Method, device, equipment and storage medium for concealed transmission of user sensitive information

Abstract

The present application relates to a method, apparatus, device, and storage medium for covertly transmitting user sensitive information, wherein the method comprises: performing image conversion on acquired user sensitive information to obtain a first image coefficient matrix corresponding to the user sensitive information; scrambling and compressing the first image coefficient matrix to obtain a processed first image coefficient matrix; compressing the user sensitive information in the processed first image coefficient matrix to obtain compressed user sensitive information, and encrypting the compressed user sensitive information to obtain ciphertext information corresponding to the user sensitive information; embedding the ciphertext information into a second image coefficient matrix corresponding to a carrier image to obtain a target image coefficient matrix; performing an inverse transformation on the target image coefficient matrix to obtain a target image including the user sensitive information, and transmitting the target image. This method can improve the integrity and security of user sensitive information transmission.

Description

Technical Field

[0001] The present application relates to the field of data processing, and in particular to a method, apparatus, device and storage medium for covertly transmitting user sensitive information. Background Art

[0002] With the rapid development of information technology, the security and transmission efficiency of personal privacy data are receiving increasing attention. In user applications (apps), efficient information hiding methods are needed to ensure both the covert transmission and integrity verification of user privacy data. Covert communication technology and digital watermarking technology, as key branches of information hiding, are particularly important in this context. Covert communication technology embeds data into other media to conceal transmitted information during communication. Digital watermarking technology embeds identifying information into digital media to protect intellectual property, ensure data integrity, and track information sources.

[0003] However, using covert communication technology may cause slight changes in the medium when embedding data, which may lead to unreliable data integrity. Using digital watermarking technology, the embedding process of the digital watermark may cause slight distortion of the data, which may lead to unreliable data integrity.

[0004] Therefore, how to improve the integrity and security of user sensitive information transmission has become an urgent problem to be solved. Summary of the Invention

[0005] The embodiments of the present application provide a method, apparatus, device and storage medium for covert transmission of user sensitive information, which can improve the integrity and security of the transmission of user sensitive information.

[0006] In a first aspect, an embodiment of the present application provides a method for covertly transmitting user sensitive information, the method comprising:

[0007] Performing image conversion on the acquired user sensitive information to obtain a first image coefficient matrix corresponding to the user sensitive information;

[0008] Performing scrambling and compression processing on the first image coefficient matrix to obtain a processed first image coefficient matrix;

[0009] Compressing the user sensitive information in the processed first image coefficient matrix to obtain compressed user sensitive information, and encrypting the compressed user sensitive information to obtain ciphertext information corresponding to the user sensitive information;

[0010] Embed the ciphertext information into the second image coefficient matrix corresponding to the carrier image to obtain the target image coefficient matrix;

[0011] Perform an inverse transformation on the target image coefficient matrix to obtain a target image including user sensitive information, and transmit the target image.

[0012] In one embodiment, image conversion is performed on the acquired user sensitive information to obtain a first image coefficient matrix corresponding to the user sensitive information, including: decomposing the acquired user sensitive information based on a target discrete wavelet transform function to obtain a low-frequency signal and a high-frequency signal corresponding to the user sensitive information; filtering and down-sampling the low-frequency signal and the high-frequency signal respectively to obtain low-frequency sensitive information and high-frequency sensitive information; and reconstructing the low-frequency sensitive information and the high-frequency sensitive information through an inverse transform to obtain a first image coefficient matrix corresponding to the user sensitive information.

[0013] In one embodiment, the first image coefficient matrix is ​​scrambled and compressed to obtain a processed image coefficient matrix, including: using a dynamic Josephus algorithm to scramble the first image coefficient matrix to obtain a scrambled first image coefficient matrix; using a partial Hadamard matrix to compress the scrambled first image coefficient matrix to obtain a processed first image coefficient matrix.

[0014] In one embodiment, the user sensitive information in the processed first image coefficient matrix is ​​compressed to obtain compressed user sensitive information, including: dividing the user sensitive information in the processed first image coefficient matrix into multiple sub-information; compressing the multiple sub-information respectively to obtain multiple compressed sub-information; and determining the compressed user sensitive information based on the multiple compressed sub-information.

[0015] In one embodiment, the ciphertext information is embedded into the second image coefficient matrix corresponding to the carrier image to obtain the target image coefficient matrix, including: selecting, from the second image coefficient matrix corresponding to the carrier image, an element position whose pixel value is less than a preset pixel threshold or whose image texture richness is greater than a preset richness threshold as a target embedding position; and embedding the ciphertext information into the target embedding position in the second image coefficient matrix to obtain the target image coefficient matrix.

[0016] In one embodiment, the ciphertext information is embedded into a target embedding position in the second image coefficient matrix to obtain a target image coefficient matrix, including: using a preset verification mechanism to verify the ciphertext information to obtain verified ciphertext information; and embedding the verified ciphertext information into a target embedding position in the second image coefficient matrix to obtain a target image coefficient matrix.

[0017] In a second aspect, the present application provides a device for concealed transmission of user sensitive information, the device comprising:

[0018] An image conversion unit, configured to perform image conversion on the acquired user sensitive information to obtain a first image coefficient matrix corresponding to the user sensitive information;

[0019] a processing unit, configured to perform scrambling and compression processing on the first image coefficient matrix to obtain a processed first image coefficient matrix;

[0020] The processing unit is further configured to compress the user sensitive information in the processed first image coefficient matrix to obtain compressed user sensitive information, and encrypt the compressed user sensitive information to obtain ciphertext information corresponding to the user sensitive information;

[0021] an embedding unit, configured to embed the ciphertext information into a second image coefficient matrix corresponding to the carrier image to obtain a target image coefficient matrix;

[0022] The processing and transmission unit is further used to perform inverse transformation processing on the target image coefficient matrix to obtain the target image including the user sensitive information, and transmit the target image.

[0023] In a third aspect, the present application provides a computer device comprising a memory and a processor, wherein the memory stores a computer program, and when the processor executes the computer program, the following steps are performed:

[0024] Performing image conversion on the acquired user sensitive information to obtain a first image coefficient matrix corresponding to the user sensitive information;

[0025] Performing scrambling and compression processing on the first image coefficient matrix to obtain a processed first image coefficient matrix;

[0026] Compressing the user sensitive information in the processed first image coefficient matrix to obtain compressed user sensitive information, and encrypting the compressed user sensitive information to obtain ciphertext information corresponding to the user sensitive information;

[0027] Embed the ciphertext information into the second image coefficient matrix corresponding to the carrier image to obtain the target image coefficient matrix;

[0028] Perform an inverse transformation on the target image coefficient matrix to obtain a target image including user sensitive information, and transmit the target image.

[0029] In a fourth aspect, the present application further provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the following steps:

[0030] Performing image conversion on the acquired user sensitive information to obtain a first image coefficient matrix corresponding to the user sensitive information;

[0031] Performing scrambling and compression processing on the first image coefficient matrix to obtain a processed first image coefficient matrix;

[0032] Compressing the user sensitive information in the processed first image coefficient matrix to obtain compressed user sensitive information, and encrypting the compressed user sensitive information to obtain ciphertext information corresponding to the user sensitive information;

[0033] Embed the ciphertext information into the second image coefficient matrix corresponding to the carrier image to obtain the target image coefficient matrix;

[0034] Perform an inverse transformation on the target image coefficient matrix to obtain a target image including user sensitive information, and transmit the target image.

