Security Anti-counterfeiting method and apparatus for digital human AIGC video

Abstract

Provided in the present application are a security anti-counterfeiting method and apparatus for a digital human AIGC video. The method comprises: forming a video production information code on the basis of information related to the creation of a digital human AIGC video; processing production content involved in a production process of the digital human AIGC video, so as to form a generated content code; processing data at least including the video production information code and the generated content code, so as to form a video generation context MD5 value; in a format masking mode of transparent pixels, inserting the video generation context MD5 value into a specified anti-counterfeiting area in a digital human video frame; forming a video integrity MD5 value from the digital human AIGC video; and constructing a security anti-counterfeiting system mapping table at least including a video serial number, the video production information code, the generated content code, the video generation context MD5 value and the video integrity MD5 value. The present application reduces the risk of anti-counterfeiting information being maliciously tampered with or removed, thereby enhancing the reliability of the anti-counterfeiting information.

Description

A digital human AIGC video security anti-counterfeiting method and device Technical Field

[0001] The present application belongs to the field of video processing technology, and in particular relates to a digital human AIGC video security anti-counterfeiting method and device. Background Art

[0002] Digital human AIGC video technology is gradually being applied in numerous industries, including e-commerce, advertising, news broadcasting, training, and education. Current developments in AIGC technology have made it difficult to distinguish between videos produced by digital humans and those produced by real people. This has led to the challenge of verifying whether a video was intentionally shot by a real person or maliciously produced by a digital human. In particular, when an illegal video appears, efficient methods are needed to determine whether it was produced by a digital human, who produced it, when, and on what platform, to facilitate dispute resolution. Because AIGC is a nascent industry, anti-counterfeiting verification technology in this area is severely lacking.

[0003] Current authentication systems, based on traditional technologies, assign unique digital identities to each digital person. This unique identifier is attached to each frame of a video in the form of a plaintext or encrypted string, creating a digital signature for the video. This approach suffers from poor video robustness, making it easily identified and removed by humans and machines. Furthermore, the identifier contains limited information, ignoring the relevance of the digital person to the video content they participated in, and making it impossible to trace and restore information related to the producer.

[0004] Summary of the Invention

[0005] In order to solve at least one of the above technical problems, the present application provides a digital human AIGC video security anti-counterfeiting method and device to trace and restore the producer, digital human and original content information.

[0006] The first aspect of this application is a digital human AIGC video security and anti-counterfeiting method, which mainly includes:

[0007] Forming a video production information code based on information related to the digital human AIGC video creation;

[0008] Process the production content involved in the production process of the digital human AIGC video based on the MD5 algorithm to form a generated content code;

[0009] Processing data including at least the video production information code and the generated content code based on the MD5 algorithm to form a video generation context MD5 value;

[0010] For the image frame containing the digital human in the AIGC video of the digital human, the MD5 value of the video generation context is inserted into the area constructed by the digital human's body features in a coded manner in the format of transparent pixels;

[0011] The digital human AIGC video is converted into a video integrity MD5 value based on the MD5 algorithm;

[0012] Construct a security and anti-counterfeiting system mapping table including at least the video number, the video production information code, the generated content code, the video generation context MD5 value and the video integrity MD5 value.

[0013] Preferably, the forming of the video production information code includes:

[0014] The digital human information related to the digital human AIGC video creation is converted into the first video production information code;

[0015] The producer information related to the digital human AIGC video creation is converted into a second video production information code;

[0016] At least the first video production information code and the second video production information code are spliced ​​together to form the video production information code.

[0017] Preferably, forming the generated content code includes:

[0018] Determine the sub-MD5 value of each production content involved in the production process of the digital human AIGC video based on the MD5 algorithm, wherein each production content includes text, audio, picture and video;

[0019] Each of the sub-MD5 values ​​is concatenated to form the generated content code.

[0020] Preferably, the area constructed by the digital human's body features includes: a triangular area constructed by the digital human's two eye pupils and nose tip.

