 8, increment the counter q by 1 and return to execute 2.
步骤9，将Pq作为群体的团结度。Step 9: Take Pq as the solidarity of the group.
通过该方式计算出的团结度表示在所有协作度不低于团结度的实体对进行合作时，该群体任意两个实体之间的距离不会超过Dist。The solidarity calculated in this way means that when all pairs of entities with a cooperation degree not less than the solidarity cooperate, the distance between any two entities in the group will not exceed Dist.
示例性的，表4是某个群体中6个实体间的协作度：For example, Table 4 shows the degree of collaboration among six entities in a group:
表4Table 4
如表4所示，按协作度降序排序后的成员对为(3,4)，(3,6)，(1,4)， …， (2,4)，(1,2)，新建一含有6个节点，不含边的图结构，假设阈值Dist=3，则按该顺序依次将边加入图，最终当图如图2所示时，图中直径为3，小于等于阈值3，此时刚刚加入的边为(2,3)，其协作度为0.36，则该群体的团结度为0.36。As shown in Table 4, the member pairs sorted in descending order by collaboration degree are (3,4), (3,6), (1,4), …, (2,4), (1,2). A new graph structure with 6 nodes and no edges is created. Assuming the threshold Dist=3, the edges are added to the graph in this order. Finally, when the graph is as shown in Figure 2, the diameter of the graph is 3, which is less than or equal to the threshold 3. At this time, the edge just added is (2,3), and its collaboration degree is 0.36. The solidarity of the group is 0.36.
S130，将实体的属性信息输入影响因子预测模型，输出实体的影响因子。S130, inputting the attribute information of the entity into the impact factor prediction model, and outputting the impact factor of the entity.
其中，影响因子预测模型可以是决策树、神经网络等，例如可以是一多层感知机（MLP）模型，图3是本实施例中一种影响因子预测模型的结构示意图，如图3所示，该模型为第一层4个输入神经元，中间隐藏层6个神经元，输出层为一个神经元加上Sigmoid激活函数。实体属性信息可以是自然属性信息和/或社会属性信息，例如：可以包括设备历史宕机次数、已使用年限、设备维护者信用分及采购价格等。Among them, the impact factor prediction model can be a decision tree, a neural network, etc., for example, it can be a multi-layer perceptron (MLP) model. Figure 3 is a structural schematic diagram of an impact factor prediction model in this embodiment. As shown in Figure 3, the model has 4 input neurons in the first layer, 6 neurons in the middle hidden layer, and an output layer of one neuron plus a Sigmoid activation function. Entity attribute information can be natural attribute information and/or social attribute information, for example: it can include the number of historical equipment downtimes, years of use, equipment maintainer credit points and purchase price, etc.
具体的，将实体的属性信息输入影响因子预测模型，输出实体的影响因子的方式可以是：对所属实体的属性信息进行归一化处理，将归一化处理后的属性信息输入影响因子预测模型，输出实体的影响因子。Specifically, the attribute information of the entity is input into the impact factor prediction model, and the method of outputting the impact factor of the entity can be: normalizing the attribute information of the entity, inputting the normalized attribute information into the impact factor prediction model, and outputting the impact factor of the entity.
示例性的，表5是编号为1-6的实体的属性信息：For example, Table 5 is the attribute information of entities numbered 1-6:
表5Table 5
对表5中六个实体的属性信息进行归一化处理之后，分别输入影响因子预测模型，输出各个实体的影响因子。表6列出了上述六个实体的影响因子。After normalizing the attribute information of the six entities in Table 5, they are input into the impact factor prediction model respectively, and the impact factor of each entity is output. Table 6 lists the impact factors of the above six entities.
