Power plant data node backup method and backup system based on big data

Abstract

The invention discloses a power plant data node backup method and backup system based on big data, and belongs to the technical field of power plant data backup. In the process of executing file encryption, version creation and Hash calculation, an AES-256 strong encryption algorithm is selected to encrypt the content of a power plant data file; through the step, the safety and reliability of the whole power plant data backup method are remarkably improved. Firstly, the application of the AES-256 encryption algorithm ensures the confidentiality of the power plant data in the transmission and storage process, and the power plant data is not easy to leak even in the face of advanced network attack or physical storage medium loss, thereby greatly protecting the sensitive information and operation safety of the power system. The generation of the hash value not only ensures the integrity of the power plant data before and after encryption, but also provides a non-tampering proof for data verification, so that the backup and recovery process of the power plant data is more reliable and efficient.

Description

Technical Field

[0001] The present invention belongs to the technical field of power plant data backup, and specifically relates to a power plant data node backup method and backup system based on big data. Background Art

[0002] With the rapid development of information technology, big data technology is increasingly used in the power industry. As an important part of the power system, power plant data nodes carry a large amount of key business data, auxiliary business data, and log data. These data are crucial for the safe and stable operation of the power system. However, with the increasing amount of data and the increasing complexity of data types, how to efficiently and securely back up power plant data nodes has become an urgent problem to be solved. Therefore, it is necessary to back up power plant data nodes.

[0003] However, the existing power plant data node backup methods have the following main shortcomings: The backup strategy is not flexible enough: Traditional backup methods often use fixed backup cycles and backup frequencies, which are difficult to adapt to the rapid growth of power plant data volume and data changes. Low security: During the backup process, the security of data transmission and storage cannot be effectively guaranteed, which easily leads to risks such as data leakage and tampering. Summary of the invention

[0004] The purpose of the present invention is to provide a power plant data node backup method and backup system based on big data in order to solve the above-mentioned problems.

[0005] The technical solution adopted by the present invention is as follows: a power plant data node backup method based on big data, comprising the following steps:

[0006] S1: Define the backup objectives and analyze in detail the data structure, data volume, data growth rate, and legal and regulatory requirements for backup of power plant data nodes; at the same time, evaluate the importance of data and recovery time objectives to ensure that the backup plan meets business continuity requirements;

[0007] S2: Research and compare various big data backup solutions in the market, and select backup tools and platforms with high availability, high scalability, and high security; ensure that the selected tools can support large-scale data processing and provide efficient data compression and encryption functions;

[0008] S3: Develop a detailed data backup strategy, including the full backup cycle, incremental backup frequency, and differential backup time points; at the same time, set a backup window to reduce the impact on the production environment;

[0009] S4: Build a stable and reliable backup environment, configure sufficient network bandwidth, storage space and server resources; strengthen the backup environment, including setting up firewalls, access control lists and data encryption transmission;

[0010] S5: Perform deep data cleaning on the power plant data nodes before backup, identify and process invalid, erroneous and duplicate data, optimize data structure, and improve backup efficiency and data quality;

[0011] S6: Perform file encryption, version creation and hash calculation, and select an AES-256 strong encryption algorithm to encrypt the file content;

[0012] S7: Update the ordered hash chain and insert the hash value of the new version into the ordered hash chain;

[0013] S8: Perform the first full backup to completely copy all data of the power plant data nodes to the backup server; ensure the synchronization and consistency of data during the backup process to avoid data omissions;

[0014] S9: Perform incremental backup regularly according to the set backup strategy, backing up only the data blocks that have changed since the last backup; plan the time points of incremental backup reasonably to reduce the impact on the business system;

[0015] S10: Monitor the backup process in real time, and use the backup software's monitoring interface or third-party monitoring tools to ensure that the backup task is carried out as planned; take timely measures to adjust and repair any abnormal situations;

[0016] S11: After the backup is completed, the backup data is fully verified, including data integrity check and data consistency verification, after which the entire power plant data node backup process based on big data can be completed.

[0017] In a preferred embodiment, in step S1, all data samples of the power plant data nodes are collected, and features are extracted from these samples, including the type of data, access frequency, and modification frequency; then, a classification model is constructed using a decision tree algorithm to divide the data into multiple categories, including key business data, auxiliary business data, and log data; based on the classification results, different backup priorities and recovery time targets are set for different categories of data.

