System data security evaluation method and device, storage medium and electronic equipment

Abstract

The application discloses a kind of system data security evaluation method and device, storage medium and electronic equipment, related to the field of financial technology.The method comprises the following steps: obtaining a knowledge graph and a full table, wherein the knowledge graph is used to evaluate the security risk of system data, and the full table is reference information of the knowledge graph;Based on the knowledge graph and the full table, an association table is created for evaluating the risk of system data;According to the association table, the risk value for evaluating the security of system data is calculated using the analytic hierarchy process;According to the risk value, the security risk level of system data is determined.By the present application, the problem that enterprises are difficult to evaluate the security of their own system data in related technology is solved.

Description

Technical Field

[0001] This application relates to the field of financial technology, and more specifically, to a method and apparatus for security assessment of system data, a storage medium, and an electronic device. Background Technology

[0002] With the advent of the "Internet+" and "Big Data" era, enterprises are facing security risks and hidden dangers related to data and personal privacy. For example, banks also face such risks and hidden dangers. Moreover, the banking industry is a major producer and user of data; therefore, if a bank experiences a data breach, it could have serious consequences for citizens, legal entities, society, and even the nation. Therefore, laws and regulations such as the "Data Security Law" (draft) and the "Guidelines for Financial Data Capability Building" (draft for comments) have all put forward relevant requirements for conducting risk assessments for data security. Furthermore, my country has successively issued "GB / T 20984-2007 Information Security Technology Information Security Risk Assessment Specification" in 2007 and "GB / T 31509-2015 Information Security Technology Information Security Risk Assessment Implementation Guide" in 2015 as general information security risk assessment standards. However, for data security, the operability of general standards is not strong, and currently, neither the national nor industry-specific risk assessment standards related to data security have been issued. In addition, there is a lack of relevant literature on theoretical frameworks or technical practices in this field. This shows that the field of data security risk assessment lacks systematic guidance in both theory and practice.

[0003] There is currently no effective solution to the problem that companies find it difficult to assess the security of their own system data in related technologies. Summary of the Invention

[0004] The main objective of this application is to provide a method, apparatus, storage medium, and electronic device for security assessment of system data, in order to solve the problem in related technologies that enterprises find it difficult to assess the security of their own system data.

[0005] To achieve the above objectives, according to one aspect of this application, a method for security assessment of system data is provided. The method includes: acquiring a knowledge graph and a full table, wherein the knowledge graph is used to assess the security risks of the system data, and the full table serves as reference information for the knowledge graph; creating an association table for assessing the risks of the system data based on the knowledge graph and the full table; calculating a risk value for assessing the security of the system data using the analytic hierarchy process (AHP) based on the association table; and determining the security risk level of the system data based on the risk value.

[0006] Further, determining the security risk level of the system data based on the risk value includes: obtaining a mapping table, wherein the mapping table includes at least: the security risk level, the risk value, and the mapping relationship between the security risk level and the risk value; matching the risk value in the mapping table to determine the security risk level of the system data.

[0007] Furthermore, before acquiring the knowledge graph and the full table, the method further includes: determining the basic element classes of risk assessment; based on the basic element classes of risk assessment, constructing the relationships between each basic element and its attributes in each basic element class in the system; constructing the knowledge graph based on the relationships between the basic elements and their attributes; determining the relationships between each basic element and the data lifecycle; and constructing the full table based on the relationships between the basic elements and the data lifecycle.

[0008] Furthermore, based on the knowledge graph and the full table, creating an association table for assessing the risk of system data includes: based on the content of the knowledge graph and the full table, using target basic elements as association fields, and combining target information, creating an association table for assessing the risk of system data, wherein the target information is at least one of the following: vulnerability rating standard information, security event monitoring logs, threat frequency information, and data asset importance information.

[0009] Further, based on the association table, the risk value for assessing the security of the system data is calculated using the analytic hierarchy process (AHP). This includes: based on the data processing scenario and data lifecycle, the security risks of the system data are hierarchically modeled using AHP to obtain a calculation model for assessing the security risks of the system data. The data processing scenario, the data lifecycle, and the correspondence between the data processing scenario and the data lifecycle are stored in the association table. The calculation model includes: a target layer, a criterion layer, and a solution layer. A matrix one of all factors in the data processing scenario and a matrix two of all factors in the data lifecycle are constructed. Based on the matrix one, the... The matrix-2 and normalization algorithm is used to calculate the weights corresponding to each factor in the data processing scenario and the data lifecycle; determine the risk value corresponding to each factor in the data lifecycle; calculate the risk value of the data lifecycle based on the weights and risk values ​​of each factor; calculate the risk value of each factor in the data processing scenario based on the risk value of the data lifecycle; calculate the risk value of the data processing scenario based on the weights and risk values ​​of each factor in the data processing scenario; and calculate a risk value for assessing the security of the system data based on the risk values ​​of multiple data processing scenarios.

[0010] Further, determining the risk value corresponding to each factor in the data lifecycle includes: identifying each basic element corresponding to each factor in the data lifecycle to obtain an identification result; setting a value for each basic element corresponding to each factor in the data lifecycle based on the identification result; calculating the probability value of the corresponding risk and the value of the loss caused by the risk based on the value; calculating the target risk value based on the probability value of the corresponding risk and the value of the loss caused by the risk; determining the risk value corresponding to each factor in the data lifecycle based on the target risk value, the quantity of target information corresponding to each factor in the data lifecycle, and a preset value, wherein the quantity of target information corresponding to each factor in the data lifecycle is stored in the association table, and the preset value is set by the target object according to its own situation to ensure that the risk value corresponding to each factor in the data lifecycle is within a preset range.

[0011] Further, constructing Matrix 1 of all factors in the data processing scenario and Matrix 2 of all factors in the data lifecycle includes: determining the importance level between every two factors in the data processing scenario and the importance level between every two factors in the data lifecycle; setting a corresponding value for each level based on the importance level between every two factors; obtaining the value corresponding to each factor in the data processing scenario and the data lifecycle based on the value corresponding to each level, the importance level between all factors in the data processing scenario, and the importance level between all factors in the data lifecycle; and constructing Matrix 1 of all factors in the data processing scenario and Matrix 2 of all factors in the data lifecycle based on the value corresponding to each factor in the data processing scenario and the data lifecycle.

[0012] Furthermore, after constructing a matrix one of all factors in the data processing scenario and a matrix two of all factors in the data lifecycle, the method further includes: verifying the importance between every two factors in the data processing scenario and the data lifecycle, in order to verify the accuracy of the matrix one of all factors in the data processing scenario and the matrix two of all factors in the data lifecycle.

[0013] To achieve the above objectives, according to another aspect of this application, a system data security assessment apparatus is provided. The apparatus includes: a first acquisition unit, configured to acquire a knowledge graph and a full table, wherein the knowledge graph is used to assess the security risks of the system data, and the full table serves as reference information for the knowledge graph; a first creation unit, configured to create an association table for assessing the risks of the system data based on the knowledge graph and the full table; a first calculation unit, configured to calculate a risk value for assessing the security of the system data using the analytic hierarchy process (AHP) based on the association table; and a first determination unit, configured to determine the security risk level of the system data based on the risk value.

[0014] Further, the first determining unit includes: a first acquiring module, used to acquire a mapping relationship table, wherein the mapping relationship table includes at least: the security risk level, the risk value, and the mapping relationship between the security risk level and the risk value; and a first matching module, used to match the risk value in the mapping relationship table to determine the security risk level of the system data.

[0015] Furthermore, the apparatus further includes: a second determining unit, configured to determine the basic element classes of risk assessment before acquiring the knowledge graph and the full table; a first constructing unit, configured to construct the relationships between each basic element and its attributes in each basic element class based on the basic element classes of risk assessment; a second constructing unit, configured to construct the knowledge graph based on the relationships between the basic elements and their attributes; a third determining unit, configured to determine the relationships between each basic element and the data lifecycle; and a third constructing unit, configured to construct the full table based on the relationships between the basic elements and the data lifecycle.

