Anti-counterfeiting data right confirmation method, device, system, equipment, medium and product

Abstract

The invention provides an anti-counterfeiting data right confirmation method, device, system, equipment, medium and product, and relates to the technical field of right confirmation, the anti-counterfeiting data right confirmation method is applied to the right confirmation system, and comprises the following steps: receiving a first feature set sent by a right confirmation application agent; determining a first insertion rule corresponding to the first to-be-confirmed right data and first insertion content corresponding to the first to-be-confirmed right data; sending the first insertion rule and the first insertion content to a right confirmation application agent, and receiving a second feature set sent by the right confirmation application agent; and determining an ownership certificate corresponding to the first to-be-confirmed right data and sending the ownership certificate to the right confirmation application agent based on the distinction degree between each feature in the second feature set and / or the first feature set and the feature set library of the confirmed right data. The first to-be-confirmed right data is prevented from being tampered, and then the right of the right holder of the first to-be-confirmed right data corresponding to the ownership certificate is denied, so that the legal right of the right holder is guaranteed.

Description

TECHNICAL FIELD

[0001] The present application relates to the field of data rights protection, and in particular to a data rights protection method, device, system, equipment, medium and product for preventing forgery. BACKGROUND

[0002] At present, most of the data rights protection methods for preventing forgery match the original rights protection data with the rights protection database, and generate a rights certificate for the original rights protection data when the matching is successful. However, the existing data rights protection method for preventing forgery has the defect that the process of generating the rights certificate is simple, so that the data corresponding to the generated rights certificate is easily forged by tampering, and the legitimate rights and interests of the right holder cannot be protected. SUMMARY

[0003] The present application provides a data rights protection method, device, system, equipment, medium and product for preventing forgery, which solves the defect that the process of generating the rights certificate is simple in the prior art, so that the data corresponding to the generated rights certificate is easily forged by tampering, and the legitimate rights and interests of the right holder cannot be protected, and realizes feature extraction of the second to-be-protected data after inserting content in the first to-be-protected data, comprehensive generation of a rights certificate according to the first feature set and / or the second feature set, prevention of the features and / or feature discrimination degrees in the first feature set and / or the second feature set of the first to-be-protected data corresponding to the rights certificate from being forged by tampering with the first to-be-protected data, and negation of the right holder's rights and interests of the first to-be-protected data corresponding to the rights certificate, so as to protect the legitimate rights and interests of the right holder.

[0004] The present application provides a data rights protection method for preventing forgery, applied to a rights protection system, comprising the following steps: receiving a first feature set sent by a rights protection application agent; the first feature set is obtained by the rights protection application agent based on a first feature extraction algorithm and by performing feature extraction on first to-be-protected data; determining a first insertion rule corresponding to the first to-be-protected data and a first insertion content corresponding to the first to-be-protected data based on the discrimination degrees between each feature in the first feature set and a feature set library of rights-protected data; sending the first insertion rule and the first insertion content to the rights protection application agent, receiving a second feature set sent by the rights protection application agent, the second feature set being obtained by the rights protection application agent based on a second feature extraction algorithm and by performing feature extraction on second to-be-protected data, the second to-be-protected data being obtained by the rights protection application agent based on the first insertion rule and by inserting the first insertion content into a corresponding position in the first to-be-protected data; determine the target ownership certificate corresponding to the first data to be authorized based on the discrimination degree between each feature in the second feature set and the feature set library of the authorized data, and send the target ownership certificate to the authorization application agent.

[0005] According to the anti-forgery data authorization method provided by the application, the first insertion rule includes a first insertion sub-rule, and the first insertion content includes a first insertion sub-content. The determination of the first insertion rule corresponding to the first data to be authorized and the first insertion content corresponding to the first data to be authorized based on the discrimination degree between each feature in the first feature set and the feature set library of the authorized data includes: determining a first sub-feature set in the first feature set that meets the discrimination degree condition based on the discrimination degree between each feature in the first feature set and the feature set library of the authorized data; and generating the first insertion sub-rule and the first insertion sub-content based on the first sub-feature set.

[0006] According to the anti-forgery data authorization method provided by the application, the first insertion rule includes a second insertion sub-rule, and the first insertion content includes a second insertion sub-content. The determination of the first insertion rule corresponding to the first data to be authorized and the first insertion content corresponding to the first data to be authorized based on the discrimination degree between each feature in the first feature set and the feature set library of the authorized data includes: in the case that the discrimination degree between a feature in the first feature set and the feature set library of the authorized data does not meet the discrimination degree condition and the number of times of sending the ownership application by the authorization application agent does not exceed the threshold, sending a first unqualified feature in the first feature set that does not meet the discrimination degree condition to the authorization application agent; receiving a second sub-feature set sent by the authorization application agent; wherein the second sub-feature set includes a feature different from the first unqualified feature, or a new feature value corresponding to the first unqualified feature extracted from the first data to be authorized by using a third feature extraction algorithm; the third feature extraction algorithm is different from the first feature extraction algorithm; and generating the second insertion sub-rule and the second insertion sub-content based on the discrimination degree between each feature in the second sub-feature set and the feature set library of the authorized data.

[0007] According to the anti-counterfeiting data right method provided by the application, the second inserted sub-rule and the second inserted sub-content are generated based on the discrimination degree between each feature in the second sub-feature set and the feature set library of the right data, comprising: determining a third sub-feature set in the second sub-feature set that meets the discrimination degree condition based on the discrimination degree between each feature in the second sub-feature set and the feature set library of the right data; generating the second inserted sub-rule and the second inserted sub-content based on the third sub-feature set.

[0008] According to the anti-counterfeiting data right method provided by the application, the second inserted sub-rule and the second inserted sub-content are generated based on the discrimination degree between each feature in the second sub-feature set and the feature set library of the right data, comprising: in the case that there is a feature in the second sub-feature set that does not meet the discrimination degree condition and the number of ownership applications sent by the right application agent does not exceed the number threshold, sending the second unpassed feature in the second sub-feature set that does not meet the discrimination degree condition to the right application agent; receiving the fourth sub-feature set sent by the right application agent; wherein the fourth sub-feature set includes features different from the second unpassed feature, or new feature values corresponding to the second unpassed feature re-extracted from the first data to be righted using a fourth feature extraction algorithm; the fourth feature extraction algorithm is different from the first feature extraction algorithm and the third feature extraction algorithm; generating the second inserted sub-rule and the second inserted sub-content based on the discrimination degree between each feature in the fourth sub-feature set and the feature set library of the right data.

[0009] According to the anti-counterfeiting data right method provided by the application, the second inserted sub-rule and the second inserted sub-content are generated based on the discrimination degree between each feature in the second sub-feature set and the feature set library of the right data, comprising: determining a third sub-feature set in the second sub-feature set that meets the discrimination degree condition based on the discrimination degree between each feature in the second sub-feature set and the feature set library of the right data; generating the second inserted sub-rule and the second inserted sub-content based on the third sub-feature set.