[0018] In a preferred embodiment, in step S2, when selecting backup tools and platforms, a hierarchical decision analysis algorithm is used to assist decision making; first, the mainstream big data backup solutions on the market are listed, and the key attributes for evaluating these solutions are determined, including high availability, high scalability, high security, and cost-effectiveness; then, the relative importance weights of these attributes are determined through expert scoring and paired comparison method; on this basis, each alternative solution is scored, and a comprehensive score is calculated in combination with the weights; finally, the backup tool and platform with the highest score is selected according to the comprehensive score;

[0019] In step S3, when formulating the data backup strategy, the ARIMA time series prediction algorithm is used to predict the data growth rate and plan the backup cycle accordingly; first, the historical data volume is collected, and the ARIMA model is established to predict the data volume change trend in the future by performing time series analysis on the data; according to the prediction results, the full backup cycle, the incremental backup frequency, and the specific time point of the differential backup are set; at the same time, the backup window is set to reduce the impact on the production environment; this process ensures that the backup strategy can adapt to data growth and maintain the stable operation of the business system.

[0020] In a preferred embodiment, in step S6, performing file encryption, version creation and hash calculation specifically includes the following steps:

[0021] S6-1. File modification identification: After detecting that a file has been modified, the system will lock the file to prevent further modification during the encryption and version creation process;

[0022] S6-2. Apply encryption algorithm: Select a strong encryption algorithm to encrypt the file content; the encryption process includes the following sub-steps:

[0023] Generate encryption key: Generate or obtain encryption key according to system security policy;

[0024] Encrypt file content: encrypt each data block of the file using an encryption key;

[0025] Secure key storage: Ensure secure storage of encryption keys for subsequent decryption operations;

[0026] S6-3. Create a new version: Generate a new file version, which should contain the following information:

[0027] Encrypted file content;

[0028] File attribute update: including modification time, modifier information, and file type;

[0029] Version metadata: records the timestamp and other related information of version creation;

[0030] S6-4. Calculate hash value: Perform hash calculation on the newly generated file version. The specific steps are as follows:

[0031] Use a hash function to hash the encrypted file content; ensure that the hash value reflects the integrity and uniqueness of the file content; associate the calculated hash value with the file version metadata for subsequent verification and synchronization operations.

[0032] In a preferred embodiment, in step S6-3, a new file version is generated, and the hash value calculation formula is:

[0033] Hash(new_version)=Hash(file_content||timestamp||previous_hash) where || represents a concatenation operation, file_content represents the file content, timestamp represents the timestamp, and previous_hash represents the hash value of the previous version;

[0034] Use the AES-CBC encryption algorithm; increase encryption security by introducing an initialization vector (IV); in CBC mode, each plaintext block is XORed with the previous ciphertext block before encryption;

[0035] The encryption process is:

[0036] Choose a key length (128, 192, or 256 bits), denoted as k;

[0037] Generate a random initialization vector (IV), denoted as IV, whose length is the same as the AES block size (128 bits);

[0038] Split the plaintext data PP into blocks of 128 bits in length, denoted as P1, P2, ..., Pn;

[0039] XOR each plaintext block Pi with the previous ciphertext block}Ci-1 or IV, and then apply the AES encryption algorithm to obtain the ciphertext block Ci;

[0040] The encryption formula is:

[0041] C1=AES Encrypt (P1⊕IV,k)

[0042] Ci=AES Encrypt (Pi⊕Ci-1,k)fori=2,...,n;

[0043] Among them: AES_Encrypt: is a function that represents the AES encryption operation; it accepts a plaintext block Pi (128 bits) and a key kk (128, 192 or 256 bits) and outputs a ciphertext block Ci (128 bits);

[0044] AES_Decrypt: is a function that represents the AES decryption operation; it accepts a ciphertext block Ci (128 bits) and a key k (128, 192, or 256 bits) and outputs a plaintext block Pi (128 bits);

[0045] ⊕ is the XOR operator; when performing an XOR operation on two binary sequences of equal length, the result is 0 if the bits in the same position are the same, and 1 if they are different;

[0046] IV stands for Initialization Vector, which is a randomly generated bit sequence that is XORed with the first plaintext block to ensure that even if the same plaintext is encrypted multiple times, different ciphertexts will be generated. In CBC mode, the length of IV is the same as the block size of AES, which is 128 bits.

[0047] Pi represents the i-th block in the plaintext data;

[0048] Ci represents the i-th block in the ciphertext data;

[0049] Pi′ represents the intermediate plaintext block in the decryption process, that is, the plaintext block obtained by decryption before the XOR operation; n represents the total number of plaintext or ciphertext blocks.

[0050] In a preferred embodiment, in step S4, when building a stable and reliable backup environment, a network optimization algorithm is used to configure network bandwidth, storage space and server resources; first, the optimization goal is defined to minimize the backup time or maximize resource utilization; then, the chromosome encoding of the genetic algorithm is designed, and the optimal resource allocation solution is iteratively solved through selection, crossover and mutation operations; in addition, the backup environment is securely reinforced, including setting up firewalls, access control lists and data encryption transmission to ensure the security of backup data; this process ensures that the backup environment is both efficient and secure.

