Welding data transmission method and system based on quantum encryption technology

Abstract

The invention provides a welding data transmission method and system based on a quantum encryption technology. The welding data transmission method comprises the steps that welding matrix data is obtained, subjected to feature extraction and uploaded and stored to an interstellar file system; welding encrypted data corresponding to the welding matrix data are generated in the interstellar file system based on a quantum chaotic data encryption technology; extracting a region of interest of the welding matrix data, and generating encrypted data of each region based on a quantum one-time encryption technology; performing feature extraction on to-be-queried data, and then calling an interstellar file system to retrieve to obtain welding encrypted data similar to the queried data; and executing an encryption inverse process on the similar welding encrypted data for decryption.

Description

Technical Field

[0001] This invention belongs to the technical field of welding data transmission, and particularly relates to a welding data transmission method and system based on quantum encryption technology. Background Technology

[0002] The statements in this section are merely background information related to the present invention and do not necessarily constitute prior art.

[0003] The Nord Stream gas pipeline leak underscores the extreme importance of the safety of energy transportation infrastructure. Welding, as a primary means of repairing pipelines and other infrastructure, faces the urgent need to achieve high-quality operations at the fastest speed. In the context of conflict, damage to energy infrastructure such as pipelines, as well as weapons like ships, aircraft, and tanks, is inherently adversarial, and the consequences are often complex and challenging. Existing welding processes may be insufficient for rapid and accurate reconstruction, necessitating the support of superior welding techniques. Furthermore, in real-world conflict scenarios, most welding computing devices lack the modeling capabilities and computational power required for rapid process optimization. This necessitates first transmitting sensor data (images and point clouds, etc.) of the object to be welded to a remote experimental base, then relying on the powerful computing capabilities of the remote base for process optimization experiments, and finally accurately transmitting the relevant processes and programs to the welding equipment in the conflict scenario for welding.

[0004] In conflict scenarios, the confidentiality of welding data transmission must be considered: ① Some parts of the welding sensor data have confidentiality requirements, and even welding experts are not authorized to access them. Such data must be encrypted; ② During transmission, the data may be subject to adversarial eavesdropping and tampering, so its transmission security must be ensured. Summary of the Invention

[0005] To overcome the shortcomings of the prior art, the present invention provides a welding data transmission method and system based on quantum encryption technology, which ensures the confidentiality and efficient retrieval of welding data by introducing quantum block-based data encryption and a distributed interplanetary data feature file system.

[0006] To achieve the above objectives, one or more embodiments of the present invention provide the following technical solutions: A welding data transmission method based on quantum encryption technology, comprising: S1: Obtain welding matrix data, extract features, and upload and store it to the Interplanetary File System; S2: Generate welding encryption data corresponding to the welding matrix data in the interplanetary file system based on quantum chaotic data encryption technology; S3: Extracting the region of interest from the welding matrix data generates encrypted data for each region based on quantum one-time encryption technology; S4: After extracting features from the data to be queried, call the InterPlanetary File System to retrieve welding encrypted data similar to the data to be queried; perform the reverse encryption process on the similar welding encrypted data to decrypt it.

[0007] A second aspect of the present invention provides a welding data transmission system based on quantum encryption technology, comprising: Data acquisition module: Acquires welding data, extracts features, and uploads them to the Interplanetary File System; Overall data encryption module: Generates encrypted welding data corresponding to the welding matrix data based on quantum chaotic data encryption technology in the interplanetary file system; Confidential Area Encryption Module: Extracts regions of interest from the welding matrix data and generates encrypted data for each region based on quantum one-time encryption technology; Data retrieval module: After extracting features from the data to be queried, it calls the InterPlanetary File System to retrieve welding encrypted data similar to the query data; it then performs the reverse encryption process to decrypt the similar welding encrypted data.

[0008] A third aspect of the present invention provides a computer-readable storage medium for storing computer instructions, which, when executed by a processor, perform the steps described in the above method.

[0009] A fourth aspect of the present invention provides an electronic device including a memory and a processor, and computer instructions stored in the memory and running on the processor, wherein the computer instructions, when executed by the processor, perform the steps described in the above method.

[0010] The above one or more technical solutions have the following beneficial effects: In this invention, the confidentiality and efficient retrieval of welding data are ensured by introducing quantum block-based data encryption and a distributed interplanetary data feature file system.

