Biological resource sharing authority management system based on risk level

Abstract

The invention discloses a biological resource sharing authority management system based on risk levels, relates to the technical field of biological resource management, and aims to solve the technical problems of high-risk abuse and low-risk sharing efficiency caused by lack of dynamic risk levels and scenarized authority management and control in existing biological resource management. The construction module is used for constructing a biological resource grading evaluation index system; the weight determination module is used for determining the weight of each evaluation index; the grading judgment module is used for generating a biological resource risk grade based on the index data, the index weight and a preset grading threshold value; the authority management module is used for matching a corresponding sharing authority rule and a preservation management strategy according to the risk level; and the data storage module is used for storing the index data, the weight information, the grading result, the authority rule and the resource data. The method has the advantages of high-risk strict control and low-risk efficient circulation.

Description

Technical Field

[0001] This invention relates to the field of biological resource management technology, and more specifically, to a risk-level-based biological resource sharing access management system. Background Technology

[0002] Currently, in the context of managing physical resources for biosecurity at national borders, the customs system needs to centrally collect and standardize the preservation of various physical resources, including samples of quarantine pests, specimens of endangered species, and general biological research specimens. This data must be shared across departments (customs directly under its jurisdiction, the General Administration of Customs, research institutions, disease control centers, etc.) for application in key tasks such as disease prevention and control technology development, quarantine standard setting, and ecological risk monitoring. These biological resources have unique characteristics: improper sharing of high-risk resources (such as samples of quarantine pests and specimens of endangered species) may lead to significant safety hazards such as ecological invasion and disease transmission, while the efficient circulation of low-risk resources (such as routine biological specimens) directly affects the efficiency of scientific research.

[0003] Currently, most management methods in the industry are based on static classification standards (simply dividing species according to whether they are listed in a fixed authoritative directory), lacking a systematic consideration of the dynamic changes in the risks of biological resource dissemination and ecological impacts. Furthermore, access control rules are relatively simplistic, failing to differentiate configurations for internal sharing, cross-institutional sharing, and public sharing scenarios. This leads to key technical problems: the existing management of national border biological resources lacks a precise grading system based on dynamic risk factors and an access control mechanism adapted to different risk levels and sharing scenarios. This results in the risk of misuse of high-risk biological resources, while the cumbersome management processes for low-risk resources affect sharing efficiency. Therefore, we propose a risk-level-based biological resource sharing access control system. Summary of the Invention

[0004] The purpose of this invention is to provide a risk-level-based biological resource sharing permission management system to solve the technical problems of existing biological resource management lacking dynamic risk classification and scenario-based permission control, resulting in high-risk abuse and low-risk inefficient sharing.

[0005] To solve the above-mentioned technical problems, the present invention provides the following technical solution: a risk-level-based biological resource sharing access management system, comprising: The indicator configuration module is used to construct a graded evaluation indicator system for biological resources; The weight determination module is used to determine the weight of each evaluation indicator; The classification and determination module generates the risk level of biological resources based on indicator data, indicator weights, and preset classification thresholds. The access control module matches corresponding sharing permission rules and data preservation management strategies based on risk levels. The data storage module is used to store indicator data, weight information, classification results, permission rules, and resource data.

[0006] Preferably, the indicator configuration module includes a basic indicator unit, a characteristic indicator unit, and a dynamic risk indicator unit; The basic indicator unit is configured with species attribute indicators and specimen attribute indicators. The species attribute indicators include indicators for determining whether a species is a quarantine pest, an invasive species, or an endangered species, and are associated with corresponding authoritative lists as the basis for judgment. The specimen attribute indicators include indicators for determining whether it is a type specimen, its physical condition, and the number of specimens. The characteristic index unit is configured with specific characteristic indices corresponding to different biological types; The dynamic risk indicator unit is configured with the transmission risk coefficient of biological resources and the dynamic assessment index of ecological impact, and is associated with real-time ecological environment monitoring data and transmission path tracking data as the basis for judgment. The transmission risk coefficient is calculated using the following formula: ; in, To mitigate the risk of transmission, The preset weighting coefficients corresponding to the number of propagation paths. These are the preset weighting coefficients corresponding to the quantified values ​​of real-time ecological environment monitoring data. The number of identified transmission routes for biological resources. This refers to the quantified value of real-time ecological environment monitoring data.

[0007] Preferably, the weight determination module includes a hierarchical analysis unit and an indicator correlation verification unit; The hierarchical analysis unit divides the evaluation index system into target layer, criterion layer and index layer, constructs a hierarchical structure model, and calculates the logical weight of each index through pairwise comparison judgment matrix. The indicator correlation verification unit calculates the correlation coefficient between each indicator, identifies redundant or conflicting indicators, automatically removes redundant indicators and adjusts the hierarchical affiliation of conflicting indicators, and then triggers the hierarchical analysis unit to recalculate the logical weights and directly outputs the adjusted logical weights as the final indicator weights. The correlation coefficient between indicators is calculated using the following formula: ; in, For the first The first indicator and the first The correlation coefficient of each indicator For the number of biological resource samples, For the first Quantitative data for each indicator For the first Quantitative data for each indicator; Preset correlation threshold: A critical value used to determine whether an indicator is redundant. When the threshold is reached, it indicates that the two indicators have a high degree of overlap and are therefore considered redundant indicators.

[0008] Preferably, the grading determination module includes a data acquisition unit, an automatic scoring unit, a grade matching unit, and a cross-validation unit; The data acquisition unit extracts or receives manually entered biological resource indicator data from the data storage module, and simultaneously collects historical grading data of the same type of resources from an authoritative database. The automatic scoring unit quantifies and scores each indicator data according to preset evaluation standards, and calculates the total score by combining the indicator weights. The level matching unit compares the total score with a preset level threshold to generate a preliminary risk level. The cross-validation unit cross-compares the preliminary risk level with historical classification data from an authoritative database and the current classification results of similar resources, calculates the deviation value, and if the deviation value exceeds the preset threshold, it automatically corrects the scoring standard and recalculates the total score until the deviation value meets the requirements and then outputs the final risk level. The total score and deviation score are calculated using the following formula: Total score calculation formula: ; Deviation value calculation formula: ; in, This is the preliminary total score. The final logical weights after adjustment. Quantify the scoring results for each indicator. For the total number of indicators, This is the deviation value. This is a reference total score corresponding to historical grading data from an authoritative database.

[0009] Preferably, the data storage module includes a categorized storage unit, a backup unit, an intelligent backup unit, and a traceability and association unit; The classification storage unit classifies and stores data according to biological resource risk level, indicator type, and permission type, and sets structured fields corresponding to evaluation indicators and traceability information; The backup unit matches a basic backup strategy according to the risk level; The intelligent backup unit monitors the access frequency and modification frequency of resources in real time, dynamically adjusts the backup cycle, and optimizes the distribution of backup nodes to avoid storage pressure caused by centralized backup of multiple resources. The traceability association unit stores traceability data of biological resources from collection, identification, preservation to sharing and use, and is linked with the permission management module. Only authorized users can query the traceability information of the corresponding resources, and the integrity of the traceability information serves as a necessary auxiliary basis for permission approval.

