Electronic archive data security system and method

Abstract

The invention discloses an electronic archive data security system and method, and relates to the technical field of electronic document management. The electronic archive data preservation method comprises the following steps: acquiring a plurality of storage files to be stored and file attribute data of each storage file in real time; analyzing the risk level value of each storage file according to the file attribute data of the storage files, and marking the risk level value; classifying and storing the plurality of marked storage files into an electronic archive database; after a plurality of storage files are stored in a classified mode, time period access data of each storage file are obtained in real time, and real-time analysis is carried out in combination with risk level values. File attribute data are obtained in real time, and risk level evaluation is carried out on the file attribute data, so that the files can be marked and stored in a classified mode in real time; according to the method, the high-risk file is ensured to accept stricter protection measures, the risk assessment index is updated in real time, and the encryption strength is dynamically adjusted according to the risk assessment index, so that the protection capability on sensitive information is remarkably improved.

Description

Technical Field

[0001] The present invention relates to the technical field of electronic document management, and in particular to an electronic archive data preservation system and method. Background Art

[0002] As an important form of data storage and management in modern society, the security, integrity and accessibility of electronic archives directly affect the long-term validity and credibility of data. Therefore, with the continuous development of information technology, the research on electronic archive preservation technology has become increasingly important.

[0003] At present, many electronic archive management systems mainly rely on basic file storage and backup technologies. These systems often do not conduct in-depth analysis and processing of the actual risks of stored files, and the following problems are common:

[0004] Static storage: Most existing systems only provide static storage and lack a real-time assessment mechanism for file risk changes. After files are stored, it is usually difficult to adjust security policies based on their usage, access frequency, and sensitivity.

[0005] Insufficient encryption strategy: Although many systems support file encryption, they often adopt a single encryption strategy and fail to dynamically adjust the encryption strength according to the importance or risk level of the file. This results in some sensitive files not being adequately protected, while low-risk files may be over-encrypted, wasting system resources.

[0006] Lack of real-time monitoring: Existing systems rarely monitor and analyze file access behaviors in real time, making it difficult to effectively identify abnormal access behaviors or potential security threats, and difficult to implement active defense.

[0007] Inadequate secure transmission mechanism: During file migration and data transmission, many systems lack an encrypted transmission mechanism, increasing the risk of data being intercepted or tampered with during transmission.

[0008] Prior art, such as the electronic archive data preservation system and method disclosed in the invention patent application with announcement number: CN110795766A, wherein the system includes an archive data receiving module, an archive data storage module, an archive data utilization module and an archive data exit module. The archive data receiving module performs data preprocessing, data verification and data reception process records on the archive data to be stored; the archive data storage module monitors the data status of the archive data to be stored in real time according to the preset independent detection and classification rules, and performs autonomous repair and preservation of the archive data to be stored in accordance with the full timeline status of the data; the archive data utilization module provides the required archive data to be stored in the warehouse for authorized users, and stores the corresponding data utilization records; the archive data exit module is used to automatically execute the exit procedure of the archive data when the verification license file is correct and the party requesting the archive data to be released is the authorized user; thereby effectively ensuring the security, integrity, authenticity and availability of the electronic archive data content.

[0009] Based on the above solution, it is found that the limitations of the existing technology include at least the following problems. First, in the existing electronic archive data preservation system, it is often limited to only basic attribute recording and static classification of files when storing files, and fails to conduct in-depth analysis of the actual usage scenarios and access modes of the files. As a result, even if the file storage environment technically meets the basic security requirements, in actual operations, there may still be security loopholes in the actual use of the files due to the lack of real-time monitoring and risk assessment of access modes. Secondly, traditional methods often adopt consistent security strategies in file encryption processing, ignoring the need to adjust the encryption strength based on the actual risk level of the file, which easily leads to a waste of resources. It is particularly not conducive to improving efficiency when processing large amounts of data. At the same time, high-risk files do not receive the key protection they deserve, thus affecting the security of the overall system. Summary of the invention

[0010] In view of the deficiencies in the prior art, the present invention provides an electronic archive data preservation system and method, which solves the problem that in the existing electronic archive data preservation system, the system is often limited to only basic attribute recording and static classification of files when storing files, and fails to conduct in-depth analysis of the actual usage scenarios and access modes of the files, which may easily lead to security loopholes in the actual use of files even if the file storage environment technically meets the basic security requirements, due to the lack of real-time monitoring and risk assessment of access modes in actual operations. Secondly, traditional methods often adopt a consistent security strategy in file encryption processing, ignoring the need to adjust the encryption strength based on the actual risk level of the file, which may easily cause a waste of resources, which is particularly not conducive to improving efficiency when processing large amounts of data. At the same time, high-risk files cannot receive the key protection they deserve, thereby affecting the security of the overall system.

