Dynamic production control system and method based on data collection

Abstract

The present invention discloses a dynamic production control system and method based on data collection, including: dividing the encryption result of the collected data into a plurality of binary numbers of fixed length, thereby obtaining a plaintext image, dividing all plaintext pixel points into a plurality of plaintext point pairs according to a verification key, scrambling the indexes of the horizontal and vertical coordinate axes in the tortoise shell matrix by a parameter key and a chaotic mapping algorithm, hiding the digital certificate of the device in all plaintext point pairs according to the scrambled tortoise shell matrix, obtaining a cipher image composed of all ciphertext point pairs, transmitting the data in the form of a cipher image, extracting verification information from the received cipher image by an Internet of Things platform, and when the verification information is the same as the digital certificate of the device stored in the Internet of Things platform, obtaining the data of the device according to the cipher image after extracting the verification information, so as to facilitate dynamic production control of the factory. The present invention provides accurate data support for subsequent dynamic production control of the factory.

Description

Technical Field

[0001] The present invention relates to the technical field of dynamic production control and management, and more specifically, to a dynamic production control and management system and method based on data collection. Background Art

[0002] In existing factory management, data between different devices and systems cannot be effectively integrated, resulting in information islands, which in turn affects production efficiency and product quality. These problems have prompted factories to provide equipment data collection based on IoT technology and data collection gateways, and transmit the collected equipment data to the IoT platform. The IoT platform uses the equipment data to dynamically control the factory's production, solving the information island of the last mile of the factory, opening up the connection between equipment, people, and systems, and allowing industrial data to play a greater value.

[0003] When data is transmitted between the data acquisition gateway and the IoT platform, the data will be encrypted before transmission to ensure that even if the data is intercepted during transmission, sensitive information can be prevented from being leaked to attackers. However, simple encryption cannot completely guarantee that the transmitted data will not be tampered with; therefore, in order to ensure the integrity of the data, it is necessary to detect whether the data has been tampered with during transmission. Summary of the invention

[0004] In order to solve the technical problem that when dynamically controlling the factory production based on the collected data, in order to ensure the integrity of the data, it is necessary to detect whether the data has been tampered with during the transmission process, the present invention provides solutions in the following aspects.

[0005] In a first aspect, the present invention provides a dynamic production control method based on data collection, including: collecting data of equipment in a factory based on a data collection gateway, and transmitting the data in the form of a confidential image, wherein the digital certificate of the equipment is hidden in the confidential image; the Internet of Things platform extracts verification information from the received confidential image, and when the verification information is the same as the digital certificate of the equipment stored in the Internet of Things platform, the data of the equipment is obtained according to the confidential image after the verification information is extracted, and dynamic production control of the factory is performed according to the data, wherein the dynamic production control includes equipment management, production management and data management; the method for obtaining the confidential image is: encrypting the data according to the information key; dividing the encrypted data into A plurality of fixed-length binary numbers are used, and all decimal numbers corresponding to all binary numbers are used as the grayscale values ​​of all plaintext pixels constituting the plaintext image; all plaintext pixels are divided into a plurality of plaintext point pairs according to the fixed direction and fixed step length in the verification key; the indexes of the horizontal and vertical axes in the tortoise shell matrix are scrambled by the parameter key and the chaotic mapping algorithm; according to the scrambled tortoise shell matrix, the digital certificate of the device is used as the secret information and hidden in all the plaintext point pairs by the image information hiding algorithm based on the tortoise shell matrix to obtain all the ciphertext point pairs; all the ciphertext point pairs are combined into a secret image; the information key, the verification key and the parameter key are all agreed upon by the data acquisition gateway and the Internet of Things platform.

[0006] The present invention transmits the data of the device in the form of a secret image through a data acquisition gateway, and hides the digital certificate of the device in the secret image. The Internet of Things platform extracts verification information from the received secret image, and compares it with the digital certificate of the device stored in the Internet of Things platform to detect whether the data of the device transmitted between the data acquisition gateway and the Internet of Things platform is tampered with. In the process of obtaining the secret image, the encryption result of the data is converted into a plaintext image. In the process of hiding the digital certificate of the device as secret information in the plaintext image, the combination mode of the plaintext point pair is determined according to the fixed direction and fixed step length in the verification key, and the indexes of the horizontal and vertical axes in the tortoise shell matrix are scrambled by the parameter key and the chaotic mapping algorithm. Finally, according to the scrambled tortoise shell matrix, the secret information is hidden in the plaintext point pair, so as to increase the difficulty for an attacker to crack and steal the digital certificate of the device from the secret image, and also increase the difficulty for an attacker to tamper with the data of the device contained in the secret image, thereby ensuring the integrity of the data of the device received by the Internet of Things platform, providing accurate data support for the subsequent dynamic production control of the factory, and thus improving the production efficiency and product quality of the factory.