[0010] Preferably, the permission management module includes a rule configuration unit, an approval unit, a shared control unit, a shared scenario unit, and a compliance review unit; The rule configuration unit presets basic shared permission rules corresponding to different risk levels; The shared scenario unit is divided into three core scenarios: internal sharing, cross-organizational sharing, and public sharing, and different permission thresholds are configured for each scenario; The compliance review unit automatically verifies the recipient's biosafety qualifications, confidentiality qualifications, and compliance of intended use for cross-institutional, publicly shared medium- to high-risk resources, and generates a compliance review report. The approval unit configures approval processes for different risk levels and combinations of shared scenarios; The shared control unit precisely manages the access scope, access permissions, and data export permissions of biological resources based on the approval results, compliance review reports, and filing information, and records the sharing operation log in real time.

[0011] Preferably, the indicator configuration module further includes a directory update unit and a directory conflict reconciliation unit; The directory update unit is used to synchronize the content changes of the authoritative directory in real time. When species information is added, deleted or modified in the directory, the judgment criteria for species attribute indicators are automatically updated. The conflict resolution unit is used to automatically extract the publishing agency level, update time, and sufficiency of the judgment basis of each directory when multiple related authoritative directories have inconsistent judgments on the attributes of the same species. The final judgment basis is determined according to the rule of "priority of publishing agency level, proximity of update time, and weighting of sufficiency of evidence", and the conflict resolution process is recorded to ensure the timeliness, accuracy and traceability of species attribute judgment.

[0012] Preferably, it also includes a data verification and anomaly warning module, which includes a data verification unit and an abnormal behavior monitoring unit; The data verification unit is used to verify the integrity and compliance of the indicator data. By comparing it with authoritative directory data and preset indicator ranges, it identifies invalid data and erroneous data and issues prompts. The abnormal behavior monitoring unit monitors the data entry behavior and resource access behavior in real time. When abnormal behavior is detected, it immediately issues an early warning notification and simultaneously links with the shared control unit to restrict operation permissions and records the abnormal behavior log for traceability and verification.

[0013] Preferably, it also includes a dynamic adjustment module, which includes a risk monitoring unit and a risk superposition assessment unit; The risk monitoring unit monitors real-time changes in indicator data, authoritative directories, shared scenario requirements, and compliance policies. When the risk superposition assessment unit detects that multiple risk-related factors change simultaneously, it marks the risk superposition state, first triggering the weight determination module to recalculate the indicator weights, triggering the classification judgment module to regenerate the risk level, and linking the permission management module and data storage module to synchronously update the shared permission rules, approval process and backup strategy, thereby shortening the dynamic adjustment response time. The risk accumulation value is calculated using the following formula: ; in, This is a risk accumulation value. This is a preset adjustment coefficient corresponding to the product of the correlation coefficient and the transmission risk coefficient. This is a preset adjustment coefficient corresponding to the quantitative value of changes in compliance policies. The correlation coefficient is the index. To mitigate the risk of transmission, This is a quantitative value representing changes in compliance policies. Preset overlay threshold: A critical value used to determine whether a risk overlay state exists. When this threshold is reached, it is marked as a state of overlapping risks.

[0014] A risk-level-based method for managing access to biological resources sharing includes the following steps: S1. Configure a graded evaluation index system for biological resources. The index system includes species attribute indicators, specimen attribute indicators, specific characteristic indicators for different biological types, and dynamic risk indicators, and is associated with authoritative lists and real-time ecological environment monitoring data as the basis for judgment. S2. Use the analytic hierarchy process (AHP) to determine the weights of each evaluation indicator, construct a hierarchical structure model of target layer, criterion layer, and indicator layer. First, verify the correlation between indicators and eliminate redundancies and adjust conflicting indicators. Then, calculate the logical weights of each indicator through pairwise comparison judgment matrices and output them as the final indicator weights. S3. Collect or input various indicator data and full-chain traceability data of biological resources, verify the integrity and compliance of the data, and simultaneously collect historical graded data of similar resources from authoritative databases and store them in the data storage module. S4. Quantify and score the indicator data according to the preset evaluation criteria, calculate the total score by combining the indicator weights, compare it with the preset grading threshold to generate a preliminary risk level, and output three final risk levels: high, medium and ordinary after correcting the deviation through cross-validation. S5. Match the corresponding sharing permission rules, approval process and preservation management strategy according to the risk level and sharing scenario. High-risk resources correspond to dual backup + dynamic adjustment of backup cycle + strict approval + restricted sharing. Medium-risk resources correspond to single backup + on-demand adjustment of backup cycle + limited approval + limited sharing. Ordinary risk resources correspond to regular storage + filing system + open sharing. Cross-institutional / public sharing of medium and high-risk resources requires additional compliance review. S6. Based on the shared permission rules, approval results, and compliance review reports, control the access, retrieval, and export operations of biological resources, monitor abnormal behavior in real time and issue early warnings, record data throughout the entire process, dynamically monitor changes in indicators, rules, and policies, and trigger synchronous updates of risk levels and permission configurations.

[0015] Compared with the prior art, the beneficial effects of the present invention are: 1. This invention constructs a multi-level hierarchical evaluation system comprising basic indicators, characteristic indicators, and dynamic risk indicators. Combined with access control rules linking risk levels and sharing scenarios, it achieves comprehensive and precise assessment and differentiated management of biological resource risks. The dynamic risk indicator unit quantifies propagation risks by integrating propagation path tracking data and real-time ecological environment monitoring data. The access control module configures differentiated access thresholds and approval processes for three core scenarios: internal, cross-institutional, and public. This approach not only blocks improper sharing channels of high-risk resources through strict measures such as general administration-level approval and dual backup storage, but also simplifies the circulation process of low-risk resources through a registration system and open sharing permissions. This fundamentally solves the problems of abuse in sharing high-risk resources and rigid management of low-risk resources, achieving a dual balance between security control and sharing efficiency.

[0016] 2. This invention also significantly improves the accuracy and reliability of risk classification by combining the indicator correlation verification function of the weight determination module with the cross-validation mechanism of the classification judgment module, further ensuring the precision of high-risk resource management. The indicator correlation verification unit automatically eliminates redundant indicators and adjusts the levels of conflicting indicators by calculating the correlation coefficients between indicators, avoiding weight allocation deviations caused by redundancy in the indicator system. After calculating the total score with weights, the classification judgment module cross-compares the historical classification data from the authoritative database with the current results of similar resources, and corrects the scoring standards through a deviation correction mechanism, effectively avoiding misjudgment problems caused by a single judgment logic, ensuring that the risk level classification is highly matched with the actual risk level of biological resources, providing solid data support for the accurate adaptation of permission rules, and avoiding management failures or over-management caused by classification deviations.

