A CNC system encryption method and device based on the device's own features

Abstract

The present invention discloses a method and device for encrypting a numerical control system based on the inherent characteristics of the device. The method comprises: collecting the inherent characteristics of the industrial Internet devices in the numerical control system, generating the device fingerprint of the corresponding industrial Internet device based on the inherent characteristics of the industrial Internet device, and saving the generated device fingerprint; wherein the inherent characteristics of the industrial Internet device collected include: the inherent hardware information of the device and the response time of the device processing request; when the device communicates, identity authentication is achieved by verifying the device fingerprint of the communication device. The numerical control system encryption method of the present invention can be applied to the numerical control system, and can achieve the security protection of the numerical control system information. The method of the present invention has good protection performance and high execution efficiency.

Description

Technical Field

[0001] The present invention relates to the technical field of network security of numerical control systems, and in particular to a numerical control system encryption method and device based on device inherent characteristics. Background Art

[0002] CNC systems guarantee high efficiency in modern manufacturing. Through the interconnection of numerous devices and systems, the manufacturing industry has undergone a transformation and upgrade. However, as the core of the Industrial Internet, CNC systems inevitably face cybersecurity risks.

[0003] The development of CNC systems is characterized by integrated production systems, digital and parallel product development, agile production, and information-based enterprise management. The CNC manufacturing industry's production environment has evolved from a closed environment to an open one, creating opportunities for industrial viruses and cyberattacks. Once a CNC system is compromised, the entire industrial production system faces a devastating impact.

[0004] Currently, CNC systems lack security controls on external interfaces such as universal serial bus (USB), serial ports, and network ports. The storage and transmission of critical system data are also not encrypted. This exposes CNC system processing files, processing parameters, and important logs to the risk of theft and corruption. Traditional device identification solutions typically rely on identifiers such as device names, signatures, labels, and codes. However, these identifiers are susceptible to tampering or forgery. Summary of the Invention

[0005] This invention provides a CNC system encryption method and device based on the device's inherent characteristics to address the current lack of security control over external interfaces such as universal serial bus (USB), serial ports, and network ports in CNC systems. The storage and transmission of important system data is also not encrypted, which poses a risk of theft and destruction of information such as CNC system processing files, processing parameters, and important logs.

[0006] In order to solve the above technical problems, the present invention provides the following technical solutions:

[0007] In one aspect, the present invention provides a CNC system encryption method based on the device's own characteristics, comprising:

[0008] Collecting inherent characteristics of industrial Internet devices in the numerical control system, generating a device fingerprint of the corresponding industrial Internet device based on the inherent characteristics of the industrial Internet device, and saving the generated device fingerprint; wherein the inherent characteristics include: inherent hardware information of the device and response time of the device processing request;

[0009] When the device is communicating, identity authentication is achieved by verifying the device fingerprint of the communication device.

[0010] Furthermore, the collecting of the inherent characteristics of the industrial Internet devices in the numerical control system, generating a device fingerprint of the corresponding industrial Internet device based on the inherent characteristics of the industrial Internet device, and saving the generated device fingerprint include:

[0011] Collect the inherent characteristics of industrial Internet devices in the CNC system and generate device fingerprints of corresponding industrial Internet devices based on the inherent characteristics of the industrial Internet devices;

[0012] The generated device fingerprint is encrypted using a preset encryption algorithm;

[0013] Save the encrypted device fingerprint to a database of the preset type.

[0014] Furthermore, the collecting of the inherent characteristics of the industrial Internet devices in the numerical control system and generating the device fingerprint of the corresponding industrial Internet devices according to the inherent characteristics of the industrial Internet devices include:

[0015] The device hardware information is measured according to the preset character length requirement, and the device hardware information vector is obtained: U = {u1, u2, ..., u n}, wherein the hardware information includes multiple feature data, u i is the character string data collected from the i-th feature data corresponding to the corresponding device, i = 1, 2…n, and n is the number of feature data of the hardware information;

[0016] Set a weight vector for the hardware information measurement value, assign the weight vector to the hardware information, and obtain the hardware information fingerprint vector: in, is the collision probability of the i-th feature data;

