Safety compression method and device for process data, electronic equipment and storage medium

Abstract

The invention provides a safe compression method and device for process data, electronic equipment and a storage medium, and the method comprises the steps: obtaining a group of to-be-compressed process data, and determining a compression initial data point of the process data; and performing data compression processing on the compression initial data point based on a second-order curve function of the improved SDT algorithm, and after data compression of the compression initial data point is completed, sequentially taking out the data points to be compressed from the process data for data compression. Stopping storing the to-be-compressed data points obtained after data compression before the new compressed data starting point is determined until the new compressed data starting point is determined, so as to complete one-time data compression; and carrying out data compression on the remaining process data from the new compressed data starting point based on the improved SDT algorithm, and stopping processing until all the to-be-compressed process data are compressed. The process data is compressed by using the improved SDT algorithm, so that the data compression processing efficiency and the compression effect are improved.

Description

Technical Field

[0001] The present application relates to the technical field of data compression, and in particular to a method, device, electronic device and storage medium for secure compression of process data. Background Art

[0002] The real-time database in the industrial control system provides a historical data storage function to save the process data on site for future process analysis, fault tracing, and control scheme improvement. In actual data storage, the real-time database also needs to solve the problem of how to efficiently process massive data. If the data is stored intact, it will inevitably require a large amount of memory and disk space, and take up a lot of CPU time to process, so the real-time data must be compressed and stored. The following data compression technologies are currently used: LZW compression algorithm (string table compression algorithm), BWT compression algorithm (Burrows-Wheele_transform), Huffman coding data compression algorithm. When processing data compression, the existing data compression technology solutions have the following problems: Large storage space occupancy: When compressing big data, some compression algorithms have the problem of relatively high compression, resulting in a large storage space occupation problem, affecting user experience. Long compression time: Because different compression algorithms have different compression and decompression rates, there is a problem of slow processing rate when the data volume is large. Therefore, how to improve the efficiency and compression effect of data compression has become a technical problem that cannot be ignored. Summary of the invention

[0003] In view of this, the purpose of the present application is to provide a method, device, electronic device and storage medium for secure compression of process data, by utilizing an improved SDT algorithm to compress process data, thereby improving data compression processing efficiency and compression effect.

[0004] The present application provides a method for secure compression of process data, the method comprising: Acquire a set of process data to be compressed, and determine a compression starting data point of the process data; wherein the compression starting data point is composed of an initial time point and a process data value at the initial time point; The compression starting data point is subjected to data compression based on the second-order curve function of the improved SDT algorithm, and after the data compression of the compression starting data point is completed, the data points to be compressed are sequentially taken out from the process data for data compression until a new compression data starting point is determined, and the data points to be compressed after the data compression before the new compression data starting point are stored to complete one data compression; Continue to compress the remaining process data from the new compressed data starting point based on the improved SDT algorithm until the compression of all the process data to be compressed is completed and then stop the processing.

[0005] In a possible implementation manner, the second-order curve function based on the improved SDT algorithm performs data compression processing on the compression starting data point, including: Substituting the compression starting data point into the second-order curve function to determine the maximum variable value and the minimum variable value corresponding to the compression starting data point; The compression starting data point is subjected to data compression processing based on the maximum variable value and the minimum variable value.

[0006] In a possible implementation manner, the second-order curve function is: y = a·t 2 +b ΔE Among them, a is the variable value, t is the time of compressing the data point, b is the process data value of the compressed data point, y is the compressed process data value, and ΔE is the compression accuracy parameter of the improved SDT algorithm.

[0007] In a possible implementation manner, the performing data compression processing on the compression starting data point based on the maximum variable value and the minimum variable value includes: If the minimum variable value is greater than or equal to the maximum variable value, the maximum variable value is increased and the minimum variable value is decreased, so that a target variable value capable of fitting all data points is determined between the increased maximum variable value and the decreased minimum variable value; Substitute the target variable value and the compression starting data point into the second-order curve function to perform data compression processing on the compression starting data point.

[0008] In a possible implementation, a new compressed data starting point is determined by the following steps: Substituting the compressed data point into the second-order curve function to determine the maximum variable value and the minimum variable value corresponding to the compressed data point; If the minimum variable value is smaller than the maximum variable value, the compressed data point is used as a new compressed data starting point.