[0021] Preferably, the digital human AIGC video security and anti-counterfeiting method further comprises:

[0022] According to the video integrity MD5 value of the video to be authenticated, a search is performed in the security and anti-counterfeiting system mapping table to determine whether the authenticated video is generated by the designated production system;

[0023] By extracting the video generation context MD5 value in the image frame where the digital human exists, searching in the security and anti-counterfeiting system mapping table according to the video generation context MD5 value, the retrieved video information is used to determine the degree of modification of the identified video based on the video production information code and the video creation information and video production content mapped by the generated content coding.

[0024] In the second aspect of this application, a digital human AIGC video security and anti-counterfeiting device mainly includes:

[0025] A video production information code generation module is used to generate a video production information code based on information related to the digital human AIGC video creation;

[0026] A content coding generation module is used to process the production content involved in the production process of the digital human AIGC video based on the MD5 algorithm to form a generated content code;

[0027] A video generation context MD5 value generation module, configured to process data including at least the video production information code and the generated content code based on an MD5 algorithm to form a video generation context MD5 value;

[0028] A coding module is used to insert the video generation context MD5 value in the area constructed by the digital human's body features into the image frame containing the digital human in the digital human AIGC video by coding in the format of transparent pixels;

[0029] A video integrity MD5 value generation module is used to generate a video integrity MD5 value from the digital human AIGC video based on the MD5 algorithm;

[0030] The security and anti-counterfeiting system mapping table construction module is used to construct a security and anti-counterfeiting system mapping table including at least the video number, the video production information code, the generated content code, the video generation context MD5 value and the video integrity MD5 value.

[0031] Preferably, the video production information code generation module includes:

[0032] A digital human information processing unit, configured to convert digital human information related to the digital human AIGC video creation into a first video production information code;

[0033] A producer information processing unit, configured to convert producer information related to the digital human AIGC video creation into a second video production information code;

[0034] The first splicing unit is used to splice at least the first video production information code and the second video production information code to form the video production information code.

[0035] Preferably, the content encoding generation module includes:

[0036] A sub-MD5 value calculation unit, configured to determine the sub-MD5 value of each production content involved in the production process of the digital human AIGC video based on the MD5 algorithm, wherein each production content includes text, audio, picture, and video;

[0037] The second concatenation unit is configured to concatenate the sub-MD5 values ​​to form the generated content code.

[0038] Preferably, the area constructed by the digital human's body features includes: a triangular area constructed by the digital human's two eye pupils and nose tip.

[0039] Preferably, the digital human AIGC video security and anti-counterfeiting device further comprises:

[0040] A video integrity MD5 value verification module is used to search the security and anti-counterfeiting system mapping table according to the video integrity MD5 value of the video to be authenticated, so as to determine whether the authenticated video is generated by the designated production system;

[0041] The video generation context MD5 value verification module is used to extract the video generation context MD5 value in the image frame where the digital human exists, search the security and anti-counterfeiting system mapping table according to the video generation context MD5 value, and determine the degree of modification of the video being authenticated based on the video creation information and video production content mapped according to the video production information code and the generated content coding.

[0042] The third aspect of the present application is a computer system comprising a processor, a memory, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the above-mentioned digital human AIGC video security and anti-counterfeiting method.

[0043] The fourth aspect of the present application is a readable storage medium, which stores a computer program. When the computer program is executed by a processor, it is used to implement the above-mentioned digital human AIGC video security and anti-counterfeiting method.

[0044] By being able to efficiently and accurately identify whether a video is generated by the digital human AIGC, and trace back to restore the producer and digital human, as well as the original content information, the concealment and confidentiality of anti-counterfeiting information are improved, and the risk of anti-counterfeiting information being maliciously tampered with or removed is reduced, thereby enhancing the reliability of anti-counterfeiting information. BRIEF DESCRIPTION OF THE DRAWINGS

[0045] FIG1 is a flow chart of an embodiment of the digital human AIGC video security and anti-counterfeiting method of the present application.

[0046] FIG2 is a schematic diagram of the structure of a computer device suitable for implementing a terminal or server according to an embodiment of the present application. DETAILED DESCRIPTION

[0047] In order to make the purpose, technical solutions and advantages of the implementation of this application clearer, the technical solutions in the implementation of this application will be described in more detail below in conjunction with the drawings in the implementation of this application. In the drawings, the same or similar numbers throughout represent the same or similar elements or elements with the same or similar functions. The described implementation is a part of the implementation of this application, not all of the implementations. The implementation described below with reference to the drawings is exemplary and is intended to be used to explain this application, and should not be understood as a limitation on this application. Based on the implementation in this application, all other implementations obtained by ordinary technicians in this field without making creative work are within the scope of protection of this application. The implementation of this application is described in detail below in conjunction with the drawings.