[0010] According to the anti-forgery data right confirmation method provided by the application, after the first right confirmation certificate corresponding to the first to-be-determined data is generated based on the fifth sub-feature set, the method further comprises: in the case that the distinguishing degree between the features in the second feature set and / or the first feature set and the feature set library of the confirmed data does not meet the distinguishing degree condition and the number of right confirmation application sent by the right confirmation application agent does not exceed the threshold, sending the third unqualified features that do not meet the distinguishing degree condition to the right confirmation application agent; receiving the sixth sub-feature set sent by the right confirmation application agent; wherein the sixth sub-feature set is obtained by the right confirmation application agent based on a fifth feature extraction algorithm and by extracting features from the second to-be-confirmed data, the fifth feature extraction algorithm is different from the second feature extraction algorithm; or, receiving the sixth sub-feature set sent by the right confirmation application agent, and sending the second insertion rule and the second insertion content to the right confirmation application agent; wherein the sixth sub-feature set is obtained by the right confirmation application agent based on a sixth feature extraction algorithm and by extracting features from the third to-be-confirmed data, the third to-be-confirmed data is obtained by replacing the content of the object corresponding to the sixth sub-feature set in the second to-be-confirmed data with the second insertion content according to the second insertion rule; the sixth feature extraction algorithm can be the same as or different from the second feature extraction algorithm.

[0011] According to the anti-forgery data right confirmation method provided by the application, after the first right confirmation certificate corresponding to the first to-be-determined data is generated based on the fifth sub-feature set, the method further comprises: in the case that the distinguishing degree between the features in the second feature set and / or the first feature set and the feature set library of the confirmed data does not meet the distinguishing degree condition and the number of right confirmation application sent by the right confirmation application agent does not exceed the threshold, sending the third unqualified features that do not meet the distinguishing degree condition to the right confirmation application agent; receiving the sixth sub-feature set sent by the right confirmation application agent; wherein the sixth sub-feature set is obtained by the right confirmation application agent based on a fifth feature extraction algorithm and by extracting features from the second to-be-confirmed data, the fifth feature extraction algorithm is different from the second feature extraction algorithm; or, receiving the sixth sub-feature set sent by the right confirmation application agent, and sending the second insertion rule and the second insertion content to the right confirmation application agent; wherein the sixth sub-feature set is obtained by the right confirmation application agent based on a sixth feature extraction algorithm and by extracting features from the third to-be-confirmed data, the third to-be-confirmed data is obtained by replacing the content of the object corresponding to the sixth sub-feature set in the second to-be-confirmed data with the second insertion content according to the second insertion rule; the sixth feature extraction algorithm can be the same as or different from the second feature extraction algorithm.

[0012] According to the anti-forgery data right method provided by the application, after receiving the sixth sub-feature set sent by the right application agent, the method further comprises: in the case that the discrimination degree between the features in the sixth sub-feature set and the feature set library of the righted data does not meet the discrimination degree condition and the number of ownership application sent by the right application agent does not exceed the number threshold, sending the fourth unpassed features in the sixth sub-feature set that do not meet the discrimination degree condition to the right application agent; receiving the eighth sub-feature set sent by the right application agent; wherein the eighth sub-feature set is obtained by the right application agent based on a seventh feature extraction algorithm for feature extraction on the second to-be-righted data, and the seventh feature extraction algorithm is different from the second feature extraction algorithm and the fifth feature extraction algorithm; or, receiving the eighth sub-feature set sent by the right application agent, and simultaneously sending the third insertion rule and the third insertion content to the right application agent; wherein the eighth sub-feature set is obtained by the right application agent based on an eighth feature extraction algorithm for feature extraction on fourth to-be-righted data, the fourth to-be-righted data is obtained by replacing the content of the object corresponding to the eighth sub-feature set in the third to-be-righted data with the third insertion content according to the third insertion rule; and the eighth feature extraction algorithm can be the same as or different from the second feature extraction algorithm.

[0013] According to the anti-forgery data right method provided by the application, the first ownership certificate is determined as the target ownership certificate and sent to the right application agent in the case that the first ownership certificate is the same as the second ownership certificate; and the second ownership certificate is determined as the target ownership certificate and sent to the right application agent in the case that the first ownership certificate is different from the second ownership certificate.

[0014] According to the anti-forgery data right method provided by the application, the setting form of the first / second / third insertion content and the first / second / third insertion rule comprises at least one of the following: rule, configuration file, button, circle, check, mark, key, pulley, menu, voice, video, eye contact, gesture, text, biological electrical signal, and virtual reality.

[0015] The application further provides an anti-forgery data right method applied to a right application agent, and the anti-forgery data right method comprises the following steps: determining first to-be-righted data; performing feature extraction on the first to-be-righted data based on a first feature extraction algorithm to obtain a first feature set; send the first feature set to the right system, receive the first insertion rule and the first insertion content corresponding to the first feature set sent by the right system; the first insertion rule and the first insertion content are generated by the right system based on the degree of distinction between each feature in the first feature set and the feature set library of the right data; insert the first insertion content into the corresponding position in the first to be right data based on the first insertion rule, to obtain the second to be right data; extract features from the second to be right data based on a second feature extraction algorithm to obtain a second feature set; send the second feature set to the right system, and receive the target ownership certificate corresponding to the first to be right data sent by the right system, wherein the target ownership certificate is determined by the right system based on the degree of distinction between each feature in the second feature set and / or the first feature set and the feature set library of the right data.

[0016] According to the anti-forgery data right method provided by the application, the second feature set is sent to the right system, and the target ownership certificate corresponding to the first to be right data sent by the right system is received, which comprises: the second feature set is sent to the right system, and the first failed feature sent by the right system is received; select a feature different from the first failed feature as a second sub-feature set, or re-extract a new feature value corresponding to the first failed feature from the first to be right data by using a third feature extraction algorithm as a second sub-feature set; the second sub-feature set is sent to the right system, and the target ownership certificate sent by the right system is received, wherein the target ownership certificate is generated by the right system based on the passing feature in the second sub-feature set that meets the distinction condition.

[0017] The application also provides an anti-forgery data right device, comprising the following modules: The first receiving module is used for receiving the first feature set sent by the right application agent; the first feature set is obtained by the right application agent based on the first feature extraction algorithm and the feature extraction of the first to be right data; The first determining module is used for determining the first insertion rule corresponding to the first to be right data and the first insertion content corresponding to the first to be right data based on the degree of distinction between each feature in the first feature set and the feature set library of the right data. The first transmission module is configured to send the first insertion rule and the first insertion content to the right application agent, and receive a second feature set sent by the right application agent; the second feature set is obtained by the right application agent based on a second feature extraction algorithm and second to-be-right data; the second to-be-right data is obtained by the right application agent based on the first insertion rule and the first insertion content inserted into a corresponding position of the first to-be-right data. The second determination module is configured to determine a target right attribute certificate corresponding to the first to-be-right data based on a discrimination degree between each feature in the second feature set and / or the first feature set and a feature set library of the right data, and send the target right attribute certificate to the right application agent.

[0018] The application further provides a data right confirmation device for preventing forgery, which comprises the following modules. The third determination module is configured to determine the first to-be-right data. The first extraction module is configured to extract features of the first to-be-right data based on a first feature extraction algorithm, and obtain a first feature set. The second transmission module is configured to send the first feature set to a right system, and receive a first insertion rule and corresponding first insertion content corresponding to the first feature set sent by the right system; the first insertion rule and the first insertion content are generated by the right system based on a discrimination degree between each feature in the first feature set and a feature set library of the right data. The insertion module is configured to insert the first insertion content into a corresponding position in the first to-be-right data based on the first insertion rule, and obtain second to-be-right data. The second extraction module is configured to extract features of the second to-be-right data based on a second feature extraction algorithm, and obtain a second feature set. The third transmission module is configured to send the second feature set to the right system, and receive a target right attribute certificate corresponding to the first to-be-right data sent by the right system; the target right attribute certificate is determined by the right system based on a discrimination degree between each feature in the second feature set and a feature set library of the right data.

