Short video tracing method and system, storage medium and electronic equipment

Abstract

The invention provides a short video tracing method and system, a storage medium and electronic equipment, and the method comprises the steps: obtaining an access request, and judging whether the access request is legal or not; if the access request is illegal, extracting a target URL feature from the access request, and traversing all URL honey points in a preset URL knowledge base according to the target URL feature to obtain a similarity value between the target URL feature and the URL feature of any URL honey point; screening out a target URL honey point from a preset URL knowledge base according to the similarity value, and obtaining IP address information, port information and URL path information of the target URL honey point; and modifying the access request according to the IP address information, the port information and the URL path information of the target URL honey point. According to the method and the device, some specific access requests are forwarded, so that the host deployed with the target URL honey point can attract an attacker to actively attack the target URL honey point by using the access request, the target URL honey point is easily and successfully trapped, and the network defense effect is improved.

Description

Technical Field

[0001] The present invention relates to the technical field of short video source tracing, and in particular to a short video source tracing method, system, storage medium and electronic device. Background Art

[0002] Short videos are short-duration video content recorded, edited and shared through electronic devices (such as smartphones, tablets, cameras, etc.). With its characteristics of being short and concise, easy to share, socially interactive, creative and emotionally resonant, short videos cater to the needs of modern people's fast-paced lives and diverse interests, and have become a popular form of Internet entertainment.

[0003] At the same time, there are some obvious problems with short videos, such as: 1) Bad content affects young people and their healthy growth; 2) False information misleads the audience: False information, false advertising, etc. may mislead the audience and cause damage to consumer rights; 3) Malicious attacks and rumor spread: Illegal videos may be used to spread rumors, maliciously attack individuals or groups, and have a negative impact on society; 4) Privacy leaks and infringement issues: Illegal videos on the platform may involve other people’s privacy leaks, intellectual property infringements and other issues, causing losses to individuals and businesses.

[0004] Short videos need to be traced for the following reasons: 1) Social responsibility and compliance requirements: As an important channel for information dissemination, short video platforms should assume social responsibility and ensure that the content disseminated is legal and compliant. 2) Prevent the spread of bad content. 3) Maintain network security and privacy: Some malicious short videos may involve network attacks, infringement of personal privacy and other issues. 4) Fight against false information and rumors: Tracing can help expose the producers of false information, reduce the spread of false information and rumors, and maintain the authenticity and credibility of information. 5) Legal accountability and punishment: For malicious dissemination of bad information, infringement of the rights and interests of others, tracing the source will help to hold the producers accountable in accordance with the law, serve as a warning, and maintain social order.

[0005] However, there are many difficulties in tracing short videos: 1) Anonymity and false identities: People who make illegal videos may use false identities or anonymous accounts, making it difficult to accurately determine their true identities and sources. 2) Massive videos: Short video platforms generate a large number of videos every day. Tracing the source of each video requires huge human and technical resources, making it difficult to achieve complete coverage. 3) Technical challenges: Developing powerful tracing technologies, including image recognition, data mining, user behavior analysis, etc., requires overcoming many technical difficulties, such as automatically identifying illegal content and establishing traceability links. Summary of the invention

[0006] The purpose of the present invention is to provide a short video tracing method, system, storage medium and electronic device, aiming to solve at least one problem in the background technology.

[0007] In a first aspect, the present invention provides a short video source tracing method, the method comprising:

[0008] When a user uploads a target video to the client, determine whether the target video is an original video;

[0009] If the target video is an original video, uploading a plurality of additional information corresponding to the client to the cloud at a first preset time, generating a random string in the cloud according to the plurality of additional information, and writing the random string into the target video;

[0010] Constructing a key-value relationship table of the original user in the cloud according to the additional information and random character strings respectively corresponding to the target video, and associating the key-value relationship table of the original user with the random character string, wherein the key-value relationship table of the original user includes a one-to-one correspondence table between the random character string and the additional information, a one-to-one correspondence table between the original user ID and the random character string, and a two-to-two correspondence table between the original user ID and the random character string and the video file name, wherein the original user ID is obtained when the user registers or logs in to the account on the client, and the video file name is obtained when the user uploads the video;

[0011] If the target video is a non-original video, the non-original video is marked as a non-original state, and a relationship table between random character strings and user IDs of non-original users is constructed according to the random character strings.

