Biosafety physical resource multi-dimensional data management system

Abstract

The invention discloses a biosafety physical resource multi-dimensional data management system, relates to the technical field of biosafety physical resource management, and aims to solve the technical problem of linkage of data synchronization fault-authorization verification failure-traceability risk conduction in an existing management system. Storing a resource identifier, an operation log and real-time state data, configuring a chain weight migration mechanism triggered by a security level, and synchronously constructing an inter-chain data consistency verification mechanism to avoid data tampering or loss in a chain weight migration process; the multi-modal authorization module is used for constructing a multi-dimensional biological key system, verifying a cross-mechanism retrieval request through an intelligent contract, triggering security control and early warning if verification fails, and supporting on-chain emergency reset and temporary authority hosting when a key is abnormal; and the on-chain and off-chain traceability module is used for associating the on-chain evidence and the off-chain data. The method has the advantage of providing reliable data and authority basis for emergency scheduling.

Description

Technical Field

[0001] This invention relates to the field of biosafety physical resource management technology, and more specifically, to a multi-dimensional data management system for biosafety physical resources. Background Technology

[0002] In scenarios where provincial and municipal CDCs collaborate with third-party testing laboratories to handle cross-regional public health emergencies (such as pneumonia of unknown origin or outbreaks of emerging infectious diseases), the cross-institutional transfer and management of biosafety resources (including virus isolates, positive pharyngeal swab samples, and inactivated samples for testing) is a core aspect of emergency response. These resources must meet high safety and traceability requirements. Their transfer process must record in real-time the resource's unique identifier, operator qualifications, storage environment parameters (temperature, humidity), and cross-node transfer trajectory. Furthermore, it must rapidly respond to cross-institutional access requests and emergency dispatch needs to support critical tasks such as viral gene sequencing, strain comparison, and vaccine development. Currently, most biosafety resource management systems in the industry adopt the traditional architecture of "single-chain storage + static authorization," which is difficult to adapt to the needs of cross-institutional and highly dynamic emergency scenarios and has significant technical bottlenecks: When resources flow from municipal laboratories (operation nodes) to provincial disease control centers (regional domain chains) and national regulatory platforms (core chains), there is a lack of hierarchical data synchronization and verification mechanisms. Hash value deviations often occur due to asynchronous data updates between node chains and domain chains, resulting in "data synchronization gaps." At the same time, the authorization mechanism relies solely on a single password or fixed qualification certificate and cannot combine historical violation records of operators and physical characteristics of resource carriers to achieve dynamic verification. Verification is prone to "authorization failure" (e.g., operators with expired qualifications can still access high-level samples); in addition, the lack of correlation and verification between on-chain operation logs and off-chain sensor data makes it impossible to trace upstream and downstream flow nodes once a suspicious operation occurs, leading to "risk transmission out of control". The above-mentioned chain problem of "data synchronization failure - authorization verification failure - source traceability risk transmission" directly causes resource positioning delays during emergency dispatch, operational risks cannot be blocked, delays the cross-institutional allocation and testing progress of core epidemic samples, and may even cause biosafety accidents due to data tampering or loss. In view of this, we propose a multi-dimensional data management system for biosafety physical resources. Summary of the Invention

[0003] The purpose of this invention is to provide a multi-dimensional data management system for biosafety physical resources, so as to solve the chain of technical problems in existing management systems, such as data synchronization gaps, authorization verification failures, and the transmission of traceability risks.

[0004] To address the aforementioned technical problems, this invention provides the following technical solution: a multi-dimensional data management system for biosafety physical resources, comprising: The blockchain architecture module adopts a three-level dynamic chain architecture to store resource identifiers, operation logs and real-time status data. It is configured with a chain ownership migration mechanism triggered by security level and simultaneously builds an inter-chain data consistency verification mechanism to prevent data tampering or loss during the chain ownership migration process. The multimodal authorization module constructs a multi-dimensional biometric key system, verifies cross-institutional access requests through smart contracts, and triggers security control and early warning if verification fails. It also supports on-chain emergency reset and temporary permission management in case of key abnormalities. The on-chain and off-chain traceability module links on-chain evidence storage with off-chain data, generates a full lifecycle traceability report and marks suspicious operations, and can trace all resource flow paths associated with suspicious operations to block the transmission of risks; The emergency dispatch module builds a cross-agency emergency resource database in the core chain. In the event of a public health emergency, it automatically filters nodes, generates dispatch instructions and pushes task notifications, and configures a resource conflict coordination mechanism.

[0005] Preferably, the three-level dynamic chain architecture of the blockchain architecture module is "core chain - domain chain - node chain"; The core chain stores the unique identifier of resources and key node information for cross-domain transfer. The regulatory body acts as a super node, which is responsible for the final review of core chain data and the issuance of synchronization instructions. The domain chain is divided according to administrative regions or institutional types. An improved practical Byzantine fault-tolerant algorithm is configured to realize data synchronization within the domain. During the synchronization process, data must be confirmed by a majority of nodes within the domain before being written to the domain chain, and resource operation logs within the corresponding range are stored. The node chain is deployed on each resource storage or operation node to store real-time status data of resources. When the node chain data is updated, the operator's identity information and operation timestamp must be recorded first. The chain rights migration mechanism is as follows: when the resource security level changes, the node chain data is automatically synchronized to the domain chain, and the domain chain core information is synchronized to the core chain. Before synchronization, the original node chain operation permissions are frozen. After synchronization is completed, a chain rights migration certificate is generated and written to the entire chain. The certificate contains chain layer information before and after migration and data verification results. The inter-chain data consistency verification mechanism is as follows: During the chain rights migration process, the core chain, domain chain, and node chain generate independent hash values ​​for the synchronized data, and confirm the data consistency by cross-comparing them pairwise. If there is a difference, the data rollback operation is triggered immediately, and an alarm message containing the location of the difference data and the comparison result is pushed to the regulatory node. To quantify the degree of data consistency differences, an inter-chain data consistency deviation value is introduced for calculation. The specific formula is as follows: ; in, This represents the inter-chain data consistency deviation value. The hash value generated by the core chain for synchronizing data. The hash value generated by the domain chain for synchronizing data. The hash value generated by the node chain for synchronizing data. This is an absolute value symbol used to eliminate the positive and negative effects of hash value differences, retaining only the magnitude of the difference.

