Electric power data analysis and encryption method and system and storage medium

Abstract

The invention discloses an electric power data analysis and encryption method and system and a storage medium, and relates to the technical field of electric power data. Scanning and processing the electric power data; obtaining a database, converting the power data, and obtaining readable data; scanning the readable data, and disordering the readable data by using a random algorithm to obtain disordered data; acquiring an encrypted public key and an encrypted private key according to the disordered data; encrypting the disordered data according to the encryption public key and the encryption private key; a random operator of a random algorithm is extracted, an AES algorithm is utilized to encrypt the random operator, a symmetric encryption mode and an asymmetric encryption mode do not need complex hardware support or a special software environment, and a generated key is compatible with an existing encryption standard and protocol, so that the method can be seamlessly integrated with other encryption systems; and the overall efficiency and effect of data protection are improved, so that the overall data processing capability of the system is ensured.

Description

Technical Field

[0001] The present invention relates to the technical field of power data, and specifically relates to a power data analysis and encryption method, system and storage medium. Background Art

[0002] Power data is a digital information collection reflecting the operating state of the entire life cycle of the power system, covering all-chain data elements from power generation, transmission and distribution to terminal consumption. It not only includes basic indicators such as power generation, power consumption, and load curves, but also contains multi-dimensional data such as grid equipment operation parameters, market transaction prices, and user behavior characteristics. As the core asset of the energy digital transformation, power data can achieve goals such as precise grid dispatching, equipment health management, new energy consumption optimization, and user energy efficiency improvement through analysis and application, and is an important foundation for building a new power system. With the full coverage of smart meters and the popularization of edge computing technology, power data is accelerating its evolution from a traditional monitoring tool to the "digital oil" of the energy economy.

[0003] Since in the digital economy era, the value density of power data is increasing at a rate of 30% per year, it is necessary to encrypt power data. The so-called data encryption technology refers to converting an information through an encryption key and an encryption function into meaningless ciphertext, while the recipient restores this ciphertext into plaintext through a decryption function and a decryption key. Encryption technology is the cornerstone of network security technology.

[0004] Existing technologies often need to sacrifice security to a certain extent while pursuing encryption performance. High-performance encryption algorithms may require more computing resources and storage space, while algorithms with higher security may lead to an increase in the delay of the encryption and decryption processes, thus reducing security. Therefore, the present invention proposes a power data analysis and encryption method, system and storage medium. Summary of the Invention

[0005] To solve the above technical problems, a power data analysis and encryption method, system and storage medium are provided, which solve the problem of reduced security caused by pursuing encryption performance.

[0006] To achieve the above object, the technical solution adopted by the present invention is as follows:

[0007] A power data analysis and encryption method includes:

[0008] Obtain power data;

[0009] Scan the power data and perform processing;

[0010] Obtain a database, convert the power data, and obtain readable data;

[0011] Scan the readable data, shuffle the readable data using a random algorithm, and obtain messy data;

[0012] Based on the messy data, obtain the encryption public key and the encryption private key;

[0013] Based on the encryption public key and the encryption private key, encrypt the messy data;

[0014] Extract the random operator of the random algorithm, and encrypt the random operator using the AES algorithm.

[0015] Preferably, the scanning and processing of the power data include the following steps:

[0016] Scan the power data, obtain the abnormal data in the power data and mark it;

[0017] Obtain the historical record and process it;

[0018] Extract multiple analysis data in the processed historical record that have the same conditions as the abnormal data;

[0019] Obtain the mean value of the multiple analysis data, and interpolate the abnormal data;

[0020] Among them, the mean value calculation formula is:

[0021]

[0022] In the formula, is the mean value, and E is the analysis data.

[0023] Preferably, the obtaining and processing of the historical record include the following steps:

[0024] Obtain the historical record;

[0025] Scan the historical record, and obtain the deviation data in the historical record;

[0026] Extract multiple filling data in the historical record that have the same conditions as the deviation data;

[0027] Construct a rectangular coordinate system based on the multiple filling data;

[0028] Adopt point-by-point comparison to obtain the data to be filled that is closer to the deviation data;

[0029] The data to be filled fills the deviation data.