[0007] Preferably, the encrypting of data according to the information key includes: the data acquisition gateway creates a key pair that complies with the RSA algorithm as the information key, the key pair includes a private key and a public key, and sends the public key in the information key to the Internet of Things platform; the data acquisition gateway encrypts the data according to the private key in the information key through the RSA algorithm to obtain the encryption result of the data.

[0008] Preferably, the fixed direction in the verification key has a value range of , when the fixed direction exist When the value of the fixed step length in the verification key is within ; When the fixed direction exist When the value of the fixed step length in the verification key is within , is the inverse tangent function, , Respectively represent the number of rows and columns of the plaintext image.

[0009] Preferably, the method of dividing all plaintext pixel points into a plurality of plaintext point pairs according to the fixed direction and the fixed step length in the verification key includes: calculating the horizontal coordinate offset according to the fixed direction and the fixed step length. and the vertical offset ; Set the coordinates in the plaintext image to Plaintext pixels With coordinates Plaintext pixels , forming a plaintext pair ; , They are plaintext pixels. The horizontal and vertical coordinates of The value range is , The value range is , , Respectively represent the number of rows and columns of the plaintext image, , Plain text pixels The horizontal and vertical coordinates satisfy the expressions: ; .

[0010] Preferably, the calculation of the horizontal coordinate offset and the vertical offset The formula satisfies the following expression: ; ; In the formula, For fixed direction, is a fixed step size, is the horizontal axis offset, is the vertical axis offset, is the tangent function in trigonometric function.

[0011] Preferably, the method of scrambling the indexes of the horizontal and vertical axes in the tortoise shell matrix by using the parameter key and the chaotic mapping algorithm includes: generating the parameter key according to the initial conditions of the two-dimensional chaotic mapping algorithm; iterating the equation of the two-dimensional chaotic mapping algorithm according to the parameter key. times, and each iteration obtains a chaotic value pair. is equal to the number of all gray values ​​in the range of [0,225]; each chaotic value pair consists of two chaotic values, and the two chaotic values ​​are the first chaotic value and the second chaotic value respectively; all first step lengths and all second step lengths are obtained according to all first chaotic values ​​and all second chaotic values, wherein the first step length The first step , No. Second step length , , Respectively The first chaos value and the second chaos value, is a rounding up function; all first step lengths are grouped into all first sequences, and all second step lengths are grouped into all second sequences; the first sequence and the second sequence are respectively used as step length sequences, and the indexes of the horizontal axis and the vertical axis in the tortoise shell matrix are scrambled respectively through the variable step size Joseph traversal algorithm to obtain the scrambled tortoise shell matrix.

[0012] Preferably, the method of using the scrambled tortoise shell matrix and an image information hiding algorithm based on the tortoise shell matrix to hide the digital certificate of the device as secret information in all plaintext point pairs to obtain all ciphertext point pairs includes: plaintext points, and the first Codeword to The binary number composed of code words is used as the plaintext point pairs, where According to the scrambled tortoise shell matrix, the image information hiding algorithm based on the tortoise shell matrix is ​​used to hide the first The embedded information of the plaintext pairs is hidden in the plaintext points, and obtain The ciphertext points are correct.

[0013] Preferably, the The embedded information of the plaintext pairs is hidden in the plaintext point pairs, including: The grayscale values ​​of the two plaintext pixels of the plaintext point pair are used to determine the The corresponding elements of the plaintext point pairs in the scrambled tortoise shell matrix ; with elements As the center point, a 3×3 matrix block is obtained from the scrambled tortoise shell matrix; according to The decimal number corresponding to the embedded information of the plaintext point pair is used to determine two new elements from the matrix block. and , according to the element and elements The coordinates in the scrambled tortoise shell matrix obtain two ciphertext point pairs, namely the main ciphertext point pair and the auxiliary ciphertext point pair. The main ciphertext point pair and the auxiliary ciphertext point pair together constitute the The ciphertext points are correct.

[0014] Preferably, forming all ciphertext point pairs into a secret image includes: an image formed by all primary ciphertext point pairs is recorded as a first ciphertext image; an image formed by all auxiliary ciphertext point pairs is recorded as a second ciphertext image; the first ciphertext image and the second ciphertext image together constitute the secret image.