[0006] Preferably, the multi-dimensional biometric key system of the multimodal authorization module includes: The inherent key is generated based on the resource's own characteristics using a symmetric encryption algorithm. The inherent key is bound to the resource's unique identifier and cannot be tampered with. The dynamic key generated by fusing the operator's iris or fingerprint features with the qualification certificate number requires desensitization of biometric features and qualification information during the fusion process. The binding key is generated based on the physical markings on the surface of the resource storage carrier or the unique code of the RFID chip. The binding key corresponds one-to-one with the carrier and is updated with the carrier status. The dynamic key is automatically updated at a preset period. The update frequency is adjusted based on the risk assessment results of the operator's historical operation behavior. The assessment takes into account the number of compliant operations and abnormal operation records. The emergency reset of the key abnormality is as follows: when it is detected that the key has been tampered with or the operator is unable to provide the key due to special reasons, the supervisory node initiates an on-chain vote. The voting nodes are preset authoritative nodes within the domain. After the vote passes, a temporary key is generated and entrusted to a designated backup person. At the same time, all operation permissions associated with the original key are frozen. The reason for the operation must be recorded when the temporary key is used. The verification process is as follows: simultaneously verify the validity of the inherent key, dynamic key, and bound key, and verify whether the biosafety protection level qualification of the accessing institution matches the resource security level; if any verification step fails, the on-chain data will be frozen immediately, the storage medium will be physically locked, and a warning message containing the verification failure step and the reason for the failure will be pushed to the regulatory node. To accurately calculate the risk assessment results of operators' historical operational behaviors and thus determine the dynamic key update frequency, an operational risk value calculation method is introduced, using the following formula: ; in, For operator risk values, This refers to the number of times an operator has complied with regulations in their historical operations. This records the number of times an operator has made a historical error. This represents the total number of operations performed by the operator in history.

[0007] Preferably, the association process of the on-chain and off-chain traceability modules is as follows: The sensor and communication modules integrated into the resource storage carrier collect environmental data and resource status data in real time. After collection, the data integrity is first verified. After the verification is passed, a status hash value is generated and uploaded to the node chain at a preset interval. The operation process information is recorded by a dedicated terminal with a biometric module. Before recording, the operator must be identified. After successful verification, the operation information is stored on the blockchain. After processing, the key information is synchronized to the domain chain. The risk transmission blocking is as follows: after marking a suspicious operation, all upstream transfer nodes and downstream receiving nodes of the resources involved in the operation are automatically traced, and prompt information containing details of the suspicious operation and risk level is pushed to each relevant node. Further access and detection operations of the associated resources are restricted until the risk investigation is completed and an investigation report is generated. When generating a report, the operation logs and status data of the node chain corresponding to the resource unique identifier of the core chain are compared one by one with the timestamps of the on-chain operation records and the collection timestamps of the off-chain sensor data. If there is a time deviation that exceeds the reasonable range, it is marked as a suspicious operation and the duration of the deviation is recorded. To quantify whether time deviation exceeds a reasonable range, a time deviation risk coefficient is introduced, with the specific formula as follows: ; in, For time deviation risk coefficient, This represents the absolute deviation between the on-chain operation record timestamp and the off-chain sensor data acquisition timestamp. For operator risk values, This is the risk adjustment coefficient.

[0008] Preferably, the cross-agency emergency resource database of the emergency dispatch module stores the resource detection capability information, protective material reserve information and personnel standby information of each node. All information must be reviewed by the node itself and verified twice by the domain chain before being uploaded. After the verification is passed, it is encrypted and written into the core chain. The resource conflict coordination mechanism is as follows: when multiple public health emergencies apply for the same node resource at the same time, a priority ranking model is constructed according to the urgency of the event, the scope of impact and the resource matching degree. When the model is calculated, the information of each dimension is first quantitatively evaluated, and then the event priority is determined comprehensively. Resources are prioritized to high priority events, while functional matching and geographically nearby alternative nodes are recommended for low priority events, and the resource availability status of alternative nodes is simultaneously informed. When selecting nodes, the geographical scope is limited by the resource traceability results. Nodes are sorted according to the principles of priority for response speed and optimal resource utilization. After sorting, scheduling instructions are generated. The instructions include the resource allocation path, the responsibility of the receiving node and the time requirements. The instructions are synchronized to the relevant node chain and the core chain. The pushed task notification includes on-chain authorization credentials. The scheduling operation can only be executed after the credentials are verified by the receiving node.

[0009] Preferably, the unique identifier of the resource stored in the core chain includes an encrypted resource ID and a hash root value generated based on the resource genome features. The hash root value generated based on the resource genome features is obtained by extracting species-unique fragments from the resource genome and encrypting them. During extraction, easily mutated fragments in the genome need to be excluded to ensure uniqueness. The core chain stores key node information for cross-domain transfer, including the validity period of node qualifications and historical compliance records. These serve as prerequisite verification conditions for chain rights migration. During verification, the node qualifications are first checked to see if they are valid, and then it is confirmed that there are no major violations in the historical compliance records. Chain rights migration can only be initiated after both conditions are met. To quantify the historical compliance level of nodes and serve as a basis for pre-verification of chain rights migration, a node compliance calculation is introduced, with the specific formula as follows: ; in, For node compliance, This represents the average value of the consistency deviation values ​​between historical chain data of the nodes. The preset maximum allowable deviation value is set when the node qualification is within its validity period and When the preset compliance threshold is reached, the chain rights migration can be initiated.

[0010] Preferably, the domain chain's resource operation log includes resource access time and operator qualification summary. The operator qualification summary includes the operator's biosafety level operation qualification certificate number and validity period information. The summary information needs to be regularly synchronized with the regulatory authority's qualification database to ensure accuracy. When receiving synchronization data from node chains, the domain chain must first verify the device status and network security of the node chains. Data can only be received after the verification is passed. If the verification fails, the failure item will be reported and the node chains will be required to rectify the issues and resynchronize.

[0011] Preferably, the symmetric encryption algorithm is the SM4 encryption algorithm, which is used to ensure the encryption security of the inherent key, and a randomly generated initial vector is used during the encryption process to improve the encryption strength; The escrow period of the temporary key can be preset. When setting the escrow period, a reasonable duration is determined based on actual business needs. After the temporary key expires, it will automatically become invalid and trigger a new key generation process. After the new key is generated, it needs to be updated to all related chain layers in a synchronized manner to avoid the risk of long-term escrow of permissions.

[0012] Preferably, the biometric module of the dedicated terminal completes identity verification by collecting the operator's iris or fingerprint information. During the collection, it is necessary to ensure the clarity and integrity of the biometric information. The operation process information can only be recorded after the verification is successful. The dedicated terminal will automatically record abnormal behavior during the operation. When recording, it is necessary to associate the operation time, operation steps and operator information, and upload them to the domain chain as the basis for judging suspicious operations. After receiving the domain chain, the abnormal behavior information needs to be classified and stored for subsequent query. To quantify the severity of operational anomalies and serve as a supplementary basis for determining suspicious operations, an operational anomaly severity calculation is introduced, with the specific formula as follows: ; in, For the severity of operational abnormalities, For time deviation risk coefficient, Quantification of operational process violations , The weighting coefficients for each dimension are preset based on the impact of operational anomaly risks. They represent the importance of time deviation risks and process violations in the severity assessment of anomalies, and the sum of the weighting coefficients is 1 to ensure the comprehensiveness of the assessment.