[0030] Preferably, the steps of obtaining the database, converting the power data, and obtaining the readable data include:

[0031] Obtain the database;

[0032] Extract the comparison table of the database;

[0033] Compare the power data with the control table to obtain readable data.

[0034] Preferably, the steps include scanning the readable data, using a random algorithm to shuffle the readable data to obtain messy data as follows:

[0035] Scan the readable data;

[0036] Average the readable data into multiple data intervals;

[0037] Assign values to the bits within the data intervals according to the data interval sorting;

[0038] Use a random algorithm to generate random operators with the same number as the bits within the data intervals;

[0039] Sort the bits within the data intervals according to the size of the random algorithm to obtain messy data.

[0040] Preferably, the steps include obtaining an encryption public key and an encryption private key according to the messy data as follows:

[0041] Extract multiple messy data;

[0042] Respectively convert multiple messy data into decimal quantization data;

[0043] Randomly construct two prime numbers;

[0044] Respectively obtain the modulus corresponding to the quantization data according to the two prime numbers;

[0045] According to the Euler's totient function, combine the two prime numbers to obtain the Euler's totient function value;

[0046] According to the Euler's totient function value, obtain the public key exponent;

[0047] According to the public key exponent and the Euler's totient function value, obtain the private key exponent;

[0048] According to the public key exponent, the private key exponent and the modulus, obtain the encryption public key and the encryption private key;

[0049] Among them, the calculation formula of the Euler's totient function value is:

[0050] (q - 1)(p - 1) = T;

[0051] Among them, the calculation formula of the modulus is:

[0052] N = pq;

[0053] Among them, the specific composition of the encryption public key and the encryption private key:

[0054] Encryption public key: (E, N);

[0055] Encryption private key: (D, N);

[0056] Wherein, q and p are two selected prime numbers, T is the Euler's totient function value, E is the public key exponent, D is the private key exponent, and N is the modulus.

[0057] Preferably, the method for encrypting messy data based on the encryption public key and the encryption private key includes the following steps:

[0058] Extract multiple quantization data respectively;

[0059] Raise the quantization data to a power according to the public key exponent to obtain the power exponent;

[0060] According to the power exponent, combine the modulus to obtain the corresponding remainder;

[0061] Replace the quantization data according to the remainder, thereby completing the encryption of the messy data.

[0062] Preferably, the method for encrypting the random operator of the random algorithm using the AES algorithm includes the following steps:

[0063] Extract the random operator in the random algorithm;

[0064] Convert the random operator into 128-bit byte data;

[0065] According to the byte data, perform an exclusive OR operation on the byte data in combination with CTR, thereby encrypting the random operator.

[0066] Preferably, a power data analysis encryption system is proposed for implementing the above power data analysis encryption method, including:

[0067] Control module: The control module is used to control the data transmission in the system;

[0068] Data acquisition module: The data acquisition module is used to acquire power data;

[0069] Data analysis module: The data analysis module is used to analyze and process power data;

[0070] Data conversion module: The data conversion module is used to convert power data into computer language;

[0071] Random algorithm module: The random algorithm module is used to generate a random operator;

[0072] AES algorithm encryption module: The AES algorithm encryption module is used to encrypt the random operator;

[0073] Encryption module: The encryption module is used to encrypt the transmitted data.

[0074] Further, a non-transitory computer-readable storage medium storing computer instructions is provided, and the computer instructions are used to cause the computer to execute the above-mentioned power data analysis and encryption method.