[0015] In a second aspect, the present invention provides a dynamic production control system based on data collection, including a processor and a memory, wherein the memory stores computer program instructions, and when the computer program instructions are executed by the processor, the above-mentioned dynamic production control method based on data collection is implemented.

[0016] By adopting the above technical solution, the above-mentioned dynamic production control method based on data collection is generated into a computer program and stored in a memory to be loaded and executed by a processor, so that a terminal device is made according to the memory and the processor for easy use.

[0017] The beneficial effects of the present invention are:

[0018] The present invention transmits the data of the device in the form of a secret image through a data acquisition gateway, and hides the digital certificate of the device in the secret image. The Internet of Things platform extracts verification information from the received secret image, and compares it with the digital certificate of the device stored in the Internet of Things platform to detect whether the data of the device transmitted between the data acquisition gateway and the Internet of Things platform is tampered with. In the process of obtaining the secret image, the encryption result of the data is converted into a plaintext image. In the process of hiding the digital certificate of the device as secret information in the plaintext image, the combination mode of the plaintext point pair is determined according to the fixed direction and fixed step length in the verification key, and the indexes of the horizontal and vertical axes in the tortoise shell matrix are scrambled by the parameter key and the chaotic mapping algorithm. Finally, according to the scrambled tortoise shell matrix, the secret information is hidden in the plaintext point pair, so as to increase the difficulty for an attacker to crack and steal the digital certificate of the device from the secret image, and also increase the difficulty for an attacker to tamper with the data of the device contained in the secret image, thereby ensuring the integrity of the data of the device received by the Internet of Things platform, providing data analysis and decision support for subsequent dynamic production control of the factory, thereby improving the production efficiency and product quality of the factory. BRIEF DESCRIPTION OF THE DRAWINGS

[0019] The above and other purposes, features and advantages of the exemplary embodiments of the present invention will become readily understood by reading the detailed description below through the accompanying drawings. In the accompanying drawings, several embodiments of the present invention are shown in an exemplary and non-limiting manner, and the same or corresponding reference numerals represent the same or corresponding parts, wherein:

[0020] Figure 1 is a flow chart schematically illustrating a dynamic production control method based on data collection in the present invention;

[0021] Figure 2 It is a topological diagram schematically showing data collection and transmission between a data collection gateway, a device, and an IoT platform;

[0022] Figure 3 is a flow chart schematically illustrating a method for obtaining a confidential image in step S2;

[0023] Figure 4 is a schematic diagram schematically illustrating a tortoise shell matrix;

[0024] Figure 5 is a schematic diagram schematically showing a scrambled tortoise shell matrix. DETAILED DESCRIPTION

[0025] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative work are within the scope of protection of the present invention.

[0026] The specific embodiments of the present invention are described in detail below with reference to the accompanying drawings.

[0027] The embodiment of the present invention discloses a dynamic production control method based on data collection, referring to Figure 1 , including steps S1 to S3:

[0028] Based on the Internet of Things technology and data acquisition gateway, the factory is provided with data collection for equipment such as injection molding machines, CNC machine tools, and PLC controllers, and the collected equipment data is transmitted to the Internet of Things platform. The Internet of Things platform uses the equipment data to conduct effective equipment management, production management, and data management, thereby realizing dynamic production control of the factory, solving the information island of the last mile of the factory, and opening up the connection between equipment, people, and systems, allowing industrial data to play a greater value.

[0029] The topology diagram of data collection and transmission between data collection gateway, devices and IoT platform is as follows: Figure 2 As shown, the main process is: data from equipment in the factory is collected based on the data acquisition gateway and the data is transmitted. The IoT platform dynamically controls the factory production based on the received data.

[0030] When data is transmitted between the data acquisition gateway and the IoT platform, the data will be encrypted before transmission to ensure that even if the data is intercepted during transmission, sensitive information can be prevented from being leaked to attackers. However, simple encryption cannot completely guarantee that the transmitted data will not be tampered with; therefore, in order to ensure the integrity of the data, it is necessary to detect whether the data has been tampered with during transmission.

[0031] S1. Collect data from equipment in the factory based on the data acquisition gateway.

