Access control method and system of natural resource integration platform

Abstract

The application relates to the technical field of communication access control, in particular to an access control method and system of a natural resource integrated platform, which solve the technical problem of insufficient security protection capability of the prior art. The method comprises the following steps: in response to a resource access request message of a target user, obtaining a request resource set requested by the resource access request message, and extracting historical access behavior data of each natural resource in the request resource set by a department to which the target user belongs; performing historical access tendency analysis according to the historical access behavior data, and performing sensitivity evaluation in combination with spatial correlation characteristics of the request resource set to determine a risk index of a current access behavior; and performing access control on the target user according to the risk index.

Description

Technical Field

[0001] This invention relates to the field of communication access control technology, and specifically to an access control method and system for an integrated natural resource platform. Background Technology

[0002] The integrated natural resource platform centrally hosts multi-dimensional spatial natural resource data, including arable land resources, mineral rights resources, and watershed ecology. Access control technology is a crucial element in ensuring data security within this platform, protecting sensitive natural resource data by controlling user access behavior. Currently, mainstream integrated natural resource platforms in the industry generally employ Role-Based Access Control (RBAC) or Attribute-Based Access Control (ABAC) models for permission management.

[0003] In existing technologies, the aforementioned access control models primarily rely on user role attributes or static permission configurations for one-time permission determination. That is, when a user initiates a resource access request, the system decides whether to allow access solely based on the user's role or preset attribute rules. However, natural resource data exhibits significant spatial correlation characteristics. For example, adjacent land parcels may have ownership relationships, water resource data within the same watershed may have overlapping relationships, and resource data under the same project may have overall logical connections. When a user continuously accesses multiple spatially correlated natural resources within their legal permission scope, each individual access is legal under the static model's determination. However, the combination of multiple access results may allow the user to infer highly sensitive information beyond their permission scope. Traditional static access control models cannot identify such dynamic risks arising from the spatial correlation of multiple resources, resulting in blind spots in data security protection. Their security protection capabilities are insufficient to meet the needs of integrated natural resource platforms for refined protection of sensitive data. Summary of the Invention

[0004] To address the technical problem of insufficient security protection capabilities in existing technologies, the present invention aims to provide an access control method and system for an integrated natural resource platform. The specific technical solution adopted is as follows: This application provides an access control method for an integrated natural resources platform, including: In response to a resource access request message from a target user, obtain the set of requested resources requested in the resource access request message, and extract the historical access behavior data of the target user's department to each natural resource in the requested resource set; Historical access behavior data is used to analyze historical access tendencies, and sensitivity assessment is conducted by combining the spatial correlation characteristics of the requested resource set to determine the risk index of the current access behavior. Access control is implemented for target users based on risk index.

[0005] In one possible implementation, the method includes: Historical access tendency analysis is performed based on historical access behavior data to determine the historical access tendency of the target user's department to each natural resource in the requested resource set; the historical access tendency is used to characterize the degree of access preference of the target user's department to natural resources. Determine the set of projects involved in the requested resource set; Spatial correlation features are extracted based on the spatial boundary information of the natural resources of each project in the project set of the requested resource set to assess the spatial sensitivity of the requested resource set; spatial sensitivity is used to characterize the degree of risk of spatial leakage of natural resources in the requested resource set. The risk index of the current access behavior is determined based on the historical access tendency of the target user's department to the natural resources of each project in the project set of the requested resource set, as well as the spatial sensitivity of the requested resource set.

[0006] In one possible implementation, the method includes: Based on historical access behavior data, determine the average number of times and the average duration of access per person to each natural resource in the requested resource set by the department to which the target user belongs; The historical access tendency of the target user's department to each natural resource in the requested resource set is determined based on the historical average number of visits and the historical average access duration of each natural resource in the requested resource set by the target user's department.

[0007] In one possible implementation, the method includes: For each project in the project set, based on the spatial boundary information of the natural resources belonging to the project in the request resource set, determine the spatial clustering degree, spatial connectivity degree, and project coverage completeness of the project; spatial clustering degree is used to characterize the degree of spatial distribution clustering of the natural resources belonging to the project in the request resource set; spatial connectivity degree is used to characterize the degree of spatial connectivity of the natural resources belonging to the project in the request resource set; project coverage completeness is used to characterize the degree of coverage of the natural resources belonging to the project in the request resource set over the overall scope of the project. The spatial sensitivity of the requested resource set is determined based on the spatial clustering, spatial connectivity, and project coverage completeness of each project.

[0008] In one possible implementation, the method includes: For each project in the project set, based on the spatial boundary information of the natural resources belonging to the project in the request resource set, determine the sub-regions corresponding to each natural resource belonging to the project in the request resource set; The spatial agglomeration degree of the project is determined based on the area of ​​the sub-region corresponding to each natural resource and the area of ​​the smallest outlying region where the sub-region corresponding to each natural resource is located. Connectivity identification is performed on the sub-regions corresponding to each natural resource, and one or more connected sub-regions are obtained from the sub-regions corresponding to each natural resource. The spatial connectivity of a project is determined by the area of ​​one or more connected sub-regions and the area of ​​the sub-regions corresponding to each natural resource. The project coverage completeness is determined based on the area of ​​one or more connected sub-regions and the area of ​​the sub-regions corresponding to all natural resources in the project.

[0009] In one possible implementation, the method includes: For each project in the project set, the project sensitivity is determined based on the spatial clustering, spatial connectivity, and project coverage completeness of the project. The spatial sensitivity of the requested resource set is determined based on the project sensitivity of each project.

[0010] In one possible implementation, the method includes: For each project in the project set, the distribution characteristics of the historical access tendency of all natural resources in the project are analyzed to determine the access status of the target user's department to the project; the access status includes stable status and risk status. The risk index of the current access behavior is determined based on the historical access tendency of the target user's department to each natural resource in the requested resource set, the spatial sensitivity of the requested resource set, and the access status of each project.