[0019] The application further provides a data right confirmation system for preventing forgery, which comprises a right system and a right application agent, and wherein: The right confirmation application agent is configured to determine first to-be-confirmed data, perform feature extraction on the first to-be-confirmed data based on a first feature extraction algorithm to obtain a first feature set, send the first feature set to a right confirmation system, insert first insertion content into a corresponding position in the first to-be-confirmed data based on a first insertion rule to obtain second to-be-confirmed data, perform feature extraction on the second to-be-confirmed data based on a second feature extraction algorithm to obtain a second feature set, send the second feature set to the right confirmation system, and receive a target right confirmation certificate corresponding to the first to-be-confirmed data sent by the right confirmation system. The right confirmation system is configured to receive the first feature set sent by the right confirmation application agent, determine a first insertion rule corresponding to the first to-be-confirmed data and first insertion content corresponding to the first to-be-confirmed data based on a degree of distinction between each feature in the first feature set and a feature set library of already-confirmed data, send the first insertion rule and the first insertion content to the right confirmation application agent, receive the second feature set sent by the right confirmation application agent, determine a target right confirmation certificate corresponding to the first to-be-confirmed data based on a degree of distinction between each feature in the second feature set and the feature set library of already-confirmed data, and send the target right confirmation certificate to the right confirmation application agent.

[0020] The application further provides an electronic device, including a memory, a processor, and a computer program stored in the memory and executable on the processor, and the processor implements the anti-forgery data right confirmation method according to any one of the above when executing the computer program.

[0021] The application further provides a non-transitory computer readable storage medium, which stores a computer program, and the computer program is executable on a processor to implement the anti-forgery data right confirmation method according to any one of the above.

[0022] The application further provides a computer program product, which includes a computer program, and the computer program is executable on a processor to implement the anti-forgery data right confirmation method according to any one of the above.

[0023] The present invention provides a data ownership confirmation method, apparatus, system, device, medium, and product for preventing counterfeiting. The method involves receiving a first feature set sent by an ownership confirmation application agent. This first feature set is obtained by the ownership confirmation application agent from first data to be confirmed using a first feature extraction algorithm. Based on the distinguishability between each feature in the first feature set and a feature set library of already confirmed data, a first insertion rule and a first insertion content corresponding to the first data to be confirmed are determined. The first insertion rule and the first insertion content are sent to the ownership confirmation application agent. The method also involves receiving a second feature set sent by the ownership confirmation application agent. This second feature set is obtained by the ownership confirmation application agent from second data to be confirmed using a second feature extraction algorithm. The second data to be confirmed is the data of the ownership confirmation application agent. The agent, based on the first insertion rule, inserts the first inserted content into the corresponding position in the first data to be confirmed; based on the distinguishability between each feature in the second feature set and / or the first feature set and the feature set library of the confirmed data, the agent determines the target ownership certificate corresponding to the first data to be confirmed and sends it to the ownership application agent. In this way, by performing feature extraction on the second data to be confirmed after inserting content into the first data to be confirmed, and generating an ownership certificate based on the first feature set and / or the second feature set, the agent prevents the forgery of features and / or feature distinguishability in the first feature set and / or the second feature set of the first data to be confirmed by tampering with the first data to be confirmed, thereby denying the rights and interests of the right holder of the first data to be confirmed, and thus protecting the legitimate rights and interests of the right holder. Attached Figure Description

[0024] To more clearly illustrate the technical solutions in this invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of this invention. For those skilled in the art, other drawings can be obtained from these drawings without creative effort.

[0025] Figure 1 This is one of the flowcharts illustrating the anti-counterfeiting data ownership confirmation method provided by the present invention.

[0026] Figure 2 This is the second flowchart of the data ownership confirmation method for preventing counterfeiting provided by the present invention.

[0027] Figure 3 This is a flowchart illustrating steps 301-314 of the anti-counterfeiting data ownership confirmation method provided by the present invention.

[0028] Figure 4This is a flowchart illustrating steps 315-330 of the anti-counterfeiting data ownership confirmation method provided by the present invention.

[0029] Figure 5 This is the third flowchart of the data ownership confirmation method for preventing counterfeiting provided by the present invention.

[0030] Figure 6 This is one of the structural schematic diagrams of the anti-counterfeiting data ownership confirmation device provided by the present invention.

[0031] Figure 7 This is the second structural schematic diagram of the anti-counterfeiting data ownership confirmation device provided by the present invention.

[0032] Figure 8 This is a schematic diagram of the structure of the electronic device provided by the present invention. Detailed Implementation

[0033] To make the objectives, technical solutions, and advantages of this invention clearer, the technical solutions of this invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some, not all, of the embodiments of this invention. All other embodiments obtained by those skilled in the art based on the embodiments of this invention without creative effort are within the scope of protection of this invention.

[0034] The following is combined with Figures 1-4 The present invention describes a data ownership verification method for preventing counterfeiting. This method can be applied to the generation of any ownership certificate. The subject executing this method can be an electronic device or a data ownership verification method for preventing counterfeiting installed in the electronic device. The data ownership verification device for preventing counterfeiting can be implemented by software, hardware, or a combination of both.

[0035] Figure 1 This is one of the flowcharts illustrating the anti-counterfeiting data ownership confirmation method provided by the present invention, such as... Figure 1 As shown, this method, applied to the land ownership confirmation system, includes the following steps: Step 101: Receive the first set of features sent by the agent of the confirmation of rights application.

[0036] The first feature set is obtained by the rights confirmation application agent through feature extraction of the first data to be confirmed based on the first feature extraction algorithm.

[0037] Optionally, the first to be right data can be composed of different modalities, different data formats, or the same modality and the same data format. For example, the first to be right data can be displayed in text, image, video and other modalities, or in structured and unstructured data form. Moreover, the data size of the first to be right data can be large or small, and the embodiments of the present application do not make specific limitation thereon. Here, the first to be right data includes but is not limited to any one of xml, html, graph database, relational database, txt text, format document (ofd, pdf format), streaming document (doc, docx, xls, xlsx, ppt, pptx format), image (jpg, png, psd, bmp format), audio (mp3, aac, ogg format), video (mp4, avi, flv, wmv, mov format).

[0038] Optionally, the feature extraction algorithm includes but is not limited to hash, fuzzy hash, neural network, data block, etc.

[0039] Optionally, the first feature set includes one or more features.

[0040] Step 102, based on the discrimination between each feature in the first feature set and the feature set library of the right data, determining the first insertion rule corresponding to the first to be right data and the first insertion content corresponding to the first to be right data.

[0041] Optionally, the feature set library of the right data can be a feature set library in one right system, or a feature set in multiple right systems. For example, when there are N right systems, the features passed by the i-th right system need to be compared with the feature set library of the right data in the other N-1 right systems.

[0042] Optionally, the discrimination calculation includes but is not limited to duplicate comparison, weighted duplicate comparison, distance-based similarity operation and other forms.

[0043] Specifically, the right system determines whether the first to be right data belongs to the data whose right has been completed in the right library by calculating the discrimination between each feature in the first feature set and the feature set of the data whose right has been completed and stored in the right library in advance, thereby judging whether the right application sent by the right application agent can be approved.

