High-load data steganography method, system, equipment and medium

Abstract

The invention discloses a high-load data steganography method, system and device and a medium, and the method comprises the steps: obtaining secret data of a power system, and converting the secret data into a novenary sequence; a quantum key distribution system is utilized to generate a shared key, the novenary sequence is encrypted through an encryption key, encrypted information is obtained, and the shared key comprises the encryption key and a mapping key; determining a corresponding first unit matrix from a preset mapping library based on the mapping key, and performing non-overlapping tiling on the first unit matrix in a two-dimensional plane to obtain a second-order reference matrix; and scanning a preset carrier image into a non-overlapping first pixel pair sequence according to a Hilbert curve, and embedding the encrypted information into the first pixel pair sequence by using the second-order reference matrix to obtain a steganographic image, so that the data transmission security can be improved.

Description

Technical Field

[0001] The present invention relates to the field of data steganography, and in particular to a high-load data steganography method, system, device and medium. Background Art

[0002] In modern information systems like smart grids, the secure transmission and storage of images, videos, and sensitive data face numerous challenges. With the continuous advancement of quantum computing technology, quantum computers can efficiently solve large number factorization and discrete logarithm problems, making it difficult for traditional encryption algorithms (such as AES and RSA) to maintain their security, thus exposing sensitive data to the risk of leakage. Therefore, to ensure efficient communication while also ensuring data security, image steganography has become a key research area. It can hide sensitive information within image data, making information transmission more discreet and secure.

[0003] In the existing art, information hiding algorithms based on reference matrices are a common image steganography method. These algorithms improve information embedding capacity through strategies such as optimizing pixel value adjustment. However, this method has some significant drawbacks. On the one hand, under high embedding loads, the visual quality of the image is significantly affected, resulting in noticeable distortion, which makes the steganographic data more detectable and reduces its concealment. On the other hand, the security of traditional image steganography technology is difficult to guarantee in the face of new security attacks such as quantum computing, as quantum computing can easily crack encryption algorithms based on traditional mathematical problems, thereby threatening the security of the steganographic data. In addition, existing technologies often sacrifice embedding rate when improving attack resistance, making it difficult to achieve a good balance between hiding capacity, visual quality, and attack resistance. This makes it unable to meet the dual requirements of high security and high concealment in scenarios such as smart grids. Summary of the Invention

[0004] The present invention provides a high-load data steganography method, system, device and medium, which can improve the security of data transmission.

[0005] An embodiment of the present invention provides a high-load data steganography method, comprising:

[0006] Obtaining secret data of the power system and converting the secret data into a 9-ary sequence;

[0007] Generate a shared key using a quantum key distribution system, and encrypt the nonadic sequence using an encryption key to obtain encrypted information, wherein the shared key includes the encryption key and a mapping key;

[0008] Determine a corresponding first unit matrix from a preset mapping library based on the mapping key, and tile the first unit matrix in a two-dimensional plane without overlap to obtain a second-order reference matrix;

[0009] The preset carrier image is scanned into a non-overlapping first pixel pair sequence according to the Hilbert curve, and the encryption information is embedded into the first pixel pair sequence using the second-order reference matrix to obtain a stego image.

[0010] The embodiment of the present invention can increase the complexity of data through base conversion, so that the original data undergoes preliminary conversion and disguise before transmission, thereby improving the confidentiality of the data; using a quantum key distribution system to generate a shared key, the shared key can be securely generated and distributed, effectively preventing the key from being stolen and cracked; by encrypting the base-9 sequence, it is ensured that even if the information is intercepted, it is difficult to decrypt and obtain the original data without the correct key; the use of the mapping key ensures the randomness and unpredictability of the selected unit matrix, and the second-order reference matrix formed by tiling the unit matrix without overlap provides a complex mapping rule for subsequent information embedding, making the secret information more concealed when embedded in the carrier image, increasing the difficulty for attackers to analyze and detect the stego information; Hilbert curve scanning can maintain the local coherence of pixels, making the secret information more evenly distributed when embedded in the carrier image, reducing the changes in image statistical characteristics caused by information embedding, and reducing the risk of stego information being detected; using a second-order reference matrix for information embedding can enhance the complexity and concealment of the embedding process, making the secret information more difficult to be discovered and extracted during transmission, effectively improving the security of data transmission. Compared with the prior art, the present application can improve the security of data transmission.

[0011] Furthermore, the method of using the second-order reference matrix to embed the encrypted information into the first pixel pair sequence to obtain a steganographic image is specifically as follows:

[0012] sequentially reading every two digits of the nonadic sequence from the encrypted information, and extracting corresponding pixel pairs from the first pixel pair sequence;

[0013] Positioning the pixel pairs at corresponding coordinate points of the second-order reference matrix, and constructing a second unit matrix with a second-order embedding space with the coordinate points as the center;

[0014] In the second unit matrix, pixel adjustment positions that meet preset conditions are searched, and the first pixel pair sequence is traversed. With the goal of minimizing the pixel adjustment amplitude, the pixel pairs in the carrier image are replaced with the corresponding pixel adjustment positions in sequence until all pixel pairs in the first pixel pair sequence are replaced, thereby obtaining a stego image.

[0015] In this way, by embedding the encrypted nonadic sequence into the pixel pairs of the carrier image and using the second-order reference matrix and pixel adjustment strategy to minimize visual distortion, the secret information is effectively hidden and the security of data transmission is improved.

[0016] Furthermore, searching for a pixel adjustment position that meets a preset condition in the second unit matrix is ​​specifically:

[0017] Using every two digits of the nonadic sequence as an index, traversing the horizontal axis coordinate and the vertical axis coordinate based on the second-order embedding space characteristic of the second unit matrix;

[0018] If the horizontal axis coordinate and the vertical axis coordinate meet a preset condition, a pixel adjustment position is determined based on the horizontal axis coordinate and the vertical axis coordinate.

[0019] In this way, the pixel adjustment position is determined by the ninary sequence index and the second-order embedding space characteristics, making the embedding of secret information in the carrier image more covert and dispersed, increasing the difficulty of analysis and detection for attackers, thereby effectively improving the security of data transmission.

[0020] Furthermore, the converting of the secret data into a base-9 sequence is specifically as follows:

[0021] The secret information is converted into a binary bit stream, and the binary bit stream is converted into a ninary sequence.

[0022] In this way, through base conversion, the complexity of the data can be increased, so that the original data can be preliminarily converted and disguised before transmission, thereby improving the confidentiality of the data.

[0023] Furthermore, the scanning of the preset carrier image into a non-overlapping first pixel pair sequence according to the Hilbert curve is specifically as follows:

[0024] According to the size of the carrier image, a scanning parameter of the Hilbert curve is selected so that the coverage of the Hilbert curve completely matches the pixel boundary of the carrier image;

[0025] According to the scanning parameters, each pixel of the carrier image is traversed in sequence from a preset starting direction, the pixels are arranged into a one-dimensional pixel sequence in the traversal order, and the one-dimensional pixel sequence is paired according to a preset rule to obtain the first pixel pair sequence, wherein the preset rule includes pairing adjacent pixels without overlapping.