[0013] Preferably, the geographical range of the nodes defined by the emergency dispatch module is: Based on the resource collection location or circulation path in the resource traceability results, nodes within a preset distance range are selected. Nodes without corresponding resource processing capabilities within the geographical range must be excluded during the selection process. In the priority ranking model, the urgency of the event is based on the event response time limit, the scope of impact is based on the number of people who may be affected, and the resource matching degree is based on the fit between the existing resources of the node and the event requirements. The evaluation results of each dimension are combined to calculate the priority according to the preset weight.

[0014] Compared with the prior art, the beneficial effects of the present invention are: 1. This invention, through a three-level dynamic chain architecture of "core chain - domain chain - node chain" and an inter-chain data consistency verification mechanism, can synchronize resource data across levels and institutions in real time. Combined with a multi-dimensional biometric key system, it achieves dynamic authorization verification, fundamentally addressing the chain problem of "data synchronization failure - authorization verification failure - source traceability risk transmission". It ensures that data is authentic and traceable and authorization is accurate and compliant during resource transfer, providing a reliable data and permission foundation for emergency dispatch.

[0015] 2. This invention also addresses the resource contention problem when multiple public health emergencies occur concurrently through a cross-agency emergency resource database and priority ranking model. Priorities can be quantified according to the urgency of the event, the scope of impact, and resource matching, prioritizing resource allocation to scenarios with high demand. At the same time, it recommends geographically nearby alternative nodes to avoid resource idleness or mismatch, thereby improving the rationality and efficiency of emergency dispatch.

[0016] 3. This invention further addresses the residual issues of "authority escrow risk" and "missed detection of suspicious operations" through an emergency reset mechanism on the key chain and an operation anomaly severity assessment model: When key tampering is detected or the operator is unable to provide the key, a temporary escrow key can be generated through voting by authoritative nodes within the domain, and the original permissions can be frozen; When an operation anomaly occurs, the severity of the anomaly can be quantified by combining the time deviation risk coefficient and the process violation item, accurately marking suspicious behavior and blocking the risk transmission, achieving triple protection of "data security - controllable permissions - risk blocking", and strengthening the system's ability to manage high-security-level resources throughout their entire lifecycle. Attached Figure Description

[0017] Figure 1 This is a schematic diagram of the system framework of the present invention. Detailed Implementation

[0018] 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.

[0019] Example 1, such as Figure 1 As shown, this invention provides a multi-dimensional data management system for biosafety physical resources, comprising: The blockchain architecture module adopts a three-level dynamic chain architecture to store resource identifiers, operation logs and real-time status data. It is configured with a chain ownership migration mechanism triggered by security level and simultaneously builds an inter-chain data consistency verification mechanism to prevent data tampering or loss during the chain ownership migration process. The multimodal authorization module constructs a multi-dimensional biometric key system, verifies cross-institutional access requests through smart contracts, and triggers security control and early warning if verification fails. It also supports on-chain emergency reset and temporary permission management in case of key abnormalities. The on-chain and off-chain traceability module links on-chain evidence storage with off-chain data, generates a full lifecycle traceability report and marks suspicious operations, and can trace all resource flow paths associated with suspicious operations to block the transmission of risks; The emergency dispatch module builds a cross-agency emergency resource database in the core chain. In the event of a public health emergency, it automatically filters nodes, generates dispatch instructions and pushes task notifications. It also configures a resource conflict coordination mechanism to solve the problem of resource contention when multiple events occur concurrently.

[0020] In an embodiment of the present invention, the three-level dynamic chain architecture of the blockchain architecture module is "core chain - domain chain - node chain"; The core chain stores the unique identifier of resources and key node information for cross-domain transfer. The regulatory body acts as a super node, which is responsible for the final review of core chain data and the issuance of synchronization instructions. The domain chain is divided according to administrative regions or institutional types. An improved practical Byzantine fault-tolerant algorithm is configured to realize data synchronization within the domain. During the synchronization process, data must be confirmed by a majority of nodes within the domain before being written to the domain chain, and resource operation logs within the corresponding range are stored. The node chain is deployed on each resource storage or operation node to store real-time resource status data (including resource storage temperature fluctuation information and resource remaining information). When updating node chain data, the operator's identity information and operation timestamp must be recorded first. The chain rights migration mechanism is as follows: When the resource security level changes, the node chain data is automatically synchronized to the domain chain, and the domain chain core information is synchronized to the core chain. Before synchronization, the original node chain operation permissions are frozen. After synchronization is completed, a chain rights migration certificate is generated and written to the entire chain. The certificate contains chain layer information before and after migration and data verification results. The inter-chain data consistency verification mechanism is as follows: During the chain rights migration process, the core chain, domain chain, and node chain generate independent hash values ​​for the synchronized data. The data consistency is confirmed by cross-comparison between pairs. If there is a difference, the data rollback operation is triggered immediately, and an alarm message containing the location of the difference data and the comparison result is pushed to the regulatory node. To quantify the degree of data consistency differences, an inter-chain data consistency deviation value is introduced for calculation. The specific formula is as follows: ; in, This is the inter-chain data consistency deviation value, used to intuitively reflect the degree of difference in the synchronized data of the three chains, and is the criterion for triggering data rollback operations; The hash value generated by the core chain for the synchronization data is calculated by the core chain according to a preset hash algorithm and represents the characteristics of the synchronization data stored by the core chain. The hash value generated by the domain chain for the synchronization data is calculated by the domain chain using the same hash algorithm as the core chain, and represents the characteristics of the synchronization data stored in the domain chain. The hash value generated by the node chain for the synchronization data is calculated by the node chain using the same hash algorithm as the core chain and the domain chain, and represents the characteristics of the synchronization data stored in the node chain; The absolute value sign is used to eliminate the positive and negative effects of hash value differences, retaining only the magnitude of the difference and ensuring that the deviation value is a non-negative value; This formula is used to quantitatively assess the degree of consistency differences among the core chain, domain chain, and node chain in a blockchain architecture during data synchronization. By calculating the sum of the absolute differences between the hash values ​​of the synchronized data generated by each of the three chains, it determines whether the data has been tampered with or lost: if the sum of the differences is greater than 0, it means that the hash values ​​of at least two chains do not match, and there is a data difference; if the sum of the differences is equal to 0, it means that the hash values ​​of the three chains are completely consistent, and the data synchronization is error-free. This algorithm can quickly and accurately detect the consistency of data synchronization between chains, avoiding biosafety risks caused by data tampering or loss (such as detection errors caused by incorrect sample information). Compared to traditional "single-chain verification" or "pairwise comparison" methods, this formula further improves the comprehensiveness and reliability of data consistency verification by cross-comparing three chains, providing security for chain ownership transfer mechanisms and ensuring the integrity and authenticity of biosafety physical resource data during cross-chain transfer.

