Clinical test electronic file safety management system and method
By encrypting clinical trial electronic records, implementing role-based access control, cloud backup, and deep learning model detection, combined with blockchain storage, the security issues of existing systems are addressed, enabling secure data management and regulatory compliance.
Patent Information
- Application Number
- CN202510988809.8
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2025-07-17
- Publication Date
- 2025-10-28
AI Technical Summary
The existing clinical trial electronic record management system has deficiencies in security. Data is easily illegally accessed, tampered with or leaked. It lacks an effective audit tracking mechanism and is unable to meet increasingly stringent regulatory requirements.
A symmetric encryption algorithm is used to encrypt clinical trial electronic files, and user permissions are managed through a role-based access control model. The audit log module is used to record access behavior, and cloud backup is used for regular backup. A deep learning model is used to detect network intrusion behavior, and audit logs are stored on the blockchain. The Shamir threshold key sharing algorithm is used to split and store encryption keys to ensure data security and integrity.
It effectively ensures the data security and integrity of clinical trial electronic files, meets regulatory requirements, prevents data loss and unauthorized access, and provides multi-level security protection.
Smart Images
Figure CN120853784A_ABST
Abstract
Description
Technical Field
[0001] This invention belongs to the field of data security technology, specifically relating to a secure management system and method for electronic records of clinical trials. Background Technology
[0002] Clinical trial data is a crucial foundation for evaluating the safety and efficacy of new drugs, treatments, and medical devices. This data is collected throughout all phases of clinical trials, from trial design to outcome analysis, and must strictly adhere to regulations and quality management standards. Data types include raw records, case report forms, and medical images, typically collected and managed electronically to ensure data authenticity, integrity, and traceability. The application of modern technologies (such as electronic data capture systems) has significantly improved the efficiency and accuracy of data management. In short, clinical trial data is central to driving medical innovation and ensuring patient safety. With the development of information technology, the electronic management of clinical trial data has become a trend. However, existing electronic record management systems have many shortcomings in terms of security, such as vulnerability to unauthorized access, tampering, or leakage of data, a lack of effective audit trail mechanisms, and difficulty in meeting increasingly stringent regulatory requirements. Therefore, a secure and reliable electronic record management system is urgently needed to ensure the security and integrity of clinical trial data. Summary of the Invention
[0003] This invention provides a secure management system and method for electronic clinical trial records, which addresses the shortcomings of existing technologies in the security performance of electronic clinical trial record management.
[0004] On one hand, the present invention provides a secure management system for electronic clinical trial records, comprising:
[0005] The data encryption module is used to encrypt the electronic records of clinical trials using a symmetric encryption algorithm, and to obtain the encrypted electronic records of clinical trials.
[0006] The access control module is used to control user roles and permissions using a role-based access control model, allowing users to access encrypted electronic records of clinical trials only within their authorized access permissions.
[0007] The audit log module is used to record user access behavior to the encrypted electronic records of clinical trials; wherein, the access behavior includes access time, operation type and visitor information;
[0008] The data backup and recovery module is used to periodically back up encrypted electronic records of clinical trials using cloud backup methods;
[0009] The intrusion detection module is used to detect real-time network traffic using a deep learning model, identify network intrusion behaviors, and perform secure management of encrypted electronic records of clinical trials based on the network intrusion behaviors.
[0010] Furthermore, after obtaining the encrypted electronic clinical trial records, the process also includes: using the Shamir threshold key sharing algorithm to segment and store the encryption key to ensure the security of the encrypted electronic clinical trial records.
[0011] Furthermore, it also includes:
[0012] Blockchain is used to store the access behavior recorded by the audit log module, forming tamper-proof traceability data.
[0013] Furthermore, the audit log module records user access behavior to the encrypted electronic clinical trial files, which is then stored on a separate log server for security auditing and tracking.
[0014] Furthermore, the data backup and recovery module includes: a first data processing submodule, a second data processing submodule, a verification submodule, and an incremental backup submodule;
[0015] The first data processing submodule is used to divide the encrypted electronic records of clinical trials into blocks and number them when the backup cycle arrives, and to determine the first MD5 checksum corresponding to each block.