[0009] In a possible implementation manner, after continuing to compress the remaining process data from the new compressed data starting point based on the improved SDT algorithm until the compression of all the process data to be compressed is completed and the processing is stopped, the secure compression method further includes: The compressed process data is encrypted based on the homomorphic encryption algorithm.

[0010] In a possible implementation manner, before obtaining a set of process data to be compressed and determining a compression starting data point of the process data, the secure compression method further includes: A change threshold of process data is set, and abnormal process data values ​​exceeding the threshold are eliminated to reduce error interference of noise data.

[0011] The embodiment of the present application also provides a process data security compression device, the security compression device comprising: An acquisition module, used to acquire a set of process data to be compressed, and determine a compression starting data point of the process data; wherein the compression starting data point is composed of an initial time point and a process data value at the initial time point; A first processing module is used to perform data compression processing on the compression starting data point based on the second-order curve function of the improved SDT algorithm, and after completing the data compression of the compression starting data point, sequentially extract the data points to be compressed from the process data for data compression until a new compression data starting point is determined, and store the data points to be compressed after the data compression before the new compression data starting point, so as to complete one data compression; The second processing module is used to continue to compress the remaining process data from the new compressed data starting point based on the improved SDT algorithm until the compression of all the process data to be compressed is completed and the processing is stopped.

[0012] An embodiment of the present application also provides an electronic device, including: a processor, a memory and a bus, wherein the memory stores machine-readable instructions executable by the processor, and when the electronic device is running, the processor and the memory communicate through the bus, and when the machine-readable instructions are executed by the processor, the steps of the method for secure compression of process data as described above are performed.

[0013] An embodiment of the present application further 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 the method for securely compressing process data as described above are executed.

[0014] The embodiment of the present application provides a method, device, electronic device and storage medium for secure compression of process data, the method comprising: obtaining a set of process data to be compressed, determining the compression starting data point of the process data; wherein the compression starting data point is composed of an initial time point and a process data value at the initial time point; performing data compression processing on the compression starting data point based on a second-order curve function of an improved SDT algorithm, and after completing the data compression of the compression starting data point, sequentially extracting the data points to be compressed from the process data for data compression, until a new compressed data starting point is determined, storing the compressed data points before the new compressed data starting point to complete a data compression; continuing to perform data compression on the remaining process data based on the improved SDT algorithm from the new compressed data starting point, until the compression of all the process data to be compressed is completed and the processing is stopped. By using the improved SDT algorithm to compress process data, the data compression processing efficiency and compression effect are improved.

[0015] In order to make the above-mentioned objects, features and advantages of the present application more obvious and easy to understand, preferred embodiments are specifically cited below and described in detail with reference to the attached drawings. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] In order to more clearly illustrate the technical solutions of the embodiments of the present application, the drawings required for use in the embodiments will be briefly introduced below. It should be understood that the following drawings only show certain embodiments of the present application and therefore should not be regarded as limiting the scope. For ordinary technicians in this field, other related drawings can be obtained based on these drawings without paying creative work.

[0017] Figure 1 A flowchart of a method for securely compressing process data provided by an embodiment of the present application; Figure 2 A schematic diagram of a method for securely compressing process data provided by an embodiment of the present application; Figure 3 One of the structural schematic diagrams of a process data security compression device provided in an embodiment of the present application; Figure 4 A second structural diagram of a process data security compression device provided in an embodiment of the present application; Figure 5 A schematic diagram of the structure of an electronic device provided in an embodiment of the present application. DETAILED DESCRIPTION

[0018] To make the purpose, technical scheme and advantages of the embodiments of the present application clearer, the technical scheme in the embodiments of the present application will be clearly and completely described below in conjunction with the drawings in the embodiments of the present application. Obviously, the described embodiments are only a part of the embodiments of the present application, rather than all of the embodiments. The components of the embodiments of the present application usually described and shown in the drawings here can be arranged and designed in various different configurations. Therefore, the following detailed description of the embodiments of the present application provided in the drawings is not intended to limit the scope of the application claimed for protection, but merely represents the selected embodiments of the present application. Based on the embodiments of the present application, each other embodiment obtained by those skilled in the art without making creative work belongs to the scope of protection of the present application.