[0017] Extract the response time of the device processing request, let M = {m1,m2,......,m n} is the cross-layer response time measurement value of a group of devices, B is the number of features in the equivalent vector, the estimate H of the global maximum value of the current group measurement value is selected as the heuristic threshold, and the threshold T is defined as {t1, t2, ..., t n}, where t i is the i-th cross-layer response time measurement value m i Corresponding threshold, i=1,2…n,t i Calculated by the following formula:

[0018]

[0019] Divide each cross-layer response time measurement value by its corresponding threshold to obtain the cross-layer response time fingerprint vector: S = {s1, s2, ..., s n};

[0020] Based on the hardware information fingerprint vector and the cross-layer response time fingerprint vector, the device fingerprint vector F is calculated:

[0021] F={λS,(1-λ)V}

[0022] Wherein, λ is the preset weight corresponding to the hardware information fingerprint vector.

[0023] Furthermore, the preset encryption algorithm is the SM2 algorithm.

[0024] Furthermore, the preset type of database is a relational database.

[0025] On the other hand, the present invention further provides a numerical control system encryption device based on the device's own characteristics, the numerical control system encryption device based on the device's own characteristics comprising:

[0026] Device fingerprint registration module, used for:

[0027] Collecting inherent characteristics of industrial Internet devices in the numerical control system, generating a device fingerprint of the corresponding industrial Internet device based on the inherent characteristics of the industrial Internet device, and saving the generated device fingerprint; wherein the inherent characteristics include: inherent hardware information of the device and response time of the device processing request;

[0028] Device fingerprint recognition module, used for:

[0029] When the device is communicating, identity authentication is achieved by verifying the device fingerprint of the communication device.

[0030] Furthermore, the device fingerprint registration module includes:

[0031] The device fingerprint extraction unit is used to collect the inherent characteristics of the industrial Internet devices in the numerical control system and generate the device fingerprint of the corresponding industrial Internet devices based on the inherent characteristics of the industrial Internet devices;

[0032] A data encryption unit, used to encrypt the generated device fingerprint using a preset encryption algorithm;

[0033] The device fingerprint database unit is used to save the encrypted device fingerprint into a database of a preset type.

[0034] Furthermore, the device fingerprint extraction unit is specifically used to:

[0035] The device hardware information is measured according to the preset character length requirement, and the device hardware information vector is obtained: U = {u1, u2, ..., u n}, wherein the hardware information includes multiple feature data, ui is the character string data collected from the i-th feature data corresponding to the corresponding device, i = 1, 2…n, and n is the number of feature data of the hardware information;

[0036] Set a weight vector for the hardware information measurement value, assign the weight vector to the hardware information, and obtain the hardware information fingerprint vector: in, is the collision probability of the i-th feature data;

[0037] Extract the response time of the device processing request, let M = {m1,m2,......,m n} is the cross-layer response time measurement value of a group of devices, B is the number of features in the equivalent vector, the estimate H of the global maximum value of the current group measurement value is selected as the heuristic threshold, and the threshold T is defined as {t1, t2, ..., t n}, where t i is the i-th cross-layer response time measurement value m i Corresponding threshold, i=1,2…n,t i Calculated by the following formula:

[0038]

[0039] Divide each cross-layer response time measurement value by its corresponding threshold to obtain the cross-layer response time fingerprint vector: S = {s1, s2, ..., s n};

[0040] Based on the hardware information fingerprint vector and the cross-layer response time fingerprint vector, the device fingerprint vector F is calculated:

[0041] F={λS,(1-λ)V}

[0042] Wherein, λ is the preset weight corresponding to the hardware information fingerprint vector.

[0043] Furthermore, the preset encryption algorithm adopted by the data encryption unit is the SM2 algorithm.

[0044] Furthermore, the preset type of database used by the device fingerprint database unit is a relational database.

[0045] On the other hand, the present invention further provides an electronic device, comprising a processor and a memory; wherein the memory stores at least one instruction, and the instruction is loaded and executed by the processor to implement the above method.

[0046] In yet another aspect, the present invention further provides a computer-readable storage medium, wherein the storage medium stores at least one instruction, and the instruction is loaded and executed by a processor to implement the above method.