[0026] In this way, the Hilbert curve scanning parameters are selected according to the carrier image size and the pixel boundaries are completely matched. Then, a non-overlapping first pixel pair sequence is generated according to preset rules. This can ensure that the secret information is embedded evenly and continuously in the image, thereby effectively improving the security of data transmission.

[0027] Furthermore, after obtaining the stego image, the method further includes:

[0028] Scanning the steganographic image using the Hilbert curve to generate a second pixel pair sequence;

[0029] Searching for a third unit matrix from a preset mapping library based on the mapping key, and tiling the third unit matrix without duplication to obtain a decryption reference matrix;

[0030] The second pixel pair sequence is traversed, the encrypted information of each pixel pair is reversely parsed according to the second-order embedding space characteristic of the decryption reference matrix, and the secret data is determined based on the encrypted information.

[0031] In this way, by using the Hilbert curve to scan the steganographic image to generate a sequence of pixel pairs, and constructing a decryption reference matrix based on the mapping key and the preset mapping library, the encrypted information in the pixel pairs is reversely parsed based on the second-order embedding space characteristics of the matrix, and the secret data is finally determined. This whole process effectively ensures the security and accuracy of data transmission and prevents information from being stolen or tampered with during transmission.

[0032] Furthermore, the determining of the secret data based on the encrypted information is specifically:

[0033] Decrypting the encrypted information using the encryption key to obtain the nonamendian sequence;

[0034] The non-ary sequence is converted into a binary bit stream to obtain the secret data of the power system.

[0035] In this way, the encrypted information is decrypted by using the encryption key generated by the quantum key distribution system, and then the nine-base sequence is converted into a binary bit stream, so as to safely recover the secret data of the power system, effectively ensuring the security of data transmission.

[0036] Another embodiment of the present invention further provides a high-load data steganography system, comprising: an acquisition module, an encryption module, a tiling module, and an embedding module;

[0037] The acquisition module is used to acquire secret data of the power system and convert the secret data into a 9-ary sequence;

[0038] The encryption module is configured to generate a shared key using a quantum key distribution system, and encrypt the nonadic sequence using the encryption key to obtain encrypted information, wherein the shared key includes the encryption key and the mapping key;

[0039] The tiling module is configured to determine a corresponding first unit matrix from a preset mapping library based on the mapping key, and to tile the first unit matrix in a two-dimensional plane without overlap to obtain a second-order reference matrix;

[0040] The embedding module is used to scan the preset carrier image into a non-overlapping first pixel pair sequence according to the Hilbert curve, and embed the encrypted information into the first pixel pair sequence using the second-order reference matrix to obtain a steganographic image.

[0041] The embodiment of the present invention can increase the complexity of data through base conversion, so that the original data undergoes preliminary conversion and disguise before transmission, thereby improving the confidentiality of the data; using a quantum key distribution system to generate a shared key, the shared key can be securely generated and distributed, effectively preventing the key from being stolen and cracked; by encrypting the base-9 sequence, it is ensured that even if the information is intercepted, it is difficult to decrypt and obtain the original data without the correct key; the use of the mapping key ensures the randomness and unpredictability of the selected unit matrix, and the second-order reference matrix formed by tiling the unit matrix without overlap provides a complex mapping rule for subsequent information embedding, making the secret information more concealed when embedded in the carrier image, increasing the difficulty for attackers to analyze and detect the stego information; Hilbert curve scanning can maintain the local coherence of pixels, making the secret information more evenly distributed when embedded in the carrier image, reducing the changes in image statistical characteristics caused by information embedding, and reducing the risk of stego information being detected; using a second-order reference matrix for information embedding can enhance the complexity and concealment of the embedding process, making the secret information more difficult to be discovered and extracted during transmission, effectively improving the security of data transmission. Compared with the prior art, the present application can improve the security of data transmission.

[0042] Another embodiment of the present invention further provides a terminal device, comprising: a processor, a memory, and a computer program stored in the memory and configured to be executed by the processor. When the processor executes the computer program, the steps of the high-load data steganography method of the present invention are implemented.

[0043] Another embodiment of the present invention further provides a computer-readable storage medium item, comprising: a stored computer program, which, when the computer program is executed, controls the device where the computer-readable storage medium is located to execute the steps of the high-load data steganography method of the present invention. BRIEF DESCRIPTION OF THE DRAWINGS

[0044] In order to more clearly illustrate the technical solution of the present application, the following is a brief introduction to the drawings required for use in the implementation. Obviously, the drawings described below are only some implementation methods of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without any creative work.

[0045] Figure 1 This is a flowchart of an embodiment of the high-load data steganography method provided by the present application;

[0046] Figure 2 This is a flowchart of steps S201 to S203 provided by this application;

[0047] Figure 3 is a schematic diagram of the second-order reference matrix and the first unit matrix provided by this application;

[0048] Figure 4 is an image diagram of the carrier image and the steganographic image provided by this application;

[0049] Figure 5 It is a flowchart of steps S501 to S503 provided by this application;

[0050] Figure 6 It is a structural diagram of an embodiment of the high-load data steganography system provided by this application. DETAILED DESCRIPTION

[0051] To make the objectives, technical solutions, and advantages of this application more clear, the technical solutions in this application will be clearly and completely described below in conjunction with the accompanying drawings in the embodiments of this application. Obviously, the described embodiments are only part of the embodiments of this application, not all of them. Based on the embodiments in this application, all other embodiments obtained by ordinary technicians in this field without making any creative efforts are within the scope of protection of this application.

[0052] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by those skilled in the art to which this application belongs; the terms used herein are only for the purpose of describing specific embodiments and are not intended to limit this application; the terms "including" and "having" and any variations thereof in the specification and claims of this application and the above-mentioned figure descriptions are intended to cover non-exclusive inclusions.

[0053] In the description of the embodiments of this application, the technical terms "first" and "second" are used only to distinguish different objects and should not be understood to indicate or imply relative importance or implicitly specify the quantity, specific order, or primary and secondary relationship of the indicated technical features. In the description of the embodiments of this application, the meaning of "plurality" is more than two, unless otherwise clearly and specifically defined.

[0054] References herein to "embodiments" mean that a particular feature, structure, or characteristic described in connection with the embodiments may be included in at least one embodiment of the present application. The appearance of this phrase in various places in the specification does not necessarily refer to the same embodiment, nor does it constitute an independent or alternative embodiment that is mutually exclusive of other embodiments. It is understood, both explicitly and implicitly, by those skilled in the art that the embodiments described herein may be combined with other embodiments.