[0032] Specifically, data of equipment in the factory is collected based on a data collection gateway; the data collection gateway involves a collection gateway for multiple categories of data, including but not limited to an injection molding machine collection gateway, a CNC (numerical control machining) collection gateway, a PLC (programmable logic controller) collection gateway, an IO collection gateway, an energy consumption collection gateway, and an environment collection gateway; the data of the collected equipment involves multiple dimensions, including but not limited to real-time output data, equipment status data, process parameter data, fault alarm data, and production energy consumption data.

[0033] Among them, through real-time monitoring of the collected real-time output data, the production progress can be grasped at any time; through the collected equipment status data, the equipment operation status can be effectively monitored and the operation status of the production line can be accurately understood; through the collected process parameter data, process traceability can be achieved and the yield rate can be improved; through the collected fault alarm data, abnormal situations such as equipment failure and shutdown can be monitored, fault handling time can be reduced, and equipment utilization can be improved; through the collected production energy consumption data, equipment electricity consumption can be monitored, and waste can be discovered in time, which helps enterprises achieve energy saving in management and reduce costs; therefore, data collection brings multi-dimensional practical value to the factory, such as production monitoring, quality traceability, predictive maintenance, reverse control, etc., discovers problems through data, and makes decisions driven by data, which promotes the digital transformation and upgrading of the factory.

[0034] S2. Transmit the data in the form of a encrypted image.

[0035] Specifically, the data is transmitted in the form of a secret image, in which the digital certificate of the device is hidden. The flowchart of the method for obtaining the secret image in step S2 is shown in FIG. Figure 3 , including steps S201 to S205, specifically:

[0036] S201. The data collection gateway encrypts the data of the device using the information key to obtain the encryption result of the data.

[0037] Specifically, the data acquisition gateway creates a key pair that complies with the RSA algorithm as an information key. The key pair includes a private key and a public key for encrypted communication. The data acquisition gateway sends its public key to the IoT platform so that the IoT platform can decrypt the encryption result of the received data according to the public key to obtain the device data. Therefore, the information key is jointly agreed upon by the data acquisition gateway and the IoT platform.

[0038] Furthermore, the data acquisition gateway encrypts the data of the device through the RSA algorithm according to its own private key to obtain an encryption result of the data, wherein the encryption result is a binary sequence, and the binary sequence is composed of multiple code words, and the code words include digital 0 and digital 1; and the RSA algorithm is a well-known technology and will not be described here.

[0039] S202, dividing the encryption result of the data into a plurality of binary numbers of fixed length, thereby obtaining a plaintext image.

[0040] Specifically, the encryption result of the data is divided into a plurality of binary numbers of fixed length. In this embodiment, the fixed length is equal to 8.

[0041] Furthermore, all decimal numbers corresponding to all binary numbers are used as the grayscale values ​​of all plaintext pixels constituting the plaintext image.

[0042] It should be noted that the present invention uses all decimal numbers corresponding to all binary numbers as the grayscale values ​​of all plaintext pixels constituting the plaintext image. Since the range of grayscale values ​​is [0, 225], the length of the obtained binary number is equal to 8, so as to ensure that the grayscale values ​​of the plaintext pixels in the obtained plaintext image are within the range of [0, 225].

[0043] S203. Divide all plaintext pixel points in the plaintext image into a plurality of plaintext point pairs according to the verification key.

[0044] Specifically, the verification key is agreed upon by the data collection gateway and the Internet of Things platform. The verification key includes a fixed direction and a fixed step length. The value range of the fixed direction is , when the fixed direction exist When , the fixed step size range is ; When the fixed direction exist When , the fixed step size range is , is the inverse tangent function, , Respectively represent the number of rows and columns of the plaintext image.

[0045] Further, according to the fixed direction and fixed step length in the verification key, all plaintext pixel points are divided into multiple plaintext point pairs, including: according to the fixed direction and fixed step length, the horizontal coordinate offset is calculated and the vertical offset ; Set the coordinates in the plaintext image to Plaintext pixels With coordinates Plaintext pixels , forming a plaintext pair ; , Plain text pixels The horizontal and vertical coordinates of The value range is , The value range is , , Respectively represent the number of rows and columns of the plaintext image, , Plain text pixels The horizontal and vertical coordinates of .

[0046] In the process of dividing all the plaintext pixels in the plaintext image into a plurality of plaintext point pairs, the plaintext point pairs corresponding to each plaintext pixel in the plaintext image are obtained in sequence according to the order of zigzag scanning.