[0035] In a fifth aspect, the present application further provides a computer program product, comprising a computer program, which, when executed by a processor, implements the following steps:

[0036] Performing image conversion on the acquired user sensitive information to obtain a first image coefficient matrix corresponding to the user sensitive information;

[0037] Performing scrambling and compression processing on the first image coefficient matrix to obtain a processed first image coefficient matrix;

[0038] Compressing the user sensitive information in the processed first image coefficient matrix to obtain compressed user sensitive information, and encrypting the compressed user sensitive information to obtain ciphertext information corresponding to the user sensitive information;

[0039] Embed the ciphertext information into the second image coefficient matrix corresponding to the carrier image to obtain the target image coefficient matrix;

[0040] Perform an inverse transformation on the target image coefficient matrix to obtain a target image including user sensitive information, and transmit the target image.

[0041] In the above-mentioned method, apparatus, device, and storage medium for covertly transmitting user sensitive information, a computer device can perform image conversion on the acquired user sensitive information to obtain a first image coefficient matrix corresponding to the user sensitive information; perform scrambling and compression processing on the first image coefficient matrix to obtain a processed first image coefficient matrix; perform compression processing on the user sensitive information in the processed first image coefficient matrix to obtain compressed user sensitive information, and encrypt the compressed user sensitive information to obtain ciphertext information corresponding to the user sensitive information; embed the ciphertext information into a second image coefficient matrix corresponding to the carrier image to obtain a target image coefficient matrix; perform an inverse transformation on the target image coefficient matrix to obtain a target image including the user sensitive information, and transmit the target image. Using this method, a computer device can embed the ciphertext information corresponding to the user sensitive information into the second image coefficient matrix corresponding to the carrier image, and then perform an inverse transformation on the target image coefficient matrix to obtain a target image including the user sensitive information, and transmit the target image. This improves the integrity and security of the transmission of user sensitive information. BRIEF DESCRIPTION OF THE DRAWINGS

[0042] In order to more clearly illustrate the technical solutions in the embodiments of the present application or related technologies, the following briefly introduces the drawings required for use in the embodiments of the present application or related technical descriptions. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other related drawings can be obtained based on these drawings without paying any creative work.

[0043] Figure 1 This is a schematic diagram of an application scenario of a method for covertly transmitting user sensitive information provided by an embodiment of the present application;

[0044] Figure 2 This is a flow chart of a method for covertly transmitting user sensitive information provided by an embodiment of the present application;

[0045] Figure 3 This is a flow chart of another method for covertly transmitting user sensitive information provided by an embodiment of the present application;

[0046] Figure 4 It is a process diagram of a dynamic Josephus algorithm;

[0047] Figure 5 This is a flowchart of another method for covertly transmitting user sensitive information provided by an embodiment of the present application;

[0048] Figure 6 This is a flowchart of a decryption process provided by an embodiment of the present application;

[0049] Figure 7This is a schematic diagram of the structure of a device for concealed transmission of user sensitive information provided by an embodiment of the present application;

[0050] Figure 8 It is a structural diagram of a computer device provided in an embodiment of the present application. DETAILED DESCRIPTION

[0051] In order to make the purpose, technical solutions and advantages of this application more clear, the following further describes this application in detail with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain this application and are not intended to limit this application.

[0052] The following introduces the application scenarios of the method for covert transmission of user sensitive information provided in the embodiments of the present application.

[0053] See Figure 1 , Figure 1 This is a schematic diagram of an application scenario of a method for concealed transmission of user sensitive information provided by an embodiment of the present application. Figure 1 As shown, the computer device 101 ( Figure 1 In the figure, the computer device 101 is drawn as an example of a terminal device) and a database server 102, wherein data can be transmitted between the computer device 101 and the database server 102 through a network.

[0054] In a scenario where a user needs to upload user sensitive information to an application, the computer device 101 can obtain the user sensitive information from the database server 102; then, perform image conversion on the obtained user sensitive information to obtain a first image coefficient matrix corresponding to the user sensitive information; perform scrambling and compression processing on the first image coefficient matrix to obtain a processed first image coefficient matrix; perform compression processing on the user sensitive information in the processed first image coefficient matrix to obtain compressed user sensitive information, and encrypt the compressed user sensitive information to obtain ciphertext information corresponding to the user sensitive information; embed the ciphertext information into the second image coefficient matrix corresponding to the carrier image to obtain a target image coefficient matrix; perform inverse transformation on the target image coefficient matrix to obtain a target image including the user sensitive information, and then upload the target image to the target application.

[0055] Optionally, the computer device 101 may be a terminal device, wherein the terminal device mentioned here may include but is not limited to: a smart phone, a tablet computer, a laptop computer, a desktop computer, a smart watch, a smart TV, a smart car terminal, etc.

[0056] See Figure 2 , Figure 2This is a flow chart of a method for concealed transmission of user sensitive information provided by an embodiment of the present application. The method can be executed by a computer device (for example, the computer device 201 mentioned above). Figure 2 As shown, the method for covertly transmitting user sensitive information may include but is not limited to the following steps:

[0057] S201: Perform image conversion on the acquired user sensitive information to obtain a first image coefficient matrix corresponding to the user sensitive information.

[0058] In an optional embodiment, before step S201, the computer device may obtain user sensitive information from a database. The user sensitive information may include but is not limited to the user's mobile phone number, ID number, etc.

[0059] In an optional embodiment, the computer device performs image conversion on the acquired user sensitive information to obtain a first image coefficient matrix corresponding to the user sensitive information. The computer device may utilize a discrete wavelet transform (DWT) method to perform image conversion on the acquired user sensitive information to obtain a first image coefficient matrix corresponding to the user sensitive information.

[0060] Discrete wavelet transform is a signal processing technology that decomposes a signal into sub-signals of different frequencies by convolving it with a specific wavelet function. The specific process of discrete wavelet transform may include the following steps:

[0061] (1) Select a wavelet function that is suitable for the signal characteristics, such as the Haar wavelet or the Daubechies wavelet (the Daubechies wavelet is orthogonal, continuous, and compactly supported).

[0062] (2) Decompose the original signal into approximate signals and detail signals at different levels, where the approximate signals represent the low-frequency part of the signal and the detail signals represent the high-frequency part of the signal.

[0063] (3) Filter the signals at each level (approximate signal and detail signal) to extract the information within the frequency range and downsample to reduce the amount of data.

[0064] (4) Reconstruct the decomposed signal into the original signal or approximate the original signal through inverse transformation.

[0065] S202: Perform scrambling and compression processing on the first image coefficient matrix to obtain a processed first image coefficient matrix.

[0066] In an optional embodiment, the computer device scrambles and compresses the first image coefficient matrix to obtain a processed first image coefficient matrix, which may include: scrambling the first image coefficient matrix to obtain a scrambled first image coefficient matrix; and compressing the scrambled first image coefficient matrix to obtain a processed first image coefficient matrix. In this way, by scrambling the first image coefficient matrix, the computer device can disrupt the structure of the first image coefficient matrix, making user sensitive information more difficult to identify and attack, thereby improving the security of subsequent transmission of user sensitive information; compressing the scrambled first image coefficient matrix can reduce the amount of data and improve the efficiency of subsequent data transmission, while retaining key information in the user sensitive information for subsequent covert transmission and embedding operations.

