User sensitive information hidden transmission method and device, equipment and storage medium

Abstract

The invention relates to a user sensitive information hidden transmission method and device, equipment and a storage medium, and the method comprises the steps: carrying out the image conversion of obtained user sensitive information, and obtaining 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; performing compression processing on the user sensitive information in the processed first image coefficient matrix to obtain compressed user sensitive information, and performing encryption processing on 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 the carrier image to obtain a target image coefficient matrix; and performing inverse transformation on the target image coefficient matrix to obtain a target image including the user sensitive information, and transmitting the target image. By adopting the method, the integrity and security of user sensitive information transmission can be improved.

Description

Technical Field

[0001] The present application relates to the field of data processing, and in particular to a method, device, equipment 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 increasingly valued. In user applications (Applications, Apps), in order to ensure the concealed transmission and integrity verification of user privacy data at the same time, an efficient information hiding method is needed. Among them, covert communication technology and digital watermarking technology, as important branches in the field of information hiding, are particularly important in this context. Covert communication technology can embed data into other carriers to achieve the purpose of hiding transmitted information during the communication process. Digital watermarking technology can embed identification information into digital media to protect intellectual property rights, ensure data integrity, and track the source of information.

[0003] However, using covert communication technology may cause minor changes in the medium due to the embedded data, which may make the data integrity unreliable. Using digital watermarking technology, the embedding process of the digital watermark may cause slight distortion of the data, resulting in 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 covertly transmitting 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] The target image coefficient matrix is ​​inversely transformed to obtain a target image including user sensitive information, and the target image is transmitted.

[0012] In one of the embodiments, 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 of the embodiments, 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 of the embodiments, the ciphertext information is embedded into a second image coefficient matrix corresponding to the carrier image to obtain a 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 a target image coefficient matrix.

[0016] In one of the embodiments, the ciphertext information is embedded into a target embedding position in a 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; 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, used 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, used for performing scrambling and compression processing on the first image coefficient matrix to obtain a processed first image coefficient matrix;

[0020] The processing unit is further used 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, used for embedding 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 also 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, including a memory and a processor, wherein the memory stores a computer program, and when the processor executes the computer program, the following steps are implemented:

[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] The target image coefficient matrix is ​​inversely transformed to obtain a target image including user sensitive information, and the target image is transmitted.

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

[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] The target image coefficient matrix is ​​inversely transformed to obtain a target image including user sensitive information, and the target image is transmitted.

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

[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] The target image coefficient matrix is ​​inversely transformed to obtain a target image including user sensitive information, and the target image is transmitted.

[0041] In the above-mentioned method, device, equipment and storage medium for concealed transmission of user sensitive information, the computer device can perform image conversion on the acquired user sensitive information to obtain the first image coefficient matrix corresponding to the user sensitive information; perform scrambling and compression processing on the first image coefficient matrix to obtain the processed first image coefficient matrix; perform compression processing on the user sensitive information in the processed first image coefficient matrix to obtain the compressed user sensitive information, and encrypt the compressed user sensitive information to obtain the 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 the target image coefficient matrix; perform inverse transformation on the target image coefficient matrix to obtain the target image including the user sensitive information, and transmit the target image. Using this method, the 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 inverse transformation on the target image coefficient matrix to obtain the target image including the user sensitive information, and transmit the target image, thereby improving 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 drawings required for use in the embodiments of the present application or related technical descriptions will be briefly introduced below. 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 creative work.

[0043] 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;

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

[0045] Figure 3 It is a flowchart of another method for concealed transmission of 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 concealed transmission of user sensitive information provided by an embodiment of the present application;

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

[0049] Figure 7It is a structural schematic diagram of a device for concealed transmission of user sensitive information provided in 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 solution and advantages of the present application more clearly understood, the present application is further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present application and are not used to limit the present application.

[0052] The following introduces the application scenarios of the method for covertly transmitting user sensitive information provided by the embodiments of the present application.

[0053] See also Figure 1 , Figure 1 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 via a network.