[0016] The second data processing submodule is used to divide and number the backed-up data of the encrypted clinical trial electronic file in the same way as the encrypted clinical trial electronic file, and determine the second MD5 checksum corresponding to each block.
[0017] The verification submodule is used to compare the first MD5 checksum with the second MD5 checksum using a Bloom filter, thereby determining the difference blocks between the encrypted clinical trial electronic records and the backed-up data.
[0018] The incremental backup submodule is used to replace the corresponding data block in the backed-up data of the encrypted clinical trial electronic file with the content corresponding to the difference block, thereby completing the incremental update.
[0019] The encrypted electronic records of clinical trials are stored on a different physical server than their corresponding backed-up data.
[0020] Furthermore, the encrypted electronic records of clinical trials are divided into blocks, including:
[0021] A1. Set a fixed-length window T, and determine the maximum and minimum values in the fixed-length window T;
[0022] A2. Set a sliding window H after the fixed-length window T. Starting from the first byte of the sliding window H, compare it with the maximum and minimum values in the fixed-length window T. If it is greater than the maximum value or less than the minimum value, then the position of the sliding window H is taken as a cut point and a data block is obtained; otherwise, the sliding window slides to the next byte until a cut point is found.
[0023] The position of the sliding window H represents the last byte of the sliding window, and the data block includes all bytes in the current sliding window.
[0024] A3. For each data block, use the location of the data block as a new fixed-length window T, and return to step A2 until the data block is divided.
[0025] Furthermore, the intrusion detection module includes a deep learning submodule, a network intrusion detection submodule, and a security management submodule;
[0026] The deep learning submodule is used to deploy a network intrusion detection model using a deep learning model;
[0027] The network intrusion detection submodule is used to schedule the network intrusion detection model deployed by the deep learning submodule to detect real-time network traffic and identify network intrusion behaviors; wherein, the network intrusion behaviors include the current user intruding into the network or the current user accessing the network normally;
[0028] The security management submodule is used to perform security management on the encrypted electronic records of clinical trials based on the network intrusion behavior.
[0029] Furthermore, network intrusion detection models are deployed using deep learning models, including: deploying network intrusion detection models using CNN-BP neural network models.
[0030] Furthermore, based on the aforementioned network intrusion behavior, the encrypted electronic records of clinical trials are securely managed, including:
[0031] When the network intrusion behavior corresponding to a user includes the user currently intruding into the network, the user will be denied access. The more times a user is identified as intruding into the network, the longer the access will be denied.
[0032] On the other hand, the present invention provides a method for secure management of electronic clinical trial records, comprising:
[0033] The data encryption module uses a symmetric encryption algorithm to encrypt the electronic records of clinical trials, and then obtains the encrypted electronic records of clinical trials.
[0034] The encrypted electronic records of clinical trials are backed up regularly using cloud backup via the data backup and recovery module.
[0035] The access control module employs a role-based access control model to control user roles and permissions, allowing users to access encrypted clinical trial electronic files only within their authorized access limits. During the access process, access is prioritized to the encrypted clinical trial electronic files; if access fails, the backup data of the encrypted clinical trial electronic files is then accessed.
[0036] During access to the encrypted electronic clinical trial records, the user's access behavior to the encrypted electronic clinical trial records is recorded through the audit log module; wherein, the access behavior includes access time, operation type and visitor information;
[0037] During access to the encrypted electronic records of clinical trials, the intrusion detection module uses a deep learning model to detect real-time network traffic, identify network intrusion behaviors, and perform security management on the encrypted electronic records based on the network intrusion behaviors.
[0038] This invention provides a secure management system and method for electronic clinical trial records. By employing a symmetric encryption algorithm to encrypt electronic clinical trial records, the system effectively ensures data security. A role-based access control model is then used to control user roles and permissions, allowing users to access the encrypted records only within their authorized access limits, further enhancing security. User access behavior is recorded for traceability. Cloud backup is then used to periodically back up the encrypted records, preventing data loss. Finally, a deep learning model is employed to detect real-time network traffic, identify network intrusion behaviors, and manage the encrypted records securely based on these intrusions, enabling secure control over the access process. Attached Figure Description
[0039] The accompanying drawings, which are incorporated in and form part of this specification, illustrate embodiments consistent with the invention and, together with the description, serve to explain the principles of the invention.