[0075] Compared with the prior art, the advantages of the present invention are as follows: The present invention shuffles power data through a random algorithm, encrypts the messy data through an asymmetric encryption method, and encrypts the random operator through a symmetric encryption method, thereby realizing triple encryption of power data. Since the readable data after the conversion of power data is regionally divided, and due to the adoption of the random algorithm, the encryption of the messy data is enhanced. While ensuring the efficient operation of the system, the security during the data processing and transmission is ensured, avoiding the situation of sacrificing security for the pursuit of a single performance index. Moreover, neither the symmetric encryption method nor the asymmetric encryption method requires complex hardware support or a special software environment, and the generated keys are compatible with existing encryption standards and protocols, enabling the method to be seamlessly integrated with other encryption systems, improving the overall efficiency and effect of data protection, and thus ensuring the overall data processing ability of the system. BRIEF DESCRIPTION OF THE DRAWINGS

[0076] Figure 1 It is a schematic flow chart of steps S100 - S700 in a power data analysis and encryption method, system and storage medium proposed by the present invention;

[0077] Figure 2 It is a schematic flow chart of steps S201 - S204 in a power data analysis and encryption method, system and storage medium proposed by the present invention;

[0078] Figure 3 It is a schematic flow chart of steps S2021 - S2026 in a power data analysis and encryption method, system and storage medium proposed by the present invention;

[0079] Figure 4 It is a schematic flow chart of steps S301 - S303 in a power data analysis and encryption method, system and storage medium proposed by the present invention;

[0080] Figure 5 It is a schematic flow chart of steps S401 - S405 in a power data analysis and encryption method, system and storage medium proposed by the present invention;

[0081] Figure 6 It is a schematic flow chart of steps S501 - S508 in a power data analysis and encryption method, system and storage medium proposed by the present invention;

[0082] Figure 7 It is a schematic flow chart of steps S601 - S604 in a power data analysis and encryption method, system and storage medium proposed by the present invention;

[0083] Figure 8 Flow diagram of steps S701 - S703 in a power data analysis encryption method, system and storage medium proposed by the present invention;

[0084] Figure 9 Block diagram of a power data analysis encryption method, system and storage medium proposed by the present invention. Detailed implementation manners

[0085] The following description is used to disclose the present invention so that those skilled in the art can implement the present invention. The preferred embodiments in the following description are only examples, and those skilled in the art can think of other obvious variations.

[0086] Referring to Figures 1-9 As shown, a power data analysis encryption method includes:

[0087] S100. Obtain power data;

[0088] S200. Scan the power data and perform processing;

[0089] S300. Obtain a database, convert the power data, and obtain readable data;

[0090] S400. Scan the readable data, shuffle the readable data using a random algorithm, and obtain messy data;

[0091] S500. Obtain an encryption public key and an encryption private key based on the messy data;

[0092] S600. Encrypt the messy data based on the encryption public key and the encryption private key;

[0093] S700. Extract the random operator of the random algorithm and encrypt the random operator using the AES algorithm;

[0094] Those skilled in the art can understand that by processing power data, ensuring the accuracy of power data, converting power data into readable data that can be recognized by a computer, scanning and evenly dividing the readable data, and shuffling the data intervals through a random operator, this is the first layer of encryption. By shuffling the data, the computing power required for brute-force cracking of the data is increased. Then, the messy data is encrypted using an encryption public key and an encryption private key, which is the second layer of encryption. The basic process of encrypting transmission information using an asymmetric encryption algorithm is as follows: Party A first generates a pair of keys and takes one of them as the public key; Party B, who obtains the public key, then uses this key to encrypt the information to be encrypted and sends it to Party A; Party A then uses the other corresponding private key to decrypt the encrypted information, thus realizing the transmission of confidential data. The encryption public key can be publicly distributed, and the encryption private key is saved by the user himself / herself without the need to exchange keys before communication, reducing the risk of being attacked during the transmission process and ensuring the confidentiality of data transmission during the data transmission. By using symmetric encryption for the random operator, since the mathematical operations of symmetric encryption are relatively simple and the efficiency of processing a large amount of data is high, it is thus the preferred encryption method for the random operator. Through the triple encryption method, the power data is securely protected.