[0011] To achieve the above objectives, the present invention is implemented through the following technical solutions: an electronic archive data preservation method, comprising the following steps: real-time acquisition of a number of storage files to be stored and file attribute data of each storage file; analysis of the risk level value of each storage file according to the file attribute data of the storage file, and marking; classification and storage of the marked storage files in an electronic archive database; after the storage of the storage files, real-time acquisition of the time period access data of each storage file, and real-time analysis combined with the risk level value to obtain a risk assessment index for each storage file; inputting the risk assessment index of each storage file into an encryption analysis model for analysis to obtain an encryption strength bit value of each storage file, and taking encryption measures for each storage file according to the encryption strength bit value.

[0012] Furthermore, the file attribute data includes file type information, file size information, file access permission information, and the number of sensitive keywords; the time period access data specifically includes the risk level value of the stored file, the number of times the stored file is accessed in the current time period, and the time interval between the end of the file access in the current time period and the creation time of the stored file.

[0013] Furthermore, the specific steps of analyzing the risk level value of each stored file according to the file attribute data of the stored file are as follows: the file type information, file size information, and file access permission information of each stored file are respectively input into the preset quantification rules for quantitative analysis to obtain the file type quantification value, file size quantification value, and file access permission quantification value of each stored file; the file type quantification value, file size quantification value, file access permission quantification value, and the number of sensitive keywords of each stored file are comprehensively analyzed to obtain the risk level value of each stored file.

[0014] Furthermore, the specific formula for calculating the risk level value of each storage file is as follows: FxD i =ω1*WxH i +ω2*WdH i +ω3*WcH i +ω4*McS i Among them, FxD i is the risk level value of the i-th storage file, WxH i is the file type quantization value of the i-th stored file, ω1 is the file type weight value stored in the database, WdH i is the file size quantization value of the i-th stored file, ω2 is the file size weight value stored in the database, WcH i is the file access permission quantization value of the i-th storage file, ω3 is the file access permission weight value stored in the database, McS iis the number of sensitive keywords in the i-th stored file, ω4 is the weight value of the sensitive keywords stored in the database, ω1+ω2+ω3+ω4=1, i=1, 2, 3, …, i0, i0 is the number of stored files.

[0015] Furthermore, the specific steps for obtaining the risk assessment index of each storage file are as follows: for each storage file, the risk level value, the number of times the storage file is accessed in the current period, and the time interval between the end of the file access in the current period and the storage file creation time are read respectively, and the analysis is performed separately to obtain the risk assessment index of each storage file.

[0016] Furthermore, the specific formula for calculating the risk assessment index of each storage file is as follows: Among them, FxP i is the risk assessment index of the i-th storage file, FxD i is the risk level value of the i-th storage file, BfW i is the number of times the i-th storage file is accessed in the current period, T i is the time interval between the end of the current period file access of the i-th storage file and the storage file creation time, i=1, 2, 3, ..., i0, i0 is the number of storage files.

[0017] Furthermore, the cryptographic analysis model is specifically as follows: Among them, JmW i is the encryption strength bit value of the i-th stored file, FxP i is the risk assessment index of the i-th stored file, m is any real number except zero, α1 is the first discrimination threshold stored in the database, α2 is the second discrimination threshold stored in the database, i=1, 2, 3,…, i0, i0 is the number of stored files.

[0018] Furthermore, taking encryption measures for each storage file according to the encryption strength bit value is specifically as follows: reading the encryption strength bit value of each storage file, and performing encryption operations on the storage file based on a preset corresponding encryption algorithm.

