Electronic screen content tampering detection method and system

Abstract

The invention provides an electronic screen content tampering detection method and system, and relates to the technical field of content tampering detection, and the method comprises the steps: obtaining to-be-detected electronic screen content, the to-be-detected electronic screen content comprises video information and video parameter information; the electronic screen content is subjected to integrity check and frame-by-frame processing, a first processing result is obtained, and the first processing result comprises a timestamp of each frame of video information, a first transformation matrix obtained through matrix transformation and an encryption sequence of an operation sequence of matrix transformation; sending the video information to a detection terminal for frame-by-frame processing again, and performing similarity calculation based on a second processing result of the frame-by-frame processing again and the first processing result to obtain a similarity value; and judging whether the content of the electronic screen is tampered or not based on the similarity value and a preset similarity threshold to obtain a judgment result. According to the method, effective tampering detection can be carried out in various complex environments, and the problems of inaccurate identification and large interference are solved.

Description

Technical Field

[0001] The present invention relates to the technical field of content tampering detection, and in particular to a method and system for detecting tampering of electronic screen content. Background Art

[0002] With the widespread adoption of electronic screen technology, video content tampering is an increasingly serious problem, especially in public spaces and advertising displays. Traditional video tampering detection methods rely on image recognition and content analysis, but most face technical bottlenecks when processing high-quality video content. Existing technologies are largely ineffective in detecting video tampering, especially for subtle changes in the video. Furthermore, these technologies often rely on simple image comparison or frame difference analysis, which are susceptible to interference from methods such as image compression and camouflaged editing.

[0003] Therefore, there is an urgent need for a method and system for detecting tampering of electronic screen content to solve the above problems. Summary of the Invention

[0004] The purpose of the present invention is to provide a method and system for detecting tampering of electronic screen content to improve the above-mentioned problem. To achieve the above-mentioned purpose, the technical solution adopted by the present invention is as follows:

[0005] In a first aspect, the present application provides a method for detecting tampering of electronic screen content, comprising:

[0006] Acquiring electronic screen content to be detected, wherein the electronic screen content to be detected includes video information and video parameter information;

[0007] Performing integrity checking and frame-by-frame processing on the electronic screen content to obtain a first processing result, the first processing result including a timestamp of each frame of video information, a first transformation matrix obtained by matrix transformation, and an encrypted sequence of the matrix transformation operation sequence;

[0008] Sending the video information to a detection terminal for further frame-by-frame processing, and performing similarity calculation based on a second processing result of the further frame-by-frame processing and the first processing result to obtain a similarity value;

[0009] Based on the similarity value and a preset similarity threshold, it is determined whether the electronic screen content has been tampered with to obtain a determination result.

[0010] In a second aspect, the present application further provides a system for detecting tampering of electronic screen content, comprising:

[0011] an acquisition unit, configured to acquire electronic screen content to be detected, wherein the electronic screen content to be detected includes video information and video parameter information;

[0012] a processing unit, configured to perform integrity verification and frame-by-frame processing on the electronic screen content to obtain a first processing result, wherein the first processing result includes a timestamp of each frame of video information, a first transformation matrix obtained by matrix transformation, and an encrypted sequence of an operation sequence of the matrix transformation;

[0013] a calculation unit, configured to send the video information to a detection terminal for further frame-by-frame processing, and perform similarity calculation based on a second processing result of the further frame-by-frame processing and the first processing result to obtain a similarity value;

[0014] The judgment unit is configured to judge whether the electronic screen content has been tampered with based on the similarity value and a preset similarity threshold, and obtain a judgment result.

[0015] The beneficial effects of the present invention are:

[0016] The present invention obtains the electronic screen content to be detected, including video information and video parameter information, and combines integrity verification and frame-by-frame processing to efficiently identify whether the video content has been tampered with. First, the integrity of the video content is checked to ensure the consistency of the video parameters and the video identification parameters; then, the video content is accurately detected frame by frame through timestamp extraction and matrix transformation processing. Further, through encryption processing and the generation of operation sequences, combined with a random number generator, the security and accuracy of the detection are enhanced. Finally, through similarity calculation, based on matrix decomposition technology, it is possible to accurately determine whether the video has been tampered with. The detection method of the present invention can perform effective tampering detection in a variety of complex environments, solving the problems of inaccurate identification and high interference in the prior art.