[0011] In one possible implementation, the method includes: The average historical access tendency of the target user's department to the requested resource set is determined based on the historical access tendency of the target user's department to each natural resource in the requested resource set. When the access status of each project is stable, spatial sensitivity is suppressed based on the average historical access tendency to obtain the risk index of the current access behavior. When at least one item in the project set is in a risky access state, the spatial sensitivity is augmented based on the average historical access tendency to obtain the risk index of the current access behavior.

[0012] In one possible implementation, the method further includes: For projects in the project set whose access status is stable, each natural resource is filtered according to the historical access tendency of the target user's department to each natural resource in the requested resource set, resulting in a first resource subset and a second resource subset; the historical access tendency of natural resources in the first resource subset is less than the first tendency threshold, and the historical access tendency of natural resources in the second resource subset is greater than the second tendency threshold; the first tendency is less than the second tendency threshold. For each natural resource in the first resource subset, the natural resources are modified based on the historical access tendency of the natural resources in the second resource subset.

[0013] This application provides an access control system for an integrated natural resources platform, comprising: The data acquisition unit is used to respond to the resource access request message of the target user, acquire the set of requested resources requested in the resource access request message, and extract the historical access behavior data of the target user's department to each natural resource in the set of requested resources; The risk assessment unit is used to analyze historical access trends based on historical access behavior data, and to conduct sensitivity assessments by combining the spatial correlation characteristics of the requested resource set, thereby determining the risk index of the current access behavior. Access control unit, used to control access to target users based on risk index.

[0014] The present invention has the following beneficial effects: Based on the above technical solution, this application obtains the requested resource set and historical access behavior data in response to the resource access request message of the target user. It performs historical access tendency analysis based on the historical access behavior data and conducts sensitivity assessment by combining spatial correlation characteristics to determine the risk index. Then, it performs dynamic access control based on the risk index to solve the problem that traditional static models cannot identify combined leakage risks. This application achieves risk quantification by integrating departmental historical behavior characteristics and resource spatial correlation characteristics, thereby dynamically adjusting access strategies based on the risk index and effectively improving the security protection capability of natural resource data. Attached Figure Description

[0015] To more clearly illustrate the technical solutions and advantages in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0016] Figure 1 A flowchart illustrating an access control method for an integrated natural resource platform provided in one embodiment of the present invention; Figure 2 This is a system architecture diagram of an access control system for an integrated natural resource platform provided in one embodiment of the present invention. Detailed Implementation

[0017] To further illustrate the technical means and effects adopted by the present invention to achieve its intended purpose, the following, in conjunction with the accompanying drawings and preferred embodiments, details the specific implementation, structure, features, and effects of an access control method and system for an integrated natural resource platform proposed according to the present invention. In the following description, different "one embodiment" or "another embodiment" do not necessarily refer to the same embodiment. Furthermore, specific features, structures, or characteristics in one or more embodiments can be combined in any suitable form.

[0018] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention pertains.

[0019] In all division and logarithmic operations covered in this application, a smoothing mechanism is employed to prevent computer program crashes or invalid values ​​from being generated due to a zero denominator or zero input. Specifically, a positive correction factor is superimposed on the denominator term of the division operation or the argument term of the logarithmic function, thereby ensuring the robustness and feasibility of the algorithm under extreme conditions.

[0020] The following description, in conjunction with the accompanying drawings, details the specific scheme of the access control method and system for an integrated natural resource platform provided by this invention.

[0021] Please see Figure 1 The diagram illustrates a flowchart of an access control method for an integrated natural resource platform according to an embodiment of the present invention. The method includes the following steps: Step 101: In response to the resource access request message from the target user, obtain the set of requested resources requested in the resource access request message, and extract the historical access behavior data of the target user's department to each natural resource in the requested resource set.

[0022] Among them, the resource access request message is a data access request initiated by the target user in the integrated natural resources platform. The requested resource set includes one or more natural resources that the target user requests to access in this request. Historical access behavior data is used to characterize the past access situation of the natural resource by the department to which the target user belongs.

[0023] It should be noted that users of the integrated natural resources platform typically conduct their business according to their respective departments. Users within the same department share similar business responsibilities and data access needs; therefore, their historical access behavior can reflect the department's access preferences and habits for various natural resources. Historical access behavior data includes, but is not limited to, statistical information such as the number of times and duration of accesses to various natural resources by users from different departments. By analyzing historical access behavior data, the system can understand the frequency of access to different natural resources by each department, thus providing a data foundation for subsequent historical access trend analysis.

[0024] For example, when a target user initiates a resource access request, the system first parses the resource access request message and extracts the identification information of each natural resource in the requested resource set. Simultaneously, the system determines the target user's department based on their identity information and retrieves historical access behavior data for each natural resource in the requested resource set from the historical log database. For example, the historical log database can record statistical data such as the cumulative number of accesses and the cumulative access duration for each natural resource by users in each department within a recent time period (e.g., the last 30 days).

[0025] Step 102: Analyze historical access behavior based on historical access behavior data, and conduct sensitivity assessment by combining the spatial correlation characteristics of the requested resource set to determine the risk index of the current access behavior.

[0026] The risk index is used to quantify the potential risk level of the current access behavior. The higher the risk index, the greater the possibility that the current access behavior will cause a combination of data leakage risks, and the more stringent access control measures need to be taken.

[0027] It should be noted that historical access tendency analysis is used to assess the target user's department's familiarity with the requested resource. If the department has a stable history of high-frequency access to a certain type of natural resource, the risk of the current access behavior is relatively low.

[0028] Furthermore, due to the significant spatial correlation characteristics of natural resources, spatial relationships such as adjacent plots, coverage of the same watershed, and overlapping boundaries mean that multiple seemingly independent access behaviors to natural resources may combine to create data leakage risks. Therefore, this application also needs to extract spatial correlation features from the requested resource set for sensitivity assessment, analyzing the degree of correlation between the requested resource set in the spatial dimension. If multiple natural resources are highly clustered, connected, and have a wide coverage area in space, their combined leakage risk is high.