[0040] Figure 1 This is a schematic diagram of the structure of a secure electronic record management system for clinical trials provided in an embodiment of the present invention.
[0041] Figure 2 A flowchart illustrating a method for secure management of electronic clinical trial records provided in an embodiment of the present invention.
[0042] Among them, 101-data encryption module, 102-access control module, 103-audit log module, 104-data backup and recovery module, and 105-intrusion detection module.
[0043] The accompanying drawings have illustrated specific embodiments of the invention, which will be described in more detail below. These drawings and descriptions are not intended to limit the scope of the invention in any way, but rather to illustrate the concept of the invention to those skilled in the art through reference to particular embodiments. Detailed Implementation
[0044] Exemplary embodiments will now be described in detail, examples of which are illustrated in the accompanying drawings. When the following description relates to the drawings, unless otherwise indicated, the same numerals in different drawings denote the same or similar elements. The embodiments described in the following exemplary embodiments do not represent all embodiments consistent with the present invention. Rather, they are merely examples of apparatuses and methods consistent with some aspects of the invention as detailed in the appended claims.
[0045] The embodiments of the present invention will now be described in detail with reference to the accompanying drawings.
[0046] like Figure 1 As shown, an embodiment of the present invention provides a secure management system for electronic clinical trial records, comprising:
[0047] The data encryption module 101 is used to encrypt the electronic records of clinical trials using a symmetric encryption algorithm, and to obtain the encrypted electronic records of clinical trials.
[0048] For example, the AES (Advanced Encryption Standard) algorithm can be used to encrypt electronic clinical trial records, thereby achieving rapid encryption of electronic clinical trial records and improving data security.
[0049] Access control module 102 is used to control user roles and permissions using a role-based access control model, allowing users to access encrypted electronic clinical trial records only within their authorized access permissions.
[0050] Role-based access control (RBAC) is an efficient user access management method that enables fine-grained management of system resources and data by assigning users to different roles and defining corresponding permissions for each role. RBAC is particularly important in the security management system of electronic clinical trial records (eTMF).
[0051] The core lies in the definition of roles and the allocation of permissions. For example, the system administrator has the highest privileges and can manage users and assign roles; the data administrator is responsible for maintaining files; the reviewer can only view and review data; and ordinary users have limited permissions. Users are granted corresponding operation permissions according to their roles, such as creating, reading, updating, or deleting files.
[0052] The advantages of RBAC lie in simplifying access control and improving security. By centrally controlling roles and permissions, it avoids the complexity of directly assigning permissions to each user, reducing the risk of accidental operations. At the same time, clear permission divisions ensure data security and compliance; only authorized users can access sensitive information. The RBAC model makes the eTMF security management system more secure, efficient, and easy to manage, guaranteeing the integrity and reliability of clinical trial data.
[0053] The audit log module 103 is used to record user access behavior to the encrypted electronic records of clinical trials; wherein, the access behavior includes access time, operation type and visitor information;
[0054] The above-described access behavior is merely a preferred embodiment of the present invention. In the electronic clinical trial record (eTMF) security management system, recording user access behavior to the encrypted records is crucial, not only for security reasons but also to meet compliance requirements. Recording user access behavior can include the following key aspects:
[0055] User authentication: Before a user accesses the eTMF security management system, the system should verify the user's identity to ensure that only authorized users can access it.
[0056] Access timestamp: The system should record the time of each access, including the date and time, for auditing and tracking purposes.
[0057] Access type: Records the type of access a user makes to a file, such as viewing, downloading, modifying, or deleting.
[0058] Access content: Records the specific file content accessed by the user, including the file name, number, or other identifiers.
[0059] Session Management: Records user session information, including login time, logout time, and session duration.
[0060] Anomaly detection: The system should be able to detect and record abnormal access behavior, such as multiple failed login attempts or abnormal access times.