[0017] Other features and advantages of the present invention will be described in the following description, and in part will become apparent from the description, or understood by practicing the embodiments of the present invention. The purposes and other advantages of the present invention can be realized and obtained by the structures particularly pointed out in the written description, claims, and drawings. BRIEF DESCRIPTION OF THE DRAWINGS

[0018] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the following briefly introduces the drawings required for use in the embodiments. It should be understood that the following drawings only illustrate certain embodiments of the present invention and therefore should not be regarded as limiting the scope. For ordinary technicians in this field, other relevant drawings can be obtained based on these drawings without paying any creative work.

[0019] Figure 1 Schematic diagram of the process of detecting tampering of electronic screen content according to an embodiment of the present invention;

[0020] Figure 2Schematic diagram of the structure of the electronic screen content tampering detection system described in an embodiment of the present invention.

[0021] In the figure: 701, acquisition unit; 702, processing unit; 703, calculation unit; 704, judgment unit. DETAILED DESCRIPTION

[0022] In order to make the purpose, technical solutions and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. The components of the embodiments of the present invention generally described and shown in the drawings herein can be arranged and designed in various different configurations. Therefore, the following detailed description of the embodiments of the present invention provided in the drawings is not intended to limit the scope of the claimed invention, but merely represents selected embodiments of the present invention. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative work are within the scope of protection of the present invention.

[0023] It should be noted that similar reference numerals and letters represent similar items in the following drawings. Therefore, once an item is defined in one drawing, it does not need to be further defined or explained in subsequent drawings. At the same time, in the description of the present invention, the terms "first", "second", etc. are used only to distinguish the description and should not be understood as indicating or implying relative importance.

[0024] Example 1:

[0025] This embodiment provides a method for detecting tampering of electronic screen content.

[0026] See also Figure 1 , the figure shows that the method includes step S1, step S2, step S3 and step S4.

[0027] Step S1: Acquire the electronic screen content to be detected, wherein the electronic screen content to be detected includes video information and video parameter information;

[0028] It can be understood that this step provides accurate basic data for subsequent detection, effectively supports the integrity verification and analysis of the video content, and provides high-quality input for the subsequent tampering detection process. Video information usually refers to the specific content data of the video, that is, the video image data of each frame. These image data are usually compressed and decompressed and played when displayed, including color data, pixel information, etc. The video parameter information is the attribute data that describes the video, including a unique number, download address, name, format, video size and total number of frames. Video parameter information provides an important reference for subsequent integrity verification and analysis. It can help the system determine whether the video has been tampered with during transmission or storage. In particular, when the video is compressed, transcoded or re-encoded, the video parameters will change, which may cover up traces of tampering.

[0029] Step S2: performing integrity check and frame-by-frame processing on the electronic screen content to obtain a first processing result, wherein the first processing result includes a timestamp of each frame of video information, a first transformation matrix obtained by matrix transformation, and an encrypted sequence of the matrix transformation operation sequence;

[0030] It can be understood that this step accurately analyzes and protects the video through integrity verification and frame-by-frame processing, ensuring the authenticity and security of each frame of data. The combination of timestamps, matrix transformations, and encryption sequences provides a solid foundation for subsequent similarity calculations and tamper detection, effectively preventing tampering. In this step, step S2 includes steps S21, S22, and S23.

[0031] Step S21: Perform parameter identification on the unique number, download address, name, format, video size, and total number of frames in the video information to obtain video identification parameter information;

[0032] It's understandable that by identifying these parameters in this step, the system can accurately obtain the basic information of the video and lay the foundation for subsequent verification and processing. These parameters provide strong support for the legitimacy and integrity of the video. Especially during video transmission, storage, and playback, they can help detect whether the video has been tampered with, ensure the authenticity of the video, and prevent upload errors that may lead to incorrect recognition.

