Medical insurance data secure transmission system and method based on data processing

Abstract

The invention relates to the technical field of data security transmission, and discloses a medical insurance data security transmission system and method based on data processing. The system extracts attributes and security levels of medical insurance data, and dynamically plans a transmission path according to the attributes and the security levels. And according to the capability file of each node in the path, different security encapsulation protocols are configured for different transmission segments of the data packet, and a transmission unit constrained by a strategy is formed. In the transmission process, the system continuously collects node logs and performance data and generates full-link state snapshots. And after the data arrives, analyzing the snapshot to evaluate the transmission quality, and dynamically triggering a corresponding storage strategy according to an evaluation result to complete data disk falling. According to the scheme, fine adaptation of the security policy and the network environment is realized, and a closed-loop management mechanism with a verifiable transmission process and a traceable storage decision is constructed.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of data security transmission, in particular to a medical insurance data security transmission system and method based on data processing. BACKGROUND

[0002] When the current medical insurance data is transmitted between multiple heterogeneous systems, it needs to meet the requirements of security and compliance. The existing technology usually uses a static and unified security policy to process the transmission data. This processing mode does not consider the differences in computing power, protocol support and security level of different network nodes in the actual transmission path. The unified security policy may exceed the processing load of some relay nodes, causing delay or packet loss; it may also be incompatible with the security protocol stack of a specific node, causing transmission interruption. The defect is that it cannot be adapted to the dynamically changing network environment and node capability, and it is difficult to balance security and reliability with transmission efficiency in a complex medical insurance network topology.

[0003] The existing scheme usually takes the successful reception of data as the end point of the transmission task, and then triggers the pre-set storage process. The actual processing behavior of each relay node in the transmission process, the possible performance fluctuations or protocol deviations, lack systematic recording and aggregation. There is no correlation between the storage decision and the quality of the specific transmission process. This makes it impossible to verify the integrity of the transmission path and the compliance of each link after the data is landed, making it difficult to provide reliable process evidence during auditing, and making it impossible to classify and store data based on the actual performance in the transmission process. A technical solution is needed that can finely perceive the transmission process and dynamically decide storage based on the quality of the process. SUMMARY

[0004] The purpose of the present application is to provide a medical insurance data security transmission system and method based on data processing to solve the problems raised in the background art.

[0005] To achieve the above purpose, the present application provides a medical insurance data security transmission system based on data processing, which comprises: A medical insurance data source feature extraction module is used to obtain original data packets from multiple heterogeneous medical insurance data sources, and identify the data attribute label and security level identification of each original data packet; A transmission path dynamic planning module is used to generate an initial security transmission requirement matched with each original data packet according to the data attribute label and security level identification of the original data packet, and to plan a preliminary transmission path containing multiple relay nodes for each original data packet in combination with real-time network topology and node state; a security encapsulation and policy binding module configured to configure differentiated security encapsulation protocols for the original data packets segment by segment according to the security processing capability profiles of the intermediate nodes in the preliminary transmission path, and bind the security encapsulation protocols with the original data packets to form policy-constrained data units to be transmitted; a distributed execution and state tracking module configured to inject the data units to be transmitted into their corresponding preliminary transmission paths, and continuously collect processing logs and performance metrics of the intermediate nodes during the transmission to form a full-link transmission state snapshot; an adaptive storage decision module configured to analyze the full-link transmission state snapshot after the data units to be transmitted arrive at the preset data sink pool, evaluate the integrity and compliance of the transmission process, and trigger corresponding dynamic storage strategies to complete the final landing of the data according to the evaluation results.

[0006] Preferably, the initial security transmission requirement matched with each original data packet specifically includes: analyzing the data attribute label of the original data packet, the data attribute label including the medical insurance business type to which the data belongs, the data sensitivity classification, and the data lifecycle stage; reading the security level identifier of the original data packet, the security level identifier being generated by the audit record of the data source system and the predefined security rules; matching the medical insurance business type to which the data belongs with a preset business type priority mapping table to obtain a business transmission priority; inputting the data sensitivity classification and the data lifecycle stage into a security requirement calculation model to output a basic security strength requirement; fusing the business transmission priority and the basic security strength requirement, and superimposing a system load factor corresponding to a real-time timestamp to calculate an initial security transmission requirement, the initial security transmission requirement including a minimum encryption strength, a maximum allowed delay, and a mandatory verification node list.

[0007] Preferably, the preliminary transmission path containing multiple intermediate nodes is planned for each original data packet in combination with the real-time network topology and node state, specifically including: obtaining the node state of all available data processing nodes at the current time, the node state including the current computing power remaining of the node, the availability of the encryption co-processor, the recent failure rate statistics, and the network hop number to the data sink pool; locking the fixed nodes that must be passed through in the real-time network topology according to the mandatory verification node list in the initial security transmission requirement; filtering out a candidate node set satisfying the minimum encryption strength requirement between the fixed nodes according to the current computing power remaining and the availability of the encryption co-processor in the node state; Based on the maximum allowed delay constraint, in the candidate node set, the estimated total delay of the path formed by different node combinations is calculated, which is obtained by accumulating the network delay between nodes and the estimated processing time of each node; Select the path that meets the maximum allowed delay constraint and has the lowest recent failure rate statistical sum of the nodes it passes through as the preliminary transmission path of the original data packet.

[0008] Preferably, the differentiated security encapsulation protocol is configured for the original data packet in segments, specifically including: Retrieve the security processing capability profile of each transit node in the preliminary transmission path, which records the list of encryption algorithms supported by the transit node, the type of hardware acceleration engine, and the maximum number of concurrent processing threads; For each transmission interval of the preliminary transmission path, use the security processing capability profile of the starting node of the transmission interval as the main basis, and use the security processing capability profile of the end node of the interval as the compatibility reference; From the list of encryption algorithms supported by the starting node, select an algorithm that meets the minimum encryption strength requirement and is compatible with the end node as the specified encryption algorithm for the transmission interval; According to the operation characteristics of the specified encryption algorithm and the type of hardware acceleration engine of the starting node, dynamically generate the key derivation function parameter and the data block size; Encapsulate the specified encryption algorithm, key derivation function parameter, and data block size as the security encapsulation protocol for the transmission interval, and bind it with the transmission order identifier of the original data packet in the transmission interval.

[0009] Preferably, the formation of the policy-constrained data unit to be transmitted specifically includes: Serialize the original data packet according to the pre-defined format, and embed the path index code in the header of the serialized data, which points to the unique number of its preliminary transmission path; Generate independent protocol instruction sets for the security encapsulation protocol of each transmission interval, and assemble all protocol instruction sets into a policy execution script according to the transmission order; Sign the serialized data using the hash value of the policy execution script, package the signature, policy execution script, and serialized data together to generate the data unit to be transmitted; The structure of the data unit to be transmitted is set to only when the policy execution script is correctly interpreted and executed by the transit nodes in sequence, the core serialized data can be finally read.