[0067] S203 . Compress the user sensitive information in the processed first image coefficient matrix to obtain compressed user sensitive information, and encrypt the compressed user sensitive information to obtain ciphertext information corresponding to the user sensitive information.

[0068] In an optional embodiment, the computer device can use Parallel Compressive Sensing (PCS) technology to compress the user-sensitive information in the processed first image coefficient matrix to obtain compressed user-sensitive information. This can reduce data transmission overhead while preserving key features of the data.

[0069] PCS is an advanced signal processing technology used to process sparse signals. The following is a detailed introduction to PCS technology.

[0070] (1) Sparse signal sampling and reconstruction: PCS technology achieves data compression and reconstruction during the signal sampling process by utilizing the sparseness of the signal. This simultaneous sampling and reconstruction capability gives PCS technology significant advantages in data transmission and storage.

[0071] (2) Parallel processing advantage: PCS technology uses a parallel processing strategy to split the input signal into multiple sub-signals and simultaneously perform independent sampling and reconstruction processing on these sub-signals. Through parallel processing, PCS technology can not only improve processing efficiency, but also effectively reduce the system's computational complexity and power consumption, thereby achieving more efficient utilization of system resources.

[0072] (3) Adaptive compression rate control: PCS technology has adaptive compression rate control capabilities, which means that it automatically adjusts the compression rate to achieve the best performance and efficiency balance based on the characteristics of the signal and the requirements of the application scenario. This adaptability enables PCS technology to achieve good compression results in different application scenarios and can adapt to dynamic changes in the signal.

[0073] (4) Data integrity and reliability: Although PCS technology achieves a high compression ratio while compressing data, it can still maintain data integrity and reliability. During data transmission and storage, PCS technology can effectively handle data loss and corruption, thereby ensuring data integrity and reliability.

[0074] S204: Embed the ciphertext information into the second image coefficient matrix corresponding to the carrier image to obtain the target image coefficient matrix.

[0075] Optionally, the carrier image can be any image, such as a natural scene, a standard photograph, or other unrelated image. These images serve as carriers for covert transmission, embedding encrypted user sensitive information for covert communication. The purpose of selecting ordinary images is to ensure that the embedded user sensitive information is visually imperceptible, thereby achieving a camouflaged effect during transmission.

[0076] S205 . Perform an inverse transformation on the target image coefficient matrix to obtain a target image including the user sensitive information, and transmit the target image.

[0077] In an embodiment of the present application, a computer device may perform image conversion on the acquired user sensitive information to obtain a first image coefficient matrix corresponding to the user sensitive information; perform scrambling and compression processing on the first image coefficient matrix to obtain a processed first image coefficient matrix; perform compression processing on the user sensitive information in the processed first image coefficient matrix to obtain compressed user sensitive information, and encrypt the compressed user sensitive information to obtain ciphertext information corresponding to the user sensitive information; embed the ciphertext information into a second image coefficient matrix corresponding to the carrier image to obtain a target image coefficient matrix; perform an inverse transformation on the target image coefficient matrix to obtain a target image including the user sensitive information, and transmit the target image. Using this method, a computer device may embed the ciphertext information corresponding to the user sensitive information into the second image coefficient matrix corresponding to the carrier image, and then perform an inverse transformation on the target image coefficient matrix to obtain a target image including the user sensitive information, and transmit the target image, thereby improving the integrity and security of the transmission of the user sensitive information.

[0078] See Figure 3 , Figure 3This is a flow chart of another method for concealed transmission of user sensitive information provided by an embodiment of the present application. Figure 2 Compared with the hidden transmission method of user sensitive information shown in Figure 3 The method shown specifically describes how the computer device performs image conversion on the acquired user sensitive information to obtain the first image coefficient matrix corresponding to the user sensitive information, and how to perform scrambling and compression processing on the first image coefficient matrix to obtain the processed first image coefficient matrix. Figure 3 As shown, the method for covertly transmitting user sensitive information may include but is not limited to the following steps:

[0079] S301 : Decompose the acquired user sensitive information based on a target discrete wavelet transform function to obtain a low-frequency signal and a high-frequency signal corresponding to the user sensitive information.

[0080] Optionally, the target discrete wavelet transform function may be a Haar wavelet or a Daubechies wavelet, which is not limited here.

[0081] S302 : Filter and downsample the low-frequency signal and the high-frequency signal respectively to obtain low-frequency sensitive information and high-frequency sensitive information.

[0082] In an optional embodiment, the computer device may filter the low-frequency signal using a low-pass filter and filter the high-frequency signal using a high-pass filter, thereby removing noise and unnecessary frequency components from the signal.

[0083] Among them, downsampling the low-frequency and high-frequency signals can reduce the amount of data and improve computing efficiency.

[0084] S303 : Reconstruct the low-frequency sensitive information and the high-frequency sensitive information through inverse transformation to obtain a first image coefficient matrix corresponding to the user sensitive information.

[0085] Among them, the inverse transformation process is the inverse process of the decomposition operation. By combining low-frequency sensitive information and high-frequency sensitive information, an approximate reconstruction of the original user sensitive information is obtained.

[0086] S304 , using a dynamic Josephus algorithm to perform scrambling processing on the first image coefficient matrix to obtain a scrambled first image coefficient matrix.

[0087] The dynamic Josephus algorithm is a mathematical algorithm for scrambling data. Its core concept is derived from the Josephus problem. In the Josephus problem, n people sit in a circle. Starting with the first person, one person is counted and removed at fixed intervals g, and then counting starts again with the next person until only one person remains. The dynamic Josephus algorithm generalizes this concept to scrambling elements in matrices or arrays, increasing the randomness and obfuscation of data, thereby improving data security and confidentiality. The following describes the dynamic Josephus algorithm.

[0088] (1) Algorithm principle: The dynamic Josephus algorithm implements the scrambling operation on matrix or array elements by dynamically determining the interval g of each round. In each round of traversal, starting from a specified starting position, a certain number of elements are skipped in sequence according to the predetermined interval g, and the element at the current position is moved to a new position. The determination of this new position usually depends on a random number generator or other parameters related to the input data.

[0089] (2) Randomization enhances security: To increase the randomness of the scrambling operation, the dynamic Josephus algorithm usually uses a random number generator to dynamically determine the interval g of each round. This can prevent attackers from analyzing the fixed rules of the algorithm to reversely deduce the order of data before scrambling, thereby improving data security and confidentiality.

[0090] (3) Obfuscating data relationships: The dynamic Josephus algorithm continuously rearranges the order of data elements, blurring and obfuscating the relationships between the original data. This obfuscation operation can effectively prevent attackers from obtaining sensitive information by analyzing the correlation between data, thereby enhancing the confidentiality and privacy of data.

[0091] (4) Reversibility and reverse operation: Although the dynamic Josephus algorithm scrambles the data, the scrambling operation is reversible. This means that the scrambled data can be restored to its original state through the corresponding reverse operation. In the application scenario of this patent, the reverse operation usually requires a specific decryption key or parameters to ensure that only authorized users can decrypt and restore the data.

[0092] The following combination Figure 4 , introduce the dynamic Josephus algorithm, Figure 4 It is a process diagram of a dynamic Josephus algorithm.

[0093] First, determine the initialization parameters and variables required for the scrambling operation, including the matrix size, initial position pointer, and scrambling interval. These parameters are determined based on the specific application requirements and data characteristics to ensure the effectiveness and security of the scrambling operation. Next, initialize the matrix, including determining the initial position pointer, current position pointer, and other parameters. Typically, you start at a fixed position in the matrix, such as the top left or bottom right corner.