[0016] Furthermore, the first creation unit includes: a first creation module, used to create an association table for assessing the risk of system data based on the knowledge graph and the content of the full table, using target basic elements as association fields and combining target information, wherein the target information is at least one of the following: vulnerability rating standard information, security event monitoring logs, threat frequency information, and data asset importance information.

[0017] Further, the first computing unit includes: a first processing module, used to perform hierarchical modeling of the security risks of the system data based on the data processing scenario and data lifecycle, using the analytic hierarchy process (AHP), to obtain a computing model for assessing the security risks of the system data, wherein the data processing scenario, the data lifecycle, and the correspondence between the data processing scenario and the data lifecycle are stored in the association table, and the computing model includes: a target layer, a criterion layer, and a scheme layer; a first construction module, used to construct a matrix one of all factors in the data processing scenario and a matrix two of all factors in the data lifecycle; and a first computing module, used to calculate the data processing scenario based on the matrix one, the matrix two, and a normalization algorithm. The system comprises five modules: a first determining module, a second calculating module, and a third calculating module, a fourth calculating module, and a fifth calculating module. The first module determines the risk value corresponding to each factor in the data lifecycle, and the second module calculates the risk value of the data lifecycle based on the weights and risk values ​​of each factor. The second module calculates the risk value of the data processing scenario based on the risk values ​​of the data lifecycle. The third module calculates the risk value of each factor in the data processing scenario based on the risk values ​​of multiple data processing scenarios.

[0018] Further, the first determining module includes: a first processing submodule, used to identify each basic element corresponding to each factor in the data lifecycle and obtain an identification result; a first setting submodule, used to set a value for each basic element corresponding to each factor in the data lifecycle according to the identification result; a first calculation submodule, used to calculate the probability value of the corresponding risk and the value of the loss caused by the risk according to the value; a second calculation submodule, used to calculate the target risk value according to the probability value of the corresponding risk and the value of the loss caused by the risk; and a first determining submodule, used to determine the risk value corresponding to each factor in the data lifecycle according to the target risk value, the quantity of target information corresponding to each factor in the data lifecycle, and a preset value, wherein the quantity of target information corresponding to each factor in the data lifecycle is stored in the association table, and the preset value is set by the target object according to its own situation to ensure that the risk value corresponding to each factor in the data lifecycle is within a preset range.

[0019] Further, the first construction module includes: a second determining submodule, configured to determine the importance level between every two factors in the data processing scenario and the importance level between every two factors in the data lifecycle before constructing matrix one of all factors in the data processing scenario and matrix two of all factors in the data lifecycle; a second setting submodule, configured to set a corresponding value for each level according to the importance level between every two factors; a second processing submodule, configured to obtain the value corresponding to each factor in the data processing scenario and the data lifecycle according to the value corresponding to each level, the importance level between all factors in the data processing scenario, and the importance level between all factors in the data lifecycle; and a first construction submodule, configured to construct matrix one of all factors in the data processing scenario and matrix two of all factors in the data lifecycle according to the value corresponding to each factor in the data processing scenario and the data lifecycle.

[0020] Furthermore, the apparatus further includes: a first verification unit, configured to verify the importance between every two factors in the data processing scenario and the data lifecycle after constructing a matrix one of all factors in the data processing scenario and a matrix two of all factors in the data lifecycle, in order to verify the accuracy of the matrix one of all factors in the data processing scenario and the matrix two of all factors in the data lifecycle.

[0021] To achieve the above objectives, according to another aspect of this application, a computer-readable storage medium is provided, the storage medium including a stored program, wherein the program executes the security assessment method for system data described in any of the above claims.

[0022] To achieve the above objectives, according to another aspect of this application, a processor is provided for running a program, wherein the program executes the system data security assessment method described in any one of the above claims.

[0023] To achieve the above objectives, according to another aspect of this application, an electronic device is provided, the electronic device including one or more processors and a memory, the memory being used to store one or more programs, wherein when the one or more programs are executed by the one or more processors, the one or more processors cause the one or more processors to implement the system data security assessment method described in any one of the above.

[0024] This application employs the following steps: acquiring a knowledge graph and a full table, whereby the knowledge graph is used to assess the security risks of system data, and the full table serves as reference information for the knowledge graph; creating an association table based on the knowledge graph and the full table to assess the risks of system data; calculating the risk value for assessing the security of system data using the analytic hierarchy process (AHP) based on the association table; and determining the security risk level of the system data based on the risk value. This solves the problem in related technologies where enterprises find it difficult to assess the security of their own system data. By automatically calculating the data security risk value of the entire system using the knowledge graph, full table, association table, and AHP, and determining the security risk level of the entire system data based on the risk value, enterprises can accurately grasp the current security risk status of their own system data, thereby achieving the effect of enabling enterprises to assess the security of their own system data. Attached Figure Description

[0025] The accompanying drawings, which form part of this application, are used to provide a further understanding of this application. The illustrative embodiments and descriptions of this application are used to explain this application and do not constitute an undue limitation of this application. In the drawings:

[0026] Figure 1 This is a flowchart of a system data security assessment method provided according to an embodiment of this application;

[0027] Figure 2 This is a schematic diagram illustrating the mapping relationship between risk values ​​and risk levels in the embodiments of this application;

[0028] Figure 3 This is a schematic diagram of the knowledge graph for security risk assessment of system data in an embodiment of this application;

[0029] Figure 4This is a schematic diagram of the full table of system data in an embodiment of this application;

[0030] Figure 5 This is a schematic diagram of the security risk assessment association table of system data in an embodiment of this application;

[0031] Figure 6 This is a schematic diagram of the security risk calculation structure model of system data in the embodiments of this application;

[0032] Figure 7 This is a schematic diagram showing the weights corresponding to each factor in the criteria layer in the embodiments of this application;

[0033] Figure 8 This is a schematic diagram illustrating the security risk analysis of single vulnerability data in an embodiment of this application;

[0034] Figure 9 This is a schematic diagram of a method for determining the importance level of system data factors in an embodiment of this application;

[0035] Figure 10 This is a schematic diagram of the decision matrix in an embodiment of this application when each sub-layer of the criterion layer has n decision factors;

[0036] Figure 11 This is a schematic diagram of the hierarchical decision matrix of the criterion layer in the embodiments of this application;

[0037] Figure 12 This is a schematic diagram of a system data security assessment device provided according to an embodiment of this application. Detailed Implementation

[0038] It should be noted that, unless otherwise specified, the embodiments and features described in this application can be combined with each other. This application will now be described in detail with reference to the accompanying drawings and embodiments.

[0039] To enable those skilled in the art to better understand the present application, the technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present application, and not all embodiments. Based on the embodiments in the present application, all other embodiments obtained by those of ordinary skill in the art without creative effort should fall within the scope of protection of the present application.

[0040] It should be noted that the terms "first," "second," etc., in the specification, claims, and accompanying drawings of this application are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate for the embodiments of this application described herein. Furthermore, the terms "comprising" and "having," and any variations thereof, are intended to cover non-exclusive inclusion; for example, a process, method, system, product, or apparatus that comprises a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or units not explicitly listed or inherent to such processes, methods, products, or apparatus.

[0041] The present invention will now be described in conjunction with preferred implementation steps. Figure 1 This is a flowchart of a system data security assessment method provided according to an embodiment of this application, such as... Figure 1 As shown, the method includes the following steps:

[0042] Step S101: Obtain the knowledge graph and the full table. The knowledge graph is used to assess the security risks of system data, and the full table serves as reference information for the knowledge graph.

[0043] A security risk knowledge graph of the system data is obtained. This knowledge graph clearly defines the factors that need to be considered in conducting data security risk assessments, as well as the relationships between these factors. Therefore, the security risks of the system data can be assessed based on the knowledge graph. A full table is obtained and used as reference information for the knowledge graph.

[0044] Step S102: Based on the knowledge graph and the full table, create an association table for assessing the risk of system data.