[0055] In the description of the embodiments of this application, the term "and / or" is simply a description of the association relationship between associated objects, indicating that three relationships can exist. For example, A and / or B can represent the following three situations: A exists alone, A and B exist simultaneously, and B exists alone. In addition, the character " / " in this document generally indicates that the associated objects are in an "or" relationship.

[0056] In the description of the embodiments of the present application, the term "multiple" refers to more than two (including two). Similarly, "multiple groups" refers to more than two groups (including two groups), and "multiple pieces" refers to more than two pieces (including two pieces).

[0057] In the description of the embodiments of the present application, unless otherwise expressly specified or limited, technical terms such as "installed," "connected," "connected," and "fixed" should be understood in a broad sense. For example, they can refer to fixed connections, detachable connections, or integration; mechanical connections or electrical connections; direct connections or indirect connections through an intermediate medium; internal connections between two components or interactions between two components. Those skilled in the art can understand the specific meanings of the above terms in the embodiments of the present application based on specific circumstances.

[0058] In modern information systems such as smart grids, the secure transmission and storage of images, videos, and sensitive data present challenges. Advances in quantum computing technology have put traditional encryption algorithms (such as AES and RSA) at risk of being cracked, potentially leading to the leakage of sensitive data. Consequently, image steganography has become a research hotspot, hiding sensitive information within image data to enhance the confidentiality and security of transmission. While existing information hiding algorithms based on reference matrices can increase information embedding capacity, they can degrade image visual quality and produce noticeable distortion at high embedding loads, reducing confidentiality. Furthermore, they struggle to guarantee security against quantum computing attacks, failing to meet the high security and confidentiality requirements of scenarios such as smart grids.

[0059] See also Figure 1 , Figure 1 1 is a flow chart of an embodiment of a high-load data steganography method provided by the present application. To improve the security of data transmission, an embodiment of the present invention provides a high-load data steganography method, including steps S101 to S104.

[0060] Step S101, obtaining secret data of the power system and converting the secret data into a 9-ary sequence;

[0061] In some embodiments, secret data of the power system is obtained. The secret data may be images, videos, or device data in the substation. These data are typically stored and transmitted in digital form. For example, image data may be in JPEG or PNG format, video data may be in MP4 or AVI format, and device data may be numerical data such as temperature, humidity, voltage, and current collected by sensors.

[0062] In some embodiments, converting the secret data into a nonadic sequence is specifically performed by converting the secret information into a binary bit stream, and then converting the binary bit stream into a nonadic sequence. Specifically, after obtaining the secret data, the secret data is converted into a binary bit stream to ensure that the message exists in a universal digital form. This is because in computers, all data is stored and processed in binary form. The binary bit stream is then grouped into groups of a certain length, and each group of binary numbers is converted into a corresponding nonadic number to obtain a nonadic sequence. For example, every 4-bit binary number can be grouped into a group. Since 24=16, and the range of nonadic numbers is 0 to 8, a 4-bit binary number can represent 16 states, which is sufficient to cover the 9 states of nonadic numbers. Then, the binary number 0000 is converted into the nonadic number 0, the binary number 0001 is converted into the nonadic number 1, and so on until the binary number 1001 is converted into the nonadic number 8. In this way, the binary numbers 1010 to 1111 can be mapped to the nonadic numbers 0 to 8.

[0063] It should be noted that the purpose of this step is to convert secret data in any base into a base-9 secret digit, or a nonadic sequence. Binary is the universal representation of all numbers in computers. Whether it's text, images, or sound, everything ultimately exists in the system as a binary bit stream. Converting secret data into a binary bit stream is done to standardize and allow for uniform processing of all information. The algorithm uses a base-9 system because its embedding logic embeds two base-9 digits into a pixel pair. The nonadic system corresponds to the nine digits from 0 to 8, and the constructed 9×9 unit matrix perfectly covers all 81 possible combinations (9×9=81). This allows for one-to-one mapping without duplication or waste. Therefore, binary is used to standardize processing, while nonadic is used to match the designed embedding matrix.

[0064] It should be noted that if the secret data is image data, you can use an image processing library (such as OpenCV or PIL) to read the image file as a pixel matrix, and then convert each pixel value into a binary representation; if the secret data is video data, you can use a video processing tool (such as FFmpeg) to decompose the video file into frames, and then convert each frame image into a binary bit stream; if the secret data is device data (numeric value), you can directly convert it into a binary representation.

[0065] In this way, through base conversion, the complexity of the data can be increased, so that the original data can be preliminarily converted and disguised before transmission, thereby improving the confidentiality of the data.

[0066] Step S102: generating a shared key using a quantum key distribution system, and encrypting the nonamel sequence using an encryption key to obtain encrypted information, wherein the shared key includes the encryption key and the mapping key;

[0067] In some embodiments, a shared key is generated using a quantum key distribution system, specifically: a quantum key distribution (QKD) system is constructed based on the BB84 protocol, which uses the non-cloning and uncertainty principles of quantum mechanics to ensure the security of key distribution, distributes quantum states between the sender and the receiver, and generates a shared key K by measuring and comparing the quantum states, wherein the shared key consists of two parts K = {K1, K2}, which are encryption key K1 and mapping key K2, respectively. The encryption key K1 is used to encrypt the nine-ary sequence or decrypt the steganographic information to ensure the confidentiality of the data; the mapping key K2 is used to subsequently determine the unit matrix used in the construction of the second-order reference matrix, thereby introducing randomness and anti-quantum attack capabilities to the steganographic process, and ensuring the smooth progress of the steganographic process.

[0068] It's important to note that the core purpose of a QKD system is to ensure that both communicating parties (sender A and receiver B) share an identical secret key, while any third party remains completely unaware. Therefore, the shared key is jointly and synchronously generated by both parties (sender A and receiver B), making it known only to them and unknown to all other parties. Therefore, in a QKD system, although the initially generated quantum bit sequence is random, the sender and receiver, through protocol steps such as basis selection comparison, bit error rate detection, error correction, and privacy amplification, can ultimately collaboratively derive a consistent and private shared key without revealing the key content. Therefore, despite the randomness of the key generation process, QKD's error correction and privacy amplification mechanisms ensure that the final shared key is consistent between both communicating parties. This negotiation is not an independent generation, but rather a collaborative process to arrive at the same key sequence.

[0069] It should be noted that if QKD is eavesdropped or tampered with during transmission, it will be detected in time by characteristics such as the collapse of the quantum entangled state or the change in the bit error rate, thereby effectively resisting man-in-the-middle attacks and quantum computing threats. After detecting and correcting the bit errors through the public channel, the security key K can be obtained.

[0070] In this way, quantum key distribution (QKD) technology is used to achieve secure key generation and transmission, making the 9×9 unit matrix selected based on the pre-shared key highly random and unpredictable, effectively preventing the risks of key theft and man-in-the-middle attacks.