[0094] The matrix is ​​then scrambled using a cyclic scrambling operation. In each scrambling round, the element at a fixed distance from the current position is found and moved to a new position based on the current position pointer. The move operation can be performed by swapping elements to ensure that each element is rearranged to its new position.

[0095] Afterwards, the current position pointer is updated so that the next round of scrambling operation can proceed smoothly. The scrambling operation is repeated and a check is made to see whether the termination condition is met. If the termination condition is met, the scrambling is determined to be complete. The termination condition may be, for example, that all elements are scrambled.

[0096] Ultimately, the resulting scrambled image coefficient matrix is ​​obtained. The order of the elements in this matrix has been rearranged, creating a chaotic state that increases the randomness and unpredictability of the data. This chaotic state makes it difficult to recover the structure and features of the original image, thereby increasing data security.

[0097] S305 , using a partial Hadamard matrix, compressing the first image coefficient matrix after scrambling to obtain a processed first image coefficient matrix.

[0098] The Hadamard matrix is ​​an orthogonal square matrix consisting of +1 and -1 elements.

[0099] S306 . Compress the user sensitive information in the processed first image coefficient matrix to obtain compressed user sensitive information, and encrypt the compressed user sensitive information to obtain ciphertext information corresponding to the user sensitive information.

[0100] In an optional implementation, the relevant description of step S306 can be found in the description of the aforementioned step S203, which will not be repeated here.

[0101] S307 : Embed the ciphertext information into the second image coefficient matrix corresponding to the carrier image to obtain the target image coefficient matrix.

[0102] In an optional embodiment, the computer device embeds the ciphertext information into the second image coefficient matrix corresponding to the carrier image to obtain the target image coefficient matrix, which may include: selecting, from the second image coefficient matrix corresponding to the carrier image, an element position whose pixel value is less than a preset pixel threshold or whose image texture richness is greater than a preset richness threshold as a target embedding position; and embedding the ciphertext information into the target embedding position in the second image coefficient matrix to obtain the target image coefficient matrix.

[0103] In this embodiment, the computer device embeds the ciphertext information into the target embedding position in the second image coefficient matrix to obtain the target image coefficient matrix, which may include: using a preset verification mechanism to verify the ciphertext information to obtain verified ciphertext information; embedding the verified ciphertext information into the target embedding position in the second image coefficient matrix to obtain the target image coefficient matrix.

[0104] S308 . Perform an inverse transformation on the target image coefficient matrix to obtain a target image including the user sensitive information, and transmit the target image.

[0105] In an embodiment of the present application, the computer device can decompose the acquired user sensitive information based on the target discrete wavelet transform function to obtain a low-frequency signal and a high-frequency signal corresponding to the user sensitive information; filter and downsample the low-frequency signal and the high-frequency signal respectively to obtain low-frequency sensitive information and high-frequency sensitive information; reconstruct the low-frequency sensitive information and the high-frequency sensitive information through inverse transformation to obtain a first image coefficient matrix corresponding to the user sensitive information. In this way, by converting the user sensitive information into an image coefficient matrix, the efficiency and security of subsequent processing can be improved. Secondly, the dynamic Josephus algorithm is used to scramble the first image coefficient matrix to obtain the scrambled first image coefficient matrix, and the partial Hadamard matrix is ​​used to compress the scrambled first image coefficient matrix to obtain the processed first image coefficient matrix, which can further improve the security of the first image coefficient matrix. Therefore, the user sensitive information in the processed first image coefficient matrix is ​​compressed and encrypted, which can further improve the security and processing efficiency of the user sensitive information; then, the ciphertext information is embedded in the second image coefficient matrix corresponding to the carrier image to obtain the target image coefficient matrix; the target image coefficient matrix is ​​inversely transformed to obtain the target image including the user sensitive information, and when the target image is transmitted, the integrity and security of the user sensitive information transmission can be improved, and the efficiency of the user sensitive information transmission can be improved.

[0106] See Figure 5 , Figure 5 This is another flow chart of a method for concealed transmission of user sensitive information provided by an embodiment of the present application. Figure 3 Compared with the hidden transmission method of user sensitive information shown in Figure 5 The method shown specifically describes how the computer device compresses the user sensitive information in the processed first image coefficient matrix to obtain compressed user sensitive information, and encrypts the compressed user sensitive information to obtain ciphertext information corresponding to the user sensitive information. Figure 5 As shown, the method for covertly transmitting user sensitive information may include but is not limited to the following steps:

[0107] S501 : Decompose the acquired user sensitive information based on a target discrete wavelet transform function to obtain a low-frequency signal and a high-frequency signal corresponding to the user sensitive information.

[0108] S502 : Filter and downsample the low-frequency signal and the high-frequency signal respectively to obtain low-frequency sensitive information and high-frequency sensitive information.

[0109] S503 : Reconstruct the low-frequency sensitive information and the high-frequency sensitive information through inverse transformation to obtain a first image coefficient matrix corresponding to the user sensitive information.

[0110] S504: Using a dynamic Josephus algorithm, perform scrambling processing on the first image coefficient matrix to obtain a scrambled first image coefficient matrix.

[0111] S505 , using a partial Hadamard matrix, compressing the first image coefficient matrix after scrambling to obtain a processed first image coefficient matrix.

[0112] In an optional implementation, the relevant descriptions of steps S501 to S505 can be found in the descriptions of the aforementioned steps S301 to S305, and will not be repeated here.

[0113] S506: Divide the user sensitive information in the processed first image coefficient matrix into multiple sub-information, and compress the multiple sub-information to obtain compressed sub-information. This can improve processing efficiency and reduce computational complexity and power consumption.

[0114] Optionally, when the computer device compresses the multiple sub-information separately to obtain the compressed sub-information, it can utilize the sparsity of the signal and employ a compressed sensing algorithm to sparsely represent the signal, thereby achieving efficient signal compression. Optionally, commonly used compressed sensing algorithms include sparse representation-based methods, such as sparse representation-based reconstruction algorithms (e.g., the Orthogonal Matching Pursuit (OMP) algorithm and the Back Propagation (BP) algorithm).

[0115] S507: Determine compressed user sensitive information based on the compressed sub-information.

[0116] Since the data volume is greatly reduced after compression, it can be transmitted and stored efficiently over the network or on storage media. In the subsequent transmission process, it can be transmitted in the form of data packets so that the receiving end can receive and decompress the data more efficiently.

[0117] S508: Encrypt the compressed user sensitive information to obtain ciphertext information corresponding to the user sensitive information.

[0118] S509: Embed the ciphertext information into the second image coefficient matrix corresponding to the carrier image to obtain the target image coefficient matrix.

[0119] In an optional implementation, the relevant description of step S509 can be found in the description of the aforementioned step S407, which will not be repeated here.

[0120] Steps S508 and S509 can be implemented by a computer device using a reversible matrix coding embedding method. Reversible matrix coding embedding is a key method for covert transmission and verification. In this application, this method allows encrypted user information to be embedded in specific locations or features of an image in a covert and imperceptible manner, thereby achieving the effect of transmitting an ordinary image to the user, while actually embedding the user's sensitive information.