[0029] In traditional static access control models, permission determination is typically completed only once based on user roles or attributes, failing to identify abnormal changes in user behavior patterns. This application, however, introduces historical access tendency analysis to establish a baseline model of user access behavior to various natural resources across different departments. When a user's current access behavior deviates from the historical baseline (e.g., a sudden surge in access to resources previously accessed infrequently), it may indicate abnormal behavior, requiring increased vigilance. Simultaneously, through spatial correlation feature extraction and spatial sensitivity assessment, the potential data leakage risks arising from spatial resource associations can be identified. By comprehensively analyzing information from these two dimensions, this application achieves dynamic risk perception of access behavior, effectively compensating for the shortcomings of traditional static models.

[0030] Step 103: Implement access control for target users based on the risk index.

[0031] Access control includes various access control measures such as allowing access, rate limiting access, partially anonymized access, and denying access.

[0032] In some embodiments, this application may divide the risk index into different risk levels according to preset risk thresholds and risk level classification rules, and take corresponding access control measures according to the risk level corresponding to the risk index.

[0033] For example, the mapping relationship between risk index thresholds and access control measures can be pre-configured. Once the risk index of the current access behavior is determined, the corresponding access control measures can be selected and executed based on the threshold range in which the risk index falls.

[0034] For example, the access control policies are shown in Table 1 below: Table 1 Access Control Policy Table

[0035] Through the above methods, this application can implement differentiated access control measures based on the quantitative results of the risk index. It ensures business continuity for low-risk access behaviors, takes mitigation measures for medium-risk access behaviors, and implements strict control over high-risk access behaviors, thereby achieving a balance between security and availability, effectively preventing combined leakage risks while avoiding excessive interference with normal business operations.

[0036] Based on the above technical solution, this application obtains the requested resource set and historical access behavior data in response to the resource access request message of the target user. It performs historical access tendency analysis based on the historical access behavior data and conducts sensitivity assessment by combining spatial correlation characteristics to determine the risk index. Then, it performs dynamic access control based on the risk index to solve the problem that traditional static models cannot identify combined leakage risks. This application achieves risk quantification by integrating departmental historical behavior characteristics and resource spatial correlation characteristics, thereby dynamically adjusting access strategies based on the risk index and effectively improving the security protection capability of natural resource data.

[0037] As a possible embodiment of this application, the above-mentioned "analyzing historical access tendencies based on the historical access behavior data, and conducting sensitivity assessments in conjunction with the spatial correlation characteristics of the requested resource set to determine the risk index of the current access behavior" can be achieved through the following steps: Step 201: Analyze historical access trends based on historical access behavior data to determine the historical access trend of the target user's department to each natural resource in the requested resource set.

[0038] Among them, historical access preference is used to characterize the degree of access preference of the target user's department for natural resources. The higher the historical access preference, the more frequently and familiar the department is with the natural resource.

[0039] In one possible implementation, this application can determine the historical average number of visits and the historical average visit duration per person for each natural resource in the requested resource set by the department to which the target user belongs, based on historical access behavior data.

[0040] Among them, the historical average number of visits per person is used to characterize the average frequency of visits to the natural resource by each member of the department, and the historical average visit duration per person is used to characterize the average depth of visits to the natural resource by each member of the department.

[0041] Because different departments have different staff sizes, it is difficult to make cross-departmental comparisons by directly using total number of visits and total visit duration. By calculating per capita indicators, the impact of department size differences on the analysis results can be eliminated, making the visit preferences of different departments comparable.

[0042] For example, this application can extract the total number of historical visits and the total historical visit duration from historical visit behavior data, and at the same time obtain the total number of people in the department. Then, the total number of historical visits is divided by the total number of people to obtain the average number of historical visits per person, and the total historical visit duration is divided by the total number of people to obtain the average historical visit duration per person.

[0043] Subsequently, the historical access tendency of the target user's department to each natural resource in the requested resource set is determined based on the historical average number of visits and the historical average access duration of each natural resource in the requested resource set.

[0044] Among them, the historical average number of visits per person reflects the breadth of visits, while the historical average visit duration per person reflects the depth of visits. The more historical average number of visits per person and the longer the historical average visit duration per person, the stronger the user preference for this type of natural resource, and the higher the corresponding historical visit tendency.

[0045] For example, historical visit preference satisfies the following formula: ; in, For the department to which the target user belongs, the first item in the requested resource set Historical access preferences for natural resources For the department to which the target user belongs, the first item in the requested resource set The historical average number of visits per person to each natural resource For the department to which the target user belongs, the first item in the requested resource set The average historical visit duration per person for each natural resource To find the maximum value function, Used to obtain the maximum number of visits per person in historical visits. Used to obtain the maximum historical average visit duration per visitor. It is a safety parameter used to correct for denominators of 0. Dimensions and The same applies; the specific value can be determined based on... The value of the value determines the outcome, such as , Dimensions and The same applies; the specific value can be determined based on... The value of the value determines the outcome, such as .

[0046] The above formula combines the historical average number of visits per person and the historical average visit duration per person, and normalizes the result using the maximum value to obtain the historical visit tendency. In this way, the range of historical visit tendency values ​​can be controlled within a reasonable range, facilitating subsequent risk index calculations.

[0047] Step 202: Determine the set of projects involved in the requested resource set.

[0048] The project collection includes projects belonging to each natural resource in the request resource collection. Resources in the integrated natural resource platform are usually organized and managed according to the project dimension, such as farmland monitoring projects and mining rights management projects.

[0049] Each natural resource can belong to one or more projects, such as "Farmland Protection Project in County A" or "Mineral Resource Development Project in City B." A project is a unit that manages and organizes a class of natural resources in a unified manner. By determining the set of projects involved in the requested resource set, the scope of subsequent spatial correlation feature extraction and analysis can be clarified. This application can determine the project to which each natural resource in the requested resource set belongs, and summarize and deduplicate all the obtained projects to obtain the project set.

[0050] Step 203: Based on the spatial boundary information of the natural resources of each project in the project set, extract spatial correlation features and evaluate the spatial sensitivity of the request resource set.