[0019] An electronic archive data preservation system comprises: a data acquisition module, an analysis and marking module, a storage module, a monitoring and analysis module, and an encryption module; the data acquisition module is used to acquire in real time a number of storage files to be stored and the file attribute data of each storage file; the analysis and marking module is used to analyze the risk level value of each storage file according to the file attribute data of the storage file and mark it; the storage module is used to classify and store the marked storage files in an electronic archive database; the monitoring and analysis module is used to acquire in real time the time period access data of each storage file after the storage files are classified, and perform real-time analysis in combination with the risk level value to obtain the risk assessment index of each storage file; the encryption module is used to input the risk assessment index of each storage file into an encryption analysis model for analysis to obtain the encryption strength bit value of each storage file, and take encryption measures for each storage file according to the encryption strength bit value.

[0020] The present invention has the following beneficial effects:

[0021] (1) This electronic archive data preservation method obtains file attribute data in real time and conducts risk level assessment on it, so that it can instantly mark and classify stored files to ensure that high-risk files receive more stringent protection measures. By updating the risk assessment index in real time and dynamically adjusting the encryption strength accordingly, the protection capability of sensitive information is significantly improved. The targeted encryption measures not only enhance data security, but also optimize the use of encryption resources, avoiding unnecessary re-encryption of low-risk files, thereby improving the efficiency and response speed of the overall system.

[0022] (2) This electronic archive data preservation method stipulates that encrypted transmission must be performed during the process of migrating files from temporary storage locations to classified storage. This measure greatly enhances the data integrity and security of files during the migration process, thereby ensuring that even if an attack occurs during data transmission, the data content is protected by encryption, reducing the risk of data leakage.

[0023] (3) The electronic archive data preservation system, through the implementation of its monitoring and analysis module, has greatly enhanced the control and audit capabilities of file access activities. The system can not only monitor file access in real time, but also dynamically adjust access rights based on access patterns and risk assessment indices. For example, if a file is frequently accessed in a short period of time, the system can automatically increase the security level of the file, restrict unauthorized access, and trigger a security alarm. In addition, all access records will be recorded and stored in detail, providing a complete audit trail to help track potential improper access or data leakage incidents. In this way, it can ensure that access to sensitive data is legitimate and compliant, increase transparency and traceability in the data processing process, and significantly reduce legal and compliance risks.

[0024] Of course, any product implementing the present invention does not necessarily need to achieve all of the advantages described above at the same time. BRIEF DESCRIPTION OF THE DRAWINGS

[0025] Figure 1 The present invention is a flow chart of an electronic archive data preservation method.

[0026] Figure 2 The present invention is a flowchart of the specific steps of analyzing the risk level value of each stored file according to the file attribute data of the stored file in an electronic archive data preservation method.

[0027] Figure 3 The present invention is a block diagram of an electronic archive data preservation system. DETAILED DESCRIPTION

[0028] The embodiment of the present application solves the problem that the existing electronic archive data preservation system is often limited to only basic attribute recording and static classification of files when storing files, and fails to conduct in-depth analysis of the actual usage scenarios and access modes of the files, which may easily lead to security loopholes in the actual use of files even if the file storage environment technically meets the basic security requirements, due to the lack of real-time monitoring and risk assessment of access modes in actual operations. Secondly, traditional methods often adopt consistent security strategies in file encryption processing, ignoring the need to adjust the encryption strength based on the actual risk level of the file, which easily leads to waste of resources, which is particularly not conducive to improving efficiency when processing large amounts of data. At the same time, high-risk files do not receive the key protection they deserve, thereby affecting the security of the overall system.

[0029] The overall idea of ​​the problem in the embodiment of this application is as follows:

[0030] First, the system obtains the files to be stored and their attribute data (such as file type, size, access rights and number of sensitive keywords) in real time. Then, based on these attribute data, the system analyzes and calculates the risk level of each file and marks it. After marking, the files are classified and stored in electronic archive databases with different security levels according to their risk levels. High-risk files are stored in more secure or more redundant systems. After the files are classified and stored, the system continues to monitor the access data of each file in real time, and performs real-time analysis based on the risk level, and updates the risk assessment index of each file. Based on the updated risk assessment index, the system calculates the encryption strength bit value of each file through the encryption analysis model. Finally, based on the obtained encryption strength bit value, the system implements corresponding encryption measures for each file to ensure data security.