[0017] 3. This invention also achieves real-time response and full lifecycle coverage of risk management through the risk superposition assessment of the dynamic adjustment module and the intelligent adaptation function of the data storage module, further enhancing the timeliness and stability of high-risk resource management. The dynamic adjustment module monitors multiple risk-related factors such as indicator data, authoritative directories, and compliance policies in real time. When it detects a combination of changes such as species attribute upgrades and increased spread risks, tightening compliance policies, and increased demand for cross-institutional sharing, it prioritizes weight recalculation and level updates through risk superposition value calculation, and links the permission management module to synchronously adjust the approval process, sharing rules, and data storage backup strategy. The intelligent backup unit of the data storage module dynamically adjusts the backup cycle and node distribution according to the resource access frequency and modification frequency, while the traceability and association unit stores full-link traceability data and uses it as an auxiliary basis for approval. This not only solves the problem that static management cannot cope with risk fluctuations, but also realizes full-process traceability and controllability from resource collection, classification, sharing to preservation, ensuring that high-risk resources are always under precise control throughout their lifecycle, while taking into account the flexibility and data security of low-risk resource sharing. Attached Figure Description

[0018] Figure 1 This is a schematic diagram of the overall system framework of the present invention; Figure 2 This is a schematic diagram of the structural framework of the indicator configuration module of the present invention; Figure 3 This is a schematic diagram of the structural framework of the weight determination and classification judgment module of the present invention; Figure 4 This is a schematic diagram of the structural framework of the permission management module of the present invention; Figure 5 This is a schematic diagram of the structural framework of the data storage module of the present invention. Detailed Implementation

[0019] To facilitate understanding of the technical solution of the present invention by those skilled in the art, the technical solution of the present invention will now be further described in conjunction with the accompanying drawings.

[0020] Example 1, such as Figures 1-5 As shown, this invention provides a risk-level-based biological resource sharing access management system, comprising: The indicator configuration module is used to construct a graded evaluation indicator system for biological resources; The weight determination module is used to determine the weight of each evaluation indicator; The classification and determination module generates the risk level of biological resources based on indicator data, indicator weights, and preset classification thresholds. The access control module matches corresponding sharing permission rules and data preservation management strategies based on risk levels. The data storage module is used to store indicator data, weight information, grading results, permission rules and resource-related data, so as to realize the full-process automated control of biological resources from grading evaluation to sharing permissions and preservation management, and adapt to the needs of differentiated resource management.

[0021] In an embodiment of the present invention, the indicator configuration module includes a basic indicator unit, a characteristic indicator unit, and a dynamic risk indicator unit; The basic indicator unit is configured with species attribute indicators and specimen attribute indicators. The species attribute indicators include indicators for determining whether a species is a quarantine pest, an invasive species, or an endangered species, and are associated with corresponding authoritative lists as the basis for judgment. Implementation of basic indicator units: Species attribute indicators: Associate authoritative lists such as "List of Quarantine Pests of Plants Entering China", "List of Invasive Alien Species in China", and "List of National Key Protected Wild Animals / Plants" to determine whether a species is a quarantine pest, invasive species, or endangered species by matching the lists. Quantitative rule: Inclusion in any one of the high-risk lists (quarantine pests / invasive species / endangered species): quantification value of 90 points; Being listed in two or more high-risk categories: a quantitative value of 100 points; Not listed in any high-risk list: Quantitative value: 20 points; Example: If an insect sample is matched with the list and confirmed to be included in the "List of Quarantine Pests of Plants Entering the People's Republic of China", then the quantitative value of the species attribute index is 90 points.

[0022] The specimen attribute indicators include indicators for determining whether it is a type specimen, its physical condition, and the number of specimens. Specimen attribute index: Criteria for determining whether it is a type specimen: The determination is made by consulting original species naming literature (such as new species naming papers published in journals like *Acta Phytotaxonomica Sinica* and *Acta Zoologica Sinica*), naming information certified by the International Code of Nomenclature for Plants (ICN) / International Code of Nomenclature for Zoology (ICZN), and publicly available catalogues of type specimens in the collections of authoritative herbaria (such as the Herbarium of the Institute of Botany, Chinese Academy of Sciences, and the Herbarium of the National Zoological Museum of China). (Some herbaria publish type specimen numbers and related information on their official websites.) If it can be verified as a type specimen through the above-mentioned public channels, the quantitative value is 80 points; otherwise, it is 30 points. The "physical condition" quantification rules are as follows: scores are given in four levels: "intact (100 points), slightly damaged (70 points), severely damaged (30 points), and deteriorated (0 points)". The "sample quantity" quantification rules are as follows: quantification is carried out in three levels: "≤5 samples (90 points), 6-20 samples (60 points), >20 samples (30 points)", with the lower the quantity, the higher the risk weight. The characteristic index unit is configured with specific characteristic indicators corresponding to different biological types (plants, animals, microorganisms); Implementation of characteristic indicator units: Differentiated configuration based on biological type, with quantitative standards referencing the "General Rules for Risk Assessment of Biological Resources" (industry standard): Plants: Reproduction coefficient (average annual reproduction number): ≤10 plants = 80 points, 11-50 plants = 50 points, >50 plants = 20 points; Dispersion distance (maximum range of single spread): >10km = 90 points, 3-10km = 60 points, <3km = 30 points; Animals: Migration radius: >500km=90 points, 100-500km=60 points, <100km=30 points; Pathogenicity rate (probability of causing disease to the host): >50%=100 points, 20%-50%=70 points, <20%=30 points; Microbial: Culture difficulty (required experimental condition level): P3 laboratory and above = 90 points, P2 laboratory = 60 points, P1 laboratory = 30 points; Toxicity level (GB15193.1-2014 "National Food Safety Standard Food Safety Toxicology Evaluation Procedures"): High toxicity = 100 points, moderate toxicity = 70 points, low toxicity = 40 points, non-toxicity = 20 points; The dynamic risk indicator unit is configured with the transmission risk coefficient of biological resources and the dynamic assessment indicator of ecological impact, and is associated with real-time ecological environment monitoring data and transmission path tracking data as the basis for judgment; each indicator meets the configuration requirements of being quantifiable, easy to obtain and dynamically updated. The transmission risk coefficient is calculated using the following formula: ; in, The risk coefficient is a core quantitative indicator for measuring the level of risk of biological resource transmission, and its value directly corresponds to the basis for determining the risk level. Preset weighting coefficients corresponding to the number of transmission paths are used to adjust the importance of transmission path factors in risk assessment; Preset weighting coefficients corresponding to the quantified values ​​of real-time ecological environment monitoring data are used to adjust the importance of ecological environment factors in risk assessment, and This ensures the rationality and uniformity of the weight allocation for the two core factors; The number of identified propagation pathways of biological resources is an objective statistical data point that directly reflects the scale of possible dispersal channels of biological resources. To quantify real-time ecological environment monitoring data, non-standardized ecological monitoring data such as temperature, humidity, and vegetation coverage are converted into standardized values ​​of 0-100 through preset standards, thereby achieving unified measurement of different types of ecological data. This algorithm employs a weighted summation logic, integrating the characteristics of biological resource propagation pathways with real-time ecological and environmental impacts to quantify the propagation risk coefficient. First, it assigns specific weight coefficients to the number of propagation pathways and the quantified values ​​of real-time ecological and environmental monitoring data. Then, it multiplies the two data points by their corresponding weight coefficients and sums the results to obtain a comprehensive quantitative result reflecting the degree of biological resource propagation risk, thus achieving the quantitative calculation of dynamic risk indicators. This algorithm breaks through the limitation of static indicators in capturing changes in biological resource risks by weightedly integrating two dynamic factors: the propagation path and the ecological environment. This makes the propagation risk assessment more in line with the dynamic changes in the actual scenario, effectively improving the timeliness and accuracy of risk indicators, and providing scientific and reliable dynamic data support for subsequent risk level determination.