[0051] Spatial sensitivity is used to characterize the risk of spatial leakage of natural resources in a requested resource set. Higher spatial sensitivity indicates a stronger spatial correlation between the requested resource set and a greater risk of combined leakage.

[0052] The aforementioned spatial boundary information describes the distribution range and boundary morphology of natural resources in geographic space, typically represented in the form of vector polygon data. Spatial boundary information is one of the core characteristics of natural resources, and the positional relationship of different natural resources in geographic space directly affects the degree of information leakage risk. When multiple natural resources are highly clustered in space, interconnected, and have a wide coverage area, users can use geographic information system (GIS) technologies such as spatial overlay analysis and buffer analysis to reconstruct complete regional information from scattered resource data. For example, the combination of ownership information of adjacent land parcels may reveal the overall development plan, and the combination of water quality data from multiple monitoring points within the same watershed may infer the distribution of pollution sources. This application can quantify the risk of information leakage in this spatial dimension by extracting spatial correlation features, and assess the spatial sensitivity of the requested resource set by analyzing the spatial distribution morphology, connectivity, and coverage of natural resources.

[0053] Step 204: Determine the risk index of the current access behavior based on the historical access tendency of the target user's department to the natural resources of each project in the project set and the spatial sensitivity of the requested resource set.

[0054] It should be noted that historical access tendency reflects the rationality of access from a behavioral pattern perspective, while spatial sensitivity reflects the possibility of leakage from a resource attribute perspective. A single-dimensional assessment is insufficient for a comprehensive analysis of the risk situation: considering only historical access tendency may overlook the combined leakage risk caused by spatial correlations, while considering only spatial sensitivity may misjudge routine business access as high-risk behavior. Therefore, this application integrates the assessment results from both dimensions to construct a comprehensive risk index.

[0055] In this application, the interaction between historical access tendency and spatial sensitivity can be considered during the integration process. For example, when a department has a stable access history to a project, the risk brought by high spatial sensitivity can be partially offset; while when a department's access pattern to a project is unstable, there may be abnormal access risk even if the spatial sensitivity is low.

[0056] Based on the above technical solution, this application determines the historical access tendency by analyzing historical access behavior data. Then, it identifies the set of projects involved in the requested resource set, and further extracts spatial correlation features based on spatial boundary information to assess spatial sensitivity. Finally, it integrates historical access tendency and spatial sensitivity to determine a risk index, thereby achieving multi-dimensional quantification of risk assessment. This technical solution, through the collaborative analysis of departmental behavioral characteristics and resource spatial characteristics, considers both the historical rationality of access behavior and the spatial risk of resource combinations, improving the accuracy and comprehensiveness of risk identification.

[0057] As a possible embodiment of this application, the above-mentioned "extracting spatial association features based on the spatial boundary information of the natural resources of each project in the project set of the requested resource set, and evaluating the spatial sensitivity of the requested resource set" can be achieved through the following steps: Step 301: For each project in the project set, determine the spatial clustering degree, spatial connectivity degree, and project coverage completeness of the project based on the spatial boundary information of the natural resources belonging to the project in the request resource set.

[0058] Among them, spatial clustering is used to characterize the degree of spatial distribution clustering of natural resources belonging to the project in the requested resource set, spatial connectivity is used to characterize the degree of spatial connectivity of natural resources belonging to the project in the requested resource set, and project coverage integrity is used to characterize the degree of coverage of natural resources belonging to the project in the requested resource set to the overall scope of the project.

[0059] It should be noted that spatial correlation feature extraction can be carried out from three dimensions: spatial clustering, spatial connectivity, and coverage completeness. Spatial clustering reflects the compactness of resources in space; the higher the clustering, the closer the spatial distance between resources and the stronger the information association. Spatial connectivity reflects the spatial continuity between resources; the higher the connectivity, the greater the possibility of resources forming continuous regions, and the higher the overall risk of information leakage. Coverage completeness reflects the coverage ratio of the requested resources to the overall scope of the project; the higher the coverage ratio, the greater the possibility of reconstructing the full picture of the project through combinatorial reasoning. By integrating the features of the above three dimensions, the spatial sensitivity of the requested resource set can be comprehensively evaluated.

[0060] Step 302: Determine the spatial sensitivity of the requested resource set based on the spatial clustering, spatial connectivity, and project coverage completeness of each project.

[0061] In one possible implementation, this application can determine the project sensitivity of each project in the project set based on the spatial clustering degree, spatial connectivity degree, and project coverage completeness of the project.

[0062] Among them, project sensitivity is used to characterize the degree of spatial leakage risk of the project under the current access request.

[0063] For example, project sensitivity satisfies the following formula: ; in, For the first Project sensitivity of each project For the first Spatial clustering of individual projects For the first Spatial connectivity of each project For the first The completeness of project coverage for each project.

[0064] Spatial clustering, spatial connectivity, and project coverage completeness reflect spatial correlation characteristics from different dimensions. The above formula can comprehensively reflect the overall spatial leakage risk of a project from these three dimensions. When any one dimension is low, the project sensitivity will decrease accordingly; only when all three dimensions are high will the project sensitivity reach a high level.

[0065] Then, the spatial sensitivity of the requested resource set is determined based on the project sensitivity of each project.

[0066] In some embodiments, this application may use the maximum value of the project sensitivity of each project as the spatial sensitivity of the requested resource set to ensure the conservatism and security of the risk assessment.

[0067] Based on the above technical solution, this application can determine the spatial clustering, spatial connectivity, and project coverage completeness of each project in the project set according to the spatial boundary information of the natural resources belonging to the project in the requested resource set. Then, it can determine the spatial sensitivity based on the three factors, thereby realizing the multi-dimensional quantification of the spatial association characteristics of resources. Through the comprehensive analysis of clustering, connectivity, and coverage, the spatial dimension characteristics of combined leakage risk are accurately assessed.

