Communication data encryption transmission method, device, equipment and storage medium

Abstract

The present invention relates to an encrypted transmission method, device, equipment and storage medium for communication data. The method: performing analog-to-digital conversion processing on a temperature signal collected by a power supply temperature sensor to obtain digital power supply temperature data; performing data encryption on the digital power supply temperature data to obtain encrypted power supply temperature data; decrypting the encrypted power supply temperature data using a preset LZW algorithm to obtain decrypted power supply temperature data; generating a power supply temperature change curve based on the decrypted power supply temperature data, and transmitting the power supply temperature change curve to a communication terminal for data display. The implementation of the present invention can efficiently process and transmit a large amount of real-time power supply temperature data while ensuring high security.

Description

Technical Field

[0001] The present invention relates to the technical field of encrypted transmission of communication data, and in particular to an encrypted transmission method, device, equipment and storage medium for communication data. Background Art

[0002] As a key parameter for evaluating the operating status of equipment and preventing failures, the secure transmission and accurate analysis of power supply temperature data are particularly important. However, traditional power supply temperature data transmission methods often have problems such as insufficient security, weak anti-interference ability, and low data compression efficiency. These problems not only increase the risk of data leakage, but may also lead to the failure to detect temperature anomalies in time, affecting the normal operation and service life of the equipment.

[0003] In addition, most of the existing power supply temperature data encryption methods use a single encryption algorithm, which is difficult to cope with increasingly complex network attacks. At the same time, these methods often cause large computational overhead when processing large amounts of real-time temperature data, affecting the real-time response capability of the system. On the other hand, during the data decryption and analysis process, due to the lack of in-depth understanding and utilization of temperature data characteristics, it is often impossible to effectively restore the accurate temperature change trend, thus affecting subsequent equipment status monitoring and early warning. Summary of the invention

[0004] The main purpose of the present invention is to provide a method, device, equipment and storage medium for encrypting and transmitting communication data, so as to achieve efficient processing and transmission of a large amount of real-time power supply temperature data while ensuring high security.

[0005] To achieve the above object, the present invention provides a method for encrypting and transmitting communication data, comprising the following steps:

[0006] Perform analog-to-digital conversion on the temperature signal collected by the power supply temperature sensor to obtain digital power supply temperature data;

[0007] Encrypting the digital power supply temperature data to obtain encrypted power supply temperature data;

[0008] Decrypting the encrypted power supply temperature data by using a preset LZW algorithm to obtain decrypted power supply temperature data;

[0009] A power supply temperature variation curve is generated according to the decrypted power supply temperature data, and the power supply temperature variation curve is transmitted to a communication terminal for data display.

[0010] The present invention also provides a communication data encryption transmission device, comprising:

[0011] A conversion unit, used to perform analog-to-digital conversion on the temperature signal collected by the power supply temperature sensor to obtain digital power supply temperature data;

[0012] An encryption unit, used for encrypting the digital power supply temperature data to obtain encrypted power supply temperature data;

[0013] A decryption unit, used to decrypt the encrypted power supply temperature data by using a preset LZW algorithm to obtain decrypted power supply temperature data;

[0014] The transmission unit is used to generate a power supply temperature change curve according to the decrypted power supply temperature data, and transmit the power supply temperature change curve to the communication terminal for data display.

[0015] The present invention also provides a computer device, comprising a memory and a processor, wherein the memory stores a computer program, and the processor implements the steps of any one of the above methods when executing the computer program.

[0016] The present invention also provides a computer-readable storage medium on which a computer program is stored. When the computer program is executed by a processor, the steps of any of the above-mentioned methods are implemented.

[0017] In summary, the technical solution provided by the present invention greatly enhances the security of power supply temperature data by adopting multiple encryption technologies, including differential coding, Huffman coding, check code encryption and symmetric encryption, and effectively prevents data from being illegally intercepted or tampered during transmission. By combining differential coding and Huffman coding, the compression rate of power supply temperature data is significantly improved, the bandwidth required for data transmission is reduced, and the storage cost is reduced. Through Kalman filtering, the noise and interference in the power supply temperature data are effectively removed, and the reliability and accuracy of the data are improved. The use of time series splitting and continuity recognition technology can effectively handle the packet loss problem that may occur during data transmission, ensuring the integrity of the power supply temperature data. Combined with the LZW algorithm and the attention mechanism, the time and space characteristics of the power supply temperature data are fully utilized in the decryption process, and the accuracy of decryption is improved. By extracting extreme points and analyzing time intervals of the decrypted temperature data, the abnormal changes in the power supply temperature can be more accurately identified, which is conducive to timely discovery of potential equipment failures. By constructing a multi-level temperature change curve, the change trend of the power supply temperature is intuitively displayed, which is convenient for managers to quickly grasp the operating status of the equipment. The present invention can be flexibly applied to various power management systems without requiring substantial modification of existing hardware devices, and has good compatibility and scalability. BRIEF DESCRIPTION OF THE DRAWINGS

[0018] Figure 1 This is a schematic diagram of the steps of a method for encrypting and transmitting communication data in one embodiment of the present invention;

[0019] Figure 2It is a structural block diagram of a communication data encryption transmission device in one embodiment of the present invention;

[0020] Figure 3 It is a schematic block diagram of the structure of a computer device according to an embodiment of the present invention.

[0021] The realization of the purpose, functional features and advantages of the present invention will be further explained in conjunction with embodiments and with reference to the accompanying drawings. DETAILED DESCRIPTION

[0022] 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 intended to limit the present invention.

[0023] Reference Figure 1 , this embodiment provides a method for encrypting and transmitting communication data, comprising the following steps:

[0024] S1, performing analog-to-digital conversion on the temperature signal collected by the power supply temperature sensor to obtain digital power supply temperature data;

[0025] Among them, the power supply temperature sensor collects the temperature signal generated by the power supply device during operation. A temperature sensor is a device that converts physical temperature into a corresponding voltage signal or current signal, such as a thermocouple, thermistor and other types of sensors, which converts the temperature change of the surrounding environment into an electrical signal proportional to the temperature. The electrical signal is usually an analog signal, which is characterized by being continuous and smooth, and changes linearly or nonlinearly with the change of temperature. The process of converting the analog temperature signal collected by the sensor into a digital signal is called analog-to-digital conversion. The analog-to-digital conversion process is implemented by a dedicated analog-to-digital converter chip. The function of the analog-to-digital converter is to discretize the analog signal and quantize it into a digital signal with a specific number of bits, which is convenient for a computer or microprocessor to process. In the process of analog-to-digital conversion, the analog signal output by the sensor is sampled, and the continuous analog signal is periodically measured at a certain sampling frequency to obtain a series of discrete signal values. The sampling frequency satisfies the Nyquist sampling theorem, that is, the sampling frequency must be at least twice the highest frequency of the signal to avoid signal distortion and loss of information. After sampling is completed, the quantization process is performed. Quantization is to map the sampled value of the analog signal to a discrete digital value. Since the resolution of the analog-to-digital converter is limited, such as 8 bits, 10 bits, 12 bits, etc., the analog signal will be mapped to these limited values ​​after quantization. The higher the resolution, the higher the quantization accuracy, and the quantized digital signal can better approximate the original analog signal. During the quantization process, the amplitude of the analog signal will be assigned to different digital intervals, which are determined by the number of bits of the analog-to-digital converter. Assuming an 8-bit ADC, the input signal is divided into 256 different quantization levels, and the corresponding digital signal is output. The quantized signal will enter the encoding stage. The encoding process is to convert the quantized signal value into binary code so that the computer can recognize and process it. The output of the analog-to-digital converter is usually a discrete, binary digital quantity, which represents the temperature information collected by the sensor, thereby realizing the transformation from analog signal to digital signal. The analog signal output by the sensor is appropriately preprocessed. Including amplification and filtering, the role of the amplifier is to amplify the weak voltage signal output by the sensor to the input range of the ADC, thereby ensuring the accuracy of the analog-to-digital conversion, and the filter is used to eliminate high-frequency noise in the temperature signal to avoid noise affecting the result of the analog-to-digital conversion and improve the signal-to-noise ratio.