[0047] Among them, the plaintext pixel The horizontal axis and the vertical coordinate Satisfy the expressions:

[0048] ;

[0049] ;

[0050] In the formula, , Plain text pixels The horizontal and vertical coordinates of , are the horizontal and vertical offsets respectively. , Plain text pixels The horizontal and vertical coordinates of .

[0051] Wherein, the calculation of the horizontal coordinate offset and the vertical offset The formula satisfies the expression:

[0052] ;

[0053] ;

[0054] In the formula, For fixed direction, is a fixed step size, is the horizontal axis offset, is the vertical axis offset, is the tangent function in trigonometric function.

[0055] S204, scrambling the indexes of the horizontal and vertical axes in the tortoise shell matrix by using a parameter key and a chaotic mapping algorithm to obtain a scrambled tortoise shell matrix.

[0056] 1. Generate parameter keys based on the initial conditions of the two-dimensional chaotic mapping algorithm.

[0057] It should be noted that chaotic mapping functions are pseudo-random, sensitive to initial conditions, non-periodic and long-term unpredictable, and are often used as key generators.

[0058] Specifically, the parameter keys are jointly agreed upon by the data acquisition gateway and the Internet of Things platform. Within the value range of the initial conditions of the two-dimensional chaotic mapping algorithm, an initial condition is randomly generated as the parameter key. This embodiment only takes the two-dimensional Logistic chaotic mapping algorithm as an example for description. In other embodiments, other two-dimensional chaotic mapping algorithms can be used to generate parameter keys. The two-dimensional chaotic mapping algorithm includes but is not limited to a two-dimensional Henon mapping chaotic algorithm and a Lotka-Volterra model. The two-dimensional Logistic chaotic mapping algorithm, the two-dimensional Henon mapping chaotic algorithm and the Lotka-Volterra model are all well-known technologies and will not be described in detail here.

[0059] The initial conditions of the two-dimensional Logistic chaotic mapping algorithm include 4 parameters and 2 initial values. As parameters, and is the initial value, and the parameter The value range is ,parameter The value range is ,parameter The value range is ,parameter The value range is , initial value and The value range of ,in, is an interval open on the left and closed on the right, For open interval.

[0060] When the parameters and initial values ​​are within their respective ranges, the two-dimensional Logistic chaotic mapping algorithm is in a chaotic state. Therefore, within the range of the parameters and initial values ​​of the two-dimensional Logistic chaotic mapping algorithm, an initial condition is randomly generated. , as the parameter key.

[0061] 2. Generate multiple chaotic value pairs according to the parameter key and the two-dimensional chaotic mapping algorithm, and then obtain the first sequence and the second sequence.

[0062] Specifically, according to the parameter key, the equation of the two-dimensional chaos mapping algorithm is iterated times, and each iteration obtains a chaotic value pair; each chaotic value pair consists of two chaotic values, and the two chaotic values ​​are respectively a first chaotic value and a second chaotic value. In this embodiment, is equal to the number of all grayscale values ​​in the range [0,225], so Equal to 256.

[0063] Further, all the first step lengths are obtained according to all the first chaos values, then The first step , For the The first chaos value, is the rounding up function; according to all the second chaotic values, all the second step lengths are obtained, then Second step length , For the The second chaos value, is the ceiling function.

[0064] Furthermore, all first step lengths are grouped into all first sequences, and all second step lengths are grouped into all second sequences.

[0065] 3. According to the first sequence and the second sequence, the indexes of the horizontal and vertical axes in the tortoise shell matrix are scrambled to obtain the scrambled tortoise shell matrix.

[0066] The tortoise shell matrix is ​​a 256×256 matrix with special distribution rules for elements. The value of each element in the tortoise shell matrix is ​​between [0,7] and arranged according to a certain difference rule. Each tortoise shell area in the tortoise shell matrix contains 8 values ​​from 0 to 7 without redundancy. The schematic diagram of the tortoise shell matrix is ​​as follows Figure 4 As shown, the indexes in the horizontal and vertical axes include all grayscale values ​​in the range of [0,255].

[0067] Specifically, the first sequence is used as the step sequence, and the index of the horizontal axis in the tortoise shell matrix is ​​scrambled through the variable step size Joseph traversal algorithm. Then the second sequence is used as the step sequence, and the index of the vertical axis in the tortoise shell matrix is ​​scrambled through the variable step size Joseph traversal algorithm to obtain the scrambled tortoise shell matrix; the variable step size Joseph traversal algorithm is a well-known technology and will not be described here.