[0068] As a possible embodiment of this application, the above-mentioned "determining the spatial clustering degree, spatial connectivity degree, and project coverage completeness of each project in the project set based on the spatial boundary information of the natural resources belonging to the project in the requested resource set" can be achieved through the following steps: Step 401: For each project in the project set, determine the sub-regions corresponding to each natural resource in the request resource set that belongs to the project, based on the spatial boundary information of the natural resources belonging to the project in the request resource set.

[0069] Each natural resource has corresponding spatial boundary information. In the Geographic Information System (GIS) data of the integrated natural resource platform, the spatial form of natural resources includes point-like natural resources (such as single ancient trees and mining sites), linear natural resources (such as river centerlines and roads), and areal natural resources (such as cultivated land plots and lake surfaces). For areal natural resources, the area covered by its spatial boundary is the original sub-region corresponding to that natural resource; for point-like and linear natural resources, since they do not have two-dimensional area attributes, corresponding equivalent sub-regions need to be generated through preset spatial transformation rules.

[0070] For point-like natural resources in the requested resource set, a circular buffer with a preset radius is generated based on their spatial coordinates. The range of this buffer is used as the equivalent sub-region corresponding to the point-like natural resource. The preset radius can be configured according to the type of natural resource and business sensitivity. For example, a buffer with a radius of 50 meters can be set for a single ancient tree protection point, and a buffer with a radius of 200 meters can be set for a mining right inflection point.

[0071] For linear natural resources in the requested resource set, a buffer zone of preset width is generated on both sides based on its line path, and the range of this buffer zone is used as the equivalent sub-region corresponding to the linear natural resource. The preset width can be configured according to the type of natural resource and business sensitivity. For example, a buffer zone of 100 meters can be set on both sides of the center line of a river, and a buffer zone of 50 meters can be set on both sides of the planned road red line.

[0072] Step 402: Determine the spatial clustering degree of the project based on the area of ​​the sub-region corresponding to each natural resource and the area of ​​the smallest outlying area where the sub-region corresponding to each natural resource is located.

[0073] For example, the minimum bounding area can be represented by the minimum bounding rectangle containing the sub-regions corresponding to all natural resources belonging to the project in the requested resource set.

[0074] It should be noted that when the sub-regions are relatively dispersed, the area of ​​the minimum outer region will be significantly larger than the area of ​​the union of the sub-regions, resulting in low spatial clustering; conversely, when the sub-regions are highly clustered, the area of ​​the minimum outer region is close to the area of ​​the union of the sub-regions, resulting in high spatial clustering.

[0075] For example, spatial clustering satisfies the following formula: ; in, For the first Spatial clustering of individual projects For the first The area of ​​the joint region corresponding to each project can be determined by requesting resources belonging to the first [project name]. The area of ​​each sub-region corresponding to the natural resources of each project is determined by the area of ​​the sub-regions in the requested resource set. The project consists of sub-regions corresponding to the various natural resources of each project. For the set of requested resources belonging to the first The area of ​​the minimum bounding rectangle of each natural resource sub-region of each project.

[0076] Step 403: Perform connectivity identification on the sub-regions corresponding to each natural resource, and obtain one or more connected sub-regions from the sub-regions corresponding to each natural resource.

[0077] Connectivity identification is used to determine whether sub-regions are spatially adjacent or share boundaries. If two sub-regions share a boundary or overlap, they are considered connected. Through connectivity identification, all interconnected sub-regions can be merged into a single connected sub-region, resulting in one or more connected sub-regions. If a sub-region does not share a boundary or overlap with any other sub-region, it is considered a non-connected sub-region, also known as an isolated sub-region, and does not participate in the formation of connected sub-regions.

[0078] Step 404: Determine the spatial connectivity of the project based on the area of ​​one or more connected sub-regions and the area of ​​the sub-regions corresponding to each natural resource.

[0079] Spatial connectivity reflects the spatial continuity between natural resources. The higher the spatial connectivity, the closer the spatial connection between the requested natural resources, and the wider the coverage of the resulting data combination.

[0080] For example, spatial connectivity satisfies the following formula: ; in, For the first Spatial connectivity of each project For the first The number of connected sub-regions for each project. For the first The first project The area of ​​each connected subregion. For the first The area of ​​the joint region corresponding to each project can be determined by requesting resources belonging to the first [project name]. The area of ​​each sub-region corresponding to the natural resources of each project is determined by the area of ​​the sub-regions in the requested resource set. The project consists of sub-regions corresponding to the various natural resources of each project.

[0081] Step 405: Determine the project coverage completeness based on the area of ​​one or more connected sub-regions and the area of ​​the sub-regions corresponding to all natural resources in the project.

[0082] The area of ​​the sub-regions corresponding to all natural resources in the project refers to the total geographical area covered by all natural resources registered in the system for the project. Considering that there may be multiple overlapping natural resource records in the same geographic space (such as monitoring patches from different years or overlay layers with different ownership), the total geographical area should be determined based on spatial union operation, that is, by merging the sub-regions corresponding to all natural resources in the project and removing the overlapping parts to determine the actual coverage area.

[0083] It should be noted that project coverage completeness reflects the proportion of the overall project information covered by the currently requested resource. The higher the project coverage completeness, the larger the proportion of the project scope covered by the requested resource, and the higher the probability of inferring information about sensitive areas in the project that have not been requested through data combination analysis.

[0084] For example, project coverage completeness satisfies the following formula: ; in, For the first The completeness of project coverage for each project For the first The area of ​​the joint region corresponding to each project can be determined by requesting resources belonging to the first [project name]. The area of ​​each sub-region corresponding to the natural resources of each project is determined by the area of ​​the sub-regions in the requested resource set. The project consists of sub-regions corresponding to the various natural resources of each project. For the first The total geographical area of ​​each project, i.e., the first... The area of ​​the joint region obtained by spatially integrating the sub-regions corresponding to all natural resources in each project.

[0085] Based on the above technical solution, this application determines the sub-regions corresponding to each natural resource, and then calculates the spatial clustering degree, identifies connected sub-regions and calculates the spatial connectivity and project coverage completeness, thereby realizing the refined extraction of spatial association features. Through area ratio and connectivity analysis, the closeness of the spatial association of resources is accurately quantified.