[0011] In this invention, the uncertainty principle of quantum mechanics is used to design the basic gates for quantum control. These controlled gates are used to generate quantum key matrices, key images, and quantum keys associated with ordinary images to perform adaptive disordering and diffusion processes. In principle, it is difficult for intruders to obtain the shuffling pattern from the retrieved general data, effectively preventing intruders from obtaining data.

[0012] Advantages of additional aspects of the invention will be set forth in part in the description which follows, and in part will be obvious from the description, or may be learned by practice of the invention. Attached Figure Description

[0013] The accompanying drawings, which form part of this invention, are used to provide a further understanding of the invention. The illustrative embodiments of the invention and their descriptions are used to explain the invention and do not constitute an improper limitation of the invention.

[0014] Figure 1 This is a schematic diagram of the storage of welding sensor data in Embodiment 1 of the present invention; Figure 2 This is a schematic diagram of the distributed storage process of welding sensor data in Embodiment 1 of the present invention; Figure 3 This is a schematic diagram of the quantum welding sensor data encryption process based on data segmentation in Embodiment 1 of the present invention; Figure 4 This is a schematic diagram of the NEDR representation of a data block and its quantum circuit in Embodiment 1 of the present invention; Figure 5 This is the encryption and embedding process for confidential block data in Embodiment 1 of the present invention; Figure 6 This is a schematic diagram of the welding data retrieval process in Embodiment 1 of the present invention. Detailed Implementation

[0015] It should be noted that the following detailed descriptions are exemplary and intended to provide further illustration of the invention. Unless otherwise specified, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention pertains.

[0016] It should be noted that the terminology used herein is for the purpose of describing particular implementations only and is not intended to limit the exemplary implementations of the present invention.

[0017] Where there is no conflict, the embodiments and features in the embodiments of the present invention can be combined with each other.

[0018] Example 1 like Figure 1 As shown, this embodiment provides a welding data transmission method based on quantum encryption technology, including: S1: Obtain welding matrix data, extract features, and upload and store it to the Interplanetary File System; S2: Generate welding encryption data corresponding to the welding matrix data based on quantum chaotic data encryption technology in the InterPlanetary File System; S3: Extracting the region of interest from the welding matrix data generates encrypted data for each region based on quantum one-time encryption technology; S4: After extracting features from the query data, call the InterPlanetary File System to retrieve similar encrypted welding data; perform the reverse encryption process to decrypt the similar encrypted welding data.

[0019] In this embodiment, the physical quantum computer needs to have the number of qubits required to support NEQR quantum image representation, be able to execute basic quantum logic operations such as Hadamard gates, CNOT gates, and Swap gates, and have the ability to load image-related initial seeds, control chaotic mapping parameters, and construct quantum key stream matrices. Simultaneously, the computer also needs to support encrypted shuffling between and within quantum blocks, observation and entanglement measurement of quantum states, and CNOT diffusion and its inverse operation to complete the encryption, storage, retrieval, and decryption process of welding data proposed in this invention. Due to the current limitations of physical quantum computing capabilities, each module of this invention needs to be prototyped and simulated on a classical computing platform using quantum simulators (such as Qiskit, Origin Quantum Platform, etc.) to support algorithm testing, encryption process design, and system-level deployment.

[0020] The technical solution of this embodiment is divided into four stages: distributed welding feature data storage, quantum welding data encryption, confidential area data generation and encryption, and welding data retrieval. First, confidential areas are extracted from the welding data, and each area's data is generated and encrypted using quantum one-time encryption technology. Then, quantum block-based cryptography is used to encrypt the entire data. During retrieval, the query features are compared with the stored data features, and the matching degree of the overall data is checked by verifying the regional data.

[0021] Since intelligent welding planning requires a large amount of welding sensor data (such as weld seam images and point clouds), the first step is to construct a cloud-based sensor database of the object to be welded. For simplicity, in this embodiment, the point cloud data is limited to point clouds with a matrix storage format (such as depth images), and its element values ​​are normalized to integers between [0, 255]. At this time, both the image and point cloud data of the object to be welded can be represented using a matrix method, which is referred to as matrix data in this embodiment.

[0022] In this example, for the choice of quantum computing platform, one alternative is to perform prototype verification on a quantum computing cloud platform (such as the Origin Quantum platform), and another option is to perform prototype verification using quantum computing simulation software on a classical computer.