表6Table 6
可选的，影响因子预测模型的训练方式为：获取实体样本的属性信息样本及其基础信用评分；基于基础信用评分确定实体样本的真实影响因子；基于属性信息样本及真实影响因子对影响因子预测模型进行训练。Optionally, the impact factor prediction model is trained in the following manner: obtaining attribute information samples of entity samples and their basic credit scores; determining the real impact factors of the entity samples based on the basic credit scores; and training the impact factor prediction model based on the attribute information samples and the real impact factors.
具体的，基于基础信用评分确定实体样本的真实影响因子的方式可以是：若基础信用评分大于或等于0，则将真实影响因子确定为1，表示该个体较为可信，若基础信用评分小于0，则将真实影响因子确定为0，表示该个体较为不可信。Specifically, the method of determining the real impact factor of the entity sample based on the basic credit score can be: if the basic credit score is greater than or equal to 0, the real impact factor is determined to be 1, indicating that the individual is more trustworthy; if the basic credit score is less than 0, the real impact factor is determined to be 0, indicating that the individual is less trustworthy.
具体的，基于属性信息样本及真实影响因子对影响因子预测模型进行训练的过程可以是：首先对属性信息样本进行归一化处理，然后将归一化处理后的属性信息样本输入影响因子预测模型，输出预测影响因子，再然后确定预测影响因子与真实影响因子间的损失函数，最后基于该损失函数对影响因子预测模型进行调参。Specifically, the process of training the impact factor prediction model based on the attribute information samples and the real impact factors can be: first normalize the attribute information samples, then input the normalized attribute information samples into the impact factor prediction model, output the predicted impact factor, then determine the loss function between the predicted impact factor and the real impact factor, and finally adjust the impact factor prediction model based on the loss function.
S140，基于第一基础信用评分、第二基础信用评分、团结度及影响因子确定实体的信任度。S140, determining the trustworthiness of the entity based on the first basic credit score, the second basic credit score, the solidarity, and the influencing factor.
本实施例中，首先确定出群体的信任度，再基于群体的信任度确定实体的信任度。In this embodiment, the trust level of the group is determined first, and then the trust level of the entity is determined based on the trust level of the group.
具体的，基于第一基础信用评分、第二基础信用评分、团结度及影响因子确定实体的信任度的方式可以是：根据第二基础信用评分和团结度确定群体的信任度；基于群体的信任度、第一基础信用评分、团结度及影响因子确定实体的信任度。Specifically, the method of determining the trust of an entity based on the first basic credit score, the second basic credit score, solidarity and influencing factors can be: determining the trust of a group based on the second basic credit score and solidarity; determining the trust of an entity based on the trust of the group, the first basic credit score, solidarity and influencing factors.
其中，根据第二基础信用评分和团结度确定群体的信任度可以按照如下公式计算：H1=F(e1T+C2)。其中，H1为群体的信任度，e1为超参数，T为群体的团结度，C2为第二基础信用评分，F()为Sigmoid函数，可以表示为。The trust of a group can be determined based on the second basic credit score and solidarity by the following formula: H1 =F(e1 T+C2 ). H1 is the trust of the group, e1 is a hyperparameter, T is the solidarity of the group, C2 is the second basic credit score, and F() is a Sigmoid function, which can be expressed as .
其中，基于所述群体的信任度、所述第一基础信用评分、所述团结度及所述影响因子确定所述实体的信任度可以按照如下公式进行计算：H2=F(H1(e1T+C1+e2d))，其中，e1和e2均为超参数，T为群体的团结度，d为实体的影响因子，F()为Sigmoid函数，可以表示为。示例性的，e1=0.7，e2=0.2。The trust of the entity determined based on the trust of the group, the first basic credit score, the solidarity and the impact factor can be calculated according to the following formula: H2 =F(H1 (e1 T+C1 +e2 d)), where e1 and e2 are hyperparameters, T is the solidarity of the group, d is the impact factor of the entity, and F() is a Sigmoid function, which can be expressed as For example, e1 =0.7, e2 =0.2.
