A data security transmission method for an EDC system

Abstract

The application relates to the technical field of electronic data collection, in particular to a data security transmission method for an EDC system, which comprises the following steps: performing semantic layering on data packets, and setting target transmission reliability for data of different semantic levels; evaluating network transmission states in real time, dynamically calculating minimum redundancy required for achieving the target transmission reliability, and determining forward error correction coding parameters; performing adaptive forward error correction coding on data of different semantic levels according to the parameters, and performing hierarchical transmission according to priorities; and performing progressive reconstruction at a receiving end, and presenting reconstructed data in real time. Through the technical scheme, appropriate redundancy protection can be accurately calculated and applied according to data value and real-time network quality, reliable transmission of high-value data is ensured, and transmission efficiency is maximally improved in a weak network environment.

Description

Technical Field

[0001] This application relates to the field of electronic data acquisition technology, and in particular to a method for secure data transmission in an EDC system. Background Technology

[0002] As clinical research models evolve towards decentralized clinical trials (DCTs), data collection scenarios have become increasingly complex. In DCTs, participants often use mobile devices to input clinical data in non-traditional research center environments such as homes and community clinics. Network connectivity in these locations is often unstable, with issues like weak signals, high latency, and frequent interruptions. This poses a significant challenge to the transmission of critical clinical data, especially time-sensitive information such as serious adverse events (SAEs). Ensuring that this information is uploaded to the central server in a timely and reliable manner is crucial for protecting participant safety and ensuring research compliance.

[0003] Currently, to address the unavoidable packet loss problem in network transmission, Forward Error Correction (FEC) technology is commonly used. Its basic working principle is to process the original data block using a specific encoding algorithm before sending the data, generating additional redundant data blocks, also known as check blocks. The sending end sends the original data block along with these redundant data blocks. Thus, even if the receiving end only receives a portion of these data blocks due to network issues, as long as the total number received reaches a minimum threshold, it can reconstruct the entire original data through decoding operations.

[0004] However, the fixed redundancy strategy employed by FEC technology cannot adapt to real-time fluctuating network environments. Existing technologies typically pre-define a fixed set of redundancy rules for different types of data. However, when network quality is excellent, such as a packet loss rate of less than 1%, sending a large number of redundant blocks becomes unnecessary bandwidth and mobile device power consumption; conversely, when network quality is extremely poor, this fixed high redundancy strategy may actually be insufficient in its protection capabilities, leading to transmission failures as well. Therefore, existing technologies lack an intelligent mechanism that can dynamically and accurately calculate an appropriate redundancy protection level based on real-time network conditions and the value of the data itself, thereby maximizing transmission efficiency while ensuring reliability. Summary of the Invention

[0005] To address the technical problem that fixed redundancy strategies in existing technologies cannot adapt to dynamic network environments, resulting in low transmission efficiency, this application provides a data security transmission method for EDC systems.

[0006] This application provides a data security transmission method for an EDC system, comprising: semantically layering data packets and setting target transmission reliability for data at different semantic levels; real-time evaluation of network transmission status, and dynamically calculating the minimum total number of data blocks required to achieve the target transmission reliability based on the network transmission status and the target transmission reliability using an optimization algorithm; adaptive forward error correction coding of the data at different semantic levels according to the minimum total number of data blocks, and performing layered transmission according to the priority of the semantic levels; progressively reconstructing the received data blocks at the receiving end, and presenting the reconstructed data in real time according to the priority of the semantic levels, thereby achieving data security transmission in a weak network environment.

[0007] This application can combine the clinical semantic value of data packets with real-time network status to construct a dynamic optimization model, accurately calculate and match appropriate redundancy protection for data of different importance, and achieve efficient utilization of network resources and equipment energy consumption while ensuring the reliability of critical data transmission.

[0008] In one embodiment, the semantic layering of data packets includes dividing fields within high-priority data packets into at least one of a core summary layer, a key context layer, and a detailed description layer, wherein the core summary layer contains the most critical information required to constitute a minimum effective alert.