[0019] First, the application scenarios to which the present application is applicable are introduced. The present application can be applied in the field of data compression technology.

[0020] According to research, the real-time database in the industrial control system provides historical data storage function to save on-site process data for future process analysis, fault tracing, and control scheme improvement. In actual data storage, the real-time database also needs to solve the problem of how to efficiently process massive data. If the data is stored intact, it will inevitably require a large amount of memory and disk space, and take up a lot of CPU time to process, so the real-time data must be compressed and stored. The following data compression technologies are currently used: LZW compression algorithm (string table compression algorithm), BWT compression algorithm (Burrows-Wheele_transform), Huffman coding data compression algorithm. When processing data compression, the existing data compression technology solutions have the following problems: Large storage space occupancy: When compressing big data, some compression algorithms have the problem of relatively high compression, resulting in a large storage space occupation problem, affecting user experience. Long compression time: Because different compression algorithms have different compression and decompression rates, there is a problem of slow processing rate when the data volume is large. Therefore, how to improve the efficiency and compression effect of data compression has become a technical problem that cannot be ignored.

[0021] Based on this, an embodiment of the present application provides a secure compression method for process data, which improves data compression processing efficiency and compression effect by utilizing an improved SDT algorithm to compress process data.

[0022] See also Figure 1 , Figure 1 This is a flow chart of a method for securely compressing process data provided by an embodiment of the present application. Figure 1 As shown in , the secure compression method provided by the embodiment of the present application includes: S101: Acquire a group of process data to be compressed, and determine a compression starting data point of the process data; wherein the compression starting data point is composed of an initial time point and a process data value at the initial time point.

[0023] In this step, a group of process data to be compressed is obtained, and a compression starting data point of the process data is determined.

[0024] Among them, process data refers to various real-time data collected in industrial control systems, which are mainly used to monitor and control the production process. These data usually contain timestamps and corresponding measurement values, which can help engineers understand and optimize the production process.

[0025] In a possible implementation manner, before obtaining a set of process data to be compressed and determining a compression starting data point of the process data, the secure compression method further includes: A change threshold of process data is set, and abnormal process data values ​​exceeding the threshold are eliminated to reduce error interference of noise data.

[0026] Here, by setting a change threshold of process data, abnormal process data values ​​exceeding the threshold are eliminated to reduce error interference of noise data.

[0027] S102: Perform data compression processing on the compression starting data point based on the second-order curve function of the improved SDT algorithm, and after completing the data compression of the compression starting data point, sequentially take out the data points to be compressed from the process data for data compression, until a new compression data starting point is determined, and stop storing the data points to be compressed after the data compression before the new compression data starting point, so as to complete one data compression.

[0028] In this step, the compression starting data point is compressed according to the second-order curve function of the improved SDT algorithm. After the data compression of the compression starting data point is completed, the data points to be compressed are sequentially taken out from the process data for data compression until a new compression data starting point is determined. The data points to be compressed after the data compression before the new compression data starting point are stopped and stored to complete one data compression.

[0029] Among them, the traditional SDT algorithm uses a straight line to fit the data points, but in many cases the data change trend is nonlinear. The improved SDT algorithm in this solution introduces a second-order curve function for data fitting, which can more accurately capture the data change trend, and the compression effect can be flexibly adjusted by setting the compression accuracy parameters.

[0030] In a possible implementation manner, the second-order curve function based on the improved SDT algorithm performs data compression processing on the compression starting data point, including: A: Substitute the compression starting data point into the second-order curve function to determine the maximum variable value and the minimum variable value corresponding to the compression starting data point.

[0031] Here, the compression starting data point is substituted into the second-order curve function to determine the maximum variable value and the minimum variable value corresponding to the compression starting data point.

[0032] Wherein, the second-order curve function is: y = a·t 2 +b ΔE Among them, a is the variable value, t is the time of compressing the data point, b is the process data value of the compressed data point, y is the compressed process data value, and ΔE is the compression accuracy parameter of the improved SDT algorithm.