S150，根据实体的信任度确定实体的信任度等级。S150, determining the trust level of the entity according to the trust level of the entity.
其中，信任度等级可以是预先划分的。The trust levels may be pre-divided.
具体的，据实体的信任度确定实体的信任度等级的方式可以是：基于多个群体中多个实体的信任度进行等级划分，获得多个信任度等级范围；确定实体的信任度所处的信任度等级范围；基于信任度等级范围确定实体的信任度等级。Specifically, the method of determining the trust level of an entity based on the trust of the entity can be: classifying the trust of multiple entities in multiple groups to obtain multiple trust level ranges; determining the trust level range in which the trust of the entity lies; and determining the trust level of the entity based on the trust level range.
本实施例中，基于多个群体中多个实体的信任度进行等级划分的方式可以是：对于所有实体的信任度，首先确定其平均值u和标准差b，根据3倍标准差原则，将信任度划分为（-inf，u-2b]，（u-2b，u-b]，（u-b，u+b]，（u+b，u+2b]，（u+2b，inf）共五个区间，信任度位于对应区间的实体信用评级即分别为极差、较差、正常、较好、极好五种情况。In this embodiment, the method of grading the trust of multiple entities in multiple groups can be: for the trust of all entities, first determine their average value u and standard deviation b, and according to the principle of 3 times the standard deviation, divide the trust into five intervals: (-inf, u-2b], (u-2b, u-b], (u-b, u+b], (u+b, u+2b], (u+2b, inf), and the credit rating of the entity whose trust is in the corresponding interval is respectively very poor, poor, normal, good, and excellent.
本实施例中，在获得每个实体的信任度后，确定实体的信任度所处的信任度等级范围，基于信任度等级范围确定实体的信任度等级。示例性的，假设信任度落入（u-b，u+b]，则该实体的信任度为正常。In this embodiment, after obtaining the trust of each entity, the trust level range of the entity's trust is determined, and the trust level of the entity is determined based on the trust level range. Exemplarily, assuming that the trust falls within (u-b, u+b], the trust of the entity is normal.
本实施例的技术方案，基于第一行为序列确定第一基础信用评分以及基于第二行为序列确定第二基础信用评分；其中，第一行为序列为实体的行为序列，第一基础信用评分为实体的基础信用评分，第二行为序列为群体的行为序列，第二基础信用评分为群体的基础信用评分；群体中包括多个实体；基于群体中两两实体间的协作度确定群体的团结度；将实体的属性信息输入影响因子预测模型，输出实体的影响因子；基于第一基础信用评分、第二基础信用评分、团结度及影响因子确定实体的信任度；根据实体的信任度确定实体的信任度等级。本发明实施例提供的电力网络空间中实体信任度的评估方法，可以提高实体信任度评估的准确性。The technical solution of this embodiment determines the first basic credit score based on the first behavior sequence and the second basic credit score based on the second behavior sequence; wherein the first behavior sequence is the behavior sequence of the entity, the first basic credit score is the basic credit score of the entity, the second behavior sequence is the behavior sequence of the group, and the second basic credit score is the basic credit score of the group; the group includes multiple entities; the solidarity of the group is determined based on the degree of cooperation between two entities in the group; the attribute information of the entity is input into the influence factor prediction model, and the influence factor of the entity is output; the trust of the entity is determined based on the first basic credit score, the second basic credit score, the solidarity and the influence factor; the trust level of the entity is determined according to the trust of the entity. The method for evaluating the trust of entities in the power network space provided by the embodiment of the present invention can improve the accuracy of entity trust evaluation.