[0009] By semantically layering the data, the system can identify the core value of the information, enabling limited network resources to be prioritized for ensuring the transmission of the most critical information. This ensures that, in extreme circumstances, staff can at least receive core alerts sufficient to make initial judgments and take action.

[0010] In one embodiment, the real-time assessment of network transmission status specifically involves continuously monitoring the average packet loss rate of the current network before initiating data transmission.

[0011] By monitoring the network packet loss rate in real time, the system can obtain the key input parameters required for dynamic redundancy calculation, ensuring that subsequent optimization calculations are based on the most realistic current network conditions, thereby making the adjustment of redundancy strategies timely and accurate.

[0012] In one embodiment, the minimum total number of data blocks required to achieve the target transmission reliability is dynamically calculated using an optimization algorithm, based on a transmission success rate that satisfies the following relationship: ;in, This indicates that the average packet loss rate is Under the network, send The total data blocks were able to be successfully reconstructed. The probability of each original data block. Let be the combination number, representing the number of combinations from . Select from the total data blocks The number of ways to combine data blocks.

[0013] In one embodiment, the step of dynamically calculating the minimum total number of data blocks required to achieve the target transmission reliability through an optimization algorithm includes: initializing the total number of data blocks n to be equal to the original number of data blocks k; iteratively calculating the transmission success rate corresponding to the current total number of data blocks n; if the calculated transmission success rate is less than the target transmission reliability, then incrementing n by 1 and repeating the iterative calculation steps until the transmission success rate is not less than the target transmission reliability, and taking n at this time as the minimum total number of data blocks.

[0014] By employing an efficient iterative search algorithm, the minimum total number of data blocks that meet the target reliability can be found quickly, avoiding complex exhaustive search and improving computational efficiency while ensuring optimal results.

[0015] In one embodiment, the adaptive forward error correction coding employs Reed-Solomon coding to generate a check block based on the original data block and the minimum total number of data blocks.

[0016] In one embodiment, the hierarchical transmission according to the priority of the semantic level includes: prioritizing the transmission of all core digest layer data blocks; after the core digest layer data blocks have been transmitted, re-evaluating the network transmission status, calculating the minimum total number of data blocks corresponding to the key context layer data, and then transmitting the data.

[0017] In one embodiment, after completing the transmission of data blocks at a higher priority semantic level, the method further includes: re-evaluating the current network transmission status to obtain an updated average packet loss rate; and dynamically calculating a new minimum total number of data blocks for the next priority semantic level based on the updated average packet loss rate.

[0018] In one embodiment, the progressive reconstruction is as follows: when any semantic level receives any k data blocks, the decoder is immediately triggered to reconstruct the complete original data of that level using these k data blocks.

[0019] Through progressive reconstruction and instant presentation, the highest-value information is delivered to users with minimal delay. Staff can obtain key alerts and take action immediately without waiting for the entire report to be transmitted, greatly improving the timeliness of clinical risk response.

[0020] In one embodiment, the instant presentation of the reconstructed data includes: immediately generating and displaying a highlighted alert on the monitoring interface after successfully reconstructing the data at the core summary layer; and subsequently, progressively updating the details of the alert after successfully reconstructing data at other semantic levels.

[0021] The technical solution of this application has the following beneficial technical effects:

[0022] This application constructs a dynamic optimization model by combining the clinical semantic value of data packets with real-time network status. It accurately calculates and matches appropriate redundancy protection for data of different importance, achieving efficient utilization of network resources and equipment energy consumption while ensuring the reliability of critical data transmission.

[0023] Furthermore, by using tiered and prioritized processing, all available resources can be concentrated to ensure the most critical alert information, ensuring that clinical risks are detected in a timely manner. This effectively solves the dilemma that traditional methods may result in the complete loss of critical information due to network problems, providing a solid guarantee for the data integrity and subject safety of decentralized clinical trials. Attached Figure Description

[0024] Figure 1 This is a flowchart of a data security transmission method for an EDC system according to an embodiment of this application.

[0025] Figure 2 This is a schematic diagram comparing the data transmission effect of the data transmission method according to the embodiments of this application and the traditional method in a weak network environment. Detailed Implementation

[0026] The technical solutions in the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, and not all embodiments.