[0023] In this embodiment S1, the welding client uploads sensor data such as images and point clouds of the object to be welded to a remote storage platform and extracts features. This embodiment uses a gradient histogram as the feature extractor and stores the extracted features in a feature table. An intermediate server calculates similar data features and stores them in the corresponding cluster. During retrieval, the query results depend on feature comparison, so data features also need to be retained. These features are key entries for similar data identification and are stored in plaintext on the cloud server, making them accessible to intruders. To overcome this problem, this embodiment uses an interplanetary data feature file system to store welding data features, such as... Figure 2 As shown. The InterPlanetary File System (IPS) is a distributed storage method where data is distributed in a "striped" manner. Each node or disk stores only a fragment of data, which cannot be viewed individually and appears as a "damaged" file from the file system's perspective. Therefore, it is physically more secure than centralized storage.

[0024] In this embodiment, the feature information of the welding data is extracted through gradient histograms, formatted into structured feature vectors, hashed, and then uploaded to the InterPlanetary File System (IPFS) using the hash value as the index key. The system employs a content addressing mechanism and a Merkle DAG structure to divide the feature vectors into multiple data blocks, each assigned a unique Content Identifier (CID) and stored in distributed nodes. Because IPFS inherently possesses decentralization, redundancy, fault tolerance, and immutability, fragmented feature data held by a single node cannot reconstruct complete information, significantly improving the physical security and anti-intrusion capabilities of the data. Simultaneously, the system associates the feature index mapping relationship with the corresponding encrypted welding data, forming a secure index structure for querying the data, ensuring the integrity and tamper-proof nature of subsequent feature comparison and data retrieval processes.

[0025] In this embodiment S2, to ensure data confidentiality, the following is used: Figure 3 The data encryption method based on quantum chaos is shown. First, an initial seed is generated based on ordinary welding data and used in the random key sequence generation process of the hyperchaotic Lorentz system. Second, pixel positions are shuffled using inter-block and intra-block permutations to obtain disordered image data. Then, a quantum key image is generated by iterative Arnold chaotic mapping on the original data. Finally, a diffusion process is performed by applying CNOT operations to the disordered image data and the quantum key image. A general description of the block-based quantum welding data encryption process is given in Algorithm 1.

[0026]

[0027] Specifically, it includes: S21: Generate the initial seed based on the original welding matrix data; S22: Use the chaotic Lorentz mapping to generate a qubit keystream matrix from the initial seed; S23: Quantum block data representation of raw welding matrix data based on NEQR; S24: Shuffle the quantum block representation according to the generated quantum bit key stream matrix.

[0028] In S21, a dynamic seed (i.e., initial condition) generation mechanism related to ordinary data is introduced to ensure the randomness and sensitivity of the quantum cryptosystem. Let the original welding data be... Stored in In the matrix, then in Randomly select 4 overlapping ones For each data block, calculate the mean of its elements. And it is used as the initial point for the high-dimensional hyperchaotic Lorentz mapping in the generation of random key streams.

[0029] In S22, the chaotic Lorentz map is initialized with an initial seed value. For input, iterate Each iteration generates 4 chaotic sequences. Then convert it to The integer sequence, while the quantum key stream matrix is ​​composed of pairs of... Tensor product of binary number sequences The specific steps for generating the quantum key stream matrix are as follows: S221: Given an initial... Select control parameters .

[0030] S222: Yes Perform the following iterative calculations:

[0031] S223: Yes Perform the following operations:

[0032]

[0033] in, This is the floor function.

[0034] S224: The two chaotic sequences obtained from step 3 and Converted into an 8-bit binary qubit sequence, these are called qubit key sequences. and Two chaotic sequences and The conversion to an 8-bit binary qubit sequence is achieved using a conventional decimal-to-binary method: first, ... and The values ​​are normalized to integer values ​​in the range [0, 255], and then converted into 8-bit binary bit strings according to standard rules, which constitute the quantum bit key sequences. and As for and In this step, it is not used for key sequence construction, but rather participates as an internal coupling variable in the chaotic system. and The generation process ensures its chaotic nature and the unpredictability of the key.

[0035] S225: Calculate the qubit keystream matrix: (7) in, .

[0036] In S23, the original welding matrix data is converted into a quantum data representation format using a novel enhanced quantum representation (NEQR).