[0121] Among them, reversible matrix coding embedding can include the following key steps:

[0122] (1) Encryption: First, the user's sensitive information will be strictly encrypted to ensure the security and confidentiality of the data. Common encryption algorithms include Advanced Encryption Standard (AES) and asymmetric encryption algorithms. These algorithms can effectively protect the user's private data from unauthorized access and theft.

[0123] (2) Embedding process: The encrypted user information is embedded in a plain image in a covert manner. During the embedding process, locations or features that are difficult to detect in the image are usually selected, such as areas with small pixel values ​​or areas with rich image textures. Using matrix coding technology, the encrypted user information is embedded in these locations or features, leaving the visual effect of the plain image largely unaffected while achieving covert transmission of the user information.

[0124] (3) Verification mechanism: In order to ensure the integrity and correctness of the embedded ciphertext information, an effective verification mechanism is designed. These verification mechanisms usually include technologies such as redundant information, checksums, and error detection codes, which can detect and correct possible errors or tampering, thereby improving the reliability and security of data transmission.

[0125] Optionally, a specific implementation method of the verification mechanism may include redundant information embedding, checksum, error checking code, error correction code, etc.

[0126] S510 , performing an inverse transformation on the target image coefficient matrix to obtain a target image including user sensitive information, and transmitting the target image.

[0127] In an embodiment of the present application, a computer device can divide user sensitive information into multiple sub-information; compress each of the multiple sub-information to obtain compressed sub-information; determine compressed user sensitive information based on the compressed sub-information; and encrypt the compressed user sensitive information to obtain ciphertext information corresponding to the user sensitive information. This can further improve the security of user sensitive information, thereby facilitating the subsequent improvement of the integrity and security of the transmission of user sensitive information.

[0128] In an optional embodiment, before steps S202, S304, and S504, the computer device may also calculate the characteristics and hash value of the carrier image (or the user-uploaded image) to generate the initial state required for the encryption and decryption process. This can enhance the security and reliability of the subsequent covert transmission of user sensitive information, ensuring that user sensitive information is fully protected during transmission.

[0129] In this embodiment, the computer device may first extract feature information from the carrier image, such as the carrier image's size, pixel distribution, color channels, etc. These features can reflect the basic properties of the image and provide an important data basis for subsequent steps.

[0130] The extracted feature information is then hashed to obtain the hash value corresponding to the carrier image. A hash value is a fixed-length string of data calculated based on the image content. It is unique and irreversible, effectively representing the image's content characteristics and ensuring its uniqueness and integrity.

[0131] Then, combining the encryption algorithm for user sensitive information and the requirements of the covert transmission system, the control parameters and initialization vectors required for the encryption process are generated. These parameters and initialization vectors can affect the encryption effect and security of the encryption algorithm, so they need to be reasonably selected and generated according to actual needs.

[0132] Finally, the initial states required for encryption and decryption are generated based on the encryption parameters (along with control parameters and initialization vectors) and the hash value corresponding to the carrier image. These initial states, including keys and random number seeds, can influence the trajectory and results of the encryption and decryption processes, playing a vital role in the security and reliability of the system.

[0133] This implementation, by calculating the carrier image's features and hash values ​​to generate the initial states required for encryption and decryption, can enhance system security and reliability. This not only provides the necessary prerequisites and guarantees for the system's normal operation, but also plays a significant role in protecting user privacy and data security.

[0134] In an optional embodiment, this application also proposes a one-dimensional modified cosine chaotic map (denoted as 1-DICCM) with a control parameter μ > 0. Computer equipment can evaluate its chaotic properties to ensure its suitability for covert transmission systems. A chaotic map is a nonlinear dynamical system characterized by high randomness, complexity, and sensitivity to initial conditions. In this application, the design of the 1-DICCM has the following features:

[0135] (1) Improved design based on cosine function: 1-DICCM uses the cosine function as its basis, but improves it to enhance the chaotic performance. The improved cosine function may include nonlinear terms, periodic changes, or other forms of enhancement.

[0136] (2) Introduction of control parameter μ: The behavior of chaotic mapping is usually controlled by one or more parameters. In 1-DICCM, a control parameter μ is introduced to adjust the dynamic behavior of chaotic mapping, thereby affecting the properties of the generated chaotic sequence.

[0137] (3) Chaotic performance evaluation: The performance of the chaotic mapping is evaluated using a variety of metrics, such as Lyapunov exponent, sensitivity analysis, and Shannon entropy. In this application, these evaluation metrics can be used to verify the chaotic properties of the 1-DICCM to ensure its suitability for covert transmission of user sensitive information.

[0138] (4) No periodic window: 1-DICCM does not have a periodic window in its chaotic distribution. This means that the chaotic sequence generated by 1-DICCM has greater randomness and irregularity, making it more suitable for the encryption and decryption operations in the user information covert transmission method provided in this application.

[0139] In summary, 1-DICCM, as an improved cosine chaotic mapping, has special advantages in its design and selection of control parameters. It can generate sequences with good chaotic characteristics, thus providing a reliable basis for the covert transmission method of user sensitive information provided in this application.

[0140] In an optional embodiment, the computer device transmitting the target image may be transmitting the target image to an application; thereafter, the computer device may receive the target image through the application and decrypt the received target image to obtain the user's sensitive information.

[0141] Optional, see Figure 6 , Figure 6 This is a flowchart of a decryption process provided by an embodiment of the present application. Figure 6 As shown, the decryption process may include the following steps:

[0142] (1) Ciphertext information extraction: First, the embedded ciphertext information is extracted from the received target image.

[0143] (2) Inverse matrix encoding: Perform inverse matrix encoding on the extracted ciphertext information to obtain the user sensitive information before encryption.

[0144] (3) Inverse compressed sensing: The user sensitive information before encryption restored by inverse matrix coding is inversely compressed to obtain the user sensitive information before compression.

[0145] (4) Inverse dynamic Josephus scrambling: Perform inverse dynamic Josephus scrambling operation on the user sensitive information before compression restored by inverse compression processing to obtain the original data sequence.

[0146] (5) Finally restore the original data: After the above steps, the original user sensitive information can be obtained.

[0147] With this implementation, during the decryption process, the computer device can execute the operations taken during the encryption process in the reverse order, thereby ensuring that the original user sensitive information is completely restored.

[0148] It should be understood that, although the various steps in the flowcharts involved in the various embodiments described above are displayed in sequence according to the instructions of the arrows, these steps are not necessarily executed in sequence in the order indicated by the arrows. Unless otherwise specified herein, there is no strict order restriction on the execution of these steps, and these steps can be executed in other orders. Moreover, at least a portion of the steps in the flowcharts involved in the various embodiments described above can include multiple steps or multiple stages, and these steps or stages are not necessarily executed and completed at the same time, but can be executed at different times, and the execution order of these steps or stages is not necessarily to be carried out in sequence, but can be executed in turn or alternately with other steps or at least a portion of steps or stages in other steps.

[0149] Based on the same inventive concept, embodiments of the present application also provide a device for covertly transmitting user sensitive information for implementing the aforementioned method for covertly transmitting user sensitive information. The solution provided by this device is similar to the solution described in the aforementioned method. Therefore, the specific limitations in one or more embodiments of the device for covertly transmitting user sensitive information provided below can be found in the limitations of the method for covertly transmitting user sensitive information above and will not be repeated here.