[0044] Optionally, the first inserted content can be generated according to the type of the first to be right data by a certain rule, and the first inserted content includes but is not limited to: a character string, a binary code, a number, a text, a node of a graph database, a column in a relational database table, an image, audio, video, etc. The first inserted content can be generated by a first inserted content generation strategy and / or manually, and the first inserted generation strategy includes but is not limited to: a random value, a modulo operation, etc. The present embodiment does not make specific constraints on the first inserted content, the generation strategy of the first inserted content, the first to be right data content, and the size, etc.

[0045] The first insertion rule includes but is not limited to: an insertion time, an insertion position, an insertion manner, etc.

[0046] Optionally, the first insertion rule and the first inserted content can be generated for the first feature that meets the degree of distinction condition, or can be generated for the feature that does not meet the degree of distinction condition, or can be generated for the feature that is different from the feature that does not meet the degree of distinction condition.

[0047] Exemplarily, the first insertion rule includes a first insertion sub-rule, the first inserted content includes a first insertion sub-content, and the determination of the first insertion rule corresponding to the first to be right data and the first inserted content corresponding to the first to be right data based on the degree of distinction between each feature in the first feature set and the feature set library of the right data includes: determining a first sub-feature set that meets the degree of distinction condition in the first feature set based on the degree of distinction between each feature in the first feature set and the feature set library of the right data; and generating the first insertion sub-rule and the first insertion sub-content based on the first sub-feature set.

[0048] Specifically, after determining the first sub-feature set that first meets the generation of the degree of distinction condition in the first feature set, the first insertion sub-rule and the first insertion sub-content can be generated, and then the first insertion sub-content is inserted into the object corresponding to the first sub-feature set in the first to be right data according to the first insertion sub-rule to obtain the first inserted data. The first inserted data can be the second to be right data or can not be the second to be right data.

[0049] In the present embodiment, by determining the first sub-feature set that meets the degree of distinction condition according to the degree of distinction between each feature in the first feature set and the feature set library of the right data, the first insertion sub-content is inserted into the first to be right data according to the first insertion sub-rule to generate the right certificate, so as to prevent the features and / or the feature degree of distinction in the first sub-feature set of the first to be right data corresponding to the right certificate from being forged by tampering the first to be right data, and further negate the right person's rights and interests of the first to be right data corresponding to the right certificate, so as to protect the legal rights and interests of the right person.

[0050] Illustratively, the first insertion rule includes a second insertion sub-rule, the first insertion content includes a second insertion sub-content, and the determining of the first insertion rule corresponding to the first to-be-righted data and the first insertion content corresponding to the first to-be-righted data based on the discrimination degrees between each feature in the first feature set and the feature set library of the righted data comprises: in a case where the discrimination degrees between the features in the first feature set and the feature set library of the righted data do not satisfy the discrimination degree condition and the number of times of right application sent by the right application agent does not exceed the number threshold, sending the first un-passed features in the first feature set that do not satisfy the discrimination degree condition to the right application agent; receiving a second sub-feature set sent by the right application agent; the second sub-feature set includes features different from the first un-passed features or new feature values of the first un-passed features re-extracted from the first to-be-righted data by using a third feature extraction algorithm; the third feature extraction algorithm is different from the first feature extraction algorithm; and generating the second insertion sub-rule and the second insertion sub-content based on the discrimination degrees between each feature in the second sub-feature set and the feature set library of the righted data.

[0051] Optionally, the number threshold can be any suitable value, such as 5, 6, etc.

[0052] It should be noted that when the number of times of right application sent by the right application agent exceeds the number threshold, the right application is terminated, that is, the right certificate is not issued.

[0053] Optionally, the second sub-feature set can be features different from the first un-passed features, that is, features different from the features in the first feature set; or the second sub-feature set can be new feature values of the first un-passed features re-extracted from the first to-be-righted data by using a feature extraction algorithm different from the first feature extraction algorithm.

[0054] Optionally, the second insertion sub-rule and the second insertion sub-content can be generated for the features in the second sub-feature set that satisfy the discrimination degree condition for the first time, or can be generated for the features that satisfy the discrimination degree condition multiple times.

[0055] In the embodiment of the application, for the features that do not satisfy the discrimination degree condition, a sub-feature set is re-generated, and the features that satisfy the discrimination degree condition are further searched for in the sub-feature set, thereby increasing feature diversity and improving the anti-counterfeiting property of the first to-be-righted data, so as to protect the legal rights and interests of the right holder.

[0056] For example, the generating the second insertion sub-rule and the second insertion sub-content based on the degree of distinction between each feature in the second sub-feature set and the feature set library of the authorized data comprises: determining a third sub-feature set in the second sub-feature set that meets the degree of distinction condition based on the degree of distinction between each feature in the second sub-feature set and the feature set library of the authorized data; and generating the second insertion sub-rule and the second insertion sub-content based on the third sub-feature set.

[0057] Specifically, after determining the third sub-feature set in the second feature set that first meets the generation degree of distinction condition, and generating the second insertion sub-rule and the second insertion sub-content, the second insertion sub-content is inserted into the object corresponding to the third sub-feature set of the first to-be-authorized data according to the second insertion sub-rule to obtain second insertion data, and the first insertion data and the second insertion data are fused to obtain second to-be-authorized data.

[0058] Further, the generating the second insertion sub-rule and the second insertion sub-content based on the degree of distinction between each feature in the second sub-feature set and the feature set library of the authorized data comprises: in a case where there is a feature in the second sub-feature set that does not meet the degree of distinction condition and the number of ownership applications sent by the authorization application agent does not exceed the number threshold, sending the second unpassed feature in the second sub-feature set that does not meet the degree of distinction condition to the authorization application agent; receiving a fourth sub-feature set sent by the authorization application agent; wherein the fourth sub-feature set comprises a feature different from the second unpassed feature or a new feature value corresponding to the second unpassed feature re-extracted from the first to-be-authorized data by a fourth feature extraction algorithm; the fourth feature extraction algorithm is different from the first feature extraction algorithm and the third feature extraction algorithm; and generating the second insertion sub-rule and the second insertion sub-content based on the degree of distinction between each feature in the fourth sub-feature set and the feature set library of the authorized data.

[0059] It should be noted that when the features in the fourth sub-feature set are different from the second unpassed feature, it means that the features in the fourth sub-feature set are all different from the features in the first feature set.

[0060] Specifically, the discrimination between each feature in the fourth sub-feature set and the feature set library of the authenticated data is calculated, and for the unpassed features in the fourth sub-feature set that do not meet the discrimination condition, the unpassed features are replaced or new feature values corresponding to the unpassed features are extracted by replacing the feature extraction algorithm to obtain a new sub-feature set. Then, the discrimination between the new sub-feature set and the feature set library of the authenticated data is calculated, and for the unpassed features in the new sub-feature set that do not meet the discrimination condition, the unpassed features are replaced or new feature values corresponding to the unpassed features are extracted by replacing the feature extraction algorithm to obtain a next new sub-feature set. The unpassed features in the new sub-feature set that do not meet the discrimination condition are determined, and new feature values corresponding to the unpassed features are extracted by replacing the unpassed features or replacing the feature extraction algorithm to obtain a next new sub-feature set, until a stop condition is met. For all features that meet the discrimination condition, a second insertion sub-rule and a second insertion sub-content are generated. The stop condition can be that the number of features is reached, or the staff does not want to continue the cycle, or the number of applications exceeds a threshold, etc.

[0061] In the embodiment of the application, for features that do not meet the discrimination condition, a sub-feature set is regenerated, and features that meet the discrimination condition are constantly searched for in the sub-feature set, which increases feature diversity and improves the anti-counterfeiting property of the first to-be-authenticated data, thereby protecting the legitimate rights and interests of the right holder.