[0037] NEQR is a quantum grayscale representation method in which the original matrix element values ​​are converted into corresponding binary numbers and undergo a series of quantum operations.

[0038] If the data matrix dimension is ,use Each qubit represents its pixel value in the range [0, 255]. Each qubit represents the coordinate of a pixel (front). Each qubit represents a column, after which... (each qubit represents a row), therefore a total of 100 qubits are needed. q+2n qubits. First, initialize the q+2n qubits as follows: The qubits are q bits used to represent the pixel grayscale value and 2n bits used to represent the pixel coordinates. An identity gate I is applied to the q bits to maintain the current state, and a Hadamard gate H is applied to the 2n coordinate bits to construct a superposition state, thereby enabling the pixel position to be accessed in quantum parallel mode, providing a basis for subsequent quantum image loading and manipulation.

[0039] Specifically, the original welding image (matrix) data NEQR means It has the following form: (8) in Pixel value of Entanglement of qubits It represents the pixel position. Entangled representation of qubits.

[0040] In this embodiment, as Figure 4 As shown, assuming the welding sensor data matrix The element values ​​(e.g., in a weld depth image) are... For integers above a certain value, a binary sequence can be used. coding The element values : (9) in .

[0041] one The quantum image representation of the weld depth image can be written as: (10) Formula (10) injects the binary code of each bit into the quantum state through tensor product, thus forming an executable pixel grayscale encoding process.

[0042] Specifically, consider for The simplest case is the matrix. Specifically, consider... (11) This represents the number of qubits of the pixel value. The number of qubits representing the pixel position is That is, a total of One quantum bit to realize the image NEQR quantum representation: (12) Therefore, NEQR representations can be designed and fabricated in a targeted manner. The quantum circuit requires four 2-controlled NOT gates (CNOT) in its specific circuit.

[0043] Figure 3 The text provides a reference to... Data matrix block A schematic diagram of the quantum welding sensor data encryption process.

[0044] In S24, the input quantum block data is shuffled according to the quantum bit key stream matrix, including two steps: inter-block shuffling and intra-block shuffling, which are used to perturb the values ​​of the original matrix elements between and within NEQR blocks.

[0045] In S23, the original welding data is converted into a quantum image in NEQR format and further divided into several quantum block data according to a preset block size. Each quantum block consists of multiple qubits, containing entangled states corresponding to pixel values ​​and pixel positions, serving as the basic unit for shuffling and diffusion operations in subsequent encryption steps.

[0046] The input for stage S24 is the qubit keystream matrix. NEQR quantum representation of data The output is an image. The specific steps include: S241: Yes Each position in the middle is All elements use By changing its position, the final quantum representation is: ; S242: For | Each For each sub-block, first apply a swapgate to it, then perform a swap gate on each line. Rotate, and repeat for each column. Rotation yields two-dimensional matrix data with an image structure, which can be viewed as an image. ,image The key image, perturbed by the Arnold chaotic map, is used to drive the diffusion operation. This indicates the hierarchical number into which the current quantum image is divided, used to control the size of sub-blocks in the image at multiple scales (such as a pyramid structure). Indicates the first The size of each sub-block in the layer.

[0047] To further obfuscate the element values, the Arnold chaotic mapping is used on the original data matrix to generate the quantum key matrix data. The generalized two-dimensional Arnold mapping is as follows: (13) Where N is the size of the image, and p and q are control parameters. Arnold chaotic graphs are used to create quantum key maps for diffusion processes by converting them into novel enhanced quantum representations. The steps for generating quantum key matrix data using Arnold chaotic maps on the original data matrix are as follows: S241': For each original data matrix The Middle Elements, iterated over The Arnold chaotic mapping is used to obtain And represent it using NEQR to obtain the key matrix. ; S242': Yes and Perform a CNOT operation on each pixel to obtain ; S243': Will Obtain by deformation Transformation refers to rearranging the CNOT-encrypted quantum image blocks according to their original positions to restore the complete quantum image structure.

[0048] Key space is a crucial criterion for the effectiveness of encryption algorithms against brute-force attacks. Brute-force attacks are directly related to key space; therefore, an ideal encryption scheme should have a large key space. Four initial seeds are used in the data encryption process based on a hyperchaotic Lorentz system. and 4 control parameters The data is modified, and parameters a and b are used to initialize control parameters p and q during the diffusion process based on the Arnold chaotic map. The access to each parameter uses 64-bit double-precision computation precision as per the IEEE standard, ensuring that the number of elements in the key space designed in this invention is no less than 10 to the power of 180. This key space is large enough to make brute-force attacks infeasible.