[0033] Here, the process data is a two-dimensional data set D(t i ,y i ),i=0,1,2....,k-1. Among them (t 0 ,y 0 ) is the starting data point of the compression interval. 0 ,y 0 ) point in the vertical direction (t 0 ,y 0 ) point ΔE has two pivot points (t 0 ,y 0 +ΔE) and (t 0 ,y 0 -ΔE), each element in the data set D corresponds to these two pivots and is connected by a second-order curve of the expression. These two second-order curves are regarded as two virtual "doors" with the pivot as the axis. At the beginning of the algorithm, these two doors are closed. During the execution of the algorithm, the two doors can only be opened but not closed. max and Y min To represent the description function of the two curves, then Y max and Y min The function expression of Y is: max =a·t 2 +b+ΔE and Y min =a·t 2 +b-ΔE. Substitute the compression starting data points into Y max and Y min Among the functions of max ) and the minimum variable value (a min ).

[0034] B: Performing data compression processing on the compression starting data point based on the maximum variable value and the minimum variable value.

[0035] Here, data compression processing is performed on the compression starting data point according to the maximum variable value and the minimum variable value.

[0036] In a possible implementation manner, the performing data compression processing on the compression starting data point based on the maximum variable value and the minimum variable value includes: (1): If the minimum variable value is greater than or equal to the maximum variable value, the maximum variable value is increased and the minimum variable value is decreased, so that a target variable value that can fit all data points is determined between the increased maximum variable value and the decreased minimum variable value.

[0037] Here, if the minimum variable value is greater than or equal to the maximum variable value, the maximum variable value is increased and the minimum variable value is decreased, so that a target variable value that can fit all data points is determined between the increased maximum variable value and the decreased minimum variable value.

[0038] Among them, the target variable value that can fit all data points is Y max and Y min The target variable value. Specifically, for any point N (t n ,y n ), if a min ≥a max , if Y max Over (t n ,y n ) point, you need to increase a max For any point N(t n ,y n ), if a min ≥a max , if Y min Over (t n ,y n ) point, you need to reduce a min The value of .

[0039] Here, Y max and Y min The target variable value is Y max and Y min The variable value corresponding to the intersection.

[0040] (2): Substituting the target variable value and the compression starting data point into the second-order curve function to perform data compression processing on the compression starting data point.

[0041] Here, the target variable value and the compression starting data point are substituted into the second-order curve function to perform data compression processing on the compression starting data point to determine the compressed data value.

[0042] In a possible implementation, a new compressed data starting point is determined by the following steps: Substitute the compressed data point into the second-order curve function to determine the maximum variable value and the minimum variable value corresponding to the compressed data point; if the minimum variable value is smaller than the maximum variable value, use the compressed data point as a new compressed data starting point.

[0043] Here, the compressed data point is substituted into the second-order curve function to determine the maximum variable value and the minimum variable value corresponding to the compressed data point; if the minimum variable value is smaller than the maximum variable value, the compressed data point is used as the new compressed data starting point.

[0044] S103: Continue to compress the remaining process data from the new compressed data starting point based on the improved SDT algorithm, and stop the processing when the compression of all the process data to be compressed is completed.

[0045] In this step, the remaining process data is continuously compressed from the new compression data starting point according to the improved SDT algorithm until the compression of all the process data to be compressed is completed and the processing is stopped.

[0046] In a possible implementation manner, after continuing to compress the remaining process data based on the improved SDT algorithm from the new compressed data starting point until the compression of all the process data to be compressed is completed and the processing is stopped, the secure compression method further includes: The compressed process data is encrypted based on the homomorphic encryption algorithm.

[0047] Homomorphic encryption is an encryption technology that allows calculations to be performed on ciphertext and obtain the same result as the plaintext calculation when the decryption result is obtained. The homomorphic encryption algorithm is based on the composite remainder class problem. The core of homomorphic encryption is that it supports arithmetic or logical operations on encrypted data, including addition, multiplication, etc., and the operation remains correct after decryption. Let the integer Abelian group be Z N , group order N>1, pseudo-random function F: {0,1} n x{0.1} n →Z N The definition of F k (x)=F(k,x), the function is to map a string of length n to the Abelian group Z NWhere n is the key length, which can be set according to specific needs. Homomorphic encryption methods usually include the following three parts: 1) Key generation CreateNewKey: Input key generation source n=1 n , output the key used for encryption, k=CreateNewKey(1 n ),k∈{0,1} n ; 2) Encryption: According to the key k, select a random data seed r∈{0,1} n , combined with the pseudo-random function to compress the process data m∈Z N Encrypt and output ciphertext c=<(m+F k (r))mod N,[r],δ>;3)Decryption: According to the key k, for the ciphertext message c, m=decrypt(k,c).