[0150] See Figure 7 , Figure 7 This is a schematic diagram of the structure of a device for concealed transmission of user sensitive information provided by an embodiment of the present application. Figure 7 As shown, the user sensitive information covert transmission device may include but is not limited to:

[0151] The image conversion unit 701 is configured to perform image conversion on the acquired user sensitive information to obtain a first image coefficient matrix corresponding to the user sensitive information;

[0152] The processing unit 702 is configured to perform scrambling and compression processing on the first image coefficient matrix to obtain a processed first image coefficient matrix;

[0153] The processing unit 702 is further configured to compress the user sensitive information in the processed first image coefficient matrix to obtain compressed user sensitive information, and encrypt the compressed user sensitive information to obtain ciphertext information corresponding to the user sensitive information.

[0154] The embedding unit 703 is used to embed the ciphertext information into the second image coefficient matrix corresponding to the carrier image to obtain the target image coefficient matrix;

[0155] The processing and transmission unit 704 is further configured to perform inverse transformation processing on the target image coefficient matrix to obtain the target image including the user sensitive information, and transmit the target image.

[0156] In one embodiment, when the image conversion unit 701 is used to perform image conversion on the acquired user sensitive information and obtain a first image coefficient matrix corresponding to the user sensitive information, it is specifically used to: decompose the acquired user sensitive information based on a target discrete wavelet transform function to obtain a low-frequency signal and a high-frequency signal corresponding to the user sensitive information; filter and downsample the low-frequency signal and the high-frequency signal respectively to obtain low-frequency sensitive information and high-frequency sensitive information; reconstruct the low-frequency sensitive information and the high-frequency sensitive information through an inverse transform to obtain a first image coefficient matrix corresponding to the user sensitive information.

[0157] In one embodiment, when the processing module 702 is used to scramble and compress the first image coefficient matrix to obtain the processed image coefficient matrix, it is specifically used to: use the dynamic Josephus algorithm to scramble the first image coefficient matrix to obtain the scrambled first image coefficient matrix; use the partial Hadamard matrix to compress the scrambled first image coefficient matrix to obtain the processed first image coefficient matrix.

[0158] In one embodiment, when the processing module 702 is used to compress the user sensitive information in the processed first image coefficient matrix to obtain compressed user sensitive information, it is specifically used to: divide the user sensitive information in the processed first image coefficient matrix into multiple sub-information; compress the multiple sub-information respectively to obtain multiple compressed sub-information; and determine the compressed user sensitive information based on the multiple compressed sub-information.

[0159] In one embodiment, when the embedding unit 703 is used to embed the ciphertext information into the second image coefficient matrix corresponding to the carrier image to obtain the target image coefficient matrix, it is specifically used to: select, from the second image coefficient matrix corresponding to the carrier image, the element position whose pixel value is less than a preset pixel threshold or the image texture richness is greater than a preset richness threshold as the target embedding position; embed the ciphertext information into the target embedding position in the second image coefficient matrix to obtain the target image coefficient matrix.

[0160] In one embodiment, when the embedding unit 703 is used to embed the ciphertext information into the target embedding position in the second image coefficient matrix to obtain the target image coefficient matrix, it is specifically used to: use a preset verification mechanism to verify the ciphertext information to obtain the verified ciphertext information; embed the verified ciphertext information into the target embedding position in the second image coefficient matrix to obtain the target image coefficient matrix.

[0161] Each module in the above-mentioned device for covertly transmitting user sensitive information can be implemented in whole or in part through software, hardware, or a combination thereof. Each module can be embedded in or independent of the processor in the terminal device in hardware form, or can be stored in the memory of the terminal device in software form, so that the processor can call and execute the corresponding operations of each module.

[0162] In an exemplary embodiment, the present application provides a computer device, which may be a terminal, and its internal structure diagram may be as follows: Figure 8 As shown. The computer device includes a processor, a memory, an input / output interface, a communication interface, a display unit and an input device. The processor, the memory and the input / output interface are connected via a system bus, and the communication interface, the display unit and the input device are connected to the system bus via the input / output interface. The processor of the computer device is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system and a computer program. The internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The input / output interface of the computer device is used to exchange information between the processor and an external device. The communication interface of the computer device is used to communicate with an external terminal in a wired or wireless manner. The wireless manner can be achieved through WIFI, a mobile cellular network, near field communication (NFC) or other technologies. When the computer program is executed by the processor, a method for concealed transmission of user sensitive information is implemented.

[0163] Those skilled in the art will understand that Figure 8 The structure shown in the figure is only a block diagram of a part of the structure related to the solution of the present application, and does not constitute a limitation on the computer device to which the solution of the present application is applied. The specific computer device may include more or fewer components than shown in the figure, or combine certain components, or have a different component arrangement.

[0164] In an exemplary embodiment, the present application provides a computer device including a memory and a processor, wherein a computer program is stored in the memory, and when the processor executes the computer program, the following steps are implemented:

[0165] Performing image conversion on the acquired user sensitive information to obtain a first image coefficient matrix corresponding to the user sensitive information;

[0166] Performing scrambling and compression processing on the first image coefficient matrix to obtain a processed first image coefficient matrix;

[0167] Compressing the user sensitive information in the processed first image coefficient matrix to obtain compressed user sensitive information, and encrypting the compressed user sensitive information to obtain ciphertext information corresponding to the user sensitive information;

[0168] Embed the ciphertext information into the second image coefficient matrix corresponding to the carrier image to obtain the target image coefficient matrix;

[0169] Perform an inverse transformation on the target image coefficient matrix to obtain a target image including user sensitive information, and transmit the target image.

[0170] In one embodiment, when a processor executes a computer program to perform image conversion on the acquired user sensitive information and obtains a first image coefficient matrix corresponding to the user sensitive information, the following steps are specifically implemented: based on a target discrete wavelet transform function, the acquired user sensitive information is decomposed to obtain a low-frequency signal and a high-frequency signal corresponding to the user sensitive information; the low-frequency signal and the high-frequency signal are filtered and down-sampled respectively to obtain low-frequency sensitive information and high-frequency sensitive information; and the low-frequency sensitive information and the high-frequency sensitive information are reconstructed through an inverse transform to obtain a first image coefficient matrix corresponding to the user sensitive information.

[0171] In one embodiment, the processor executes a computer program to implement scrambling and compression processing on the first image coefficient matrix. When obtaining the processed image coefficient matrix, the following steps are specifically implemented: using a dynamic Josephus algorithm to scramble the first image coefficient matrix to obtain the scrambled first image coefficient matrix; using a partial Hadamard matrix to compress the scrambled first image coefficient matrix to obtain the processed first image coefficient matrix.

[0172] In one embodiment, the processor executes a computer program to compress the user sensitive information in the processed first image coefficient matrix. When the compressed user sensitive information is obtained, the following steps are specifically implemented: dividing the user sensitive information in the processed first image coefficient matrix into multiple sub-information; compressing the multiple sub-information separately to obtain multiple compressed sub-information; and determining the compressed user sensitive information based on the multiple compressed sub-information.

[0173] In one embodiment, the processor executes a computer program to embed the ciphertext information into the second image coefficient matrix corresponding to the carrier image. When obtaining the target image coefficient matrix, the following steps are specifically implemented: from the second image coefficient matrix corresponding to the carrier image, the element position whose pixel value is less than a preset pixel threshold or the image texture richness is greater than a preset richness threshold is selected as the target embedding position; the ciphertext information is embedded into the target embedding position in the second image coefficient matrix to obtain the target image coefficient matrix.