[0051] In a preferred embodiment, in step S5, when deep data cleaning is performed before backup, a data mining algorithm, including an association rule mining algorithm, is used to optimize data quality; first, the data in the power plant data node is preprocessed, including removing null values ​​and correcting incorrect formats; then, a transaction database is constructed, and support and confidence thresholds are set, and the potential relationship in the data is found through the association rule mining algorithm to identify invalid, erroneous and duplicate data; according to the mining results, the data is cleaned and the data structure is optimized, thereby improving backup efficiency and data quality;

[0052] In step S8, the hash values ​​of the files are first calculated on the source data and the backup server respectively, and then the hash values ​​are compared to identify the differences; then, only the difference data blocks are transmitted, thereby reducing the amount of data transmission and improving the backup efficiency; during the entire backup process, data synchronization and consistency are ensured to avoid data omission or damage.

[0053] In a preferred embodiment, in step S9, when incremental backup is performed regularly, a Delta backup algorithm is used to back up the changed data; first, a data change log is recorded to identify the changed data blocks; then, the difference of these data blocks is calculated, and the differential data is transmitted to the backup server; when restoring the data, the differential data is merged with the full backup to restore the complete data set; this process ensures the timeliness of the backup and the consistency of the data, while reducing the impact of the backup on the business system.

[0054] In a preferred embodiment, the step S7 specifically includes:

[0055] S7-1. Locate the insertion point: According to the timestamp of the new version, determine its correct position in the ordered hash chain; this step involves the following operations:

[0056] Compare timestamps: compare the timestamp of the new version with the timestamp of the existing nodes in the chain;

[0057] Determine the sequence: find the right position to ensure the timing of the chain;

[0058] S7-2. Insert a new node: Insert a new node containing the new version hash value into the ordered hash chain. The specific steps are as follows:

[0059] Create a new node: construct a new node, including the hash value and version metadata of the new version;

[0060] Update chain structure: inserting new nodes into the chain requires adjusting pointers or links to maintain the integrity of the chain; Save chain state: ensure that the latest state of the ordered hash chain is saved to stable storage to prevent system failures;

[0061] S7-3. Verify the integrity of the chain: After inserting a new node, perform the following verification steps to ensure the integrity of the chain: Verify node links: Make sure the new node is correctly linked to the previous and next nodes; Calculate the hash of the chain: Optionally, calculate the hash value of the entire chain to provide a quick way to verify the integrity of the chain.

[0062] In summary, due to the adoption of the above technical solution, the beneficial effects of the present invention are:

[0063] 1. In the present invention, in the process of executing file encryption, version creation and hash calculation, the AES-256 strong encryption algorithm is selected to encrypt the content of the power plant data file. This step brings significant security and reliability improvements to the entire power plant data backup method. First, the use of the AES-256 encryption algorithm ensures the confidentiality of the power plant data during transmission and storage. Even in the face of advanced network attacks or the loss of physical storage media, the power plant data will not be easily leaked, thereby greatly protecting the sensitive information and operational safety of the power system. Secondly, by creating a new encrypted version for each backup of the power plant data, combined with hash calculation, multiple time point options are provided for the recovery of the power plant data, so that when data loss or damage occurs, it can be accurately restored to a specific power plant data state. The generation of hash values ​​not only ensures the integrity of the power plant data before and after encryption, but also provides an unalterable proof for data verification, making the backup and recovery process of the power plant data more reliable and efficient.

[0064] 2. In the present invention, the hash value of the new version of the power plant data is inserted into the ordered hash chain. This strategy further enhances the overall performance and security of the power plant data backup system. The maintenance of the ordered hash chain provides a clear audit trail for the version control and timeline tracking of the power plant data, so that every change in the power plant data can be traced. This chronological hash chain structure is not only convenient for quickly locating a specific version of the power plant data when needed, but also can immediately detect any improper tampering of the power plant data, because any tampering will cause the hash chain to break. Therefore, the update of the ordered hash chain not only improves the speed and accuracy of power plant data recovery, but also provides strong support for the long-term protection and compliance audit of power plant data, ensuring the security and stability of power system data. BRIEF DESCRIPTION OF THE DRAWINGS

[0065] Figure 1 It is a schematic diagram of the process principle of the present invention. DETAILED DESCRIPTION

[0066] In order to make the purpose, technical solution and advantages of the present invention more clearly understood, the present invention is further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present invention and are not used to limit the present invention.