[0071] In some embodiments, the non-ary sequence is encrypted using an encryption key to obtain encrypted information. Specifically, first, a symmetric encryption algorithm (such as AES) is used to encrypt the non-ary sequence. The encryption key in the shared key generated above is used to encrypt the non-ary sequence; then, each digit in the non-ary sequence is subjected to a corresponding encryption operation (such as a modular operation, etc.) with the encryption key K1 to generate encrypted non-ary information, i.e., encrypted information. For example, a number of encryption rounds and operation steps similar to the AES algorithm can be used to perform multiple rounds of replacement and permutation operations on the non-ary sequence, so that the encrypted information has a high degree of randomness and unpredictability compared to the original information, ensuring the security of the encrypted information. The encrypted information obtained in this way is the secret information to be subsequently embedded in the carrier image. It has been processed by the quantum key distribution system and the symmetric encryption algorithm, and has a high degree of confidentiality and anti-attack capability, and can be safely transmitted and stored.

[0072] It should be noted that the symmetric encryption algorithm has the characteristics of fast encryption and decryption speed and high efficiency, and is suitable for encryption processing of large amounts of data. In this scheme, it is used to encrypt secret information converted into base-9 to ensure the security and efficiency of the encryption process.

[0073] Step S103: determining a corresponding first unit matrix from a preset mapping library based on the mapping key, and tiling the first unit matrix on a two-dimensional plane without overlap to obtain a second-order reference matrix;

[0074] In some embodiments, the corresponding first unit matrix is ​​determined from a preset mapping library based on the mapping key, specifically as follows: first, a mapping relationship library is pre-defined, which stores multiple possible 9×9 unit matrices C, each unit matrix C has a unique identifier or index (that is, each mapping key K2 corresponds to a uniquely determined 9×9 unit matrix C), and each unit matrix has a second-order embedding space, that is, two adjacent pairs of numbers on the horizontal coordinate contain all possible non-repeating non-ary number combinations; since the value of the mapping key K2 corresponds to the identifier or index of the unit matrix stored in the preset mapping library, the mapping key K2 can be used to quickly and accurately find the uniquely determined first unit matrix from the preset mapping library, wherein the first unit matrix is ​​a non-ary matrix of size 9×9 with a second-order embedding space.

[0075] It should be noted that the mapping key can be an integer, a string, or an identifier in another form, which is used to point to a specific unit matrix in a preset mapping library.

[0076] It's important to note that the first unit matrix serves as an embedding space for the secret information. Essentially, it serves as an embedding template or "reference coordinate system" used in the subsequent embedding process and has no direct connection to the original data itself. The original data "enters" the embedding process during the subsequent pixel mapping process, which involves first converting the original data into base-9. The first unit matrix is ​​then used to determine the two pixel values ​​into which the two base-9 digits should be embedded, thereby enhancing the randomness of the embedding template and the overall security of the system.

[0077] In some embodiments, the first unit matrix is ​​tiled on a two-dimensional plane without overlapping to obtain a second-order reference matrix. Specifically, first, the size of the second-order reference matrix to be generated is determined, which is usually 256×256 to match the dynamic range of the grayscale image pixel value (0 to 255). Afterwards, a two-dimensional plane of the same size as the target is created to store the generated second-order reference matrix. Then, the selected first unit matrix (9×9) is used as the basic unit to be tiled on the initialized two-dimensional plane without overlapping, that is, it is repeatedly copied from left to right and from top to bottom on the two-dimensional plane, and arranged in sequence without overlapping or jumping, thereby constructing a 256×256 second-order reference matrix, wherein the starting position of each first unit matrix is ​​the area adjacent to the end of the previous first unit matrix, ensuring that the entire matrix is ​​tiled by multiple first unit matrices to form a regular and fully covered embedded reference structure; subsequently, during the tiling process, when the boundary of the two-dimensional plane is reached, boundary processing is required. If there is insufficient remaining space, To completely place a 9×9 unit matrix (i.e., not an integer multiple of 9), adjustments are made according to preset rules, such as reconstructing a new unit matrix along the matrix boundary so that it still has a second-order embedding space to ensure that the entire two-dimensional plane is completely covered without gaps. Finally, after completing the above tiling and boundary processing, a 256×256 second-order reference matrix is ​​obtained, where the second-order reference matrix is ​​formed by tiling multiple first unit matrices without overlap, has a coordinate system that matches the pixel value range of the grayscale image, each coordinate point corresponds to a specific pixel position, and each position has sufficient embedding representation space for subsequent secret information embedding operations.

[0078] It should be noted that non-overlapping tiling involves placing multiple 9×9 first unit matrices one after another in a two-dimensional matrix like floor tiles, without overlapping, repeating, or skipping, until the entire 256×256 matrix M is filled, thus forming the second-order reference matrix. Specifically, the unit matrix C is repeatedly copied and tiled from left to right and top to bottom: the first unit matrix is ​​9×9 in size, and 256 ÷ 9 = 28.4, meaning that 29×29 = 841 first unit matrices can be used to cover the entire 256×256 space (matrices at the edges need to be cropped). Each time a first unit matrix is ​​placed, it is placed in a position that does not overlap with the area occupied by the previous first unit matrix, hence the term non-overlapping tiling.

[0079] It should be noted that the second-order reference matrix M is a two-dimensional space matrix of size 256×256 based on the 9×9 first unit matrix without overlapping tiling. The coordinate point on the second-order reference matrix M can be expressed as M(p i ,p i+1 ), p i and p i+1 are two adjacent pixels, and p i ,p i+1 ∈{0,1,2,…,255}, which stipulates that the value range of the horizontal and vertical coordinates of the second-order reference matrix M is 0 to 255, which is consistent with the dynamic change range of the grayscale image pixel value. Each nine-ary first unit matrix has a second-order embedding space, that is, for any coordinate (x,y) and its adjacent coordinate about the horizontal axis (x+1mod 9,y), it satisfies: {(C(x,y),C((x+1)mod9,y))|x,y∈{0,1,…,8}} is a set of non-repeating nine-ary digit combinations to ensure sufficient embedding representation space.

[0080] In this way, by constructing a 256×256 second-order reference matrix, multiple 9×9 unit matrices are tiled in a non-overlapping manner to guide the embedding of each two bits of ninary secret information into the corresponding pixel pairs of the original image in a manner that minimizes distortion. This design not only achieves a hidden payload of up to 3.17bpp, but also ensures that the visual quality of the steganographic image is approximately 39.6dB. This allows the algorithm to maintain a high payload information embedding capacity while also obtaining good steganographic image quality.

[0081] Step S104 : Scanning the preset carrier image into a non-overlapping first pixel pair sequence according to the Hilbert curve, and embedding the encryption information into the first pixel pair sequence using the second-order reference matrix to obtain a stego-image.