[0061] Audit logs: All access activities should be recorded in the audit logs to facilitate subsequent audits and compliance checks.
[0062] Encryption key management: Records the usage of encryption keys, including key generation, distribution, updating, and destruction.
[0063] User roles and permissions: Record user roles and permissions so that when an access action occurs, it can be quickly determined whether the user has the right to perform that action.
[0064] Data integrity check: After a user accesses an encrypted file, the system should perform a data integrity check to ensure that the file has not been tampered with.
[0065] By recording these access behaviors, the eTMF security management system can ensure the confidentiality, integrity, and availability of data.
[0066] The data backup and recovery module 104 is used to periodically back up the encrypted electronic records of clinical trials using cloud backup.
[0067] Regularly backing up encrypted electronic clinical trial records using cloud backup is a crucial measure. It effectively ensures data security and integrity, preventing data loss due to hardware failure, human error, or natural disasters. Cloud backup provides convenient data recovery capabilities, ensuring rapid restoration of critical data in emergencies and minimizing impact on clinical trial progress.
[0068] In addition, cloud backup offers advantages such as cost-effectiveness, scalability, and ease of management. By selecting a reliable cloud service provider and implementing strict access control and encryption policies, data security and compliance can be further ensured. Regular backup and recovery tests help verify the effectiveness of backup data and enhance the reliability of disaster recovery plans.
[0069] In conclusion, regularly backing up encrypted electronic records of clinical trials using methods such as cloud backup is the best practice to ensure data security, maintain trial continuity, and comply with regulatory requirements.
[0070] It is worth noting that, under normal circumstances, the electronic clinical trial record security management system is deployed locally. When changes occur to the electronic clinical trial record, the encrypted version of the electronic clinical trial record should be updated and then backed up to ensure the timeliness and security of the electronic clinical trial record.
[0071] The intrusion detection module 105 is used to detect real-time network traffic using a deep learning model, identify network intrusion behaviors, and perform secure management of encrypted electronic records of clinical trials based on the network intrusion behaviors.
[0072] Using deep learning models to detect real-time network traffic is an advanced security technology for identifying network intrusions. This model analyzes network traffic patterns and anomalies to detect potential attacks in real time, such as malware and hacking. Once a network intrusion is detected, the system automatically triggers security mechanisms to protect the encrypted electronic records of clinical trials.
[0073] This security management approach includes restricting access, enhancing encryption measures, and initiating audits and alerts. Real-time monitoring through deep learning models effectively prevents unauthorized access and data breaches, ensuring the security and integrity of electronic clinical trial records. This method combines artificial intelligence and encryption technology to provide multi-layered security for sensitive data.
[0074] In one possible implementation, after obtaining the encrypted electronic clinical trial record, the method further includes: using the Shamir threshold key sharing algorithm to segment and store the encryption key to ensure the security of the encrypted electronic clinical trial record.
[0075] The Shamir threshold key-sharing algorithm is employed to divide the encryption key into multiple shares, which are stored in different locations. This approach ensures that even if some shares are lost or leaked, the original key cannot be recovered, thus effectively protecting the security of the encrypted electronic clinical trial records. Only when a sufficient number of shares are collected can the key be reconstructed, enabling decryption of the records. This algorithm provides robust security for electronic records, preventing unauthorized access and data leakage.
[0076] In one possible implementation, it also includes:
[0077] Blockchain is used to store access behaviors recorded by the audit log module, forming tamper-proof traceability data.
[0078] Blockchain technology, with its immutability and transparency, provides reliable protection for the storage of access behavior in audit log modules. Utilizing cryptographic hash functions and consensus mechanisms, blockchain ensures that records, once generated, cannot be modified or deleted, forming immutable traceable data. Simultaneously, decentralized storage avoids the risk of single points of failure, enhancing data security. In clinical trial electronic records, blockchain-recorded access behaviors (such as user logins and file modifications) provide authentic, complete, and traceable evidence for auditing and compliance checks, thereby improving the overall credibility and security of the electronic records.
[0079] In one possible implementation, the audit log module stores user access behavior to the encrypted electronic clinical trial records on a separate log server for security auditing and tracking.