[0048] This application uses a homomorphic encryption algorithm to encrypt compressed process data, which plays a role in protecting the security and privacy of data access. Because homomorphic encryption has the characteristic of not affecting data arithmetic and logical operations, data statistics can be performed directly in the ciphertext during data access, and the results after statistical analysis can be decrypted once, which not only ensures the security of the data, but also improves the efficiency of encrypted data.

[0049] For further information, see Figure 2 , Figure 2 A schematic diagram of a method for securely compressing process data provided by an embodiment of the present application. Figure 2 As shown, a set of process data is obtained, ΔE is set for the process data and data compression is performed, and the parameter a is determined according to the second-order curve function and the data points to be compressed. min and a max , detect a min Is it less than a max If not, continue to compress the data. If yes, determine a new compressed data starting point, store the compressed data points before the new compressed data starting point, and complete a data compression. Continue to compress the remaining process data from the new compressed data starting point according to the improved SDT algorithm until all process data are compressed and stop processing.

[0050] The embodiment of the present application provides a method for safely compressing process data, the method comprising: obtaining a group of process data to be compressed, determining the compression starting data point of the process data; wherein the compression starting data point is composed of an initial time point and a process data value at the initial time point; performing data compression processing on the compression starting data point based on a second-order curve function of an improved SDT algorithm, and after completing the data compression of the compression starting data point, sequentially extracting the data points to be compressed from the process data for data compression, until a new compression data starting point is determined, storing the data points to be compressed after the data compression before the new compression data starting point, so as to complete a data compression; continuing to perform data compression on the remaining process data starting from the new compression data starting point based on the improved SDT algorithm, until the compression of all the process data to be compressed is completed and the processing is stopped. By using the improved SDT algorithm to compress process data, the data compression processing efficiency and compression effect are improved.

[0051] See also Figure 3 , Figure 4 , Figure 3 One of the structural schematic diagrams of a process data security compression device provided in an embodiment of the present application; Figure 4 This is a second structural diagram of a process data security compression device provided in an embodiment of the present application. Figure 3 As shown in , the safety compression device 300 includes: The acquisition module 310 is used to acquire a set of process data to be compressed and determine a compression starting data point of the process data; wherein the compression starting data point is composed of an initial time point and a process data value at the initial time point; The first processing module 320 is used to perform data compression processing on the compression starting data point based on the second-order curve function of the improved SDT algorithm, and after completing the data compression of the compression starting data point, sequentially extract the data points to be compressed from the process data for data compression until a new compression data starting point is determined, and store the data points to be compressed after the data compression before the new compression data starting point, so as to complete one data compression; The second processing module 330 is used to continue to compress the remaining process data from the new compressed data starting point based on the improved SDT algorithm until the compression of all the process data to be compressed is completed and the processing is stopped.

[0052] Further, when the first processing module 320 is used to perform data compression processing on the compression starting data point using the second-order curve function based on the improved SDT algorithm, the first processing module 320 is specifically used to: Substituting the compression starting data point into the second-order curve function to determine the maximum variable value and the minimum variable value corresponding to the compression starting data point; The compression starting data point is subjected to data compression processing based on the maximum variable value and the minimum variable value.

[0053] Further, when the first processing module 320 is used to perform data compression processing on the compression starting data point based on the maximum variable value and the minimum variable value, the first processing module 320 is specifically used to: If the minimum variable value is greater than or equal to the maximum variable value, the maximum variable value is increased and the minimum variable value is decreased, so that a target variable value that can fit all data points is determined between the increased maximum variable value and the decreased minimum variable value; Substitute the target variable value and the compression starting data point into the second-order curve function to perform data compression processing on the compression starting data point.