[0082] In some embodiments, the method of scanning a preset carrier image into a non-overlapping first pixel pair sequence according to a Hilbert curve is as follows: based on the size of the carrier image, selecting scanning parameters of the Hilbert curve so that the coverage range of the Hilbert curve completely matches the pixel boundary of the carrier image; traversing each pixel of the carrier image in sequence from a preset starting direction according to the scanning parameters, arranging the pixels into a one-dimensional pixel sequence in the traversal order, and pairing the one-dimensional pixel sequence according to preset rules to obtain the first pixel pair sequence, wherein the preset rules include pairing adjacent pixels without overlapping. Specifically, first, the width and height of the carrier image are obtained to determine the pixel size of the image. The order of the Hilbert curve (that is, the scanning parameters) needs to be selected according to the image size to ensure that the curve can cover the entire image area; then, according to the size of the carrier image, a suitable Hilbert curve order is selected, and it is ensured that the starting position and direction of the Hilbert curve are aligned with the pixel boundary of the carrier image; then, an empty one-dimensional array is created to store the pixels arranged in the order of the Hilbert curve, and starting from a preset starting direction (such as the upper left corner), each pixel of the carrier image is accessed in turn along the path of the Hilbert curve. A recursive or iterative algorithm can be used to generate the path of the Hilbert curve, and pixels are collected along the path, and each accessed pixel value is added to the one-dimensional array in the traversal order until all pixels are traversed, and a one-dimensional pixel sequence P = (p1, p2, p3, ..., p h×W Finally, create an empty list to store the paired pixel pairs. According to the preset rules (such as adjacent pixels are paired and do not overlap), take two adjacent pixels from the one-dimensional pixel sequence to form a pixel pair. For example, the i-th and i+1-th pixels in the sequence form a pixel pair. Each generated pixel pair is added to the list of the pixel pair sequence (p i ,p i+1 ), where i∈{1,3,5,...,h×w-1}, and finally we get h×w / 2 non-overlapping pixel pairs. If the total number of pixels is odd, the last pixel can be temporarily unpaired, or special processing can be performed according to specific needs. Starting from the first bit of the sequence, take a pair of every two bits to form the first pixel pair sequence: (p1,p2), (p3,p4), etc., mathematically expressed as: (p i ,p i+1 ), where i∈{1,3,5,...,h×w-1} and finally we get h×w / 2 non-overlapping pixel pairs.

[0083] It should be noted that the order of the Hilbert curve determines the complexity and coverage of the curve. For an image of size h×w, the order n is usually selected so that 2 nClose to but greater than or equal to the maximum size of the image, for example, if the image size is 256×256, then n=8 can be selected, because 2 8 =256.

[0084] It should be noted that the Hilbert curve is a recursively defined space-filling curve that can map a one-dimensional sequence into a two-dimensional image space so that spatial locality is preserved. The construction method can be described as follows: (1) Let the original image size be h×w, and fill or crop it to 2 n ×2 n (e.g. 256×256) to match the order requirement of the Hilbert curve. (2) Select an appropriate order n and use a standard recursive algorithm or an existing library to generate the access sequence. (3) Get a sequence containing 2 n ×2 n The access order table of pixel coordinates is used as the pixel scanning path. After constructing the access path of the Hilbert curve, we only need to access the image pixels one by one according to the order of the generated coordinates. Assuming that the access path of a certain order Hilbert curve is: [(0,0), (0,1), (1,1), (1,0), (2,0), ...], then we access the pixel values ​​at these positions in sequence and arrange them into a one-dimensional sequence of pixel pairs.

[0085] The Hilbert curve is a self-similar fractal curve with the property of filling two-dimensional space. During the scanning process, the Hilbert curve will cover all pixels in the image and try to keep adjacent sampling points adjacent in two-dimensional space. An access sequence table can be generated through the standard Hilbert curve construction algorithm, and then each pixel point with corresponding coordinates in the carrier image can be accessed in sequence according to this path to form a one-dimensional pixel sequence, which is conducive to the subsequent secret information embedding operation.

[0086] It should be noted that when generating the Hilbert curve path, ensure that the curve does not exceed the pixel boundary of the carrier image. n If necessary, the image can be padded (e.g., with black or white pixels) or cropped to make it fit within the 2D image. n requirements to adapt to the generation of the Hilbert curve.

[0087] In this way, the Hilbert curve scanning parameters are selected according to the carrier image size and the pixel boundaries are completely matched. Then, a non-overlapping first pixel pair sequence is generated according to preset rules. This can ensure that the secret information is embedded evenly and continuously in the image, thereby effectively improving the security of data transmission.

[0088] Please refer to Figure 2In some embodiments, the step of embedding the encrypted information into the first pixel pair sequence using the second-order reference matrix to obtain a steganographic image includes steps S201 to S203;

[0089] Step S201, sequentially reading every two digits of the nonamel sequence from the encrypted information, and extracting corresponding pixel pairs from the first pixel pair sequence;

[0090] In some embodiments, an index variable is set to track the position of the currently read non-ary sequence. After that, a loop structure is used to read two digits of the non-ary sequence from the encrypted information each time. For example, if the encrypted information is stored in an array or a string, each time the index corresponding to the position s is read. i and s i+1 After reading the two elements, the index increases by 2 so that the next two-bit sequence can be read next time. At the same time, the corresponding pixel pairs (p i ,p i+1 ), assuming that the pixel pair sequence is stored in a list, each time the pixel pair corresponding to the current index position is extracted, the index is incremented by 1.

[0091] Step S202, positioning the pixel pairs at corresponding coordinate points of the second-order reference matrix, and constructing a second unit matrix with a second-order embedding space with the coordinate points as the center;

[0092] In some embodiments, the extracted pixel pairs (p i ,p i+1 ) is located at the corresponding coordinate point M(p i ,p i+1 ), which can be achieved by converting the coordinates of the pixel pair into the row and column indices of the matrix. For example, if the position of the pixel pair in the image is (x, y), the position in the second-order reference matrix can be calculated by the coordinate transformation formula; then, with the located coordinate point as the center, a second unit matrix C with a second-order embedding space is constructed in the second-order reference matrix ′ , this unit matrix inherits the properties of the second-order reference matrix, ensuring that it has sufficient embedding space.

[0093] It should be noted that the process of “locating pixel pairs on the reference matrix” is to locate a pixel pair (p i ,p i+1) as two-dimensional coordinates (x, y), and find the corresponding position on the 256×256 second-order reference matrix M. Assuming that a pair of pixel values ​​is (130, 85), then find the coordinate M(130, 85) on the matrix M. It is used as the "center point". We need to construct a new 9×9 unit matrix C' with it as the center to embed information in this local space. The operation of "constructing the unit matrix C' with the coordinate point as the center" has two cases: (1) If the center point is far enough from the edge (4≤p i ,p i+1 ≤251) is taken as the center and expanded 4 units upward, downward, left and right to form a 9×9 local area, that is, from (x-4, y-4) to (x+4, y+4); (2) If the center point is too close to the edge (p i ,p i+1 ≤4 or 251≤p i ,p i+1 ), then the unit matrix C is reconstructed along the boundary of the second-order matrix M ′ .