[0027] Figure 1 This is a flowchart illustrating a data security transmission method for an EDC system according to an embodiment of this application. Figure 1 As shown, the data security transmission method for the EDC system includes steps S101 to S104, which are described in detail below.

[0028] S101 performs semantic layering on data packets and sets target transmission reliability for data at different semantic levels.

[0029] In one embodiment, a semantic hierarchy model based on industry standards, such as CDISC SDTM or E2B formats and clinical practices, can be pre-configured. For example, in a high-priority serious adverse event (SAE) report, the system will divide the fields into different semantic levels.

[0030] Specifically, the first layer, L1, serves as the core summary layer. This layer contains the most critical information needed to form a minimal yet sufficient alert for medical monitors to make an initial judgment and take action. For example, the core summary layer of an SAE report might include: subject ID, event term (such as "myocardial infarction"), severity criteria (such as "life-threatening"), and the date of the event.

[0031] The second layer, L2, is the key context layer, which contains information that provides the necessary background for understanding the core summary. Examples may include: combined medication information, determinations of the relationship with the investigational drug, and actions already taken.

[0032] The third layer, L3, is the detailed description layer, which contains all other supplementary details of the report. Examples include a detailed description of the event, laboratory test results, etc.

[0033] In this alternative embodiment, an assessed target transmission reliability is then assigned to each semantic level. This value represents the minimum probability of successful transmission that the data at that level must achieve. The value is set based on clinical risk assessment, and the more critical the level, the higher its reliability target.

[0034] Specifically, the target transmission reliability of the L1 layer core summary can be set to 0.999, representing extremely high reliability requirements to ensure that critical alerts are almost always delivered; the target transmission reliability of the L2 layer critical context can be set to 0.99, representing high reliability requirements; and the target transmission reliability of the L3 layer detailed description can be set to 0.95, representing relatively low reliability requirements, allowing for sacrifices under extreme network conditions.

[0035] In this way, by performing semantic layering and criticality assessment on the data, the system can identify the primary and secondary value of information, providing a basis for decision-making on subsequent differentiated and value-based redundancy protection strategies.

[0036] S102, evaluates the network transmission status in real time, and dynamically calculates the minimum total number of data blocks required to achieve the target transmission reliability based on the network transmission status and the target transmission reliability through an optimization algorithm.

[0037] In one embodiment, the client of the EDC system, exemplarily such as the eCOAApp installed on the subject's mobile phone, continuously monitors the average packet loss rate of the current network before initiating a transmission by sending probe packets or analyzing confirmation information from recent data transmissions. , It is a floating-point number between 0 and 1 that reflects the unreliability of the network link in real time.

[0038] Furthermore, the success of data transmission is a probabilistic event. If n data blocks are sent, the probability of each block successfully arriving is... The probability of successfully receiving at least k data blocks is called the transmission success rate, which satisfies the following relationship:

[0039]

[0040] in, This indicates that the average packet loss rate is Under the network, send The total data blocks were able to be successfully reconstructed. The probability of k original data blocks; k is the minimum number of data blocks required for decoding, which is equal to the number of original data blocks; n is the total number of data blocks sent, including k original blocks and nk redundant blocks; Let be the combination number, representing the number of combinations from . Select from the total data blocks The number of ways to combine data blocks; This represents the probability that i data blocks successfully arrive. This represents the probability of ni data blocks being lost.

[0041] Finally, the minimum redundancy optimization algorithm is executed. The goal of the algorithm is to find the smallest integer n (where n ≥ k) such that the transmission success rate is greater than or equal to the preset target reliability for the first time. Specifically, the total number of data blocks n is initialized to be equal to the original number of data blocks k. Then, the transmission success rate corresponding to the current total number of data blocks n is iteratively calculated. If the calculated transmission success rate is less than the target transmission reliability, n is incremented by 1 and the iterative calculation steps are repeated until the transmission success rate is not less than the target transmission reliability. The n at this point is taken as the minimum total number of data blocks.