[0062] Step 103, sending the first insertion rule and the first insertion content to the authentication application agent and receiving a second feature set sent by the authentication application agent.

[0063] The second feature set is obtained by the authentication application agent based on a second feature extraction algorithm by performing feature extraction on second to-be-authenticated data, and the second to-be-authenticated data is obtained by the authentication application agent by inserting the first insertion content into the corresponding position in the first to-be-authenticated data based on the first insertion rule.

[0064] It should be noted that the corresponding position in the first to-be-authenticated data refers to an object corresponding to a feature that meets the discrimination condition. For example, the first sub-feature set is the first feature set that meets the discrimination condition, the third sub-feature set is the feature set that meets the discrimination condition after processing the unpassed features and performing discrimination calculation again, and the second to-be-authenticated data is obtained by inserting the first insertion content into the objects corresponding to the first sub-feature set and the third sub-feature set according to the first insertion rule, wherein the object range cannot exceed the first sub-feature set and the third sub-feature set.

[0065] Step 104, determining the target ownership certificate corresponding to the first to-be-righted data based on the discrimination degree between each feature in the second feature set and / or the first feature set and the feature set library of the righted data and sending to the righting application agent.

[0066] It should be noted that, the first ownership certificate can be generated for the first feature meeting the discrimination degree condition, and the second ownership certificate can be generated for the feature meeting the discrimination degree condition later, the target ownership certificate can be determined by comparing the contents of the first ownership certificate and the second ownership certificate; or the target ownership certificate can be directly generated according to the feature meeting the discrimination degree condition, and the feature not meeting the discrimination degree condition can be directly discarded.

[0067] Exemplarily, the target ownership certificate corresponding to the first to-be-righted data is determined based on the discrimination degree between each feature in the second feature set and / or the first feature set and the feature set library of the righted data, including: determining a fifth sub-feature set meeting the discrimination degree condition based on the discrimination degree between each feature in the second feature set and / or the first feature set and the feature set library of the righted data; generating the first ownership certificate corresponding to the first to-be-determined data based on the fifth sub-feature set; and determining the target ownership certificate based on the first ownership certificate.

[0068] Here, the fifth sub-feature set is a feature in the second feature set and / or the first feature set.

[0069] Specifically, after obtaining the second feature set and / or the first feature set, the discrimination degree between each feature in the second feature set and / or the first feature set and the feature set library of the righted data is calculated, the features meeting the discrimination degree condition are determined as the fifth sub-feature set, and the first ownership certificate is generated according to the fifth sub-feature set, that is, the first ownership certificate is generated for the first feature meeting the discrimination degree condition in the second feature set and / or the first feature set.

[0070] Optionally, the first ownership certificate can be the target ownership certificate, or the first ownership certificate can be updated by adding the feature meeting the discrimination degree condition, and the new ownership certificate is determined as the target ownership certificate.

[0071] In the embodiment of the application, the feature set is re-extracted in the second to-be-righted data with the first inserted content, the features meeting the discrimination degree condition are searched for the new feature set, the ownership certificate is generated based on the new features meeting the discrimination degree condition, and the ownership certificate is generated based on the first feature set and the second feature set, so that the first to-be-righted data corresponding to the generated ownership certificate is prevented from being counterfeited, thereby protecting the legal rights and interests of the right holder.

[0072] Further, after generating the first right certificate corresponding to the first to-be-determined data based on the fifth sub-feature set, the method further includes: in a case where a degree of distinction between a feature in the second feature set and / or the first feature set and a feature set library of the righted data does not satisfy the degree of distinction condition and a number of right application times sent by the right application agent does not exceed a threshold, sending the third un-passed feature that does not satisfy the degree of distinction condition to the right application agent; receiving a sixth sub-feature set sent by the right application agent; wherein the sixth sub-feature set is obtained by the right application agent based on a fifth feature extraction algorithm by performing feature extraction on the second to-be-righted data, and the fifth feature extraction algorithm is different from the second feature extraction algorithm. or, receiving the sixth sub-feature set sent by the right application agent, and sending a second insertion rule and a second insertion content to the right application agent; wherein the sixth sub-feature set is obtained by the right application agent based on a sixth feature extraction algorithm by performing feature extraction on third to-be-righted data, the third to-be-righted data is obtained by replacing content of an object corresponding to the sixth sub-feature set in the second to-be-righted data with the second insertion content according to the second insertion rule, and the sixth feature extraction algorithm can be the same as or different from the second feature extraction algorithm.

[0073] It should be noted that the third un-passed feature can be a feature in the second feature set and / or the first feature set.

[0074] Specifically, after generating the first right certificate, the third un-passed feature that does not satisfy the degree of distinction condition in the second feature set and / or the first feature set is determined, the third un-passed feature that does not satisfy the degree of distinction condition is sent to the right application agent, the right application agent reextracts the third un-passed feature from the second to-be-righted data based on a fifth feature extraction algorithm different from the second feature extraction algorithm to obtain a sixth sub-feature set, or the right application agent is sent a second insertion rule and a second insertion content, the right application agent replaces content of an object corresponding to the sixth sub-feature set in the second to-be-righted data with the second insertion content according to the second insertion rule to obtain third to-be-righted data, and the right application agent reextracts a new feature value corresponding to the third un-passed feature from the third to-be-righted data by using a sixth feature extraction algorithm to obtain the sixth sub-feature set.

[0075] After obtaining the sixth sub-feature set, it is further determined whether the features in the sixth sub-feature set satisfy the degree of distinction condition, for the features satisfying the degree of distinction condition, a second right certificate is generated, and for the features not satisfying the degree of distinction condition, content is reinserted or a feature extraction algorithm is replaced, and the features satisfying the degree of distinction condition are continuously searched.

[0076] Exemplarily, after receiving the sixth sub-feature set sent by the right application agent, the method further comprises: determining a seventh sub-feature set in the sixth sub-feature set that meets the discrimination condition based on the discrimination between each feature in the sixth sub-feature set and the feature set library of the already-righted data; and generating a second right certificate based on the seventh sub-feature set.

[0077] Specifically, for the seventh sub-feature set in the sixth sub-feature set that first meets the discrimination condition, the second right certificate can be directly generated according to the seventh sub-feature set and other features that meet the discrimination condition, and the search for features can be abandoned, or after the second right certificate is generated, the features that meet the discrimination condition can be searched for again to generate a new right certificate.

[0078] Further, after receiving the sixth sub-feature set sent by the right application agent, the method further comprises: in a case where the discrimination between a feature in the sixth sub-feature set and the feature set library of the already-righted data does not meet the discrimination condition and the number of right application times sent by the right application agent does not exceed the threshold, sending the fourth un-passed feature in the sixth sub-feature set that does not meet the discrimination condition to the right application agent; receiving an eighth sub-feature set sent by the right application agent; wherein the eighth sub-feature set is obtained by the right application agent based on a seventh feature extraction algorithm for feature extraction on the second data to be righted, and the seventh feature extraction algorithm is different from the second feature extraction algorithm and the fifth feature extraction algorithm. Or, Receiving the eighth sub-feature set sent by the right application agent, and sending a third insertion rule and a third insertion content to the right application agent; wherein the eighth sub-feature set is obtained by the right application agent based on an eighth feature extraction algorithm for feature extraction on fourth data to be righted, the fourth data to be righted is obtained by replacing the content of the object corresponding to the eighth sub-feature set in the third data to be righted with the third insertion content according to the third insertion rule; and the eighth feature extraction algorithm can be the same as or different from the second feature extraction algorithm.