[0033] Step S22: Match the video recognition parameter information with the video parameter information one by one, and perform pairwise comparison based on the corresponding results, wherein the comparison result is obtained by matching the time and frame number of the video recognition parameter information with the video parameter information;

[0034] It is understandable that when performing pairwise comparisons in this step, the focus is on determining whether the video is complete and has not been tampered with by comparing time and frame number. Timestamps and frame numbers are very critical data in video parameter information, which describe the timing of the video and the number of images. When a video is tampered with, especially when it is edited or re-encoded, the timestamp and frame number are often affected. For example, after a video is edited, the length and frame number may change, or during the transcoding process, the time sequence and frame rate of the video may become inconsistent. These subtle changes can be effectively detected by comparing time and frame number.

[0035] Through this comparison, the system can generate a comparison result, which provides a basis for subsequent detection. If the comparison result shows that there is an inconsistency between the video recognition parameter information and the video parameter information, the system can promptly identify possible tampering and trigger further detection process.

[0036] Step S23: If the comparison result shows that the video recognition parameter information and the video parameter information are different, reacquire the video information for recognition until the video recognition parameter information and the video parameter information are the same.

[0037] It's understandable that this step iteratively reacquires and recognizes video information, ensuring that each recognition result is consistent with expectations. This prevents misidentifications caused by network transmission errors, data loss, or video file tampering. This approach allows the system to quickly respond and correct inconsistencies, significantly improving the accuracy and reliability of video integrity verification.

[0038] It can be understood that in this step, step S2 also includes step S24.

[0039] Step S24, the frame-by-frame processing includes timestamp extraction, wherein the timestamp of each frame of video in the video parameter information is extracted, the extracted timestamp is converted into a corresponding time point, and the timestamp converted into the corresponding time point is used as the initialization input of the random number generator.

[0040] It is understandable that this step, by combining the mapping of timestamps and time points, provides a stable and random benchmark for subsequent operations. Since timestamps are closely related to the actual playback time of the video content, their precise extraction and conversion ensure that the chronological order of the video content will not be misprocessed or disrupted. Using time points as the initialization input of the random number generator provides the necessary randomness for subsequent matrix transformation operations, ensuring that each transformation is unique, thereby effectively preventing the video content from being maliciously tampered with. In this step, step S24 is followed by steps S25, S26, S27, and S28.

[0041] Step S25: compress each frame of video information and convert it into a second matrix, and generate an operation sequence of matrix transformation based on the random number generator;

[0042] It can be understood that this step converts the pixel block size of each frame of video information into a matrix A. For color images, a matrix is then constructed with a dimension of (m, n*cc), where cc is the number of channels, usually RGB images have 3 channels. The (R, G, B) value of each pixel can be expanded into a vector by row. For black and white images, the matrix dimension is (m, n). Then, the timestamp information of each frame is obtained and converted into an integer as a random number seed to initialize the random number generator. For example: Taking the python code as an example, if the timestamp of a frame is 00:01:23.45, it is converted to timestamp_ms = 83456 milliseconds, and then used to initialize the random number generator, random.seed(timestamp_ms). Furthermore, through compression and matrix conversion, the computational burden of each frame of video information can be greatly reduced, and the speed and efficiency of data processing can be improved. The compressed matrix reduces storage requirements.

[0043] Step S26: Calculate the operation sequence and the second matrix based on a preset random factor calculation formula to obtain a random factor of the operation sequence;

[0044] It can be understood that this step combines the operation sequence with the second matrix and generates a random factor based on a preset random factor calculation formula, making each matrix transformation operation highly random. This not only increases the complexity of the transformation operation, but also makes it very difficult to reverse-engineer the transformation process using standard matrix inversion methods. By enhancing the randomness of the operation, the system can provide stronger security when detecting video content tampering, preventing conventional tampering methods from evading detection.

[0045] Here, the operation sequence of the matrix transformation has a total of n operation elements, the total number of random factors required is count, and the calculation formula for the total number of random factors is as follows:

[0046]

[0047] Among them, t i represents the random factor required for the i-th operation,

[0048] A random number generator is then called to obtain random factors of the corresponding length. The required number of random factors is then associated with each basic transformation operation in the sequence, following the order of the elements in the matrix transformation operation sequence, forming an ordered mapping of the matrix transformation operations. The four basic operations require the following number of random factors: one for each rotation, a random factor equal to the number of matrix elements for each XOR operation, and two for each row and column swap. To maintain matrix order, the random factors for rotation operations are generated from [0, 90, 180, 270]. Due to the binary nature of XOR operations, the random factors for XOR operations are generated from [0, 1]. The random factors for row / column swaps are derived by taking the modulo of the rows / columns of the matrix using any random positive integer.