[0012] Furthermore, when the user uploads the target video to the client, the step of determining whether the target video is an original video includes:

[0013] Detecting whether the format of the target video is normal;

[0014] If normal, the definition of the target video is obtained based on the video definition algorithm, and it is determined whether the definition of the target video is greater than or equal to a preset definition threshold;

[0015] If the definition of the target video is greater than or equal to a preset definition threshold, extracting the digital watermark of the target video, and determining whether the target video has a random character string according to the digital watermark;

[0016] If the target video contains a random string, the target video is a non-original video;

[0017] If the target video does not have a random character string, the target video is an original video.

[0018] Furthermore, if the target video is an original video, uploading a plurality of additional information corresponding to the client to the cloud at a first preset time, generating a random string in the cloud according to the plurality of additional information, and writing the random string into the target video comprises:

[0019] Collecting various additional information through the client, including user name, real name, mobile phone number, ID number, device information unique identifier, collection time, and collection location string;

[0020] Set additional information using i1, ..., i x ,...,i7 represent 7 types of additional information respectively. The 7 types of additional information are converted into string information and i1,...i x ...i7 is concatenated to generate the concatenated string i all ;

[0021] According to the message digest algorithm, the concatenated string i all Perform summary generation operation to obtain a random string s all .

[0022] Furthermore, if normal, the step of obtaining the definition of the target video based on the video definition algorithm and determining whether the definition of the target video is greater than or equal to a preset definition threshold value further includes:

[0023] If the definition of the target video is less than the preset definition threshold, it will prompt that the video definition is insufficient. Please re-upload a video that meets the requirements.

[0024] Furthermore, the method further comprises:

[0025] When a user browses the target video and forwards it, the user ID of the user who forwards the target video is recorded and marked as non-original, and a key-value relationship table of non-original users is constructed based on the user ID of the user who forwards the target video.

[0026] In a second aspect, the present invention provides a short video source tracing system, the system comprising:

[0027] The video detection module is used to determine whether the target video is an original video when the user uploads the target video to the client;

[0028] An information acquisition module, for uploading a plurality of additional information corresponding to the client to the cloud at a first preset time if the target video is an original video, so as to generate a random string in the cloud according to the plurality of additional information, and write the random string into the target video;

[0029] A first relationship table construction module is used to construct a key-value relationship table of the original user in the cloud according to the additional information and random character strings respectively corresponding to the target video, and associate the key-value relationship table of the original user with the random character string, wherein the key-value relationship table of the original user includes a one-to-one correspondence table between the random character string and the additional information, a one-to-one correspondence table between the original user ID and the random character string, and a two-to-two correspondence table between the original user ID and the random character string and the video file name, wherein the original user ID is obtained when the user registers or logs in to the account on the client, and the video file name is obtained when the user uploads the video;

[0030] The second relationship table construction module is used to mark the non-original video as a non-original state if the target video is a non-original video, and to construct a relationship table between the random character string and the user ID of the non-original user according to the random character string.

[0031] In a third aspect, the present invention provides a storage medium, which stores one or more programs, which implement the above-mentioned short video tracing method when executed by a processor.

[0032] In a fourth aspect, the present invention provides an electronic device, the electronic device comprising a memory and a processor, wherein:

[0033] The memory is used to store computer programs;

[0034] When the processor is used to execute the computer program stored in the memory, the above-mentioned short video tracing method is implemented.

[0035] Compared with the prior art, the present invention has the following advantages:

[0036] 1. After the present invention uploads the short video (target video) to the cloud system through the client, the system simultaneously obtains the short video owner information, client information, etc. as additional information, generates a random string according to the additional information, and writes the random string into the short video as the digital watermark content, and saves the "one-to-one correspondence table of additional information and random string" in the cloud system. Short videos can be forwarded and copied during the dissemination process. Once the administrator finds that there is a need to trace the source of the video, he first extracts the watermark hidden in the video, that is, the random string, and then retrieves the additional information in the cloud system according to the random string, and then determines the source of the video. At the same time, all videos associated with this random string in the cloud system can be linked to query, so as to realize batch processing of videos.

[0037] 2. The present invention embeds a hidden digital watermark into each uploaded original short video in the system, stores the additional information of the related video in the cloud database, and constructs a one-to-one corresponding relationship table based on these additional information and random character strings and other information. On the one hand, these digital watermarks are invisible during the dissemination of short videos and do not affect the user's viewing experience. On the other hand, when it is found that the short video contains sensitive information, illegal content or false information, the source publisher of the video can be found quickly and accurately by querying the additional information of the video in the cloud database through the hidden digital watermark. The administrator can effectively delete or ban the problematic video by looking up the additional information of the digital watermark, reduce the scope of information dissemination, and maintain the health and order of the network environment. The advantages of the present invention: less watermark content is written, the watermark is robust, the written content is not directly related to the content, and the content cannot be directly identified except by the user and the platform. The big data platform is used to associate and retrieve information without relying on extracting information from the video.