[0080] In the electronic clinical trial record security management system, storing user access behavior recorded by the audit log module on a separate log server is a critical security measure. This approach effectively enhances data security and traceability, facilitating security auditing and incident tracking. The advantage of a separate log server lies in its isolation; even if the main system of the electronic clinical trial record security management system is attacked or malfunctions, the log data remains secure and intact. By centrally managing and analyzing log data, the security team can promptly detect abnormal behavior and take appropriate measures to ensure the security of electronic clinical trial records.
[0081] In one possible implementation, the data backup and recovery module includes: a first data processing submodule, a second data processing submodule, a verification submodule, and an incremental backup submodule;
[0082] The first data processing submodule is used to divide the encrypted electronic records of clinical trials into blocks and number them when the backup cycle arrives, and to determine the first MD5 checksum corresponding to each block.
[0083] The second data processing submodule is used to divide and number the backed-up data of the encrypted clinical trial electronic file in the same way as the encrypted clinical trial electronic file, and determine the second MD5 checksum corresponding to each block.
[0084] The verification submodule is used to compare the first MD5 checksum with the second MD5 checksum using a Bloom filter, thereby determining the difference blocks between the encrypted clinical trial electronic records and the backed-up data.
[0085] The incremental backup submodule is used to replace the corresponding data block in the backed-up data of the encrypted clinical trial electronic file with the content corresponding to the difference block, thereby completing the incremental update.
[0086] The encrypted electronic records of clinical trials are stored on a different physical server than their corresponding backed-up data.
[0087] The incremental update method provided in this invention can effectively improve data security and data loss prevention, and can reduce the consumption of computer resources during the backup process, thereby improving backup efficiency.
[0088] In one possible implementation, the encrypted electronic clinical trial records are divided into blocks, including:
[0089] A1. Set a fixed-length window T, and determine the maximum and minimum values in the fixed-length window T;
[0090] A2. Set a sliding window H after the fixed-length window T. Starting from the first byte of the sliding window H, compare it with the maximum and minimum values in the fixed-length window T. If it is greater than the maximum value or less than the minimum value, then the position of the sliding window H is taken as a cut point and a data block is obtained; otherwise, the sliding window slides to the next byte until a cut point is found.
[0091] The position of the sliding window H represents the last byte of the sliding window, and the data block includes all bytes in the current sliding window.
[0092] A3. For each data block, use the location of the data block as a new fixed-length window T, and return to step A2 until the data block is divided.
[0093] The block segmentation method provided in this embodiment of the invention can effectively avoid the problems of block failure or excessively long block data, thereby ensuring that incremental updates are fast and normal.
[0094] In one possible implementation, the intrusion detection module includes a deep learning submodule, a network intrusion detection submodule, and a security management submodule;
[0095] The deep learning submodule is used to deploy a network intrusion detection model using a deep learning model;
[0096] The network intrusion detection submodule is used to schedule the network intrusion detection model deployed by the deep learning submodule to detect real-time network traffic and identify network intrusion behaviors; wherein, the network intrusion behaviors include the current user intruding into the network or the current user accessing the network normally;
[0097] The security management submodule is used to perform security management on the encrypted electronic records of clinical trials based on the network intrusion behavior.
[0098] In one possible implementation, a network intrusion detection model is deployed using a deep learning model, including: deploying a network intrusion detection model using a CNN-BP (Convolutional Neural Network-Backpropagation) neural network model.
[0099] In one possible implementation, the secure management of encrypted electronic clinical trial records based on the network intrusion behavior includes:
[0100] When the network intrusion behavior corresponding to a user includes the user currently intruding into the network, the user will be denied access. The more times a user is identified as intruding into the network, the longer the access will be denied.
[0101] The intrusion detection module provided in this embodiment of the invention can effectively improve the security of the clinical trial electronic record security management system during the access process, and comprehensively enhance the data protection security capabilities.