[0031] See also Figure 1 The embodiment of the present invention provides a technical solution: a method for preserving electronic archive data, comprising the following steps: obtaining in real time a number of storage files to be stored and file attribute data of each storage file; analyzing the risk level value of each storage file according to the file attribute data of the storage file, and marking it; classifying and storing the marked storage files in a pre-established electronic archive database (selecting an appropriate storage location according to the risk level, high-risk files may need to be stored in a safer or more redundant storage system, migrating the files from the temporary storage location to the final classified storage location, ensuring the integrity and security of the data during the migration process, and requiring encrypted transmission); after the storage of the storage files, obtaining the time period access data of each storage file in real time, and performing real-time analysis in combination with the risk level value to obtain a risk assessment index for each storage file; inputting the risk assessment index of each storage file into an encryption analysis model for analysis to obtain an encryption strength bit value of each storage file, and taking encryption measures for each storage file according to the encryption strength bit value.

[0032] File attribute data includes file type information (text, image, video, etc., obtained through file extension), file size information (in MB, read through the file system API), file access permission information (read-only, read-write, etc., queried through the operating system's file management API), and the number of sensitive keywords. The time period access data specifically includes the risk level value of the stored file, the number of times the stored file is accessed in the current time period, and the time interval between the end of the current time period file access and the storage file creation time.

[0033] The number of sensitive keywords is identified and counted by scanning the file content through a content analysis tool. For example, if a file contains the following keywords: ["confidential", "private", "secret"], the value of the number of sensitive keywords is increased each time these words appear.

[0034] The number of times the storage file is accessed in the current period is obtained through the access tracking mechanism. Each time the file is accessed, the access counter increases, which is implemented through middleware, database triggers or file system monitoring tools.

[0035] The steps to obtain the time interval between the end of the current period file access and the storage file creation time are as follows: First, record the timestamp when the file is created and store it in the file metadata. At the end of each access, subtract the timestamp of the creation time from the current time to get the time interval. This requires time recording at the beginning and end of the file access event.

[0036] Specifically, Figure 2 As shown, the specific steps of analyzing the risk level value of each stored file according to the file attribute data of the stored file are as follows: the file type information (text, picture, video, etc.), file size information (in MB), and file access permission information (read-only, read-write, etc.) of each stored file are respectively input into the preset quantification rules for quantitative analysis to obtain the file type quantification value, file size quantification value, and file access permission quantification value of each stored file; the file type quantification value, file size quantification value, file access permission quantification value, and the number of sensitive keywords of each stored file are comprehensively analyzed to obtain the risk level value of each stored file.

[0037] Among them, specific examples of preset quantization rules are as follows:

[0038] For file type information: text file=1, picture file=2, video file=3.

[0039] For file size information: less than 10MB=1, 10 to 100MB=2, greater than 100MB=3.

[0040] For file access permission information: read-only = 1, read-write = 2.

[0041] The specific formula for calculating the risk level value of each storage file is as follows: FxD i =ω1*WxH i +ω2*WdH i +ω3*WcH i +ω4*McS i Among them, FxD i is the risk level value of the i-th storage file, WxH iis the file type quantization value of the i-th stored file, ω1 is the file type weight value stored in the database, WdH i is the file size quantization value of the i-th stored file, ω2 is the file size weight value stored in the database, WcH i is the file access permission quantization value of the i-th storage file, ω3 is the file access permission weight value stored in the database, McS i is the number of sensitive keywords in the i-th stored file, ω4 is the weight value of the sensitive keywords stored in the database, ω1+ω2+ω3+ω4=1, i=1, 2, 3, …, i0, i0 is the number of stored files.

[0042] It needs to be explained that the specific calculation process of ω1, ω2, ω3, and ω4 is: collecting historical data including file type, file size, file permissions, and the number of sensitive keywords, as well as known security event records of these files, using statistical analysis methods, such as logistic regression analysis, to evaluate the impact of each factor on known security events (such as data leakage), calculating the coefficient of each factor based on the results of the statistical analysis, and normalizing it so that the sum of all weights is 1.

[0043] The specific implementation example of calculating the risk level value of a certain storage file is as follows, and the following data is available:

[0044] The file type weight of the stored file = 0.2.

[0045] The file size weight of the stored file = 0.3.

[0046] The file permission weight of the storage file = 0.1.

[0047] The weight of the number of sensitive keywords in the stored file = 0.4.

[0048] The file type quantization value of the storage file = 2 (picture file).

[0049] The file size quantization value of the stored file = 3 (for example, greater than 100 MB).

[0050] The file access permission quantization value of the storage file = 1 (read-only).

[0051] The number of sensitive keywords in the stored file = 4 (containing 4 sensitive words).