[0049] Step S27: Based on the order of the elements in the operation sequence, associate each transformation operation in the operation sequence with a corresponding number of random factors to obtain an ordered mapping set;

[0050] It can be understood that this step works by matching the generated random factors to each transformation operation in the operation sequence. Here, each operation is associated with one or more random factors, which are used to adjust the details of the operation to ensure the randomness of the transformation process. In other words, the random factors determine how the transformation is performed based on the type and order of the operations, further increasing the complexity and unpredictability of the matrix transformation.

[0051] Step S28: Perform a transformation operation on the second matrix based on the ordered mapping set to obtain a first matrix.

[0052] It can be understood that in this step, during rotation operations, the rotation angle is the random factor corresponding to the rotation operation in the ordered mapping. During XOR operations, the XOR key is the random factor corresponding to the XOR operation in the ordered mapping. During row or column swap operations, the index of the swapped row or column is the random factor in the ordered mapping. This step ensures that every frame of the video is processed through precise matrix transformations, providing a stable foundation for subsequent similarity calculations and tamper detection, further enhancing the robustness and accuracy of the entire system. For example, the specific operation is: the matrix A is a 5*4 matrix, A=[[3,5,6,7],[11,12,13,14],[9,8,17,16],[15,16,17,18],[1,2,3,4]], the ordered mapping of the matrix transformation operation is {'rotation': 90; 'row swap': (1,3); 'XOR': [[1,0,1,1,0],[0,1,1,0,1],[1,1, 0,0,1],[0,0,1,1,1]]; 'Rotate': 90; 'Column Swap': (1,4)}, transform the matrix A according to the ordered map Map. Operation 1 rotates the matrix 90 degrees clockwise from left to right and from top to bottom, and the result is [[1,15,9,11,3],[2,16,8,12,5],[3,17,7,13,6],[4,18,6,14,7]], operation 2 swaps the rows. After swapping rows 1 and 3, the result is [[3,17,7,13,6],[2,16,8,12,5],[1,15,9,11,3],[4,18,6,14,7]]. Operation 3 performs an XOR operation on each matrix element and the corresponding element in the secret matrix, and the result is [[2,17,6,12,6],[2,17,9,12,4],[0,14,9,11,2],[4,18,7,1 The result after operation 4 rotation is [[4,2,0,2],[18,17,14,17],[7,9,9,6],[15,12,11,12],[6,4,2,6]], and the final result after operation 5 column swapping the 1st and 4th columns is [[2,2,0,4],[17,17,14,18],[6,9,9,7],[12,12,11,15],[6,4,2,6]].

[0053] It can be understood that in this step, step S2 also includes step S29.

[0054] Step S29: encrypt the operation sequence to obtain an encrypted operation sequence of matrix transformation;

[0055] In this step, the encryption operation uses a common symmetric encryption algorithm, such as AES (Advanced Encryption Standard) and Caesar Cipher. Taking the Caesar Cipher encryption algorithm as an example, Rotation, XOR, Row, and Column represent rotation, XOR, row exchange, and column exchange operations, respectively. If the matrix transformation operation sequence is [rotation, row exchange, XOR, rotation, column exchange], it is converted to the string "Rotation, Row, XOR, Rotation, Column" and the secret key is 123. The encrypted results are Khmtmbhg, Khp, QHK, Khmtmbhg, Vhenfg.

[0056] Step S3: sending the video information to the detection terminal for further frame-by-frame processing, and performing similarity calculation based on the second processing result of the further frame-by-frame processing and the first processing result to obtain a similarity value;

[0057] It can be understood that this step not only enhances the accuracy and reliability of video tampering detection by calculating the similarity based on the first processing result and the second processing result, but also improves the intelligence level of the system, providing strong technical support for subsequent tampering judgment. In this step, step S3 includes step S31 and step S32.