[0102] This invention provides a secure management system for electronic clinical trial records. It employs a symmetric encryption algorithm to encrypt electronic clinical trial records, effectively ensuring data security. A role-based access control model controls user roles and permissions, allowing access only to the encrypted records within authorized limits, further enhancing security. The system also records user access behavior for traceability. Furthermore, it uses cloud backup to periodically back up the encrypted records, preventing data loss. Finally, a deep learning model detects real-time network traffic, identifies network intrusion attempts, and manages the encrypted records securely based on these intrusions, enabling secure control over the access process.
[0103] like Figure 2 As shown, this embodiment of the invention provides a method for secure management of electronic clinical trial records, including:
[0104] S201. The electronic records of clinical trials are encrypted using a symmetric encryption algorithm through the data encryption module, and the encrypted electronic records of clinical trials are obtained.
[0105] S202. The encrypted electronic records of clinical trials are backed up regularly using cloud backup via the data backup and recovery module;
[0106] S203. The access control module uses a role-based access control model to control the user's role and permissions, allowing users to access the encrypted electronic clinical trial records only within their access permissions. During the access process, the encrypted electronic clinical trial records are accessed first. If the access fails, the backed-up data of the encrypted electronic clinical trial records is accessed.
[0107] S204. During the access process of the encrypted electronic clinical trial records, the user's access behavior to the encrypted electronic clinical trial records is recorded through the audit log module; wherein, the access behavior includes access time, operation type and visitor information;
[0108] S205. During the access process of the encrypted electronic clinical trial records, the intrusion detection module uses a deep learning model to detect real-time network traffic, identify network intrusion behaviors, and perform security management of the encrypted electronic clinical trial records based on the network intrusion behaviors.
[0109] The clinical trial electronic record security management method provided in this embodiment of the invention is applied to the above system technical solution. Its principle and beneficial effects are similar, and will not be described again here.
[0110] Those skilled in the art will understand that embodiments of this application can be provided as methods, systems, or computer program products. Therefore, this application can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, this application can take the form of a computer program product embodied on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.
[0111] This application is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of this application. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, generate instructions for implementing the flowchart... Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.
[0112] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing device to function in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process Figure 1 One or more processes and / or boxes Figure 1 The function specified in one or more boxes.
[0113] These computer program instructions may also be loaded onto a computer or other programmable data processing equipment to cause a series of operational steps to be performed on the computer or other programmable equipment to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable equipment for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 A step that specifies a function in one or more boxes.
[0114] Those skilled in the art will understand that all or part of the steps in the above facts and methods can be implemented by a program instructing related hardware. The program or the program described therein can be stored in a computer-readable storage medium. When the program is executed, it includes the following steps: at this time, the corresponding method steps are introduced. The storage medium can be ROM / RAM, magnetic disk, optical disk, etc.
[0115] The specific embodiments described above further illustrate the purpose, technical solution, and beneficial effects of the present invention. It should be understood that the above description is only a specific embodiment of the present invention and is not intended to limit the scope of protection of the present invention. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the scope of protection of the present invention.
Claims
1. A secure management system for electronic clinical trial records, characterized in that, include: The data encryption module is used to encrypt the electronic records of clinical trials using a symmetric encryption algorithm, and to obtain the encrypted electronic records of clinical trials. The access control module is used to control user roles and permissions using a role-based access control model, allowing users to access encrypted electronic records of clinical trials only within their authorized access permissions. The audit log module is used to record user access behavior to the encrypted electronic records of clinical trials; wherein, the access behavior includes access time, operation type and visitor information; The data backup and recovery module is used to periodically back up encrypted electronic records of clinical trials using cloud backup methods; The intrusion detection module is used to detect real-time network traffic using a deep learning model, identify network intrusion behaviors, and perform secure management of encrypted electronic records of clinical trials based on the network intrusion behaviors.
2. The clinical trial electronic record security management system according to claim 1, characterized in that, After obtaining the encrypted electronic clinical trial records, the process also includes: using the Shamir threshold key sharing algorithm to segment and store the encryption key to ensure the security of the encrypted electronic clinical trial records.
3. The clinical trial electronic record security management system according to claim 1, characterized in that, Also includes: Blockchain is used to store access behaviors recorded by the audit log module, forming tamper-proof traceability data.