[0010] Preferably, the formation of the full-link transmission state snapshot specifically includes: When each relay node processes a data unit to be transmitted, the relay node performs operations according to the corresponding protocol instruction set in the bound strategy execution script; After a node completes an operation, it generates a status record, which includes the node's identity identifier, the timestamps of the start and end of the operation, the specific resource metric used, the operation result code, and the next-hop node information. The distributed execution and state tracking module asynchronously collects the state records uploaded by all relay nodes during the transmission process; The status records arranged in chronological order are compared with the theoretical node sequence of the initial transmission path to verify the integrity and correctness of the path execution. All status records, verification results, and the final transmission completion time are integrated into a full-link transmission status snapshot.

[0011] Preferably, the assessment of the integrity and compliance of the transmission process specifically includes: Analyze the entire link transmission status snapshot and extract the operation result code uploaded by each node. Check the operation result code sequence to confirm that each code indicates successful execution and that the number of status records is exactly the same as the number of relay nodes in the initial transmission path; Check the start and end timestamps of each node's operation, calculate the time interval between operations of adjacent nodes, and determine whether all time intervals are less than the preset network timeout threshold; Verify that the specific resource metrics used by each node are within the normal ranges described in its security handling capability profile, and check for any abnormal resource access patterns. Based on the results of the above checks, verifications and validations, a binary assessment conclusion is generated, which is either complete compliance or an anomaly exists.

[0012] Preferably, triggering the corresponding dynamic storage strategy to complete the final data write-to-disk process specifically includes: If the binary evaluation conclusion is complete compliance, then the serialized data is parsed from the data unit to be transmitted, and its data attribute tags are read. Based on the medical insurance business type and data sensitivity classification in the data attribute tags, query the storage strategy matrix to obtain the type of target storage medium, the number of redundant data copies, and the data cooling and archiving rules. According to the obtained storage configuration, the serialized data and its end-to-end transmission status snapshot are treated as an indivisible whole and written to the specified target storage medium to complete the final disk write-to-disk process. If the binary assessment concludes that there is an anomaly, the automatic disk write process will be suspended, and the data unit to be transmitted, the full-link transmission status snapshot, and the anomaly details will be marked as isolated data packets and transferred to the security audit queue for manual intervention.

[0013] Preferably, the system further includes: The post-transmission strategy optimization module is used to perform backtracking analysis of the historical transmission process to optimize the strategy after the data has been finally written to disk. Specifically, it includes: Periodically extract cases that have completed transmission. Each case includes its initial secure transmission requirements, the planned initial transmission path, and the actual generated full-link transmission status snapshot. By comparing the theoretical performance indicators of the initial transmission path with the actual transmission process in terms of delay and resource consumption, path segments with significant deviations are identified. Analyze the causes of the deviation, correlate the global load logs of the relevant nodes during the transmission process, and determine whether the deviation is caused by occasional performance fluctuations of the nodes or by defects in the path planning logic. Based on the analysis results, the node state evaluation model or path selection weight parameters in the transmission path dynamic planning module are adaptively modified.

[0014] Preferably, the present invention also includes a method for secure transmission of medical insurance data based on data processing, the method comprising all the modules and method flow of the medical insurance data secure transmission system based on data processing described above.

[0015] Compared with the prior art, the beneficial effects of the present invention are: Based on the security processing capabilities of each relay node in the transmission path, a matching security encapsulation protocol is dynamically configured for the same data packet in different network segments. This segment-by-segment differentiation strategy ensures that high-strength encryption and other security resources are accurately delivered to link segments with sufficient processing capacity, while adaptable lightweight or compatible encapsulation is used in segments with limited processing capacity or specific protocol requirements. This avoids the unnecessary burden on weak nodes caused by a single high-strength protocol running throughout the entire process, and also overcomes transmission failures caused by protocol incompatibility. In the complex and heterogeneous medical insurance network environment, a balance between security strength and transmission efficiency is achieved, improving the overall link reliability and throughput performance.

[0016] After data transmission is complete, fixed storage is not immediately implemented. Instead, a snapshot of the entire transmission process, dynamically aggregated from the processing logs and performance metrics of each node, is analyzed and evaluated. Based on the specific results reflected in this evaluation, such as transmission integrity and node behavior compliance, corresponding storage policies are dynamically triggered. Data with completely compliant and anomaly-free transmission can be directly stored in the production database; data with minor performance fluctuations or requiring audit documentation can be transferred to a buffer or audit database; data with suspected security alerts or serious deviations is isolated and marked for investigation. This ensures that every data storage action is directly linked to and controlled by the quality verification of its current transmission process, establishing an auditable closed loop from transmission to storage, enhancing the traceability of the data lifecycle and the accountability for security incidents. Attached Figure Description

[0017] Figure 1 This is a timing diagram of the medical insurance data security transmission system based on data processing described in this invention; Figure 2 A flowchart for generating initial secure transmission requirements; Figure 3 A flowchart for configuring the security encapsulation protocol segment by segment; Figure 4 A multi-dimensional scoring heatmap for end-to-end compliance checks; Figure 5 This is a graph showing the correlation between relay node failure rate and transmission success rate. Detailed Implementation

[0018] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0019] Please see Figure 1This invention provides a medical insurance data secure transmission system and method based on data processing. The system includes: a medical insurance data source feature extraction module, a transmission path dynamic planning module, a security encapsulation and policy binding module, a distributed execution and state tracking module, and an adaptive storage decision module. The medical insurance data source feature extraction module connects to multiple heterogeneous medical insurance data sources, obtains raw data packets from these data sources, and performs feature analysis on each raw data packet to identify its data attribute tags and security level identifiers. The transmission path dynamic planning module receives the data attribute tags and security level identifiers from the feature extraction module, and generates initial secure transmission requirements matching the raw data packet based on this information. This module also accesses real-time network status monitoring data, and, combined with real-time network topology and node status, plans a preliminary transmission path containing multiple relay nodes for each raw data packet. The security encapsulation and policy binding module, based on the planned preliminary transmission path, retrieves the security processing capability profiles of each relay node in the path, configures differentiated security encapsulation protocols for each transmission segment of the raw data packet from the origin to the destination based on these profiles, and then binds these security encapsulation protocols to the raw data packet to form a policy-constrained data unit to be transmitted. The distributed execution and state tracking module is responsible for injecting the data units to be transmitted into their corresponding initial transmission paths, initiating the transmission process, and continuously collecting processing logs and performance metrics from each relay node during transmission. This scattered information is then aggregated into a snapshot of the entire transmission state. The adaptive storage decision module is activated after the data units arrive at the preset data aggregation pool. This module analyzes the snapshot of the entire transmission state provided by the state tracking module, comprehensively assesses the integrity and compliance of the transmission process, and finally triggers the corresponding dynamic storage strategy based on the assessment results to complete the final data write-to-disk operation.