实施例二Embodiment 2
图4是本发明实施例二提供的一种电力网络空间中实体信任度的评估装置的结构示意图，如图4所示，该装置包括：FIG4 is a schematic diagram of the structure of a device for evaluating the trustworthiness of entities in a power network space provided by a second embodiment of the present invention. As shown in FIG4 , the device includes:
基础信用评分确定模块410，用于基于第一行为序列确定第一基础信用评分以及基于第二行为序列确定第二基础信用评分；其中，第一行为序列为实体的行为序列，第一基础信用评分为实体的基础信用评分，第二行为序列为群体的行为序列，第二基础信用评分为群体的基础信用评分；群体中包括多个实体；The basic credit score determination module 410 is used to determine a first basic credit score based on a first behavior sequence and to determine a second basic credit score based on a second behavior sequence; wherein the first behavior sequence is a behavior sequence of an entity, and the first basic credit score is a basic credit score of the entity; the second behavior sequence is a behavior sequence of a group, and the second basic credit score is a basic credit score of the group; and the group includes multiple entities;
团结度确定模块420，用于基于群体中两两实体间的协作度确定群体的团结度；A solidarity determination module 420, for determining the solidarity of a group based on the degree of cooperation between two entities in the group;
影响因子确定模块430，用于将实体的属性信息输入影响因子预测模型，输出实体的影响因子；An impact factor determination module 430 is used to input the attribute information of the entity into the impact factor prediction model and output the impact factor of the entity;
实体信任度确定模块440，用于基于第一基础信用评分、第二基础信用评分、团结度及影响因子确定实体的信任度；An entity trustworthiness determination module 440, configured to determine the trustworthiness of an entity based on the first basic credit score, the second basic credit score, the solidarity, and the influencing factor;
信任度等级确定模块450，用于根据实体的信任度确定实体的信任度等级。The trust level determination module 450 is used to determine the trust level of the entity according to the trust level of the entity.
可选的，基础信用评分确定模块410，还用于如下计算：Optionally, the basic credit score determination module 410 is further used to calculate as follows:
，其中，为第一基础信用评分，K为第一行为序列包括的行为数量，为可调节参数，为第i个行为的取值； ,in, is the first basic credit score, K is the number of behaviors included in the first behavior sequence, is an adjustable parameter, is the value of the ith behavior;
可选的，基础信用评分确定模块410，还用于如下计算：Optionally, the basic credit score determination module 410 is further used to calculate as follows:
，其中，为第二基础信用评分，L为第二行为序列包括的行为数量，为可调节参数，为第j个行为的取值。 ,in, is the second basic credit score, L is the number of behaviors included in the second behavior sequence, is an adjustable parameter, is the value of the jth behavior.
可选的，团结度确定模块420，还用于：Optionally, the solidarity determination module 420 is further configured to:
对协作度进行降序排序，获得排序后的协作度；Sort the collaboration degrees in descending order to obtain the sorted collaboration degrees;
基于群体中的实体构建一不含边的图结构；其中，图结构中包括多个节点，节点与实体一一对应；A graph structure without edges is constructed based on entities in the group; wherein the graph structure includes a plurality of nodes, and the nodes correspond to the entities one by one;
按照排序后的协作度依次在图结构中对应的两两实体间添加边；Add edges between corresponding entities in the graph structure according to the sorted collaboration degree;
在图结构中每添加一条边，确定图结构中两两节点间的距离；Each time an edge is added to the graph structure, the distance between any two nodes in the graph structure is determined;
若所有两两节点间的距离均小于或等于设定阈值，则将当前协作度作为群体的团结度；If the distances between all pairs of nodes are less than or equal to the set threshold, the current degree of cooperation is taken as the solidarity of the group;
若两两节点间的距离中的一个或多个大于设定阈值，则继续按照排序后的协作度在图结构中对应的两两实体间添加边，直到所有两两节点间的距离均小于或等于设定阈值。If one or more of the distances between two nodes is greater than the set threshold, edges are added between the corresponding two entities in the graph structure according to the sorted collaboration degree until the distances between all two nodes are less than or equal to the set threshold.
可选的，影响因子确定模块430，还用于：Optionally, the impact factor determination module 430 is further configured to:
对所属实体的属性信息进行归一化处理，Normalize the attribute information of the entity.