[0048] According to the first aspect of the present application, a digital human AIGC video security and anti-counterfeiting method is provided, as shown in FIG1 , which mainly includes:

[0049] Step S100: forming a video production information code based on information related to digital human AIGC video creation.

[0050] In step S100, the present application first processes information related to the creation of the digital human AIGC video. This information may be various information such as the digital human's own information, producer information, production time, platform, verification code, etc. For example, by encoding and storing the digital human's own information and producer information, the content of the digital human AIGC video can be guaranteed to be safe and compliant, and illegal and unlawful information can be avoided. The real-name generation system will carry the above information and can quickly find all owner information in any identification system without relying on a certain original coding system.

[0051] Specifically, in some optional implementations, forming the video production information code includes:

[0052] Step S101: Digital human information related to the digital human AIGC video creation is converted into a first video production information code;

[0053] Step S102: The producer information related to the digital human AIGC video creation is converted into a second video production information code;

[0054] Step S103: at least concatenate the first video production information code and the second video production information code to form the video production information code.

[0055] In step S101, the digital human information corresponds to the information of the digital human owner, and the encoding logic of the corresponding first video production information code can be as shown in Table 1.

[0056] Table 1 Digital human information encoding method

[0057] In step S102, the producer information may be, for example, the producer's registered communication mark, mobile phone number or email address, etc. The producer information uses a public mobile phone number or email address to enable the content tracing link to quickly contact the producer for illegal, infringing or infringed information, thereby realizing fast and effective dynamic management of content.

[0058] In step S103, at least the above two information codes are spliced ​​together to form the video production information code.

[0059] In an alternative implementation, in step S103, a third video production information code formed by the production time of the digital human AIGC video, a fourth video production information code formed by the production platform of the digital human AIGC video, and a verification code can be further added. The above information codes and verification codes are spliced ​​together to form the video production information code.

[0060] In the above embodiment, the check code generation logic uses a CRC algorithm to verify the digital human information, producer information, production timestamp, and production platform number, resulting in a check code with good performance and effectiveness. CRC (Cyclic Redundancy Checksum) is an error correction technology that stands for cyclic redundancy checksum. CRC can be used to verify stored data. During data storage, a CRC check value can be calculated and stored. When data needs to be read, the check value can be recalculated and compared with the stored check value to determine data integrity.

[0061] The video production information code synthesized using the aforementioned splicing technology truly connects the digital human's information with the producer, time, and location (production platform) of production. Furthermore, the checksum allows for quick and easy improvement of error correction mechanisms, and the CRC length can be extended based on content level to improve error detection reliability. Large enterprises and government agencies with highly critical content or high security requirements can use longer checksums.

[0062] Step S200: Process the production content involved in the production process of the digital human AIGC video based on the MD5 algorithm to form a generated content code.

[0063] In addition to encoding the creator information in step S100, the present application also encodes the produced content in step S200. The principle of the MD5 algorithm can be briefly described as follows: the MD5 code processes the input information in 512-bit groups, and each group is divided into 16 32-bit sub-groups. After a series of processing, the output of the algorithm consists of four 32-bit groups. After concatenating these four 32-bit groups, a 128-bit hash value is generated.

[0064] In some optional implementations, forming the generated content code includes: determining the sub-MD5 values ​​of each production content involved in the production process of the digital human AIGC video based on the MD5 algorithm, wherein each production content includes text, audio, picture and video; and splicing each of the sub-MD5 values ​​to form the generated content code.

[0065] In this embodiment, the production content is categorized and MD5 encoded for different types of production content. Specifically, as shown in Table 2, MD5 encoding is performed on each of the text, audio, image, and video materials to obtain multiple sub-MD5 values, which are then concatenated as shown in Table 3.

[0066] Table 2 Production content coding table

[0067] Table 3 Coding data concatenation table

[0068] Step S300: Processing data including at least the video production information code and the generated content code based on the MD5 algorithm to form a video generation context MD5 value.