[0026] S2, encrypting the digital power supply temperature data to obtain encrypted power supply temperature data;

[0027] Specifically, the digital power supply temperature data is subjected to Kalman filtering to obtain the filtered power supply temperature data. Kalman filtering is a recursive filtering technology that can effectively eliminate noise in temperature data and obtain a smoother and more accurate temperature value. The filtered power supply temperature data is time-series split, and the filtered power supply temperature data is divided into a number of small data segments, each of which represents a time segment of the temperature signal. By performing time-series continuity recognition on the data segments after time-series splitting, the corresponding time-series continuity feature coding is obtained, and the feature coding can describe the continuous change characteristics of the temperature data in time. The discontinuous time-series coding in the time-series continuity feature coding is extracted, and the filtered power supply temperature data is expanded according to the discontinuous time-series coding to obtain the expanded power supply temperature data, so that the data is more complete and continuous on the time axis. After completing the data expansion, the data segment label corresponding to the expanded power supply temperature data is matched, and the expanded data is filled into the original time-series split data segment based on the data segment label to obtain continuous filtered power supply temperature data. The continuous filtered power supply temperature data is differentially encoded to obtain the first encoded power supply temperature data. Differential coding is a data compression method that greatly reduces the amount of data and improves compression efficiency by recording the changes between data instead of the original data value. The differentially encoded data contains the temperature change information between each time period. The first coded power supply temperature data is Huffman encoded to obtain the second coded power supply temperature data. Huffman coding is a lossless data compression technology that uses variable-length coding to represent data. The more common data with higher frequency will be assigned shorter codes, while the less frequent parts will be assigned longer codes to achieve further data compression. Huffman coding can effectively reduce data redundancy and improve the efficiency of data storage and transmission. The second coded power supply temperature data is encrypted with a checksum to obtain the third coded power supply temperature data. The third coded power supply temperature data is symmetrically encrypted to obtain the final encrypted power supply temperature data. Symmetric encryption uses the same key to encrypt and decrypt data. This method has a higher encryption speed and lower computational overhead, and is suitable for real-time encrypted transmission of large-scale data. In this process, symmetric encryption can ensure the security of power supply temperature data during transmission, prevent unauthorized users from accessing and tampering with data, and thus protect the privacy and confidentiality of temperature data.

[0028] The continuous filtered power supply temperature data is time-sequentially sorted to obtain the sorted power supply temperature points. Ensure that the subsequent encoding operations are processed in time order so that the differential operation can reflect the change relationship of the temperature data on the time axis. The first power supply temperature point data in the sorted power supply temperature points is used as the first target power supply temperature data, and then based on the first target power supply temperature data, the sorted power supply temperature points are sequentially differentially calculated to obtain differential power supply temperature data. Differential calculation is a calculation method based on the difference between adjacent data points, which can reduce the redundant information of the original data. By encoding the change between adjacent temperature data, the data volume can be effectively compressed while retaining the trend information of temperature change. The continuous filtered power supply temperature data is differentially encoded for the first time according to the differential power supply temperature data and the first target power supply temperature data to generate initial differential encoding data. The process of the first differential encoding is to combine the differential calculation result with the first target temperature point to restore the complete encoding data. The initial differential encoding data is time-sequentially sorted to obtain the sorted encoded power supply temperature points. The second encoded power temperature point data in the sorted encoded power temperature points is used as the second target power temperature data, and the first encoded power temperature point data in the sorted encoded power temperature points is filled into the first sorted position of the sorted encoded power temperature points to obtain a mixed encoded power temperature point. Based on the second target power temperature data, differential temperature calculations are performed on the mixed encoded power temperature points in sequence to obtain differential encoded power temperature data. According to the differential encoded power temperature data and the second target power temperature data, the initial differential encoded data is differentially encoded again to obtain the first encoded power temperature data.

[0029] The first coded power supply temperature data is subjected to power supply temperature string recognition to obtain multiple power supply temperature strings. The continuous temperature data is segmented and identified according to certain rules, and the change sequence of the temperature data is represented in the form of a string, so that the original data becomes more structured. Statistical feature calculation is performed on multiple power supply temperature strings to obtain statistical feature data, including average power supply temperature value, high-frequency power supply temperature and low-frequency power supply temperature, so as to understand the overall distribution of temperature data and the frequency of occurrence of certain temperature values. The temperature difference calculation is performed on the high-frequency power supply temperature by the average power supply temperature value to obtain the first power supply temperature difference. Similarly, the temperature difference calculation is performed on the low-frequency power supply temperature by the average power supply temperature value to obtain the second power supply temperature difference. The temperature difference calculation helps determine the degree of deviation between different temperature intervals and the average temperature, so as to allocate appropriate encoding lengths for temperature values ​​of different frequencies. The difference between the high-frequency temperature point and the average temperature value is small, so its encoding character length is set shorter to facilitate the compression of high-frequency data. The difference between the low-frequency temperature point and the average temperature value is large, and a longer encoding character length needs to be allocated to ensure that these less frequent data points can also be correctly represented. By matching the first power supply temperature character string set corresponding to the high-frequency power supply temperature and the second power supply temperature character string set corresponding to the low-frequency power supply temperature, the power supply temperature character strings are classified according to their frequency characteristics, so as to assign appropriate encoding strategies to different data. The first encoding character length is set by the first power supply temperature difference, and the second encoding character length is set by the second power supply temperature difference to determine the encoding lengths of different temperature character strings. The first power supply temperature character string set is Huffman encoded based on the first encoding character length to obtain the first encoding character string. Similarly, the second power supply temperature character string set is Huffman encoded based on the second encoding character length to obtain the second encoding character string. Huffman encoding is a lossless compression encoding method that effectively reduces the overall length of the data by assigning variable-length codes to different data using different frequencies of occurrence. The high-frequency power supply temperature character string obtains a shorter code, thereby improving the compression efficiency of the overall data; while the low-frequency power supply temperature character string obtains a longer code to ensure the accuracy of the data. The first encoded power supply temperature data is fused by the first encoding character string and the second encoding character string to obtain the second encoded power supply temperature data. The high-frequency and low-frequency encoding character strings are merged together to form a complete encoding data set for subsequent transmission and storage.