[0086] As a possible embodiment of this application, the above-mentioned "determining the risk index of the current access behavior based on the historical access tendency of the target user's department to the natural resources of each project in the project set and the spatial sensitivity of the requested resource set" can be achieved through the following steps: Step 501: For each project in the project set, perform a distribution characteristic analysis on the historical access tendency of all natural resources in the project to determine the access status of the target user's department to the project.

[0087] The access status includes a stable status and a risk status. A stable status indicates that the target user's department's access behavior to the project conforms to historical patterns, and the access records are stable and predictable. A risk status indicates that the target user's department's access behavior to the project deviates from historical patterns, and there is suspicion of abnormal access.

[0088] This application can analyze the distribution characteristics of historical access tendency from the following two dimensions: The first dimension is the fluctuation of historical access tendency, which can be measured using statistical indicators such as variance. The smaller the fluctuation, the more stable the access pattern. The second dimension is the proportion of resources with high historical access tendency. This can be calculated by counting the proportion of resources with historical access tendency exceeding a preset threshold to the total resources. The higher the proportion, the wider the department's access coverage of the project and the clearer the access focus. By comprehensively considering these two dimensions, the access status of the target user's department to the project can be determined.

[0089] In some embodiments, for each project in the project set, if the variance of the historical access tendency of the target user's department to all natural resources in the requested resource set for that project is less than a preset variance threshold, and the proportion of natural resources with a historical access tendency greater than the preset tendency threshold is greater than a preset proportion, the access status of the target user's department to that project is determined to be a stable state; otherwise, the access status of the target user's department to that project is determined to be a risky state.

[0090] The preset variance threshold, preset bias threshold, and preset percentage can be determined based on actual statistical data. For example, the preset variance threshold can be 0.05, the preset bias threshold can be 0.6, and the preset percentage can be 0.5.

[0091] This application can pre-calculate the access status of each department to each project offline and store the calculation results as access status tags for quick query and use when processing access requests.

[0092] Step 502: Determine the risk index of the current access behavior based on the historical access tendency of the target user's department to each natural resource in the requested resource set and the spatial sensitivity of the requested resource set, combined with the access status of each project.

[0093] It should be noted that for projects in a stable state, a department's high-frequency access history can reduce risk; however, for projects in a risky state, even a high degree of access history bias may still pose an abnormal access risk. Therefore, this application can further combine the access status of each project to adopt appropriate analysis strategies to determine the risk index of current access behavior.

[0094] Based on the above technical solution, this application determines the access status by analyzing the distribution characteristics of the historical access tendency of all resources in the project, and then determines the risk index by combining the historical access tendency, spatial sensitivity and access status, thereby realizing the dynamic adaptability of risk assessment. By distinguishing between stable access and abnormal access scenarios, the targeting and accuracy of risk index calculation are improved.

[0095] As a possible embodiment of this application, the above-mentioned "determining the risk index of the current access behavior based on the historical access tendency of the target user's department to each natural resource in the requested resource set and the spatial sensitivity of the requested resource set, combined with the access status of each project" can be achieved through the following steps: Step 601: Determine the average historical access tendency of the target user's department to the requested resource set based on the historical access tendency of the target user's department to each natural resource in the requested resource set.

[0096] The average historical access tendency is used to characterize the department's overall familiarity with the requested resource.

[0097] For example, this application can obtain the average historical access tendency by dividing the sum of the historical access tendency of each natural resource in the requested resource set by the number of natural resources in the requested resource set.

[0098] Step 602: When the access status of each project is stable, the spatial sensitivity is suppressed based on the average historical access tendency to obtain the risk index of the current access behavior.

[0099] When all items are in a stable state, it indicates that the target user's department has a stable access history to these items, and the current access behavior falls within the scope of routine business. In this case, the higher the average historical access tendency, the lower the risk. Spatial sensitivity should be suppressed to reduce the risk index.

[0100] For example, the risk index of the current access behavior satisfies the following formula: ; in, This represents the risk index of the current access behavior. To request the spatial sensitivity of the resource set, To represent the average historical visit tendency, This is a normalization activation function used to normalize the calculation results to a range between 0 and 1.

[0101] Step 603: When at least one item in the item set has a risk status, the spatial sensitivity is augmented based on the average historical access tendency to obtain the risk index of the current access behavior.

[0102] When a project is considered risky, it indicates that the target user's department has unstable access patterns for at least some projects, and their current access behavior may be abnormal. In this case, if the target user's department has a high average historical access tendency for the requested resources, it suggests that the department has a strong familiarity with the relevant resources and a deep understanding of the business. While high familiarity is a positive factor in routine business, in the context of abnormal behavior patterns, higher familiarity means that the user is more capable of reconstructing highly sensitive overall information from discrete, spatially correlated resource data through combined analysis, thus exacerbating the severity of the potential leakage consequences represented by spatial sensitivity. Therefore, this application should adopt a gain processing approach in risky situations. When the average historical access tendency is high, spatial sensitivity should be increased to keep the final calculated risk index at a high level, thereby triggering stricter access control measures.

[0103] For example, the risk index of the current access behavior satisfies the following formula: ; in, This represents the risk index of the current access behavior. To request the spatial sensitivity of the resource set, To represent the average historical visit tendency, This is a normalization activation function used to normalize the calculation results to a range between 0 and 1.

[0104] Based on the above technical solution, this application achieves dynamic calculation of the risk index by determining the average historical access tendency and selecting suppression processing or gain processing according to the access status. By distinguishing between stable scenarios and risk scenarios and adopting differentiated calculation logic, it not only ensures the access efficiency of regular business but also strengthens the risk prevention and control of abnormal access.

[0105] As a possible embodiment of this application, prior to step 601 above, the method further includes the following steps: Step 701: For projects in the project set whose access status is stable, filter each natural resource according to the historical access tendency of the target user's department to each natural resource in the requested resource set to obtain the first resource subset and the second resource subset.