[0095] [[ID=,3]]As Figure 2 shown, it includes scanning the power data and performing the following steps for processing:

[0096] S201. Scan the power data, obtain the abnormal data in the power data and mark it;

[0097] S202. Obtain the historical records and process them;

[0098] S203. Extract multiple analysis data in the processed historical records that have the same conditions as the abnormal data;

[0099] S204. Obtain the mean value of the multiple analysis data and perform interpolation on the abnormal data;

[0100] Among them, the mean value calculation formula is:

[0101]

[0102] In the formula, is the mean value, and E is the analysis data;

[0103] Those skilled in the art can understand that the historical record contains past data and events, and this information is crucial for understanding and processing anomalies in current data. By obtaining the historical record and processing it, useful information can be extracted. From the processed historical record, analytical data with the same conditions as the current anomalous data can be extracted. These data have characteristics or patterns similar to the anomalous data. By calculating the mean of multiple pieces of analytical data, a relatively stable and reliable reference value can be obtained. The reference value can be used to interpolate the anomalous part in the current data, thereby correcting errors or missing values in the data. The interpolated data is more complete and accurate.

[0104] As Figure 3 shown, obtaining the historical record and processing it include the following steps:

[0105] S2021. Obtain the historical record;

[0106] S2022. Scan the historical record to obtain the deviation data in the historical record;

[0107] S2023. Extract multiple filling data with the same conditions as the deviation data from the historical record;

[0108] S2024. Construct a rectangular coordinate system based on multiple filling data;

[0109] S2025. Use point-by-point comparison to obtain the data to be filled that is close to the deviation data;

[0110] S2026. Use the data to be filled to fill the deviation data;

[0111] Those skilled in the art can understand that by comprehensively scanning the historical record, the aim is to identify deviations or abnormal points in the historical data. These deviation data may be caused by reasons such as equipment failures, measurement errors, or special events. These filling data have similar characteristics or conditions to the deviation data, so they can be used as candidate data to fill the deviation data. By constructing a rectangular coordinate system, in order to more intuitively compare and analyze the similarity between the filling data and the deviation data. In this coordinate system, a scatter plot or line graph of the filling data and the deviation data can be drawn. In the rectangular coordinate system, by comparing the filling data and the deviation data point by point, the filling data points that are most similar to the deviation data can be found. These similar filling data points can be used as the data to be filled to replace or correct the deviation data. By replacing or correcting the deviation data, the filled data is made to better conform to the actual situation.

[0112] As Figure 4 shown, it includes the following steps: obtaining a database, converting power data, and obtaining readable data.

[0113] S301. Obtain the database;

[0114] S302. Extract the comparison table of the database;

[0115] S303. Compare the power data with the comparison table to obtain readable data;

[0116] Those skilled in the art can understand that the specific Python code is as follows:

[0117]

[0118]

[0119] The database usually contains a large amount of standard data, rules or mapping tables. By comparing the comparison table in the database with the power data, the power data is converted into readable data that can be read by a computer, making subsequent data analysis and processing more convenient and accurate.

[0120] Such as Figure 5 shown, including scanning the readable data, using a random algorithm to scramble the readable data to obtain messy data, the following steps:

[0121] S401. Scan the readable data;

[0122] S402. Evenly divide the readable data into multiple data intervals;

[0123] S403. Assign values to the bits within the data interval according to the data interval sorting;

[0124] S404. Use a random algorithm to generate random operators with the same number as the number of bits within the data interval;

[0125] S405. Sort the bits within the data interval according to the size of the random algorithm to obtain messy data;

[0126] Those skilled in the art can understand that since the readable data is binary, the data is divided into multiple data intervals, and each interval is independently processed and analyzed. By assigning values to different 0 / 1 positions within the data interval and re - sorting the data within the data interval according to these operators, the randomness and unpredictability of the data can be significantly increased. Through sorting and assignment, a false ordered structure can be established for the data within the data interval, so as to meet different data encryption or obfuscation requirements. This method is applicable to various types of data and scenarios. Whether it is text data, numerical data or image data, similar methods can be used for division, sorting, assignment and encryption operations.