[0021] In embodiments of the present invention, the multi-dimensional biometric key system of the multimodal authorization module includes: The inherent key is generated based on the resource's own characteristics using a symmetric encryption algorithm. The inherent key is bound to the resource's unique identifier and cannot be tampered with. The dynamic key generated by fusing the operator's iris or fingerprint features with the qualification certificate number requires desensitization of biometric features and qualification information during the fusion process. The binding key is generated based on the physical markings on the surface of the resource storage carrier or the unique code of the RFID chip. The binding key corresponds one-to-one with the carrier and is updated with the carrier status. The dynamic key is automatically updated at a preset period. The update frequency is adjusted based on the risk assessment results of the operator's historical operation behavior. The assessment takes into account the number of compliant operations and abnormal operation records. The emergency reset for key anomalies is as follows: When it is detected that the key has been tampered with or the operator is unable to provide the key due to special reasons, the supervisory node initiates an on-chain vote. The voting nodes are the preset authoritative nodes within the domain. After the vote passes, a temporary key is generated and entrusted to a designated backup person. At the same time, all operation permissions associated with the original key are frozen. The reason for the operation must be recorded when the temporary key is used. The verification process is as follows: simultaneously verify the validity of the inherent key, dynamic key, and bound key, and verify whether the biosafety protection level qualification of the accessing institution matches the resource security level; if any verification step fails, the on-chain data will be frozen immediately, the storage medium will be physically locked, and a warning message containing the verification failure step and the reason for the failure will be pushed to the regulatory node. To accurately calculate the risk assessment results of operators' historical operational behaviors and thus determine the dynamic key update frequency, an operational risk value calculation method is introduced, using the following formula: ; in, The operator risk value is used to measure the compliance risk level of the operator's operation behavior and is the core basis for adjusting the frequency of dynamic key updates. The historical number of compliant operations by operators refers to the total number of operations performed by operators in the past that complied with biosafety operating procedures and had no deviation in inter-chain data consistency verification (D=0). The number of historical operational anomalies recorded by operators refers to the total number of times that operators have violated biosafety operating procedures or had deviations in inter-chain data consistency verification in the past. The total number of operations performed by the operator in history, which is the sum of compliant and abnormal operations, is used as the base for calculating the risk value. This formula is used to quantify the risk value of an operator's historical operational behavior, thereby determining the update frequency of the dynamic key. By calculating the number of compliant and abnormal records in an operator's historical operations, the percentage of compliant operations in the total operations is calculated. Subtracting this percentage from 1 yields the risk value: a higher percentage of compliant operations results in a lower risk value and a lower dynamic key update frequency; conversely, a lower percentage of compliant operations results in a higher risk value and a higher dynamic key update frequency. Furthermore, the calculation is based solely on operational records with unbiased inter-chain data consistency verification, ensuring the accuracy of the data foundation. This algorithm achieves a precise match between the dynamic key update frequency and the risk level of operators, avoiding a "one-size-fits-all" fixed update model: increasing the key update frequency for high-risk operators reduces the risk of key cracking or misuse; decreasing the update frequency for low-risk operators reduces unnecessary operational costs. Simultaneously, based on unbiased operation record calculations using inter-chain data consistency verification, it ensures the objectivity and accuracy of risk assessment, further strengthening the security of the multimodal authorization module and providing a scientific basis for the control of operational permissions for biosafety physical resources.

[0022] In an embodiment of the present invention, the association process between the on-chain and off-chain traceability modules is as follows: The sensor and communication module integrated into the resource storage carrier collects environmental data (including temperature, humidity and vibration data) and resource status data in real time. After collection, the data integrity is first verified. After the verification is passed, a status hash value is generated and uploaded to the node chain at a preset interval. The operation process information (including resource sampling amount and test items) is recorded through a dedicated terminal configured with a biometric module. The operator's identity must be verified before recording. After verification, the operation information is stored on the blockchain. After processing, the key information is synchronized to the domain chain. Risk transmission blocking is achieved by automatically tracing all upstream circulation nodes (including resource collection and transfer nodes) and downstream receiving nodes (including detection and storage nodes) of the resources involved in the operation after marking a suspicious operation. The system pushes a prompt message containing details of the suspicious operation and the risk level to each relevant node and restricts further access and detection operations of the associated resources until the risk investigation is completed and an investigation report is generated. When generating a report, the operation logs and status data of the node chain corresponding to the resource unique identifier of the core chain are compared one by one with the timestamps of the on-chain operation records and the collection timestamps of the off-chain sensor data. If there is a time deviation that exceeds the reasonable range, it is marked as a suspicious operation and the duration of the deviation is recorded. To quantify whether time deviation exceeds a reasonable range, a time deviation risk coefficient is introduced, with the specific formula as follows: ; in, The time deviation risk coefficient is used to comprehensively assess the risk level of timestamp deviation and is a key indicator for marking suspicious operations. It is the absolute deviation between the on-chain operation record timestamp and the off-chain sensor data acquisition timestamp, that is, the absolute value of the difference between the two timestamp values, reflecting the magnitude of the time synchronization deviation. This is the operator's operational risk value, used to reflect the operator's historical operational risk level and adjust the risk tolerance for time deviations. This is the risk adjustment coefficient, generated based on the operator's risk value. The higher the risk value, the larger the adjustment coefficient, and the stronger the amplification effect on time deviation. This formula is used to quantify whether the deviation between the timestamp of the on-chain operation record and the timestamp of the off-chain sensor data acquisition exceeds a reasonable range, thereby identifying suspicious operations. It correlates the absolute deviation value of the timestamp with the operator's risk value: the higher the operator's risk value, the lower their tolerance for time deviation, and the larger the risk coefficient calculated for the same time deviation; when the risk coefficient exceeds a preset threshold, it is judged as a suspicious operation, requiring further risk investigation. This algorithm overcomes the limitations of traditional "fixed time threshold" judgment of suspicious operations. By dynamically adjusting the judgment criteria based on operator risk, it avoids over-control of low-risk operators (e.g., misjudging a slight time deviation as a suspicious operation) while strengthening strict supervision of high-risk operators (e.g., triggering a risk warning even with a minor time deviation). Through the correlation assessment between time deviation and personnel risk, it improves the accuracy of on-chain and off-chain traceability modules in identifying suspicious operations and promptly prevents the transmission of risks that may be caused by time synchronization anomalies (e.g., traceability confusion caused by a mismatch between sample operation records and actual status).