[0030] The second coded power supply temperature data is hashed to obtain multiple hash values. The hash value calculation process is a one-way function operation based on an algorithm. By performing a hash operation on the data, a set of fixed-length outputs is generated. These hash values ​​can effectively represent the content of the second coded power supply temperature data. A random operation is performed on each hash value to obtain a random hash value corresponding to each hash value. Random operation is a step to introduce randomness, the purpose of which is to increase the unpredictability of the hash value so that there is no definite pattern between each hash value and its corresponding random hash value. The random operation involves some random number generators or random functions, the purpose of which is to add a random offset or disturbance to each hash value. The second coded power supply temperature data is encrypted with a check code by using the random hash value corresponding to each hash value to obtain the third coded power supply temperature data. The process of check code encryption is to add randomness to the original hash value, and to encrypt the entire coded power supply temperature data by combining the random hash value with the original hash value. The purpose of check code encryption is to ensure the integrity and security of data during transmission. By introducing the check code, the data is checked at the receiving end to verify whether an error or tampering has occurred in the data during transmission. The security is enhanced by using random hash values ​​for checksum encryption. The checksum encryption process protects each data segment. Even if some data segments are attacked during transmission, the receiving end can verify them through the checksum, find anomalies in the data, and take appropriate measures to deal with them.

[0031] S3, decrypting the encrypted power supply temperature data by using a preset LZW algorithm to obtain decrypted power supply temperature data;

[0032] It should be noted that the encrypted power supply temperature data is converted into an event stream, and the original encrypted data is converted into a series of discrete events that can represent temperature changes, reflecting the change state of the power supply temperature at different time points, and obtaining the power supply temperature change event stream. Event stream is a time series data structure that can describe the dynamic change of temperature over time. The power supply temperature change time attention feature is calculated for the power supply temperature change event stream to obtain the time attention feature. The introduction of the attention mechanism effectively improves the efficiency of the decryption process. By modeling the time attention of the temperature event, the model pays more attention to the key temperature change time points. At the same time, the power supply temperature change spatial attention feature is calculated for the power supply temperature change event stream to obtain the spatial attention feature. By calculating the spatial attention, the temperature change features at different spatial locations are effectively identified, such as the temperature fluctuations at different parts of the power supply system. The time weight of the power supply temperature change corresponding to the time attention feature is matched, and the spatial weight of the power supply temperature change corresponding to the spatial attention feature is matched. The matching process of the time weight and the space weight is to quantify the attention feature and assign specific weight values, so that feature extraction can be performed based on these weights during the decoding process. The time weight is used to emphasize those temperature changes that are significant on the time axis, while the space weight is used to identify the important temperature change positions in the spatial dimension. The significant features of the power supply temperature change event stream are extracted by time weight and space weight to obtain the significant features of the power supply temperature change. The decoding dictionary is constructed by the preset LZW algorithm for the significant features of the power supply temperature change to obtain a decoding dictionary set. LZW is a lossless compression algorithm that achieves data compression and decompression by constructing a dictionary. During the decryption process, the LZW algorithm constructs a decoding dictionary based on the significant features and learns the repeated patterns in the data by continuously updating the dictionary so that the original data can be efficiently restored during decoding. The construction of the decoding dictionary set is the core step of decryption. By learning the significant features and dynamically expanding the dictionary, the LZW algorithm effectively decodes the encrypted temperature data. The encrypted power supply temperature data is decrypted by the decoding dictionary set to finally obtain the decrypted power supply temperature data. LZW decoding uses the previously constructed dictionary set to gradually restore the encrypted power supply temperature data to the original temperature information.

[0033] S4, generating a power supply temperature change curve according to the decrypted power supply temperature data, and transmitting the power supply temperature change curve to a communication terminal for data display.

[0034] Specifically, the power supply temperature extreme points are extracted from the decrypted power supply temperature data to obtain multiple power supply temperature extreme points, and the highest and lowest temperatures that occur during the temperature change process are identified. These extreme points are key nodes of temperature change and represent that the temperature reaches a specific rise or fall limit. The decrypted power supply temperature data is analyzed for the time interval of stable power supply temperature change to obtain a first time interval. The stable power supply temperature change time interval refers to a period in which the temperature changes relatively stably within a certain time range. These intervals are shown as relatively smooth parts in the temperature curve. Through multiple power supply temperature extreme points, the decrypted power supply temperature data is analyzed for the power supply temperature mutation time interval to obtain a second time interval. The mutation time interval refers to a time period in which the temperature changes significantly in a short period of time. These changes are caused by changes in the load of the power supply, fluctuations in ambient temperature, or other external factors. By analyzing these mutation time intervals, abnormal conditions or sudden load changes that occur during the operation of the power supply are identified. The power supply temperature curve is constructed for the first time interval to obtain a first power supply temperature curve set. The first power supply temperature curve set is based on the data of the stable change time interval. By fitting and connecting the data of the stable section, the obtained curve part usually shows a smooth rising or falling trend. These curve sets reflect the change pattern of temperature in the stable stage and show the temperature characteristics of the power supply under normal working conditions. The power supply temperature change slope is calculated for the second time interval to obtain the change slope data, which quantifies the change speed of the temperature in the sudden change time interval. The size of the slope reflects the severity of the temperature change. Based on the change slope data, the first power supply temperature curve is connected by a line to obtain the second power supply temperature curve set. The stable change curve of the first time interval and the sudden change part of the second time interval are combined so that the entire temperature curve can fully reflect the change of temperature in each time period. By combining the slope data with the first power supply temperature curve set, the constructed connection line can make the temperature curve naturally transition between the sudden change interval and the stable interval, avoiding discontinuous or abrupt changes in the curve. According to the first power supply temperature curve set and the second power supply temperature curve set, a complete power supply temperature change curve is generated. The generated temperature change curve is transmitted to the communication terminal through the communication network for data display.

[0035] In one example, digital power supply temperature data is encrypted to obtain encrypted power supply temperature data, including: performing Kalman filtering on the digital power supply temperature data to obtain filtered power supply temperature data; performing time series splitting on the filtered power supply temperature data to obtain time series split data segments corresponding to the filtered power supply temperature data; performing time series continuity recognition on the time series split data segments to obtain time series continuity feature codes; extracting discontinuous time series codes in the time series continuity feature codes, and performing data expansion on the filtered power supply temperature data according to the discontinuous time series codes to obtain expanded power supply temperature data; matching the data segment labels corresponding to the expanded power supply temperature data, and based on the data segment labels, filling the expanded power supply temperature data into the time series split data segments to obtain continuous filtered power supply temperature data; differentially encoding the continuous filtered power supply temperature data to obtain first encoded power supply temperature data; performing Huffman encoding on the first encoded power supply temperature data to obtain second encoded power supply temperature data; performing checksum encryption on the second encoded power supply temperature data to obtain third encoded power supply temperature data; and symmetrically encrypting the third encoded power supply temperature data to obtain encrypted power supply temperature data.