[0068] It should be noted that the indexes of the horizontal and vertical axes in the conventional turtle shell matrix are arranged in order from small to large, such as Figure 4 As shown, therefore, the horizontal and vertical axes of adjacent elements in the conventional tortoise shell matrix are relatively close. Subsequently, after the secret information is hidden in the plaintext image through the image information hiding algorithm based on the tortoise shell matrix, the grayscale values ​​of the pixels at the same position in the secret image and the plaintext image are relatively close. In other words, the secret image retains most of the features in the plaintext image, resulting in the ability to infer the data corresponding to the plaintext image through the secret image.

[0069] It should be further explained that, in this embodiment, the indexes of the horizontal and vertical axes in the tortoise shell matrix are scrambled by using the parameter key and the chaotic mapping algorithm to obtain the scrambled tortoise shell matrix, such as Figure 5As shown, the horizontal and vertical coordinate axes of adjacent elements in the scrambled tortoise shell matrix are quite different. After the secret information is subsequently hidden in the plaintext image through the image information hiding algorithm based on the tortoise shell matrix, the grayscale values ​​of pixels at the same position in the secret image and the plaintext image are quite different. In other words, the secret image does not have the features in the plaintext image, and it is impossible to infer the data corresponding to the plaintext image through the secret image, which further ensures the data security of the device.

[0070] S205. According to the scrambled tortoise shell matrix, the digital certificate of the device is used as secret information and hidden in all plaintext point pairs to obtain a secret image.

[0071] Specifically, the digital certificate of the device is used as the secret information. According to the scrambled tortoise shell matrix, the secret information is hidden in all plaintext point pairs through the image information hiding algorithm based on the tortoise shell matrix, all ciphertext point pairs are obtained, and all ciphertext point pairs are combined into a secret image.

[0072] Before the device leaves the factory, a centralized certificate authority (CA) is used to issue and manage the device's digital certificate, which is stored in the device. The device's digital certificate is a binary sequence.

[0073] Among them, for the plaintext points, and the first Codeword to The binary number composed of code words is used as the plaintext point pairs; in this embodiment, .

[0074] Furthermore, through the image information hiding algorithm based on the tortoise shell matrix, the The embedded information of the plaintext pairs is hidden in the plaintext points, and obtain The image information hiding algorithm based on the tortoise shell matrix is ​​a well-known technology and will not be described in detail here.

[0075] Among them, the The embedded information of the plaintext pairs is hidden in the The specific process of the plaintext point pair is as follows: The grayscale values ​​of the two plaintext pixels of the plaintext point pair are used to determine the The corresponding elements of the plaintext point pairs in the scrambled tortoise shell matrix ; with elements As the center point, a 3×3 matrix block is obtained from the scrambled tortoise shell matrix; according to The decimal number corresponding to the embedded information of the plaintext point pair is used to determine two new elements from the matrix block. and , according to the element and elements The coordinates in the scrambled tortoise shell matrix obtain two ciphertext point pairs, namely the main ciphertext point pair and the auxiliary ciphertext point pair.

[0076] Furthermore, the image composed of all the main ciphertext point pairs is recorded as the first ciphertext image; the image composed of all the auxiliary ciphertext point pairs is recorded as the second ciphertext image; the first ciphertext image and the second ciphertext image together constitute the secret image.

[0077] It should be noted that, subsequently, based on the first ciphertext image and the second ciphertext image constituting the secret image, the secret information can be extracted without distortion, and the plaintext image can be restored completely and correctly.

[0078] It should be noted that, in the process of acquiring the secret image, the present invention converts the encryption result of the data into a plaintext image, and in the process of hiding the digital certificate of the device as secret information in the plaintext image, determines the combination of plaintext point pairs according to the fixed direction and fixed step size in the verification key, and scrambles the indexes of the horizontal and vertical axes in the tortoise shell matrix through the parameter key and the chaotic mapping algorithm. Finally, according to the scrambled tortoise shell matrix, the secret information is hidden in the plaintext point pairs, thereby increasing the difficulty for attackers to crack and steal the digital certificate of the device from the secret image, and also increasing the difficulty for attackers to tamper with the data of the device contained in the secret image, thereby ensuring the integrity of the data of the device received by the Internet of Things platform, and providing accurate data support for the subsequent dynamic production control of the factory, thereby improving the factory's production efficiency and product quality.

[0079] S3. The IoT platform extracts verification information from the received confidential image. When the verification information is the same as the digital certificate of the device stored in the IoT platform, the device data is obtained based on the confidential image after the verification information is extracted, and the factory is dynamically controlled in production based on the data.