[0045] The system data security risk knowledge graph is based on the full reference table content and automatically derives a risk assessment association table, which is used to assess the risks of the system data.

[0046] Step S103: Based on the association table, the risk value used to assess the security of system data is calculated using the analytic hierarchy process (AHP).

[0047] By using the Analytic Hierarchy Process (AHP) combined with a risk assessment association table, the data security risk value of the entire system can be automatically calculated.

[0048] Step S104: Determine the security risk level of the system data based on the risk value.

[0049] Each security risk level corresponds to a range of risk values, so the security risk level of the system data can be determined based on the range of risk values.

[0050] Through the steps S401 to S404 described above, the data security risk value of the entire system is automatically calculated using knowledge graphs, full tables, association tables, and analytic hierarchy process. Based on the risk value, the security risk level of the entire system's data is determined, thereby enabling enterprises to accurately grasp the current status of their own system's data security risks and achieve the effect of assessing the security of their own system's data.

[0051] Optionally, in the system data security assessment method provided in this application embodiment, determining the security risk level of the system data based on the risk value includes: obtaining a mapping relationship table, wherein the mapping relationship table includes at least: security risk level, risk value, and mapping relationship between security risk level and risk value; matching the risk value in the mapping relationship table to determine the security risk level of the system data.

[0052] For example, according to the national standard GB / T 20984-2007, risk levels are divided into 5 levels, and the mapping relationship between risk values ​​and risk levels can be set as follows: Figure 2 The table shown is used to compare the system's data security risk values. Figure 2 The table shown can be used to determine the security risk level of the corresponding system data.

[0053] By using the above approach, the security risk level of the system data can be accurately determined based on the system data's security risk value. This allows enterprises to scientifically understand the current state of data security risks in their own information systems and promptly address any security vulnerabilities.

[0054] Optionally, in the system data security assessment method provided in this application embodiment, before obtaining the knowledge graph and the full table, the method further includes: determining the basic element classes of risk assessment; constructing the association relationships between each basic element and the attributes of each basic element in each basic element class of the system based on the basic element classes of risk assessment; constructing a knowledge graph based on the association relationships between each basic element and the attributes of each basic element; determining the association relationships between each basic element and the data lifecycle; and constructing the full table based on the association relationships between each basic element and the data lifecycle.

[0055] Before acquiring a knowledge graph and a full table, it is necessary to construct them. For example, a knowledge graph for data security risk assessment of a banking system based on ontology can be constructed based on ontology, national standards and norms, and expert experience. Below, we first introduce the concepts of relevant terms used in constructing a knowledge graph based on ontology. In the field of artificial intelligence, an ontology is a standard and universal description of knowledge or concepts in a particular domain and the relationships between these concepts. It is formalized (e.g., graphically) using a standardized conceptual model, and this knowledge representation can be recognized by humans and understood by machines. There are many languages ​​for describing ontology; a common ontology language is OWL. Therefore, an ontology consists of elements such as classes, attributes, and relationships. An individual is an instantiation of a class; an entity is a concept in the knowledge graph domain, referring to objectively existing and distinguishable things. Entities can be concrete people, events, or things, or abstract concepts or relationships. The content of an entity can include classes, attributes, and individuals from an ontology. A knowledge graph can be represented as a set of triples, namely "entity-relationship-entity" or "entity-relationship-attribute value," forming a knowledge representation method that is both human-recognizable and machine-understandable. It displays structured knowledge, categorized and organized, in a network graph format. Furthermore, knowledge graphs can connect multi-source heterogeneous data into a network structure, focusing on discovering, analyzing, and solving problems from a "relationship" perspective, showcasing the integrity and interconnectedness of data at a deeper level, and broadening the dimensions of data information storage. In addition, knowledge graphs can use multi-dimensional relationship queries, community mining, and other computational algorithms to assist in querying deep relationships and uncovering potential relationships. Therefore, based on the above ontological concepts, tools can be used to construct a knowledge graph for the security risk assessment of banking system data, including establishing relationships between entities such as classes, attributes, and individuals. First, the main basic risk assessment element classes in the domain are constructed. Then, based on these basic risk assessment element classes, the relationships between basic elements and attributes such as assets, vulnerabilities, threats, security measures, and risks in the field of banking system data security are constructed. Taking a bank's online banking system as an example, here is a schematic diagram of constructing a knowledge graph for security risk assessment of the system's data, such as... Figure 3As shown in the diagram, the knowledge graph of data security risk assessment for the online banking system outlines the following categories: Assets are categorized according to the data flow stages of the system, including office terminal data, mobile client data, communication messages, database data, storage media data, and server data; Vulnerabilities are categorized according to information security domains, including application security vulnerabilities, network security vulnerabilities, server security vulnerabilities, and endpoint security vulnerabilities; Threats are categorized according to the data processing scenarios of the system, including internal office threats, operation and maintenance threats, hacker attack threats, and partner threats; Security Measures are categorized according to the data lifecycle, including general security measures, data acquisition security measures, data transmission security measures, data usage security measures, data storage security measures, data deletion security measures, and data destruction security measures. Individuals: Assets refer to all data assets in the online banking system, including user-uploaded personal data, approval forms, sensitive user information, client source code, transmitted data, and important business data. Vulnerabilities refer to system flaws discovered through inspection, assessment, penetration testing, and vulnerability scanning, such as SQL injection vulnerabilities, inadequate firewall controls, and weak database passwords. Threats refer to potential threats exposed in various data processing scenarios, including unauthorized photo downloading and transfer of sensitive information, accidental deletion of databases, and data transfer. The frequency of threats is derived from past events and monitoring logs of the system, as well as publicly available threat frequency information from the industry during the period of focus. Security measures refer to specific security measures at each stage of the data lifecycle in the online banking system, including authentication, authorization, compliance of data collection, and encrypted transmission. Attributes: Assets have an asset value attribute, which is defined by the assessed entity. For example, the value of user-uploaded personal data is medium, while the value of important business data is high. Vulnerabilities have a severity attribute, including the severity of the vulnerability itself and the severity of the environment in which it occurs. Threats have a threat frequency attribute, which can be obtained through security incidents, situational awareness tools, and publicly released threat intelligence. Relationships: In terms of assets, for example, user-uploaded personal data and approval forms are entities of the office terminal data type, while important business data are entities of the database data type; in terms of vulnerabilities, for example, SQL injection vulnerabilities are entities of the application security vulnerability type, while lax firewall controls are entities of the network security vulnerability type; in terms of threats, for example, unauthorized taking of photos, downloading, and transferring of sensitive information are entities of the internal office threat type; in terms of security measures, for example, authentication and authorization are entities of the general security measures type, while data collection compliance is an entity of the data collection security measures type.

[0056] For example, some examples of the constructed full table are as follows: Figure 4 As shown. From Figure 4The full vulnerability table clearly shows the relationships between all known vulnerabilities and threats, security measures, and data lifecycle in the field of data security. Furthermore, the data in the full vulnerability table can be developed based on publicly available vulnerability information, expert experience, and relevant data security protection standards. Additionally, since security measures mitigate threats, the security measures in the full vulnerability table are categorized into direct and indirect effects. Direct effects refer to threats that can be largely eliminated through security measures, while indirect effects refer to threats that can be weakened through security measures, but residual risks may remain.

[0057] The above approach clearly identifies the factors that need to be considered when conducting data security risk assessments, as well as the potential relationships between these factors. Therefore, when enterprises face complex systems, ordinary security personnel can leverage the experience of security experts and assessment staff to fully uncover data security risks.

[0058] Optionally, in the system data security assessment method provided in this application embodiment, creating an association table for assessing the risk of system data based on a knowledge graph and a full table includes: creating an association table for assessing the risk of system data based on the content of the knowledge graph and the full table, using target basic elements as association fields, and combining target information, wherein the target information is at least one of the following: vulnerability rating standard information, security event monitoring logs, threat frequency information, and data asset importance information.