[0036] In this example, the digital power supply temperature data is processed by Kalman filtering to obtain the filtered power supply temperature data. Kalman filtering is a recursive filtering algorithm suitable for the state estimation process of dynamic systems with noise pollution. In the Kalman filtering process, the prediction and update steps are combined to estimate the temperature at the next moment using the state estimation and the current observation value. Assume that the filtering process is described by the following two formulas: Prediction equation:

[0037]

[0038] in, represents the prediction of the current temperature, is the state transfer matrix, representing the intrinsic dynamic characteristics of the system, is the state estimate at the previous moment, is the control input matrix, Denotes the control input. Update equation:

[0039]

[0040] in, is the updated temperature state estimate, is the Kalman gain, is the current observation value, is the observation matrix. Kalman filtering is used to reduce the noise interference in the temperature data and obtain smoother filtered temperature data. The filtered power supply temperature data is time-series split, and the temperature data in the time series is divided into multiple small data segments to obtain time-series split data segments, each of which represents a part of the temperature change. Time series continuity recognition is performed on the time series split data segments, and the change trend of the temperature data within each data segment is judged to generate the corresponding time series continuity feature code. Feature coding is used to describe the continuity of temperature change, for example, the temperature in a certain data segment is stable, rising or falling. The discontinuous time series code in the time series continuity feature code is extracted, and the discontinuous time series code indicates the part with discontinuous changes in the time series. In order to make the data have good continuity, the filtered power supply temperature data is expanded to obtain the expanded power supply temperature data. The purpose of expansion is to fill the discontinuous part, make the data segments more continuous, and reduce the impact of discontinuity on subsequent encoding and transmission. Match the data segment label corresponding to the expanded power supply temperature data, and fill the expanded data into the original time-series split data segment based on the data segment label to obtain the continuous filtered power supply temperature data. The data segment label is used to identify the position and order of each data segment. By refilling the expanded data according to the label, the continuity of the data on the time axis is ensured to form complete continuous filtered temperature data. The continuous filtered temperature data is differentially encoded to obtain the first encoded power supply temperature data. Differential encoding is a coding technology that reduces data redundancy by recording the differences between adjacent data points. Assume that the temperature data is , the result of differential encoding is , by storing the initial temperature value And all differential values ​​are used to effectively represent the original data and realize data compression. The first coded power supply temperature data is Huffman encoded to obtain the second coded power supply temperature data. Huffman encoding is a lossless compression encoding method that analyzes the frequency of different symbols in the data and uses variable-length encoding instead of fixed-length encoding to reduce the length of the overall data. The third coded power supply temperature data is symmetrically encrypted to obtain encrypted power supply temperature data. Symmetric encryption is an encryption method that uses the same key to encrypt and decrypt data. Assuming the encryption algorithm is AES, the third coded power supply temperature data With key After encryption function After processing, the encrypted data is obtained .

[0041] In one example, differential encoding is performed on continuously filtered power supply temperature data to obtain first encoded power supply temperature data, including: time-sequentially sorting the continuously filtered power supply temperature data to obtain sorted power supply temperature points; using the first power supply temperature point data among the sorted power supply temperature points as the first target power supply temperature data, and performing differential temperature calculations on the sorted power supply temperature points in turn according to the first target power supply temperature data to obtain differential power supply temperature data; performing first differential encoding on the continuously filtered power supply temperature data according to the differential power supply temperature data and the first target power supply temperature data to obtain initial differential encoded data; and time-sequentially sorting the initial differential encoded data. The invention relates to a method for obtaining a mixed coded power temperature point by sorting the mixed coded power temperature points, wherein the mixed coded power temperature points are sorted and the mixed coded power temperature points are obtained; the second coded power temperature point data among the sorted coded power temperature points is used as the second target power temperature data, and the first coded power temperature point data among the sorted coded power temperature points is filled into the first sorting position of the sorted coded power temperature points to obtain a mixed coded power temperature point; based on the second target power temperature data, differential temperature calculations are performed on the mixed coded power temperature points in sequence to obtain differential coded power temperature data; the initial differential coded data is differentially encoded again according to the differential coded power temperature data and the second target power temperature data to obtain the first coded power temperature data.

[0042] In this example, the continuous filtered power supply temperature data is time-sequentially sorted to obtain the sorted power supply temperature points. Assuming that there is continuous filtered temperature data ,in Representative The temperature values ​​of the power supply temperature points at each time point are obtained. Through the sorting operation, these temperature points are arranged in chronological order to obtain a time series data set. The first temperature point data among the sorted power supply temperature points is used as the first target power supply temperature data. According to the first target power supply temperature data, the differential temperature calculation is performed on the sorted power supply temperature points in turn to obtain the differential power supply temperature data. The differential temperature calculation process is expressed by the following formula:

[0043] ;

[0044] in, Indicates The temperature difference between a time point and the previous time point, and Respectively represent and The temperature value at each time point. In this way, the original temperature data is converted into differential temperature data, which describes the temperature change at each time point. The continuous filtered power supply temperature data is first differentially encoded according to the differential power supply temperature data and the first target power supply temperature data to obtain initial differential encoded data. The process of first differential encoding is expressed as the following formula:

[0045] ;

[0046] in, Represents the initial differential encoding data, consisting of the first target temperature data and subsequent differential temperature data The initial differential encoding data is sorted in time sequence to obtain the sorted encoding power supply temperature points, ensuring that the encoded data is still arranged in time sequence. Assume that the sorted encoding temperature points are ,in Represents the sorted The second encoded temperature point data is used as the second target power supply temperature data. At the same time, the first encoded temperature point data in the sorted encoded temperature points is filled to the first sorted position of the sorted encoded temperature points to obtain a mixed encoded power supply temperature point. The mixed encoded data set is expressed as:

[0047] ;

[0048] In the mixed coding dataset, is refilled to the first position, and As the second target data, it provides a reference for subsequent calculations. Based on the second target power supply temperature data, the temperature point of the hybrid coded power supply is differentially calculated to obtain differential coded power supply temperature data. This process is similar to the previous differential calculation, which is expressed as:

[0049]

[0050] in, Indicates the mixed coding dataset The difference between the first data point and the previous data point can effectively capture the change information in the mixed data. According to the differentially encoded power supply temperature data and the second target power supply temperature data, the initial differentially encoded data is differentially encoded again to obtain the first encoded power supply temperature data. The second differential encoding is expressed by the following formula:

[0051] ;

[0052] in, represents the first coded power supply temperature data, and the second target temperature data and subsequent differentially encoded data Together they form.

[0053] In one example, Huffman encoding is performed on first coded power supply temperature data to obtain second coded power supply temperature data, including: performing power supply temperature string recognition on the first coded power supply temperature data to obtain multiple power supply temperature strings; performing statistical feature calculation on the multiple power supply temperature strings to obtain statistical feature data, wherein the statistical feature data includes: an average power supply temperature value, a high-frequency power supply temperature, and a low-frequency power supply temperature; performing temperature difference calculation on the high-frequency power supply temperature by using the average power supply temperature value to obtain a first power supply temperature difference; performing temperature difference calculation on the low-frequency power supply temperature by using the average power supply temperature value to obtain a second power supply temperature difference; matching a first power supply temperature string set corresponding to the high-frequency power supply temperature, and matching a second power supply temperature string set corresponding to the low-frequency power supply temperature; setting a first coded character length by using the first power supply temperature difference, and setting a second coded character length by using the second power supply temperature difference; performing Huffman encoding on the first power supply temperature string set based on the first coded character length to obtain a first coded character string; performing Huffman encoding on the second power supply temperature string set based on the second coded character length to obtain a second coded character string; performing data fusion on the first coded power supply temperature data by using the first coded character string and the second coded character string to obtain the second coded power supply temperature data.