[0020] Example 1: See Figure 2 When generating initial security transmission requirements matching each raw data packet, the transmission path dynamic planning module parses the data attribute tags of the raw data packets. These tags include the medical insurance business type to which the data belongs, the data sensitivity classification, and the data lifecycle stage. Simultaneously, the module reads the security level identifier of the raw data packets, which is generated jointly by the audit records of the data source system and predefined security rules. The module matches the medical insurance business type to which the data belongs with a preset business type priority mapping table to obtain the business transmission priority. It then inputs the data sensitivity classification and data lifecycle stage into the security requirement calculation model, which outputs basic security strength requirements. The module integrates the business transmission priority and basic security strength requirements, and overlays the system load factor corresponding to the real-time timestamp, to calculate the initial security transmission requirements. These initial security transmission requirements include the minimum encryption strength, the maximum allowable delay, and a list of mandatory verification nodes.

[0021] When planning an initial transmission path containing multiple relay nodes for each raw data packet by combining real-time network topology and node status, the transmission path dynamic planning module obtains the node status of all available data processing nodes at the current moment. The node status includes the node's current remaining computing power, encryption coprocessor availability, recent failure rate statistics, and network hop count with the data aggregation pool. Based on the mandatory verification node list in the initial secure transmission requirements, the module identifies the fixed nodes that must be traversed in the real-time network topology. Among these fixed nodes, based on the current remaining computing power and encryption coprocessor availability in the node status, it selects a set of candidate nodes that meet the minimum encryption strength requirements. Based on the maximum allowable delay constraint, the module calculates the estimated total delay of paths formed by different node combinations within the candidate node set. This estimated total delay is obtained by summing the network delay between nodes and the estimated processing time of each node. The module selects the path that meets the maximum allowable delay constraint and has the lowest sum of recent failure rate statistics for the traversed nodes as the initial transmission path for the raw data packet.

[0022] In practice, the medical insurance data source feature extraction module obtains raw data packets from multiple heterogeneous medical insurance data sources. For example, raw data packets may originate from the outpatient settlement system of designated medical institutions, inpatient medical record databases, or the reimbursement record database of medical insurance agencies. The medical insurance data source feature extraction module parses the raw data packets, identifying data attribute tags and security level identifiers. Data attribute tags include the medical insurance business type to which the data belongs, the data sensitivity classification, and the data lifecycle stage. The medical insurance business type can be outpatient settlement, inpatient registration, or drug procurement. The data sensitivity classification is divided into public, internal, and confidential levels according to preset rules. The data lifecycle stage indicates whether the data is in the collection, transmission, or archiving state. The security level identifier is generated jointly by the audit records of the data source system and predefined security rules, which include the security authentication level and historical violation count of the data source system.

[0023] In some embodiments, the transmission path dynamic planning module reads the security level identifier of the original data packet and parses the data attribute tags of the original data packet. The transmission path dynamic planning module has a pre-set service type priority mapping table. It matches the medical insurance service type to which the data belongs in the data attribute tags with the service type priority mapping table to obtain the service transmission priority. For example, the service type priority mapping table specifies that the service transmission priority for "emergency settlement" is "P0", and the service transmission priority for "chronic disease management" is "P2". The transmission path dynamic planning module inputs the data sensitivity classification and data lifecycle stage from the data attribute tags into the security requirement calculation model, and the security requirement calculation model outputs the basic security strength requirements. In its implementation, the security requirements calculation model receives data sensitivity classification and data lifecycle stage from data attribute tags as input parameters. Data sensitivity classification is divided into public, internal, or secret levels according to preset rules, and the data lifecycle stage indicates whether the data is in the collection, transmission, or archiving stage. The model processes these input parameters through internally predefined evaluation logic, comprehensively evaluating the data based on its sensitivity classification level and the criticality of its lifecycle stage, and outputs basic security strength requirements. These requirements, expressed as quantitative indicators, explicitly specify the minimum number of bits that the encryption algorithm must achieve and the strength level that the integrity verification mechanism must meet. The basic security strength requirements include quantitative indicators for the encryption algorithm's bit depth and the integrity verification strength.

[0024] In practical implementation, the transmission path dynamic planning module integrates business transmission priority and basic security strength requirements, and overlays the system load factor corresponding to the real-time timestamp to calculate the initial secure transmission requirements. The system load factor is a dynamic variable reflecting the current overall utilization of system computing resources. The initial secure transmission requirements include the minimum encryption strength, the maximum allowable delay, and a list of mandatory verification nodes. The minimum encryption strength is the number of bits that the encryption algorithm must achieve, such as AES-256. The maximum allowable delay is the maximum time allowed for a data packet to travel from its origin to its destination in the data aggregation pool. The list of mandatory verification nodes is a set of node identifiers with specific auditing functions that must be traversed in the transmission path. The calculation of the initial secure transmission requirements can be quantitatively expressed using the following formula:

[0025] in: This represents the calculated secure transmission requirement value, which is used for subsequent mapping to generate specific requirement parameters. Weighting coefficients representing the priority of service transmission; This represents the numerical level obtained after mapping service transmission priority. The quantitative value of the basic security strength requirement output by the security requirement calculation model; Represents the load impact coefficient; This represents the quantized value of the system load factor corresponding to the real-time timestamp.

[0026] In some embodiments, the transmission path dynamic planning module obtains the node status of all available data processing nodes at the current moment. The node status includes the node's current remaining computing power, cryptographic coprocessor availability, recent failure rate statistics, and network hop count with the data pool. Current remaining computing power is expressed as a percentage. Cryptographic coprocessor availability indicates whether the node has hardware encryption acceleration capabilities. Recent failure rate statistics are the proportion of failed transactions processed by the node over a past period. Based on the mandatory verification node list in the initial secure transmission requirements, the transmission path dynamic planning module locks down the fixed nodes that must be traversed in the real-time network topology.

[0027] In practical implementation, among fixed nodes, the transmission path dynamic planning module filters out a set of candidate nodes that meet the minimum encryption strength requirement based on the node's current remaining computing power and the availability of the encryption coprocessor. For example, if the minimum encryption strength requirement is AES-256, nodes with an encryption coprocessor availability of "not supported" will be excluded from the candidate node set, as will nodes with current remaining computing power below a threshold. Based on the maximum allowable delay constraint, the transmission path dynamic planning module calculates the estimated total delay of paths formed by different node combinations within the candidate node set. The estimated total delay is obtained by summing the network delay between nodes and the estimated processing time of each node. The network delay between nodes is based on real-time network monitoring data. The estimated processing time of each node is estimated based on the node's current remaining computing power and the size of the data packets to be processed.