[0047] The beneficial effects brought about by the technical solution provided by the present invention include at least:

[0048] In response to the problems of poor security of existing CNC systems and lack of security protection for storage and access of important data in CNC systems, the present invention provides a CNC system encryption method based on the device's own characteristics. This method can realize the extraction and entry of device fingerprints and device identification based on device fingerprints, thereby effectively resisting malicious attacks and information leakage suffered by the CNC system, thereby improving the security protection level of the CNC system, making up for the lack of security performance of the CNC system's data storage and access process, and ensuring the data security of the CNC system. BRIEF DESCRIPTION OF THE DRAWINGS

[0049] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the following briefly introduces the drawings required for use in the description of the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0050] Figure 1 This is a flow chart of a numerical control system encryption method based on device characteristics provided by an embodiment of the present invention;

[0051] Figure 2 This is a flow chart of the device fingerprint extraction and calculation method provided by an embodiment of the present invention;

[0052] Figure 3 This is a flow chart of data encryption and identity authentication based on the national secret algorithm provided by an embodiment of the present invention;

[0053] Figure 4 This is a flow chart of creating an encrypted device fingerprint database provided by an embodiment of the present invention;

[0054] Figure 5 This is a system block diagram of a device fingerprint registration module provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0055] To make the objectives, technical solutions and advantages of the present invention more clear, the embodiments of the present invention will be described in further detail below with reference to the accompanying drawings.

[0056] First embodiment

[0057] Based on the device fingerprint technology and the encryption requirements of the CNC system, this embodiment provides a CNC system encryption method based on the device's own characteristics (device fingerprint). The method can be implemented by an electronic device, which can be a terminal or a server. The execution process of the method is as follows: Figure 1 As shown, the following steps are included:

[0058] S1, collecting inherent characteristics of industrial Internet devices in the numerical control system, generating a device fingerprint of the corresponding industrial Internet device based on the inherent characteristics of the industrial Internet device, and saving the generated device fingerprint; wherein the inherent characteristics include: inherent hardware information of the device and response time of the device processing request;

[0059] It should be noted that this embodiment combines the networking characteristics of the CNC system and uses the inherent hardware information of the device and the response time of the device processing request as calculation parameters to form fingerprint information that can uniquely identify the identity of the device, thereby achieving the purpose of being able to identify a specific device individual. Specifically, the above S1 includes the following steps:

[0060] S11, collecting the inherent characteristics of the industrial Internet devices in the numerical control system, and generating the device fingerprint of the corresponding industrial Internet devices according to the inherent characteristics of the industrial Internet devices; Figure 2 As shown, it includes:

[0061] S111, extracting device hardware information.

[0062] The unique physical characteristics of hardware devices can be used to identify their fingerprints. The hardware information of a device usually includes the device serial number, mac, cpu, memory card, dynamic information, sensor, battery, etc. Under normal circumstances, it should be verified that the manufacturer complies with the construction rules before using the hardware information of these devices. However, in CNC systems, the hardware varieties are relatively simple, the manufacturing is relatively standardized, and the privacy data permissions open to customers are relatively unified. Therefore, the above hardware information can be used to measure and calculate the device fingerprint. Based on this, this embodiment measures the device hardware information according to the preset character length requirements to obtain the device hardware information vector: U = {u1, u2,......, u n}, where the hardware information includes multiple feature data, u i is the character string data collected from the i-th feature data corresponding to the corresponding device, i = 1, 2…n, and n is the number of feature data of the hardware information;

[0063] Among the feature data collected from the device, some feature data are highly unique, while some feature data are less unique. According to the principles of probability theory, by combining multiple feature data with low uniqueness, a highly unique combined feature data can be obtained. Based on the uniqueness of the feature data, a weight vector W = {w1, w2, ... w n}, where w i is the feature data u i The weight of iFeatures with higher uniqueness will receive larger weights, while features with lower uniqueness will be assigned lower weights to minimize the probability of collision between the combined features of the device hardware information fingerprint.