[0094] Please note that, please refer to Figure 3 , Figure 3 This is a schematic diagram of the second-order reference matrix and the first unit matrix provided in this application, wherein the size of the second-order reference matrix is ​​256×256, and the first unit matrix is ​​the red bold part, which is a unit matrix of 9×9 in size.

[0095] Step S203: In the second unit matrix, pixel adjustment positions that meet preset conditions are searched, and the first pixel pair sequence is traversed. With the goal of minimizing the pixel adjustment amplitude, the pixel pairs in the carrier image are replaced with the corresponding pixel adjustment positions in sequence until all pixel pairs in the first pixel pair sequence are replaced, thereby obtaining a stego image.

[0096] In some embodiments, the pixel adjustment position that meets the preset conditions is searched in the second unit matrix, specifically: using each two digits of the nine-digit sequence as an index, relying on the second unit matrix C ′The horizontal coordinate and the vertical coordinate are traversed based on the second-order embedding space characteristics (i.e., adjacent combinations of the horizontal axis cover 81 non-repeating nonadic number pairs); if the horizontal coordinate and the vertical coordinate meet the preset conditions, the pixel adjustment position is determined based on the horizontal coordinate and the vertical coordinate. Specifically, each two-digit nonadic digit is read from the encrypted nonadic sequence in sequence, and these two digits will be used as the index for subsequent search for the pixel adjustment position; thereafter, the initial values ​​of the horizontal coordinate (x) and the vertical coordinate (y) are set, usually starting from the starting position of the matrix (such as the upper left corner, x=0, y=0), and each position in the second unit matrix is ​​traversed in a preset order (such as row priority or column priority). For each position, check whether its corresponding nonadic digit combination matches the two-digit nonadic sequence currently read to ensure that the position meets the embedding rules, such as minimizing the pixel adjustment amplitude or other preset conditions. Finally, when a matching nine-base digit combination is found and a position that meets the preset conditions is found, the horizontal and vertical coordinates of the position are recorded, and the recorded coordinate positions are stored in a list or array for subsequent pixel adjustment operations. If a matching position is found and the preset conditions are met, the current traversal process can be ended and pixel adjustment can be prepared.

[0097] It should be noted that the precondition is: C ′ (p i ′ ,p i+1 ′ )=s i And C ′ (p i ′ +1mod 9,p i+1 ′ )=s i+1 .

[0098] The use of refined embedding strategies and pixel fine-tuning algorithms effectively improves the steganographic system's resistance to statistical analysis attacks such as PDH and RS, further enhancing the security of the entire steganographic system.

[0099] In this way, the pixel adjustment position is determined by the ninary sequence index and the second-order embedding space characteristics, making the embedding of secret information in the carrier image more covert and dispersed, increasing the difficulty of analysis and detection for attackers, thereby effectively improving the security of data transmission.

[0100] In some embodiments, the first pixel pair sequence is traversed, and with the goal of minimizing the pixel adjustment amplitude, pixel pairs in the carrier image are sequentially replaced with corresponding pixel adjustment positions until all pixel pairs in the first pixel pair sequence are replaced, thereby obtaining a stego-image. Specifically, the following steps are performed: First, among multiple pixel adjustment positions that meet the embedding conditions, a position is selected that minimizes the pixel adjustment amplitude. This means that the difference between the new pixel values ​​and the original pixel values ​​should be as small as possible to reduce visual distortion. Next, the original pixel pair is replaced with the pixel adjustment position. The replaced pixel pair contains the secret information but remains visually highly consistent with the original image. After the replacement of the current pixel pair is completed, the next pixel pair in the pixel pair sequence is moved to, and the above steps are repeated until all pixel pairs are replaced. When all pixel pairs in the first pixel pair sequence have been replaced according to the above method, the resulting image is the stego-image. This image is visually very similar to the original carrier image but has embedded the secret information.

[0101] Please note that, please refer to Figure 4 , Figure 4 The figure is a schematic diagram of the carrier image and the steganographic image provided by the present invention, wherein a, b, c, d are the original carrier images, and e, f, g, h are the steganographic images after embedding the secret data.

[0102] In this way, by embedding the encrypted nonadic sequence into the pixel pairs of the carrier image and using the second-order reference matrix and pixel adjustment strategy to minimize visual distortion, the secret information is effectively hidden and the security of data transmission is improved.

[0103] Please refer to Figure 5 In some embodiments, after obtaining the stego image, the method further includes steps S501 to S503;

[0104] Step S501, scanning the stego image using the Hilbert curve to generate a second pixel pair sequence;

[0105] In some embodiments, the receiving party receives the stego image I ′ The same scanning and dividing method as the Hilbert curve is used to transform the stego image I ′ Convert to the second pixel pair sequence (p i ′ ,p i+1 ′ ), where i∈{1,3,5,…,h×w-1}.

[0106] Step S502: searching a third unit matrix from a preset mapping library based on the mapping key, and tiling the third unit matrix without duplication to obtain a decryption reference matrix;

[0107] In some embodiments, first, a mapping key is used to find the corresponding third unit matrix from a preset mapping library, and the size of the decryption reference matrix is ​​determined, which is usually 256×256 to match the dynamic range of grayscale image pixel values ​​(0 to 255). Then, the selected third unit matrix (9×9) is used as a basic unit and is tiled without overlap on an initialized two-dimensional plane to obtain a decryption reference matrix with a second-order embedding space.

[0108] Step S503 , traversing the second pixel pair sequence, reversely parsing the encryption information of each pixel pair according to the second-order embedding space characteristics of the decryption reference matrix, and determining the secret data based on the encryption information.

[0109] In some embodiments, the receiver has already obtained the same shared key K={K1, K2} through the QKD system in advance, and then

[0110] According to the mapping key K2, a unique 9×9 second unit matrix is ​​found from the predefined mapping relationship library, and the second-order reference matrix M of 257×257 size is tiled in the same way. ′ , which has the same mapping rule as the sender's reference matrix M. For the steganographic image I ′ Each pixel pair (p i ′ ,p i+1 ′ ), locate it to the second-order reference matrix M ′ Coordinate point M on ′ (p i ′ ,p i+1 ′ ), then the nine-digit information to be extracted is calculated as s i =M ′ (p i ′ ,p i+1 ′ ) and s i+1 =M ′ (p i ′ +1,p i+1 ′ ), and then continue to traverse the pixel pair sequence, repeating the above positioning, searching and extraction process until the stego image I ′ All the information in the system is extracted, and the encrypted information S in base nine is obtained. ′ .