[0058] Step S31: decrypting the encrypted sequence of matrix transformation operations in the first processing result, and generating an ordered mapping set of matrix transformation operations to be processed again frame by frame based on the decrypted sequence of matrix transformation operations and a random number generator;

[0059] It can be understood that this step decrypts the encrypted sequence of matrix transformation operations in the first processing result and, based on the decrypted sequence of operations and a random number generator, generates an ordered mapping set of matrix transformation operations to be processed again frame by frame. This process establishes a mapping relationship between the encrypted operations and the decrypted sequence of operations, providing an effective basis for subsequent detection and processing steps. The decrypted sequence of operations accurately restores the original matrix transformation steps and ensures that they are executed during the detection terminal.

[0060] Step S32: performing matrix transformation on the video information again based on the ordered mapping set of matrix transformation operations processed frame by frame again to obtain a third matrix.

[0061] It can be understood that this step ensures the consistency of video information during the two frame-by-frame processing steps by performing matrix transformations based on an ordered mapping set. The mapping set not only ensures the order of operations but also ensures the uniqueness of each transformation operation by introducing a random factor, thus avoiding deviations in the transformation results caused by different operation orders or factors.

[0062] It can be understood that in this step, step S3 also includes step S33, step S34 and step S35.

[0063] Step S33: Decomposing the first matrix and the third matrix, wherein each frame of video is divided into at least two local image regions according to a preset size, and the matrix data corresponding to each local image region is used as a submatrix to obtain a submatrix of the first matrix and a submatrix of the third matrix;

[0064] It is understandable that this step, by dividing the entire video frame into local areas and extracting corresponding submatrices, allows the system to independently analyze local changes in the video. In this way, local details can be more meticulously identified and processed, improving the accuracy of video analysis. For example, for local changes in certain video content, the system can focus on these changes separately, without having to rely on the processing of the overall video frame, avoiding errors that may be introduced during large-scale processing. After the large matrix is decomposed into multiple submatrices, the processing of each submatrix can be carried out in parallel, thereby significantly improving the efficiency of video data processing. Especially when processing high-resolution video, the division of local areas can reduce the complexity of a single matrix, making the entire processing process more scalable.

[0065] Step S34: Substitute the submatrix of the first matrix and the submatrix of the third matrix into a preset similarity calculation formula to calculate and obtain the similarity between the submatrix of the first matrix and the submatrix of the third matrix corresponding to each local area;

[0066] It can be understood that the similarity calculation in this step can accurately evaluate whether the transformation effect of each local area meets the expectations, thereby providing a quantitative method to judge the stability and consistency of the transformation. Among them, when calculating the similarity of the submatrix of the first matrix and the submatrix of the third matrix, the similarity of the same local area is calculated. A high similarity value indicates that the transformation result is consistent with the original matrix, while a low similarity value may indicate that there is an error or problem in the transformation.

[0067] The similarity calculation formula is as follows:

[0068]

[0069] Among them, Sim(b,c) represents the similarity between the submatrix of the first matrix and the submatrix of the third matrix, μ b 、μ c represents the mean of submatrix b and submatrix c, Represents the variance of submatrix b and submatrix c, cov(b,c) represents the covariance of submatrix b and submatrix c, c1 and c2 are constants.

[0070] Step S35: Calculate the mean of all similarities to obtain the similarity between the first matrix and the third matrix.

[0071] It is understood that this step, through the calculation of mean similarity, can intuitively assess whether the video content maintains the expected consistency after the matrix transformation. At this time, the level of similarity is the key basis for judging whether the transformation operation is successful. If the similarity value is high, it means that the transformation effects of the first matrix and the third matrix are similar, and the transformation process is stable and accurate. If the similarity value is low, it means that there are significant differences in the transformation results in certain local areas, and optimization adjustments may be required.

[0072] Step S4: judging whether the electronic screen content has been tampered with based on the similarity value and a preset similarity threshold, and obtaining a judgment result.