[0049] A perturbation matrix is ​​obtained by performing multiple rounds of Arnold chaotic mapping on the original welding data matrix. This perturbation matrix is ​​then transformed using the NEQR quantum image encoding method to form a quantum key image, which is used as the control terminal in quantum logic operations such as CNOT gates for encryption. Figure 3 The quantum key data shown is the implementation form of this quantum controllable data.

[0050] When intruders encounter cryptographic data in cyberspace, their primary objective is often to obtain intermediate parameters rather than key parameters. To address the most common known plaintext attacks (where the intruder maintains information about the plaintext and its corresponding cryptographic data and attempts to propagate the key) and chosen-plaintext attacks (where the intruder can temporarily access the cryptographic system and randomly select a set of plaintext to generate corresponding ciphertext, aiming to leak the key or the original plaintext), this embodiment proposes the following specific countermeasures: Intruders can choose random ordinary data with different data value distribution patterns to obtain intermediate parameters. For Weld depth image First, we perform a disordered quantum representation on it. ,in The qubit key transformation matrix is ​​generated by a chaotic system, and then the disordered image is... With key image XOR operations are performed using controlled NOT gates (CNOT). Once this process is understood, an intruder can learn the shuffling pattern from retrieved images of ordinary weld depths. To overcome this and achieve high resistance to cryptanalysis attacks, this embodiment uses the uncertainty principle of quantum mechanics to design quantum-controlled basic gates. These controlled gates are used to generate a quantum key matrix, key image, and quantum key associated with the ordinary image to perform an adaptive disordering and diffusion process. Dynamic qubit key matrix. It is obtained by designing a high-dimensional hyperchaotic Lorentz diagram (in this embodiment, the control parameter is...). ), its initial point The value is calculated from the average pixel value of a depth image block, and the random sequence is converted into a quantum vector using controlled basic gates. Then, the tensor product is applied to any two integers of size 1. and The sequence is used to obtain the key matrix. Furthermore, the adaptive quantum key matrix generates different disorder matrices at each stage of the pixel disordering process and dynamically controls the image. Used for the diffusion process. Therefore, different input images will have different key images and password images, making it theoretically difficult for intruders to obtain the shuffling pattern from the retrieved general data.

[0051] In this embodiment, the generation of the key image and quantum key not only relies on the perturbation operation of the Arnold chaotic map on the original image, but also further introduces quantum controlled gates (such as the controlled NOT gate CNOT) to enhance the correlation and controllability between images. Specifically, the original welding image matrix is ​​first transformed into a chaotic perturbation image through multiple rounds of Arnold mapping, and then converted into a quantum image state as the quantum key base map using the NEQR model. Next, using quantum controlled gates such as the CNOT gate as the control terminal, the key base map is coupled with the image block data to generate the final key image and quantum key sequence, thereby achieving adaptive perturbation and encryption at the image level during the diffusion stage.

[0052] like Figure 5 As shown, in this embodiment S3, to ensure the confidentiality of certain parts of the welding sensing data, data encryption based on the region of interest (ROI) is used (the ROI contains confidential data). First, using specified data boundaries, the ROI is extracted and a pixel difference stream called the region data is generated. If the element value at the ROI boundary is... Then, the differences in element values ​​are calculated to generate regional data. This is then converted into qubits. These qubits are entangled together, their angle is measured and used as an encryption key, and after obtaining the key, it is used to generate encrypted region data.

[0053] In this embodiment, after generating encrypted region data, the region of interest should be extracted first and encrypted region data should be generated. Then, block processing and subsequent encryption operations should be performed. That is, generating encrypted region data comes first, followed by block processing.

[0054] The region of interest (ROI) is subdivided into four sub-blocks—left, right, top, and bottom—using a standard integer wavelet transform (IWT) method. For each sub-block, lower and higher frequency sub-bands are calculated using IWT. After obtaining the frequency bands, the region data is embedded as a reversible watermark. Specifically, given the ROI data... Convert it into binary qubits And measure the quantum entanglement between qubits. Then Assign to and run Finally use The low-frequency subband is used as an embedding.