[0054] In a scenario where a user needs to upload user sensitive information to an application, the computer device 101 may 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; scramble and compress the first image coefficient matrix to obtain a processed first image coefficient matrix; 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; 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 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 also Figure 2 , Figure 22 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 above-mentioned computer device 201). Figure 2 As shown, the method for concealed transmission of 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 implementation, 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 card number, etc.

[0059] In an optional implementation, 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 method may be to use 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] Among them, discrete wavelet transform is a signal processing technology that decomposes the signal into sub-signals of different frequencies by convolution 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 information within the frequency range and downsample them 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 implementation, the computer device scrambles and compresses the first image coefficient matrix to obtain the processed first image coefficient matrix, which may include: scrambling the first image coefficient matrix to obtain the scrambled first image coefficient matrix; compressing the scrambled first image coefficient matrix to obtain the processed first image coefficient matrix. In this way, the computer device can disrupt the structure of the first image coefficient matrix by scrambling the first image coefficient matrix, making the user sensitive information more difficult to be identified and attacked, thereby improving the security of subsequent user sensitive information transmission; 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, 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.

[0068] In an optional implementation, the computer device may 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. In this way, the data transmission overhead can be reduced while retaining the key features of the data.

[0069] Among them, PCS is an advanced signal processing technology used to process sparse signals. The PCS technology is introduced in detail below.

[0070] (1) Sparse signal sampling and reconstruction: PCS technology achieves data compression and reconstruction during the signal sampling process by utilizing the sparsity of the signal. This ability to simultaneously sample and reconstruct gives PCS technology a significant advantage in data transmission and storage.

[0071] (2) Advantages of parallel processing: PCS technology adopts a parallel processing strategy to divide the input signal into multiple sub-signals and perform independent sampling and reconstruction processing on these sub-signals at the same time. Through parallel processing, PCS technology can not only improve processing efficiency, but also effectively reduce the computational complexity and power consumption of the system, thereby achieving more effective utilization of system resources.

[0072] (3) Adaptive compression rate control: PCS technology has adaptive compression rate control capability, that is, it automatically adjusts the compression rate to achieve the best balance between performance and efficiency according to the characteristics of the signal and the requirements of the application scenario. This adaptability enables PCS technology to achieve good compression effects in different application scenarios and adapt to dynamic changes in signals.

[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 image, an ordinary photo, or other irrelevant image. These images are used as carriers in covert transmission, and covert communication is performed by embedding encrypted user sensitive information. The purpose of selecting ordinary images is to ensure that the embedded user sensitive information is not visually noticeable, so as to achieve a camouflage effect during the transmission process.

[0076] S205 . Perform an inverse transformation on the target image coefficient matrix to obtain a target image including 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; scramble and compress the first image coefficient matrix to obtain a processed first image coefficient matrix; 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; embed the ciphertext information into a second image coefficient matrix corresponding to the carrier image to obtain a target image coefficient matrix; inversely transform 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 inversely transform 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 user sensitive information.

[0078] See also Figure 3 , Figure 31 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 concealed transmission of 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 , 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.

[0082] In an optional implementation, the computer device may filter the low-frequency signal through a low-pass filter and filter the high-frequency signal through a high-pass filter, so that noise and unnecessary frequency components in the signal can be removed through filtering operations.

[0083] Among them, downsampling the low-frequency signal and the high-frequency signal can reduce the amount of data and improve the calculation 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's sensitive information is obtained.

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

[0087] Among them, the dynamic Josephus algorithm is a mathematical algorithm for scrambling data, and its core idea comes from. In the Josephus problem, there are n people sitting in a circle. Starting from the first person, one person is counted and removed at a fixed interval g, and then the counting starts again from the next person until only one person is left. The dynamic Josephus algorithm generalizes this concept to the element scrambling operation of matrices or arrays to increase the randomness and confusion of the data, thereby improving the security and confidentiality of the data. The dynamic Josephus algorithm is introduced below.

[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 the 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: In order 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 reversely deducing the order of data before scrambling by analyzing the fixed rules of the algorithm, thereby improving data security and confidentiality.

[0090] (3) Obfuscating data relationships: The dynamic Josephus algorithm continuously rearranges the order of data elements to make the relationship between the original data blurred and confusing. 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, its 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 parameter to ensure that only authorized users can decrypt and restore the data.