[0067] Reference Figure 1 ,

[0068] A power plant data node backup method based on big data comprises the following steps:

[0069] S1: Define the backup objectives and analyze in detail the data structure, data volume, data growth rate, and legal and regulatory requirements for backup of the power plant data nodes. At the same time, evaluate the importance of the data and the recovery time objective (RTO) to ensure that the backup plan meets the business continuity requirements;

[0070] S2: Research and compare various big data backup solutions in the market, and select backup tools and platforms with high availability, high scalability, and high security. Ensure that the selected tools can support large-scale data processing and provide efficient data compression and encryption functions;

[0071] S3: Develop a detailed data backup strategy, including the full backup cycle (such as once a week), the incremental backup frequency (such as once a day), and the specific time point for differential backup. At the same time, set a backup window to reduce the impact on the production environment;

[0072] S4: Build a stable and reliable backup environment, configure sufficient network bandwidth, storage space and server resources. Strengthen the backup environment, including setting up firewalls, access control lists (ACLs) and data encryption transmission;

[0073] S5: Perform deep data cleaning on the power plant data nodes before backup, identify and process invalid, erroneous and duplicate data, optimize data structure, and improve backup efficiency and data quality;

[0074] S6: Perform file encryption, version creation and hash calculation, and select an AES-256 strong encryption algorithm to encrypt the file content;

[0075] S7: Update the ordered hash chain and insert the hash value of the new version into the ordered hash chain;

[0076] S8: Perform the first full backup and completely copy all the data of the power plant data nodes to the backup server. Ensure the synchronization and consistency of data during the backup process to avoid data omissions;

[0077] S9: Perform incremental backup regularly according to the set backup strategy, and only back up the data blocks that have changed since the last backup. Reasonably plan the time point of incremental backup to reduce the impact on the business system;

[0078] S10: Monitor the backup process in real time, and use the backup software's monitoring interface or third-party monitoring tools to ensure that the backup task is carried out as planned. If any abnormal situation occurs, take timely measures to adjust and repair it;

[0079] S11: After the backup is completed, the backup data is fully verified, including data integrity check and data consistency verification, after which the entire power plant data node backup process based on big data can be completed.

[0080] In step S1, all data samples of the power plant data nodes are collected and features are extracted from these samples, including data type, access frequency, and modification frequency. Next, a classification model is built using the decision tree algorithm to classify the data into multiple categories, such as key business data, auxiliary business data, and log data. Based on the classification results, different backup priorities and recovery time targets are set for different categories of data.

[0081] In step S2, when selecting backup tools and platforms, a hierarchical decision analysis algorithm is used to assist decision making. First, the mainstream big data backup solutions on the market are listed, and the key attributes for evaluating these solutions are determined, including high availability, high scalability, high security, cost-effectiveness, etc. Then, the relative importance weights of these attributes are determined through expert scoring and paired comparison method. On this basis, each alternative solution is scored, and the comprehensive score is calculated based on the weight. Finally, the backup tool and platform with the highest score is selected based on the comprehensive score.

[0082] In step S3, when formulating the data backup strategy, the ARIMA time series prediction algorithm is used to predict the data growth rate and plan the backup cycle accordingly. First, collect the historical data volume, perform time series analysis on these data, and establish an ARIMA model to predict the data volume change trend in the future. According to the prediction results, set the full backup cycle, the incremental backup frequency, and the specific time point of the differential backup. At the same time, set the backup window to reduce the impact on the production environment. This process ensures that the backup strategy can adapt to data growth while maintaining the stable operation of the business system.

[0083] In step S6, executing file encryption, version creation and hash calculation specifically includes the following steps:

[0084] S6-1. File modification identification: When a file modification is detected, the system will lock the file to prevent further modification during the encryption and version creation process.

[0085] S6-2. Apply encryption algorithm: Select a strong encryption algorithm (such as AES-256) to encrypt the file content. The encryption process includes the following sub-steps:

[0086] Generate encryption key: Generate or obtain encryption key according to system security policy.

[0087] Encrypt file content: Encrypt each data block of the file using an encryption key.

[0088] Secure key storage: Ensure secure storage of encryption keys for subsequent decryption operations.

[0089] S6-3. Create a new version: Generate a new file version, which should contain the following information:

[0090] The encrypted file content.

[0091] File attribute updates: including modification time, modifier information, file type, etc.

[0092] Version metadata: records the timestamp and other related information of the version creation.

[0093] S6-4. Calculate hash value: Perform hash calculation on the newly generated file version. The specific steps are as follows:

[0094] Use a hash function (such as SHA-256) to hash the encrypted file content. Ensure that the hash value reflects the integrity and uniqueness of the file content. Associate the calculated hash value with the file version metadata for subsequent verification and synchronization operations;.