[0059] For example, the knowledge graph for data security risk assessment of online banking systems, based on the content of the full reference table, uses vulnerability points as the main associated fields, combined with CVSS vulnerability rating standards, security event monitoring logs, publicly available threat frequency information, and information such as the importance of bank data assets, can automatically derive a risk assessment association table, such as... Figure 5As shown. Vulnerabilities are those discovered through inspection, assessment, penetration testing, and vulnerability scanning; vulnerability severity is calculated using the basic score rating method in the CVSS vulnerability rating standard, which classifies vulnerabilities into four levels: Severe (9.0-10.0), High (7.0-8.9), Medium (4.0-6.9), and Low (0-3.9); Threat refers to the threat corresponding to the vulnerability, which is objectively real; Threat frequency refers to the frequency of threat occurrence, mainly based on the system's past events and monitoring logs, as well as publicly available threat frequency information within the monitored period, according to the national standard GB / T 20984-2007, which classifies threat frequency into five levels: Very High (>=1 time / week), High (>=1 time / month), Medium (> times / half-year), Low (low frequency), and Very Low (almost impossible); Assets are the data assets corresponding to the vulnerability, derived from the asset category association knowledge graph in the reference table; Asset value is the value of the data assets, defined by the system's owner based on the importance of the data and the degree of impact caused by damage, according to the national standard GB / T From 2007 to 20984, asset value was divided into five levels: Very High (Very Important), High (Important), Medium (Relatively Important), Low (Not Very Important), and Very Low (Unimportant). The data lifecycle refers to the stages during data flow that may be attacked; this content originates from... Figure 4 The full table; data processing scenario refers to the specific data processing scenario where the threat exists, determined based on the threat category, this content is derived from the knowledge graph; actual security measures refer to the security measures actually adopted by the system, corresponding to the data lifecycle stages. Figure 3 Security measures in the knowledge graph; missing security measures refer to additional security measures needed to counter threats, besides the actual security measures. This is derived by comparing the security measures in the reference table with the actual security measures.

[0060] The above approach clearly identifies the relationships between various factors during data security risk assessment, the potential attack points in the data flow process, and the specific data processing scenarios where threats exist.

[0061] Optionally, in the system data security assessment method provided in this application embodiment, the risk value for assessing system data security is calculated using the analytic hierarchy process (AHP) based on the association table. This includes: based on the data processing scenario and data lifecycle, using the AHP to perform hierarchical modeling of system data security risks to obtain a calculation model for assessing system data security risks. The data processing scenario, data lifecycle, and the correspondence between the data processing scenario and data lifecycle are stored in the association table. The calculation model includes: a target layer, a criterion layer, and a scheme layer; constructing a matrix one of all factors in the data processing scenario and a matrix two of all factors in the data lifecycle; calculating the weights corresponding to each factor in the data processing scenario and data lifecycle based on matrices one, two, and a normalization algorithm; determining the risk value corresponding to each factor in the data lifecycle; calculating the risk value of the data lifecycle based on the weights and risk values ​​corresponding to each factor in the data lifecycle; calculating the risk value corresponding to each factor in the data processing scenario based on the risk value of the data lifecycle; calculating the risk value of the data processing scenario based on the weights and risk values ​​corresponding to each factor in the data processing scenario; and calculating the risk value for assessing system data security based on the risk values ​​of multiple data processing scenarios.

[0062] For example, utilizing the basic theory of the Analytic Hierarchy Process (AHP), a data security risk assessment algorithm is proposed that achieves hierarchical quantification of data assets based on data processing scenarios and data lifecycles. Risk analysis based on actual system data processing scenarios and data lifecycles more closely reflects the real-world operation of the system. The Analytic Hierarchy Process (AHP) is a decision-making method that decomposes elements relevant to decision-making into levels such as objectives, criteria, and solutions, and then performs qualitative and quantitative analysis based on this. The AHP treats a complex multi-objective decision problem as a system, decomposing the objective into multiple objectives or criteria, and further decomposing them into several levels of multiple indicators (or criteria, constraints). Through qualitative indicator fuzzy quantification methods, the hierarchical single ranking (weights) and overall ranking are calculated as a system method for optimizing decisions involving multiple objectives (multiple indicators) and multiple solutions. The AHP is particularly suitable for objective systems with hierarchically interleaved evaluation indicators, and for decision problems where the objective values ​​are difficult to describe quantitatively. Moreover, the AHP (Analytic Hierarchy Process) modeling involves four steps: first, establishing a hierarchical structure model, generally divided into three layers: target layer, criterion layer, and scheme layer; second, constructing a judgment matrix, comparing the influence between factors in the same layer and with the previous related factors for each layer; and third, calculating the weights of each layer, determining the matrix eigenvectors and calculating the weights based on the algorithm. Specifically, as follows: (1) Establishing a data security risk calculation structure model: using the AHP (Analytic Hierarchy Process), based on the data processing scenario and data lifecycle of the bank's online banking system, hierarchical modeling of the data security risk calculation of the system is carried out, such as... Figure 6As shown. Among them, the target layer: through a bottom-up mode, the system data security risk value is finally aggregated; the criteria layer: based on the actual data processing scenario of the system and the data life cycle risk under each data processing scenario, it is divided into two related upper and lower dimensions, that is, the risk values ​​under all data processing scenarios are aggregated to form the overall risk value of the system, and the risk values ​​of each link of the data life cycle under a certain data processing scenario are aggregated to form the risk value of that data processing scenario; the solution layer: determines the basic risk value algorithm of a single vulnerability point, and the risk values ​​corresponding to all vulnerability points under a certain data life cycle link are aggregated to form the risk value of that data life cycle link. The basic risk value of a single vulnerability point is a function of vulnerability, threat, asset and security measures. (2) Construct a hierarchical judgment matrix. (3) Calculate the weight of each layer: for the judgment matrix of each sub-layer of the criteria layer, and based on the matrix feature vector, the weight allocation of the judgment factors of each layer is obtained by normalization algorithm, such as Figure 7 As shown. Therefore, the calculation method for the system data security risk value is as follows: The data scenario risk value calculation formula is: System Data Security Risk Value = Internal Office Risk Value * 9.1% + Operation and Maintenance Management Risk Value * 18.2% + Internet Customer Risk Value * 45.5% + Partner Interaction * 27.2%; The data lifecycle risk value calculation formula is: Data Lifecycle Risk Value = Data Acquisition Risk Value * 12.5% ​​+ Data Transmission Risk Value * 18.75% + Data Usage Risk Value * 31.25% + Data Storage Risk Value * 25% + Data Deletion Risk Value * 6.25% + Data Destruction Risk Value * 6.25%. Finally, the system data security risk value is calculated through iterative layer-by-layer calculation of the criterion layer weights.

[0063] In summary, by utilizing the Analytic Hierarchy Process (AHP) to establish a hierarchical risk calculation structure model based on data processing scenarios and data lifecycles, a complete set of quantitative assessment formulas is obtained. Combined with a risk table, the data security risk value of the entire system is automatically calculated, enabling quantitative assessment of system data security risks. Furthermore, this calculation structure model supports risk calculation modes across different dimensions, including data processing scenarios and data lifecycle stages. This facilitates multi-dimensional analysis and investigation of system data by enterprises, continuously improving system data security.

[0064] Optionally, in the system data security assessment method provided in this application embodiment, determining the risk value corresponding to each factor in the data lifecycle includes: identifying each basic element corresponding to each factor in the data lifecycle and obtaining an identification result; setting a value for each basic element corresponding to each factor in the data lifecycle based on the identification result; calculating the probability value of the corresponding risk and the value of the loss caused by the risk based on the value; calculating the target risk value based on the probability value of the corresponding risk and the value of the loss caused by the risk; and determining the risk value corresponding to each factor in the data lifecycle based on the target risk value, the quantity of target information corresponding to each factor in the data lifecycle, and a preset value. The quantity of target information corresponding to each factor in the data lifecycle is stored in an association table, and the preset value is set by the target object according to its own situation to ensure that the risk value corresponding to each factor in the data lifecycle is within a preset range.