[0073] It is understandable that in this step, if the similarity value is greater than or equal to the preset similarity threshold, it means that the first matrix and the third matrix are highly consistent as a whole, and the video content has not been obviously tampered with, and the video content is judged to be "not tampered with". If the similarity value is less than the threshold, it means that there is a large difference between the first matrix and the third matrix, which may mean that the video content has been tampered with or changed in some aspects, and the video content is judged to be "tampered with". By determining whether the video content has been tampered with, the system can decide whether further action is required. For example, if the video content is determined to be tampered with, the system can trigger a warning and initiate a more in-depth verification mechanism, such as requesting a retrospective check, a higher-precision tampering detection algorithm, manual review, etc.; if the video content has not been tampered with, other operations can continue, such as content publishing, archiving, etc.

[0074] Example 2:

[0075] like Figure 2 As shown, this embodiment provides a tamper detection system for electronic screen content, see Figure 2 The system includes an acquisition unit 701 , a processing unit 702 , a calculation unit 703 and a judgment unit 704 .

[0076] An acquisition unit 701 is configured to acquire electronic screen content to be detected, where the electronic screen content to be detected includes video information and video parameter information;

[0077] The processing unit 702 is configured to perform integrity verification and frame-by-frame processing on the electronic screen content to obtain a first processing result, where the first processing result includes a timestamp of each frame of video information, a first transformation matrix obtained by matrix transformation, and an encrypted sequence of the matrix transformation operation sequence;

[0078] a calculation unit 703 configured to send the video information to a detection terminal for further frame-by-frame processing, and perform similarity calculation based on a second processing result of the further frame-by-frame processing and the first processing result to obtain a similarity value;

[0079] The judgment unit 704 is configured to judge whether the electronic screen content has been tampered with based on the similarity value and a preset similarity threshold, and obtain a judgment result.

[0080] It should be noted that, regarding the system in the above embodiment, the specific manner in which each module performs operations has been described in detail in the embodiment of the method, and will not be elaborated on here.

[0081] The foregoing description is merely a preferred embodiment of the present invention and is not intended to limit the present invention. Those skilled in the art will readily appreciate that various modifications and variations of the present invention are possible. Any modifications, equivalent substitutions, or improvements made within the spirit and principles of the present invention are intended to be within the scope of protection of the present invention.

[0082] The above description is merely a specific embodiment of the present invention, but the scope of protection of the present invention is not limited thereto. Any modifications or substitutions that can be easily conceived by a person skilled in the art within the technical scope disclosed in the present invention should be included within the scope of protection of the present invention. Therefore, the scope of protection of the present invention should be based on the scope of protection of the claims.

Claims

1. A method for detecting tampering of electronic screen content, characterized in that: include: Acquiring electronic screen content to be detected, wherein the electronic screen content to be detected includes video information and video parameter information; Performing integrity checking and frame-by-frame processing on the electronic screen content to obtain a first processing result, the first processing result including a timestamp of each frame of video information, a first transformation matrix obtained by matrix transformation, and an encrypted sequence of the matrix transformation operation sequence; Sending the video information to a detection terminal for further frame-by-frame processing, and performing similarity calculation based on a second processing result of the further frame-by-frame processing and the first processing result to obtain a similarity value; Based on the similarity value and a preset similarity threshold, it is determined whether the electronic screen content has been tampered with to obtain a determination result.

2. The method for detecting tampering of electronic screen content according to claim 1, characterized in that , performing integrity checks on the electronic screen contents in sequence, including: Perform parameter identification on the unique number, download address, name, format, video size and total number of frames in the video information to obtain video identification parameter information; Matching the video recognition parameter information with the video parameter information one by one, and performing pairwise comparison based on the corresponding results, wherein the comparison results are obtained by matching the time and frame number of the video recognition parameter information with the video parameter information; If the comparison result shows that the video recognition parameter information and the video parameter information are different, the video information is re-acquired for recognition until the video recognition parameter information and the video parameter information are the same.

3. The method for detecting tampering of electronic screen content according to claim 1, characterized in that The frame-by-frame processing includes: The frame-by-frame processing includes timestamp extraction, wherein the timestamp of each frame of video in the video parameter information is extracted, the extracted timestamp is converted into a corresponding time point, and the timestamp converted into the corresponding time point is used as an initialization input of a random number generator.