[0023] Implementation of transmission risk coefficient calculation: Preset weighting coefficients , ( (This can be adjusted based on the ecological sensitivity of the region). For example, the transmission route of a certain quarantine insect has been identified. Quantitative values ​​of real-time ecological environment monitoring data (air, insect vectors, cargo transport). (If the temperature and humidity are suitable for its survival and reproduction), then the risk of transmission is high. .

[0024] Dynamic assessment indicators for ecological impact: Based on the "Methods for Ecological Risk Assessment of Biological Invasions" (LY / T2893-2017), quantification rules: Severe impact (leading to the extinction of native species / destruction of ecosystems): 100 points; Moderate impact (reduction of native species by more than 30%): 70 points; Slight impact (10%-30% reduction in native species): 40 points; No impact (no change in local species): 20 points.

[0025] In an embodiment of the present invention, the weight determination module includes a hierarchical analysis unit and an index correlation verification unit; The hierarchical analysis unit divides the evaluation index system into target layer, criterion layer and index layer, constructs a hierarchical structure model, and calculates the logical weight of each index through pairwise comparison judgment matrix. Hierarchical structure model construction: The target layer is "determination of the risk level of biological resources", the criterion layer is "basic indicators, characteristic indicators, and dynamic risk indicators" (the initial weight allocation is 0.3, 0.2, and 0.5), and the indicator layer is the specific indicators under each criterion layer (such as species attributes and specimen attribute indicators under basic indicators). Pairwise comparison judgment matrix construction and logical weight calculation: Scale rules (using the internationally accepted 1-9 scale):

[0026] Example of constructing a pairwise comparison judgment matrix:

[0027] Logical weight calculation: Calculate the product of elements in each centered row. : Basic indicators: Characteristic indicators: Dynamic risk indicators: ; calculate The nth root (n = number of criteria layer indicators = 3): Basic indicators: Characteristic indicators: Dynamic risk indicators: ; Normalization (weights) (Root value / Sum of all root values) Total = 1 + 0.4055 + 2.4662 ≈ 3.8717; Basic indicator weights: Characteristic index weights: Dynamic risk indicator weights: ; Consistency check: Calculate the largest eigenvalue : ; To determine the matrix, This is the weight vector; Calculate the consistency index ; Find the average random consistency index ( hour, ); Consistency ratio ,like If the matrix passes the consistency check, the weights are valid; otherwise, the judgment matrix needs to be adjusted. Example: Calculated , , The weights are effective; The indicator correlation verification unit calculates the correlation coefficient between each indicator, identifies redundant or conflicting indicators, automatically removes redundant indicators and adjusts the hierarchical affiliation of conflicting indicators, and then triggers the hierarchical analysis unit to recalculate the logical weights, directly outputting the adjusted logical weights as the final indicator weights. This avoids weight allocation deviations caused by redundancy or conflict in the indicator system, ensuring the logic and scientific nature of weight allocation without relying on external subjective evaluation input. The correlation coefficient between indicators is calculated using the following formula: ; in, For the first The first indicator and the first The correlation coefficient of the two indicators ranges from [-1, 1]. The closer the absolute value is to 1, the stronger the correlation between the two indicators. The closer the absolute value is to 0, the weaker the correlation. To ensure sufficient data for biological resource sample quantity and correlation analysis of indicators, and to guarantee the reliability of calculation results; For the first The quantitative data of each indicator is the standardized value of any one indicator in the indicator system; For the first The quantitative data of one indicator is the standardized value of another arbitrary indicator in the indicator system; Preset correlation threshold: A critical value used to determine whether an indicator is redundant. When the threshold is reached, it indicates that the two indicators have a high degree of overlap and are judged as redundant indicators. Correlation coefficient calculation: Calculated according to the Pearson correlation coefficient formula, with a preset correlation threshold of 0.8 (determined based on the "Statistical Data Analysis Specifications" and adjustable through system parameters, ranging from 0.7 to 0.9). Redundant indicator identification and removal: If Indicators deemed redundant are removed due to their "low information contribution" (information contribution = indicator variation coefficient × weight, variation coefficient = standard deviation / mean; indicators with low contribution are removed first). Conflict indicator adjustment: If the correlation coefficient between indicators is... (Preset conflict threshold) If it is determined to be a conflict indicator, its hierarchical classification will be adjusted (e.g., "microbial virulence level" will be adjusted from a characteristic indicator to a dynamic risk indicator). Weight recalculation steps: After removing redundant indicators and adjusting conflicting indicators, the hierarchical structure model is reconstructed (e.g., after removing species attribute indicators, only specimen attributes are retained as basic indicators); Recalculate according to the above process of "constructing pairwise comparison judgment matrix → weight calculation → consistency check"; The recalculated weights are output as the final indicator weights, requiring no manual intervention. Example: Species attribute indicators and transmission risk coefficient indicators The information contribution was calculated as follows: species attribute (coefficient of variation = 0.6, weight = 0.2583, contribution = 0.155), and transmission risk coefficient (coefficient of variation = 0.8, weight = 0.6370, contribution = 0.5096). Species attribute indicators were removed. The criteria layer was reconstructed as "basic indicators (specimen attributes), characteristic indicators, and dynamic risk indicators". The judgment matrix was reconstructed and the weights were calculated. Finally, the weights of the basic indicators were 0.2, the weights of the characteristic indicators were 0.1, and the weights of the dynamic risk indicators were 0.7. This algorithm, based on the Pearson correlation coefficient calculation principle, quantifies the degree of linear correlation between any two indicators by analyzing indicator data of biological resource samples. It first calculates the covariance of the two indicator data, then divides it by the product of the standard deviations of the two indicators to obtain the correlation coefficient. By comparing the absolute value of the correlation coefficient with a preset association threshold, it accurately identifies redundant or conflicting indicators in the indicator system, providing data support for indicator system optimization and ensuring the rationality of weight allocation. This algorithm quantifies the correlation between indicators, enabling the automatic removal of redundant indicators and the hierarchical adjustment of conflicting indicators. It effectively solves the problem of weight allocation deviation caused by redundancy or conflict in the indicator system, making the constructed indicator system more scientific and concise. It provides an optimized indicator basis for subsequent weight calculation and further improves the logic and reliability of weight allocation.