将归一化处理后的属性信息输入影响因子预测模型，输出实体的影响因子。The normalized attribute information is input into the impact factor prediction model, and the impact factor of the entity is output.
可选的，还包括：影响因子预测模型训练模块，用于：Optionally, it also includes: an impact factor prediction model training module, which is used to:
获取实体样本的属性信息样本及其基础信用评分；Obtaining attribute information samples of entity samples and their basic credit scores;
基于基础信用评分确定实体样本的真实影响因子；Determine the true impact factor of a sample of entities based on the underlying credit score;
基于属性信息样本及真实影响因子对影响因子预测模型进行训练。The impact factor prediction model is trained based on attribute information samples and real impact factors.
可选的，实体信任度确定模块440，还用于：Optionally, the entity trust determination module 440 is further configured to:
根据第二基础信用评分和团结度确定群体的信任度；Determine the trustworthiness of the group based on the second basic credit score and solidarity;
基于群体的信任度、第一基础信用评分、团结度及影响因子确定实体的信任度。The trustworthiness of an entity is determined based on the trustworthiness of the group, the first basic credit score, solidarity, and influence factors.
可选的，信任度等级确定模块450，还用于：Optionally, the trust level determination module 450 is further configured to:
基于多个群体中多个实体的信任度进行等级划分，获得多个信任度等级范围；Based on the trustworthiness of multiple entities in multiple groups, multiple trustworthiness level ranges are obtained;
确定实体的信任度所处的信任度等级范围；Determining the trust level range in which the trustworthiness of the entity lies;
基于信任度等级范围确定实体的信任度等级。A trust level of the entity is determined based on a trust level range.
上述装置可执行本发明前述所有实施例所提供的方法，具备执行上述方法相应的功能模块和有益效果。未在本实施例中详尽描述的技术细节，可参见本发明前述所有实施例所提供的方法。The above device can execute the methods provided by all the above embodiments of the present invention, and has the corresponding functional modules and beneficial effects of executing the above methods. For technical details not described in detail in this embodiment, please refer to the methods provided by all the above embodiments of the present invention.
实施例三Embodiment 3
图5示出了可以用来实施本发明的实施例的电子设备10的结构示意图。电子设备旨在表示各种形式的数字计算机，诸如，膝上型计算机、台式计算机、工作台、个人数字助理、服务器、刀片式服务器、大型计算机、和其它适合的计算机。电子设备还可以表示各种形式的移动装置，诸如，个人数字处理、蜂窝电话、智能电话、可穿戴设备（如头盔、眼镜、手表等）和其它类似的计算装置。本文所示的部件、它们的连接和关系、以及它们的功能仅仅作为示例，并且不意在限制本文中描述的和/或者要求的本发明的实现。FIG5 shows a schematic diagram of the structure of an electronic device 10 that can be used to implement an embodiment of the present invention. The electronic device is intended to represent various forms of digital computers, such as laptop computers, desktop computers, workstations, personal digital assistants, servers, blade servers, mainframe computers, and other suitable computers. The electronic device can also represent various forms of mobile devices, such as personal digital processing, cellular phones, smart phones, wearable devices (such as helmets, glasses, watches, etc.) and other similar computing devices. The components shown herein, their connections and relationships, and their functions are merely examples and are not intended to limit the implementation of the present invention described and/or required herein.