[0069] In this step, the video production information code and the generated content code can be spliced ​​together, and then the video generation context MD5 value can be calculated through the MD5 algorithm. In an alternative implementation, the security anti-counterfeiting system self-increment ID, target video number, video production information code, and generated content code can be calculated together through MD5 to obtain the video generation context MD5 value.

[0070] Step S400: For the image frame containing the digital human in the AIGC video of the digital human, the video generation context MD5 value is inserted into the area constructed by the digital human's body features in a coded manner in the form of transparent pixels.

[0071] In this embodiment, the digital human video produced by the AIGC is processed frame by frame. For image frames where a digital human appears, an anti-counterfeiting zone is formed using fixed physical features of the digital human. Within the anti-counterfeiting zone, the MD5 value of the context generated by the digital human video is coded in transparent pixels, and this is repeated across all frames. Frames where the digital human does not appear or where physical features cannot be located are skipped to ensure sufficient fault tolerance.

[0072] In some optional implementations, the area constructed by the digital human's body features includes: a triangular area constructed by the digital human's pupils and nose.

[0073] In this embodiment, a security triangle is formed using three points defined by the pupils of both eyes and the tip of the nose. The digital human video security MD5 value is embedded within this area, effectively enhancing the robustness of the video. This design makes it difficult for the security triangle to be accidentally cut out when the video is clipped, edited, or reposted, effectively protecting the integrity of the security information.

[0074] A triangular area, formed between the pupils and nose of the digital person, is used for transparent coding. This provides a high degree of error tolerance and prevents the inability to extract verification codes after repeated video editing, as is often the case with forged videos. To enhance authenticity, large areas of the person's face are typically not significantly altered, preserving more information. If a large area of ​​the person's face is censored, obscuring MD5 extraction from the video, this, to a certain extent, protects the AIGC video host's personal characteristics, indirectly achieving compliant privacy protection.

[0075] Using the pupils of both eyes and the tip of the nose to locate the security triangle makes it more accurate and stable. This allows the system to more quickly extract the code value from a specific facial region, enabling highly efficient authentication. This positioning method not only facilitates automatic positioning but also aids manual inspection and verification, accelerating the identification of security codes and verification of security information. The high efficiency of this range technology makes it extremely low-cost, making it suitable for everyday large-scale digital human AIGC video range generation.

[0076] By embedding the anti-counterfeiting MD5 value of the digital human video into the anti-counterfeiting triangle area through transparent pixel coding, the anti-counterfeiting information is not only preserved but also efficiently located in the video. This design enables the digital human authentication system to directly identify the anti-counterfeiting area and decode the anti-counterfeiting MD5 value, thereby quickly finding the anti-counterfeiting code, reducing the decoding time of the anti-counterfeiting information and improving system efficiency.

[0077] The video anti-counterfeiting authentication code in this application uses transparent pixel coding to embed the digital human video anti-counterfeiting MD5 value into the anti-counterfeiting triangle area. This method does not affect the normal playback and viewing of the video content, but also effectively hides the anti-counterfeiting information. This design improves the concealment and confidentiality of the anti-counterfeiting information, reduces the risk of malicious tampering or removal of the anti-counterfeiting information, and thus enhances the reliability of the anti-counterfeiting information.

[0078] Step S500: generating a video integrity MD5 value from the digital human AIGC video based on the MD5 algorithm.

[0079] In this embodiment, after all the above-mentioned system coding is completed, a new video integrity MD5 value is generated for the final video.

[0080] Step S600: Construct a security and anti-counterfeiting system mapping table that at least includes the video number, the video production information code, the generated content code, the video generation context MD5 value, and the video integrity MD5 value.

[0081] In this step, data including the video integrity MD5 value constructed in step S500 is filled into the anti-counterfeiting mapping table. The security and anti-counterfeiting identification system thus forms a relatively complete production information mapping table, covering producer information and information related to production content. In actual use, the integrity of the entire video is verified by the video integrity MD5 value, and whether the video has been tampered with is verified by the video generation context MD5 value. The producer information and generated content information can be further tracked in the database through the video production information code, generated content code and corresponding video number, and the smallest granularity tracking and backtracking can be completed. It can not only achieve security and anti-counterfeiting, but also quickly identify any tampered unit by algorithm and provide the original comparison result.