[0127] Such as Figure 6 shown, including obtaining the encryption public key and the encryption private key based on the messy data, the following steps:

[0128] S501. Extract multiple messy data;

[0129] S502. Convert multiple messy data into decimal quantization data respectively;

[0130] S503. Randomly construct two prime numbers;

[0131] S504. Obtain the modulus of the corresponding quantization data according to the two prime numbers respectively;

[0132] S505. Obtain the Euler's totient function value according to the Euler's totient function, combining the two prime numbers;

[0133] S506. Obtain the public key exponent according to the Euler's totient function value;

[0134] S507. Obtain the private key exponent according to the public key exponent and the Euler's totient function value;

[0135] S508. Obtain the encryption public key and the encryption private key according to the public key exponent, the private key exponent and the modulus;

[0136] Among them, the calculation formula of the Euler's totient function value is:

[0137] (q - 1)(p - 1) = T;

[0138] Among them, the calculation formula of the modulus is:

[0139] N = pq;

[0140] Among them, the specific composition of the encryption public key and the encryption private key:

[0141] Encryption public key: (E, N);

[0142] Encryption private key: (D, N);

[0143] In the formula, q and p are the two prime numbers selected respectively, T is the Euler's totient function value, E is the public key exponent, D is the private key exponent, and N is the modulus;

[0144] Those skilled in the art can understand that by converting messy data into decimal quantization data, the data can be subjected to subsequent mathematical operations in a standardized form. Prime numbers play an important role in encryption algorithms because their mathematical properties make them an ideal choice for generating secure keys. Using two selected prime numbers, the modulus of the corresponding quantization data is calculated respectively. The modulus is a key parameter in the encryption algorithm, which determines the range of the encrypted data and affects the strength and security of the encryption. According to the definition of the Euler's totient function, combined with the two selected prime numbers, the value of the Euler's totient function is calculated. The value of the Euler's totient function is used in the encryption algorithm to determine the public key exponent and the private key exponent. Based on the value of the Euler's totient function, a suitable public key exponent is selected. The public key exponent is part of the encryption public key. Using the public key exponent and the value of the Euler's totient function, the private key exponent is calculated. Combining the public key exponent, the private key exponent and the modulus, the encryption public key and the encryption private key are generated. These two pairs of keys are the core of the encryption and decryption processes, ensuring the confidentiality and integrity of the data. Each step of this method is based on mathematical operations and algorithms, without the need for complex hardware support or special software environments, and the generated encryption public key and private key can be compatible with existing encryption standards and protocols, enabling this method to be seamlessly integrated with other encryption systems, improving the overall efficiency and effectiveness of data protection.

[0145] As Figure 7 shown, it includes the following steps of encrypting messy data according to the encryption public key and the encryption private key:

[0146] S601. Extract multiple quantization data respectively;

[0147] S602. Raise the quantization data to the power according to the public key exponent to obtain the power exponent;

[0148] S603. Combine the power exponent with the modulus to obtain the corresponding remainder;

[0149] S604. Replace the quantization data according to the remainder, thereby completing the encryption of the messy data;

[0150] Those skilled in the art can understand that exponentiation is an important step in encryption algorithms. It generates an intermediate result by performing mathematical operations on data and a public key exponent, which will be used in subsequent encryption processes. In encryption algorithms, modulo operation is a common operation used to limit the range of encryption results, making the encryption results more difficult to predict and crack. The substitution operation is the last step of the encryption process, which converts the original plaintext data into ciphertext data, making it impossible for unauthorized personnel to easily read and understand the content of the data. Although the encryption and decryption processes involve complex mathematical operations, modern computers and algorithm optimizations make these operations relatively efficient in practical applications. Moreover, public key encryption algorithms have clear mathematical bases and implementation steps, making them easy to be programmed and integrated into various applications.