[0054] Furthermore, the first processing module 320 determines a new compressed data starting point through the following steps: Substituting the compressed data point into the second-order curve function to determine the maximum variable value and the minimum variable value corresponding to the compressed data point; If the minimum variable value is smaller than the maximum variable value, the compressed data point is used as a new compressed data starting point.

[0055] Further, such as Figure 4 As shown, the security compression device 300 further includes an encryption processing module 340, and the encryption processing module 340 is used to: The compressed process data is encrypted based on the homomorphic encryption algorithm.

[0056] Further, such as Figure 4 As shown, the safety compression device 300 further includes a data preprocessing module 350, and the data preprocessing module 350 is used to: A change threshold of process data is set, and abnormal process data values ​​exceeding the threshold are eliminated to reduce error interference of noise data.

[0057] The embodiment of the present application provides a safe compression device for process data, the safe compression device comprising: an acquisition module, used to acquire a group of process data to be compressed, and determine the compression starting data point of the process data; wherein the compression starting data point is composed of an initial time point and the process data value at the initial time point; a first processing module, used to perform data compression processing on the compression starting data point based on the second-order curve function of the improved SDT algorithm, and after completing the data compression of the compression starting data point, sequentially extract the data points to be compressed from the process data for data compression, until a new compression data starting point is determined, and store the data points to be compressed after the data compression before the new compression data starting point to complete a data compression; a second processing module, used to continue to perform data compression on the remaining process data based on the improved SDT algorithm starting from the new compression data starting point, until the compression of all the process data to be compressed is completed and the processing is stopped. By using the improved SDT algorithm to compress the process data, the data compression processing efficiency and compression effect are improved.

[0058] See also Figure 5 , Figure 5 This is a schematic diagram of the structure of an electronic device provided in an embodiment of the present application. Figure 5 As shown in , the electronic device 500 includes a processor 510 , a memory 520 and a bus 530 .

[0059] The memory 520 stores machine-readable instructions executable by the processor 510. When the electronic device 500 is running, the processor 510 communicates with the memory 520 via the bus 530. When the machine-readable instructions are executed by the processor 510, the above-mentioned Figure 1 as well as Figure 2 The specific implementation of the steps of the method for securely compressing process data in the method embodiment shown can be found in the method embodiment, and will not be described in detail here.

[0060] The present application also provides a computer-readable storage medium on which a computer program is stored. When the computer program is executed by a processor, the computer program can execute the above-mentioned Figure 1 as well as Figure 2 The specific implementation of the steps of the method for securely compressing process data in the method embodiment shown can be found in the method embodiment, and will not be described in detail here.

[0061] Those skilled in the art can clearly understand that, for the convenience and brevity of description, the specific working processes of the systems, devices and units described above can refer to the corresponding processes in the aforementioned method embodiments and will not be repeated here.

[0062] In the several embodiments provided in the present application, it should be understood that the disclosed systems, devices and methods can be implemented in other ways. The device embodiments described above are merely schematic. For example, the division of the units is only a logical function division. There may be other division methods in actual implementation. For example, multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some communication interfaces, and the indirect coupling or communication connection of devices or units can be electrical, mechanical or other forms.

[0063] The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed on multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0064] In addition, each functional unit in each embodiment of the present application may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit.

[0065] If the functions are implemented in the form of software functional units and sold or used as independent products, they can be stored in a non-volatile computer-readable storage medium that is executable by a processor. Based on this understanding, the technical solution of the present application, or the part that contributes to the prior art or the part of the technical solution, can be embodied in the form of a software product. The computer software product is stored in a storage medium, including several instructions for a computer device (which can be a personal computer, server, or network device, etc.) to execute all or part of the steps of the method described in each embodiment of the present application. The aforementioned storage medium includes: U disk, mobile hard disk, read-only memory (ROM), random access memory (RAM), disk or optical disk, and other media that can store program codes.

[0066] Finally, it should be noted that the above-described embodiments are only specific implementation methods of the present application, which are used to illustrate the technical solutions of the present application, rather than to limit them. The protection scope of the present application is not limited thereto. Although the present application is described in detail with reference to the above-mentioned embodiments, ordinary technicians in the field should understand that any technician familiar with the technical field can still modify the technical solutions recorded in the above-mentioned embodiments within the technical scope disclosed in the present application, or can easily think of changes, or make equivalent replacements for some of the technical features therein; and these modifications, changes or replacements do not make the essence of the corresponding technical solutions deviate from the spirit and scope of the technical solutions of the embodiments of the present application, and should be included in the protection scope of the present application. Therefore, the protection scope of the present application shall be based on the protection scope of the claims.