[0028] Optionally, the transmission path dynamic planning module selects the path that satisfies the maximum allowable delay constraint and has the lowest sum of recent failure rates of the nodes along the route as the initial transmission path for the original data packet. For example, if two paths both satisfy the maximum allowable delay constraint, and the sum of failure rates of the nodes along path A is 0.05 while the sum of failure rates of the nodes along path B is 0.12, then path A is selected as the initial transmission path. It can be understood that the initial transmission path planned by the transmission path dynamic planning module for each original data packet is an ordered sequence of nodes, indicating the intermediate nodes that the data packet needs to pass through sequentially from the source to the data aggregation pool.

[0029] Example 2: See Figure 3When configuring differentiated security encapsulation protocols for each segment of the original data packet, the security encapsulation and policy binding module retrieves the security processing capability profile of each relay node in the initial transmission path. This profile records the list of encryption algorithms supported by each relay node, the type of hardware acceleration engine, and the maximum number of concurrent processing threads. For each transmission segment of the initial transmission path, the module uses the security processing capability profile of the starting node of the segment as the primary basis and the security processing capability profile of the ending node as a compatibility reference. From the list of encryption algorithms supported by the starting node, it selects an algorithm that meets the minimum encryption strength requirements and is compatible with the ending node as the designated encryption algorithm for that transmission segment. Based on the computational characteristics of the designated encryption algorithm and the type of hardware acceleration engine of the starting node, the module dynamically generates key derivation function parameters and data block size. It then encapsulates the designated encryption algorithm, key derivation function parameters, and data block size into a security encapsulation protocol for that transmission segment and binds it to the transmission order identifier of the original data packet within that segment.

[0030] When forming a policy-constrained data unit to be transmitted, the secure encapsulation and policy binding module serializes the original data packet according to a predefined format and embeds a path index code in the header of the serialized data. This path index code points to a unique number of its initial transmission path. The module generates an independent protocol instruction set for the secure encapsulation protocol of each transmission segment and assembles all protocol instruction sets into a policy execution script according to the transmission order. The hash value of the policy execution script is used to sign the serialized data. The signature, the policy execution script, and the serialized data are then packaged together to generate the data unit to be transmitted. The structure of the data unit to be transmitted is configured such that its core serialized data can only be finally read after the policy execution script has been correctly interpreted and executed sequentially by the relay nodes.

[0031] In practical implementation, the security encapsulation and policy binding module receives preliminary transmission path information from the transmission path dynamic planning module. This preliminary transmission path information includes an ordered sequence of relay nodes. The module retrieves the security processing capability profile of each relay node in the preliminary transmission path. This profile records the list of encryption algorithms supported by the relay node, the type of hardware acceleration engine, and the maximum number of concurrent processing threads. The list of encryption algorithms lists all encryption algorithm names and versions that the node can execute. The hardware acceleration engine type describes whether the node is equipped with a dedicated cryptographic hardware module and its model. The maximum number of concurrent processing threads indicates the node's upper limit for processing multiple data packets simultaneously. The module configures a security encapsulation protocol for each transmission segment of the preliminary transmission path for the original data packets. A transmission segment is defined as a unidirectional data transfer segment between two adjacent relay nodes on the path. The module uses the security processing capability profile of the starting node of the transmission segment as the primary basis and the security processing capability profile of the ending node as a compatibility reference. From the list of encryption algorithms supported by the starting node, it selects an algorithm that meets the minimum encryption strength requirements and is compatible with the ending node as the specified encryption algorithm for the transmission segment. For example, if the starting node of a transmission segment supports "AES-256-GCM" and "ChaCha20-Poly1305", and the ending node supports "AES-256-GCM" and "AES-128-GCM", and the minimum encryption strength requirement is 256 bits, then the security encapsulation and policy binding module selects "AES-256-GCM" as the specified encryption algorithm for this transmission segment.

[0032] In some embodiments, the security encapsulation and policy binding module dynamically generates key derivation function parameters and data block size based on the computational characteristics of the specified encryption algorithm and the hardware acceleration engine type of the starting node. The computational characteristics include whether the algorithm is a block cipher or stream cipher, the block length, and the authentication mode type. The hardware acceleration engine type affects key generation efficiency and block processing optimization. When dynamically generating the data block size, the security encapsulation and policy binding module considers the node's parallel processing capabilities and memory caching efficiency, determining the size through a computational model. This computational model can be expressed by the following formula:

[0033] in: This represents the calculated size of the data block in bytes. The maximum number of bytes that a node can process as defined in the security processing capability profile; This represents the maximum number of concurrent processing threads recorded in the security processing capability profile. This represents a base value in bytes for the block size, determined by the specified encryption algorithm and hardware acceleration engine type. The secure encapsulation and policy binding module encapsulates the specified encryption algorithm, key derivation function parameters, and data block size into a secure encapsulation protocol for the transmission interval, and binds it to the transmission order identifier of the original data packet within the transmission interval.

[0034] In practical implementation, the secure encapsulation and policy binding module serializes the original data packets according to a predefined format, which can be JSON, Protocol Buffers, or a custom binary format. It embeds a path index code in the header of the serialized data, pointing to a unique number of its initial transmission path. The secure encapsulation and policy binding module generates an independent protocol instruction set for each transmission segment's secure encapsulation protocol. This protocol instruction set is a set of machine-readable commands that details the specific operational steps to be performed on the data within the corresponding transmission segment, such as "using key K to encrypt the data block using AES-256-GCM and generate an authentication tag."

[0035] Optionally, the secure encapsulation and policy binding module uses the hash value of the policy execution script to sign the serialized data. The hash value is obtained by applying a hash algorithm to the content of the policy execution script, and the signing process uses an asymmetric encryption algorithm to ensure integrity. The secure encapsulation and policy binding module packages the signature, policy execution script, and serialized data together to generate a data unit to be transmitted. The structure of the data unit to be transmitted is set so that its core serialized data can only be finally read after the policy execution script is correctly interpreted and executed by the relay nodes in sequence. For example, the packet structure of the data unit to be transmitted is as follows: fixed format packet header, policy execution script length field, policy execution script content, digital signature, serialized data length field, and serialized data content.