[0065] For example, according to the national standard GB / T 20984-2007, risk analysis mainly involves three basic elements and their attributes: assets, threats, and vulnerabilities. Therefore, based on this theory, combined with the characteristics of data security risks, and introducing the mitigation effect of security measures on threats, the principle of single vulnerability data security risk analysis is formulated as follows: (1) Identify data assets and assign asset values; (2) Identify data security threats and assign values ​​to the frequency of threat occurrence; (3) Identify data security vulnerabilities and assign values ​​to the severity of vulnerabilities of specific assets; (4) Determine the probability of a security incident based on data security threats, the ease with which threats exploit vulnerabilities, and the mitigation effect of security control measures on threats; (5) Calculate the losses caused by the security incident based on the severity of data security vulnerabilities and the value of data assets affected by the security incident; (6) Calculate the impact of a security incident on the organization, i.e., the risk value, based on the probability of a security incident and the losses after the security incident occurs. A schematic diagram of single vulnerability data security risk analysis is shown below. Figure 8 As shown, from Figure 8 It can be seen that the risk value of a single vulnerability is a function of the probability of a security incident and the loss caused by the incident. The probability of a security incident is a function of the likelihood of the threat faced, the vulnerability of the asset, and the effectiveness of security measures, while the loss caused by the security incident is a function of the asset's value and its vulnerability. Therefore, based on... Figure 8 Based on the analysis principle, the risk calculation for a single vulnerability is as follows: (1) Risk probability calculation formula: Where rh is the severity of vulnerability, ranging from 0 to 10, rc is the mitigation level of security measures, ranging from 0 to 10, t is the threat frequency, ranging from 0 to 10, and Rp ranges from 0 to 10; (2) Risk consequence calculation formula: Where rh is the severity of vulnerability, ranging from 0 to 10, wp is the asset value, ranging from 0 to 10, and Rl ranges from 0 to 10; (3) Formula for calculating the risk value of a single vulnerability: Wherein, Ri ranges from 0 to 10. Based on the above single vulnerability risk values, and according to... Figure 5 The system data security risk assessment association table contains data scenarios and vulnerability data throughout the data lifecycle, which are used to derive the risk value for a specific lifecycle stage within a given data scenario: Among them, μ is an adjustment factor, which is used by enterprises to control the range of risk values ​​based on the basic situation of the system. It is generally 0-20, and Rs is 0-10.

[0066] By using the above scheme, based on the values ​​of each basic element corresponding to each factor in the data lifecycle, the risk value corresponding to each factor in the data lifecycle can be accurately obtained. Furthermore, enterprises can set the values ​​of adjustment factors according to their own circumstances, thereby keeping the risk value within a certain range, and thus determining the risk level through the risk value.

[0067] Optionally, in the system data security assessment method provided in this application embodiment, constructing a matrix one of all factors in the data processing scenario and a matrix two of all factors in the data lifecycle includes: determining the importance level between every two factors in the data processing scenario and the importance level between every two factors in the data lifecycle; setting a corresponding value for each level based on the importance level between every two factors; obtaining the value corresponding to each factor in the data processing scenario and the data lifecycle based on the value corresponding to each level, the importance level between all factors in the data processing scenario, and the importance level between all factors in the data lifecycle; and constructing a matrix one of all factors in the data processing scenario and a matrix two of all factors in the data lifecycle based on the value corresponding to each factor in the data processing scenario and the data lifecycle.

[0068] Before constructing the hierarchical judgment matrix, it is necessary to first provide quantitative judgment criteria. In the analytic hierarchy process (AHP), several quantitative judgment methods can be used. For example, we can employ a 1-5 scale to provide quantitative scales for evaluating different situations, achieving a qualitative-to-quantitative calibration. Figure 9 As shown. Based on the above judgment method, combined with the system's own situation and expert experience, a judgment matrix is ​​constructed for the criterion layer. The judgment matrix for each of the n judgment factors in each sub-layer of the criterion layer can be shown as follows. Figure 10 As shown, where aii = 1, aji = aj / ai = 1 / aij, aij = aik / ajk (i,j,k = 1,2,3…n). Using the above determination method, a criterion layer is constructed as follows. Figure 11 The decision matrix is ​​shown.

[0069] The above method allows us to intuitively determine the importance of all factors, thus facilitating a comparison of the hierarchical relationship of importance among them.

[0070] Optionally, in the system data security assessment method provided in the embodiments of this application, after constructing a matrix one of all factors in the data processing scenario and a matrix two of all factors in the data lifecycle, the method further includes: verifying the importance between every two factors in the data processing scenario and the data lifecycle, so as to verify the accuracy of the matrix one of all factors in the data processing scenario and the matrix two of all factors in the data lifecycle.

[0071] After constructing the matrix, it is necessary to verify the consistency of the matrix, that is, to verify the accuracy of the matrix. This can be done by verifying the correctness of the matrix through the importance ranking of the factors.

[0072] The above method ensures the accuracy of the matrix, thereby guaranteeing the correctness of the final calculated safety risk value.

[0073] In summary, the system data security assessment method provided in this application acquires a knowledge graph and a full table, where the knowledge graph is used to assess the security risks of system data, and the full table serves as reference information for the knowledge graph. Based on the knowledge graph and the full table, an association table is created to assess the risks of system data. Using the association table, the analytic hierarchy process (AHP) is employed to calculate the risk value for assessing the security of the system data. Based on the risk value, the security risk level of the system data is determined, thus solving the problem in related technologies where enterprises find it difficult to assess the security of their own system data. By automatically calculating the data security risk value of the entire system using the knowledge graph, full table, association table, and AHP, and determining the security risk level of the entire system data based on the risk value, enterprises can accurately grasp the current security risk status of their own system data, thereby achieving the effect of enabling enterprises to assess the security of their own system data.

[0074] It should be noted that the steps shown in the flowchart in the accompanying drawings can be executed in a computer system such as a set of computer-executable instructions, and although a logical order is shown in the flowchart, in some cases the steps shown or described may be executed in a different order than that shown here.

[0075] This application also provides a system data security assessment device. It should be noted that the system data security assessment device of this application can be used to execute the system data security assessment method provided in this application. The system data security assessment device provided in this application is described below.

[0076] Figure 12 This is a schematic diagram of a system data security assessment device according to an embodiment of this application. Figure 12 As shown, the device includes: a first acquisition unit 1201, a first creation unit 1202, a first calculation unit 1203, and a first determination unit 1204.

[0077] Specifically, the first acquisition unit 1201 is used to acquire a knowledge graph and a full table, wherein the knowledge graph is used to assess the security risks of system data, and the full table serves as reference information for the knowledge graph.

[0078] The first creation unit 1202 is used to create an association table for assessing the risk of system data based on the knowledge graph and the full table.

[0079] The first calculation unit 1203 is used to calculate the risk value for assessing the security of system data based on the association table and using the analytic hierarchy process.

[0080] The first determining unit 1204 is used to determine the security risk level of system data based on the risk value.

[0081] In summary, the system data security assessment device provided in this application embodiment acquires a knowledge graph and a full table through a first acquisition unit 1201. The knowledge graph is used to assess the security risks of system data, and the full table serves as reference information for the knowledge graph. A first creation unit 1202 creates an association table for assessing the risks of system data based on the knowledge graph and the full table. A first calculation unit 1203 calculates the risk value for assessing the security of system data using the analytic hierarchy process (AHP) based on the association table. A first determination unit 1204 determines the security risk level of the system data based on the risk value. This solves the problem in related technologies where enterprises find it difficult to assess the security of their own system data. By automatically calculating the data security risk value of the entire system using the knowledge graph, full table, association table, and AHP, and determining the security risk level of the entire system data based on the risk value, enterprises can accurately grasp the current security risk status of their own system data, thereby achieving the effect of enabling enterprises to assess the security of their own system data.

[0082] Optionally, in the system data security assessment device provided in the embodiments of this application, the first determining unit includes: a first acquiring module, used to acquire a mapping relationship table, wherein the mapping relationship table includes at least: security risk level, risk value, and mapping relationship between security risk level and risk value; and a first matching module, used to match the risk value in the mapping relationship table to determine the security risk level of the system data.