[0052] Inputting the above data into the calculation formula of the risk level value of the storage file, we can obtain: 0.2*2+0.3*3+0.1*1+0.4*4=0.4+0.9+0.1+1.6=3, so the risk level value of the storage file is 3.

[0053] In this implementation scheme, by inputting the specific attributes of each file (such as file type, size, access rights and number of sensitive keywords) into the preset quantitative rules for analysis, the scheme can achieve accurate risk level assessment for each file. This method based on detailed data and statistical analysis not only improves the accuracy of risk assessment, but also ensures that each file can get corresponding protection measures according to its specific risk. The calculated risk level value directly affects the storage and encryption processing of the file, which means that security measures can be dynamically adjusted according to the actual risk of the file. For example, high-risk files will be encrypted and stored in a more secure environment, while low-risk files can reduce resource consumption, thereby optimizing the performance and cost of the entire system. With the real-time update of the risk assessment index and the application of dynamic security measures, the system can respond quickly to external threats and internal changes, and enhance the protection of sensitive data. In addition, by real-time monitoring and analysis of risk factors, the system can promptly discover potential security issues and quickly adjust strategies to prevent risks. Accurate risk assessment also helps enterprises comply with data protection regulations and compliance requirements, such as GDPR or H IPAA and other regulations require companies to take appropriate technical and organizational measures to protect personal data. By implementing a risk-based data management strategy, companies can not only effectively protect their customers' and their own data, but also demonstrate their serious attitude towards data protection and enhance the trust of the public and regulators.

[0054] Specifically, the specific steps to obtain the risk assessment index of each storage file are: for each storage file, read the risk level value, the number of times the storage file is accessed in the current period, and the time interval between the end of the file access in the current period and the storage file creation time, and analyze them separately to obtain the risk assessment index of each storage file.

[0055] The specific formula for calculating the risk assessment index of each storage file is as follows: Among them, FxP i is the risk assessment index of the i-th storage file, FxD i is the risk level value of the i-th storage file, BfW i is the number of times the i-th storage file is accessed in the current period, T i is the time interval between the end of the current period file access of the i-th storage file and the storage file creation time, i=1, 2, 3, ..., i0, i0 is the number of storage files.

[0056] In this implementation scheme, by comprehensively considering the risk level value, access frequency and time interval information of the file, the system can more accurately calculate the actual risk assessment index of each file. This multi-dimensional analysis is not limited to the static attributes of the file, but also dynamically captures the access behavior and time changes of the file, making the risk assessment more real-time and accurate, especially in high-risk environments, and can effectively respond to security threats. Combined with access data and time intervals, the system can dynamically adjust security policies. By performing real-time analysis on the frequency and time period of file access, if a file is frequently accessed in a short period of time, the system can automatically identify the increased risk of the file and adjust encryption measures or strengthen access restrictions in a timely manner. In this way, the system can respond to potential threats more quickly and take appropriate security measures, thereby preventing potential security incidents. Through the combined analysis of access data, the system Not only does it consider the attributes of the file itself, but it also adjusts its protection measures based on the actual usage of the file. This means that if the file is accessed less frequently and the time interval is longer, its risk assessment index will be reduced accordingly, and the system can reduce its unnecessary encryption strength. This strategy can effectively avoid waste of resources while ensuring the key protection of high-access frequency and high-risk files, optimizing the system's resource allocation, and monitoring the file access frequency and time interval in real time, so that the file risk assessment process is not only static, but can also be dynamically updated over time, which enhances the system's data protection capabilities in long-term operation. In particular, for files that have not been accessed for a long time or are accessed frequently, the system can adjust protection measures in a timely manner based on the assessment index. In addition, the system can record the risk assessment index of each file, which is convenient for post-audit and risk analysis, and increases the transparency and traceability of data management.

[0057] Specifically, the encryption analysis model is as follows: Among them, JmW i is the encryption strength bit value of the i-th stored file, FxP i is the risk assessment index of the i-th stored file, m is any real number except zero (in this embodiment, the value is 2), α1 is the first discrimination threshold stored in the database, α2 is the second discrimination threshold stored in the database, i=1, 2, 3,…, i0, i0 is the number of stored files.

[0058] It should be explained that the first judgment threshold defines the critical point for upgrading the encryption strength from the lowest level (128 bits) to the middle level (192 bits).