[0064] The collision probability p of the device hardware information fingerprint c It can be calculated by the following formula:

[0065]

[0066] in, is the collision probability of the i-th feature data, which can represent the uniqueness of the feature data.

[0067] Assign the weight vector to the hardware information to obtain the hardware information fingerprint vector:

[0068]

[0069] S112, extracting the cross-layer response time of the device.

[0070] The cross-layer response time of a device is primarily determined by its computing power and network layer characteristics. Compared to general-purpose computers, CNC system devices have simpler hardware and software architectures. They are designed to perform highly specialized, critical tasks and rarely generate other operations. Because device hardware specifications remain constant, the device's execution time for commands is relatively stable. Because devices in CNC system networks are specialized for specific tasks, they are typically fixed in a permanent location. Traffic generated by their regular polling intervals is transmitted over relatively short geographical distances and simple network architectures. In these network architectures, there is little opportunity for consecutive data packets to take different paths.

[0071] Therefore, the path time taken by a fixed device to respond to a command is also relatively fixed. By leveraging the interaction between periodic polling measurements at the application layer and TCP layer acknowledgments, we can estimate the time it takes a device to process a request. The distribution of these times can be used as an important parameter in developing a fingerprint for each device.

[0072] For a specific device, extract its response time for processing requests, let M = {m1,m2,......,m n} is a set of cross-layer response time measurement values of the device, m i The meaning is the i-th cross-layer response time measurement value; B is the number of features in the equivalent vector, and the estimate H of the global maximum value of this group of measurements is selected as the heuristic threshold, and the threshold T is defined as {t1, t2, ..., t n}, where t i is the i-th cross-layer response time measurement value m i Corresponding threshold, i=1,2…n,ti Calculated by the following formula:

[0073]

[0074] Divide each cross-layer response time measurement value by its corresponding threshold to obtain the cross-layer response time fingerprint vector: S = {s1, s2, ..., s n};

[0075] S113, constructing a device fingerprint.

[0076] The device fingerprint information is calculated from the vectors obtained by S111 and S112. Define the variable λ as the weight of the hardware information fingerprint vector V obtained by S111, then the weight of the cross-layer response time fingerprint vector S obtained by S112 is 1-λ, and the calculated device fingerprint vector F is:

[0077] F={λS,(1-λ)V} (4)

[0078] S12, encrypting the generated device fingerprint using a preset encryption algorithm;

[0079] This embodiment uses the national secret SM2 algorithm to encrypt and protect the device fingerprint information of the CNC system. The national secret SM2 algorithm provides key generation function, signature generation function and signature verification function to achieve encryption of device fingerprint information and device identity authentication. The process is as follows: Figure 3 As shown, the following steps are included:

[0080] S121, key generation.

[0081] First, the device fingerprint information F generated in S113 is converted into a bit string b, and then bit-padded is performed on b so that the padded information sequence b' satisfies the multiple of 512 in bit length.

[0082] Take the elliptic curve y 2 =x 3 +ax+b is the calculation equation. Take an n-order generator Q on the curve, where n is a large prime number. Select a random number d∈(1,n-1) and calculate the point:

[0083] P=(xp,yp)=dQ (5)

[0084] You can get the public key P and private key Q.

[0085] S122, ciphertext generation.

[0086] Select a random number k∈(1,n-1) and calculate the two components c1 and c2 of the ciphertext. The calculation formula is:

[0087] c1=kQ (6)

[0088]

[0089] Through calculation, the ciphertext C can be obtained by C=(c1,c2).

[0090] S123, signature generation.

[0091] Select a random number i∈(1,n-1) and calculate the two components r and s of the ciphertext. The calculation formula is:

[0092] r=xmodn (8)

[0093] s=(k -1 (Hash(M)+dr)modn (9)

[0094] Where Hash() is a hash function. Through calculation, the digital signature can be expressed as (r, s).

[0095] S124, signature verification.