[0054] In this example, the power supply temperature string recognition is performed on the first encoded power supply temperature data. Assume that the first encoded power supply temperature data is ,in Indicates Encoded temperature data at each time point. Through power supply temperature string recognition, this set of data is converted into multiple power supply temperature strings, and adjacent temperature values ​​with similar characteristics are grouped together. For example, if continuous data segments with small temperature changes have similar patterns, these data segments are combined into one string to simplify subsequent processing. Statistical feature calculations are performed on the power supply temperature string to obtain statistical feature data. The statistical feature data mainly includes three parts: average power supply temperature value, high-frequency power supply temperature, and low-frequency power supply temperature. By calculating the average value, the overall level of the temperature data can be understood. Frequency statistics are performed on multiple temperature strings to find out the high-frequency and low-frequency temperature values. Assume represents the temperature value that appears most frequently in the data set, Indicates the temperature value with the lowest frequency. High-frequency temperature usually reflects the common temperature of the power supply system under stable operation, while low-frequency temperature corresponds to the temperature state under abnormal or special circumstances. The temperature difference of the high-frequency power supply temperature is calculated by averaging the power supply temperature value to obtain the first power supply temperature difference. The calculation of the first power supply temperature difference is expressed as:

[0055]

[0056] in, represents the first power supply temperature difference, is the high frequency power supply temperature, is the average power supply temperature value. The first power supply temperature difference reflects the degree of deviation of the high frequency temperature from the average value, and is used to determine the character length required for encoding the high frequency temperature. Similarly, the temperature difference of the low frequency power supply temperature is calculated by the average power supply temperature value to obtain the second power supply temperature difference. The calculation formula is as follows:

[0057] ;

[0058] in, represents the second power supply temperature difference, is the average power supply temperature value, is the low-frequency power supply temperature. The second power supply temperature difference reflects the deviation of the low-frequency temperature from the average value, and is used to determine the character length required to encode the low-frequency temperature. The corresponding power supply temperature character string sets are matched according to these temperature differences. The character string set corresponding to the high-frequency power supply temperature is called the first power supply temperature character string set, and the character string set corresponding to the low-frequency power supply temperature is called the second power supply temperature character string set. The purpose of matching these character string sets is to further compress the temperature data. By distinguishing between high-frequency and low-frequency character string sets, different encoding strategies are used to improve encoding efficiency. To set the first encoding character length, and through the second power supply temperature difference To set the second encoding character length. The setting of the encoding character length is based on the size of the temperature difference. For high-frequency temperatures, a shorter encoding character length is selected, while for low-frequency temperatures, a longer encoding character length is required to ensure that the integrity of the data is maintained during encoding. The first power supply temperature character string set is Huffman encoded based on the first encoding character length to obtain a first encoding character string. Huffman encoding is a lossless data compression algorithm that constructs a coding tree based on the frequency of occurrence of data, assigns shorter codes to data with higher frequency, and assigns longer codes to data with lower frequency. Since the high-frequency temperatures in the first power supply temperature character string set have a shorter character length, Huffman encoding can further compress data and improve overall encoding efficiency. Similarly, the second power supply temperature character string set is Huffman encoded based on the second encoding character length to obtain a second encoding character string. Since the temperature values ​​in the second power supply temperature character string set have a lower frequency of occurrence, a longer code will be assigned in Huffman encoding, thereby ensuring that the original data is restored during decoding. The first encoded power supply temperature data is data fused by the first encoding character string and the second encoding character string to obtain the second encoded power supply temperature data. Combine the two Huffman-encoded string sets to produce a complete encoded data set.

[0059] In one example, the second coded power supply temperature data is encrypted with a check code to obtain the third coded power supply temperature data, including: performing hash value calculation on the second coded power supply temperature data to obtain multiple hash values; performing random operation on each hash value to obtain a random hash value corresponding to each hash value; and encrypting the second coded power supply temperature data with a check code using the random hash value corresponding to each hash value to obtain the third coded power supply temperature data.

[0060] In this example, a hash value calculation is performed on the second coded power supply temperature data to obtain multiple hash values. The second coded power supply temperature data is a set of coded temperature data used to reflect the temperature change of the power supply at different time points. This set of coded data is converted into multiple unique hash values. In the hash value calculation process, a hash function, such as SHA-256 or MD5, is used to take the coded data as input to generate a corresponding hash value. A hash function is a one-way function that can convert input data of any length into an output of a fixed length, namely a hash value. An important characteristic of a hash value is uniqueness, that is, the same hash value is always generated for the same data, and it is almost impossible for different data to generate the same hash value. Multiple unique hash values ​​are obtained by performing hash calculations on different parts of the second coded power supply temperature data. A random operation is performed on each hash value to obtain a random hash value corresponding to each hash value. The purpose of the random operation is to introduce randomness on the basis of the original hash value to improve the security of data encryption. The random operation uses a method such as an XOR (exclusive or) operation combined with a random number, or generates a random number through a pseudo-random number generator (PRNG), and performs mathematical operations on it and the hash value to generate a random hash value. For example, suppose the original hash value is , the random number is , random operation is performed using the following formula:

[0061] ;

[0062] in, Represents a random hash value obtained through random operation. represents the exclusive OR operator, is the original hash value, and is the corresponding random number. Through random operations, it is ensured that even if the original hash values ​​are the same, the final random hash values ​​are different due to the introduction of different random numbers. The second coded power supply temperature data is encrypted with a check code through the random hash value corresponding to each hash value to obtain the third coded power supply temperature data. The purpose of check code encryption is to ensure that the integrity of the data is verified during data transmission to determine whether the data has been tampered with. By appending the random hash value as a check code to the coded data, a check-checked data block is formed, and the correctness of the data is verified by the check code at the receiving end. During the data transmission process, the receiving end uses the same hash function and random number generator to recalculate the hash value of the received second coded power supply temperature data part and compare it with the attached random hash value. If the comparison results are consistent, it means that the data has not been tampered with during the transmission process and the verification is successful; if they are inconsistent, it means that the data has been tampered with or a transmission error has occurred, so that it can be discovered in time and corresponding measures can be taken.

[0063] In one example, encrypted power supply temperature data is decrypted by a preset LZW algorithm to obtain decrypted power supply temperature data, including: performing event stream conversion on the encrypted power supply temperature data to obtain a power supply temperature change event stream; performing power supply temperature change time attention feature calculation on the power supply temperature change event stream to obtain a time attention feature; performing power supply temperature change space attention feature calculation on the power supply temperature change event stream to obtain a space attention feature; matching the power supply temperature change time weight corresponding to the time attention feature, and matching the power supply temperature change space weight corresponding to the space attention feature; performing significant feature extraction on the power supply temperature change event stream by using the power supply temperature change time weight and the power supply temperature change space weight to obtain a power supply temperature change significant feature; performing a decoding dictionary construction on the power supply temperature change significant feature by using the LZW algorithm to obtain a decoding dictionary set, and decrypting the encrypted power supply temperature data by using the decoding dictionary set to obtain the decrypted power supply temperature data.