[0059] The second judgment threshold defines the critical point at which the encryption strength is upgraded from the medium level (192 bits) to the highest level (256 bits).

[0060] The specific implementation example of calculating the encryption strength bit value of a certain storage file is as follows:

[0061] The following data are available:

[0062] The risk level value of the stored file is 3.

[0063] The storage file has been accessed 5 times in the current period.

[0064] The time interval between the end of file access in the current period and the creation time of the stored file is 48 hours.

[0065] The m value is 2, the first discrimination threshold is 2, and the second discrimination threshold is 3.

[0066] The risk level value of the storage file, the number of times the storage file is accessed in the current period, and the time interval between the end of the file access in the current period and the creation time of the storage file are input into the risk assessment index calculation formula, and the risk assessment index of the storage file is approximately 3.31.

[0067] The m value, the first discrimination threshold, the second discrimination threshold, and the risk assessment index are input into the encryption analysis model, and the encryption strength bit value of the storage file meets the condition: 2<log2(1+3.31)≤3, so the encryption strength bit value of the storage file is 192 bits.

[0068] In this implementation scheme, the encryption analysis model can accurately select the appropriate encryption strength bit for each stored file by comprehensively considering the risk assessment index of the file and its dynamic changes (such as access frequency, time interval, etc.). This means that high-risk files will automatically adopt higher encryption strength (such as 256 bits), while low-risk files will use moderate encryption strength (such as 128 bits or 192 bits), ensuring a balance between security and efficiency. This not only improves the security protection capability of the system, but also avoids the waste of resources for low-risk files. By dynamically adjusting the encryption strength through the encryption analysis model, the scheme can respond to changes in file usage. If the file access frequency increases, the time interval shortens, or the risk level increases, the system will automatically upgrade the encryption strength to ensure the security of data in a high-risk environment. Conversely, for files with low access frequency and decreased risk assessment index, the system can reduce the encryption strength accordingly to reduce computing overhead. This flexibility enhances the system's response capability, enabling it to adapt to actual conditions. The model adjusts the protection strategy in time. The model ensures that encryption resources are efficiently allocated by reasonably setting the first and second discrimination thresholds (for example, the critical points for upgrading from 128 bits to 192 bits and 256 bits). Different files automatically match the appropriate encryption strength according to the risk assessment index, avoiding unnecessary resource consumption caused by uniformly using the highest encryption level for all files. Therefore, the system can achieve better computing performance and storage efficiency, which helps to reduce the overall operating cost of the system, especially when processing a large number of files. By setting multiple levels of encryption strength (128 bits, 192 bits, and 256 bits), the system introduces a hierarchical data protection mechanism. This hierarchical encryption can not only ensure that high-risk data is protected with the strongest protection, but also can flexibly respond to complex security requirements according to different data types and usage scenarios. For example, when faced with data with many sensitive keywords and frequent access, the system will automatically select a higher encryption strength to protect the data, significantly improving the security and reliability of data preservation.

[0069] Specifically, taking encryption measures for each storage file according to the encryption strength bit value is as follows: reading the encryption strength bit value of each storage file, and performing encryption operations on the storage file based on a preset corresponding encryption algorithm.

[0070] The specific implementation example is as follows: Taking the encryption strength value of the stored file as 192 bits as an example:

[0071] For 192-bit encryption, the AES-192 encryption algorithm is used. The specific steps include:

[0072] Generate a 192-bit key using a cryptographic pseudo-random number generator (PRNG).

[0073] File contents are encrypted using AES-192.

[0074] Encrypted data should be stored securely, and the distribution and storage of keys should follow strict security measures to prevent unauthorized access.