[0095] In step S6-3, a new file version is generated, and the hash value calculation formula is: Hash(new_version)=Hash(file_content||timestamp||previous_hash) where || represents the concatenation operation, file_content represents the file content, timestamp represents the timestamp, and previous_hash represents the hash value of the previous version.

[0096] Use the AES-CBC encryption algorithm. The security of encryption is increased by introducing an initialization vector (IV). In CBC mode, each plaintext block is XORed with the previous ciphertext block before encryption.

[0097] The encryption process is:

[0098] Choose a key length (128, 192, or 256 bits), denoted by k.

[0099] Generate a random initialization vector (IV), denoted as IV, whose length is the same as the block size of AES (128 bits).

[0100] The plaintext data PP is divided into blocks of 128 bits in length, denoted as P1, P2, ..., Pn.

[0101] XOR each plaintext block Pi with the previous ciphertext block}Ci-1 or IV, and then apply the AES encryption algorithm to obtain the ciphertext block Ci;

[0102] The encryption formula is:

[0103] C1=AES Encrypt(P1⊕IV,k)

[0104] Ci=AES Encrypt (Pi⊕Ci-1,k)fori=2,...,n;

[0105] Among them: AES_Encrypt: is a function, which represents the AES encryption operation. It accepts a plaintext block Pi (128 bits) and a key kk (128, 192 or 256 bits) and outputs a ciphertext block Ci (128 bits).

[0106] AES_Decrypt: is a function that represents the AES decryption operation. It accepts a ciphertext block Ci (128 bits) and a key k (128, 192, or 256 bits) and outputs a plaintext block Pi (128 bits).

[0107] ⊕ is the XOR operator. When performing an XOR operation on two binary sequences of equal length, the result is 0 if the bits in the same position are the same, and 1 if they are different.

[0108] IV stands for Initialization Vector, which is a randomly generated bit sequence that is XORed with the first plaintext block to ensure that even if the same plaintext is encrypted multiple times, different ciphertexts will be generated. In CBC mode, the length of IV is the same as the block size of AES, which is 128 bits.

[0109] Pi represents the i-th block in the plaintext data.

[0110] Ci represents the i-th block in the ciphertext data.

[0111] Pi′ represents the intermediate plaintext block in the decryption process, that is, the plaintext block obtained by decryption before the XOR operation.

[0112] n represents the total number of plaintext or ciphertext blocks.

[0113] Step S7 specifically includes:

[0114] S7-1. Locate the insertion point: According to the timestamp of the new version, determine its correct position in the ordered hash chain. This step involves the following operations:

[0115] Compare timestamps: Compare the timestamp of the new version with the timestamp of the existing nodes in the chain.

[0116] Determine the sequence: Find the right position to ensure the timing of the chain.

[0117] S7-2. Insert a new node: Insert a new node containing the new version hash value into the ordered hash chain. The specific steps are as follows:

[0118] Create a new node: Construct a new node containing the hash value and version metadata of the new version.

[0119] Update chain structure: Inserting new nodes into the chain requires adjusting pointers or links to maintain the integrity of the chain. Save chain state: Ensure that the latest state of the ordered hash chain is saved to stable storage to prevent system failures.

[0120] S7-3. Verify the integrity of the chain: After inserting a new node, perform the following verification steps to ensure the integrity of the chain: Verify node links: Make sure the new node is correctly linked to the previous and next nodes. Calculate the hash of the chain: Optionally, calculate the hash value of the entire chain to provide a fast way to verify the integrity of the chain.

[0121] In step S4, when building a stable and reliable backup environment, a network optimization algorithm, such as a genetic algorithm, is used to configure network bandwidth, storage space, and server resources. First, the optimization goal is defined, such as minimizing the backup time or maximizing resource utilization. Then, the chromosome encoding of the genetic algorithm is designed, and the optimal resource configuration solution is iteratively solved through selection, crossover, and mutation operations. In addition, the backup environment is securely reinforced, including setting up firewalls, access control lists (ACLs), and data encryption transmission to ensure the security of backup data. This process ensures that the backup environment is both efficient and secure.

[0122] In step S5, when deep data cleaning is performed before backup, a data mining algorithm, such as an association rule mining algorithm, is used to optimize data quality. First, the data in the power plant data node is preprocessed, including removing null values, correcting incorrect formats, etc. Then, a transaction database is constructed, and support and confidence thresholds are set. The potential relationships in the data are found through the association rule mining algorithm, and invalid, erroneous, and duplicate data are identified. According to the mining results, the data is cleaned and the data structure is optimized, thereby improving backup efficiency and data quality;

[0123] In step S8, the hash values ​​of the files are first calculated on the source data and the backup server, and then the hash values ​​are compared to identify the differences. Then, only the difference data blocks are transmitted, thereby reducing the amount of data transmission and improving the backup efficiency. During the entire backup process, data synchronization and consistency are ensured to avoid data omission or damage.