[0023] In an embodiment of the present invention, the cross-agency emergency resource database of the emergency dispatch module stores the resource detection capability information (including the types of pathogens that can be detected and the detection and processing volume), protective material reserve information (including the quantity of protective equipment and the status of disinfection equipment) and personnel standby information (including the list of personnel with the specified biosafety level operation qualifications) of each node. All information must be reviewed by the node itself and verified twice by the domain chain before being uploaded. After the verification is passed, it is encrypted and written into the core chain. The resource conflict coordination mechanism is as follows: When multiple public health emergencies apply for the same node resource at the same time, a priority ranking model is constructed according to the urgency of the event, the scope of impact, and the resource matching degree. When the model is calculated, the information of each dimension is first quantitatively evaluated, and then the event priority is determined comprehensively. Resources are prioritized to high-priority events, while functional matching and geographically nearby alternative nodes are recommended for low-priority events, and the resource availability status of alternative nodes is simultaneously informed. When selecting nodes, the geographical range is limited by the resource traceability results. Nodes are sorted according to the principles of priority of response speed and optimal resource utilization. After sorting, scheduling instructions are generated. The instructions include the resource allocation path, the responsibility of the receiving node and the time requirements. They are synchronized to the relevant node chain and the core chain. The pushed task notification includes on-chain authorization credentials. The credential must be verified by the receiving node before the scheduling operation can be executed. To comprehensively calculate event priority, an event priority index is introduced, which combines the event's urgency, scope of impact, and resource matching degree. The specific formula is as follows: ; in, This is an event priority index used to sort the resource scheduling priority of multiple concurrent events. The higher the index, the higher the resource scheduling priority. The urgency level of an event is quantified based on the event response time requirements (such as whether emergency handling is required). The higher the urgency level, the larger the quantified value. This is a quantitative value for the scope of an event's impact, derived from the number of people and the geographical area that the event may affect. The wider the scope of impact, the larger the quantitative value. The resource matching quantification value is quantified based on the degree of fit between node resources and event requirements (such as the matching of detection equipment and protective materials). The higher the degree of fit, the larger the quantification value. The time deviation risk coefficient reflects the degree of risk caused by the time deviation of an event. The larger the risk coefficient, the larger the quantitative value. , , , The weighting coefficients for each dimension are preset according to the needs of biosafety incident management. They represent the importance of urgency, scope of impact, resource matching degree, and time deviation risk in the priority assessment, and the sum of the weighting coefficients is 1 to ensure the rationality of the assessment results. This formula is used to comprehensively calculate the priority index of public health emergencies, addressing the resource competition problem when multiple events occur concurrently. It quantifies four dimensions—urgency, scope of impact, resource matching degree, and time deviation risk coefficient—and then sums them according to preset weights to obtain the priority index: the higher the quantified value of each dimension and the greater its corresponding weight, the higher the priority index, and the higher the priority of the event in resource allocation, ensuring that high-risk, high-demand events receive priority resource support. This algorithm achieves multi-dimensional and scientific event prioritization, avoiding the subjectivity and limitations of traditional "experience-based" resource allocation. By integrating event urgency, scope of impact, resource suitability, and time risk, it ensures that resources are prioritized for the most needed events (such as highly urgent, widespread, and high-risk outbreaks), while also considering resource matching to improve resource utilization efficiency. Furthermore, the flexible setting of weighting coefficients can adapt to the management needs of different types of biosafety events, enhancing the versatility and practicality of the emergency dispatch module and providing precise decision-making basis for cross-agency resource collaborative scheduling.

[0024] In an embodiment of the present invention, the unique identifier of the resource stored in the core chain includes an encrypted resource ID and a hash root value generated based on the resource genome features. The hash root value generated based on the resource genome features is obtained by extracting species-unique fragments from the resource genome and encrypting them. During extraction, easily mutated fragments in the genome need to be excluded to ensure uniqueness. The core chain stores key node information for cross-domain transfer, including the validity period of node qualifications and historical compliance records. These serve as prerequisite verification conditions for chain rights migration. During verification, the node qualifications are first checked to see if they are valid, and then it is confirmed that there are no major violations in the historical compliance records. Chain rights migration can only be initiated after both conditions are met. To quantify the historical compliance level of nodes and serve as a basis for pre-verification of chain rights migration, a node compliance calculation is introduced, with the specific formula as follows: ; in, Node compliance is used to measure the compliance level of a node in historical data synchronization and is a core indicator for pre-verification of chain rights migration. This is the average of the historical inter-chain data consistency deviations of the node, that is, the deviation value in each of the node's past inter-chain data synchronizations. The sum divided by the number of synchronizations reflects the average deviation level of historical data synchronization of the nodes; The maximum permissible deviation value is a preset value determined according to the biosafety data management specifications. It represents the maximum acceptable deviation for node data synchronization. If this value is exceeded, the node will have serious compliance risks. When the node's qualifications are valid and When the preset compliance threshold is reached, the chain rights migration can be initiated; This formula is used to quantify the historical compliance of a node, serving as a preliminary verification basis for chain ownership migration. The compliance level is obtained by calculating the ratio of the average historical inter-chain data consistency deviation value of a node to a preset maximum allowable deviation value, and then subtracting this ratio from 1: the smaller the average historical deviation, the higher the compliance level, and the more the node meets the chain ownership migration requirements; the larger the average historical deviation, the lower the compliance level, and the more difficult it is for the node to pass the chain ownership migration verification. Furthermore, the node's qualification validity period must be considered in conjunction with the calculation to ensure a comprehensive assessment of node compliance. This algorithm sets a scientific pre-compliance threshold for blockchain rights migration, avoiding data security risks after migration due to poor historical compliance of nodes (such as frequent data deviations). By quantifying the historical compliance performance of nodes, it replaces traditional "qualitative assessments" (such as "no major violations"), improving the objectivity and accuracy of verification results. Simultaneously, combined with node qualification validity verification, it forms a dual "qualification + compliance" audit mechanism, further strengthening the security of blockchain rights migration and ensuring that when biosafety physical resources are transferred across nodes, the receiving node has a reliable compliance foundation, thus protecting data and resource security.