[0038] 3. The present invention first generates a concatenated string that completely corresponds to the concatenated string based on a plurality of additional information, and then uses a message digest algorithm to digest the concatenated string i in order to prevent the direct use of the concatenated string from causing relevant information leakage. all The summary is generated to obtain a random string that corresponds to the concatenated string one by one. On the one hand, it avoids excessive additional information and prevents the directly used string from being too long, which affects computer efficiency. At the same time, using the random string in the subsequent relationship table construction can effectively avoid information leakage. BRIEF DESCRIPTION OF THE DRAWINGS

[0039] Figure 1 This is a flow chart of a short video source tracing method proposed in one embodiment of the present invention;

[0040] Figure 2 A schematic diagram of the structure of a short video source tracing system proposed in one embodiment of the present invention.

[0041] The following specific implementation manner will further illustrate the present invention in conjunction with the above-mentioned drawings. DETAILED DESCRIPTION

[0042] 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. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention. Unless otherwise defined, the technical terms or scientific terms used herein should be understood by people with general skills in the field to which the present invention belongs. "Including" and similar words used in this article mean that the elements or objects appearing before the word include the elements or objects listed after the word and their equivalents, without excluding other elements or objects.

[0043] like Figure 1 As shown, an embodiment of the present invention provides a short video source tracing method, the method includes steps S101 to S104, wherein:

[0044] Step S101: When a user uploads a target video to a client, it is determined whether the target video is an original video;

[0045] It should be pointed out that when a user uploads a target video, the first step is to detect whether the format of the target video is normal; if normal, the clarity of the target video is obtained based on the video clarity algorithm, and it is determined whether the clarity of the target video is greater than or equal to the preset clarity threshold.

[0046] By way of example but not limitation, a user uploads a video to a cloud system using a client. The video is first checked for compliance on the client. Considering the complexity of the algorithm and its feasibility on the mobile terminal, the example uses a reference-free video quality assessment algorithm BLIINDS-II (Blind Image Integrity Notator using DCT Statistics II). If the video clarity is higher than or equal to a minimum threshold, the video is uploaded to the cloud. Otherwise, a prompt "The video clarity is insufficient, please re-upload a video that meets the requirements" is displayed. The BLIINDS-II algorithm is only used in this implementation mode. In the present invention, an appropriate video clarity evaluation algorithm can be selected according to actual conditions.

[0047] Furthermore, if the clarity of the target video is greater than or equal to a preset clarity threshold, the digital watermark of the target video is extracted, and it is determined whether the target video has a random string based on the digital watermark; if the target video has a random string, the target video is a non-original video; if the target video does not have a random string, the target video is an original video.

[0048] Step S102: if the target video is an original video, uploading a plurality of additional information corresponding to the client to the cloud at a first preset time, generating a random string in the cloud according to the plurality of additional information, and writing the random string into the target video;

[0049] It should be noted that when a user installs the software client on a mobile device, when the user uses the client for the first time, he or she will obtain a user name, namely Username. When registering, the real-name system records the user's mobile phone number PhoneNum, name XM and ID number Sfzjh, and then the system automatically assigns a unique user ID, namely userid, to the user. The user shoots a video using the video recording software or client that comes with the mobile device.

[0050] In addition, the additional information collected by the client includes: user name Username, real name XM, mobile phone number PhoneNum, ID number Sfzjh, device information unique identifier D_infoID, collection time C_time, collection location string C_location, etc., which are uploaded to the system to identify the information of the video owner and video attribute information.

[0051] Specifically, in the process of generating a random string, first set the video additional information to use i1,...i x ...i7 identifier, 1,...,7 represent 7 types of additional information respectively. First, the 7 types of information are converted into text string format, and then randomly sorted. The 7 randomly sorted strings are concatenated to generate i all , and then use the message digest algorithm SHA3-256 to add the additional information i all Perform summary generation operation to generate a random string s all Then, according to the digital video watermarking algorithm FMO Watermarking, the "random string" s all Written into the video, the algorithm uses the Flexible Macroblock Ordering (FMO) in H.264 to embed the watermark, which can increase the robustness of the watermark, because FMO can make the watermark information more evenly distributed in the video, thereby improving the ability to resist attacks. FMO Watermarking is only used to illustrate this embodiment. In the present invention, a highly robust watermarking algorithm can be selected according to actual conditions.