[0092] Combine the following 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 size of the matrix, the initial position pointer, and the scrambling interval. These parameters are determined according to the specific application requirements and data characteristics to ensure the effectiveness and security of the scrambling operation. Subsequently, the matrix is ​​initialized, including determining the initial position pointer, the current position pointer, and so on. Usually, you can start from a fixed position in the matrix, such as the upper left corner or the lower right corner.

[0094] Then, the matrix is ​​scrambled by a circular scrambling operation. In each round of scrambling, the element with a fixed distance from the current position is found according to the current position pointer and moved to a new position. The move operation can be done by exchanging elements to ensure that each element is rearranged to a new position.

[0095] After that, the current position pointer is updated so that the next round of scrambling operation can proceed smoothly. The scrambling operation is repeated, and it is checked whether the termination condition is met, and when the termination condition is met, the scrambling is determined to be finished. The termination condition is, for example, that all elements are scrambled.

[0096] Finally, we get a scrambled image coefficient matrix. The order of the elements in this matrix has been rearranged to form a chaotic state, which increases the randomness and unpredictability of the data. This chaotic state makes it difficult to restore the structure and features of the original image, thereby increasing the security of the data.

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

[0098] Among them, the Hadamard matrix is ​​an orthogonal square matrix composed of +1 and -1 elements.

[0099] S306 , 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.

[0100] In an optional implementation, the relevant description of step S306 can refer to 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, a computer device embeds ciphertext information into a second image coefficient matrix corresponding to a carrier image to obtain a 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 a target image coefficient matrix.

[0103] In this implementation, 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 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 the low-frequency signal and the high-frequency signal corresponding to the user sensitive information; filter and downsample the low-frequency signal and the high-frequency signal respectively to obtain the low-frequency sensitive information and the high-frequency sensitive information; reconstruct the low-frequency sensitive information and the high-frequency sensitive information by inverse transformation to obtain the first image coefficient matrix corresponding to the user sensitive information, so that the efficiency and security of subsequent processing can be improved by converting the user sensitive information into the image coefficient matrix. Secondly, the first image coefficient matrix is ​​scrambled using the dynamic Josephus algorithm to obtain the first image coefficient matrix after scrambling, and the first image coefficient matrix after scrambling is compressed using the partial Hadamard 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 also Figure 5 , Figure 5 This is another flowchart 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 the compressed user sensitive information, and encrypts the compressed user sensitive information to obtain the ciphertext information corresponding to the user sensitive information. Figure 5 As shown, the method for concealed transmission of 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 , 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.

[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 refer to the descriptions of the aforementioned steps S301 to S305, and will not be repeated here.

[0113] S506: Divide the processed user sensitive information in the first image coefficient matrix into multiple sub-information, and compress the multiple sub-information respectively to obtain multiple compressed sub-information. In this way, the processing efficiency can be improved, and the calculation complexity and power consumption required for calculation can be reduced.

[0114] Optionally, when the computer device compresses the multiple sub-information separately to obtain the compressed multiple sub-information, the computer device can use the sparsity of the signal to sparsely represent the signal using a compressed sensing algorithm, thereby achieving efficient compression of the signal. Optionally, commonly used compressed sensing algorithms include sparse representation-based methods, such as sparse representation-based reconstruction algorithms (such as orthogonal matching pursuit (OMP) algorithm, back propagation (BP) algorithm, etc.).

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

[0116] Since the amount of data is greatly reduced after compression, it can be efficiently transmitted and stored through network transmission or 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 refer to the description of the aforementioned step S407, which will not be repeated here.

[0120] Among them, steps S508 and S509 can be implemented by a computer device using a reversible matrix coding embedding method. Among them, the reversible matrix coding embedding method is a key method for covert transmission and verification. In this application, through this method, the encrypted user information can be embedded in a specific position or feature of the image in a hidden and imperceptible way, so as to achieve the effect of transmitting only ordinary images in user perception, but in fact the purpose of embedding user sensitive information has been achieved.

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

[0122] (1) Encryption processing: 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, which can effectively protect the user's privacy data from unauthorized access and theft.