[0036] Example 3: When forming a full-link transmission state snapshot, the distributed execution and state tracking module asynchronously collects the state records uploaded by all relay nodes during transmission. These state records are generated by each relay node when processing the data unit to be transmitted. Each node executes operations according to the corresponding protocol instruction set in the bound policy execution script. After completing the operation, the node generates a state record, which includes the node's identity identifier, the timestamps of the operation's start and end, the specific resource metric used, the operation result code, and the next-hop node information. The distributed execution and state tracking module compares the state records arranged in chronological order with the theoretical node sequence of the initial transmission path to verify the completeness and correctness of the path execution order. It then integrates all state records, verification results, and the final transmission completion time into a full-link transmission state snapshot.

[0037] In practice, after the data unit to be transmitted is injected into its corresponding initial transmission path, the distributed execution and state tracking module begins to monitor the transmission process. During transmission, each relay node, upon receiving the data unit to be transmitted, executes the corresponding protocol instruction set within the script according to the policy bound to the data unit. Operations include decryption, signature verification, re-encryption, or integrity verification. After completing the operation, the relay node generates a state record, which includes the node's identity identifier, the timestamps of the operation's start and end, the specific resource metrics used, the operation result code, and the next-hop node information. The node's identity identifier is a unique code for that node in the network. The timestamps of the operation's start and end record the precise start and end times of the node's processing of this data unit. The specific resource metrics used may include CPU utilization, peak memory consumption, and network I / O volume. The operation result code is a predefined enumeration value, such as "SUCCESS", "VERIFY_FAIL", or "DECRYPT_ERROR".

[0038] In some embodiments, the distributed execution and state tracking module asynchronously collects state records uploaded by all relay nodes during transmission. Asynchronous collection means that the collection action and the node's processing action are not synchronized. After generating a state record, the node immediately sends it to the distributed execution and state tracking module through an independent channel, without blocking the forwarding of the data unit to the next hop. The distributed execution and state tracking module maintains a buffer associated with the path index code of each data unit to be transmitted, used to temporarily store the collected state records. For example, for a transmission passing through nodes A, B, and C, the distributed execution and state tracking module receives state records from nodes B, A, and C in sequence, and classifies and sorts them according to the timestamp and path index code in the state records.

[0039] In practical implementation, the distributed execution and state tracking module compares the state records arranged in chronological order with the theoretical node sequence of the initial transmission path to verify the integrity and correctness of the path execution. The theoretical node sequence is a list of node sequences planned by the transmission path dynamic planning module, such as [A, B, C]. The comparison process checks whether the node identification order of the state record sequence sorted by the operation start timestamp is completely consistent with the theoretical node sequence [A, B, C]. The integrity check ensures that the number of state records is equal to the number of nodes in the theoretical node sequence; for example, if the theoretical number of nodes is 3, then exactly 3 state records must be collected. The correctness of the sequence check ensures that the order of the node identification in the state records is consistent with the theoretical sequence, and that the next-hop node information recorded in each state record matches the subsequent nodes of that node in the theoretical sequence.

[0040] Optionally, the distributed execution and state tracking module employs a quantitative method to evaluate the compliance of path execution and generate a consistency check value, which can be expressed by the following formula:

[0041] in: This represents the calculated path consistency check value, ranging from 0 to 1; Represents the total number of nodes in the theoretical node sequence; Represents the number sorted by time The node identity identifier in the status record; The first node in the theoretical node sequence The node's identity identifier at each location; It is a comparison function, when equal The result is 1 if the condition is met, and 0 otherwise. Representing the The next-hop node information recorded in the status record; The first node in the theoretical node sequence Each node should have the next-hop node information; This represents the number of status records actually collected. This represents the expected number of status records to be collected, and its value is equal to... .

[0042] In some embodiments, the distributed execution and state tracking module integrates all state records, verification results, and the final transmission completion time into a single end-to-end transmission state snapshot. The verification results include integrity check conclusions, sequence correctness check conclusions, and consistency check values. All state records are embedded in the end-to-end transmission state snapshot in the form of raw data and accompanying metadata. The final transmission completion time refers to the timestamp at which the data unit to be transmitted is successfully received and acknowledged by the data aggregation pool. The end-to-end transmission state snapshot exists as a structured data object, such as a JSON document containing fields for "path index code," "theoretical path," "actual state record list," "integrity verification result," "sequence verification result," "consistency check value," and "completion timestamp."

[0043] Example 4: When assessing the integrity and compliance of the transmission process, the adaptive storage decision module parses the end-to-end transmission status snapshot, extracts the operation result code uploaded by each node, checks the operation result code sequence, confirms that each code indicates successful execution, and that the number of status records is completely consistent with the number of relay nodes in the initial transmission path. The module verifies the start and end timestamps of each node's operation, calculates the time interval between operations of adjacent nodes, determines whether all time intervals are less than the preset network timeout threshold, verifies whether the specific resource metrics used by each node conform to the normal range recorded in its security processing capability profile, and checks for any abnormal resource access patterns. Based on the results of the above checks, verifications, and validations, the module generates a binary evaluation conclusion, which is either complete compliance or an anomaly exists.

[0044] When the corresponding dynamic storage strategy is triggered to complete the final data write-to-disk process, if the binary assessment conclusion is complete compliance, the adaptive storage decision module parses the serialized data from the data unit to be transmitted and reads its data attribute tags. Based on the medical insurance business type and data sensitivity classification in the data attribute tags, the module queries the storage strategy matrix to obtain the type of target storage medium, the number of redundant data copies, and the data cooling and archiving rules. According to the obtained storage configuration, the module writes the serialized data and its end-to-end transmission status snapshot as an indivisible whole to the specified target storage medium, completing the final write-to-disk process. If the binary assessment conclusion indicates an anomaly, the module pauses the automatic write-to-disk process and marks the data unit to be transmitted, the end-to-end transmission status snapshot, and the anomaly details as isolated data packets, transferring them to the security audit queue for manual intervention.

[0045] In practice, the adaptive storage decision module is activated after the data unit to be transmitted arrives at the preset data aggregation pool. The adaptive storage decision module receives and parses the end-to-end transmission status snapshot provided by the distributed execution and state tracking module. It extracts the operation result code uploaded by each node in the end-to-end transmission status snapshot. The operation result code is a predefined code representing the success or failure of the processing action of each relay node. The adaptive storage decision module checks the sequence of operation result codes to confirm that each operation result code in the sequence indicates successful execution, and that the number of status records is exactly the same as the number of relay nodes in the initial transmission path. For example, for a transmission task with a planned path containing 3 relay nodes, the adaptive storage decision module must find exactly 3 status records in the end-to-end transmission status snapshot, and the operation result code in each status record must be "SUCCESS".