如图5所示，电子设备10包括至少一个处理器11，以及与至少一个处理器11通信连接的存储器，如只读存储器（ROM）12、随机访问存储器（RAM）13等，其中，存储器存储有可被至少一个处理器执行的计算机程序，处理器11可以根据存储在只读存储器（ROM）12中的计算机程序或者从存储单元18加载到随机访问存储器（RAM）13中的计算机程序，来执行各种适当的动作和处理。在RAM 13中，还可存储电子设备10操作所需的各种程序和数据。处理器11、ROM 12以及RAM 13通过总线14彼此相连。输入/输出（I/O）接口15也连接至总线14。As shown in FIG5 , the electronic device 10 includes at least one processor 11, and a memory connected to the at least one processor 11 in communication, such as a read-only memory (ROM) 12, a random access memory (RAM) 13, etc., wherein the memory stores a computer program that can be executed by at least one processor, and the processor 11 can perform various appropriate actions and processes according to the computer program stored in the read-only memory (ROM) 12 or the computer program loaded from the storage unit 18 to the random access memory (RAM) 13. In the RAM 13, various programs and data required for the operation of the electronic device 10 can also be stored. The processor 11, the ROM 12, and the RAM 13 are connected to each other via a bus 14. An input/output (I/O) interface 15 is also connected to the bus 14.
电子设备10中的多个部件连接至I/O接口15，包括：输入单元16，例如键盘、鼠标等；输出单元17，例如各种类型的显示器、扬声器等；存储单元18，例如磁盘、光盘等；以及通信单元19，例如网卡、调制解调器、无线通信收发机等。通信单元19允许电子设备10通过诸如因特网的计算机网络和/或各种电信网络与其他设备交换信息/数据。A number of components in the electronic device 10 are connected to the I/O interface 15, including: an input unit 16, such as a keyboard, a mouse, etc.; an output unit 17, such as various types of displays, speakers, etc.; a storage unit 18, such as a disk, an optical disk, etc.; and a communication unit 19, such as a network card, a modem, a wireless communication transceiver, etc. The communication unit 19 allows the electronic device 10 to exchange information/data with other devices through a computer network such as the Internet and/or various telecommunication networks.
处理器11可以是各种具有处理和计算能力的通用和/或专用处理组件。处理器11的一些示例包括但不限于中央处理单元（CPU）、图形处理单元（GPU）、各种专用的人工智能（AI）计算芯片、各种运行机器学习模型算法的处理器、数字信号处理器（DSP）、以及任何适当的处理器、控制器、微控制器等。处理器11执行上文所描述的各个方法和处理，例如电力网络空间中实体信任度的评估方法。The processor 11 may be a variety of general and/or special processing components with processing and computing capabilities. Some examples of the processor 11 include, but are not limited to, a central processing unit (CPU), a graphics processing unit (GPU), various special artificial intelligence (AI) computing chips, various processors running machine learning model algorithms, a digital signal processor (DSP), and any appropriate processor, controller, microcontroller, etc. The processor 11 executes the various methods and processes described above, such as an evaluation method for entity trust in a power network space.
在一些实施例中，电力网络空间中实体信任度的评估方法可被实现为计算机程序，其被有形地包含于计算机可读存储介质，例如存储单元18。在一些实施例中，计算机程序的部分或者全部可以经由ROM 12和/或通信单元19而被载入和/或安装到电子设备10上。当计算机程序加载到RAM 13并由处理器11执行时，可以执行上文描述的电力网络空间中实体信任度的评估方法的一个或多个步骤。备选地，在其他实施例中，处理器11可以通过其他任何适当的方式（例如，借助于固件）而被配置为执行电力网络空间中实体信任度的评估方法。In some embodiments, the method for evaluating the trust of entities in the power network space may be implemented as a computer program, which is tangibly contained in a computer-readable storage medium, such as a storage unit 18. In some embodiments, part or all of the computer program may be loaded and/or installed on the electronic device 10 via the ROM 12 and/or the communication unit 19. When the computer program is loaded into the RAM 13 and executed by the processor 11, one or more steps of the method for evaluating the trust of entities in the power network space described above may be performed. Alternatively, in other embodiments, the processor 11 may be configured to execute the method for evaluating the trust of entities in the power network space in any other appropriate manner (e.g., by means of firmware).