[0055] Figure 5 In this process, inverse integer wavelet transform and data stitching are used to merge the encrypted data in the encrypted region with the encrypted result of the entire image, restoring a complete encrypted image and ensuring that the encrypted region remains consistent with the overall image. Figure 1 To achieve integration. Figure 5 The left side generates encrypted data for the confidential area, while the right side processes the diffuse encrypted data for the entire image. Finally, the two are fused together through inverse integer wavelet transform and data stitching to obtain a complete encrypted image.

[0056] Before data is stored in the database, the system performs feature extraction and hash calculation on the original welding data, and stores the resulting hash value along with the corresponding welding data identifier (such as ID) in the server database as the basis for comparison in subsequent similarity queries. Figure 6 As shown, in embodiment S4, the welding expert or robot inputs data into the system and hopes to retrieve similar welding data from the system. The system first extracts features from the query data and sends the query features to the interstellar feature data server. The server converts the query features into hash values ​​and compares them with stored hash values. After a match, the server returns the IDs of similar welding data to the system, thus obtaining a set of similar encrypted data. After verifying the welding expert, the system executes quantum data decryption in algorithm 2.

[0057] Once the data is decrypted, the region data is extracted from the data using its boundary values. The same process is performed to generate new region data of interest in encrypted form. To decrypt the region data, the server measures the entanglement of the qubits and obtains the key for decryption. The same process is continued for each qubit, i.e., 8 rotations. After 8 rotations, the decryption process is performed; the querying user measures the encrypted value of all qubits and records it to obtain the final value. Therefore, to verify whether the data of interest has been tampered with, the authenticated querying user records the measurement value of each qubit in the region data of interest and verifies it against the original data.

[0058] A general description of the welding database retrieval process is shown in Algorithm 2.

[0059]

[0060] The purpose of normalizing the quantum data in step 4 is to serve as reference data for subsequent steps such as step 5 and step 7, to determine whether the query data has been tampered with or forged. Step 6 performs the inverse operation of encrypting the overall welding data to obtain normalized quantum data. This normalized data is used to extract the region of interest and compare it with the query region data to determine if the data has been tampered with. The decryption operation of the confidential region begins in step 6 when quantum measurement and decoding of the region of interest data are performed.

[0061] Example 2 The purpose of this embodiment is to provide a welding data transmission system based on quantum encryption technology, including: Data acquisition module: Acquires welding data, extracts features, and uploads them to the Interplanetary File System; Overall data encryption module: Generates encrypted welding data corresponding to the welding matrix data based on quantum chaotic data encryption technology in the interplanetary file system; Confidential Area Encryption Module: Extracts regions of interest from the welding matrix data and generates encrypted data for each region based on quantum one-time encryption technology; Data retrieval module: After extracting features from the data to be queried, it calls the InterPlanetary File System to retrieve welding encrypted data similar to the query data; it then performs the reverse encryption process to decrypt the similar welding encrypted data.

[0062] Example 3 The purpose of this embodiment is to provide a computing device, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the program to implement the steps of the above-described method.

[0063] Example 4 The purpose of this embodiment is to provide a computer-readable storage medium.

[0064] A computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, performs the steps of the above method.

[0065] The steps and methods involved in the apparatuses of Embodiments 2, 3, and 4 above correspond to those in Embodiment 1. For specific implementation details, please refer to the relevant description section of Embodiment 1. The term "computer-readable storage medium" should be understood as a single medium or multiple media including one or more instruction sets; it should also be understood as including any medium capable of storing, encoding, or carrying an instruction set for execution by a processor and enabling the processor to perform any of the methods in this invention.

[0066] Those skilled in the art will understand that the modules or steps of the present invention described above can be implemented using general-purpose computer devices. Optionally, they can be implemented using computer-executable program code, thereby allowing them to be stored in a storage device for execution by a computer device, or they can be fabricated as separate integrated circuit modules, or multiple modules or steps can be fabricated as a single integrated circuit module. The present invention is not limited to any particular combination of hardware and software.

[0067] While the specific embodiments of the present invention have been described above in conjunction with the accompanying drawings, this is not intended to limit the scope of protection of the present invention. Those skilled in the art should understand that various modifications or variations that can be made by those skilled in the art without creative effort based on the technical solutions of the present invention are still within the scope of protection of the present invention.