[0079] Specifically, after the right system receives the sixth sub-feature set sent by the right application agent, the fourth un-passed feature that does not meet the discrimination condition is sent to the right application agent, the right application agent replaces the feature extraction algorithm to extract the fourth un-passed feature again to obtain the eighth sub-feature set, or replaces the content of the object corresponding to the eighth sub-feature set in the third data to be righted with the third insertion content according to the third insertion rule to obtain the fourth data to be righted, and then the eighth feature extraction algorithm is used to extract features from the fourth data to be righted to obtain the eighth sub-feature set.

[0080] After obtaining the eighth sub-feature set, it is judged whether the features in the eighth sub-feature set meet the discrimination condition, and the features meeting the discrimination condition are reserved; for the features not meeting the discrimination condition, new sub-feature sets are obtained by re-inserting contents or replacing feature extraction algorithms, then the discrimination between the new sub-feature sets and the feature set library of the authenticated data is calculated, for the failed features not meeting the discrimination condition, new features corresponding to the failed features are extracted by replacing the failed features or replacing the feature extraction algorithms to obtain next new sub-feature sets, the failed features not meeting the discrimination condition in the new sub-feature sets are determined, the new features corresponding to the failed features are extracted by replacing the failed features or replacing the feature extraction algorithms to obtain next new sub-feature sets, until a stop condition is met, and new ownership certificates are generated for all features meeting the discrimination condition.

[0081] In the embodiment of the present application, the corresponding ownership certificate is generated for the features meeting the discrimination condition, then, the features not meeting the discrimination condition are replaced by new features by changing the feature extraction algorithm and inserting the content, and the new ownership certificate is generated according to the features meeting the discrimination condition and the new features, so that the first to-be-authenticated data corresponding to the generated ownership certificate is prevented from being counterfeited, thereby protecting the legal rights and interests of the right holder.

[0082] Further, the target ownership certificate is determined based on the first ownership certificate, including: in the case that the first ownership certificate is the same as the second ownership certificate, the first ownership certificate is determined as the target ownership certificate and sent to the authentication application agent; in the case that the first ownership certificate is different from the second ownership certificate, the second ownership certificate is determined as the target ownership certificate and sent to the authentication application agent.

[0083] It should be noted that if the features not passing are replaced by new features meeting the discrimination condition by replacing the feature extraction algorithm or inserting the content, the features of the second ownership certificate are more than the features of the first ownership certificate, and the features of the second ownership certificate are the target ownership certificate; if the features not passing are still not replaced by features meeting the discrimination condition by replacing the feature extraction algorithm or inserting the content, the second ownership certificate is the same as the first ownership certificate, and the first ownership certificate is the target ownership certificate.

[0084] In the embodiment of the present application, the features are extracted from the second to-be-authenticated data obtained by inserting the content in the first to-be-authenticated data, and the ownership certificate is generated based on the first feature set and / or the second feature set, so that the first to-be-authenticated data corresponding to the generated ownership certificate is prevented from being counterfeited, thereby protecting the legal rights and interests of the right holder.

[0085] Further, the setting form of the first / second / third inserted content and the first / second / third inserted rule comprises at least one of a rule, a configuration file, a button, a circle, a check, a mark, a key, a scroll wheel, a menu, a voice, a video, a gaze, a gesture, a text, a biological electrical signal, and a virtual reality.

[0086] Optionally, the configuration method can be in one or more of the following forms: a rule, a configuration file, a button, a circle, a check, a mark, a key, a scroll wheel, a menu, a voice, a video, a gaze, a gesture, a text, a biological electrical signal, and a virtual environment. Specifically, the up and down of the mute key of the mobile phone, the left and right of the voice recorder, and the like can be reflected as inputting without a physical switch, such as screen gestures (left to right, right to left, up to down, down to up, etc.), pop-up interface filling (such as form entry), file (such as XML format) import, voice entry, configuration file input, pop-up menu selection, virtual keyboard input on the screen, and the like.

[0087] In the embodiments of the present application, the diversity of the implementation of the inserted rule and the inserted content is realized through various configuration methods.

[0088] Figure 2 is a flowchart of the anti-forgery data right confirmation method provided by the present application, as shown in Figure 2 The method is applied to a right confirmation application agent and includes the following steps. Step 201, determining first to-be-right-confirmed data.

[0089] Step 202, performing feature extraction on the first to-be-right-confirmed data based on a first feature extraction algorithm to obtain a first feature set.

[0090] Step 203, sending the first feature set to a right confirmation system and receiving first inserted rules and first inserted content corresponding to the first feature set sent by the right confirmation system.

[0091] The first inserted rules and the first inserted content are generated by the right confirmation system based on the degree of differentiation between each feature in the first feature set and a feature set library of right-confirmed data.

[0092] Step 204, inserting the first inserted content into a corresponding position in the first to-be-right-confirmed data based on the first inserted rules to obtain second to-be-right-confirmed data.

[0093] Step 205, performing feature extraction on the second to-be-right-confirmed data based on a second feature extraction algorithm to obtain a second feature set.

[0094] In step 206, the second feature set is sent to the right confirmation system, and a target right confirmation certificate corresponding to the first data to be confirmed is received and sent by the right confirmation system.

[0095] The target right confirmation certificate is determined by the right confirmation system based on the second feature set and / or each feature in the first feature set and the feature set library of the confirmed data.

[0096] In the embodiment of the application, the right confirmation application agent determines the first data to be confirmed, extracts features from the first data to be confirmed based on a first feature extraction algorithm to obtain a first feature set, sends the first feature set to the right confirmation system, and receives a first insertion rule and corresponding first insertion content corresponding to the first feature set sent by the right confirmation system. The first insertion rule and the first insertion content are generated by the right confirmation system based on the distinction between each feature in the first feature set and the feature set library of the confirmed data. The first insertion content is inserted into the corresponding position in the first data to be confirmed based on the first insertion rule to obtain second data to be confirmed. The second feature set is obtained by extracting features from the second data to be confirmed based on a second feature extraction algorithm. The second feature set is sent to the right confirmation system, and a target right confirmation certificate corresponding to the first data to be confirmed is received and sent by the right confirmation system. The right confirmation certificate is determined by the right confirmation system based on the second feature set and / or each feature in the first feature set and the feature set library of the confirmed data. In this way, by extracting features from the second data to be confirmed after inserting content in the first data to be confirmed, the right confirmation certificate is generated based on the first feature set and / or the second feature set, avoiding the first data to be confirmed corresponding to the generated right confirmation certificate being forged, thereby protecting the legitimate rights and interests of the right holder.

[0097] Further, the second feature set is sent to the right confirmation system, and a target right confirmation certificate corresponding to the first data to be confirmed is received and sent by the right confirmation system. The second feature set is sent to the right confirmation system, and a first failed feature is received and sent by the right confirmation system. A feature different from the first failed feature is selected as a second sub-feature set, or a new feature value corresponding to the first failed feature is re-extracted from the first data to be confirmed by a third feature extraction algorithm as a second sub-feature set. The second sub-feature set is sent to the right confirmation system, and a right confirmation certificate is received and sent by the right confirmation system. The right confirmation certificate is generated by the right confirmation system based on the second sub-feature set that meets the distinction condition.

[0098] The following is the application scenario of the anti-forgery data right method provided by the application. It should be noted that the number of right confirmation systems can be one or more.