[0174] In one embodiment, the processor executes a computer program to embed the ciphertext information into the target embedding position in the second image coefficient matrix. When obtaining the target image coefficient matrix, the following steps are specifically implemented: using a preset verification mechanism to verify the ciphertext information to obtain verified ciphertext information; embedding the verified ciphertext information into the target embedding position in the second image coefficient matrix to obtain the target image coefficient matrix.

[0175] In an exemplary embodiment, the present application provides a computer-readable storage medium having a computer program stored thereon. When the computer program is executed by a processor, the following steps are implemented:

[0176] Performing image conversion on the acquired user sensitive information to obtain a first image coefficient matrix corresponding to the user sensitive information;

[0177] Performing scrambling and compression processing on the first image coefficient matrix to obtain a processed first image coefficient matrix;

[0178] Compressing the user sensitive information in the processed first image coefficient matrix to obtain compressed user sensitive information, and encrypting the compressed user sensitive information to obtain ciphertext information corresponding to the user sensitive information;

[0179] Embed the ciphertext information into the second image coefficient matrix corresponding to the carrier image to obtain the target image coefficient matrix;

[0180] Perform an inverse transformation on the target image coefficient matrix to obtain a target image including user sensitive information, and transmit the target image.

[0181] In one embodiment, when a computer program is executed by a processor to perform image conversion on the acquired user sensitive information and obtain a first image coefficient matrix corresponding to the user sensitive information, the following steps are specifically implemented: based on a target discrete wavelet transform function, the acquired user sensitive information is decomposed to obtain a low-frequency signal and a high-frequency signal corresponding to the user sensitive information; the low-frequency signal and the high-frequency signal are filtered and down-sampled respectively to obtain low-frequency sensitive information and high-frequency sensitive information; and the low-frequency sensitive information and the high-frequency sensitive information are reconstructed through an inverse transform to obtain a first image coefficient matrix corresponding to the user sensitive information.

[0182] In one embodiment, a computer program is executed by a processor to implement scrambling and compression processing on a first image coefficient matrix. When obtaining a processed image coefficient matrix, the following steps are specifically implemented: using a dynamic Josephus algorithm to perform scrambling processing on the first image coefficient matrix to obtain a scrambled first image coefficient matrix; using a partial Hadamard matrix to perform compression processing on the scrambled first image coefficient matrix to obtain a processed first image coefficient matrix.

[0183] In one embodiment, a computer program is executed by a processor to compress the user sensitive information in the processed first image coefficient matrix. When the compressed user sensitive information is obtained, the following steps are specifically implemented: dividing the user sensitive information in the processed first image coefficient matrix into multiple sub-information; compressing the multiple sub-information separately to obtain multiple compressed sub-information; and determining the compressed user sensitive information based on the multiple compressed sub-information.

[0184] In one embodiment, a computer program is executed by a processor to embed ciphertext information into a second image coefficient matrix corresponding to a carrier image. When obtaining a target image coefficient matrix, the following steps are specifically implemented: from the second image coefficient matrix corresponding to the carrier image, an element position whose pixel value is less than a preset pixel threshold or whose image texture richness is greater than a preset richness threshold is selected as a target embedding position; and the ciphertext information is embedded into the target embedding position in the second image coefficient matrix to obtain a target image coefficient matrix.

[0185] In one embodiment, a computer program is executed by a processor to embed ciphertext information into a target embedding position in a second image coefficient matrix. When obtaining a target image coefficient matrix, the following steps are specifically implemented: using a preset verification mechanism, the ciphertext information is verified to obtain verified ciphertext information; and the verified ciphertext information is embedded into a target embedding position in the second image coefficient matrix to obtain a target image coefficient matrix.

[0186] In an exemplary embodiment, the present application provides a computer program product, including a computer program, which, when executed by a processor, implements the following steps:

[0187] Performing image conversion on the acquired user sensitive information to obtain a first image coefficient matrix corresponding to the user sensitive information;

[0188] Performing scrambling and compression processing on the first image coefficient matrix to obtain a processed first image coefficient matrix;

[0189] Compressing the user sensitive information in the processed first image coefficient matrix to obtain compressed user sensitive information, and encrypting the compressed user sensitive information to obtain ciphertext information corresponding to the user sensitive information;

[0190] Embed the ciphertext information into the second image coefficient matrix corresponding to the carrier image to obtain the target image coefficient matrix;

[0191] Perform an inverse transformation on the target image coefficient matrix to obtain a target image including user sensitive information, and transmit the target image.

[0192] In one embodiment, when a computer program is executed by a processor to perform image conversion on the acquired user sensitive information and obtain a first image coefficient matrix corresponding to the user sensitive information, the following steps are specifically implemented: based on a target discrete wavelet transform function, the acquired user sensitive information is decomposed to obtain a low-frequency signal and a high-frequency signal corresponding to the user sensitive information; the low-frequency signal and the high-frequency signal are filtered and down-sampled respectively to obtain low-frequency sensitive information and high-frequency sensitive information; and the low-frequency sensitive information and the high-frequency sensitive information are reconstructed through an inverse transform to obtain a first image coefficient matrix corresponding to the user sensitive information.

[0193] In one embodiment, a computer program is executed by a processor to implement scrambling and compression processing on a first image coefficient matrix. When obtaining a processed image coefficient matrix, the following steps are specifically implemented: using a dynamic Josephus algorithm to perform scrambling processing on the first image coefficient matrix to obtain a scrambled first image coefficient matrix; using a partial Hadamard matrix to perform compression processing on the scrambled first image coefficient matrix to obtain a processed first image coefficient matrix.

[0194] In one embodiment, a computer program is executed by a processor to compress the user sensitive information in the processed first image coefficient matrix. When the compressed user sensitive information is obtained, the following steps are specifically implemented: dividing the user sensitive information in the processed first image coefficient matrix into multiple sub-information; compressing the multiple sub-information separately to obtain multiple compressed sub-information; and determining the compressed user sensitive information based on the multiple compressed sub-information.

[0195] In one embodiment, a computer program is executed by a processor to embed ciphertext information into a second image coefficient matrix corresponding to a carrier image. When obtaining a target image coefficient matrix, the following steps are specifically implemented: from the second image coefficient matrix corresponding to the carrier image, an element position whose pixel value is less than a preset pixel threshold or whose image texture richness is greater than a preset richness threshold is selected as a target embedding position; and the ciphertext information is embedded into the target embedding position in the second image coefficient matrix to obtain a target image coefficient matrix.

[0196] In one embodiment, a computer program is executed by a processor to embed ciphertext information into a target embedding position in a second image coefficient matrix. When obtaining a target image coefficient matrix, the following steps are specifically implemented: using a preset verification mechanism, the ciphertext information is verified to obtain verified ciphertext information; and the verified ciphertext information is embedded into a target embedding position in the second image coefficient matrix to obtain a target image coefficient matrix.

[0197] It should be noted that the data involved in this application (including but not limited to user sensitive information, etc.) are all information and data authorized by the user or fully authorized by all parties, and the collection, use and processing of relevant data must comply with relevant regulations.