[0151] As Figure 8 shown, it includes extracting the random operator of the random algorithm and encrypting the random operator using the AES algorithm with the following steps:

[0152] S701. Extract the random operator in the random algorithm;

[0153] S702. Convert the random operator into 128-bit byte data;

[0154] S703. According to the byte data, perform an XOR operation on the byte data in combination with CTR to encrypt the random operator;

[0155] Those skilled in the art can understand that identifying and extracting the random operator from the random algorithm is the starting point of the encryption process. Converting the extracted random operator into 128-bit byte data of a fixed length ensures the length consistency of the encrypted data, facilitating subsequent encryption operations and processing. Using the counter mode, i.e., CTR, to perform an XOR operation on the converted 128-bit byte data to achieve encryption. The CTR mode is a stream cipher mode. By combining the counter value with the key to generate a pseudo-random byte stream, and then performing an XOR operation with the plaintext to obtain the ciphertext. The encryption method combining the CTR mode with the random operator provides a high level of security. Due to the randomness and unpredictability of the random operator, as well as the pseudo-random byte stream generation mechanism of the CTR mode, the encrypted data is difficult to be cracked. The XOR operation is a very fast encryption means. Combining with the stream cipher characteristics of the CTR mode, the encryption process can be carried out efficiently and is suitable for the rapid encryption of a large amount of data. Both the CTR mode and the XOR operation are relatively simple encryption means, which are easy to be implemented in hardware and software, reducing the threshold of encryption technology.

[0156] As Figure 9 shown, a power data analysis encryption system is proposed to implement the above power data analysis encryption method, including:

[0157] Control module: The control module is used to control data transmission within the system;

[0158] Data acquisition module: The data acquisition module is used to acquire power data;

[0159] Data analysis module: The data analysis module is used to analyze and process power data;

[0160] Data conversion module: The data conversion module is used to convert power data into computer language;

[0161] Random algorithm module: The random algorithm module is used to generate random operators;

[0162] AES algorithm encryption module: The AES algorithm encryption module is used to encrypt random operators;

[0163] Encryption module: The encryption module is used to encrypt transmitted data.

[0164] Furthermore, a non-transitory computer-readable storage medium storing computer instructions is provided, and the computer instructions are used to cause the computer to execute the above-mentioned power data analysis and encryption method.

[0165] In summary, the advantages of the present invention are as follows: The power data is shuffled through a random algorithm, and the messy data is encrypted by an asymmetric encryption method. At the same time, the random operator is encrypted by a symmetric encryption method, so as to achieve triple encryption of power data. Since the readable data after the conversion of power data is regionally divided, and due to the adoption of the random algorithm, the encryption of the messy data is enhanced. While ensuring the efficient operation of the system, the security in the data processing and transmission process is ensured, avoiding the situation of sacrificing security for the pursuit of a single performance index. Moreover, both the symmetric encryption method and the asymmetric encryption method do not require complex hardware support or special software environments, and the generated keys are compatible with existing encryption standards and protocols, so that this method can be seamlessly integrated with other encryption systems, improving the overall efficiency and effect of data protection, and thus ensuring the overall data processing ability of the system.

[0166] The above shows and describes the basic principles, main features and advantages of the present invention. Those skilled in the art of this industry should understand that the present invention is not limited by the above embodiments. What is described in the above embodiments and the specification is only the principle of the present invention. Without departing from the spirit and scope of the present invention, the present invention will have various changes and improvements, and these changes and improvements all fall within the scope of the present invention claimed. The scope of protection claimed by the present invention is defined by the appended claims and their equivalents.

Claims

1. A power data analysis and encryption method, characterized in that, Including: Obtain power data; Scan the power data and process it; Obtain a database, convert the power data, and obtain readable data; Scan the readable data, shuffle the readable data using a random algorithm, and obtain messy data; Based on the messy data, obtain an encryption public key and an encryption private key; Based on the encryption public key and the encryption private key, encrypt the messy data; Extract the random operator of the random algorithm and encrypt the random operator using the AES algorithm.