[0123] (2) Embedding process: The encrypted user information will be embedded into the ordinary image in a covert manner. During the embedding process, the positions or features that are not easily perceived in the image are usually selected, such as areas with small pixel values ​​or areas with rich image textures. The encrypted user information is embedded into these positions or features using matrix coding technology, so that the visual effect of the ordinary image is basically unaffected, while achieving covert transmission of 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 , inversely transform the target image coefficient matrix to obtain a target image including user sensitive information, and transmit the target image.

[0127] In the embodiment of the present application, the computer device can divide the user sensitive information into multiple sub-information; compress the multiple sub-information respectively to obtain multiple compressed sub-information; determine the compressed user sensitive information based on the multiple compressed sub-information; encrypt the compressed user sensitive information to obtain the ciphertext information corresponding to the user sensitive information. In this way, the security of the user sensitive information can be further improved, which is conducive to improving the integrity and security of the subsequent transmission of the user sensitive information.

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

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

[0130] After that, the extracted feature information is hashed to obtain the hash value corresponding to the carrier image. The hash value is a string of fixed-length data calculated based on the image content. It is unique and irreversible, and can effectively represent the content features of the image, ensuring the uniqueness and integrity of the image.

[0131] Then, combined with the encryption algorithm of user sensitive information and the requirements of the covert transmission system, the control parameters and initial vectors required in the encryption process are generated. These parameters and initial 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 (and control parameters and initial vectors) and the hash values ​​corresponding to the carrier image. These initial states include keys, random number seeds, etc., which can affect the running trajectory and results of the encryption and decryption process and play an important role in the security and reliability of the system.

[0133] By adopting this implementation mode, the computer device generates the initial state required in the encryption and decryption process by calculating the characteristics and hash value of the carrier image, which is conducive to enhancing the security and reliability of the system. In this way, it not only provides the necessary prerequisites and guarantees for the normal operation of the system, but also has important significance and value for protecting user privacy and data security.

[0134] In an optional embodiment, the present application also proposes a one-dimensional improved cosine chaotic mapping (denoted as 1-DICCM), whose control parameter μ>0. The computer device can ensure its suitability for covert transmission systems by evaluating its chaotic characteristics. Among them, the chaotic mapping is a nonlinear dynamic system characterized by high randomness, complexity and sensitivity depending on initial conditions. In the present application, the design of 1-DICCM has the following characteristics:

[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, which is used to adjust the dynamic behavior of chaotic mapping and thus affect the properties of the generated chaotic sequence.

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

[0138] (4) Characteristics without periodic windows: 1-DICCM does not have periodic windows in its chaotic distribution. This means that the chaotic sequence generated by 1-DICCM has greater randomness and irregularity, and is 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, and 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 implementation, 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 sensitive information of the user.

[0141] Optional, see Figure 6 , Figure 6 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 an inverse dynamic Josephus scrambling operation on the user sensitive information before compression that is restored through the inverse compression process 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 above-mentioned embodiments are displayed in sequence according to the indication of the arrows, these steps are not necessarily executed in sequence according to the order indicated by the arrows. Unless there is a clear explanation in this article, the execution of these steps does not have a strict order restriction, and these steps can be executed in other orders. Moreover, at least a part of the steps in the flowcharts involved in the above-mentioned embodiments can include multiple steps or multiple stages, and these steps or stages are not necessarily executed 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 part of the steps or stages in other steps.

[0149] Based on the same inventive concept, the embodiment of the present application also provides a user sensitive information hidden transmission device for implementing the user sensitive information hidden transmission method involved above. The implementation scheme for solving the problem provided by the device is similar to the implementation scheme recorded in the above method, so the specific limitations in the embodiments of one or more user sensitive information hidden transmission devices provided below can refer to the limitations of the user sensitive information hidden transmission method above, and will not be repeated here.

[0150] See also Figure 7 , Figure 7 Schematic diagram 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 concealed transmission device may include but is not limited to:

[0151] An image conversion unit 701 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;

[0152] The processing unit 702 is used 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 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.