Claims

1. A method for secure compression of process data, characterized in that: The secure compression method comprises: Acquire a set of process data to be compressed, and determine a compression starting data point of the process data; wherein the compression starting data point is composed of an initial time point and a process data value at the initial time point; The compression starting data point is subjected to data compression based on the second-order curve function of the improved SDT algorithm, and after the data compression of the compression starting data point is completed, the data points to be compressed are sequentially taken out from the process data for data compression until a new compression data starting point is determined, and the data points to be compressed after the data compression before the new compression data starting point are stored to complete one data compression; Continue to compress the remaining process data from the new compressed data starting point based on the improved SDT algorithm until the compression of all the process data to be compressed is completed and then stop the processing.

2. The secure compression method according to claim 1, characterized in that: The second-order curve function based on the improved SDT algorithm performs data compression processing on the compression starting data point, including: Substituting the compression starting data point into the second-order curve function to determine the maximum variable value and the minimum variable value corresponding to the compression starting data point; The compression starting data point is subjected to data compression processing based on the maximum variable value and the minimum variable value.

3. The secure compression method according to claim 2, characterized in that: The second-order curve function is: y= a·t 2 +b ΔE Among them, a is the variable value, t is the time of compressing the data point, b is the process data value of the compressed data point, y is the compressed process data value, and ΔE is the compression accuracy parameter of the improved SDT algorithm.

4. The secure compression method according to claim 2, characterized in that: The performing data compression processing on the compression starting data point based on the maximum variable value and the minimum variable value includes: If the minimum variable value is greater than or equal to the maximum variable value, the maximum variable value is increased and the minimum variable value is decreased, so that a target variable value that can fit all data points is determined between the increased maximum variable value and the decreased minimum variable value; Substitute the target variable value and the compression starting data point into the second-order curve function to perform data compression processing on the compression starting data point.

5. The secure compression method according to claim 1, characterized in that: The new compressed data starting point is determined by the following steps: Substituting the compressed data point into the second-order curve function to determine the maximum variable value and the minimum variable value corresponding to the compressed data point; If the minimum variable value is smaller than the maximum variable value, the compressed data point is used as a new compressed data starting point.

6. The secure compression method according to claim 1, characterized in that: After continuing to compress the remaining process data from the new compressed data starting point based on the improved SDT algorithm until the compression of all the process data to be compressed is completed and then stopping the processing, the secure compression method further includes: The compressed process data is encrypted based on the homomorphic encryption algorithm.

7. The secure compression method according to claim 1, characterized in that: Before obtaining a set of process data to be compressed and determining a compression starting data point of the process data, the secure compression method further includes: A change threshold of process data is set, and abnormal process data values ​​exceeding the threshold are eliminated to reduce error interference of noise data.

8. A secure compression device for process data, characterized in that: The safety compression device comprises: An acquisition module, used to acquire a set of process data to be compressed, and determine a compression starting data point of the process data; wherein the compression starting data point is composed of an initial time point and a process data value at the initial time point; A first processing module is used to perform data compression processing on the compression starting data point based on the second-order curve function of the improved SDT algorithm, and after completing the data compression of the compression starting data point, sequentially extract the data points to be compressed from the process data for data compression until a new compression data starting point is determined, and store the data points to be compressed after the data compression before the new compression data starting point, so as to complete one data compression; The second processing module is used to continue to compress the remaining process data from the new compressed data starting point based on the improved SDT algorithm until the compression of all the process data to be compressed is completed and the processing is stopped.

9. An electronic device, characterized in that: include: A processor, a memory and a bus, wherein the memory stores machine-readable instructions executable by the processor, and when the electronic device is running, the processor and the memory communicate via the bus, and the machine-readable instructions are executed by the processor to execute the steps of the method for secure compression of process data as described in any one of claims 1 to 7.

10. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the steps of the method for secure compression of process data according to any one of claims 1 to 7 are executed.

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