[0028] In an embodiment of the present invention, the grading determination module includes a data acquisition unit, an automatic scoring unit, a grade matching unit, and a cross-validation unit; The data acquisition unit extracts or receives manually entered biological resource indicator data from the data storage module, and simultaneously collects historical grading data of the same type of resources from an authoritative database. The automatic scoring unit quantifies and scores each indicator data according to preset evaluation standards, and calculates the total score by combining the indicator weights. The level matching unit compares the total score with the preset level threshold to generate a preliminary risk level (high, medium, or normal). The cross-validation unit cross-compares the preliminary risk level with historical classification data from an authoritative database and the current classification results of similar resources, calculates the deviation value, and if the deviation value exceeds the preset threshold, it automatically corrects the scoring standard and recalculates the total score until the deviation value meets the requirements and then outputs the final risk level. The total score and deviation score are calculated using the following formula: Total score calculation formula: ; Deviation value calculation formula: ; Automatic scoring and total score calculation, example:

[0029] Total score ; Preliminary risk level matching: Preset grading thresholds (determined based on the "Regulations on the Management of Biological Resources Safety"), High risk: Medium risk: Common risks: Example: The initial risk level is "medium risk".

[0030] Cross-validation and scoring criterion revision: Deviation calculation: This is a reference total score corresponding to historical grading data from authoritative databases (e.g., the average total score of risky resources of the same type in the National Biological Resource Bank = 52). Preset deviation threshold: 5 points (determined based on the allowable range of statistical error, can be adjusted to 3-7 points); Scoring Criteria Revision Rules: like Calculate the correction factor ; Adjust the scoring weights of indicators according to the priority of "Dynamic Risk Indicators → Characteristic Indicators → Basic Indicators" (priority is based on the indicator weight ranking, the higher the weight, the higher the priority). Adjustment range = Difference between correction factor and 1 × 0.5 (e.g., ...) (Difference = 0.051, Adjustment range = 0.0255). Recalculate the total score until... ; Example: If , , Correction factor The adjustment range is 0.0889. The weight of the dynamic risk indicator was increased by 0.0889 from 0.7 (to 0.7889), and the weight of the basic indicator was decreased by 0.0889 from 0.2 (to 0.1111); the total score was recalculated. , Further adjustments were made: the weight of the dynamic risk indicator was increased by 0.05 (to 0.8389), and the weight of the basic indicator was decreased by 0.05 (to 0.0611); recalculation was performed. , (The scoring range, not the weighting, needs to be adjusted here to correct the quantification of the transmission risk coefficient: Original) , revised to (Maximum 100), then Recalculate , (Revision complete) Final risk level output: After cross-validation, three levels are output: high, medium, and normal. In this example, the final level is "medium risk".

[0031] in, The preliminary total score is a comprehensive quantitative representation of the quantitative scoring results of various indicators of biological resources combined with weights, and is directly used to determine the preliminary risk level. The final logical weights after adjustment are the specific weights for each indicator after the correlation verification, ensuring the scientific nature of the weights; The quantitative scoring results for each indicator are numerical values ​​obtained by quantifying the indicator data according to preset evaluation standards; The total number of indicators is denoted by , which represents the total number of optimized indicators in the indicator system. The deviation value is the absolute difference between the preliminary total score and the reference total score, used to measure the degree of deviation between the preliminary judgment result and the authoritative standard. The reference total score is the historical graded data from an authoritative database, while the standard score is determined based on authoritative historical data, ensuring the reliability of cross-validation. The algorithm consists of two steps: the first step uses a weighted summation logic to multiply the quantitative scores of each indicator by their corresponding weights and then sum them up to obtain a preliminary total score reflecting the comprehensive risk level of biological resources; the second step uses an absolute deviation calculation logic to quantify the degree of deviation between the preliminary risk level and the authoritative reference total score by calculating the absolute difference between the preliminary total score and the authoritative reference total score, thus providing a quantitative basis for the correction of the risk level. This progressive algorithm first integrates the information of each indicator through weighted summation, and then cross-validates the preliminary results through absolute deviation calculation. It effectively solves the problem that a single judgment logic is prone to misjudgment of risk levels, so that the risk level judgment can not only comprehensively consider the importance of each indicator, but also rely on authoritative data to correct deviations, which significantly improves the accuracy and credibility of risk level judgment.

[0032] In an embodiment of the present invention, the data storage module includes a classification storage unit, a backup unit, an intelligent backup unit, and a traceability and association unit; The classification storage unit classifies and stores data according to biological resource risk level, indicator type, and permission type, and sets structured fields corresponding to evaluation indicators and traceability information; The categorized storage units are stored in a three-level directory structure: "Risk Level (High / Medium / Ordinary) - Indicator Type (Basic / Characteristic / Dynamic) - Permission Type (Internal / Cross-Institutional / Public)". The structured fields include "Species Name, Risk Level, Indicator Quantification Value, Weight, Approval Record, and Traceability ID". For example, the "High Risk - Dynamic Risk Indicator - Cross-Institutional Sharing" directory stores the transmission risk coefficient and ecological impact assessment data of a quarantine pest. The backup unit matches a basic backup strategy based on the risk level (high-risk dual backup, medium-risk single backup, and normal-risk conventional storage). The intelligent backup unit monitors the access frequency and modification frequency of resources in real time, dynamically adjusts the backup cycle (shortening the backup cycle for high-frequency access resources and extending the backup cycle for low-frequency access resources), and optimizes the distribution of backup nodes to avoid storage pressure caused by centralized backup of multiple resources. The traceability association unit stores the entire traceability data of biological resources from collection, identification, preservation to sharing and use (collection location, handler, transfer record, purpose of use, identification conclusion, preservation condition record), and is linked with the permission management module. Only authorized users can query the traceability information of the corresponding resources, and the completeness of the traceability information serves as a necessary auxiliary basis for permission approval.