[0096] First, convert the signature to be verified into two numbers r and s. If r and s do not meet the conditions:

[0097] r∈(1,n-1) (10)

[0098] r∈(1,n-1) (11)

[0099] If r and s meet the requirements of equations (10) and (11), the following equations are calculated in sequence:

[0100] c=(s -1 )modn (12)

[0101] u1=(Hash(M)·c)modn (13)

[0102] u2=(r·c)modn (14)

[0103] (x,y)=u1·G+u2·P (15)

[0104] If the formula is satisfied

[0105] r==xmodn (16)

[0106] If the signature verification is successful, then the signature verification fails.

[0107] S13, saving the encrypted device fingerprint into a database of a preset type.

[0108] In view of the large amount of data in network devices in numerical control systems, this embodiment uses a relational database for unified storage of encrypted device fingerprints. Create a relational database suitable for encrypted device fingerprints, and write a read and write interface for encrypted device fingerprint data for data entry. The process is as follows Figure 4 As shown, including:

[0109] S131, creating a relational database.

[0110] Due to the huge amount of data in CNC system equipment, a relational database is used to store encrypted device fingerprint information. A database is established to store the encrypted fingerprint information of each device as a corresponding data item to realize the entry of device fingerprints.

[0111] S132, compile the read and write interface of the associated database.

[0112] The data operation interface associated with the database is implemented through programming, including the entry, deletion, query and modification interfaces of encrypted device fingerprint information, to achieve convenient information management functions.

[0113] S133, encrypt the device fingerprint entry.

[0114] By calling the encrypted fingerprint information input interface implemented in S132, relational storage of device fingerprints is realized to form an encrypted device fingerprint database.

[0115] S2, when the device is communicating, identity authentication is achieved by verifying the device fingerprint of the communication device.

[0116] In summary, this embodiment addresses the problems of poor security of existing CNC systems and lack of security protection for storage and access of important data in CNC systems. The present invention provides a CNC system encryption method based on the device's own characteristics. This method can realize the extraction and entry of device fingerprints and device identification based on device fingerprints. The stable uniqueness of the device fingerprint ensures the security of the CNC system data, thereby effectively resisting malicious attacks and information leakage suffered by the CNC system, thereby improving the security protection level of the CNC system, making up for the lack of security performance in the data storage and access process of the CNC system, and ensuring the data security of the CNC system.

[0117] Second embodiment

[0118] This embodiment provides a numerical control system encryption device based on the device's own characteristics, including:

[0119] Device fingerprint registration module, used for:

[0120] Collecting inherent characteristics of industrial Internet devices in the numerical control system, generating a device fingerprint of the corresponding industrial Internet device based on the inherent characteristics of the industrial Internet device, and saving the generated device fingerprint; wherein the inherent characteristics include: inherent hardware information of the device and response time of the device processing request;

[0121] Device fingerprint recognition module, used for:

[0122] When the device is communicating, identity authentication is achieved by verifying the device fingerprint of the communication device.

[0123] Furthermore, the device fingerprint registration module is as follows Figure 5 As shown, including:

[0124] The device fingerprint extraction unit is used to collect the inherent characteristics of the industrial Internet devices in the numerical control system and generate the device fingerprint of the corresponding industrial Internet devices based on the inherent characteristics of the industrial Internet devices;

[0125] A data encryption unit, used to encrypt the generated device fingerprint using a preset encryption algorithm;

[0126] The device fingerprint database unit is used to save the encrypted device fingerprint into a database of a preset type.

[0127] The CNC system encryption device based on the device's own characteristics of this embodiment corresponds to the CNC system encryption method based on the device's own characteristics of the above-mentioned first embodiment; wherein, the functions implemented by each functional module in the CNC system encryption device based on the device's own characteristics of this embodiment correspond one-to-one to each process step in the CNC system encryption method based on the device's own characteristics of the first embodiment; therefore, they will not be repeated here.

[0128] Third embodiment

[0129] This embodiment provides an electronic device, which includes a processor and a memory; wherein the memory stores at least one instruction, and the instruction is loaded and executed by the processor to implement the method of the first embodiment.

[0130] The electronic device may have relatively large differences due to different configurations or performances, and may include one or more processors (central processing units, CPU) and one or more memories, wherein the memory stores at least one instruction, which is loaded by the processor to execute the above method.