[0082] In some optional implementations, the digital human AIGC video security and anti-counterfeiting method further includes:

[0083] Step S700: Search the security and anti-counterfeiting system mapping table based on the video integrity MD5 value of the video to be authenticated to determine whether the video to be authenticated is generated by the designated production system.

[0084] Step S800: extract the video generation context MD5 value from the image frame where the digital human exists, search the security and anti-counterfeiting system mapping table according to the video generation context MD5 value, and determine the degree of modification of the video being identified based on the video creation information and video production content mapped according to the video production information code and the generated content coding.

[0085] This embodiment mainly describes the decoding process of the digital human AIGC video identification system.

[0086] First, perform MD5 calculation on the video to be authenticated to obtain the video integrity MD5 value of the video to be authenticated, and then search it in the anti-counterfeiting system. If the corresponding video integrity MD5 value exists in the anti-counterfeiting system, it is preliminarily determined that the video is produced by the digital human AIGC system of this device and the video has integrity; if it does not exist, the video may not be produced by the digital human AIGC video system of this device or there is a possibility of forgery, and further judgment is required.

[0087] If a video is determined to be produced by the AIGC system, the security and anti-counterfeiting system can retrieve the video's generated context MD5 value, allowing for the query of sufficient information such as the digital human, producer, and generation time. This can be used by organizations such as corporate audits, legal and regulatory reviews, and judicial enforcement, addressing legal disputes, content ownership, and compliance assessments. Furthermore, the MD5 value of the video's generated context can fully trace and restore the original source material of the AIGC video-generated content, enabling even the most granular analysis, including all text, entire audio, images, and video, resolving a major dispute in AIGC content production. For example, it can quickly verify whether a particular passage is the original, authentic expression of the digital human host or has been maliciously tampered with.

[0088] In scenarios involving major authentication needs, the text, audio, and other content elements of the authentication video can be extracted as needed and verified one by one against the video traced back through the anti-counterfeiting system for secondary confirmation. This is an element that is not available in general authentication and verification systems.

[0089] If the video may not be produced by the digital human AIGC video system of this device or there is a possibility of forgery, the system can enter the local verification mechanism, that is, quickly identify the frame of the human anchor in the video, and process the specific area of ​​the character to extract the video generation context MD5 value. If the extraction is successful, it is determined that the video has been tampered with, and then the query retrieval mode can be entered. The video generation context MD5 value can be obtained by separating the video content materials such as text and audio, and confirming the tampered areas one by one to achieve the finest identification granularity; if it is unsuccessful, the video is not produced by the digital human AIGC system or is completely destroyed, and manual identification is required.

[0090] Through the reverse decoding process, the digital human authentication system can restore the original production information, including digital human information, producer, production time, platform, and the MD5 value of the content material. This method can effectively trace the production process of digital human videos to verify whether the video was generated using AIGC.

[0091] This application implements unified anti-counterfeiting coding for digital humans, producers, and production materials in the digital human AIGC anti-counterfeiting system, allowing the system's anti-counterfeiting to accurately restore who created what content using a digital human and when, and has a wider range of applicability. In industries such as finance, securities, news, and the military, which are highly sensitive to content compliance, it can well achieve the security and anti-counterfeiting management goals of tracking and tracing. After solving the risks of security applications, digital human AIGC technology will have a very large application market. The video generation context MD5 value creatively combines the self-increment ID of the security anti-counterfeiting system with the target video number, production information code, and generated content code to perform the MD5 algorithm to obtain the video generation context MD5 value. In this way, the generated video ID (including the test video ID) corresponding to each piece of content is integrated into the verification system, which reduces the possibility of tampering by the system administrator or owner from the underlying technical logic, and can prevent the security risks of internal administrators participating in the counterfeiting of digital humans AIGC.

[0092] This application not only strengthens the anti-counterfeiting protection of digital human AIGC videos, but also improves the integrity and reliability of video content through specific anti-counterfeiting areas and transparent pixel coding technology. Furthermore, the design of locating anti-counterfeiting areas and accelerating the detection of anti-counterfeiting codes further enhances system efficiency and user experience. This innovative anti-counterfeiting encryption and decoding process is of great value in the field of digital human production, providing strong technical support for the identification, traceability, and protection of digital humans.