[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 down-sample 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: verify the ciphertext information using a preset verification mechanism 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 user sensitive information concealed transmission device can be implemented in whole or in part by software, hardware and their combination. Each of the above-mentioned modules can be embedded in or independent of the processor in the terminal device in the form of hardware, or can be stored in the memory in the terminal device in the form of software, so that the processor can call and execute the corresponding operations of each of the above modules.

[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 through a system bus, and the communication interface, the display unit and the input device are connected to the system bus through 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, and the wireless manner can be implemented 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 those shown in the figure, or combine certain components, or have a different arrangement of components.

[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] The target image coefficient matrix is ​​inversely transformed to obtain a target image including user sensitive information, and the target image is transmitted.

[0170] In one embodiment, when the processor executes a computer program to implement image conversion of 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; 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: the user sensitive information in the processed first image coefficient matrix is ​​divided into multiple sub-information; the multiple sub-information are respectively compressed to obtain multiple compressed sub-information; and the compressed user sensitive information is determined 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 the target image coefficient matrix is ​​obtained, 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, and 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] The target image coefficient matrix is ​​inversely transformed to obtain a target image including user sensitive information, and the target image is transmitted.

[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; 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 compressing the first image coefficient matrix to obtain the processed image coefficient matrix, and specifically implements the following steps: 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.

[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 respectively 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 a target image coefficient matrix is ​​obtained, 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 the target image coefficient matrix is ​​obtained, 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 a target embedding position in the second image coefficient matrix to obtain the target image coefficient matrix.

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

[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] The target image coefficient matrix is ​​inversely transformed to obtain a target image including user sensitive information, and the target image is transmitted.

[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; 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 compressing the first image coefficient matrix to obtain the processed image coefficient matrix, and specifically implements the following steps: 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.

[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 respectively 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 a target image coefficient matrix is ​​obtained, 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 the target image coefficient matrix is ​​obtained, 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 a target embedding position in the second image coefficient matrix to obtain the 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] A person of ordinary skill in the art can understand that all or part of the processes in the above-mentioned embodiment method can be completed by instructing the relevant hardware through a computer program, and 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. Among them, any reference to the memory, database or other medium used in the embodiments provided in the present 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. As an illustration and not limitation, RAM can be in various forms, such as static random access memory (SRAM) or dynamic random access memory (DRAM). The database involved in each embodiment provided in this application may include at least one of a relational database and a non-relational database. Non-relational databases may include distributed databases based on blockchains, etc., but are not limited to this. The processor involved in each embodiment provided in this application may be a general-purpose processor, a central processing unit, a graphics processor, a digital signal processor, a programmable logic device, a data processing logic device based on quantum computing, an artificial intelligence (AI) processor, etc., but are not limited to this.

[0199] The technical features of the above embodiments may be combined arbitrarily. 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 only express several implementation methods of the present application, and the descriptions thereof are relatively specific and detailed, but they cannot be understood as limiting the scope of the present application. It should be pointed out that, for a person of ordinary skill in the art, several variations and improvements can be made without departing from the concept of the present application, and these all belong to the protection scope of the present application. Therefore, the protection scope of the present application shall be subject to the attached claims.

Claims

1. A method for concealed transmission of 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 a second image coefficient matrix corresponding to the carrier image to obtain a target image coefficient matrix; An inverse transformation is performed on the target image coefficient matrix to obtain a target image including the user sensitive information, and the target image is transmitted.

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: Based on the 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; 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 step of performing scrambling and compression processing on the first image coefficient matrix to obtain a processed 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 by using a partial Hadamard matrix to obtain a processed first image coefficient matrix.

4. 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; Compressing 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.

5. The method according to claim 1, characterized in that 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.

6. The method according to claim 5, 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: Using a preset verification mechanism, the ciphertext information is verified to obtain verified ciphertext 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.

7. 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 used to compress the user sensitive information corresponding to 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, used for embedding the ciphertext information and the processed first image coefficient matrix into a second image coefficient matrix corresponding to the carrier image to obtain a target image coefficient matrix; The processing and transmission unit is also used to perform inverse transformation processing on the target image coefficient matrix to obtain a target image including the user sensitive information, and transmit the target image.

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 6 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 6 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 6 are implemented.

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