本文中以上描述的系统和技术的各种实施方式可以在数字电子电路系统、集成电路系统、场可编程门阵列（FPGA）、专用集成电路（ASIC）、专用标准产品（ASSP）、芯片上系统的系统（SOC）、负载可编程逻辑设备（CPLD）、计算机硬件、固件、软件、和/或它们的组合中实现。这些各种实施方式可以包括：实施在一个或者多个计算机程序中，该一个或者多个计算机程序可在包括至少一个可编程处理器的可编程系统上执行和/或解释，该可编程处理器可以是专用或者通用可编程处理器，可以从存储系统、至少一个输入装置、和至少一个输出装置接收数据和指令，并且将数据和指令传输至该存储系统、该至少一个输入装置、和该至少一个输出装置。Various implementations of the systems and techniques described above herein can be implemented in digital electronic circuit systems, integrated circuit systems, field programmable gate arrays (FPGAs), application specific integrated circuits (ASICs), application specific standard products (ASSPs), systems on chips (SOCs), load programmable logic devices (CPLDs), computer hardware, firmware, software, and/or combinations thereof. These various implementations can include: being implemented in one or more computer programs that can be executed and/or interpreted on a programmable system including at least one programmable processor, which can be a special purpose or general purpose programmable processor that can receive data and instructions from a storage system, at least one input device, and at least one output device, and transmit data and instructions to the storage system, the at least one input device, and the at least one output device.
用于实施本发明的方法的计算机程序可以采用一个或多个编程语言的任何组合来编写。这些计算机程序可以提供给通用计算机、专用计算机或其他可编程数据处理装置的处理器，使得计算机程序当由处理器执行时使流程图和/或框图中所规定的功能/操作被实施。计算机程序可以完全在机器上执行、部分地在机器上执行，作为独立软件包部分地在机器上执行且部分地在远程机器上执行或完全在远程机器或服务器上执行。Computer programs for implementing the methods of the present invention may be written in any combination of one or more programming languages. These computer programs may be provided to a processor of a general-purpose computer, a special-purpose computer, or other programmable data processing device, so that when the computer program is executed by the processor, the functions/operations specified in the flow chart and/or block diagram are implemented. The computer program may be executed entirely on the machine, partially on the machine, partially on the machine and partially on a remote machine as a stand-alone software package, or entirely on a remote machine or server.
在本发明的上下文中，计算机可读存储介质可以是有形的介质，其可以包含或存储以供指令执行系统、装置或设备使用或与指令执行系统、装置或设备结合地使用的计算机程序。计算机可读存储介质可以包括但不限于电子的、磁性的、光学的、电磁的、红外的、或半导体系统、装置或设备，或者上述内容的任何合适组合。备选地，计算机可读存储介质可以是机器可读信号介质。机器可读存储介质的更具体示例会包括基于一个或多个线的电气连接、便携式计算机盘、硬盘、随机存取存储器（RAM）、只读存储器（ROM）、可擦除可编程只读存储器（EPROM或快闪存储器）、光纤、便捷式紧凑盘只读存储器（CD-ROM）、光学储存设备、磁储存设备、或上述内容的任何合适组合。In the context of the present invention, a computer-readable storage medium may be a tangible medium that may contain or store a computer program for use by or in conjunction with an instruction execution system, device, or equipment. A computer-readable storage medium may include, but is not limited to, electronic, magnetic, optical, electromagnetic, infrared, or semiconductor systems, devices, or equipment, or any suitable combination of the foregoing. Alternatively, a computer-readable storage medium may be a machine-readable signal medium. A more specific example of a machine-readable storage medium may include an electrical connection based on one or more lines, 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 foregoing.