[0198] Those skilled in the art will understand that all or part of the processes in the above-mentioned embodiments can be implemented by instructing the relevant hardware through a computer program. The computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the embodiments of the above-mentioned methods. In particular, any reference to memory, database, or other media used in the embodiments provided in this application can include at least one of non-volatile memory and volatile memory. Non-volatile memory can include read-only memory (ROM), magnetic tape, floppy disk, flash memory, optical memory, high-density embedded non-volatile memory, resistive random access memory (ReRAM), magnetic random access memory (MRAM), ferroelectric random access memory (FRAM), phase change memory (PCM), graphene memory, etc. Volatile memory can include random access memory (RAM) or external cache memory, etc. By way of illustration and not limitation, RAM can take various forms, such as static random access memory (SRAM) or dynamic random access memory (DRAM). The databases involved in the various embodiments provided herein may include at least one of a relational database and a non-relational database. Non-relational databases may include, but are not limited to, blockchain-based distributed databases. The processors involved in the various embodiments provided herein may be, but are not limited to, general-purpose processors, central processing units (CPUs), graphics processing units (GPUs), digital signal processors (DSPs), programmable logic devices (PLDs), quantum computing-based data processing logic devices, artificial intelligence (AI) processors, and the like.

[0199] The technical features of the above embodiments can be combined arbitrarily. In order to make the description concise, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this application.

[0200] The above-described embodiments merely represent several implementation methods of the present application. While the descriptions are relatively specific and detailed, they should not be construed as limiting the scope of the present application. It should be noted that a person of ordinary skill in the art may make various modifications and improvements without departing from the spirit of the present application, and these modifications and improvements fall within the scope of protection of the present application. Therefore, the scope of protection of the present application shall be determined by the appended claims.

Claims

1. A method for covertly transmitting user sensitive information, characterized in that: The method comprises: Performing image conversion on the acquired user sensitive information to obtain a first image coefficient matrix corresponding to the user sensitive information; performing scrambling and compression processing on the first image coefficient matrix to obtain a processed first image coefficient matrix; compressing the user sensitive information in the processed first image coefficient matrix to obtain compressed user sensitive information, and encrypting the compressed user sensitive information to obtain ciphertext information corresponding to the user sensitive information; Embedding the ciphertext information into the second image coefficient matrix corresponding to the carrier image to obtain the target image coefficient matrix; Performing an inverse transformation on the target image coefficient matrix to obtain a target image including the user sensitive information, and transmitting the target image; Before performing scrambling and compression processing on the first image coefficient matrix to obtain a processed first image coefficient matrix, the method further includes: Extracting feature information from the carrier image and performing a hash calculation on the feature information to obtain a hash value corresponding to the carrier image; the feature information includes the size, pixel distribution, and color channel of the carrier image; Based on the hash value and a preset user sensitive information encryption algorithm, an initial state required in the encryption process is generated; the initial state includes a key and a random number seed; the initial state is used to encrypt the compressed user sensitive information; The scrambling and compressing the first image coefficient matrix to obtain a processed first image coefficient matrix includes: Using a dynamic Josephus algorithm, scrambling the first image coefficient matrix to obtain a scrambled first image coefficient matrix; The first image coefficient matrix after the scrambling process is compressed using a partial Hadamard matrix to obtain a processed first image coefficient matrix.

2. The method according to claim 1, characterized in that The performing image conversion on the acquired user sensitive information to obtain a first image coefficient matrix corresponding to the user sensitive information includes: Decomposing the acquired user sensitive information based on a target discrete wavelet transform function to obtain a low-frequency signal and a high-frequency signal corresponding to the user sensitive information; Filtering and down-sampling the low-frequency signal and the high-frequency signal respectively to obtain low-frequency sensitive information and high-frequency sensitive information; The low-frequency sensitive information and the high-frequency sensitive information are reconstructed through inverse transformation to obtain a first image coefficient matrix corresponding to the user sensitive information.

3. The method according to claim 1, characterized in that The compressing the user sensitive information in the processed first image coefficient matrix to obtain compressed user sensitive information includes: dividing the user sensitive information in the processed first image coefficient matrix into a plurality of sub-information; performing compression processing on the plurality of sub-information respectively to obtain a plurality of compressed sub-information; Based on the compressed multiple sub-information, the compressed user sensitive information is determined.

4. The method according to claim 1, wherein The step of embedding the ciphertext information into a second image coefficient matrix corresponding to the carrier image to obtain a target image coefficient matrix includes: From the second image coefficient matrix corresponding to the carrier image, select an element position whose pixel value is less than a preset pixel threshold or whose image texture richness is greater than a preset richness threshold as a target embedding position; The ciphertext information is embedded into the target embedding position in the second image coefficient matrix to obtain a target image coefficient matrix.

5. The method according to claim 4, characterized in that The step of embedding the ciphertext information into the target embedding position in the second image coefficient matrix to obtain a target image coefficient matrix includes: Verifying the encrypted information using a preset verification mechanism to obtain verified encrypted information; The verified ciphertext information is embedded into the target embedding position in the second image coefficient matrix to obtain a target image coefficient matrix.

6. A device for concealed transmission of user sensitive information, characterized in that: The device comprises: An image conversion unit, configured to perform image conversion on the acquired user sensitive information to obtain a first image coefficient matrix corresponding to the user sensitive information; a processing unit, configured to perform scrambling and compression processing on the first image coefficient matrix to obtain a processed first image coefficient matrix; The processing unit is further configured to compress the user sensitive information in the processed first image coefficient matrix to obtain compressed user sensitive information, and encrypt the compressed user sensitive information to obtain ciphertext information corresponding to the user sensitive information; an embedding unit, configured to embed the ciphertext information into a second image coefficient matrix corresponding to the carrier image to obtain a target image coefficient matrix; The processing and transmission unit is further configured to perform an inverse transformation on the target image coefficient matrix to obtain a target image including the user sensitive information, and transmit the target image; Before performing scrambling and compression processing on the first image coefficient matrix to obtain a processed first image coefficient matrix, the processing unit is further configured to: extract feature information from a carrier image and perform a hash calculation on the feature information to obtain a hash value corresponding to the carrier image; the feature information includes the size, pixel distribution, and color channel of the carrier image; generate an initial state required for an encryption process based on the hash value and a preset user sensitive information encryption algorithm; the initial state includes a key and a random number seed; and the initial state is used to encrypt the compressed user sensitive information. When the processing unit is used to scramble and compress the first image coefficient matrix to obtain the processed first image coefficient matrix, it is specifically used to: use the dynamic Josephus algorithm to scramble the first image coefficient matrix to obtain the scrambled first image coefficient matrix; use the partial Hadamard matrix to compress the scrambled first image coefficient matrix to obtain the processed first image coefficient matrix.

7. The device according to claim 6, characterized in that When the image conversion unit is used to perform image conversion on the acquired user sensitive information to obtain a first image coefficient matrix corresponding to the user sensitive information, it is specifically used to: Based on the target discrete wavelet transform function, the acquired user sensitive information is decomposed to obtain the low-frequency signal and high-frequency signal corresponding to the user sensitive information; The low-frequency signal and the high-frequency signal are filtered and down-sampled respectively to obtain low-frequency sensitive information and high-frequency sensitive information; The low-frequency sensitive information and the high-frequency sensitive information are reconstructed through inverse transformation to obtain a first image coefficient matrix corresponding to the user sensitive information.

8. A computer device, characterized in that: The method comprises a memory and a processor, wherein the memory stores a computer program, and the processor implements the steps of the method according to any one of claims 1 to 5 when executing the computer program.

9. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 5 are implemented.

10. A computer program product comprising a computer program, characterized in that When the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 5 are implemented.

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