[0080] Specifically, for the secret image received by the Internet of Things platform, according to the verification key and the parameter key, the verification information is extracted from the secret image through the inverse process of the image information hiding algorithm based on the tortoise shell matrix, and the secret image after the verification information is extracted is obtained; wherein, the verification key and the parameter key are jointly agreed upon by the data acquisition gateway and the Internet of Things platform. At this time, the verification key is used to divide the secret image into ciphertext point pairs, and the parameter key is used to obtain the scrambled tortoise shell matrix; the inverse process of the image information hiding algorithm based on the tortoise shell matrix is ​​a well-known technology and will not be repeated here.

[0081] Furthermore, when the verification information is the same as the digital certificate of the device stored in the Internet of Things platform, the data of the device is obtained based on the encrypted image after extracting the verification information, and the factory is dynamically controlled in production based on the data. The dynamic production control includes equipment management, production management and data management.

[0082] The method of obtaining the data of the device according to the secret image after the verification information is extracted includes: obtaining, for the secret image after the verification information is extracted, binary numbers corresponding to the grayscale values ​​of all pixels in the secret image after the verification information is extracted, wherein the length of the binary number is equal to a fixed length; obtaining a sequence composed of all binary numbers of fixed length, decrypting the sequence through the RSA algorithm according to the information key, mainly the public key of the existing data acquisition gateway of the Internet of Things platform, to obtain the data of the device.

[0083] Among them, the equipment management refers to setting process parameters, quality parameters, and real-time parameters for equipment based on the individual needs of different industries, and conducting comparative analysis to achieve timely early warning of abnormal deviations; the production management refers to the management of production planning and scheduling, production reporting, and production abnormality and light alarms based on the common needs of the workshop; the data management realizes visual management of data and conducts data report analysis by providing workshop boards, 3D boards, cockpit boards, digital twin boards, etc.

[0084] It should be noted that the present invention transmits the data of the device in the form of a confidential image through the data acquisition gateway, and hides the digital certificate of the device in the confidential image. The Internet of Things platform extracts verification information from the received confidential image, and compares it with the digital certificate of the device stored in the Internet of Things platform to detect whether the data of the device transmitted between the data acquisition gateway and the Internet of Things platform has been tampered with, thereby ensuring the integrity of the data of the device received by the Internet of Things platform, providing accurate data support for subsequent dynamic production control of the factory, thereby improving the factory's production efficiency and product quality.

[0085] An embodiment of the present invention further discloses a dynamic production control system based on data collection, including a processor and a memory, wherein the memory stores computer program instructions, and when the computer program instructions are executed by the processor, a dynamic production control method based on data collection according to the present invention is implemented.

[0086] The above system also includes other components well known to those skilled in the art, such as a communication bus and a communication interface, and their configuration and functions are known in the art, so they will not be described in detail here.

[0087] In the description of this specification, "plurality" or "several" means at least two, such as two, three or more, etc., unless otherwise clearly and specifically defined.

[0088] Although this specification has shown and described a number of embodiments of the present invention, it will be apparent to those skilled in the art that such embodiments are provided by way of example only. Those skilled in the art will conceive of many modifications, changes and alternatives without departing from the ideas and spirit of the present invention. It should be understood that in the practice of the present invention, alternatives to the embodiments of the present invention described herein may be employed.

Claims

1. A dynamic production control method based on data collection, characterized in that: include: Collect data from devices in the factory based on a data collection gateway and transmit the data in the form of a encrypted image, in which the digital certificate of the device is hidden; The IoT platform extracts verification information from the received encrypted image. When the verification information is the same as the digital certificate of the device stored in the IoT platform, the device data is obtained according to the encrypted image after the verification information is extracted, and the factory is dynamically controlled based on the data. The dynamic production control includes equipment management, production management and data management. The method for obtaining the encrypted image is as follows: encrypting the data according to the information key; dividing the encrypted data into a plurality of binary numbers of fixed length, using all decimal numbers corresponding to all the binary numbers as the grayscale values ​​of all the plaintext pixels constituting the plaintext image; dividing all the plaintext pixels into a plurality of plaintext point pairs according to the fixed direction and fixed step length in the verification key; The indexes of the horizontal and vertical axes in the tortoise shell matrix are scrambled by using parameter keys and chaotic mapping algorithms; According to the scrambled tortoise shell matrix, the digital certificate of the device is used as secret information and hidden in all plaintext point pairs through the image information hiding algorithm based on the tortoise shell matrix to obtain all ciphertext point pairs, including: plaintext points, and the first Codeword to The binary number composed of code words is used as the The embedded information of plaintext pairs, among which, ; According to the composition The grayscale values ​​of the two plaintext pixels of the plaintext point pair are used to determine the The corresponding elements of the plaintext point pairs in the scrambled tortoise shell matrix ; with elements As the center point, a 3×3 matrix block is obtained from the scrambled tortoise shell matrix; according to The decimal number corresponding to the embedded information of the plaintext point pair is used to determine two new elements from the matrix block. and , according to the element and elements The coordinates in the scrambled tortoise shell matrix obtain two ciphertext point pairs, namely the main ciphertext point pair and the auxiliary ciphertext point pair. The main ciphertext point pair and the auxiliary ciphertext point pair together constitute the ciphertext point pairs; all ciphertext point pairs are combined into a encrypted image; the information key, verification key and parameter key are all jointly agreed upon by the data acquisition gateway and the Internet of Things platform.