[0106] Among them, the historical access tendency of natural resources in the first resource subset is less than the first tendency threshold, the historical access tendency of natural resources in the second resource subset is greater than the second tendency threshold, and the first tendency is less than the second tendency threshold.

[0107] It should be noted that not all resources in projects with a stable access status belong to the department's regular business resources; some may contain resources with historically low access intensity. While these low-intensity resources represent a minority of overall project access behavior, their inclusion in this request may imply a change in current access behavior. Therefore, these low-intensity resources need to be corrected to more accurately assess the risk.

[0108] Natural resources in the first resource subset mentioned above have a historical access tendency lower than the first tendency threshold; these natural resources can also be called low-tendency resources. Natural resources in the second resource subset have a historical access tendency higher than the second tendency threshold; these natural resources can also be called high-tendency resources.

[0109] For example, the first and second preference thresholds can be determined based on experimental data. For instance, the first preference threshold can be set to 0.5, and the second preference threshold can be set to 0.6. That is to say, low preference resources refer to natural resources with a historical access preference of less than 0.5, and high preference resources refer to natural resources with a historical access preference of greater than 0.6.

[0110] Step 702: For each natural resource in the first resource subset, modify the natural resource according to the historical access tendency of the natural resources in the second resource subset.

[0111] It should be noted that if the requested resource set belongs to the first... If the second resource subset of a stable project is empty (i.e., there are no high-inclination resources in the project's requested resources with a historical access inclination greater than the second inclination threshold), it indicates that the department lacks a stable high-frequency reference benchmark for the current project's access behavior. In this case, there is no need to correct the low-inclination resources in the first resource subset, and their original historical access inclination can be directly used for subsequent calculations.

[0112] If the second resource subset is not empty, the historical access tendency of the natural resources in the first resource subset is adjusted upwards based on the historical access tendency of the natural resources in the second resource subset. Since resources within the same project usually have strong business relevance, if a department has already accessed a large number of high-tendency resources in the project, then the department should have a high level of awareness and access rights to the project as a whole. In this case, even if there are a few low-tendency resources, it may be normal business expansion behavior, and the risk should not be overestimated.

[0113] Therefore, this application can adjust the historical access tendency of natural resources in the first resource subset upward based on the historical access tendency of natural resources in the second resource subset.

[0114] For example, the revised historical access preference satisfies the following formula: ; in, For the department to which the target user belongs, the requested resource set belongs to the first... The project in a stable state. The revised historical access tendency of each natural resource (the first one) (The natural resources are the natural resources in the first resource subset). For the requested resource set belonging to the first The quantity of natural resources in the second resource subset of a project in a stable state. For the requested resource set belonging to the first The quantity of natural resources of a project in a stable state. For the department to which the target user belongs, the requested resource set belongs to the first... The mean of historical access propensity for natural resources in the second resource subset of a project in a stable state. For the department to which the target user belongs, the requested resource set belongs to the first... The project in a stable state. The historical visitation tendency of a natural resource before revision.

[0115] The above formula determines the weights by comparing the quantity of natural resources in the second resource subset with the quantity of natural resources in the project under the stable state. Then, it performs a weighted calculation by comparing the mean of the historical access tendency of natural resources in the second resource subset with the historical access tendency of natural resources in the first resource subset before correction. This allows for the correction of the historical access tendency of natural resources in the first resource subset, and enables a more reasonable assessment of the actual risk level of low-protagonism resources under the stable state.

[0116] Based on the above technical solution, this application achieves refined processing of historical access tendency analysis by screening and distinguishing resources in stable state projects and correcting the historical access tendency of low-frequency resources. By correcting outliers, the representativeness of the average historical access tendency is improved, thereby improving the accuracy of risk index calculation.

[0117] Please see Figure 2 The diagram illustrates a system architecture of an access control system for an integrated natural resource platform according to an embodiment of the present invention. The access control system 20 of the integrated natural resource platform includes: The data acquisition unit 21 is used to respond to the resource access request message of the target user, acquire the set of requested resources requested by the resource access request message, and extract the historical access behavior data of the target user's department to each natural resource in the set of requested resources. Risk assessment unit 22 is used to analyze historical access tendencies based on historical access behavior data, and to conduct sensitivity assessment by combining the spatial correlation characteristics of the requested resource set, so as to determine the risk index of the current access behavior. Access control unit 23 is used to control access to target users based on risk index.

[0118] It should be noted that the various embodiments of this application can be referenced or learned from each other. For example, the same or similar steps, method embodiments, system embodiments and device embodiments can be referenced from each other without limitation.

[0119] It should be noted that the order of the above embodiments of the present invention is merely for descriptive purposes and does not represent the superiority or inferiority of the embodiments. The processes depicted in the accompanying drawings do not necessarily require a specific or sequential order to achieve the desired result. In some embodiments, multitasking and parallel processing are also possible or may be advantageous.

[0120] The various embodiments in this specification are described in a progressive manner. The same or similar parts between the various embodiments can be referred to each other. Each embodiment focuses on describing the differences from other embodiments.

Claims

1. An access control method for an integrated natural resources platform, characterized in that, include: In response to a resource access request message from a target user, the system obtains the set of requested resources requested in the resource access request message and extracts historical access behavior data of the target user's department to each natural resource in the requested resource set. Based on the historical access behavior data, a historical access tendency analysis is performed, and a sensitivity assessment is conducted in conjunction with the spatial correlation characteristics of the requested resource set to determine the risk index of the current access behavior; Access control is applied to the target user based on the risk index.