[0046] In some embodiments, the adaptive storage decision module verifies the start and end timestamps of each node's operation in the end-to-end transmission status snapshot and calculates the time interval between adjacent node operations. The adaptive storage decision module determines whether all calculated time intervals are less than a preset network timeout threshold. The network timeout threshold is a pre-set time value based on different network environments and service requirements, such as 500 milliseconds. The adaptive storage decision module verifies whether the specific resource metrics used by each node conform to the normal range recorded in its security processing capability profile. The normal range recorded in the security processing capability profile defines the typical range of CPU utilization and memory usage when a node processes similar tasks. The adaptive storage decision module checks for abnormal resource access patterns, including but not limited to bursts of reading large amounts of data in a very short time, abnormally frequent key access requests, or continuous memory usage several times exceeding the normal range recorded in the profile.

[0047] In practice, the adaptive storage decision module generates a binary evaluation conclusion based on the results of the above checks, verifications, and validations. The binary evaluation conclusion is either "completely compliant" or "anomaly exists." The logic for generating the binary evaluation conclusion follows a series of predefined rules. For example, the rules stipulate that the binary evaluation conclusion is "completely compliant" only if all operation result codes are success, the number of status records matches, all time intervals do not time out, all resource metrics are within the normal range, and no abnormal access patterns are detected; if any of the above conditions are not met, the binary evaluation conclusion is "anomaly exists."

[0048] Optionally, the adaptive storage decision module employs a quantitative method for calculating anomaly deviations when verifying resource metrics. This method can be expressed by the following formula: This represents the calculated comprehensive resource deviation index; in: This represents the number of resource metrics being monitored. Representing the The weighting coefficient of resource measurement in the judgment; The first snapshot recorded in the end-to-end transmission state snapshot The actual value of the resource measurement; The representative obtained from the security processing capability file Historical average values ​​of species resource measures; The representative obtained from the security processing capability file Historical standard deviation of resource measurement. When If the value exceeds the preset deviation threshold, it is determined that the resource usage is not within the normal range or there is an abnormal pattern.

[0049] If the binary assessment conclusion is "complete compliance," the adaptive storage decision module parses the serialized data from the data unit to be transmitted and reads the data attribute tags embedded in the header of the serialized data. The adaptive storage decision module queries the storage strategy matrix based on the medical insurance business type and data sensitivity classification in the data attribute tags. The storage strategy matrix is ​​a configuration table defining how different data categories should be stored. The adaptive storage decision module obtains the target storage medium type, the number of redundant data copies, and the data cooling-off archiving rules from the storage strategy matrix. The target storage medium type specifies whether the data should be stored in a high-speed solid-state storage pool, a large-capacity hard disk array, or an archive tape library. The number of redundant data copies specifies how many independent storage nodes the data should be written to simultaneously. The data cooling-off archiving rules define how long the data should remain on the initial storage medium before automatically migrating to a lower-cost archiving medium. The adaptive storage decision module writes the serialized data and its end-to-end transmission status snapshot as an indivisible whole to the specified target storage medium according to the obtained storage configuration, completing the final disk write. In some embodiments, referring to Table 1, the contents of the storage strategy matrix are defined in tabular form.

[0050] Table 1: Storage Strategy Matrix

[0051] If the binary assessment concludes that "an anomaly exists," the adaptive storage decision module pauses the automatic disk write process and marks the data unit to be transmitted, the end-to-end transmission status snapshot, and the anomaly details as isolated data packets. The anomaly details record which of the following checks failed: operation result code, record quantity, time interval, resource metric, or access mode. The adaptive storage decision module then transfers the marked isolated data packets to a security audit queue for manual intervention. The security audit queue is a special storage area with access control, accessible and analyzed only by security administrators.

[0052] It is understandable that the adaptive storage decision module dynamically determines the final destination of data based on verifiable evidence of the transmission process. Complete and compliant transmission directly triggers automated and differentiated storage to disk, while abnormal transmission is automatically intercepted and transferred to the manual audit process. This mechanism provides a final review checkpoint for data security and compliance while ensuring storage efficiency.

[0053] See Figure 4In the full-link compliance verification phase of the end-to-end compliance check, the heatmap uses the transmission task ID as the horizontal axis and the inspection dimension as the vertical axis, quantifying the performance of each task in different compliance dimensions through color gradients (50-100 points). Specifically, in the dimensions of operation result code, record quantity matching, time interval compliance, and access mode compliance, most tasks (tasks 1-6 and task 8) scored 100 points, with only task 7 showing a decrease in scores in the dimensions of record quantity matching (80 points) and time interval compliance (70 points). In the dimension of resource measurement compliance, task 7 scored as low as 50 points, while the scores of the remaining tasks were concentrated in the range of 94-99 points. The scoring logic of the heatmap corresponds to the compliance assessment rules of the end-to-end transmission status snapshot: operation result code, record quantity, time interval, resource measurement, and access mode are the core inspection items, and failure to meet the standard in any dimension is judged as "abnormal". As can be seen from the data, task 7 did not meet the compliance requirements in the dimensions of resource measurement, time interval, and record quantity, and is a typical "abnormal" task; the remaining tasks meet the judgment conditions of "complete compliance".

[0054] Example 5: The system also includes a transmission strategy post-implementation optimization module. After the data is finally written to disk, this module performs backtracking analysis on the historical transmission process to optimize the strategy. The module periodically extracts completed transmission cases, which include the initial security transmission requirements, the planned preliminary transmission path, and the actual generated full-link transmission status snapshot. The module compares the theoretical performance indicators of the preliminary transmission path with the actual transmission process in terms of latency and resource consumption, identifies path segments with significant deviations, analyzes the causes of these deviations, and correlates them with the global load logs of relevant nodes during the transmission process to determine whether the deviations are caused by occasional node performance fluctuations or path planning logic defects. Based on the analysis results, the module adaptively adjusts the node state evaluation model or path selection weight parameters in the transmission path dynamic planning module.

[0055] In practical implementation, the transmission strategy post-implementation optimization module initiates a retrospective analysis of the historical transmission process after the data is finally written to disk to optimize the strategy. This module periodically extracts completed transmission cases from the stored data records. These cases include the initial security transmission requirements, the planned preliminary transmission path, and a snapshot of the actual end-to-end transmission status. For example, at a fixed time each day, the module extracts all transmission task records marked as "fully compliant" and written to disk from the storage logs over the past 24 hours as analysis samples. The data packets for each sample case are associated with the initial security transmission requirements document generated during transmission planning, the preliminary transmission path description file composed of node sequences, and the end-to-end transmission status snapshot file generated by the distributed execution and status tracking module.