[0042] For example, suppose we need to transmit L1 layer core digest data, which is divided into k=2 raw data blocks, and the client estimates the average network packet loss rate to be... =0.6, the target transmission reliability set for L1 layer is 0.999, then: initialize the total number of blocks n=k=2, and then calculate The value is 0.16. Since this is less than 0.999, we let n = 2 + 1 = 3, and continue calculating when n is 3. The result is 0.352, which is also less than 0.999, so the iteration continues until n=19. If the value is approximately 0.99914, which is greater than 0.999, then the current n is the minimum total number of data blocks required to first meet the requirement. This means that in order to successfully transmit 2 original data blocks with a 99.9% probability under a network with a 60% packet loss rate, the system needs to send 19 total data blocks.

[0043] In this way, through real-time optimization calculations, the system can accurately match the most economical and reliable redundancy protection level for data of different values ​​in the current network environment, avoiding the waste of resources and insufficient protection of traditional fixed strategies.

[0044] S103, adaptive forward error correction coding is performed on data at different semantic levels based on the minimum total number of data blocks, and the data is transmitted in layers according to the priority of the semantic level.

[0045] In one embodiment, the system serializes a semantic layer data segment, exemplarily such as the core digest of the L1 layer, and divides it into k similarly sized original data blocks, such as k=2, based on the network's maximum transmission unit size.

[0046] Furthermore, FEC encoding and redundant block generation are performed. The system calls the FEC encoder, for example, the Reed-Solomon encoder. The input is k=2 original data blocks and the target total number of blocks, such as n=19. The encoder will perform matrix operations to generate nk=19-2=17 check blocks, and finally obtain a transmission set containing 19 data blocks.

[0047] Finally, layered and prioritized transmission is implemented. For a complete SAE report, the system prioritizes sending all 19 data blocks of the L1-level core digest. Only after all L1 blocks have been sent will the system reassess the current network state, calculate the optimal n value for the L2-level data, encode and send the L2 blocks, and so on for the L3 level. Ultimately, this achieves adaptive forward error correction coding of data at different semantic levels with the minimum total number of data blocks, and layered transmission according to the priority of the semantic level.

[0048] In this way, by applying the calculation results to encoding and priority transmission, it is ensured that network bandwidth is prioritized for the transmission of the most important information, thus achieving a dynamic match between transmission strategy and data value.

[0049] S104: The receiving end progressively reconstructs the received data block and presents the reconstructed data in real time according to the priority of the semantic level, thereby realizing secure data transmission in a weak network environment.

[0050] In one embodiment, a progressive data reconstruction can be performed on the server at the receiving end to present the most valuable information at the fastest speed, thereby achieving highly reliable and secure data transmission in weak network environments.

[0051] Specifically, the process begins with data block collection and decoding. The server continuously receives data blocks from the client and stores them in the corresponding semantic level, such as the L1 buffer, based on their identifiers. Once any k=2 data blocks have been received in the L1 buffer, regardless of whether they are original blocks or check blocks, the decoder is immediately triggered. The decoder uses these two data blocks to perform decoding operations, which can completely reconstruct the two original data blocks of the L1 layer.

[0052] Furthermore, once the core summary data of Layer L1 is successfully reconstructed, the system immediately generates a highlighted alert on the central monitoring dashboard, with the following content as an example: "SAE Alert: Subject S-007 has experienced 'myocardial infarction', severity 'life-threatening'." At this point, even if the data from Layers L2 and L3 have not yet begun transmission, the most critical clinical risk information has been delivered with minimal delay. Subsequently, as the data blocks from Layers L2 and L3 arrive and are reconstructed, the system will progressively update the details of this alert with this more detailed information, ultimately presenting a complete SAE report on the interface.