[0064] In this example, the encrypted power supply temperature data is transformed into an event stream to obtain a power supply temperature change event stream. The temperature data changes are converted from encrypted form into a series of discrete events. Each event in the event stream is a temperature change at a specific time point. Through the transformation, the original temperature data sequence is represented as different events, which more clearly describes the change trend of the power supply temperature at each time point. For example, assuming that the encrypted power supply temperature data is a series of temperature measurement values, these values ​​are represented as an event set through event stream transformation. ,in Representative in the The temperature changes at each time point. The power supply temperature change time attention feature is calculated for the power supply temperature change event stream to obtain the time attention feature. Assume that the result of the time attention feature calculation is a time weight set ,in Indicates at a point in time The time weight is calculated by the following formula:

[0065]

[0066] in, Indicates time point The attention weight, It is about events The characteristic representation function of is an exponential function, Represents the sum of the exponential values ​​of all events for normalization. The spatial attention feature of the power supply temperature change event stream is calculated to obtain the spatial attention feature. The spatial attention feature calculation is used to identify which parts of the temperature data have a significant impact on different physical spatial areas of the power supply. Assuming that the power supply system has several monitoring points, these monitoring points record temperature changes at different locations, and the spatial attention feature is represented as a set of spatial weights ,in Indicates The influence of each monitoring point in the event stream. By calculating the influence of different spatial positions in the event stream, find out the part that contributes more to the temperature change at a specific spatial position. Match the time weight of the power supply temperature change corresponding to the time attention feature, and match the spatial weight of the power supply temperature change corresponding to the spatial attention feature. Time weight and spatial weight Combined by weighting, the analysis of temperature change events is refined. By matching the time weight and space weight, more refined attention features are obtained. Based on the time weight and space weight, significant features are extracted from the power temperature change event stream to obtain significant features of power temperature change. The attention weight is weighted to the original event stream to extract those features with important influence. Assume that the significant features of power temperature change are the set , each feature The calculation is done by the following formula:

[0067] ;

[0068] in, Indicates at a point in time The notable features of and They are the time and space attention weights, is an event in the original event stream. In this way, the temporal and spatial significance is weighted to each event, and multiple prominent features are obtained. The LZW (Lempel-Ziv-Welch) algorithm is used to construct a decoding dictionary for the significant features of power supply temperature changes, and a decoding dictionary set is obtained. The LZW algorithm is a lossless data compression algorithm that can effectively use repeated patterns in data to construct a coding dictionary. In the decoding process, a decoding dictionary is constructed through the significant feature set, which is expressed as ,in Represents the pattern in the significant features. In the LZW algorithm, the dictionary initially contains all possible single characters or basic symbols. As the algorithm proceeds, new string patterns are continuously added to the dictionary. Through the analysis of significant features, the dictionary is expanded more quickly, thereby improving the efficiency of decoding. The encrypted power supply temperature data is decrypted by the decoding dictionary set to obtain the decrypted power supply temperature data. During the decryption process, the decoding dictionary set constructed previously is used to gradually restore the original temperature data according to the LZW decoding process. The decoding process is to replace the encoded data with the original temperature sequence one by one by matching the pattern in the encoded data and the entries in the dictionary. For example, assuming that the encrypted power supply temperature data is ,in Represents the encoded data by using a decoding dictionary set , gradually restore the original temperature event stream and obtain the decrypted power supply temperature data .

[0069] Furthermore, a decoding dictionary is constructed for significant features of power supply temperature changes through the LZW algorithm to obtain a decoding dictionary set, and the encrypted power supply temperature data is decrypted through the decoding dictionary set to obtain decrypted power supply temperature data, including: the LZW algorithm includes a dynamic dictionary update module and an adaptive coding length module; wherein the dynamic dictionary update module calculates the data distribution within the sliding window for each power supply temperature data point in the decoding process, and dynamically adjusts the dictionary content according to the data distribution; the adaptive coding length module automatically adjusts the number of coding bits by calculating the entropy value of the power supply temperature data; a deep neural network model is constructed to obtain a power supply temperature decryption neural network, and the power supply temperature decryption neural network includes a power supply temperature feature extraction module. The power temperature feature extraction layer consists of five one-dimensional convolutional layers, each of which has a convolution kernel size of 3 and a step size of 1, and a batch normalization layer and a ReLU activation function are added after each convolutional layer. The power temperature sequence modeling layer adopts a three-layer bidirectional long short-term memory network structure, and each layer contains 128 hidden units. The power temperature output layer uses a fully connected layer to map the features to the same space as the input dimension and uses the Softmax function for normalization. The significant features of the power temperature change are input into the LZW algorithm, and the initial power temperature decoding dictionary is obtained by parsing the significant features of the power temperature change bit by bit and comparing the parsing results with the current dictionary. The usage frequency of each dictionary item in the initial power temperature decoding dictionary in the decoding process is calculated to obtain the usage frequency distribution of the power temperature dictionary items; according to the usage frequency distribution of the power temperature dictionary items, the dictionary items in the initial power temperature decoding dictionary are reordered from high to low according to the usage frequency to obtain the optimized power temperature decoding dictionary; the optimized power temperature decoding dictionary is input into the power temperature decryption neural network, the dictionary features are extracted through the power temperature feature extraction layer, the power temperature sequence modeling layer analyzes the correlation between the dictionary items, and the power temperature output layer generates dictionary optimization suggestions to obtain the power temperature dictionary optimization suggestions; according to the power temperature dictionary optimization suggestions, the optimized power temperature decoding dictionary is modified, including adding high The high-frequency combination dictionary items and the low-frequency single dictionary items are deleted to obtain the decoding dictionary set; the encrypted power supply temperature data is input into the LZW algorithm, and each encrypted data segment is parsed and matched bit by bit using the decoding dictionary set to obtain the preliminary decrypted power supply temperature data; the preliminary decrypted power supply temperature data is input into the power supply temperature decryption neural network, the decrypted data features are extracted through the power supply temperature feature extraction layer, the time series relationship of the decrypted data is analyzed through the power supply temperature sequence modeling layer, and the power supply temperature output layer generates decryption correction suggestions to obtain the power supply temperature decryption correction suggestions; according to the power supply temperature decryption correction suggestions, the preliminary decrypted power supply temperature data is corrected point by point, including correcting abnormal temperature values ​​and smoothing temperature mutation points to obtain the decrypted power supply temperature data.