[0056] In some embodiments, the transmission strategy aftereffect optimization module compares the theoretical performance indicators of the initial transmission path in the case study with the actual transmission process metrics in terms of latency and resource consumption to identify path segments with significant deviations. Theoretical performance indicators are calculated based on node states and network topology data used during planning, such as the theoretically estimated total latency. Metrics of the actual transmission process are extracted from end-to-end transmission state snapshots; for example, the actual total latency is calculated from the difference between the start and end timestamps of the first node's operation in the state snapshot. The transmission strategy aftereffect optimization module calculates the deviation rate between the theoretical and actual values; when the deviation rate exceeds a preset threshold, the path segment is determined to have a significant deviation.

[0057] In practical implementation, the transmission strategy post-effect optimization module analyzes the causes of deviations. This module correlates the global load logs of relevant nodes during the transmission process to determine whether the deviation is due to occasional node performance fluctuations or path planning logic defects. The global load logs record time-series data on the CPU, memory, network, and encryption coprocessor usage of nodes over historical periods. The transmission strategy post-effect optimization module compares the actual transmission time of the problematic path segment with the load curves of nodes in the global load logs for the same period. If a node experiences load spikes or resource contention during the problematic time period, the deviation is caused by occasional node performance fluctuations. If the node load is stable but the actual latency is still significantly higher than the theoretical value, it suggests a defect in the model or parameters used by the path planning logic to estimate latency.

[0058] Optionally, the transmission strategy aftereffect optimization module employs a quantitative method to calculate and identify the deviation between the theoretically estimated total delay and the actual total delay. This calculation can be expressed by the following formula:

[0059] in: This represents the calculated delay deviation ratio; This represents the actual total latency calculated from a snapshot of the end-to-end transmission state. This represents the theoretically estimated total delay calculated during planning; This represents the number of relay nodes along the transmission path. This represents the absolute value of the difference between the actual total delay and the theoretically estimated total delay. Representative node The average processing latency over a recent historical time window. Greater than the preset sensitivity coefficient At that time, the transmission strategy after-effect optimization module determined that there was a significant deviation in the path.

[0060] The transmission strategy post-optimization module adaptively adjusts the node state evaluation model or path selection weight parameters in the transmission path dynamic planning module based on the analysis results. If the analysis conclusion points to occasional performance fluctuations of a node, the transmission strategy post-optimization module updates the "recent failure rate statistics" or related reliability indicators of that node in the transmission path dynamic planning module, making it more sensitive to changes in node stability. If the analysis conclusion points to flaws in the path planning logic, the transmission strategy post-optimization module adjusts the weight parameters used by the transmission path dynamic planning module in path selection to calculate the "estimated total delay" or evaluate the "sum of failure rate statistics," for example, increasing the weight of network hop count or decreasing the weight of the single encryption coprocessor availability indicator. It can be understood that the transmission strategy post-optimization module achieves continuous evolution of the strategy through a closed-loop feedback mechanism. It uses the actual effects of historical transmissions as input, diagnoses the incompatibility of the planning model or parameters, and fine-tunes the core decision-making logic of the transmission path dynamic planning module.

[0061] See Figure 5 In the optimization of the dynamic planning strategy for the transmission path of the medical insurance data security transmission system, the correlation between the average failure rate of relay nodes and the transmission success rate was revealed. Specifically, the graph uses the average failure rate of nodes on the horizontal axis and the transmission success rate on the vertical axis, quantifying the negative correlation between the two through fitting the "actual data" curve with a "secondary trend line." Simultaneously, the graph sets a "failure rate threshold (2.5%)" (marked by a red dashed line) and a "success rate threshold (95%)" (marked by a green dashed line) as policy constraint benchmarks. The actual characteristics are as follows: when the average failure rate of nodes is below 2.5%, the transmission success rate can maintain a compliance level above 95%; however, when the failure rate exceeds this threshold, the transmission success rate shows an accelerated downward trend as the failure rate increases. The core logic of this correlation is that the failure risk of relay nodes directly affects the integrity of the data transmission link and the timeliness of processing. When the failure rate exceeds the threshold, the interference of node state degradation (such as insufficient remaining computing power or decreased availability of the encryption coprocessor) on the transmission process changes from "occasional fluctuations" to "systemic impacts," ultimately leading to a rapid decline in the transmission success rate. At the parameter correlation level, the graph's baseline thresholds (2.5% failure rate, 95% success rate) can be directly used as the core constraint indicators for "recent node failure rate statistics" in the transmission path dynamic planning module. During path planning, nodes with failure rates below 2.5% should be prioritized to ensure that the transmission success rate meets system compliance requirements. Simultaneously, the fitting results of the quadratic trend line can serve as the quantitative basis for the transmission strategy post-optimization module to correct the "failure rate statistical weight parameters." For example, when actual data deviates from the trend line, the weight ratio of the failure rate indicator in path selection can be adjusted.

[0062] It should be noted that, in this document, relational terms such as "first" and "second" are used only to distinguish one entity or operation from another, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Furthermore, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such process, method, article, or apparatus.

[0063] Although embodiments of the invention have been shown and described, it will be understood by those skilled in the art that various changes, modifications, substitutions and alterations can be made to these embodiments without departing from the principles and spirit of the invention, the scope of which is defined by the appended claims and their equivalents.

Claims

1. A medical insurance data secure transmission system based on data processing, characterized in that, The system includes: The medical insurance data source feature extraction module is used to obtain raw data packets from multiple heterogeneous medical insurance data sources and identify the data attribute tags and security level identifiers of each raw data packet. The transmission path dynamic planning module is used to generate initial security transmission requirements that match each original data packet based on the data attribute tags and security level identifiers of the original data packets, and to plan a preliminary transmission path containing multiple relay nodes for each original data packet by combining real-time network topology and node status. The security encapsulation and policy binding module is used to configure differentiated security encapsulation protocols for each segment of the original data packet based on the security processing capability profile of each relay node in the initial transmission path, and bind the security encapsulation protocol to the original data packet to form a policy-constrained data unit to be transmitted. The distributed execution and state tracking module is used to inject the data unit to be transmitted into its corresponding initial transmission path, and continuously collect the processing logs and performance metrics of each relay node during the transmission process to form a full-link transmission state snapshot. The adaptive storage decision module is used to analyze the full-link transmission status snapshot after the data unit to be transmitted arrives at the preset data aggregation pool, evaluate the integrity and compliance of the transmission process, and trigger the corresponding dynamic storage strategy based on the evaluation results to complete the final data disking.

2. The medical insurance data secure transmission system based on data processing according to claim 1, characterized in that, The generation of initial secure transmission requirements matching each original data packet specifically includes: Parse the data attribute tags of the original data packet. The data attribute tags include the medical insurance business type to which the data belongs, the data sensitivity classification, and the data lifecycle stage. The security level identifier of the raw data packet is read. The security level identifier is generated by the audit records of the data source system and the predefined security rules. The data is matched with the medical insurance business type to which it belongs to a preset business type priority mapping table to obtain the business transmission priority; Input the data sensitivity classification and data lifecycle stage into the security requirements calculation model to output the basic security strength requirements; By integrating service transmission priority and basic security strength requirements, and superimposing the system load factor corresponding to the real-time timestamp, the initial secure transmission requirements are calculated. The initial secure transmission requirements include the minimum encryption strength, the maximum allowable delay, and a list of mandatory verification nodes.