[0131] Fourth embodiment

[0132] This embodiment provides a computer-readable storage medium storing at least one instruction, which is loaded and executed by a processor to implement the method of the first embodiment described above. The computer-readable storage medium may be a ROM, random access memory, CD-ROM, magnetic tape, floppy disk, or optical data storage device. The instructions stored therein can be loaded by a processor in a terminal to execute the method described above.

[0133] Furthermore, it should be noted that the present invention may be provided as a method, apparatus, or computer program product. Thus, embodiments of the present invention may take the form of entirely hardware embodiments, entirely software embodiments, or embodiments combining software and hardware aspects. Furthermore, embodiments of the present invention may take the form of a computer program product embodied on one or more computer-usable storage media containing computer-usable program code.

[0134] The embodiments of the present invention are described with reference to the flowcharts and / or block diagrams of the methods, terminal devices (systems), and computer program products according to the embodiments of the present invention. It should be understood that each process and / or block in the flowchart and / or block diagram, as well as the combination of the processes and / or blocks in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, an embedded processor, or other programmable data processing terminal device to generate a machine, so that the instructions executed by the processor of the computer or other programmable data processing terminal device generate instructions for implementing the process in the flowchart and / or block diagram. Figure 1 a process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0135] These computer program instructions may also be stored in a computer readable memory that can direct a computer or other programmable data processing terminal device to operate in a specific manner, so that the instructions stored in the computer readable memory produce a manufactured product including an instruction device, which implements the process Figure 1 a process or multiple processes and / or boxes Figure 1 These computer program instructions can also be loaded onto a computer or other programmable data processing terminal device, so that a series of operation steps are executed on the computer or other programmable terminal device to produce a computer-implemented process, thereby providing instructions for implementing the process in the process. Figure 1 a process or multiple processes and / or boxes Figure 1 A step that specifies a function in one or more boxes.

[0136] It should also be noted that, in this document, the terms "comprises," "includes," or any other variations thereof are intended to encompass non-exclusive inclusion, such that a process, method, article, or terminal device comprising a series of elements includes not only those elements but also other elements not explicitly listed, or elements inherent to such process, method, article, or terminal device. In the absence of further limitations, an element defined by the phrase "comprising a ..." does not exclude the presence of other identical elements in the process, method, article, or terminal device comprising the element.

[0137] Finally, it should be noted that the above is a preferred embodiment of the present invention. It should be noted that although the preferred embodiment of the present invention has been described, it is clear that those skilled in the art, once they understand the basic inventive concept of the present invention, can make various improvements and modifications without departing from the principles of the present invention. Such improvements and modifications should also be considered as within the scope of protection of the present invention. Therefore, the appended claims are intended to be interpreted as including the preferred embodiment and all changes and modifications that fall within the scope of the embodiments of the present invention.

Claims

1. A CNC system encryption method based on the device's own characteristics, characterized in that: include: Collecting inherent characteristics of industrial Internet devices in the numerical control system, generating a device fingerprint of the corresponding industrial Internet device based on the inherent characteristics of the industrial Internet device, and saving the generated device fingerprint; wherein the inherent characteristics include: inherent hardware information of the device and response time of the device processing request; When the device is communicating, identity authentication is achieved by verifying the device fingerprint of the communication device; The collecting of the inherent characteristics of the industrial Internet devices in the numerical control system and generating the device fingerprint of the corresponding industrial Internet devices according to the inherent characteristics of the industrial Internet devices include: The device hardware information is measured according to the preset character length requirement, and the device hardware information vector is obtained: U = {u1, u2, ..., u n }, wherein the hardware information includes multiple feature data, u i is the character string data collected from the i-th feature data corresponding to the corresponding device, i = 1, 2…n, and n is the number of feature data of the hardware information; Set a weight vector for the hardware information measurement value, assign the weight vector to the hardware information, and obtain the hardware information fingerprint vector: in, is the collision probability of the i-th feature data; Extract the response time of the device processing request, let M = {m1,m2,......,m n } is the cross-layer response time measurement value of a group of devices, B is the number of features in the equivalent vector, the estimate H of the global maximum value of the current group measurement value is selected as the heuristic threshold, and the threshold T is defined as {t1, t2, ..., t n }, where t i is the i-th cross-layer response time measurement value m i Corresponding threshold, i=1,2…n,t i Calculated by the following formula: Divide each cross-layer response time measurement value by its corresponding threshold to obtain the cross-layer response time fingerprint vector: S = {s1, s2, ..., s n }; Based on the hardware information fingerprint vector and the cross-layer response time fingerprint vector, the device fingerprint vector F is calculated: F={λS,(1-λ)V} Wherein, λ is the preset weight corresponding to the hardware information fingerprint vector.