[0099] Figure 3 is a flowchart of steps 301-314 of the anti-forgery data right method provided by the application, which includes one right confirmation application agent and two right confirmation systems, such as Figure 3 as shown, including: Step 301, the right confirmation application agent determines the first data to be right confirmed.

[0100] Step 302, the right confirmation application agent extracts features from the first data to be right confirmed based on a first feature extraction algorithm to obtain a first feature set and sends it to the right confirmation system A.

[0101] Step 303, the right confirmation system A compares the degree of differentiation with the feature set library of the right confirmed data.

[0102] Here, the degree of differentiation of the features in the first feature set is compared with the feature set library of the right confirmed data.

[0103] Step 304, the right confirmation system A judges whether all features pass the threshold check of the degree of differentiation. If yes, execute step 309; otherwise, execute step 305.

[0104] Here, the threshold of the degree of differentiation can be understood as the condition of the degree of differentiation.

[0105] Step 305, the right confirmation system A judges whether the number of right ownership applications exceeds the threshold. If yes, execute step 306; otherwise, execute steps 307-308, 304.

[0106] Step 306, the right confirmation application agent terminates the right confirmation application.

[0107] Step 307, the right confirmation system A filters the features that do not pass the threshold detection and sends them to the right confirmation application agent.

[0108] Step 308, the right confirmation application agent re-determines and replaces the features in the first feature set that do not pass the threshold detection, and / or replaces the first feature extraction algorithm to re-extract the feature values of the features in the first feature set that do not pass the threshold detection, and sends them to the right confirmation system A.

[0109] Optionally, the number of replaced features can be equal to the number of features that do not pass, less than the number of features that do not pass, or more than the number of features that do not pass, and the right confirmation application agent can also replace the algorithm to generate new feature values.

[0110] Here, the re-determined feature set can be the second or fourth sub-feature set described above, the sub-feature set includes features different from the features that do not pass, or new feature values of the features that do not pass re-extracted from the first to be right data using a different feature extraction algorithm.

[0111] Step 309, the right system A sends a right request to the right system B and sends the feature set.

[0112] Step 310, the right system B compares the feature set with the features of the right data, and returns the discrimination comparison result.

[0113] Step 311, the right system A determines whether all features in the first feature set pass the discrimination threshold check according to the discrimination comparison result, if yes, step 314 is executed; otherwise, step 312 is executed.

[0114] Step 312, the right system A determines whether the number of ownership applications exceeds the threshold, if yes, step 313 is executed; otherwise, step 307 is executed.

[0115] Step 313, the right application agent terminates the right application.

[0116] Step 314, the right system A generates insertion content and insertion rules corresponding to the number of features and sends them to the right application agent.

[0117] Here, the insertion content is the first insertion content, and the insertion rule is the first insertion rule.

[0118] Figure 4 is the flowchart of steps 315-330 in the anti-forgery data right method provided by the application, as shown in Figure 4 , comprising: Step 315, the right application agent inserts the insertion content into the corresponding position in the first to be right data according to the insertion rule to obtain the second to be right data.

[0119] Step 316, the right application agent extracts features from the second to be right data based on the second feature extraction algorithm to obtain the second feature set and sends it to the right system A.

[0120] Step 317, the right system A compares the feature set with the feature set library of the right data.

[0121] Step 318, the right system A determines whether all features pass the discrimination threshold check, if yes, steps 323, 324 and 325 are executed; otherwise, step 319 is executed.

[0122] Step 319, the right confirmation system A judges whether the right confirmation application times exceed the threshold value, if yes, step 320 is executed; otherwise, steps 321-322 and 317 are executed.

[0123] Step 320, the right confirmation application agent terminates the right confirmation application.

[0124] Step 321, the right confirmation system A screens the features that do not pass the threshold value detection, and regenerates the corresponding insertion content and insertion rule, and sends them to the right confirmation application agent.

[0125] Here, the insertion content is the second insertion content, and the insertion rule is the second insertion rule.

[0126] Step 322, the right confirmation application agent reextracts new feature values without changing the feature extraction algorithm, and / or updates the feature extraction algorithm to reextract new feature values, and sends them to the right confirmation system A.

[0127] Optionally, the number of replaced features can be equal to the number of features that do not pass, or less than the number of features that do not pass, and the right confirmation application agent can also replace the algorithm to generate new feature values.

[0128] Here, the re-determined feature set can be the fifth sub-feature set or the seventh sub-feature set described above, and the sub-feature set can be new feature values corresponding to features that do not pass reextracted from the second right confirmation data by the feature extraction algorithm, or can be reextracted from the second right confirmation data obtained by replacing the content of the object corresponding to the sixth sub-feature set in the second right confirmation data with the second insertion content according to the second insertion rule.

[0129] Step 323, the right confirmation system A sends a right confirmation request to the right confirmation system B, and sends the feature set.

[0130] Step 324, the right confirmation system B compares the feature set with the features of the right confirmed data in terms of discrimination, and returns the discrimination comparison result.

[0131] Step 325, the right confirmation system A judges whether all features in the feature set pass the discrimination threshold value check according to the discrimination comparison result, if yes, step 328 is executed; otherwise, step 326 is executed.

[0132] Step 326, the right confirmation system A judges whether the right confirmation application times exceed the threshold value, if yes, step 327 is executed; otherwise, step 321 is executed.

[0133] Step 327, the right confirmation application agent terminates the right confirmation application.

[0134] Step 328, the right confirmation system A stores the first feature set and the feature set after the insertion content, generates a right confirmation certificate and sends it to the right confirmation application agent.

[0135] Step 329, the right confirmation application agent receives the right certificate and returns to the user.

[0136] Figure 5 is a third flowchart of the anti-counterfeiting data right confirmation method provided by the application, which comprises a right confirmation application agent and a right confirmation system, as shown in Figure 5 , which comprises: Step 401, the right confirmation application agent determines first data to be confirmed.

[0137] Step 402, the right confirmation application agent extracts features from the first data to be confirmed based on a first feature extraction algorithm to obtain a first feature set and sends it to the right confirmation system A.

[0138] Step 403, the right confirmation system A compares the degree of distinction with the feature set library of the data that has been confirmed.

[0139] Step 404, the right confirmation system A judges whether all features pass the threshold value check, if yes, step 409 is executed; otherwise, step 405 is executed.

[0140] Step 405, the right confirmation system A judges whether the number of right confirmation applications exceeds the threshold value, if yes, step 406 is executed; otherwise, steps 407-408 and 403 are executed.

[0141] Step 406, the right confirmation application agent terminates the right confirmation application.

[0142] Step 407, the right confirmation system A screens the features that do not pass the threshold value detection and sends them to the right confirmation application agent.

[0143] Step 408, the right confirmation application agent re-determines and replaces the features in the first feature set that do not pass the threshold value detection, and / or replaces the first feature extraction algorithm to re-extract the feature values of the features in the first feature set that do not pass the threshold value detection, and sends them to the right confirmation system A.

[0144] Optionally, the number of replaced features can be equal to, less than, or more than the number of features that do not pass the threshold value detection, and the right confirmation application agent can also replace the algorithm to generate new feature values.

[0145] Step 409, the right confirmation system A generates insertion content and insertion rules corresponding to the number of features and sends them to the right confirmation application agent.

[0146] Step 410, the right confirmation application agent inserts the insertion content into the corresponding position in the first data to be confirmed according to the insertion rules to obtain second data to be confirmed.