[0025] In an embodiment of the present invention, the domain chain's resource operation log includes resource access time and operator qualification summary. The operator qualification summary includes the operator's biosafety level operation qualification certificate number and validity period information. The summary information needs to be regularly synchronized with the qualification database of the regulatory authority to ensure accuracy. When receiving synchronization data from the node chain, the domain chain must first verify the device status (including whether the sensors are normal and whether the storage devices are stable) and network security (including whether there is abnormal access and whether the data transmission is encrypted). Data can only be received after the verification is passed. If the verification fails, the failure item will be reported and the node chain will be required to rectify and resynchronize. To comprehensively evaluate the eligibility of nodes for data synchronization access, a node synchronization access index is introduced, taking into account device status and network security. The specific formula is as follows: ; in, The node synchronization admission index is used to determine whether a node chain is qualified to synchronize data to the domain chain. Only when the index reaches a preset threshold can it be admitted. Node compliance reflects the node's historical compliance level and is a fundamental indicator for access assessment. The device status quantification value is derived from the operating status of the node chain storage device and sensing device (such as whether it is working normally or whether there is a fault). The quantification value is high when the device is operating normally and low when it is faulty. This is a quantitative value for network security, derived from the access control and data transmission encryption of the node chain network (such as whether there is abnormal access and whether the transmission is encrypted). The more comprehensive the network security protection, the higher the quantitative value. , , The weight coefficients for each dimension are preset according to the data synchronization security requirements, representing the importance of node compliance, device status, and network security in the access assessment, and the sum of the weight coefficients is 1 to ensure the comprehensiveness of the assessment. When A reaches the preset admission threshold, the node chain is allowed to synchronize data to the domain chain; This formula is used to comprehensively evaluate the eligibility of a node chain to synchronize data with a domain chain, ensuring the security and reliability of the synchronized data. It quantifies three dimensions—node compliance, device status, and network security—and then sums them according to preset weights to obtain an access index: the higher the node compliance, the better the device status, and the stronger the network security, the higher the access index, and the easier it is to pass the synchronization access verification; conversely, the lower the access index, the more rectification is required before reapplying. Furthermore, the total weight coefficient is 1 to ensure the balance of the evaluation results. This algorithm constructs a three-pronged node synchronization access assessment system encompassing compliance, equipment, and network. It breaks through the traditional verification model that only focuses on the "data itself," ensuring synchronization data security from multiple dimensions, including node fundamental capabilities and the operating environment. By quantitatively assessing node compliance history, equipment reliability, and network security, it avoids synchronization data anomalies caused by equipment failure (such as sensor malfunction) or network attacks (such as data interception), further enhancing the accuracy and security of domain chain data. Simultaneously, flexible weight settings can adapt to the synchronization needs of data with different security levels, improving the flexibility and security of data management in the blockchain architecture modules.

[0026] In an embodiment of the present invention, the symmetric encryption algorithm is the SM4 encryption algorithm, which is used to ensure the encryption security of the inherent key. During the encryption process, a randomly generated initial vector is used to improve the encryption strength. The escrow period for temporary keys can be preset. When setting the escrow period, a reasonable duration should be determined based on actual business needs. After the temporary key expires, it will automatically become invalid and trigger a new key generation process. After the new key is generated, it needs to be updated to all related chain layers in a synchronized manner to avoid the risk of long-term permission escrow. To determine a reasonable escrow period for temporary keys, a suggested escrow period is calculated using the following formula: ; in, The suggested value for the temporary key custody period provides a quantitative reference for the duration of temporary key custody and is the core basis for determining the final custody period; The preset basic custody period is determined based on the emergency needs of biosafety operations and represents the basic custody duration for low-risk operators using temporary keys; This is the operator's operational risk value, reflecting the operator's level of operational risk, and is used to adjust the length of the trusteeship period. This is the term adjustment coefficient, generated based on the operator's risk value. The higher the risk value, the smaller the adjustment coefficient, and the shorter the recommended custody period. The lower the risk value, the larger the adjustment coefficient, and the longer the recommended custody period. This formula is used to determine a reasonable escrow period for temporary keys, avoiding security risks caused by long-term permission escrow. It links a preset base escrow period to the operator's risk value: the higher the operator's risk value, the shorter the recommended escrow period; the lower the operator's risk value, the longer the recommended escrow period. This is then fine-tuned based on actual business needs to ensure that the escrow period meets emergency use requirements while reducing the risk of permission abuse. This algorithm dynamically adapts the escrow period for temporary keys, avoiding the risks (such as high-risk individuals holding temporary keys for extended periods) or inconveniences (such as low-risk individuals frequently requesting keys) that can result from fixed-term escrow. By combining the risk values ​​of operators, differentiated escrow periods are matched for individuals with different risk levels, meeting emergency access needs while minimizing the risk of access abuse or leakage. Furthermore, it allows for fine-tuning based on actual business needs, balancing the algorithm's scientific validity with operational flexibility, further improving the key management mechanism of the multimodal authorization module, and enhancing the security and practicality of system access control.

[0027] In an embodiment of the present invention, the biometric module of the dedicated terminal completes identity verification by collecting the operator's iris or fingerprint information. During the collection, it is necessary to ensure the clarity and integrity of the biometric information. Only after the verification is passed can the operation process information be recorded. The dedicated terminal will automatically record abnormal behaviors during the operation process (such as operation timeout, failure to follow the standard procedure). When recording, it is necessary to associate the operation time, operation steps and operator information, and upload them to the domain chain as the basis for judging suspicious operations. After receiving the domain chain, the abnormal behavior information needs to be classified and stored for subsequent query. To quantify the severity of operational anomalies and serve as a supplementary basis for determining suspicious operations, an operational anomaly severity calculation is introduced, with the specific formula as follows: ; in, The severity of operational anomalies measures the risk level of a single operational anomaly and serves as an important supplementary indicator for identifying suspicious operations. The larger the value, the higher the probability that the operation will be judged as suspicious; The time deviation risk coefficient reflects the risk level of operational time synchronization deviation. The quantitative value for operational procedure violations is determined by the number of steps that violate biosafety regulations during the operation (such as failure to sample according to the procedure or failure to record operational information). The more violations, the higher the quantitative value. , The weight coefficients for each dimension are preset based on the impact of operational anomaly risks, representing the importance of time deviation risks and process violations in the severity assessment of anomalies, and the sum of the weight coefficients is 1 to ensure the comprehensiveness of the assessment. This formula is used to quantify the severity of operational anomalies, providing supplementary evidence for judging suspicious operations. The severity of the anomaly is obtained by weighting and summing the time deviation risk coefficient and the quantitative value of operational process violations according to preset weights: the higher the time deviation risk and the more violations, the higher the anomaly severity, and the greater the probability that the operation will be judged as suspicious; conversely, the lower the anomaly severity, the more likely the operation will be judged as a normal deviation. Furthermore, the total weight coefficient is 1, ensuring the reasonableness of the assessment. This algorithm enables multi-dimensional quantitative assessment of operational anomalies, overcoming the limitations of traditional methods that rely solely on a single anomaly to determine suspicious operations. By integrating time deviation risk with process violations, it more comprehensively reflects the actual severity of operational anomalies, avoiding over-control of minor anomalies (such as low-risk time deviations without process violations) while accurately identifying severe anomalies (such as high-risk time deviations with multiple process violations). Furthermore, the supplementary anomaly severity assessment provides richer evidence for suspicious operation determination, improving the accuracy and reliability of risk identification in on-chain and off-chain traceability modules, and enabling timely detection and prevention of potential biosafety operational risks.