[0033] In an embodiment of the present invention, the permission management module includes a rule configuration unit, an approval unit, a shared control unit, a shared scenario unit, and a compliance review unit; The rule configuration unit presets basic sharing permission rules corresponding to different risk levels (high risk restricted sharing, medium risk limited sharing, and normal risk open sharing); Basic access rules: High-risk resources can only be shared by the General Administration of Customs and its directly affiliated research departments; medium-risk resources can be shared by users within the customs system and by cooperating research institutions; ordinary-risk resources can be shared by all authorized users (such as university research teams and disease control centers). The shared scenario unit is divided into three core scenarios: internal sharing, cross-institutional sharing, and public sharing. Different permission thresholds are configured for each scenario (cross-institutional sharing of high-risk resources requires additional compliance qualification requirements, while public sharing only opens the basic information of ordinary risk resources). Differentiated access thresholds: Internal sharing (within the customs system) has no additional qualification requirements; cross-institutional sharing of high-risk resources requires the receiving party to have a biosafety level 2 or higher laboratory qualification; public sharing only allows access to species names and specimen images of ordinary risk resources, and does not allow access to core data such as collection sites and identification methods; The compliance review unit automatically verifies the recipient's biosafety qualifications, confidentiality qualifications, and compliance of intended use for cross-institutional, publicly shared medium- to high-risk resources, and generates a compliance review report. Review process: When sharing high-risk resources across institutions, the system automatically verifies the recipient's "Biosafety Laboratory Filing Certificate" and "Confidentiality Qualification Certificate," analyzes the intended use description using natural language processing technology (e.g., "for disease prevention and control vaccine research and development" is compliant, "for commercial profit" is non-compliant), and generates a compliance review report. The approval unit configures approval processes for different risk levels and sharing scenarios (high-risk cross-institutional sharing requires approval at the General Administration level + compliance review, and internal medium-risk sharing requires approval at the direct liaison level). Ordinary risk resources are configured with filing processes or simplified approval processes according to the scenario. Approval process configuration: High-risk cross-institutional sharing requires "initial review by the directly affiliated department → secondary review by the biosafety department of the General Administration of Customs → final review by the relevant leader of the General Administration of Customs"; internal medium-risk sharing requires "initial review by the department head → final review by the research department of the directly affiliated department"; ordinary risk public sharing only requires "registration" and no approval is required. The shared control unit precisely manages the access scope, access permissions, and data export permissions of biological resources based on the approval results, compliance review reports, and filing information, and records the sharing operation log in real time.

[0034] Access Control: After approval, high-risk resources are only allowed to be viewed by the recipient, and downloading or copying is prohibited; medium-risk resources allow data download, but secondary dissemination is prohibited; ordinary risk resources allow free download and use. Real-time recording of sharing operation logs includes "operation user ID, operation time, operation type (view / download), and approval number"; In an embodiment of the present invention, the indicator configuration module further includes a directory update unit and a directory conflict reconciliation unit; The directory update unit is used to synchronize the content changes of the authoritative directory in real time. When species information is added, deleted or modified in the directory, the judgment criteria for species attribute indicators are automatically updated. Implementation of Directory Update and Conflict Resolution Unit: List Update Unit: This unit connects to the official data interface of authoritative list publishing agencies and is set to automatically synchronize and update daily at 2:00 AM. If changes to the list are detected (such as the addition of a quarantine pest), the system automatically updates the criteria for judging species attribute indicators, marks the update time (accurate to the minute) and the updated content, and generates a list update log. Example: On May 10, 2024, a new beetle was added to the "List of Invasive Alien Species in China," and the system automatically included this species in the high-risk judgment criteria for species attribute indicators. The conflict resolution unit is used to automatically extract the publishing agency level, update time, and sufficiency of the judgment basis of each directory when multiple related authoritative directories have inconsistent judgments on the attributes of the same species. The final judgment basis is determined according to the rule of "priority of publishing agency level, proximity of update time, and weighting of sufficiency of evidence", and the conflict resolution process is recorded to ensure the timeliness, accuracy and traceability of species attribute judgment.

[0035] Directory Conflict Resolution Unit: Conflict determination: When two or more authoritative lists disagree on the same species attribute (e.g., List A lists it as a quarantine pest, while List B does not), reconciliation is triggered. Harmony rules:

[0036] Harmonized calculation: Overall score = Publishing organization level score × 0.3 + Update time score × 0.4 + Evidence sufficiency score × 0.3, and the list with the highest overall score is taken as the final basis; Example: List A (released by the General Administration of Customs in March 2024, with 3 experimental data points) vs. List B (released by the Provincial Forestry and Grassland Bureau in November 2023, with no experimental data). The score for A is 1.0 × 0.3 + 1.0 × 0.4 + 1.0 × 0.3 = 1.0, and the score for B is 0.7 × 0.3 + 0.7 × 0.4 + 0.4 × 0.3 = 0.21 + 0.28 + 0.12 = 0.61. The final score will be based on List A.

[0037] In embodiments of the present invention, a data verification and anomaly warning module is also included, which includes a data verification unit and an abnormal behavior monitoring unit. The data verification unit is used to verify the integrity and compliance of the indicator data. By comparing it with authoritative directory data and preset indicator ranges, it identifies invalid data and erroneous data and issues prompts. The abnormal behavior monitoring unit monitors data entry behavior (frequent modification of key indicators, excessive deviation between entered data and authoritative data) and resource access behavior (high-frequency access to high-risk resources during unauthorized periods, excessive resource usage, and attempts to export restricted data) in real time. When abnormal behavior is detected, an early warning notification is immediately issued, and the shared control unit is linked to restrict operation permissions and record abnormal behavior logs for traceability and verification.

[0038] In embodiments of the present invention, a dynamic adjustment module is further included, which includes a risk monitoring unit and a risk superposition assessment unit; The risk monitoring unit monitors real-time changes in indicator data, authoritative directories, shared scenario requirements, and compliance policies. Monitoring frequency: Real-time monitoring of indicator data and shared scenario requirements; daily monitoring of authoritative directories and compliance policies (synchronized with the directory update unit). Monitored changes are recorded in the "Risk Factor Change Log," including the type, content, and time of the change. When the risk superposition assessment unit detects that multiple risk-related factors (the combination of species attribute upgrading and increased spread risk, and the combination of tightened compliance policies and increased cross-institutional sharing needs) change simultaneously, it marks the risk superposition state, prioritizes triggering the weight determination module to recalculate the indicator weights, triggers the classification judgment module to regenerate the risk level, and links the permission management module and data storage module to synchronously update the sharing permission rules, approval process and backup strategy, shortening the dynamic adjustment response time. The risk accumulation value is calculated using the following formula: ; in, The risk superposition value is a comprehensive quantitative indicator under the combined effect of multiple risk-related factors, used to determine whether the priority adjustment mechanism is triggered. This is a preset adjustment coefficient corresponding to the product of the correlation coefficient and the transmission risk coefficient. This is used to adjust the degree of influence of the combined factors in the risk superposition assessment; This is a preset adjustment coefficient corresponding to the quantitative value of changes in compliance policies. This is used to adjust the degree of influence of policy change factors in risk overlay assessment; The correlation coefficient reflects the correlation characteristics between indicators and provides a reference for the structure of the indicator system for risk overlay assessment. The transmission risk coefficient reflects the dynamic transmission risk level of biological resources; To quantify changes in compliance policies, a value of 0.5-1.0 is used when policies tighten and -0.5-0.0 is used when policies loosen, thus achieving a quantitative expression of policy changes; Preset overlay threshold: A critical value used to determine whether a risk overlay state exists. When this threshold is reached, it is marked as a state of overlapping risks.