[0075] In this implementation scheme, the scheme selects the corresponding encryption strength bit according to the risk assessment index of each stored file, and uses a suitable encryption algorithm (such as AES-192) to encrypt the file. This customized encryption method ensures that each file can obtain the most appropriate protection measures according to its risk level. For example, high-risk files use AES-256, while medium-risk files use AES-192. This hierarchical encryption ensures the overall security of the system, while ensuring that sensitive data is protected at a higher level, reducing the risk of data leakage or destruction. By using mature encryption algorithms such as AES-192, the system can ensure the confidentiality, integrity and compatibility of data. AES (Advanced Encryption Standard) is a widely accepted and trusted encryption algorithm. AES-192 is particularly suitable for medium-strength encryption requirements, which means that while ensuring strong security, the system can also be compatible with existing industry standards, facilitating subsequent data exchange, decryption and access operations. The scheme uses a pseudo-random number generator (PRNG) to generate a 192-bit key, and distributes and stores the key through a strict key management strategy. Key management is the core of the encryption system. By using a high-quality pseudo-random number generator to generate a key, the risk of key leakage or cracking can be significantly reduced. In addition, strict key management and protection prevents unauthorized access and tampering, further enhancing the security and reliability of the file encryption system. By selecting the corresponding encryption algorithm based on the risk index of the file and the number of encryption strength bits, this scheme can effectively optimize the use of resources in the encryption process. The encryption efficiency of AES-192 is higher than that of AES-256. Therefore, for medium-risk files, using AES-192 can reduce the system's computing overhead while ensuring security. This not only improves the efficiency of encryption processing, but also reduces unnecessary resource waste for high-intensity encryption, achieving a balance between security and performance.

[0076] See also Figure 3The embodiment of the present invention provides a technical solution: an electronic archive data preservation system, comprising: a data acquisition module, an analysis and marking module, a storage module, a monitoring and analysis module, and an encryption module; the data acquisition module is used to acquire in real time a number of storage files to be stored and file attribute data of each storage file; the analysis and marking module is used to analyze the risk level value of each storage file according to the file attribute data of the storage file and mark it; the storage module is used to classify and store the marked storage files into a pre-established electronic archive database (select an appropriate storage location according to the risk level, high-risk files may need to be stored in a safer or more redundant storage system, migrate the files from the temporary storage location to the final classified storage location, ensure the integrity and security of the data during the migration process, and need to perform encrypted transmission); the monitoring and analysis module is used to acquire the time period access data of each storage file in real time after the storage files are classified and stored, and perform real-time analysis in combination with the risk level value to obtain the risk assessment index of each storage file; the encryption module is used to input the risk assessment index of each storage file into the encryption analysis model for analysis, obtain the encryption strength bit value of each storage file, and take encryption measures for each storage file according to the encryption strength bit value.

[0077] In summary, this application has at least the following effects:

[0078] By acquiring file attribute data in real time and assessing its risk level, it is possible to instantly mark and classify stored files to ensure that high-risk files receive more stringent protection measures. By updating the risk assessment index in real time and dynamically adjusting the encryption strength accordingly, the ability to protect sensitive information is significantly improved. Targeted encryption measures not only enhance data security, but also optimize the use of encryption resources, avoiding unnecessary re-encryption of low-risk files, thereby improving the efficiency and response speed of the overall system.

[0079] In the process of migrating files from temporary storage locations to classified storage, it is required to perform encrypted transmission. This measure greatly enhances the data integrity and security of files during the migration process, thereby ensuring that even if attacks occur during data transmission, the data content is protected by encryption, reducing the risk of data leakage.

[0080] Through the implementation of its monitoring and analysis module, the control and audit capabilities of file access activities have been greatly enhanced. The system can not only monitor file access in real time, but also dynamically adjust access rights based on access patterns and risk assessment indexes. For example, if a file is frequently accessed in a short period of time, the system can automatically increase the security level of the file, restrict unauthorized access, and trigger a security alarm. In addition, all access records will be recorded and stored in detail, providing a complete audit trail to help track potential improper access or data leaks. In this way, it can ensure that access to sensitive data is legitimate and compliant, increase transparency and traceability in the data processing process, and thus significantly reduce legal and compliance risks.

[0081] Although the preferred embodiments of the present invention have been described, those skilled in the art may make other changes and modifications to these embodiments once they have learned the basic creative concept. Therefore, the appended claims are intended to be interpreted as including the preferred embodiments and all changes and modifications that fall within the scope of the present invention.

[0082] Obviously, those skilled in the art can make various changes and modifications to the present invention without departing from the spirit and scope of the present invention. Thus, if these modifications and variations of the present invention fall within the scope of the claims of the present invention and their equivalents, the present invention is also intended to include these modifications and variations.