[0028] In an embodiment of the present invention, the geographical range of the node defined by the emergency dispatch module is as follows: Based on the resource collection location or circulation path in the resource traceability results, nodes within a preset distance range are selected. Nodes without corresponding resource processing capabilities within the geographical range must be excluded during the selection process. In the priority ranking model, the urgency of an event is based on the event response time limit (e.g., whether it needs to be handled within 24 hours), the scope of impact is based on the number of people that may be affected (e.g., whether it involves densely populated areas), and the resource matching degree is based on the fit between the existing resources of the node and the event requirements (e.g., whether the type of testing equipment matches and whether the protective materials meet the requirements). The evaluation results of each dimension are combined to calculate the priority according to the preset weights. To refine the quantification of resource matching, a precise calculation of resource matching degree is introduced, taking into account the actual resource supply of nodes. The specific formula is as follows: ; in, Resource matching degree is used to accurately measure the degree of fit between node resources and event requirements, and is a key dimension for event priority assessment. These are resource dimension numbers, representing different types of resource needs (such as testing equipment, protective equipment, professional personnel, etc.), ranging from 1 to... Number them sequentially; This represents the total number of resource dimensions, determined based on the type of resource requirement for the event, and signifies the total number of resource categories involved in assessing resource matching. For the node at the th The actual supply of a resource dimension, i.e., the number of resources a node can currently provide. The quantity or capacity of such resources; For the event in the The demand for resources in the event handling process, i.e., the amount of resources needed in the event handling process. The quantity or capacity of such resources; For the first The demand weights for each resource dimension are preset based on the degree of dependence of event handling on each resource; the higher the degree of dependence, the greater the weight. This formula is used to refine the calculation of resource matching degree, providing a more accurate quantitative basis for event priority assessment. The resource matching degree is obtained by summing the products of the actual supply of a node in each resource dimension and its corresponding demand weight, and then dividing by the sum of the products of the demand of an event in each resource dimension and its corresponding demand weight. The closer the matching degree is to 1 (especially for high-weight resource dimensions), the more suitable the node is to provide resource support for the event. The calculation results are then substituted into the event priority index formula to improve the accuracy of priority assessment. This algorithm achieves refined, multi-dimensional calculation of resource matching, avoiding the limitations of traditional "coarse matching" (such as simply judging the presence or absence of corresponding resources). By introducing resource dimension weights, it prioritizes the matching of resources with core event needs (such as high-weight detection equipment), ensuring that node resources can effectively meet the critical needs of event handling. Simultaneously, the accurate matching result is substituted into the event priority index formula, improving the scientific rigor and accuracy of event priority assessment. This avoids "resource mismatch" caused by inaccurate resource matching assessment (such as allocating high-matching node resources to low-priority events), further optimizing the resource allocation efficiency of the emergency dispatch module and providing more precise resource support for the rapid response to public health emergencies.

[0029] 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 multi-dimensional data management system for biosafety physical resources, characterized in that, include: The blockchain architecture module adopts a three-level dynamic chain architecture to store resource identifiers, operation logs and real-time status data. It is configured with a chain ownership migration mechanism triggered by security level and simultaneously builds an inter-chain data consistency verification mechanism to prevent data tampering or loss during the chain ownership migration process. The multimodal authorization module constructs a multi-dimensional biometric key system, verifies cross-institutional access requests through smart contracts, and triggers security control and early warning if verification fails. It also supports on-chain emergency reset and temporary permission management in case of key abnormalities. The on-chain and off-chain traceability module links on-chain evidence storage with off-chain data, generates a full lifecycle traceability report and marks suspicious operations, and can trace all resource flow paths associated with suspicious operations to block the transmission of risks; The emergency dispatch module builds a cross-agency emergency resource database in the core chain. In the event of a public health emergency, it automatically filters nodes, generates dispatch instructions and pushes task notifications, and configures a resource conflict coordination mechanism.

2. The multi-dimensional data management system for biosafety physical resources according to claim 1, characterized in that, The three-level dynamic chain architecture of the blockchain architecture module is "core chain - domain chain - node chain"; The core chain stores the unique identifier of resources and key node information for cross-domain transfer. The regulatory body acts as a super node, which is responsible for the final review of core chain data and the issuance of synchronization instructions. The domain chain is divided according to administrative regions or institutional types. An improved practical Byzantine fault-tolerant algorithm is configured to realize data synchronization within the domain. During the synchronization process, data must be confirmed by a majority of nodes within the domain before being written to the domain chain, and resource operation logs within the corresponding range are stored. The node chain is deployed on each resource storage or operation node to store real-time status data of resources. When the node chain data is updated, the operator's identity information and operation timestamp must be recorded first. The chain rights migration mechanism is as follows: when the resource security level changes, the node chain data is automatically synchronized to the domain chain, and the domain chain core information is synchronized to the core chain. Before synchronization, the original node chain operation permissions are frozen. After synchronization is completed, a chain rights migration certificate is generated and written to the entire chain. The certificate contains chain layer information before and after migration and data verification results. The inter-chain data consistency verification mechanism is as follows: During the chain rights migration process, the core chain, domain chain, and node chain generate independent hash values ​​for the synchronized data, and confirm the data consistency by cross-comparing them pairwise. If there is a difference, the data rollback operation is triggered immediately, and an alarm message containing the location of the difference data and the comparison result is pushed to the regulatory node. To quantify the degree of data consistency differences, an inter-chain data consistency deviation value is introduced for calculation. The specific formula is as follows: ； in, This represents the inter-chain data consistency deviation value. The hash value generated by the core chain for synchronizing data. The hash value generated by the domain chain for synchronizing data. The hash value generated by the node chain for synchronizing data. This is an absolute value symbol used to eliminate the positive and negative effects of hash value differences, retaining only the magnitude of the difference.

3. The multi-dimensional data management system for biosafety physical resources according to claim 1, characterized in that, The multi-dimensional biometric key system of the multimodal authorization module includes: The inherent key is generated based on the resource's own characteristics using a symmetric encryption algorithm. The inherent key is bound to the resource's unique identifier and cannot be tampered with. The dynamic key generated by fusing the operator's iris or fingerprint features with the qualification certificate number requires desensitization of biometric features and qualification information during the fusion process. The binding key is generated based on the physical markings on the surface of the resource storage carrier or the unique code of the RFID chip. The binding key corresponds one-to-one with the carrier and is updated with the carrier status. The dynamic key is automatically updated at a preset period. The update frequency is adjusted based on the risk assessment results of the operator's historical operation behavior. The assessment takes into account the number of compliant operations and abnormal operation records. The emergency reset of the key abnormality is as follows: when it is detected that the key has been tampered with or the operator is unable to provide the key due to special reasons, the supervisory node initiates an on-chain vote. The voting nodes are preset authoritative nodes within the domain. After the vote passes, a temporary key is generated and entrusted to a designated backup person. At the same time, all operation permissions associated with the original key are frozen. The reason for the operation must be recorded when the temporary key is used. The verification process is as follows: simultaneously verify the validity of the inherent key, dynamic key, and bound key, and verify whether the biosafety protection level qualification of the accessing institution matches the resource security level; if any verification step fails, the on-chain data will be frozen immediately, the storage medium will be physically locked, and a warning message containing the verification failure step and the reason for the failure will be pushed to the regulatory node. To accurately calculate the risk assessment results of operators' historical operational behaviors and thus determine the dynamic key update frequency, an operational risk value calculation method is introduced, using the following formula: ； in, For operator risk values, This refers to the number of times an operator has complied with regulations in their historical operations. This records the number of times an operator has made a historical error. This represents the total number of operations performed by the operator in history.