[0052] It should be noted that, by first generating a completely corresponding concatenated string based on a variety of additional information, in order to prevent the direct use of the concatenated string from causing relevant information leakage, a message digest algorithm is used to digest the concatenated string i allThe summary is generated to obtain a random string that corresponds to the concatenated string one by one. On the one hand, it avoids excessive additional information and prevents the directly used string from being too long, which affects computer efficiency. At the same time, using the random string in the subsequent relationship table construction can effectively avoid information leakage.

[0053] Step S103: constructing a key-value relationship table of the original user in the cloud according to the additional information and random character strings respectively corresponding to the target video, and associating the key-value relationship table of the original user with the random character string, wherein the key-value relationship table of the original user includes a one-to-one correspondence table between the random character string and the additional information, a one-to-one correspondence table between the original user ID and the random character string, and a two-to-two correspondence table between the original user ID and the random character string and the video file name, wherein the original user ID is obtained when the user registers or logs in to the account on the client, and the video file name is obtained when the user uploads the video;

[0054] Step S104: if the target video is a non-original video, the non-original video is marked as a non-original state, and a relationship table between random character strings and user IDs of non-original users is constructed according to the random character strings.

[0055] It should be pointed out that in the cloud system, a Redis database is built, and four relational tables are constructed in the Redis data. Table 1 Video additional information table Videoinfo_Str_Table constructs a "random string" s all and "additional information" i1,...i x ...i7 one-to-one correspondence, Table 2 Userid_Str_Table constructs the "random string" s all One-to-one correspondence with userid, Table 3 Userid_Froward_Str_Table constructs the non-original user userid and "random string" s all Table 4 Videoname_Str_Table constructs userid, "video file name" and s all The corresponding relationship between the three. The four tables are stored in the Redis database.

[0056] By constructing the above-mentioned relationship table, the video can be quickly traced. Specifically, when the video needs to be traced for some reason, the administrator extracts the digital watermark in the video, that is, the "identification string", and searches the "string and video information table" in the cloud system based on the "identification string". The "additional information" corresponding to the video can be queried, and the information such as the owner of the video can be obtained to achieve traceability.

[0057] In addition, based on the extracted "identification string", all "userids" that use the video are queried in the cloud system, including the original user ID and the non-original user ID, so that the video records belonging to the corresponding users can be processed and the cache files of the video in the client can be remotely controlled, such as remote deletion, prohibition of playback, etc.

[0058] When a video is found to be illegal, the watermark information of the video, i.e. the "identification string", is extracted from the video content. all The user containing the "identification string" is queried from Userid_Str_Table and Userid_Froward_Str_Table, and then the video file name is found from Table 4 Videoname_Str_Table, and the video files are batch processed from the user's video records.

[0059] In addition, when the current system determines that a video has violated the rules, it extracts the video watermark information, i.e., the "identification string", from the video content. all Then, the Videoinfo_Str_Table and Userid_Str_Table in the Redis database of the cloud system are searched for the data containing the "identification string s all " record, get the userid who uploaded the video, and the corresponding video "additional information" i1,...i x ...i7, you can trace back the additional information of the video (username Username, real name XM, mobile phone number PhoneNum, ID number Sf).

[0060] In some embodiments, in addition to uploading, forwarding by non-original users may also be involved, that is, when a user browses the target video and forwards it, the user ID of the user who forwards the target video is recorded and marked as non-original, and a key-value relationship table of non-original users is constructed based on the user ID of the user who forwards the target video, that is, the user ID is also associated with a random string to obtain a relationship table.

[0061] That is to say, since all videos that need to be traced must have a random string, the corresponding original user ID and all non-original user IDs can be obtained based on the random string, and then the videos to which they belong can be traced and processed in a targeted manner based on all user IDs.

[0062] In summary, the above short video source tracing method has the following advantages:

[0063] 1. After the present invention uploads the short video (target video) to the cloud system through the client, the system simultaneously obtains the short video owner information, client information, etc. as additional information, generates a random string according to the additional information, and writes the random string into the short video as the digital watermark content, and saves the "one-to-one correspondence table of additional information and random string" in the cloud system. Short videos can be forwarded and copied during the dissemination process. Once the administrator finds that there is a need to trace the source of the video, he first extracts the watermark hidden in the video, that is, the random string, and then retrieves the additional information in the cloud system according to the random string, and then determines the source of the video. At the same time, all videos associated with this random string in the cloud system can be linked to query, so as to realize batch processing of videos.