Claims

1. A method for preserving electronic archive data, characterized in that: The following steps are involved: Acquire several storage files to be stored and file attribute data of each storage file in real time; Analyze the risk level value of each stored file according to the file attribute data of the stored file and mark it; Classify and store the marked stored files in an electronic archive database; After several storage files are classified and stored, the time period access data of each storage file is obtained in real time, and real-time analysis is performed in combination with the risk level value to obtain the risk assessment index of each storage file; The risk assessment index of each storage file is input into the encryption analysis model for analysis to obtain the encryption strength bit value of each storage file, and encryption measures are taken for each storage file according to the encryption strength bit value.

2. The electronic archive data preservation method according to claim 1, characterized in that: The file attribute data includes file type information, file size information, file access permission information, and the number of sensitive keywords. The time period access data specifically includes the risk level value of the stored file, the number of times the stored file is accessed in the current time period, and the time interval between the end of the file access in the current time period and the creation time of the stored file.

3. The electronic archive data preservation method according to claim 2, characterized in that: The specific steps for analyzing the risk level value of each stored file based on the file attribute data of the stored file are as follows: Input the file type information, file size information, and file access permission information of each stored file into the preset quantification rules for quantitative analysis, and obtain the file type quantification value, file size quantification value, and file access permission quantification value of each stored file; The file type quantification value, file size quantification value, file access permission quantification value, and number of sensitive keywords of each stored file are comprehensively analyzed to obtain the risk level value of each stored file.

4. The electronic archive data preservation method according to claim 3, characterized in that: The specific formula for calculating the risk level value of each storage file is as follows: FxD i =ω1*WxH i +ω2*WdH i +ω3*WcH i +ω4*McS i ; Among them, FxD i is the risk level value of the i-th storage file, WxH i is the file type quantization value of the i-th stored file, ω1 is the file type weight value stored in the database, WdH i is the file size quantization value of the i-th stored file, ω2 is the file size weight value stored in the database, WcH i is the file access permission quantization value of the i-th storage file, ω3 is the file access permission weight value stored in the database, McS i is the number of sensitive keywords in the i-th stored file, ω4 is the weight value of the sensitive keywords stored in the database, ω1+ω2+ω3+ω4=1, i=1, 2, 3, …, i0, i0 is the number of stored files.

5. The electronic archive data preservation method according to claim 2, characterized in that: The specific steps to obtain the risk assessment index of each storage file are as follows: for each storage file, read the risk level value, the number of times the storage file is accessed in the current period, and the time interval between the end of the file access in the current period and the storage file creation time, and analyze them separately to obtain the risk assessment index of each storage file.

6. The electronic archive data preservation method according to claim 5, characterized in that: The specific formula for calculating the risk assessment index of each storage file is as follows: Among them, FxP i is the risk assessment index of the i-th storage file, FxD i is the risk level value of the i-th storage file, BfW i is the number of times the i-th storage file is accessed in the current period, T i is the time interval between the end of the current period file access of the i-th storage file and the storage file creation time, i=1, 2, 3, ..., i0, i0 is the number of storage files.

7. The electronic archive data preservation method according to claim 1, characterized in that: The encryption analysis model is as follows: Among them, JmW i is the encryption strength bit value of the i-th stored file, FxP i is the risk assessment index of the i-th stored file, m is any real number except zero, α1 is the first discrimination threshold stored in the database, α2 is the second discrimination threshold stored in the database, i=1, 2, 3,…, i0, i0 is the number of stored files.

8. The electronic archive data preservation method according to claim 1, characterized in that: The encryption measures are taken for each storage file according to the encryption strength bit value respectively, specifically: reading the encryption strength bit value of each storage file, and performing encryption operation on the storage file based on the preset corresponding encryption algorithm.

9. An electronic archive data preservation system, using the electronic archive data preservation method according to any one of claims 1 to 8, characterized in that: include: Data acquisition module, analysis and marking module, storage module, monitoring and analysis module, encryption module; The data acquisition module is used to acquire in real time a number of storage files to be stored and file attribute data of each storage file; The analysis and marking module is used to analyze the risk level value of each stored file according to the file attribute data of the stored file and mark it; The storage module is used to classify and store the marked stored files in the electronic archive database; The monitoring and analysis module is used to obtain the time period access data of each storage file in real time after the storage files are classified and stored, and to perform real-time analysis in combination with the risk level value to obtain the risk assessment index of each storage file; The encryption module is used to input the risk assessment index of each storage file into the encryption analysis model for analysis, obtain the encryption strength bit value of each storage file, and take encryption measures for each storage file according to the encryption strength bit value.

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