4. A multi-dimensional data management system for biosafety physical resources according to claim 1, characterized in that, The association process between the on-chain and off-chain traceability modules is as follows: The sensor and communication modules integrated into the resource storage carrier collect environmental data and resource status data in real time. After collection, the data integrity is first verified. After the verification is passed, a status hash value is generated and uploaded to the node chain at a preset interval. The operation process information is recorded by a dedicated terminal with a biometric module. Before recording, the operator must be identified. After successful verification, the operation information is stored on the blockchain. After processing, the key information is synchronized to the domain chain. The risk transmission blocking is as follows: after marking a suspicious operation, all upstream transfer nodes and downstream receiving nodes of the resources involved in the operation are automatically traced, and prompt information containing details of the suspicious operation and risk level is pushed to each relevant node. Further access and detection operations of the associated resources are restricted until the risk investigation is completed and an investigation report is generated. When generating a report, the operation logs and status data of the node chain corresponding to the resource unique identifier of the core chain are compared one by one with the timestamps of the on-chain operation records and the collection timestamps of the off-chain sensor data. If there is a time deviation that exceeds the reasonable range, it is marked as a suspicious operation and the duration of the deviation is recorded. To quantify whether time deviation exceeds a reasonable range, a time deviation risk coefficient is introduced, with the specific formula as follows: ； in, For time deviation risk coefficient, This represents the absolute deviation between the on-chain operation record timestamp and the off-chain sensor data acquisition timestamp. For operator risk values, This is the risk adjustment coefficient.

5. A multi-dimensional data management system for biosafety physical resources according to claim 1, characterized in that, The cross-agency emergency resource database of the emergency dispatch module stores the resource detection capability information, protective material reserve information and personnel standby information of each node. All information must be reviewed by the node itself and verified twice by the domain chain before being uploaded. After the verification is passed, it is encrypted and written into the core chain. The resource conflict coordination mechanism is as follows: when multiple public health emergencies apply for the same node resource at the same time, a priority ranking model is constructed according to the urgency of the event, the scope of impact and the resource matching degree. When the model is calculated, the information of each dimension is first quantitatively evaluated, and then the event priority is determined comprehensively. Resources are prioritized to high priority events, while functional matching and geographically nearby alternative nodes are recommended for low priority events, and the resource availability status of alternative nodes is simultaneously informed. When selecting nodes, the geographical scope is limited by the resource traceability results. Nodes are sorted according to the principles of priority for response speed and optimal resource utilization. After sorting, scheduling instructions are generated. The instructions include the resource allocation path, the responsibility of the receiving node and the time requirements. The instructions are synchronized to the relevant node chain and the core chain. The pushed task notification includes on-chain authorization credentials. The scheduling operation can only be executed after the credentials are verified by the receiving node.

6. A multi-dimensional data management system for biosafety physical resources according to claim 2, characterized in that, The unique identifier of the resource stored in the core chain includes an encrypted resource ID and a hash root value generated based on the resource genome features. The hash root value generated based on the resource genome features is obtained by extracting species-unique fragments from the resource genome and encrypting them. During extraction, easily mutated fragments in the genome need to be excluded to ensure uniqueness. The core chain stores key node information for cross-domain transfer, including the validity period of node qualifications and historical compliance records. These serve as prerequisite verification conditions for chain rights migration. During verification, the node qualifications are first checked to see if they are valid, and then it is confirmed that there are no major violations in the historical compliance records. Chain rights migration can only be initiated after both conditions are met. To quantify the historical compliance level of nodes and serve as a basis for pre-verification of chain rights migration, a node compliance calculation is introduced, with the specific formula as follows: ； in, For node compliance, This represents the average value of the consistency deviation values ​​between historical chain data of the nodes. The preset maximum allowable deviation value is set when the node qualification is within its validity period and When the preset compliance threshold is reached, the chain rights migration can be initiated.

7. A multi-dimensional data management system for biosafety physical resources according to claim 6, characterized in that, The domain chain's resource operation logs include resource access time and operator qualification summaries. The operator qualification summaries include the operator's biosafety level operation qualification certificate number and validity period information. The summary information needs to be regularly synchronized with the regulatory authority's qualification database to ensure accuracy. When receiving synchronization data from node chains, the domain chain must first verify the device status and network security of the node chains. Data can only be received after the verification is passed. If the verification fails, the failure item will be reported and the node chains will be required to rectify the issues and resynchronize.

8. A multi-dimensional data management system for biosafety physical resources according to claim 3, characterized in that, The symmetric encryption algorithm is the SM4 encryption algorithm, which is used to ensure the encryption security of the inherent key. During the encryption process, a randomly generated initial vector is used to improve the encryption strength. The escrow period of the temporary key can be preset. When setting the escrow period, a reasonable duration is determined based on actual business needs. After the temporary key expires, it will automatically become invalid and trigger a new key generation process. After the new key is generated, it needs to be updated to all related chain layers in a synchronized manner to avoid the risk of long-term escrow of permissions.

9. A multi-dimensional data management system for biosafety physical resources according to claim 4, characterized in that, The biometric module of the dedicated terminal completes identity verification by collecting the operator's iris or fingerprint information. During the collection, it is necessary to ensure the clarity and integrity of the biometric information. Only after the verification is successful can the operation process information be recorded. The dedicated terminal will automatically record abnormal behavior during the operation. When recording, it is necessary to associate the operation time, operation steps and operator information, and upload them to the domain chain as the basis for judging suspicious operations. After receiving the domain chain, the abnormal behavior information needs to be classified and stored for subsequent query. To quantify the severity of operational anomalies and serve as a supplementary basis for determining suspicious operations, an operational anomaly severity calculation is introduced, with the specific formula as follows: ； in, For the severity of operational abnormalities, For time deviation risk coefficient, Quantification of operational process violations , The weighting coefficients for each dimension are preset based on the impact of operational anomaly risks. They represent the importance of time deviation risks and process violations in the severity assessment of anomalies, and the sum of the weighting coefficients is 1 to ensure the comprehensiveness of the assessment.

10. A multi-dimensional data management system for biosafety physical resources according to claim 5, characterized in that, The geographical range of the nodes defined by the emergency dispatch module is as follows: Based on the resource collection location or circulation path in the resource traceability results, nodes within a preset distance range are selected. Nodes without corresponding resource processing capabilities within the geographical range must be excluded during the selection process. In the priority ranking model, the urgency of the event is based on the event response time limit, the scope of impact is based on the number of people who may be affected, and the resource matching degree is based on the fit between the existing resources of the node and the event requirements. The evaluation results of each dimension are combined to calculate the priority according to the preset weight.

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