Claims

1. A welding data transmission method based on quantum encryption technology, characterized by, Comprise: S1: Obtain welding matrix data for feature extraction and upload storage to interstellar file system; S2: In the interstellar file system, welding encryption data corresponding to the welding matrix data is generated based on quantum chaos data encryption technology; S3: Extract the region of interest of welding matrix data, and generate each region encryption data based on quantum one-time encryption technology; S4: After feature extraction of the query data, the interstellar file system is called to retrieve the welding encryption data similar to the query data; The similar welding encryption data is decrypted by executing the inverse process of encryption.

2. The welding data transmission method based on quantum encryption technology according to claim 1, characterized in that, In the S1, the gradient histogram is used as the feature extractor to extract the welding data features, and the interstellar file system is used to store the extracted welding data features.

3. The welding data transmission method based on quantum encryption technology according to claim 1, characterized in that, In the S2, the welding encryption data corresponding to the welding data is generated based on quantum chaos data encryption technology in the interstellar file system, specifically including: Based on the original welding matrix data, an initial seed is generated; The initial seed is generated into a quantum bit key stream matrix by using chaotic Lorenz mapping; The original welding data is represented by quantum block data based on NEQR; The quantum block representation is shuffled according to the generated quantum bit key stream matrix.

4. The welding data transmission method based on quantum encryption technology according to claim 3, characterized in that, The initial seed is obtained from the average of the block pixel of the depth image of the original welding data.

5. The welding data transmission method based on quantum encryption technology as claimed in claim 3, wherein, The quantum block representation is shuffled according to the generated quantum bit key stream matrix, including inter-block shuffling and intra-block shuffling, wherein the intra-block shuffling specifically includes: For each position in the quantum block data The element changes the position using a quantum bit key stream matrix to obtain a quantum representation; After applying the exchange gate to the data sub-block in the quantum representation, the row rotation and column rotation are performed, and the image matrix is output; The inter-block shuffling specifically includes: In each original welding matrix data, the first element is iterated using Arnold chaos mapping and then represented by NEQR to obtain the key matrix; After performing CNOT operation on each pixel in the obtained key matrix and the image matrix obtained by intra-block shuffling, the welding encryption data is obtained by deformation.

6. The welding data transmission method based on quantum encryption technology as claimed in claim 1, wherein, In the step 3, the region of interest of the welding data is encrypted based on quantum one-time encryption technology to generate each region data, specifically including: The region of interest of the welding data is divided into sub-blocks by using the standard integer wavelet transform method; For each word block, the pixel difference stream of the region data is generated by using the specified data boundary to extract the welding data word block; The generated pixel difference stream is converted into quantum bits; The angle of the quantum bit is measured as an encryption key, and the welding data word block is encrypted to generate encrypted region data using the encryption key.

7. The welding data transmission method based on quantum encryption technology as claimed in claim 1, wherein, In the step 4, specifically: The features of the query data are sent to the interstellar file system to convert the features of the query data into hash values; The hash values of the query data are compared with the hash values stored in the interstellar file system. If matched, the welding encryption data similar to the query data is returned; The returned welding encryption data is subjected to the inverse operation of quantum chaos data encryption technology to obtain normalized quantum data; The region of interest data is extracted from the data obtained from the normalized quantum data using the boundary value; The new region of interest data is generated based on the inverse operation of quantum one-time encryption technology on the region data.

8. A welding data transmission system based on quantum encryption technology, characterized by, Comprise: Data acquisition module: obtain welding data for feature extraction and upload to interstellar file system; Data overall encryption module: generating welding encryption data corresponding to the welding matrix data based on quantum chaotic data encryption technology in the interstellar file system; Secret area encryption module: extracting the region of interest of the welding matrix data and generating each region encryption data based on quantum one-time encryption technology; Data retrieval module: after feature extraction of the data to be queried, calling the interstellar file system to retrieve welding encryption data similar to the query data; and performing the inverse process of encryption on the similar welding encryption data to perform decryption.

9. A computer-readable storage medium having stored thereon a computer program, characterized in that, The program is executed by the processor to implement the steps in the welding data transmission method based on quantum encryption technology in any one of claims 1-7.

10. A processing device comprising a memory, a processor, and a computer program stored on the memory and executable on the processor, characterized in that, The processor executes the program to implement the steps in the welding data transmission method based on quantum encryption technology in any one of claims 1-7.

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