3. The medical insurance data secure transmission system based on data processing according to claim 2, characterized in that, The process of combining real-time network topology and node status to plan a preliminary transmission path containing multiple relay nodes for each original data packet specifically includes: Obtain the node status of all available data processing nodes at the current moment. The node status includes the node's current remaining computing power, the availability of the encryption coprocessor, recent failure rate statistics, and the number of network hops with the data pool. Based on the list of mandatory verification nodes in the initial secure transmission requirements, the fixed nodes that must be passed through are locked in the real-time network topology; Among fixed nodes, a set of candidate nodes that meet the minimum encryption strength requirement is selected based on the current remaining computing power and the availability of encryption coprocessors in the node status. Based on the maximum allowable delay constraint, the estimated total delay of the path formed by different combinations of nodes is calculated in the candidate node set. The estimated total delay is obtained by summing the network delay between nodes and the estimated processing time of each node. The path that satisfies the maximum allowable delay constraint and has the lowest sum of recent failure rates of the nodes along the route is selected as the initial transmission path for the original data packet.

4. The medical insurance data secure transmission system based on data processing according to claim 3, characterized in that, The aforementioned configuration of differentiated security encapsulation protocols for raw data packets segment by segment specifically includes: Retrieve the security processing capability profile of each relay node in the initial transmission path. The security processing capability profile records the list of encryption algorithms supported by the relay node, the type of hardware acceleration engine, and the maximum number of concurrent processing threads. For each transmission segment of the initial transmission path, the security processing capability file of the starting node of the transmission segment is used as the main basis, and the security processing capability file of the ending node of the segment is used as a compatibility reference. From the list of encryption algorithms supported by the starting node, select an algorithm that meets the minimum encryption strength requirement and is compatible with the ending node, and use it as the designated encryption algorithm for the transmission interval. Based on the operational characteristics of the specified encryption algorithm and the hardware acceleration engine type of the starting node, the key derivation function parameters and data block size are dynamically generated. The specified encryption algorithm, key derivation function parameters, and data block size are encapsulated into a secure encapsulation protocol for the transmission interval, and bound to the transmission order identifier of the original data packet in the transmission interval.

5. The medical insurance data secure transmission system based on data processing according to claim 4, characterized in that, The formation of the policy-constrained data unit to be transmitted specifically includes: The original data packet is serialized according to a predefined format, and a path index code is embedded in the header of the serialized data. The path index code points to a unique number of its initial transmission path. Generate an independent protocol instruction set for the security encapsulation protocol of each transmission segment, and assemble all protocol instruction sets into a policy execution script according to the transmission order; The serialized data is signed using the hash value of the policy execution script, and the signature, policy execution script and serialized data are packaged together to generate a data unit to be transmitted. The structure of the data unit to be transmitted is set so that its core serialized data can only be read after the strategy execution script is correctly interpreted and executed by the relay nodes in sequence.

6. The medical insurance data secure transmission system based on data processing according to claim 5, characterized in that, The process of forming a full-link transmission state snapshot specifically includes: When each relay node processes a data unit to be transmitted, the relay node performs operations according to the corresponding protocol instruction set in the bound strategy execution script; After a node completes an operation, it generates a status record, which includes the node's identity identifier, the timestamps of the start and end of the operation, the specific resource metric used, the operation result code, and the next-hop node information. The distributed execution and state tracking module asynchronously collects the state records uploaded by all relay nodes during the transmission process; The status records arranged in chronological order are compared with the theoretical node sequence of the initial transmission path to verify the integrity and correctness of the path execution. All status records, verification results, and the final transmission completion time are integrated into a full-link transmission status snapshot.

7. The medical insurance data secure transmission system based on data processing according to claim 6, characterized in that, The assessment of the integrity and compliance of the transmission process specifically includes: Analyze the entire link transmission status snapshot and extract the operation result code uploaded by each node. Check the operation result code sequence to confirm that each code indicates successful execution and that the number of status records is exactly the same as the number of relay nodes in the initial transmission path; Check the start and end timestamps of each node's operation, calculate the time interval between operations of adjacent nodes, and determine whether all time intervals are less than the preset network timeout threshold; Verify that the specific resource metrics used by each node are within the normal ranges described in its security handling capability profile, and check for any abnormal resource access patterns. Based on the results of the above checks, verifications and validations, a binary assessment conclusion is generated, which is either complete compliance or an anomaly exists.

8. The medical insurance data secure transmission system based on data processing according to claim 7, characterized in that, The triggering of the corresponding dynamic storage strategy to complete the final data write-to-disk process specifically includes: If the binary evaluation conclusion is complete compliance, then the serialized data is parsed from the data unit to be transmitted, and its data attribute tags are read. Based on the medical insurance business type and data sensitivity classification in the data attribute tags, query the storage strategy matrix to obtain the type of target storage medium, the number of redundant data copies, and the data cooling and archiving rules. According to the obtained storage configuration, the serialized data and its end-to-end transmission status snapshot are treated as an indivisible whole and written to the specified target storage medium to complete the final disk write-to-disk process. If the binary assessment concludes that there is an anomaly, the automatic disk write process will be suspended, and the data unit to be transmitted, the full-link transmission status snapshot, and the anomaly details will be marked as isolated data packets and transferred to the security audit queue for manual intervention.

9. The medical insurance data secure transmission system based on data processing according to claim 1, characterized in that, Also includes: The post-transmission strategy optimization module is used to perform backtracking analysis of the historical transmission process to optimize the strategy after the data has been finally written to disk. Specifically, it includes: Periodically extract cases that have completed transmission. Each case includes its initial secure transmission requirements, the planned initial transmission path, and the actual generated full-link transmission status snapshot. By comparing the theoretical performance indicators of the initial transmission path with the actual transmission process in terms of delay and resource consumption, path segments with significant deviations are identified. Analyze the causes of the deviation, correlate the global load logs of the relevant nodes during the transmission process, and determine whether the deviation is caused by occasional performance fluctuations of the nodes or by defects in the path planning logic. Based on the analysis results, the node state evaluation model or path selection weight parameters in the transmission path dynamic planning module are adaptively modified.

10. A method for secure transmission of medical insurance data based on data processing, characterized in that, It includes all modules and method flows of the medical insurance data security transmission system based on data processing as described in any one of claims 1 to 9.

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