[0111] In some embodiments, determining the secret data based on the encrypted information specifically comprises: decrypting the encrypted information using the encryption key to obtain the nonadic sequence; and converting the nonadic sequence into a binary bit stream to obtain the secret data of the power system. Specifically, the extracted encrypted information is decrypted using the encryption key to obtain the nonadic sequence, and the nonadic sequence is converted into a binary bit stream to ultimately obtain the secret data of the power system.

[0112] In this way, the encrypted information is decrypted by using the encryption key generated by the quantum key distribution system, and then the nine-base sequence is converted into a binary bit stream, so as to safely recover the secret data of the power system, effectively ensuring the security of data transmission.

[0113] In this way, by using the Hilbert curve to scan the steganographic image to generate a sequence of pixel pairs, and constructing a decryption reference matrix based on the mapping key and the preset mapping library, the encrypted information in the pixel pairs is reversely parsed based on the second-order embedding space characteristics of the matrix, and the secret data is finally determined. This whole process effectively ensures the security and accuracy of data transmission and prevents information from being stolen or tampered with during transmission.

[0114] It should be noted that this invention fully considers the practical needs of high-security application scenarios such as smart grids. It is not only applicable to the secure transmission and hidden storage of images, videos, and equipment data in power system substations, but also provides an innovative and efficient solution for large-scale data protection. In summary, this invention has achieved significant results in improving information hiding payload, optimizing image visual quality, and enhancing resistance to analytical attacks. It is suitable for data transmission and storage in high-security scenarios such as smart grids, providing solid theoretical and practical support for the development of modern information security technology.

[0115] It should be noted that the high visual quality while maintaining a large embedding capacity (ER = 3.16bpp) is mainly due to the following reasons: (1) The present invention adopts a minimum distortion embedding strategy guided by a second-order reference matrix to ensure that pixel modifications are minimized; (2) The embedding process is based on the Hilbert curve scanning path, which utilizes the local structure of spatial continuity in the image to embed data in adjacent pixel pairs, effectively reducing interference with the overall image structure.

[0116] Please refer to Table 1, which shows the experimental data for the carrier image and the stego image used in this invention. It is clear that after implementing the algorithm of this invention, the generated stego image is virtually indistinguishable from the original image to the naked eye, with consistent image details and texture, demonstrating high visual quality. The experimental data also shows that the stego image's peak signal-to-noise ratio (PSNR) remains around 39.6 dB, and its structural similarity (SSIM) is close to 1, demonstrating its high visual quality.

[0117] Table 1 Experimental data of carrier image and stego image

[0118]

[0119] Among them, Lena, Boat, Barbara, and Airplane correspond to Figure 4 Pictures a, b, c, and d in the figure: the name of the image (Lena, Boat, etc.), which are the images for experimental testing. QI (Quality Index): Image quality index, used to evaluate the similarity between the steganographic image and the original image in overall visual quality. The closer the value is to 1, the closer it is to the original image. SSIM (Structural Similarity Index): Structural similarity, which measures the similarity of images in terms of brightness, contrast, structure, etc. 1 means they are exactly the same, and usually ≥0.98 means almost lossless. MSE (Mean Squared Error): Mean squared error, which measures the difference in pixel values ​​between the steganographic image and the original image. The smaller the value, the better, indicating that it is closer to the original image. PSNR (PeakSignal-to-Noise Ratio): Peak signal-to-noise ratio, used to measure the degree of image distortion, measured in dB. It is generally believed that >30dB is visually almost lossless. The present invention reaches 39.6dB, indicating very high visual quality. ER (Embedding Rate): Embedding rate indicates the average number of bits of secret information embedded in each pixel. 3.1699bpp indicates high payload and large capacity.

[0120] The embodiment of the present invention can increase the complexity of data through base conversion, so that the original data undergoes preliminary conversion and disguise before transmission, thereby improving the confidentiality of the data; using a quantum key distribution system to generate a shared key, the shared key can be securely generated and distributed, effectively preventing the key from being stolen and cracked; by encrypting the base-9 sequence, it is ensured that even if the information is intercepted, it is difficult to decrypt and obtain the original data without the correct key; the use of the mapping key ensures the randomness and unpredictability of the selected unit matrix, and the second-order reference matrix formed by tiling the unit matrix without overlap provides a complex mapping rule for subsequent information embedding, making the secret information more concealed when embedded in the carrier image, increasing the difficulty for attackers to analyze and detect the stego information; Hilbert curve scanning can maintain the local coherence of pixels, making the secret information more evenly distributed when embedded in the carrier image, reducing the changes in image statistical characteristics caused by information embedding, and reducing the risk of stego information being detected; using a second-order reference matrix for information embedding can enhance the complexity and concealment of the embedding process, making the secret information more difficult to be discovered and extracted during transmission, effectively improving the security of data transmission. Compared with the prior art, the present application can improve the security of data transmission.

[0121] like Figure 6 As shown, based on the above method embodiment, a corresponding device embodiment is provided;

[0122] An embodiment of the present invention provides a high-load data steganography system, comprising: an acquisition module 100, an encryption module 200, a tiling module 300, and an embedding module 400;

[0123] The acquisition module 100 is used to acquire secret data of the power system and convert the secret data into a 9-ary sequence;

[0124] The encryption module 200 is configured to generate a shared key using a quantum key distribution system, and encrypt the nonadic sequence using an encryption key to obtain encrypted information, wherein the shared key includes the encryption key and a mapping key;

[0125] The tiling module 300 is configured to determine a corresponding first unit matrix from a preset mapping library based on the mapping key, and to tile the first unit matrix in a two-dimensional plane without overlap to obtain a second-order reference matrix;

[0126] The embedding module 400 is configured to scan a preset carrier image into a non-overlapping first pixel pair sequence according to a Hilbert curve, and embed the encrypted information into the first pixel pair sequence using the second-order reference matrix to obtain a stego-image.

[0127] It can be understood that the above-mentioned device embodiment corresponds to the method embodiment of the present invention, and can implement any of the above-mentioned method embodiments of the present invention to provide a high-load data steganography method.

[0128] It should be noted that the device embodiments described above are merely illustrative, and some or all of the modules may be selected according to actual needs to achieve the purpose of the present embodiment. Furthermore, in the drawings of the device embodiments provided by the present invention, the connection relationship between modules indicates that they have a communication connection, which may be implemented as one or more communication buses or signal lines. Those skilled in the art can understand and implement the present invention without inventive effort.

[0129] Based on the above-mentioned embodiment of the high-load data steganography method, another embodiment of the present invention provides a terminal device, which includes a processor, a memory, and a computer program stored in the memory and configured to be executed by the processor. When the processor executes the computer program, the high-load data steganography method of any embodiment of the present invention is implemented.