[0083] Optionally, in the system data security assessment apparatus provided in this application embodiment, the apparatus further includes: a second determining unit, configured to determine the basic element classes of risk assessment before acquiring the knowledge graph and the full table; a first constructing unit, configured to construct the association relationships between each basic element and the attributes of each basic element in each basic element class of the system based on the basic element classes of risk assessment; a second constructing unit, configured to construct the knowledge graph based on the association relationships between each basic element and the attributes of each basic element; a third determining unit, configured to determine the association relationships between each basic element and the data lifecycle; and a third constructing unit, configured to construct the full table based on the association relationships between each basic element and the data lifecycle.

[0084] Optionally, in the system data security assessment device provided in this application embodiment, the first creation unit includes: a first creation module, used to create an association table for assessing the risk of system data based on the content of the knowledge graph and the full table, with the target basic elements as the association fields, combined with the target information, wherein the target information is at least one of the following: vulnerability rating standard information, security event monitoring logs, threat frequency information, and data asset importance information.

[0085] Optionally, in the system data security assessment device provided in this application embodiment, the first calculation unit includes: a first processing module, used to perform hierarchical modeling of the security risks of system data based on the data processing scenario and data lifecycle, using the analytic hierarchy process (AHP), to obtain a calculation model for assessing the security risks of system data, wherein the data processing scenario, data lifecycle, and the correspondence between the data processing scenario and data lifecycle are stored in an association table, and the calculation model includes: a target layer, a criterion layer, and a scheme layer; a first construction module, used to construct a matrix one of all factors in the data processing scenario and a matrix two of all factors in the data lifecycle; and a first calculation module, used to calculate based on the matrix one, the matrix two, and a normalization algorithm, the following: The system comprises five modules: a data processing scenario and a data lifecycle, each with its corresponding weight; a first determination module to determine the risk value for each factor in the data lifecycle; a second calculation module to calculate the risk value for the data lifecycle based on the weights and risk values ​​of each factor; a third calculation module to calculate the risk value for each factor in the data processing scenario based on the risk value for the data lifecycle; a fourth calculation module to calculate the risk value for the data processing scenario based on the weights and risk values ​​of each factor in the data processing scenario; and a fifth calculation module to calculate the risk value for assessing the security of the system data based on the risk values ​​for multiple data processing scenarios.

[0086] Optionally, in the system data security assessment device provided in this application embodiment, the first determining module includes: a first processing submodule, used to identify each basic element corresponding to each factor in the data lifecycle and obtain an identification result; a first setting submodule, used to set a value for each basic element corresponding to each factor in the data lifecycle according to the identification result; a first calculation submodule, used to calculate the probability value of the corresponding risk and the value of the loss caused by the risk according to the value; a second calculation submodule, used to calculate the target risk value according to the probability value of the corresponding risk and the value of the loss caused by the risk; and a first determining submodule, used to determine the risk value corresponding to each factor in the data lifecycle according to the target risk value, the quantity of target information corresponding to each factor in the data lifecycle, and a preset value, wherein the quantity of target information corresponding to each factor in the data lifecycle is stored in an association table, and the preset value is set by the target object according to its own situation to ensure that the risk value corresponding to each factor in the data lifecycle is within a preset range.

[0087] Optionally, in the system data security assessment device provided in this application embodiment, the first construction module includes: a second determining submodule, used to determine the importance level between every two factors in the data processing scenario and the importance level between every two factors in the data lifecycle before constructing a matrix one of all factors in the data processing scenario and a matrix two of all factors in the data lifecycle; a second setting submodule, used to set a corresponding value for each level according to the importance level between every two factors; a second processing submodule, used to obtain the value corresponding to each factor in the data processing scenario and the data lifecycle according to the value corresponding to each level, the importance level between all factors in the data processing scenario, and the importance level between all factors in the data lifecycle; and a first construction submodule, used to construct a matrix one of all factors in the data processing scenario and a matrix two of all factors in the data lifecycle according to the value corresponding to each factor in the data processing scenario and the data lifecycle.

[0088] Optionally, in the system data security assessment device provided in the embodiments of this application, the device further includes: a first verification unit, used to verify the importance between every two factors in the data processing scenario and the data lifecycle after constructing a matrix one of all factors in the data processing scenario and a matrix two of all factors in the data lifecycle, so as to verify the accuracy of the matrix one of all factors in the data processing scenario and the matrix two of all factors in the data lifecycle.

[0089] The system data security assessment device includes a processor and a memory. The first acquisition unit 1201, the first creation unit 1202, the first calculation unit 1203, and the first determination unit 1204 are all stored in the memory as program units. The processor executes the program units stored in the memory to achieve the corresponding functions.

[0090] The processor contains a kernel, which retrieves the corresponding program units from memory. One or more kernels can be configured, and by adjusting kernel parameters, enterprises can assess the security of their system data.

[0091] The memory may include non-permanent memory in computer-readable media, such as random access memory (RAM) and / or non-volatile memory, such as read-only memory (ROM) or flash RAM, and the memory includes at least one memory chip.

[0092] This invention provides a storage medium storing a program that, when executed by a processor, implements a method for security assessment of system data.

[0093] This invention provides a processor for running a program, wherein the program executes a security assessment method for system data during runtime.

[0094] This invention provides an electronic device, which includes a processor, a memory, and a program stored in the memory and executable on the processor. When the processor executes the program, it performs the following steps: acquiring a knowledge graph and a full table, wherein the knowledge graph is used to assess the security risks of system data, and the full table serves as reference information for the knowledge graph; creating an association table for assessing the risks of system data based on the knowledge graph and the full table; calculating a risk value for assessing the security of the system data using the analytic hierarchy process (AHP) based on the association table; and determining the security risk level of the system data based on the risk value.

[0095] When the processor executes the program, it also performs the following steps: determining the security risk level of the system data based on the risk value includes: obtaining a mapping table, wherein the mapping table includes at least: the security risk level, the risk value, and the mapping relationship between the security risk level and the risk value; matching the risk value in the mapping table to determine the security risk level of the system data.

[0096] When the processor executes the program, it also performs the following steps: Before acquiring the knowledge graph and the full table, the method further includes: determining the basic element classes of risk assessment; based on the basic element classes of risk assessment, constructing the association relationships between each basic element and the attributes of each basic element in each basic element class in the system; constructing the knowledge graph based on the association relationships between each basic element and the attributes of each basic element; determining the association relationships between each basic element and the data lifecycle; and constructing the full table based on the association relationships between each basic element and the data lifecycle.

[0097] When the processor executes the program, it also performs the following steps: Based on the knowledge graph and the full table, creating an association table for assessing the risk of system data includes: based on the content of the knowledge graph and the full table, using target basic elements as association fields, and combining target information, creating an association table for assessing the risk of system data, wherein the target information is at least one of the following: vulnerability rating standard information, security event monitoring logs, threat frequency information, and data asset importance information.

[0098] When the processor executes the program, it also performs the following steps: Based on the association table, using the analytic hierarchy process (AHP), it calculates the risk value used to assess the security of the system data, including: based on the data processing scenario and data lifecycle, using the AHP, it performs hierarchical modeling of the security risks of the system data to obtain a calculation model for assessing the security risks of the system data. The data processing scenario, the data lifecycle, and the correspondence between the data processing scenario and the data lifecycle are stored in the association table. The calculation model includes: a target layer, a criterion layer, and a solution layer; it constructs a matrix one of all factors in the data processing scenario and a matrix two of all factors in the data lifecycle; based on the... Matrix 1, Matrix 2, and the normalization algorithm are used to calculate the weights corresponding to each factor in the data processing scenario and the data lifecycle; the risk value corresponding to each factor in the data lifecycle is determined; based on the weights and risk values ​​of each factor in the data lifecycle, the risk value of the data lifecycle is calculated; based on the risk value of the data lifecycle, the risk value corresponding to each factor in the data processing scenario is calculated; based on the weights and risk values ​​of each factor in the data processing scenario, the risk value of the data processing scenario is calculated; based on the risk values ​​of multiple data processing scenarios, a risk value for assessing the security of the system data is calculated.