[0093] The second aspect of the present application provides a digital human AIGC video security and anti-counterfeiting device corresponding to the above method, mainly comprising:

[0094] A video production information code generation module is used to generate a video production information code based on information related to the digital human AIGC video creation;

[0095] A content coding generation module is used to process the production content involved in the production process of the digital human AIGC video based on the MD5 algorithm to form a generated content code;

[0096] A video generation context MD5 value generation module, configured to process data including at least the video production information code and the generated content code based on an MD5 algorithm to form a video generation context MD5 value;

[0097] A coding module is used to insert the video generation context MD5 value in the area constructed by the digital human's body features into the image frame containing the digital human in the digital human AIGC video by coding in the format of transparent pixels;

[0098] A video integrity MD5 value generation module is used to generate a video integrity MD5 value from the digital human AIGC video based on the MD5 algorithm;

[0099] The security and anti-counterfeiting system mapping table construction module is used to construct a security and anti-counterfeiting system mapping table including at least the video number, the video production information code, the generated content code, the video generation context MD5 value and the video integrity MD5 value.

[0100] In some optional implementations, the video production information code generation module includes:

[0101] A digital human information processing unit, configured to convert digital human information related to the digital human AIGC video creation into a first video production information code;

[0102] A producer information processing unit, configured to convert producer information related to the digital human AIGC video creation into a second video production information code;

[0103] The first splicing unit is used to splice at least the first video production information code and the second video production information code to form the video production information code.

[0104] In some optional implementations, the content encoding generation module includes:

[0105] A sub-MD5 value calculation unit, configured to determine the sub-MD5 value of each production content involved in the production process of the digital human AIGC video based on the MD5 algorithm, wherein each production content includes text, audio, picture, and video;

[0106] The second concatenation unit is configured to concatenate the sub-MD5 values ​​to form the generated content code.

[0107] In some optional implementations, the area constructed by the digital human's body features includes: a triangular area constructed by the digital human's pupils and nose.

[0108] In some optional implementations, the digital human AIGC video security and anti-counterfeiting device further includes:

[0109] A video integrity MD5 value verification module is used to search the security and anti-counterfeiting system mapping table according to the video integrity MD5 value of the video to be authenticated, so as to determine whether the authenticated video is generated by the designated production system;

[0110] The video generation context MD5 value verification module is used to extract the video generation context MD5 value in the image frame where the digital human exists, search the security and anti-counterfeiting system mapping table according to the video generation context MD5 value, and determine the degree of modification of the video being authenticated based on the video creation information and video production content mapped according to the video production information code and the generated content coding.

[0111] According to the third aspect of the present application, a computer system includes a processor, a memory, and a computer program stored in the memory and runnable on the processor. The processor executes the computer program to implement the above-mentioned digital human AIGC video security and anti-counterfeiting method.

[0112] According to the fourth aspect of the present application, a readable storage medium stores a computer program, which is used to implement the above-mentioned digital human AIGC video security and anti-counterfeiting method when executed by a processor.

[0113] 2 shows a schematic diagram of a computer device 800 suitable for implementing the embodiments of the present application. The computer device shown in FIG2 is merely an example and should not limit the functionality and scope of use of the embodiments of the present application.

[0114] As shown in FIG2 , the computer device 800 includes a central processing unit (CPU) 801, which can perform various appropriate actions and processes according to a program stored in a read-only memory (ROM) 802 or a program loaded from a storage portion 708 into a random access memory (RAM) 803. Various programs and data required for the operation of the device 800 are also stored in the RAM 803. The CPU 801, ROM 802, and RAM 803 are connected to each other via a bus 804. An input / output (I / O) interface 805 is also connected to the bus 804.

[0115] The following components are connected to the I / O interface 805: an input section 806 including a keyboard, a mouse, and the like; an output section 807 including devices such as a cathode ray tube (CRT), a liquid crystal display (LCD), and a speaker; a storage section 808 including a hard disk; and a communication section 809 including a network interface card such as a LAN card or a modem. The communication section 809 performs communication processing via a network such as the Internet. A drive 810 is also connected to the I / O interface 805 as needed. A removable medium 811, such as a magnetic disk, an optical disk, a magneto-optical disk, or a semiconductor memory, is installed in the drive 810 as needed, so that computer programs read therefrom can be installed into the storage section 808 as needed.