[0053] like Figure 2 The diagram shown is a comparison of the data transmission effect of the data transmission method according to the embodiments of this application and the traditional method in a weak network environment. Figure 2 The first part shows that the traditional method treats the entire report, which requires 10 original data blocks, as a whole. Using a fixed high redundancy strategy, a total of 20 data blocks were sent. With a packet loss rate of 60%, only 7 blocks were successfully received. Since the required 10 blocks for reconstruction were not reached, the transmission of the entire report failed. Figure 2 The lower part shows that the method of the present invention extracts only the most critical core digest, so only 2 original data blocks are needed. Then, based on the target of 60% packet loss rate and 99.9% success rate, the minimum number of total data blocks that need to be sent is dynamically calculated. Under the same network environment, 11 of these 19 blocks arrive successfully, far exceeding the 2 blocks required for reconstruction. Therefore, the receiving end can completely restore the most critical information.

[0054] In this way, by enabling rapid and progressive data reconstruction and information presentation at the receiving end, clinical decision-makers are ensured to obtain the most valuable information in the first instance, which greatly shortens the response time for critical events.

[0055] It should be noted that those skilled in the art can make various modifications and improvements without departing from the concept of this application, and these all fall within the scope of protection of this application. Therefore, the scope of protection of this patent application shall be determined by the appended claims.

Claims

1. A method for secure data transmission in an EDC system, characterized in that, include: Semantic layering of data packets and setting target transmission reliability for data at different semantic levels. Semantic layering of data packets includes dividing the fields in high-priority data packets into at least one of a core summary layer, a key context layer, and a detailed description layer, wherein the core summary layer contains the most critical information required to constitute a minimum effective alarm. The network transmission status is evaluated in real time, and based on the network transmission status and target transmission reliability, the minimum total number of data blocks required to achieve the target transmission reliability is dynamically calculated through an optimization algorithm. The transmission success rate is based on the following relationship: ,in, This indicates that the average packet loss rate is Under the network, send The total data blocks can be successfully reconstructed. The probability of each original data block Let be the combination number, representing the number of combinations from . Select from the total data blocks The number of ways to combine data blocks; Adaptive forward error correction coding is performed on data at different semantic levels based on the minimum total number of data blocks, and the data is transmitted in layers according to the priority of the semantic level, including: sending all core summary layer data blocks first; after the core summary layer data blocks have been sent, the network transmission status is reassessed, and the minimum total number of data blocks corresponding to the key context layer data is calculated before sending; the detailed description layer is transmitted in the same manner. The receiving end progressively reconstructs the received data blocks and presents the reconstructed data in real time according to the priority of the semantic hierarchy, thereby achieving secure data transmission in weak network environments. The algorithm dynamically calculates the minimum total number of data blocks required to achieve the target transmission reliability, including: initializing the total number of data blocks n to equal the original number of data blocks k; iteratively calculating the transmission success rate corresponding to the current total number of data blocks n; if the calculated transmission success rate is less than the target transmission reliability, then n is incremented by 1 and the iterative calculation steps are repeated until the transmission success rate is not less than the target transmission reliability, and n at this time is taken as the minimum total number of data blocks.

2. The data security transmission method for an EDC system according to claim 1, characterized in that, The real-time assessment of network transmission status specifically involves continuously monitoring the average packet loss rate of the current network before initiating data transmission.

3. The data security transmission method for an EDC system according to claim 1, characterized in that, The adaptive forward error correction coding uses Reed-Solomon coding to generate a check block based on the original data block and the minimum total number of data blocks.

4. The data security transmission method for an EDC system according to claim 1, characterized in that, After completing the transmission of data blocks at higher priority semantic levels, the following is also included: Reassess the current network transmission status to obtain an updated average packet loss rate; Based on the updated average packet loss rate, a new minimum total number of data blocks is dynamically calculated for the data at the next priority semantic level.

5. A data security transmission method for an EDC system according to claim 1, characterized in that, The progressive reconstruction is as follows: when any semantic level receives any k data blocks, the decoder is immediately triggered, and the complete original data of that level is reconstructed using these k data blocks.

6. A data security transmission method for an EDC system according to claim 1, characterized in that, The instant presentation of reconstructed data includes: After successfully reconstructing the core summary layer data, a highlighted alert is immediately generated and displayed on the monitoring interface; and subsequently, after successfully reconstructing data at other semantic levels, the detailed information of the alert is progressively updated.

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