为了提供与用户的交互，可以在电子设备上实施此处描述的系统和技术，该电子设备具有：用于向用户显示信息的显示装置（例如，CRT（阴极射线管）或者LCD（液晶显示器）监视器）；以及键盘和指向装置（例如，鼠标或者轨迹球），用户可以通过该键盘和该指向装置来将输入提供给电子设备。其它种类的装置还可以用于提供与用户的交互；例如，提供给用户的反馈可以是任何形式的传感反馈（例如，视觉反馈、听觉反馈、或者触觉反馈）；并且可以用任何形式（包括声输入、语音输入或者、触觉输入）来接收来自用户的输入。To provide interaction with a user, the systems and techniques described herein may be implemented on an electronic device having: a display device (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor) for displaying information to the user; and a keyboard and a pointing device (e.g., a mouse or trackball) through which the user can provide input to the electronic device. Other types of devices may also be used to provide interaction with the user; for example, the feedback provided to the user may be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user may be received in any form (including acoustic input, voice input, or tactile input).
可以将此处描述的系统和技术实施在包括后台部件的计算系统（例如，作为数据服务器）、或者包括中间件部件的计算系统（例如，应用服务器）、或者包括前端部件的计算系统（例如，具有图形用户界面或者网络浏览器的用户计算机，用户可以通过该图形用户界面或者该网络浏览器来与此处描述的系统和技术的实施方式交互）、或者包括这种后台部件、中间件部件、或者前端部件的任何组合的计算系统中。可以通过任何形式或者介质的数字数据通信（例如，通信网络）来将系统的部件相互连接。通信网络的示例包括：局域网（LAN）、广域网（WAN）、区块链网络和互联网。The systems and techniques described herein may be implemented in a computing system that includes backend components (e.g., as a data server), or a computing system that includes middleware components (e.g., an application server), or a computing system that includes frontend components (e.g., a user computer with a graphical user interface or a web browser through which a user can interact with implementations of the systems and techniques described herein), or a computing system that includes any combination of such backend components, middleware components, or frontend components. The components of the system may be interconnected by any form or medium of digital data communication (e.g., a communication network). Examples of communication networks include: a local area network (LAN), a wide area network (WAN), a blockchain network, and the Internet.
计算系统可以包括客户端和服务器。客户端和服务器一般远离彼此并且通常通过通信网络进行交互。通过在相应的计算机上运行并且彼此具有客户端-服务器关系的计算机程序来产生客户端和服务器的关系。服务器可以是云服务器，又称为云计算服务器或云主机，是云计算服务体系中的一项主机产品，以解决了传统物理主机与VPS服务中，存在的管理难度大，业务扩展性弱的缺陷。A computing system may include a client and a server. The client and the server are generally remote from each other and usually interact through a communication network. The client and server relationship is generated by computer programs running on the corresponding computers and having a client-server relationship with each other. The server may be a cloud server, also known as a cloud computing server or cloud host, which is a host product in the cloud computing service system to solve the defects of difficult management and weak business scalability in traditional physical hosts and VPS services.
应该理解，可以使用上面所示的各种形式的流程，重新排序、增加或删除步骤。例如，本发明中记载的各步骤可以并行地执行也可以顺序地执行也可以不同的次序执行，只要能够实现本发明的技术方案所期望的结果，本文在此不进行限制。It should be understood that the various forms of processes shown above can be used to reorder, add or delete steps. For example, the steps described in the present invention can be executed in parallel, sequentially or in different orders, as long as the desired results of the technical solution of the present invention can be achieved, and this document does not limit this.
上述具体实施方式，并不构成对本发明保护范围的限制。本领域技术人员应该明白的是，根据设计要求和其他因素，可以进行各种修改、组合、子组合和替代。任何在本发明的精神和原则之内所作的修改、等同替换和改进等，均应包含在本发明保护范围之内。The above specific implementations do not constitute a limitation on the protection scope of the present invention. It should be understood by those skilled in the art that various modifications, combinations, sub-combinations and substitutions can be made according to design requirements and other factors. Any modification, equivalent substitution and improvement made within the spirit and principle of the present invention should be included in the protection scope of the present invention.
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