[0064] 2. The present invention embeds a hidden digital watermark into each uploaded original short video in the system, stores the additional information of the related video in the cloud database, and constructs a one-to-one corresponding relationship table based on these additional information and random character strings and other information. On the one hand, these digital watermarks are invisible during the dissemination of short videos and do not affect the user's viewing experience. On the other hand, when it is found that the short video contains sensitive information, illegal content or false information, the source publisher of the video can be found quickly and accurately by querying the additional information of the video in the cloud database through the hidden digital watermark. The administrator can effectively delete or ban the problematic video by looking up the additional information of the digital watermark, reduce the scope of information dissemination, and maintain the health and order of the network environment. The advantages of the present invention: less watermark content is written, the watermark is robust, the written content is not directly related to the content, and the content cannot be directly identified except by the user and the platform. The big data platform is used to associate and retrieve information without relying on extracting information from the video.

[0065] like Figure 2 As shown, an embodiment of the present invention further provides a short video source tracing system, the system comprising:

[0066] The video detection module 10 is used to determine whether the target video is an original video when the user uploads the target video to the client;

[0067] The information acquisition module 20 is used for uploading a plurality of additional information corresponding to the client to the cloud at a first preset time if the target video is an original video, so as to generate a random string in the cloud according to the plurality of additional information, and write the random string into the target video;

[0068] The first relationship table construction module 30 is used to construct a key-value relationship table of the original user in the cloud according to the additional information and random character strings respectively corresponding to the target video, and associate the key-value relationship table of the original user with the random character string, wherein the key-value relationship table of the original user includes a one-to-one correspondence table between the random character string and the additional information, a one-to-one correspondence table between the original user ID and the random character string, and a two-to-two correspondence table between the original user ID and the random character string and the video file name, wherein the original user ID is obtained when the user registers or logs in to the account on the client, and the video file name is obtained when the user uploads the video;

[0069] The second relationship table construction module 40 is used for marking the target video as a non-original video if the target video is a non-original video, and constructing a relationship table between the random character string and the user ID of the non-original user according to the random character string.

[0070] On the other hand, the present invention further proposes a storage medium on which one or more programs are stored, and when the program is executed by a processor, the above-mentioned short video tracing method is implemented.

[0071] On the other hand, the present invention further proposes an electronic device, including a memory and a processor, wherein the memory is used to store computer programs, and the processor is used to execute the computer programs stored in the memory to implement the above-mentioned short video tracing method.

[0072] Those skilled in the art will appreciate that the logic and / or steps represented in the flowchart or otherwise described herein, for example, may be considered as an ordered list of executable instructions for implementing logical functions, and may be embodied in any computer-readable medium for use by an instruction execution system, device or apparatus (such as a computer-based system, a system including a processor, or other system that can fetch instructions from an instruction execution system, device or apparatus and execute instructions), or in conjunction with such instruction execution systems, devices or apparatuses. For purposes of this specification, "computer-readable medium" may be any device that can contain, store, communicate, propagate or transmit a program for use by an instruction execution system, device or apparatus, or in conjunction with such instruction execution systems, devices or apparatuses.

[0073] More specific examples of computer-readable media (a non-exhaustive list) include the following: an electrical connection with one or more wires (electronic device), a portable computer disk case (magnetic device), a random access memory (RAM), a read-only memory (ROM), an erasable and programmable read-only memory (EPROM or flash memory), an optical fiber device, and a portable compact disk read-only memory (CDROM). In addition, the computer-readable medium may even be a paper or other suitable medium on which the program is printed, since the program may be obtained electronically, for example, by optically scanning the paper or other medium, followed by editing, deciphering or, if necessary, processing in another suitable manner, and then stored in a computer memory.

[0074] It should be understood that the various parts of the present invention can be implemented by hardware, software, firmware or a combination thereof. In the above-mentioned embodiments, a plurality of steps or methods can be implemented by software or firmware stored in a memory and executed by a suitable instruction execution system. For example, if implemented by hardware, as in another embodiment, it can be implemented by any one of the following technologies known in the art or a combination thereof: a discrete logic circuit having a logic gate circuit for implementing a logic function for a data signal, a dedicated integrated circuit having a suitable combination of logic gate circuits, a programmable gate array (PGA), a field programmable gate array (FPGA), etc.