4. The clinical trial electronic record security management system according to claim 1, characterized in that, The audit log module records user access behavior to the encrypted electronic clinical trial files, which is then stored on a separate log server for security auditing and tracking.
5. The clinical trial electronic record security management system according to claim 1, characterized in that, The data backup and recovery module includes: a first data processing submodule, a second data processing submodule, a verification submodule, and an incremental backup submodule; The first data processing submodule is used to divide the encrypted electronic records of clinical trials into blocks and number them when the backup cycle arrives, and to determine the first MD5 checksum corresponding to each block. The second data processing submodule is used to divide and number the backed-up data of the encrypted clinical trial electronic file in the same way as the encrypted clinical trial electronic file, and determine the second MD5 checksum corresponding to each block. The verification submodule is used to compare the first MD5 checksum with the second MD5 checksum using a Bloom filter, thereby determining the difference blocks between the encrypted clinical trial electronic records and the backed-up data. The incremental backup submodule is used to replace the corresponding data block in the backed-up data of the encrypted clinical trial electronic file with the content corresponding to the difference block, thereby completing the incremental update. The encrypted electronic records of clinical trials are stored on a different physical server than their corresponding backed-up data.
6. The clinical trial electronic record security management system according to claim 5, characterized in that, The encrypted electronic records of clinical trials are divided into blocks, including: A1. Set a fixed-length window T, and determine the maximum and minimum values in the fixed-length window T; A2. Set a sliding window H after the fixed-length window T. Starting from the first byte of the sliding window H, compare it with the maximum and minimum values in the fixed-length window T. If it is greater than the maximum value or less than the minimum value, then the position of the sliding window H is taken as a cut point and a data block is obtained; otherwise, the sliding window slides to the next byte until a cut point is found. The position of the sliding window H represents the last byte of the sliding window, and the data block includes all bytes in the current sliding window. A3. For each data block, use the location of the data block as a new fixed-length window T, and return to step A2 until the data block is divided.
7. The clinical trial electronic record security management system according to claim 6, characterized in that, The intrusion detection module includes a deep learning submodule, a network intrusion detection submodule, and a security management submodule; The deep learning submodule is used to deploy a network intrusion detection model using a deep learning model; The network intrusion detection submodule is used to schedule the network intrusion detection model deployed by the deep learning submodule to detect real-time network traffic and identify network intrusion behaviors; wherein, the network intrusion behaviors include the current user intruding into the network or the current user accessing the network normally; The security management submodule is used to perform security management on the encrypted electronic records of clinical trials based on the network intrusion behavior.
8. The clinical trial electronic record security management system according to claim 7, characterized in that, Deploying network intrusion detection models using deep learning models includes: deploying network intrusion detection models using CNN-BP neural network models.
9. The clinical trial electronic record security management system according to claim 8, characterized in that, Based on the aforementioned network intrusion behavior, secure management of encrypted electronic clinical trial records is implemented, including: When the network intrusion behavior corresponding to a user includes the user currently intruding into the network, the user will be denied access. The more times a user is identified as intruding into the network, the longer the access will be denied.
10. A method for secure management of electronic clinical trial records, characterized in that, include: The data encryption module uses a symmetric encryption algorithm to encrypt the electronic records of clinical trials, and then obtains the encrypted electronic records of clinical trials. The encrypted electronic records of clinical trials are backed up regularly using cloud backup via the data backup and recovery module. The access control module employs a role-based access control model to control user roles and permissions, allowing users to access encrypted clinical trial electronic files only within their authorized access limits. During the access process, access is prioritized to the encrypted clinical trial electronic files; if access fails, the backup data of the encrypted clinical trial electronic files is then accessed. During access to the encrypted electronic clinical trial records, the user's access behavior to the encrypted electronic clinical trial records is recorded through the audit log module; wherein, the access behavior includes access time, operation type and visitor information; During access to the encrypted electronic records of clinical trials, the intrusion detection module uses a deep learning model to detect real-time network traffic, identify network intrusion behaviors, and perform security management on the encrypted electronic records based on the network intrusion behaviors.