[0039] This algorithm employs a multi-factor weighted fusion logic, integrating and calculating three major risk-related factors: indicator correlation, propagation risk coefficient, and changes in compliance policies. First, the indicator correlation coefficient and the propagation risk coefficient are multiplied. Then, these are summed with the quantitative value of changes in compliance policies, each with its own adjustment coefficient, to obtain a risk superposition value that comprehensively reflects the combined effect of multiple factors. By comparing this value with a preset superposition threshold, the algorithm accurately identifies the risk superposition state, providing a quantitative basis for triggering the dynamic adjustment mechanism. This algorithm integrates multiple dimensions such as indicator correlation, dynamic propagation of risks, and policy changes to achieve accurate identification and quantitative assessment of risk superposition states. It effectively solves the problems of the lag in adjustment triggered by a single factor and the inadequacy in responding to risks superimposed by multiple factors. It can prioritize responses to high-risk superposition scenarios, shorten the response time of dynamic adjustments, and ensure that risk levels and permission configurations can adapt to risk fluctuations caused by changes in multiple factors in a timely manner, further improving the system's dynamic adaptability and the effectiveness of risk prevention and control.

[0040] Example 2, as follows Figures 1 to 4 As shown, this invention provides a risk-level-based method for managing access permissions for sharing biological resources, comprising the following steps: S1. Configure a graded evaluation index system for biological resources. The index system includes species attribute indicators, specimen attribute indicators, specific characteristic indicators for different biological types, and dynamic risk indicators, and is associated with authoritative lists and real-time ecological environment monitoring data as the basis for judgment. S2. Use the analytic hierarchy process (AHP) to determine the weights of each evaluation indicator, construct a hierarchical structure model of target layer, criterion layer, and indicator layer. First, verify the correlation between indicators and eliminate redundancies and adjust conflicting indicators. Then, calculate the logical weights of each indicator through pairwise comparison judgment matrices and output them as the final indicator weights. S3. Collect or input various indicator data and full-chain traceability data of biological resources, verify the integrity and compliance of the data, and simultaneously collect historical graded data of similar resources from authoritative databases and store them in the data storage module. S4. Quantify and score the indicator data according to the preset evaluation criteria, calculate the total score by combining the indicator weights, compare it with the preset grading threshold to generate a preliminary risk level, and output three final risk levels: high, medium and ordinary after correcting the deviation through cross-validation. S5. Match the corresponding sharing permission rules, approval process and preservation management strategy according to the risk level and sharing scenario. High-risk resources correspond to dual backup + dynamic adjustment of backup cycle + strict approval + restricted sharing. Medium-risk resources correspond to single backup + on-demand adjustment of backup cycle + limited approval + limited sharing. Ordinary risk resources correspond to regular storage + filing system + open sharing. Cross-institutional / public sharing of medium and high-risk resources requires additional compliance review. S6. Based on the shared permission rules, approval results, and compliance review reports, control the access, retrieval, and export operations of biological resources, monitor abnormal behavior in real time and issue early warnings, record data throughout the entire process, dynamically monitor changes in indicators, rules, and policies, and trigger synchronous updates of risk levels and permission configurations.

[0041] The embodiments disclosed in this invention are preferred embodiments, but are not limited thereto. Those skilled in the art can easily understand the spirit of this invention based on the above embodiments and make different extensions and variations, but as long as they do not depart from the spirit of this invention, they are all within the protection scope of this invention.

Claims

1. A risk-level-based access control system for sharing biological resources, characterized in that, include: The indicator configuration module is used to construct a graded evaluation indicator system for biological resources; The weight determination module is used to determine the weight of each evaluation indicator; The classification and determination module generates the risk level of biological resources based on indicator data, indicator weights, and preset classification thresholds. The access control module matches corresponding sharing permission rules and data preservation management strategies based on risk levels. The data storage module is used to store indicator data, weight information, classification results, permission rules, and resource data.

2. The risk-level-based biological resource sharing access management system according to claim 1, characterized in that, The indicator configuration module includes a basic indicator unit, a characteristic indicator unit, and a dynamic risk indicator unit. The basic indicator unit is configured with species attribute indicators and specimen attribute indicators. The species attribute indicators include indicators for determining whether a species is a quarantine pest, an invasive species, or an endangered species, and are associated with corresponding authoritative lists as the basis for judgment. The specimen attribute indicators include indicators for determining whether it is a type specimen, its physical condition, and the number of specimens. The characteristic index unit is configured with specific characteristic indices corresponding to different biological types; The dynamic risk indicator unit is configured with the transmission risk coefficient of biological resources and the dynamic assessment index of ecological impact, and is associated with real-time ecological environment monitoring data and transmission path tracking data as the basis for judgment. The transmission risk coefficient is calculated using the following formula: ; in, To mitigate the risk of transmission, The preset weighting coefficients corresponding to the number of propagation paths. These are the preset weighting coefficients corresponding to the quantified values ​​of real-time ecological environment monitoring data. The number of identified transmission routes for biological resources. This refers to the quantified value of real-time ecological environment monitoring data.

3. The risk-level-based biological resource sharing access management system according to claim 1, characterized in that, The weight determination module includes a hierarchical analysis unit and an indicator correlation verification unit; The hierarchical analysis unit divides the evaluation index system into target layer, criterion layer and index layer, constructs a hierarchical structure model, and calculates the logical weight of each index through pairwise comparison judgment matrix. The indicator correlation verification unit calculates the correlation coefficient between each indicator, identifies redundant or conflicting indicators, automatically removes redundant indicators and adjusts the hierarchical affiliation of conflicting indicators, and then triggers the hierarchical analysis unit to recalculate the logical weights and directly outputs the adjusted logical weights as the final indicator weights. The correlation coefficient between indicators is calculated using the following formula: ； in, For the first The first indicator and the first The correlation coefficient of each indicator For the number of biological resource samples, For the first Quantitative data for each indicator For the first Quantitative data for each indicator; Preset correlation threshold: A critical value used to determine whether an indicator is redundant. When the threshold is reached, it indicates that the two indicators have a high degree of overlap and are therefore considered redundant indicators.