[0116] In particular, according to the embodiment of the present application, the process described above with reference to the flowchart can be implemented as a computer software program. For example, the embodiment of the present application includes a computer program product, which includes a computer program carried on a computer-readable medium, and the computer program includes a program code for executing the method shown in the flowchart. In such an embodiment, the computer program can be downloaded and installed from the network through the communication part 809, and / or installed from the removable medium 811. When the computer program is executed by the central processing unit (CPU) 801, the above-mentioned functions defined in the method of the present application are executed. It should be noted that the computer storage medium of the present application can be a computer-readable signal medium or a computer-readable storage medium or any combination of the above two. The computer-readable storage medium can be, for example, but not limited to, a system, device or component of electricity, magnetism, light, electromagnetic, infrared, or semiconductor, or any combination of the above. More specific examples of computer-readable storage media may include, but are not limited to, an electrical connection having one or more conductors, a portable computer disk, a hard disk, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination thereof. In this application, a computer-readable storage medium may be any tangible medium that contains or stores a program that can be used by or in conjunction with an instruction execution system, apparatus, or device. In this application, a computer-readable signal medium may include a data signal propagated in baseband or as part of a carrier wave, which carries computer-readable program code. Such a propagated data signal may take a variety of forms, including, but not limited to, electromagnetic signals, optical signals, or any suitable combination thereof. A computer-readable signal medium may also be any computer-readable medium other than a computer-readable storage medium that can transmit, propagate, or transfer a program for use by or in conjunction with an instruction execution system, apparatus, or device. The program code embodied on a computer-readable medium may be transmitted using any suitable medium, including, but not limited to, wireless, wire, optical cable, RF, etc., or any suitable combination thereof.

[0117] The flow charts and block diagrams in the accompanying drawings illustrate the possible architecture, functions and operations of the systems, methods and computer program products according to various embodiments of the present application. In this regard, each box in the flow chart or block diagram can represent a module, program segment or a part of code, and the module, program segment or a part of code includes one or more executable instructions for realizing the specified logical function. It should also be noted that in some alternative implementations, the functions marked in the box can also occur in a sequence different from that marked in the accompanying drawings. For example, two boxes represented in succession can actually be executed substantially in parallel, and they can sometimes be executed in the opposite order, depending on the functions involved. It should also be noted that each box in the block diagram and / or flow chart, and the combination of the boxes in the block diagram and / or flow chart can be implemented by a dedicated hardware-based system that performs the specified function or operation, or can be implemented by a combination of dedicated hardware and computer instructions.

[0118] The modules or units described in the embodiments of this application may be implemented in software or hardware. The modules or units described may also be provided in a processor, and the names of these modules or units do not, in certain circumstances, limit the modules or units themselves.

[0119] The computer-readable storage medium provided in the fourth aspect of this application may be included in the apparatus described in the above embodiments, or may exist independently and not be incorporated into the apparatus. The computer-readable storage medium carries one or more programs, and when the one or more programs are executed by the apparatus, the data is processed according to the above method.

[0120] The above description is merely a specific embodiment of the present application, but the scope of protection of the present application is not limited thereto. Any changes or substitutions that can be easily conceived by a person skilled in the art within the technical scope disclosed in this application should be included in the scope of protection of the present application. Therefore, the scope of protection of the present application should be based on the scope of protection of the claims.

Claims

1. A digital human AIGC video security anti-counterfeiting method, characterized in that: include: Forming a video production information code based on information related to the digital human AIGC video creation; Process the production content involved in the production process of the digital human AIGC video based on the MD5 algorithm to form a generated content code; Processing data including at least the video production information code and the generated content code based on the MD5 algorithm to form a video generation context MD5 value; For the image frame containing the digital human in the digital human AIGC video, insert the video generation context MD5 value in a transparent pixel format coding manner in the area constructed by the digital human's body features; The digital human AIGC video is converted into a video integrity MD5 value based on the MD5 algorithm; Construct a security and anti-counterfeiting system mapping table that at least includes the video number, the video production information code, the generated content code, the video generation context MD5 value and the video integrity MD5 value.