[0124] In step S9, when performing incremental backup regularly, the Delta backup algorithm is used to back up the changed data. First, the data change log is recorded to identify the changed data blocks. Then, the difference of these data blocks is calculated and the differential data is transmitted to the backup server. When restoring the data, the differential data is merged with the full backup to restore the complete data set. This process ensures the timeliness of the backup and the consistency of the data, while reducing the impact of the backup on the business system.

[0125] A power plant data node backup system based on big data, the system runs the power plant data node backup method based on big data of the above embodiment.

[0126] In the present invention, in the process of executing file encryption, version creation and hash calculation, the AES-256 strong encryption algorithm is selected to encrypt the content of the power plant data file. This step brings significant security and reliability improvements to the entire power plant data backup method. First, the use of the AES-256 encryption algorithm ensures the confidentiality of the power plant data during transmission and storage. Even in the face of advanced network attacks or the loss of physical storage media, the power plant data will not be easily leaked, thereby greatly protecting the sensitive information and operational safety of the power system. Secondly, by creating a new encrypted version for each backup of the power plant data, combined with hash calculation, multiple time point options are provided for the recovery of the power plant data, so that when data loss or damage occurs, it can be accurately restored to a specific power plant data state. The generation of hash values ​​not only ensures the integrity of the power plant data before and after encryption, but also provides an unalterable proof for data verification, making the backup and recovery process of the power plant data more reliable and efficient.

[0127] By encrypting the file content in step S6, the system provides security protection for power plant data during storage and transmission. Even if the power plant data is accessed without authorization, the attacker cannot directly read the file content. The calculated new version hash value provides a verification mechanism for the integrity of the power plant data. By maintaining an ordered hash chain in step S7, the integrity and non-tampering of the file can be quickly verified. This not only enhances the security of power plant data, but also ensures the continuity and consistency of the file version history. In addition, the update of the ordered hash chain improves the reliability and stability of the system because it ensures the continuity and consistency of the file version history, and can quickly restore to the most recent consistent state when a system failure occurs, reducing the risk of power plant data loss. At the same time, the ordered hash chain helps identify the file versions that need to be synchronized, reduces unnecessary power plant data transmission, and improves synchronization efficiency.

[0128] In terms of traceability and auditing, the ordered hash chain provides an unalterable record of each modification of the file, which is very important for auditing and power plant data traceability. At the same time, by recording the timestamp and modifier information of each version, the person responsible for each file change can be traced, enhancing the manageability of the system.

[0129] Finally, in terms of user experience, users do not have to worry about security issues during file synchronization, because all synchronization operations are completed automatically and securely in the background, which improves the user experience. The implementation of steps S6 and S7 has significantly improved the power plant data synchronization method based on ordered hash chains in terms of power plant data security, consistency, system reliability, synchronization efficiency, traceability and auditing, and user transparency.

[0130] In the present invention, the hash value of the new version of the power plant data is inserted into the ordered hash chain. This strategy further enhances the overall performance and security of the power plant data backup system. The maintenance of the ordered hash chain provides a clear audit trail for the version control and timeline tracking of the power plant data, so that every change in the power plant data can be traced. This chronological hash chain structure is not only convenient for quickly locating a specific version of the power plant data when needed, but also can immediately detect any improper tampering of the power plant data, because any tampering will cause the hash chain to break. Therefore, the update of the ordered hash chain not only improves the speed and accuracy of power plant data recovery, but also provides strong support for the long-term protection and compliance audit of power plant data, ensuring the security and stability of power system data.

[0131] It should be noted that, in this article, relational terms such as first and second, etc. are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Moreover, the term "comprises" or any other variant thereof is intended to cover non-exclusive inclusion, so that a process, method, article or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, article or device. In the absence of further restrictions, the elements defined by the sentence "comprises a ..." do not exclude the existence of other identical elements in the process, method, article or device including the elements.

[0132] The above description enables those skilled in the art to implement or use the present invention. Various modifications to these embodiments will be apparent to those skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of the present invention. Therefore, the present invention will not be limited to the embodiments shown herein, but will conform to the widest scope consistent with the principles and novel features disclosed herein.