[0070] In one example, a power supply temperature change curve is generated based on decrypted power supply temperature data, and the power supply temperature change curve is transmitted to a communication terminal for data display, including: extracting power supply temperature extreme points from the decrypted power supply temperature data to obtain multiple power supply temperature extreme points; analyzing the time interval of stable power supply temperature change on the decrypted power supply temperature data to obtain a first time interval; analyzing the time interval of sudden power supply temperature change on the decrypted power supply temperature data through multiple power supply temperature extreme points to obtain a second time interval; constructing a power supply temperature curve for the first time interval to obtain a first power supply temperature curve set; calculating the power supply temperature change slope for the second time interval to obtain change slope data; constructing a connecting line for the first power supply temperature curve based on the change slope data to obtain a second power supply temperature curve set; generating a power supply temperature change curve based on the first power supply temperature curve set and the second power supply temperature curve set, and transmitting the power supply temperature change curve to a communication terminal for data display.

[0071] In this example, the power supply temperature extreme points are extracted from the decrypted power supply temperature data to identify the local maximum and minimum values ​​of the power supply temperature during the change process. These extreme points represent the key moments when the temperature reaches a peak or valley value. For example, assuming that the decrypted power supply temperature data is ,in Representative By traversing the temperature data, we can find all the moments with the maximum or minimum values ​​in the local range compared with the adjacent points before and after, and extract multiple power supply temperature extreme points. ,in Indicates The temperature value of the extreme point. The decrypted power supply temperature data is analyzed for the stable change time interval of the power supply temperature to obtain the first time interval. The stable change time interval refers to the time period when the temperature changes relatively slowly and without drastic fluctuations. These intervals represent the temperature state of the power supply when it is working stably. By calculating whether the absolute value of the temperature change rate is below a set threshold, it is determined whether the temperature change is stable in a certain time period. Assuming that the temperature change rate is used To express in Temperature change rate at a time point:

[0072] ;

[0073] in, Indicates time point and The absolute value of the temperature change between time points. By setting the threshold ,when , the temperature change is considered to be stable at this time point, so that the first time interval can be identified. The identification of the stable interval helps to find out that the system is in normal operation and the temperature remains within a controllable range. Through multiple power supply temperature extreme points, the decrypted power supply temperature data is analyzed for the power supply temperature mutation time interval to obtain the second time interval. The mutation time interval refers to the time period in which the temperature changes significantly in a short period of time. These changes are caused by rapid changes in load or some abnormal conditions. The temperature mutation time interval is determined by detecting whether there is a significant change in temperature before and after the extreme point. Assuming the time point and extreme points Adjacent, if If it exceeds a certain threshold, it is considered that a sudden temperature change has occurred in the interval, and it is marked as the second time interval. The power supply temperature curve is constructed for the first time interval to obtain a first power supply temperature curve set. The first power supply temperature curve set is obtained by fitting the temperature data in the stable interval, and the data is smoothed using a polynomial fitting method. Assume that the fitting function is:

[0074] ;

[0075] in, is the fitting curve of temperature over time, are the fitting parameters, Represents time. By fitting the data of the stable interval, a smooth curve describing the temperature change in these time periods is obtained. The power supply temperature change slope is calculated for the second time interval to obtain the change slope data. The temperature change slope describes the speed of temperature change in the mutation interval and is calculated by the following formula:

[0076] ;

[0077] in, Indicates The temperature change slope at a time point, and are the temperatures at two adjacent time points, and The size of the change slope reflects the severity of the temperature change and is used to identify the temperature mutation. Based on the change slope data, a connecting line is constructed for the first power supply temperature curve set to obtain the second power supply temperature curve set. The temperature curve of the stable change interval is naturally connected with the change slope of the mutation interval, so that the entire temperature change curve coherently reflects the temperature change of the power supply in different time periods. Assume that the temperature of the first power supply temperature curve at a certain time point is , and the slope of the mutation interval is , the connecting line is constructed by linear interpolation, so that the transition between the stable intervals appears more natural. A complete power supply temperature change curve is generated according to the first power supply temperature curve set and the second power supply temperature curve set, and the generated temperature change curve is transmitted to the communication terminal for data display.

[0078] Reference Figure 2 , this embodiment provides an encrypted transmission device for communication data, including:

[0079] The conversion unit 1 is used to perform analog-to-digital conversion on the temperature signal collected by the power supply temperature sensor to obtain digital power supply temperature data;

[0080] Encryption unit 2, used for encrypting the digital power supply temperature data to obtain encrypted power supply temperature data;

[0081] The decryption unit 3 is used to decrypt the encrypted power supply temperature data by using a preset LZW algorithm to obtain the decrypted power supply temperature data;

[0082] The transmission unit 4 is used to generate a power supply temperature change curve according to the decrypted power supply temperature data, and transmit the power supply temperature change curve to the communication terminal for data display.

[0083] In this embodiment, for the specific implementation of each unit in the above device embodiment, please refer to the above method embodiment, which will not be repeated here.

[0084] Reference Figure 3 In an embodiment of the present invention, a computer device is also provided. The computer device may be a server, and its internal structure may be as follows: Figure 3 As shown. The computer device includes a processor, a memory, a display screen, an input device, a network interface and a database connected through a system bus. Among them, the processor designed by the computer is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system, a computer program and a database. The internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The database of the computer device is used to store the corresponding data in this embodiment. The network interface of the computer device is used to communicate with an external terminal through a network connection. When the computer program is executed by the processor, the above method is implemented.

[0085] Those skilled in the art will understand that Figure 3 The structure shown in the figure is merely a block diagram of a portion of the structure related to the solution of the present invention, and does not constitute a limitation on the computer device to which the solution of the present invention is applied.

[0086] An embodiment of the present invention further provides a computer-readable storage medium on which a computer program is stored, and when the computer program is executed by a processor, the above method is implemented. It can be understood that the computer-readable storage medium in this embodiment can be a volatile readable storage medium or a non-volatile readable storage medium.

[0087] Those skilled in the art can understand that all or part of the processes in the above-mentioned embodiment methods can be completed by instructing the relevant hardware through a computer program, and the computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the embodiments of the above-mentioned methods. Among them, any reference to memory, storage, database or other media provided by the present invention and used in the embodiments may include non-volatile and / or volatile memory. Non-volatile memory may include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM) or flash memory. Volatile memory may include random access memory (RAM) or external cache memory. As an illustration and not limitation, RAM is available in a variety of forms, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double-speed data rate SDRAM (SSRSDRAM), enhanced SDRAM (ESDRAM), synchronous link (Synchlink) DRAM (SLDRAM), memory bus (Rambus) direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and memory bus dynamic RAM.

[0088] It should be noted that, in this article, the terms "include", "comprises" or any other variations thereof are intended to cover non-exclusive inclusion, so that a process, device, article or method including a series of elements includes not only those elements, but also includes other elements not explicitly listed, or also includes elements inherent to such process, device, article or method. In the absence of further restrictions, an element defined by the sentence "includes a ..." does not exclude the presence of other identical elements in the process, device, article or method including the element.

[0089] The above description is only a preferred embodiment of the present invention, and does not limit the patent scope of the present invention. Any equivalent structure or equivalent process transformation made by using the contents of the present invention specification and drawings, or directly or indirectly applied in other related technical fields, are also included in the patent protection scope of the present invention.