[0075] Although the embodiments of the present invention are described in detail above, it is obvious to those skilled in the art that various modifications and variations can be made to these embodiments. However, it should be understood that such modifications and variations are within the scope and spirit of the present invention as described in the claims. Moreover, the present invention described herein may have other embodiments and may be implemented or realized in a variety of ways.

Claims

1. A short video source tracing method, characterized in that: The method comprises: When a user uploads a target video to the client, determine whether the target video is an original video; If the target video is an original video, uploading a plurality of additional information corresponding to the client to the cloud at a first preset time, generating a random string in the cloud according to the plurality of additional information, and writing the random string into the target video; Constructing a key-value relationship table of the original user in the cloud according to the additional information and random character strings respectively corresponding to the target video, and associating the key-value relationship table of the original user with the random character string, wherein the key-value relationship table of the original user includes a one-to-one correspondence table between the random character string and the additional information, a one-to-one correspondence table between the original user ID and the random character string, and a two-to-two correspondence table between the original user ID and the random character string and the video file name, wherein the original user ID is obtained when the user registers or logs in to the account on the client, and the video file name is obtained when the user uploads the video; If the target video is a non-original video, the non-original video is marked as a non-original state, and a relationship table between random character strings and user IDs of non-original users is constructed according to the random character strings.

2. The short video source tracing method according to claim 1, characterized in that: When the user uploads the target video to the client, the step of determining whether the target video is an original video includes: Detecting whether the format of the target video is normal; If normal, the definition of the target video is obtained based on the video definition algorithm, and it is determined whether the definition of the target video is greater than or equal to a preset definition threshold; If the definition of the target video is greater than or equal to a preset definition threshold, extracting the digital watermark of the target video, and determining whether the target video has a random character string according to the digital watermark; If the target video contains a random string, the target video is a non-original video; If the target video does not have a random character string, the target video is an original video.

3. The short video source tracing method according to claim 1, characterized in that: If the target video is an original video, the steps of uploading multiple additional information corresponding to the client to the cloud at a first preset time, generating a random string in the cloud according to the multiple additional information, and writing the random string into the target video include: Collecting various additional information through the client, including user name, real name, mobile phone number, ID number, device information unique identifier, collection time, and collection location string; Set additional information using i1, ..., i x ,...,i7 represent 7 types of additional information respectively. The 7 types of additional information are converted into string information and i1,...i x ...i7 is concatenated to generate the concatenated string i all ; According to the message digest algorithm, the concatenated string i all Perform summary generation operation to obtain a random string s a ll .

4. The short video source tracing method according to claim 2, characterized in that: If the result is normal, the definition of the target video is obtained based on the video definition algorithm, and after the step of determining whether the definition of the target video is greater than or equal to a preset definition threshold, the method further includes: If the definition of the target video is less than the preset definition threshold, it will prompt that the video definition is insufficient. Please re-upload a video that meets the requirements.

5. The short video source tracing method according to any one of claims 1 to 4, characterized in that: The method further comprises: When a user browses the target video and forwards it, the user ID of the user who forwards the target video is recorded and marked as non-original, and a key-value relationship table of non-original users is constructed based on the user ID of the user who forwards the target video.

6. A short video source tracing system, characterized in that: The system comprises: The video detection module is used to determine whether the target video is an original video when the user uploads the target video to the client; An information acquisition module, for uploading a plurality of additional information corresponding to the client to the cloud at a first preset time if the target video is an original video, so as to generate a random string in the cloud according to the plurality of additional information, and write the random string into the target video; A first relationship table construction module is used to construct a key-value relationship table of the original user in the cloud according to the additional information and random character strings respectively corresponding to the target video, and associate the key-value relationship table of the original user with the random character string, wherein the key-value relationship table of the original user includes a one-to-one correspondence table between the random character string and the additional information, a one-to-one correspondence table between the original user ID and the random character string, and a two-to-two correspondence table between the original user ID and the random character string and the video file name, wherein the original user ID is obtained when the user registers or logs in to the account on the client, and the video file name is obtained when the user uploads the video; The second relationship table construction module is used to mark the non-original video as a non-original state if the target video is a non-original video, and to construct a relationship table between the random character string and the user ID of the non-original user according to the random character string.

7. A storage medium, characterized in that: The storage medium stores one or more programs, which, when executed by the processor, implement the short video tracing method as described in any one of claims 1 to 5.

8. An electronic device, comprising a memory and a processor, wherein: The memory is used to store computer programs; When the processor is used to execute a computer program stored in the memory, it implements the short video tracing method as described in any one of claims 1-5.

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