Claims

1. A power plant data node backup method based on big data, characterized in that: The steps include: S1: Define the backup objectives and analyze in detail the data structure, data volume, data growth rate, and legal and regulatory requirements for backup of power plant data nodes; at the same time, evaluate the importance of data and recovery time objectives to ensure that the backup plan meets business continuity requirements; S2: Research and compare various big data backup solutions in the market, and select backup tools and platforms with high availability, high scalability, and high security; ensure that the selected tools can support large-scale data processing and provide efficient data compression and encryption functions; S3: Develop a detailed data backup strategy, including the full backup cycle, incremental backup frequency, and differential backup time points; at the same time, set a backup window to reduce the impact on the production environment; S4: Build a stable and reliable backup environment, configure sufficient network bandwidth, storage space and server resources; strengthen the backup environment, including setting up firewalls, access control lists and data encryption transmission; S5: Perform deep data cleaning on the power plant data nodes before backup, identify and process invalid, erroneous and duplicate data, optimize data structure, and improve backup efficiency and data quality; S6: Perform file encryption, version creation and hash calculation, and select an AES-256 strong encryption algorithm to encrypt the file content; S7: Update the ordered hash chain and insert the hash value of the new version into the ordered hash chain; S8: Perform the first full backup and copy all the data of the power plant data nodes to the backup server; Ensure the synchronization and consistency of data during the backup process to avoid data omission; S9: Perform incremental backup regularly according to the set backup strategy, backing up only the data blocks that have changed since the last backup; Reasonably plan the time points for incremental backup to reduce the impact on business systems; S10: Monitor the backup process in real time, and use the backup software's monitoring interface or third-party monitoring tools to ensure that the backup task is carried out as planned; take timely measures to adjust and repair any abnormal situations; S11: After the backup is completed, the backup data is fully verified, including data integrity check and data consistency verification, after which the entire power plant data node backup process based on big data can be completed.

2. A power plant data node backup method based on big data as claimed in claim 1, characterized in that: In step S1, all data samples of the power plant data nodes are collected, and features are extracted from these samples, including data type, access frequency, and modification frequency; then, a classification model is constructed using a decision tree algorithm to divide the data into multiple categories, including key business data, auxiliary business data, and log data; Based on the classification results, set different backup priorities and recovery time objectives for different categories of data.

3. The method for backing up power plant data nodes based on big data according to claim 1, characterized in that: In step S2, when selecting backup tools and platforms, a hierarchical decision analysis algorithm is used to assist decision making; first, the mainstream big data backup solutions on the market are listed, and the key attributes for evaluating these solutions are determined, including high availability, high scalability, high security, and cost-effectiveness; Then, the relative importance weights of these attributes were determined through expert rating and pairwise comparison method; On this basis, each alternative is scored and the comprehensive score is calculated based on the weights; Finally, the backup tools and platforms with the highest scores were selected based on the comprehensive scores; In step S3, when formulating the data backup strategy, the ARIMA time series prediction algorithm is used to predict the data growth rate and plan the backup cycle accordingly; first, the historical data volume is collected, and the ARIMA model is established to predict the data volume change trend in the future by performing time series analysis on the data; according to the prediction results, the full backup cycle, the incremental backup frequency, and the specific time point of the differential backup are set.

4. The method for backing up power plant data nodes based on big data according to claim 1, characterized in that: In step S6, executing file encryption, version creation and hash calculation specifically includes the following steps: S6-1. File modification identification: After detecting that a file has been modified, the system will lock the file to prevent further modification during the encryption and version creation process; S6-2. Apply encryption algorithm: Select a strong encryption algorithm to encrypt the file content; the encryption process includes the following sub-steps: Generate encryption key: Generate or obtain encryption key according to system security policy; Encrypt file content: encrypt each data block of the file using an encryption key; Secure key storage: Ensure secure storage of encryption keys for subsequent decryption operations; S6-3. Create a new version: Generate a new file version, which should contain the following information: Encrypted file content; File attribute update: including modification time, modifier information, and file type; Version metadata: records the timestamp and other related information of version creation; S6-4. Calculate hash value: Perform hash calculation on the newly generated file version. The specific steps are as follows: Use a hash function to hash the encrypted file content; ensure that the hash value reflects the integrity and uniqueness of the file content; associate the calculated hash value with the file version metadata for subsequent verification and synchronization operations.