2. The access control method for the integrated natural resources platform according to claim 1, characterized in that, Based on the historical access behavior data, a historical access tendency analysis is performed, and a sensitivity assessment is conducted in conjunction with the spatial correlation characteristics of the requested resource set to determine the risk index of the current access behavior, including: Based on the historical access behavior data, a historical access tendency analysis is performed to determine the historical access tendency of the target user's department to each natural resource in the requested resource set; the historical access tendency is used to characterize the degree of access preference of the target user's department to the natural resources. Determine the set of projects involved in the requested resource set; Based on the spatial boundary information of the natural resources of each project in the project set, the spatial correlation features of the requested resource set are extracted to evaluate the spatial sensitivity of the requested resource set; the spatial sensitivity is used to characterize the degree of risk of spatial leakage of natural resources in the requested resource set. The risk index of the current access behavior is determined based on the historical access tendency of the target user's department to the natural resources of each project in the project set of the requested resource set, as well as the spatial sensitivity of the requested resource set.

3. The access control method for the integrated natural resources platform according to claim 2, characterized in that, Based on the historical access behavior data, a historical access tendency analysis is performed to determine the historical access tendency of the target user's department towards each natural resource in the requested resource set, including: Based on the historical access behavior data, determine the historical average number of visits per person and the historical average access duration per person for each natural resource in the requested resource set by the department to which the target user belongs; The historical access tendency of the target user's department to each natural resource in the requested resource set is determined based on the historical average number of visits per person and the historical average visit duration per person to each natural resource in the requested resource set.

4. The access control method for the integrated natural resources platform according to claim 2, characterized in that, Based on the spatial boundary information of the natural resources of each project in the project set, spatial correlation features are extracted from the requested resource set, and the spatial sensitivity of the requested resource set is evaluated, including: For each project in the project set, based on the spatial boundary information of the natural resources belonging to the project in the requested resource set, the spatial clustering degree, spatial connectivity degree, and project coverage completeness of the project are determined; the spatial clustering degree is used to characterize the degree of spatial distribution clustering of the natural resources belonging to the project in the requested resource set; the spatial connectivity degree is used to characterize the degree of spatial connectivity of the natural resources belonging to the project in the requested resource set; and the project coverage completeness degree is used to characterize the degree of coverage of the natural resources belonging to the project in the requested resource set over the overall scope of the project. The spatial sensitivity of the requested resource set is determined based on the spatial clustering, spatial connectivity, and project coverage completeness of each project.

5. The access control method for the integrated natural resources platform according to claim 4, characterized in that, For each project in the project set, based on the spatial boundary information of the natural resources belonging to the project in the requested resource set, the spatial clustering degree, spatial connectivity degree, and project coverage completeness corresponding to the project are determined, including: For each project in the project set, based on the spatial boundary information of the natural resources belonging to the project in the request resource set, determine the sub-regions corresponding to each natural resource belonging to the project in the request resource set; The spatial clustering degree of the project is determined based on the area of ​​the sub-region corresponding to each natural resource and the area of ​​the smallest outlying region where the sub-region corresponding to each natural resource is located. Connectivity identification is performed on the sub-regions corresponding to each natural resource to obtain one or more connected sub-regions from the sub-regions corresponding to each natural resource. The spatial connectivity of the project is determined based on the area of ​​the one or more connected sub-regions and the area of ​​the sub-regions corresponding to each natural resource. The project coverage completeness is determined based on the area of ​​the one or more connected sub-regions and the area of ​​the sub-regions corresponding to all natural resources in the project.

6. The access control method for the integrated natural resources platform according to claim 4, characterized in that, The spatial sensitivity of the requested resource set is determined based on the spatial clustering, spatial connectivity, and project coverage completeness of each project, including: For each project in the project set, the project sensitivity is determined based on the spatial clustering degree, spatial connectivity degree, and project coverage completeness of the project. The spatial sensitivity of the requested resource set is determined based on the project sensitivity of each project.

7. The access control method for the integrated natural resources platform according to claim 2, characterized in that, The risk index of the current access behavior is determined based on the historical access tendency of the target user's department to the natural resources of each project in the project set of the requested resource set, and the spatial sensitivity of the requested resource set, including: For each project in the project set, a distribution characteristic analysis is performed on the historical access tendency of all natural resources in the project to determine the access status of the target user's department to the project; the access status includes a stable status and a risk status. The risk index of the current access behavior is determined based on the historical access tendency of the target user's department to each natural resource in the requested resource set, the spatial sensitivity of the requested resource set, and the access status of each project.

8. The access control method for the integrated natural resources platform according to claim 7, characterized in that, Based on the target user's department's historical access tendency to each natural resource in the requested resource set and the spatial sensitivity of the requested resource set, and combined with the access status of each project, a risk index for the current access behavior is determined, including: The average historical access tendency of the target user's department to the requested resource set is determined based on the historical access tendency of the target user's department to each natural resource in the requested resource set. When the access status of each item is stable, the spatial sensitivity is suppressed based on the average historical access tendency to obtain the risk index of the current access behavior. When at least one item in the set of items is in a risky access state, the spatial sensitivity is augmented based on the average historical access tendency to obtain the risk index of the current access behavior.

9. The access control method for the integrated natural resources platform according to claim 8, characterized in that, Before determining the average historical access tendency of the target user's department to the requested resource set based on the historical access tendency of the target user's department to each natural resource in the requested resource set, the method further includes: For projects in the project set whose access status is stable, each natural resource is filtered according to the historical access tendency of the target user's department to each natural resource in the requested resource set, resulting in a first resource subset and a second resource subset; the historical access tendency of natural resources in the first resource subset is less than a first tendency threshold, and the historical access tendency of natural resources in the second resource subset is greater than a second tendency threshold; the first tendency is less than the second tendency threshold. For each natural resource in the first resource subset, the natural resource is modified based on the historical access tendency of the natural resources in the second resource subset.

10. An access control system for an integrated natural resource platform, characterized in that, include: The data acquisition unit is used to respond to the resource access request message of the target user, acquire the set of requested resources to be requested by the resource access request message, and extract the historical access behavior data of the target user's department to each natural resource in the set of requested resources. The risk assessment unit is used to perform historical access tendency analysis based on the historical access behavior data, and to perform sensitivity assessment in combination with the spatial correlation characteristics of the requested resource set to determine the risk index of the current access behavior. An access control unit is used to control access to the target user based on the risk index.

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