4. A risk-level-based biological resource sharing access management system according to claim 3, characterized in that, The grading determination module includes a data acquisition unit, an automatic scoring unit, a grading matching unit, and a cross-validation unit. The data acquisition unit extracts or receives manually entered biological resource indicator data from the data storage module, and simultaneously collects historical grading data of the same type of resources from an authoritative database. The automatic scoring unit quantifies and scores each indicator data according to preset evaluation standards, and calculates the total score by combining the indicator weights. The level matching unit compares the total score with a preset level threshold to generate a preliminary risk level. The cross-validation unit cross-compares the preliminary risk level with historical classification data from an authoritative database and the current classification results of similar resources, calculates the deviation value, and if the deviation value exceeds the preset threshold, it automatically corrects the scoring standard and recalculates the total score until the deviation value meets the requirements and then outputs the final risk level. The total score and deviation score are calculated using the following formula: Total score calculation formula: ; Deviation value calculation formula: ; in, This is the preliminary total score. The final logical weights after adjustment. Quantify the scoring results for each indicator. For the total number of indicators, This is the deviation value. This is a reference total score corresponding to historical grading data from an authoritative database.

5. A risk-level-based biological resource sharing access management system according to claim 1, characterized in that, The data storage module includes a categorized storage unit, a backup unit, an intelligent backup unit, and a traceability and association unit; The classification storage unit classifies and stores data according to biological resource risk level, indicator type, and permission type, and sets structured fields corresponding to evaluation indicators and traceability information; The backup unit matches a basic backup strategy according to the risk level; The intelligent backup unit monitors the access frequency and modification frequency of resources in real time, dynamically adjusts the backup cycle, and optimizes the distribution of backup nodes to avoid storage pressure caused by centralized backup of multiple resources. The traceability association unit stores traceability data of biological resources from collection, identification, preservation to sharing and use, and is linked with the permission management module. Only authorized users can query the traceability information of the corresponding resources, and the integrity of the traceability information serves as a necessary auxiliary basis for permission approval.

6. A risk-level-based biological resource sharing access management system according to claim 1, characterized in that, The permission management module includes a rule configuration unit, an approval unit, a shared control unit, a shared scenario unit, and a compliance review unit; The rule configuration unit presets basic shared permission rules corresponding to different risk levels; The shared scenario unit is divided into three core scenarios: internal sharing, cross-organizational sharing, and public sharing, and different permission thresholds are configured for each scenario; The compliance review unit automatically verifies the recipient's biosafety qualifications, confidentiality qualifications, and compliance of intended use for cross-institutional, publicly shared medium- to high-risk resources, and generates a compliance review report. The approval unit configures approval processes for different risk levels and combinations of shared scenarios; The shared control unit precisely manages the access scope, access permissions, and data export permissions of biological resources based on the approval results, compliance review reports, and filing information, and records the sharing operation log in real time.

7. A risk-level-based biological resource sharing access management system according to claim 2, characterized in that, The indicator configuration module also includes a directory update unit and a directory conflict reconciliation unit; The directory update unit is used to synchronize the content changes of the authoritative directory in real time. When species information is added, deleted or modified in the directory, the judgment criteria for species attribute indicators are automatically updated. The conflict resolution unit is used to automatically extract the publishing agency level, update time, and sufficiency of the judgment basis of each directory when multiple related authoritative directories have inconsistent judgments on the attributes of the same species. The final judgment basis is determined according to the rule of "priority of publishing agency level, proximity of update time, and weighting of sufficiency of evidence", and the conflict resolution process is recorded to ensure the timeliness, accuracy and traceability of species attribute judgment.

8. A risk-level-based biological resource sharing access management system according to claim 6, characterized in that, It also includes a data verification and anomaly warning module, which includes a data verification unit and an abnormal behavior monitoring unit; The data verification unit is used to verify the integrity and compliance of the indicator data. By comparing it with authoritative directory data and preset indicator ranges, it identifies invalid data and erroneous data and issues prompts. The abnormal behavior monitoring unit monitors the data entry behavior and resource access behavior in real time. When abnormal behavior is detected, it immediately issues an early warning notification and simultaneously links with the shared control unit to restrict operation permissions and records the abnormal behavior log for traceability and verification.

9. A risk-level-based biological resource sharing access management system according to claim 1, characterized in that, It also includes a dynamic adjustment module, which includes a risk monitoring unit and a risk superposition assessment unit; The risk monitoring unit monitors real-time changes in indicator data, authoritative directories, shared scenario requirements, and compliance policies. When the risk superposition assessment unit detects that multiple risk-related factors change simultaneously, it marks the risk superposition state, first triggering the weight determination module to recalculate the indicator weights, triggering the classification judgment module to regenerate the risk level, and linking the permission management module and data storage module to synchronously update the shared permission rules, approval process and backup strategy, thereby shortening the dynamic adjustment response time. The risk accumulation value is calculated using the following formula: ； in, This is a risk accumulation value. This is a preset adjustment coefficient corresponding to the product of the correlation coefficient and the transmission risk coefficient. This is a preset adjustment coefficient corresponding to the quantitative value of changes in compliance policies. The correlation coefficient is the index. To mitigate the risk of transmission, This is a quantitative value representing changes in compliance policies. Preset overlay threshold: A critical value used to determine whether a risk overlay state exists. When this threshold is reached, it is marked as a state of overlapping risks.

10. A method applied to a risk-level-based biological resource sharing access management system as described in any one of claims 1-9, characterized in that, Includes the following steps: S1. Configure a graded evaluation index system for biological resources. The index system includes species attribute indicators, specimen attribute indicators, specific characteristic indicators for different biological types, and dynamic risk indicators, and is associated with authoritative lists and real-time ecological environment monitoring data as the basis for judgment. S2. Use the analytic hierarchy process (AHP) to determine the weights of each evaluation indicator, construct a hierarchical structure model of target layer, criterion layer, and indicator layer. First, verify the correlation between indicators and eliminate redundancies and adjust conflicting indicators. Then, calculate the logical weights of each indicator through pairwise comparison judgment matrices and output them as the final indicator weights. S3. Collect or input various indicator data and full-chain traceability data of biological resources, verify the integrity and compliance of the data, and simultaneously collect historical graded data of similar resources from authoritative databases and store them in the data storage module. S4. Quantify and score the indicator data according to the preset evaluation criteria, calculate the total score by combining the indicator weights, compare it with the preset grading threshold to generate a preliminary risk level, and output three final risk levels: high, medium and ordinary after correcting the deviation through cross-validation. S5. Match the corresponding sharing permission rules, approval process and preservation management strategy according to the risk level and sharing scenario. High-risk resources correspond to dual backup + dynamic adjustment of backup cycle + strict approval + restricted sharing. Medium-risk resources correspond to single backup + on-demand adjustment of backup cycle + limited approval + limited sharing. Ordinary risk resources correspond to regular storage + filing system + open sharing. Cross-institutional / public sharing of medium and high-risk resources requires additional compliance review. S6. Based on the shared permission rules, approval results, and compliance review reports, control the access, retrieval, and export operations of biological resources, monitor abnormal behavior in real time and issue early warnings, record data throughout the entire process, dynamically monitor changes in indicators, rules, and policies, and trigger synchronous updates of risk levels and permission configurations.

Images