5. A power plant data node backup method based on big data as claimed in claim 5, characterized in that: In step S6-3, a new file version is generated, and the hash value calculation formula is: Hash(new_version)=Hash(file_content||timestamp||previous_hash) Among them, || represents the concatenation operation, file_content represents the file content, timestamp represents the timestamp, and previous_hash represents the hash value of the previous version; Use the AES-CBC encryption algorithm; increase encryption security by introducing an initialization vector (IV); in CBC mode, each plaintext block is XORed with the previous ciphertext block before encryption; The encryption process is: Choose a key length (128, 192, or 256 bits), denoted as k; Generate a random initialization vector (IV), denoted as IV, whose length is the same as the AES block size (128 bits); Split the plaintext data PP into blocks of 128 bits in length, denoted as P1, P2, ..., Pn; XOR each plaintext block Pi with the previous ciphertext block}Ci-1 or IV, and then apply the AES encryption algorithm to obtain the ciphertext block Ci; The encryption formula is: C1=AES Encrypt (P1⊕IV,k) Ci=AES Encrypt (Pi⊕Ci-1,k)fori=2,...,n; Among them: AES_Encrypt: is a function that represents the AES encryption operation; it accepts a plaintext block Pi (128 bits) and a key kk (128, 192 or 256 bits) and outputs a ciphertext block Ci (128 bits); AES_Decrypt: is a function that represents the AES decryption operation; it accepts a ciphertext block Ci (128 bits) and a key k (128, 192, or 256 bits) and outputs a plaintext block Pi (128 bits); ⊕ is the XOR operator; when performing an XOR operation on two binary sequences of equal length, the result is 0 if the bits in the same position are the same, and 1 if they are different; IV stands for Initialization Vector, which is a randomly generated bit sequence that is XORed with the first plaintext block to ensure that even if the same plaintext is encrypted multiple times, different ciphertexts will be generated. In CBC mode, the length of IV is the same as the block size of AES, which is 128 bits. Pi represents the i-th block in the plaintext data; Ci represents the i-th block in the ciphertext data; Pi′ represents the intermediate plaintext block in the decryption process, that is, the plaintext block obtained by decryption before the XOR operation; n represents the total number of plaintext or ciphertext blocks.

6. The method for backing up power plant data nodes based on big data according to claim 1, characterized in that: The step S7 specifically includes: S7-1. Locate the insertion point: According to the timestamp of the new version, determine its correct position in the ordered hash chain; this step involves the following operations: Compare timestamps: compare the timestamp of the new version with the timestamp of the existing nodes in the chain; Determine order: find the appropriate position to ensure the timing of the chain; S7-2. Insert a new node: Insert a new node containing the new version hash value into the ordered hash chain. The specific steps are as follows: Create a new node: construct a new node, including the hash value and version metadata of the new version; Update the chain structure: insert a new node into the chain, and adjust the pointer or link to maintain the integrity of the chain; Preserve chain state: ensure that the latest state of the ordered hash chain is saved to stable storage in case of system failure; S7-3. Verify the integrity of the chain: After inserting a new node, perform the following verification steps to ensure the integrity of the chain: Verify node links: Make sure the new node is correctly linked to the previous and next nodes; Calculate the hash of the chain: Optionally, calculate the hash value of the entire chain to provide a quick way to verify the integrity of the chain.

7. The method for backing up power plant data nodes based on big data according to claim 1, characterized in that: In step S4, when building a stable and reliable backup environment, a network optimization algorithm is used to configure network bandwidth, storage space and server resources; first, the optimization goal is defined to minimize the backup time or maximize resource utilization; then, the chromosome encoding of the genetic algorithm is designed, and the optimal resource configuration solution is iteratively solved through selection, crossover and mutation operations; in addition, the backup environment is securely reinforced, including setting up firewalls, access control lists and data encryption transmission.

8. The method for backing up power plant data nodes based on big data according to claim 1, characterized in that: In step S5, when deep data cleaning is performed before backup, a data mining algorithm, including an association rule mining algorithm, is used to optimize data quality; first, the data in the power plant data node is preprocessed, including removing null values ​​and correcting incorrect formats; then, a transaction database is constructed, and support and confidence thresholds are set, and the potential relationship in the data is found through the association rule mining algorithm to identify invalid, erroneous and duplicate data; according to the mining results, the data is cleaned and the data structure is optimized; In step S8, the hash values ​​of the files are first calculated on the source data and the backup server respectively, and then the hash values ​​are compared to identify the differences; then, only the difference data blocks are transmitted.

9. The method for backing up power plant data nodes based on big data according to claim 1, characterized in that: In step S9, when performing incremental backup regularly, a Delta backup algorithm is used to back up the changed data; first, a data change log is recorded to identify the changed data blocks; Then, the difference of these data blocks is calculated and the differential data is transmitted to the backup server. When restoring data, the differential data is merged with the full backup to restore the complete data set. This process ensures the timeliness of the backup and the consistency of the data, while reducing the impact of the backup on the business system.

10. A power plant data node backup system based on big data, characterized in that: The system runs the power plant data node backup method based on big data as described in any one of claims 1 to 9.

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