[0099] When the processor executes the program, it also performs the following steps: determining the risk value corresponding to each factor in the data lifecycle includes: identifying each basic element corresponding to each factor in the data lifecycle and obtaining an identification result; setting a value for each basic element corresponding to each factor in the data lifecycle based on the identification result; calculating the probability value of the corresponding risk and the value of the loss caused by the risk based on the value; calculating the target risk value based on the probability value of the corresponding risk and the value of the loss caused by the risk; determining the risk value corresponding to each factor in the data lifecycle based on the target risk value, the quantity of target information corresponding to each factor in the data lifecycle, and a preset value, wherein the quantity of target information corresponding to each factor in the data lifecycle is stored in the association table, and the preset value is set by the target object according to its own situation to ensure that the risk value corresponding to each factor in the data lifecycle is within a preset range.

[0100] When the processor executes the program, it also performs the following steps: constructing a matrix one of all factors in the data processing scenario and a matrix two of all factors in the data lifecycle includes: determining the importance level between every two factors in the data processing scenario and the importance level between every two factors in the data lifecycle; setting a corresponding value for each level based on the importance level between every two factors; obtaining the value corresponding to each factor in the data processing scenario and the data lifecycle based on the value corresponding to each level, the importance level between all factors in the data processing scenario, and the importance level between all factors in the data lifecycle; and constructing a matrix one of all factors in the data processing scenario and a matrix two of all factors in the data lifecycle based on the value corresponding to each factor in the data processing scenario and the data lifecycle.

[0101] The processor, when executing the program, also performs the following steps: after constructing a matrix one of all factors in the data processing scenario and a matrix two of all factors in the data lifecycle, the method further includes: verifying the importance between every two factors in the data processing scenario and the data lifecycle, to verify the accuracy of the matrix one of all factors in the data processing scenario and the matrix two of all factors in the data lifecycle. The device in this document can be a server, PC, PAD, mobile phone, etc.

[0102] This application also provides a computer program product, which, when executed on a data processing device, is suitable for executing an initialization program having the following method steps: acquiring a knowledge graph and a full table, wherein the knowledge graph is used to assess the security risks of system data, and the full table serves as reference information for the knowledge graph; creating an association table for assessing the risks of system data based on the knowledge graph and the full table; calculating a risk value for assessing the security of the system data using the analytic hierarchy process (AHP) based on the association table; and determining the security risk level of the system data based on the risk value.

[0103] When executed on a data processing device, it is also suitable to execute an initialization program with the following method steps: determining the security risk level of the system data based on the risk value includes: obtaining a mapping table, wherein the mapping table includes at least: the security risk level, the risk value, and the mapping relationship between the security risk level and the risk value; matching the risk value in the mapping table to determine the security risk level of the system data.

[0104] When executed on a data processing device, it is also suitable to execute an initialization procedure with the following method steps: before acquiring the knowledge graph and the full table, the method further includes: determining the basic element classes of risk assessment; based on the basic element classes of risk assessment, constructing the relationships between each basic element and the attributes of each basic element in each basic element class in the system; constructing the knowledge graph based on the relationships between the basic elements and the attributes of each basic element; determining the relationships between each basic element and the data lifecycle; and constructing the full table based on the relationships between the basic elements and the data lifecycle.

[0105] When executed on a data processing device, it is also suitable to execute an initialization program with the following method steps: Based on the knowledge graph and the full table, creating an association table for assessing the risk of system data includes: based on the content of the knowledge graph and the full table, using target basic elements as association fields, and combining target information, creating an association table for assessing the risk of system data, wherein the target information is at least one of the following: vulnerability rating standard information, security event monitoring logs, threat frequency information, and data asset importance information.

[0106] When executed on a data processing device, it is also suitable to execute an initialization program with the following method steps: Based on the association table, using the analytic hierarchy process (AHP), calculate the risk value for assessing the security of the system data, including: based on the data processing scenario and data lifecycle, using the AHP to perform hierarchical modeling of the security risks of the system data, obtaining a calculation model for assessing the security risks of the system data, wherein the data processing scenario, the data lifecycle, and the correspondence between the data processing scenario and the data lifecycle are stored in the association table, and the calculation model includes: a target layer, a criterion layer, and a scheme layer; constructing a matrix of all factors in the data processing scenario and a matrix of all factors in the data lifecycle. Matrix 2; Based on Matrix 1, Matrix 2, and the normalization algorithm, calculate the weights corresponding to each factor in the data processing scenario and the data lifecycle; determine the risk value corresponding to each factor in the data lifecycle; calculate the risk value of the data lifecycle based on the weights and risk values ​​of each factor in the data lifecycle; calculate the risk value corresponding to each factor in the data processing scenario based on the risk value of the data lifecycle; calculate the risk value of the data processing scenario based on the weights and risk values ​​of each factor in the data processing scenario; calculate a risk value for assessing the security of the system data based on the risk values ​​of multiple data processing scenarios.

[0107] When executed on a data processing device, it is also suitable to execute an initialization program with the following steps: determining the risk value corresponding to each factor in the data lifecycle includes: identifying each basic element corresponding to each factor in the data lifecycle and obtaining an identification result; setting a value for each basic element corresponding to each factor in the data lifecycle based on the identification result; calculating the probability value of the corresponding risk and the value of the loss caused by the risk based on the value; calculating a target risk value based on the probability value of the corresponding risk and the value of the loss caused by the risk; determining the risk value corresponding to each factor in the data lifecycle based on the target risk value, the quantity of target information corresponding to each factor in the data lifecycle, and a preset value, wherein the quantity of target information corresponding to each factor in the data lifecycle is stored in the association table, and the preset value is set by the target object according to its own situation to ensure that the risk value corresponding to each factor in the data lifecycle is within a preset range.

[0108] When executed on a data processing device, it is also suitable to execute an initialization program with the following method steps: constructing a matrix one of all factors in the data processing scenario and a matrix two of all factors in the data lifecycle, including: determining the importance level between every two factors in the data processing scenario and the importance level between every two factors in the data lifecycle; setting a corresponding value for each level according to the importance level between every two factors; obtaining the value corresponding to each factor in the data processing scenario and the data lifecycle according to the value corresponding to each level, the importance level between all factors in the data processing scenario and the importance level between all factors in the data lifecycle; and constructing a matrix one of all factors in the data processing scenario and a matrix two of all factors in the data lifecycle according to the value corresponding to each factor in the data processing scenario and the data lifecycle.

[0109] When executed on a data processing device, it is also suitable to execute an initialization procedure having the following method steps: after constructing a matrix one of all factors in the data processing scenario and a matrix two of all factors in the data lifecycle, the method further includes: verifying the importance between every two factors in the data processing scenario and the data lifecycle to verify the accuracy of the matrix one of all factors in the data processing scenario and the matrix two of all factors in the data lifecycle.

[0110] Those skilled in the art will understand that embodiments of this application can be provided as methods, systems, or computer program products. Therefore, this application can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, this application can take the form of a computer program product embodied on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0111] This application is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of this application. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, generate instructions for implementing the flowchart... Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

[0112] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing device to function in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process Figure 1 One or more processes and / or boxes Figure 1 The function specified in one or more boxes.

[0113] These computer program instructions may also be loaded onto a computer or other programmable data processing equipment to cause a series of operational steps to be performed on the computer or other programmable equipment to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable equipment for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 The steps of the function specified in one or more boxes.

[0114] In a typical configuration, a computing device includes one or more processors (CPU), input / output interfaces, network interfaces, and memory.

[0115] Memory may include non-persistent memory in computer-readable media, such as random access memory (RAM) and / or non-volatile memory, such as read-only memory (ROM) or flash RAM. Memory is an example of computer-readable media.