2. The power data analysis and encryption method according to claim 1, characterized in that: The scanning and processing of the power data includes the following steps: Scan the power data, obtain and mark the abnormal data in the power data; Obtain the historical records and process them; Extract multiple analysis data in the processed historical records with the same conditions as the abnormal data; Obtain the average value of the multiple analysis data and perform interpolation on the abnormal data; Among them, the average value calculation formula is: In the formula, is the mean value, and E is the analyzed data.

3. A power data analysis and encryption method according to claim 2, characterized in that: The obtaining and processing of the historical records includes the following steps: Obtain the historical records; Scan the historical records and obtain the deviation data in the historical records; Extract multiple filling data in the historical records with the same conditions as the deviation data; Construct a rectangular coordinate system based on the multiple filling data; Adopt point-by-point comparison to obtain the data to be filled closer to the deviation data; The data to be filled fills the deviation data.

4. A power data analysis and encryption method according to claim 3, characterized in that: The steps of obtaining a database, converting the power data, and obtaining readable data include: Obtain a database; Extract the comparison table of the database; Compare the power data with the comparison table to obtain readable data.

5. A power data analysis and encryption method according to claim 4, characterized in that: The steps of scanning the readable data, shuffling the readable data using a random algorithm, and obtaining messy data include: Scan the readable data; Evenly divide the readable data into multiple data intervals; Assign values to the bits within the data intervals according to the data interval sorting; Generate random operators with the same number as the number of bits within the data intervals using a random algorithm; Sort the bits within the data intervals according to the size of the random algorithm to obtain messy data.

6. A power data analysis and encryption method according to claim 5, characterized in that: The steps of obtaining an encryption public key and an encryption private key based on the messy data include: Extract multiple messy data; Respectively convert the multiple messy data into decimal quantization data; Randomly construct two prime numbers; Obtain the modulus corresponding to the quantization data according to the two prime numbers respectively; According to the Euler's totient function, combine the two prime numbers to obtain the Euler's totient function value; According to the Euler's totient function value, obtain the public key exponent; According to the public key exponent and the Euler's totient function value, obtain the private key exponent; According to the public key exponent, the private key exponent, and the modulus, obtain the encryption public key and the encryption private key; Among them, the calculation formula of the Euler's totient function value is: (q - 1)(p - 1) = T; Among them, the calculation formula of the modulus is: N = pq; Among them, the specific composition of the encryption public key and the encryption private key: Encryption public key: (E, N); Encryption private key: (D, N); In the formula, q and p are the two prime numbers selected respectively, T is the Euler's totient function value, E is the public key exponent, D is the private key exponent, and N is the modulus.

7. A power data analysis and encryption method according to claim 6, characterized in that: The steps of encrypting the messy data based on the encryption public key and the encryption private key include: Respectively extract multiple quantization data; Raise the quantization data to the power according to the public key exponent to obtain the power exponent; According to the power exponent, combine the modulus to obtain the corresponding remainder; Replace the quantization data according to the remainder, thereby completing the encryption of the messy data.

8. A power data analysis and encryption method according to claim 6, characterized in that: The steps include extracting the random operator of the random algorithm and encrypting the random operator using the AES algorithm: Extract the random operator in the random algorithm; Convert the random operator into 128-bit byte data; According to the byte data, perform an exclusive OR operation on the byte data in combination with CTR, thereby encrypting the random operator.

9. A power data analysis encryption system for implementing the power data analysis encryption method as described in claims 1-8, characterized in that, It includes: Control module: The control module is used to control the data transmission within the system; Data acquisition module: The data acquisition module is used to collect power data; Data analysis module: The data analysis module is used to analyze and process power data; Data conversion module: The data conversion module is used to convert power data into computer language; Random algorithm module: The random algorithm module is used to generate random operators; AES algorithm encryption module: The AES algorithm encryption module is used to encrypt random operators; Encryption module: The encryption module is used to encrypt the transmitted data.

10. A non-transitory computer-readable storage medium storing computer instructions, characterized in that, The computer instructions are used to cause the computer to execute the method according to any one of claims 1-8.

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