[0130] For example, in this embodiment, the computer program may be divided into one or more modules, which are stored in the memory and executed by the processor to implement the present invention. The one or more module elements may be a series of computer program instruction segments capable of performing specific functions, and the instruction segments are used to describe the execution process of the computer program in the terminal device.

[0131] The terminal device may be a computing device such as a desktop computer, a notebook computer, a PDA, a cloud server, etc. The terminal device may include, but is not limited to, a processor and a memory.

[0132] The processor may be a central processing unit (CPU), other general-purpose processors, digital signal processors (DSP), application-specific integrated circuits (ASIC), field-programmable gate arrays (FPGA) or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. The general-purpose processor may be a microprocessor or any conventional processor, etc. The processor is the control center of the terminal device, connecting various parts of the entire terminal device using various interfaces and lines.

[0133] Based on the above method embodiments, another embodiment of the present invention provides a computer-readable storage medium, including a stored computer program, wherein when the computer program is running, the device where the computer-readable storage medium is located is controlled to execute the high-load data steganography method described in any one of the above method embodiments of the present invention.

[0134] Wherein, the module / unit integrated in the device / terminal equipment, if implemented in the form of a software functional unit and sold or used as an independent product, can be stored in a computer-readable storage medium. Based on this understanding, the present invention implements all or part of the process in the above-mentioned embodiment method, and can also be completed by instructing the relevant hardware through a computer program. The computer program can be stored in a computer-readable storage medium, and when the computer program is executed by the processor, it can implement the steps of the above-mentioned various method embodiments. Wherein, the computer program includes computer program code, and the computer program code can be in source code form, object code form, executable file or some intermediate form. The computer-readable medium may include: any entity or device that can carry the computer program code, recording medium, USB flash drive, mobile hard disk, magnetic disk, optical disk, computer memory, read-only memory (ROM), random access memory (RAM), electric carrier signal, telecommunication signal and software distribution medium, etc.

[0135] The above is a preferred embodiment of the present invention. It should be pointed out that for ordinary technicians in this technical field, several improvements and modifications can be made without departing from the principles of the present invention. These improvements and modifications are also considered to be within the scope of protection of the present invention.

Claims

1. A high-load data steganography method, characterized in that: include: Obtaining secret data of the power system and converting the secret data into a 9-ary sequence; Generate a shared key using a quantum key distribution system, and encrypt the nonadic sequence using an encryption key to obtain encrypted information, wherein the shared key includes the encryption key and a mapping key; Determine a corresponding first unit matrix from a preset mapping library based on the mapping key, and tile the first unit matrix in a two-dimensional plane without overlap to obtain a second-order reference matrix; The preset carrier image is scanned into a non-overlapping first pixel pair sequence according to the Hilbert curve, and the encryption information is embedded into the first pixel pair sequence using the second-order reference matrix to obtain a stego image.

2. The high-load data steganography method according to claim 1, characterized in that: The method of using the second-order reference matrix to embed the encrypted information into the first pixel pair sequence to obtain a stego-image is specifically as follows: sequentially reading every two digits of the nonadic sequence from the encrypted information, and extracting corresponding pixel pairs from the first pixel pair sequence; Positioning the pixel pairs at corresponding coordinate points of the second-order reference matrix, and constructing a second unit matrix with a second-order embedding space with the coordinate points as the center; In the second unit matrix, pixel adjustment positions that meet preset conditions are searched, and the first pixel pair sequence is traversed. With the goal of minimizing the pixel adjustment amplitude, the pixel pairs in the carrier image are replaced with the corresponding pixel adjustment positions in sequence until all pixel pairs in the first pixel pair sequence are replaced, thereby obtaining a stego image.

3. The high-load data steganography method according to claim 2, characterized in that: The step of searching for a pixel adjustment position that meets a preset condition in the second unit matrix is ​​specifically as follows: Using every two digits of the nonadic sequence as an index, traversing the horizontal axis coordinate and the vertical axis coordinate based on the second-order embedding space characteristic of the second unit matrix; If the horizontal axis coordinate and the vertical axis coordinate meet a preset condition, a pixel adjustment position is determined based on the horizontal axis coordinate and the vertical axis coordinate.

4. The high-load data steganography method according to claim 1, characterized in that: The secret data is converted into a base-9 sequence, specifically: The secret information is converted into a binary bit stream, and the binary bit stream is converted into a ninary sequence.

5. The high-load data steganography method according to claim 1, characterized in that: The method of scanning the preset carrier image into a non-overlapping first pixel pair sequence according to the Hilbert curve is as follows: According to the size of the carrier image, a scanning parameter of the Hilbert curve is selected so that the coverage of the Hilbert curve completely matches the pixel boundary of the carrier image; According to the scanning parameters, each pixel of the carrier image is traversed in sequence from a preset starting direction, the pixels are arranged into a one-dimensional pixel sequence in the traversal order, and the one-dimensional pixel sequence is paired according to a preset rule to obtain the first pixel pair sequence, wherein the preset rule includes pairing adjacent pixels without overlapping.

6. The high-load data steganography method according to any one of claims 1 to 5, characterized in that: After obtaining the stego image, the method further includes: Scanning the steganographic image using the Hilbert curve to generate a second pixel pair sequence; Searching for a third unit matrix from a preset mapping library based on the mapping key, and tiling the third unit matrix without duplication to obtain a decryption reference matrix; The second pixel pair sequence is traversed, the encrypted information of each pixel pair is reversely parsed according to the second-order embedding space characteristic of the decryption reference matrix, and the secret data is determined based on the encrypted information.

7. The high-load data steganography method according to claim 6, characterized in that: The determining of the secret data based on the encrypted information is specifically: Decrypting the encrypted information using the encryption key to obtain the nonamendian sequence; The non-ary sequence is converted into a binary bit stream to obtain the secret data of the power system.

8. A high-load data steganography system, characterized in that: include: Acquisition module, encryption module, tiling module and embedding module; The acquisition module is used to acquire secret data of the power system and convert the secret data into a 9-ary sequence; The encryption module is configured to generate a shared key using a quantum key distribution system, and encrypt the nonadic sequence using the encryption key to obtain encrypted information, wherein the shared key includes the encryption key and the mapping key; The tiling module is configured to determine a corresponding first unit matrix from a preset mapping library based on the mapping key, and to tile the first unit matrix in a two-dimensional plane without overlap to obtain a second-order reference matrix; The embedding module is used to scan the preset carrier image into a non-overlapping first pixel pair sequence according to the Hilbert curve, and embed the encrypted information into the first pixel pair sequence using the second-order reference matrix to obtain a steganographic image.

9. A terminal device, characterized in that: include: one or more processors; a memory, coupled to the processor, for storing one or more programs; When the one or more programs are executed by the one or more processors, the one or more processors implement the high-load data steganography method according to any one of claims 1 to 7.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the high-load data steganography method according to any one of claims 1 to 7 is implemented.

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