4. The method for detecting tampering of electronic screen content according to claim 3, characterized in that After converting the timestamp into a corresponding time point as the initialization input of the random number generator, the method further includes: Compressing each frame of video information into a second matrix, and generating a matrix transformation operation sequence based on the random number generator; Calculating the operation sequence and the second matrix based on a preset random factor calculation formula to obtain a random factor of the operation sequence; Based on the order of elements in the operation sequence, each transformation operation in the operation sequence is associated with its corresponding number of random factors to obtain an ordered mapping set; A transformation operation is performed on the second matrix based on the ordered mapping set to obtain the first matrix.

5. The method for detecting tampering of electronic screen content according to claim 1, characterized in that The frame-by-frame processing further includes: Encrypting the operation sequence to obtain an encrypted operation sequence of matrix transformation; The sending of the video information to the detection terminal for further frame-by-frame processing includes: decrypting the encrypted sequence of matrix transformation operations in the first processing result, and generating an ordered mapping set of matrix transformation operations to be processed again frame by frame based on the decrypted sequence of matrix transformation operations and a random number generator; The video information is again subjected to matrix transformation based on the ordered mapping set of matrix transformation operations processed frame by frame to obtain a third matrix.

6. A system for detecting tampering of electronic screen content, characterized in that: include: an acquisition unit, configured to acquire electronic screen content to be detected, wherein the electronic screen content to be detected includes video information and video parameter information; a processing unit, configured to perform integrity verification and frame-by-frame processing on the electronic screen content to obtain a first processing result, wherein the first processing result includes a timestamp of each frame of video information, a first transformation matrix obtained by matrix transformation, and an encrypted sequence of an operation sequence of the matrix transformation; a calculation unit, configured to send the video information to a detection terminal for further frame-by-frame processing, and perform similarity calculation based on a second processing result of the further frame-by-frame processing and the first processing result to obtain a similarity value; The judgment unit is configured to judge whether the electronic screen content has been tampered with based on the similarity value and a preset similarity threshold, and obtain a judgment result.

7. The electronic screen content tampering detection system according to claim 6, characterized in that: The processing unit includes: The first processing subunit is configured to perform parameter identification on the unique number, download address, name, format, video size, and total number of frames in the video information to obtain video identification parameter information; a second processing subunit, configured to establish a one-to-one correspondence between the video recognition parameter information and the video parameter information, and perform a pairwise comparison based on the correspondence results, wherein the comparison result is obtained by the time and frame number of the correspondence between the video recognition parameter information and the video parameter information; The third processing subunit is configured to, if the comparison result shows that the video recognition parameter information and the video parameter information are different, reacquire the video information for recognition until the video recognition parameter information and the video parameter information are the same.

8. The electronic screen content tampering detection system according to claim 6, characterized in that: The processing unit further includes: The fourth processing sub-unit is used for the frame-by-frame processing including timestamp extraction, wherein the timestamp of each frame of video in the video parameter information is extracted, the extracted timestamp is converted into a corresponding time point, and the timestamp is converted into a corresponding time point as an initialization input of a random number generator.

9. The electronic screen content tampering detection system according to claim 8, characterized in that: After the fourth processing subunit, the method further includes: a fifth processing subunit, configured to convert each frame of video information into a second matrix after compression, and generate an operation sequence of matrix transformation based on the random number generator; a sixth processing subunit, configured to calculate the operation sequence and the second matrix based on a preset random factor calculation formula to obtain a random factor of the operation sequence; a seventh processing subunit, configured to associate each transformation operation in the operation sequence with a corresponding number of random factors based on the order of the elements in the operation sequence, to obtain an ordered mapping set; The eighth processing subunit is configured to perform a transformation operation on the second matrix based on the ordered mapping set to obtain a first matrix.

10. The electronic screen content tampering detection system according to claim 6, characterized in that: The processing unit further includes: A first transformation subunit is configured to perform encryption processing on the operation sequence to obtain an operation encryption sequence of matrix transformation; The sending of the video information to the detection terminal for further frame-by-frame processing includes: a second transformation subunit, configured to decrypt the encrypted sequence of matrix transformation operations in the first processing result, and generate an ordered mapping set of matrix transformation operations to be processed again frame by frame based on the decrypted sequence of matrix transformation operations and a random number generator; The third transformation subunit is configured to perform matrix transformation on the video information again based on an ordered mapping set of matrix transformation operations processed frame by frame again to obtain a third matrix.

Images