Claims

1. A method for encrypting and transmitting communication data, characterized in that: The following steps are involved: Perform analog-to-digital conversion on the temperature signal collected by the power supply temperature sensor to obtain digital power supply temperature data; The digital power supply temperature data is encrypted to obtain encrypted power supply temperature data; specifically comprising: performing Kalman filtering on the digital power supply temperature data to obtain filtered power supply temperature data; performing time series splitting on the filtered power supply temperature data to obtain time series splitting data segments corresponding to the filtered power supply temperature data; performing time series continuity identification on the time series splitting data segments to obtain time series continuity feature codes; extracting the discontinuous time series codes in the time series continuity feature codes, and performing data expansion on the filtered power supply temperature data according to the discontinuous time series codes to obtain expanded power supply temperature data; matching the data segment labels corresponding to the expanded power supply temperature data, and based on the data segment labels, filling the expanded power supply temperature data into the time series splitting data segments to obtain continuous filtered power supply temperature data; performing differential encoding on the continuous filtered power supply temperature data to obtain first encoded power supply temperature data; performing Huffman encoding on the first encoded power supply temperature data to obtain second encoded power supply temperature data; performing checksum encryption on the second encoded power supply temperature data to obtain third encoded power supply temperature data; performing symmetric encryption on the third encoded power supply temperature data to obtain the encrypted power supply temperature data; The encrypted power supply temperature data is decrypted by a preset LZW algorithm to obtain decrypted power supply temperature data; specifically comprising: performing event stream conversion on the encrypted power supply temperature data to obtain a power supply temperature change event stream; performing power supply temperature change time attention feature calculation on the power supply temperature change event stream to obtain a time attention feature; performing power supply temperature change space attention feature calculation on the power supply temperature change event stream to obtain a space attention feature; matching the power supply temperature change time weight corresponding to the time attention feature, and matching the power supply temperature change space weight corresponding to the space attention feature; performing significant feature extraction on the power supply temperature change event stream by using the power supply temperature change time weight and the power supply temperature change space weight to obtain a significant feature of the power supply temperature change; performing a decoding dictionary construction on the significant feature of the power supply temperature change by using the LZW algorithm to obtain a decoding dictionary set, and decrypting the encrypted power supply temperature data by using the decoding dictionary set to obtain the decrypted power supply temperature data; A power supply temperature variation curve is generated according to the decrypted power supply temperature data, and the power supply temperature variation curve is transmitted to a communication terminal for data display.

2. The method for encrypted transmission of communication data according to claim 1, characterized in that: The differential encoding of the continuously filtered power supply temperature data to obtain first encoded power supply temperature data includes: Performing time sequence sorting on the continuously filtered power supply temperature data to obtain sorted power supply temperature points; Taking the first power supply temperature point data among the sorted power supply temperature points as the first target power supply temperature data, and performing differential temperature calculation on the sorted power supply temperature points in sequence according to the first target power supply temperature data to obtain differential power supply temperature data; Performing a first differential encoding on the continuously filtered power supply temperature data according to the differential power supply temperature data and the first target power supply temperature data to obtain initial differential encoding data; Performing time sequence sorting on the initial differential coded data to obtain sorted coded power supply temperature points; Using the second encoded power temperature point data among the sorted encoded power temperature points as the second target power temperature data, and filling the first encoded power temperature point data among the sorted encoded power temperature points into the first sorted position of the sorted encoded power temperature points, to obtain a mixed encoded power temperature point; Based on the second target power supply temperature data, differential temperature calculation is performed on the mixed coding power supply temperature points in sequence to obtain differential coding power supply temperature data; The initial differentially encoded data is differentially encoded again according to the differentially encoded power supply temperature data and the second target power supply temperature data to obtain the first encoded power supply temperature data.

3. The method for encrypted transmission of communication data according to claim 2, characterized in that: The step of performing Huffman encoding on the first coded power supply temperature data to obtain second coded power supply temperature data includes: Performing power supply temperature character string recognition on the first encoded power supply temperature data to obtain a plurality of power supply temperature character strings; Performing statistical characteristic calculation on the multiple power supply temperature character strings to obtain statistical characteristic data, wherein the statistical characteristic data includes: an average power supply temperature value, a high-frequency power supply temperature, and a low-frequency power supply temperature; Calculating the temperature difference of the high-frequency power supply temperature by using the average power supply temperature value to obtain a first power supply temperature difference; Calculating the temperature difference of the low-frequency power supply temperature by using the average power supply temperature value to obtain a second power supply temperature difference; Matching a first power supply temperature character string set corresponding to the high-frequency power supply temperature, and matching a second power supply temperature character string set corresponding to the low-frequency power supply temperature; Setting a first coded character length by the first power supply temperature difference, and setting a second coded character length by the second power supply temperature difference; Performing Huffman encoding on the first power supply temperature character string set based on the first encoding character length to obtain a first encoding character string; Performing Huffman encoding on the second power supply temperature character string set based on the second encoding character length to obtain a second encoding character string; The first coded power supply temperature data is fused by using the first coded character string and the second coded character string to obtain the second coded power supply temperature data.

4. The method for encrypted transmission of communication data according to claim 3, characterized in that: The step of encrypting the second coded power supply temperature data with a check code to obtain third coded power supply temperature data comprises: Performing hash value calculation on the second encoded power supply temperature data to obtain multiple hash values; Performing a random operation on each hash value to obtain a random hash value corresponding to each hash value; The second coded power supply temperature data is encrypted with a check code using a random hash value corresponding to each of the hash values ​​to obtain the third coded power supply temperature data.

5. The method for encrypted transmission of communication data according to claim 1, characterized in that: The step of generating a power supply temperature change curve according to the decrypted power supply temperature data, and transmitting the power supply temperature change curve to a communication terminal for data display includes: Extracting power supply temperature extreme value points from the decrypted power supply temperature data to obtain a plurality of power supply temperature extreme value points; Performing a time interval analysis of a stable change in power supply temperature on the decrypted power supply temperature data to obtain a first time interval; By using the plurality of power supply temperature extreme value points, the decrypted power supply temperature data is subjected to a power supply temperature mutation time interval analysis to obtain a second time interval; Constructing a power supply temperature curve for the first time interval to obtain a first power supply temperature curve set; Calculating the power supply temperature change slope during the second time interval to obtain change slope data; Connecting the first power supply temperature curve based on the change slope data to obtain a second power supply temperature curve set; The power supply temperature change curve is generated according to the first power supply temperature curve set and the second power supply temperature curve set, and the power supply temperature change curve is transmitted to a communication terminal for data display.

6. A communication data encryption transmission device, characterized in that: For implementing the steps of the method according to any one of claims 1 to 5, the device comprises: A conversion unit, used to perform analog-to-digital conversion on the temperature signal collected by the power supply temperature sensor to obtain digital power supply temperature data; An encryption unit, used for encrypting the digital power supply temperature data to obtain encrypted power supply temperature data; A decryption unit, used to decrypt the encrypted power supply temperature data by using a preset LZW algorithm to obtain decrypted power supply temperature data; The transmission unit is used to generate a power supply temperature change curve according to the decrypted power supply temperature data, and transmit the power supply temperature change curve to the communication terminal for data display.

7. A computer device comprising a memory and a processor, wherein a computer program is stored in the memory, wherein: When the processor executes the computer program, the steps of the method according to any one of claims 1 to 5 are implemented.

8. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 5 are implemented.

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