2. The digital human AIGC video security anti-counterfeiting method according to claim 1, characterized in that: The forming of the video production information code comprises: The digital human information related to the digital human AIGC video creation is formed into the first video production information code; The producer information related to the digital human AIGC video creation is formed into a second video production information code; At least the first video production information code and the second video production information code are spliced ​​together to form the video production information code.

3. The digital human AIGC video security anti-counterfeiting method according to claim 1, characterized in that: Forming the generated content code includes: Determine the sub-MD5 value of each production content involved in the production process of the digital human AIGC video based on the MD5 algorithm, wherein each production content includes text, audio, picture and video; Each of the sub-MD5 values ​​is concatenated to form the generated content code.

4. The digital human AIGC video security anti-counterfeiting method according to claim 1, characterized in that: The area constructed by the digital human's physical features includes: a triangular area constructed by the digital human's two eye pupils and nose tip.

5. The digital human AIGC video security anti-counterfeiting method as claimed in claim 1, characterized in that: The digital human AIGC video security anti-counterfeiting method further comprises: According to the video integrity MD5 value of the video to be authenticated, a search is performed in the security anti-counterfeiting system mapping table to determine whether the video to be authenticated is generated by the designated production system; By extracting the video generation context MD5 value in the image frame where the digital human exists, searching in the security and anti-counterfeiting system mapping table according to the video generation context MD5 value, the retrieved video information is determined based on the video production information code and the video creation information and video production content mapped by the generated content encoding to determine the degree of modification of the video being identified.

6. A digital human AIGC video security anti-counterfeiting device, characterized in that: include: A video production information code generation module, used to form a video production information code based on information related to the digital human AIGC video creation; A generated content coding generation module is used to process the production content involved in the production process of the digital human AIGC video based on the MD5 algorithm to form a generated content coding; A video generation context MD5 value generation module, used for processing data including at least the video production information code and the generated content code based on the MD5 algorithm to form a video generation context MD5 value; A coding module, used for inserting the video generation context MD5 value in a transparent pixel format coding manner into the area constructed by the digital human body features in the image frame of the digital human in the digital human AIGC video; A video integrity MD5 value generation module, used for converting the digital human AIGC video into a video integrity MD5 value based on the MD5 algorithm; The security and anti-counterfeiting system mapping table construction module is used to construct a security and anti-counterfeiting system mapping table including at least the video number, the video production information code, the generated content code, the video generation context MD5 value and the video integrity MD5 value.

7. The digital human AIGC video security anti-counterfeiting device as claimed in claim 6, characterized in that: The video production information code generation module includes: A digital human information processing unit, used to convert the digital human information related to the digital human AIGC video creation into a first video production information code; A producer information processing unit, used to convert producer information related to the digital human AIGC video creation into a second video production information code; The first splicing unit is used to splice at least the first video production information code and the second video production information code to form the video production information code.

8. The digital human AIGC video security anti-counterfeiting device as claimed in claim 6, characterized in that: The content encoding generation module comprises: A sub-MD5 value calculation unit, used to determine the sub-MD5 value of each production content involved in the production process of the digital human AIGC video based on the MD5 algorithm, wherein each production content includes text, audio, picture and video; The second concatenation unit is used to concatenate the sub-MD5 values ​​to form the generated content code.

9. The digital human AIGC video security anti-counterfeiting device as claimed in claim 6, characterized in that: The area constructed by the digital human's physical features includes: a triangular area constructed by the digital human's two eye pupils and nose tip.

10. The digital human AIGC video security anti-counterfeiting device according to claim 6, characterized in that: The digital human AIGC video security anti-counterfeiting device also includes: A video integrity MD5 value verification module, used to search the security and anti-counterfeiting system mapping table according to the video integrity MD5 value of the video to be authenticated, so as to determine whether the authenticated video is generated by the designated production system; The video generation context MD5 value verification module is used to extract the video generation context MD5 value in the image frame where the digital human exists, search the security and anti-counterfeiting system mapping table according to the video generation context MD5 value, and determine the degree of modification of the video being authenticated based on the video creation information and video production content mapped by the video production information code and the generated content coding for the retrieved video information.

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