[0116] Computer-readable media includes both permanent and non-permanent, removable and non-removable media that can store information using any method or technology. Information can be computer-readable instructions, data structures, modules of programs, or other data. Examples of computer storage media include, but are not limited to, phase-change memory (PRAM), static random access memory (SRAM), dynamic random access memory (DRAM), other types of random access memory (RAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), flash memory or other memory technologies, CD-ROM, digital versatile optical disc (DVD) or other optical storage, magnetic tape, magnetic magnetic disk storage or other magnetic storage devices, or any other non-transferable medium that can be used to store information accessible by a computing device. As defined herein, computer-readable media does not include transient computer-readable media, such as modulated data signals and carrier waves.

[0117] It should also be noted that the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such process, method, article, or apparatus. Unless otherwise specified, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes that element.

[0118] Those skilled in the art will understand that embodiments of this application can be provided as methods, systems, or computer program products. Therefore, this application can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, this application can take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0119] The above are merely embodiments of this application and are not intended to limit the scope of this application. Various modifications and variations can be made to this application by those skilled in the art. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of this application should be included within the scope of the claims of this application.

Claims

1. A method for security assessment of system data, characterized in that, include: Obtain a knowledge graph and a full table, wherein the knowledge graph is used to assess the security risks of system data, and the full table serves as reference information for the knowledge graph; Based on the knowledge graph and the full table, create an association table for assessing the risk of system data; Based on the association table, the risk value used to assess the security of the system data is calculated using the analytic hierarchy process (AHP). Based on the risk value, determine the security risk level of the system data; Specifically, based on the association table, the risk values ​​used to assess the security of the system data, calculated using the analytic hierarchy process (AHP), include: Based on the data processing scenario and data lifecycle, the security risks of the system data are modeled hierarchically using the analytic hierarchy process (AHP) to obtain a computational model for assessing the security risks of the system data. The data processing scenario, the data lifecycle, and the correspondence between the data processing scenario and the data lifecycle are stored in the association table. The computational model includes: an objective layer, a criterion layer, and a solution layer. Construct a matrix one of all factors in the data processing scenario and a matrix two of all factors in the data lifecycle; Based on matrix one, matrix two, and the normalization algorithm, the weights corresponding to the data processing scenario and each factor in the data lifecycle are calculated. Determine the risk value corresponding to each factor in the data lifecycle; Based on the data processing scenario and the weights and risk values ​​corresponding to each factor in the data lifecycle, a risk value for assessing the security of the system data is calculated.

2. The method according to claim 1, characterized in that, Based on the risk value, the security risk level of the system data is determined as follows: Obtain a mapping relationship table, wherein the mapping relationship table includes at least: the security risk level, the risk value, and the mapping relationship between the security risk level and the risk value; The risk values ​​are matched against the mapping table to determine the security risk level of the system data.

3. The method according to claim 1, characterized in that, Before acquiring the knowledge graph and the full table, the method further includes: Determine the basic elements of risk assessment; Based on the basic element classes of the risk assessment, construct the association relationships between each basic element in each basic element class and the attributes of each basic element in the system; The knowledge graph is constructed based on the various basic elements and the relationships between their attributes. Determine the interrelationships between the various basic elements and the data lifecycle; Based on the relationships between the various basic elements and data lifecycles, the full table is constructed.

4. The method according to claim 3, characterized in that, Based on the knowledge graph and the full table, an association table for assessing the risk of system data is created, including: Based on the knowledge graph and the contents of the full table, an association table is created to assess the risk of system data, using the target basic elements as the association fields and combining the target information. The target information includes at least one of the following: vulnerability rating standard information, security event monitoring logs, threat frequency information, and data asset importance information.

5. The method according to claim 1, characterized in that, Based on the data processing scenario, the weight of each factor in the data lifecycle, and the risk value of each factor in the data lifecycle, a risk value for assessing the security of the system data is calculated, including: The risk value of the data lifecycle is calculated based on the weight and risk value corresponding to each factor in the data lifecycle. Based on the risk value of the data lifecycle, the risk value corresponding to each factor in the data processing scenario is calculated; The risk value of the data processing scenario is calculated based on the weight and risk value of each factor in the data processing scenario. Based on the risk values ​​of multiple data processing scenarios, a risk value for assessing the security of the system data is calculated.

6. The method according to claim 5, characterized in that, Determining the risk value for each factor in the data lifecycle includes: Each basic element corresponding to each factor in the data lifecycle is identified to obtain the identification result; Based on the identification results, set values ​​for each basic element corresponding to each factor in the data lifecycle; Based on the stated values, the probability of the risk occurring and the magnitude of the loss caused by the risk are calculated. The target risk value is calculated based on the probability value of the corresponding risk and the value of the loss caused by the risk. Based on the target risk value, the quantity of target information corresponding to each factor in the data lifecycle, and the preset value, the risk value corresponding to each factor in the data lifecycle is determined. The quantity of target information corresponding to each factor in the data lifecycle is stored in the association table. The preset value is set by the target object according to its own situation to ensure that the risk value corresponding to each factor in the data lifecycle is within a preset range.

7. The method according to claim 5, characterized in that, Constructing matrix one of all factors in the data processing scenario and matrix two of all factors in the data lifecycle includes: Determine the importance level between every two factors in the data processing scenario and the importance level between every two factors in the data lifecycle; Based on the degree of importance between each pair of factors, a corresponding numerical value is set for each level; Based on the numerical values ​​corresponding to each level, the importance levels among all factors in the data processing scenario, and the importance levels among all factors in the data lifecycle, the numerical values ​​corresponding to each factor in the data processing scenario and the data lifecycle are obtained. Based on the data processing scenario and the numerical values ​​corresponding to each factor in the data lifecycle, construct a matrix one of all factors in the data processing scenario and a matrix two of all factors in the data lifecycle.

8. The method according to claim 5, characterized in that, After constructing matrix one of all factors in the data processing scenario and matrix two of all factors in the data lifecycle, the method further includes: Verify the importance between the data processing scenario and every two factors in the data lifecycle to verify the accuracy of Matrix 1 of all factors in the data processing scenario and Matrix 2 of all factors in the data lifecycle.

9. A system data security assessment device, characterized in that, include: The first acquisition unit is used to acquire a knowledge graph and a full table, wherein the knowledge graph is used to assess the security risks of system data, and the full table serves as reference information for the knowledge graph. The first creation unit is used to create an association table for assessing the risk of system data based on the knowledge graph and the full table. The first calculation unit is used to calculate a risk value for assessing the security of the system data based on the association table using the analytic hierarchy process. The first determining unit is used to determine the security risk level of the system data based on the risk value; The first calculation unit further includes: a modeling subunit, used to perform hierarchical modeling of the security risks of the system data based on the data processing scenario and data lifecycle, using the analytic hierarchy process (AHP), to obtain a calculation model for assessing the security risks of the system data, wherein the data processing scenario, the data lifecycle, and the correspondence between the data processing scenario and the data lifecycle are stored in the association table, and the calculation model includes: a target layer, a criterion layer, and a scheme layer; a construction subunit, used to construct a matrix one of all factors in the data processing scenario and a matrix two of all factors in the data lifecycle; a first calculation subunit, used to calculate the weights corresponding to each factor in the data processing scenario and the data lifecycle based on the matrix one, the matrix two, and a normalization algorithm; a determination subunit, used to determine the risk value corresponding to each factor in the data lifecycle; and a second calculation subunit, used to calculate the risk value for assessing the security of the system data based on the weights corresponding to each factor in the data processing scenario and the data lifecycle, and the risk value corresponding to each factor in the data lifecycle.

10. A computer-readable storage medium, characterized in that, The storage medium includes a stored program, wherein the program executes the system data security assessment method according to any one of claims 1 to 8.

11. An electronic device, characterized in that, It includes one or more processors and a memory, the memory being used to store one or more programs, wherein when the one or more programs are executed by the one or more processors, the one or more processors cause the one or more processors to implement the system data security assessment method according to any one of claims 1 to 8.

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