2. The encryption method for a numerical control system based on the device's own characteristics according to claim 1, characterized in that: The collecting of the inherent characteristics of the industrial Internet devices in the numerical control system, generating a device fingerprint of the corresponding industrial Internet device based on the inherent characteristics of the industrial Internet device, and saving the generated device fingerprint includes: Collect the inherent characteristics of industrial Internet devices in the CNC system and generate device fingerprints of corresponding industrial Internet devices based on the inherent characteristics of the industrial Internet devices; The generated device fingerprint is encrypted using a preset encryption algorithm; Save the encrypted device fingerprint to a database of the preset type.

3. The encryption method for a numerical control system based on the device's own characteristics as claimed in claim 2, characterized in that: The preset encryption algorithm is the SM2 algorithm.

4. The encryption method for a numerical control system based on the device's own characteristics as claimed in claim 2, characterized in that: The preset type of database is a relational database.

5. A CNC system encryption device based on the device's own characteristics, characterized in that: include: Device fingerprint registration module, used for: Collecting inherent characteristics of industrial Internet devices in the numerical control system, generating a device fingerprint of the corresponding industrial Internet device based on the inherent characteristics of the industrial Internet device, and saving the generated device fingerprint; wherein the inherent characteristics include: inherent hardware information of the device and response time of the device processing request; Device fingerprint recognition module, used for: When the device is communicating, identity authentication is achieved by verifying the device fingerprint of the communication device; The device fingerprint extraction unit is specifically used to: The device hardware information is measured according to the preset character length requirement, and the device hardware information vector is obtained: U = {u1, u2, ..., u n }, wherein the hardware information includes multiple feature data, u i is the character string data collected from the i-th feature data corresponding to the corresponding device, i = 1, 2…n, and n is the number of feature data of the hardware information; Set a weight vector for the hardware information measurement value, assign the weight vector to the hardware information, and obtain the hardware information fingerprint vector: Among them, p ci is the collision probability of the i-th feature data; Extract the response time of the device processing request, let M = {m1,m2,......,m n } is the cross-layer response time measurement value of a group of devices, B is the number of features in the equivalent vector, the estimate H of the global maximum value of the current group measurement value is selected as the heuristic threshold, and the threshold T is defined as {t1, t2, ..., t n }, where t i is the i-th cross-layer response time measurement value m i Corresponding threshold, i=1,2…n,t i Calculated by the following formula: Divide each cross-layer response time measurement value by its corresponding threshold to obtain the cross-layer response time fingerprint vector: S = {s1, s2, ..., s n }; Based on the hardware information fingerprint vector and the cross-layer response time fingerprint vector, the device fingerprint vector F is calculated: F={λS,(1-λ)V} Wherein, λ is the preset weight corresponding to the hardware information fingerprint vector.

6. The CNC system encryption device based on the device's own characteristics as claimed in claim 5, characterized in that: The device fingerprint registration module includes: The device fingerprint extraction unit is used to collect the inherent characteristics of the industrial Internet devices in the numerical control system and generate the device fingerprint of the corresponding industrial Internet devices based on the inherent characteristics of the industrial Internet devices; A data encryption unit, used to encrypt the generated device fingerprint using a preset encryption algorithm; The device fingerprint database unit is used to save the encrypted device fingerprint into a database of a preset type.

7. The CNC system encryption device based on the device's own characteristics as claimed in claim 6, characterized in that: The default encryption algorithm used by the data encryption unit is the SM2 algorithm.

8. The CNC system encryption device based on the device's own characteristics as claimed in claim 6, characterized in that: The preset type of database used by the device fingerprint database unit is a relational database.

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