2. The dynamic production control method based on data collection according to claim 1 is characterized in that: The step of encrypting data according to the information key comprises: The data acquisition gateway creates a key pair that complies with the RSA algorithm as an information key, wherein the key pair includes a private key and a public key, and sends the public key in the information key to the IoT platform; The data collection gateway encrypts the data using the RSA algorithm based on the private key in the information key to obtain the encryption result of the data.

3. The dynamic production control method based on data collection according to claim 1 is characterized in that: The fixed direction in the verification key has a value range of , when the fixed direction exist When the value of the fixed step length in the verification key is within ; When the fixed direction exist When the value of the fixed step length in the verification key is within , is the inverse tangent function, , Respectively represent the number of rows and columns of the plaintext image.

4. The dynamic production control method based on data collection according to claim 1 is characterized in that: According to the fixed direction and fixed step size in the verification key, all plaintext pixel points are divided into multiple plaintext point pairs, including: Calculate the horizontal coordinate offset based on the fixed direction and fixed step size and the vertical offset ; The coordinates in the plaintext image are Plaintext pixels With coordinates Plaintext pixels , forming a plaintext pair ; , Plain text pixels The horizontal and vertical coordinates of The value range is , The value range is , , Respectively represent the number of rows and columns of the plaintext image, , Plain text pixels The horizontal and vertical coordinates satisfy the expressions: ; .

5. The dynamic production control method based on data collection according to claim 4 is characterized in that: The calculation of the horizontal coordinate offset and the vertical offset The formula satisfies the following expression: ； ； In the formula, For fixed direction, is a fixed step size, is the horizontal axis offset, is the vertical axis offset, is the tangent function in trigonometric function.

6. The dynamic production control method based on data collection according to claim 1 is characterized in that: The method of scrambling the indexes of the horizontal and vertical axes in the tortoise shell matrix by using the parameter key and the chaotic mapping algorithm includes: Generate parameter keys according to the initial conditions of the two-dimensional chaotic mapping algorithm; According to the parameter key, the equation of the two-dimensional chaos mapping algorithm is iterated times, and each iteration obtains a chaotic value pair. is equal to the number of all gray values ​​in the range of [0,225]; each chaotic value pair consists of two chaotic values, and the two chaotic values ​​are the first chaotic value and the second chaotic value respectively; All first step lengths and all second step lengths are obtained according to all first chaotic values ​​and all second chaotic values, where The first step , No. Second step length , , Respectively The first chaos value and the second chaos value, is a rounding up function; all first step lengths are grouped into all first sequences, and all second step lengths are grouped into all second sequences; The first sequence and the second sequence are respectively used as step sequences, and the index of the horizontal axis and the index of the vertical axis in the tortoise shell matrix are scrambled respectively through the variable step size Joseph traversal algorithm to obtain the scrambled tortoise shell matrix.

7. The dynamic production control method based on data collection according to claim 1 is characterized in that: The method of forming a ciphertext image from all ciphertext point pairs includes: The image composed of all the main ciphertext point pairs is recorded as the first ciphertext image; the image composed of all the auxiliary ciphertext point pairs is recorded as the second ciphertext image; the first ciphertext image and the second ciphertext image together constitute the secret image.

8. Dynamic production control system based on data collection, characterized by: include: A processor and a memory, wherein the memory stores computer program instructions, and when the computer program instructions are executed by the processor, a dynamic production control method based on data collection is implemented according to any one of claims 1 to 7.

Images