[0147] Step 411, the right confirmation application agent extracts features from the second to-be-confirmed data based on the second feature extraction algorithm, obtains a second feature set and sends the second feature set to the right confirmation system A.

[0148] Step 412, the right confirmation system A performs a discrimination degree comparison with the feature set library of the right-confirmed data.

[0149] Step 413, the right confirmation system A judges whether all features pass the discrimination threshold check, if yes, steps 420 and 421 are executed; otherwise, step 414 is executed.

[0150] Step 414, the right confirmation system A judges whether the number of right ownership application times exceeds a threshold, if yes, step 415 is executed; otherwise, step 416 is executed.

[0151] Step 415, the right confirmation application agent terminates the right confirmation application.

[0152] Step 416, the right confirmation system A screens features that do not pass the threshold check and regenerates corresponding insertion content and insertion rules and sends the insertion content and the insertion rules to the right confirmation application agent.

[0153] Step 417, the right confirmation application agent judges whether new features are reselected, if yes, steps 418 and 403-414 are executed; otherwise, steps 419 and 412-414 are executed.

[0154] Step 418, the right confirmation application agent replaces features in the first feature set that do not pass and sends the features to the right confirmation system A.

[0155] Step 419, the right confirmation application agent reextracts new feature values without replacing the feature extraction algorithm and / or updates the feature extraction algorithm to reextract new feature values and sends the new feature values to the right confirmation system A.

[0156] Step 420, the right confirmation system A stores the first feature set and the feature set after the insertion content, generates a right ownership certificate and sends the right ownership certificate to the right confirmation application agent.

[0157] Step 421, the right confirmation application agent receives the right ownership certificate and returns the right ownership certificate to the user.

[0158] The anti-forgery data right confirmation device provided by the application is described below, and the anti-forgery data right confirmation device described below can be correspondingly referred to the anti-forgery data right confirmation method described above.

[0159] Figure 6 is one of the structure diagrams of the anti-forgery data right confirmation device provided by the application, as Figure 6 shown, the first anti-forgery data right confirmation device 500 includes: The first receiving module 510 is configured to receive a first feature set sent by an application agent; the first feature set is obtained by the application agent based on a first feature extraction algorithm and by performing feature extraction on first to-be-right data; The first determining module 520 is configured to determine a first insertion rule corresponding to the first to-be-right data and first insertion content corresponding to the first to-be-right data based on a discrimination degree between each feature in the first feature set and a feature set library of already-right data. The first transmission module 530 is configured to send the first insertion rule and the first insertion content to the application agent, and receive a second feature set sent by the application agent; the second feature set is obtained by the application agent based on a second feature extraction algorithm and by performing feature extraction on second to-be-right data, and the second to-be-right data is obtained by the application agent based on the first insertion rule and by inserting the first insertion content into a corresponding position of the first to-be-right data. The second determining module 540 is configured to determine a target right ownership certificate corresponding to the first to-be-right data based on a discrimination degree between each feature in the second feature set and / or the first feature set and the feature set library of the already-right data, and send the target right ownership certificate to the application agent.

[0160] In another embodiment, the first insertion rule includes a first insertion sub-rule, and the first insertion content includes first insertion sub-content. The first determining module 520 is specifically configured to: determine a first sub-feature set that meets a discrimination degree condition in the first feature set based on a discrimination degree between each feature in the first feature set and a feature set library of already-right data; and generate the first insertion sub-rule and the first insertion sub-content based on the first sub-feature set.

[0161] In another embodiment, the first insertion rule includes a second insertion sub-rule, and the first insertion content includes a second insertion sub-content. The first determining module 520 is further configured to: in a case where the degree of differentiation between a feature in the first feature set and the feature set library of the authorized data does not satisfy the degree of differentiation condition and the number of times of ownership application sent by the authorization application agent does not exceed the threshold, send the first un-passed feature in the first feature set that does not satisfy the degree of differentiation condition to the authorization application agent; receive a second sub-feature set sent by the authorization application agent; the second sub-feature set includes features different from the first un-passed feature, or new feature values of the first un-passed feature re-extracted from the first data to be authorized by using a third feature extraction algorithm; the third feature extraction algorithm is different from the first feature extraction algorithm; and generate the second insertion sub-rule and the second insertion sub-content based on the degree of differentiation between each feature in the second sub-feature set and the feature set library of the authorized data.

[0162] In another embodiment, the first determining module 520 is further configured to: determine a third sub-feature set in the second sub-feature set that satisfies the degree of differentiation condition based on the degree of differentiation between each feature in the second sub-feature set and the feature set library of the authorized data; and generate the second insertion sub-rule and the second insertion sub-content based on the third sub-feature set.

[0163] In another embodiment, the first determining module 520 is further configured to: in a case where the degree of differentiation between a feature in the second sub-feature set and the feature set library of the authorized data does not satisfy the degree of differentiation condition and the number of times of ownership application sent by the authorization application agent does not exceed the threshold, send the second un-passed feature in the second sub-feature set that does not satisfy the degree of differentiation condition to the authorization application agent; receive a fourth sub-feature set sent by the authorization application agent; the fourth sub-feature set includes features different from the second un-passed feature, or new feature values of the second un-passed feature re-extracted from the first data to be authorized by using a fourth feature extraction algorithm; the fourth feature extraction algorithm is different from the first feature extraction algorithm and the third feature extraction algorithm; and generate the second insertion sub-rule and the second insertion sub-content based on the degree of differentiation between each feature in the fourth sub-feature set and the feature set library of the authorized data.

[0164] In another embodiment, the second determining module 540 is specifically configured to determine a fifth sub-feature set satisfying a discrimination condition based on a discrimination degree between each feature in the second feature set and / or the first feature set and a feature set library of the already-authorized data; generate a first ownership certificate corresponding to the first to-be-determined data based on the fifth sub-feature set; and determine the target ownership certificate based on the first ownership certificate.

[0165] In another embodiment, after the first ownership certificate corresponding to the first to-be-determined data is generated based on the fifth sub-feature set, the first anti-forgery data authorization apparatus 500 further includes a first transmission unit that is specifically configured to: in a case where a discrimination degree between a feature in the second feature set and / or the first feature set and the feature set library of the already-authorized data does not satisfy the discrimination condition and a number of times of ownership application sent by the authorization application agent does not exceed a threshold, send a third unqualified feature that does not satisfy the discrimination condition to the authorization application agent; receive a sixth sub-feature set sent by the authorization application agent; wherein the sixth sub-feature set is obtained by the authorization application agent based on a fifth feature extraction algorithm and by performing feature extraction on the second to-be-authorized data, and the fifth feature extraction algorithm is different from the second feature extraction algorithm; or receive the sixth sub-feature set sent by the authorization application agent, and send a second insertion rule and a second insertion content to the authorization application agent; wherein the sixth sub-feature set is obtained by the authorization application agent based on a sixth feature extraction algorithm and by performing feature extraction on third to-be-authorized data, the third to-be-authorized data is obtained by replacing content of an object corresponding to the sixth sub-feature set in the second to-be-authorized data with the second insertion content according to the second insertion rule, and the sixth feature extraction algorithm can be the same as or different from the second feature extraction algorithm.

[0166] In another embodiment, after the sixth sub-feature set sent by the authorization application agent is received, the first anti-forgery data authorization apparatus 500 further includes a generating unit that is specifically configured to: determine a seventh sub-feature set satisfying the discrimination condition in the sixth sub-feature set based on a discrimination degree between each feature in the sixth sub-feature set and the feature set library of the already-authorized data; and generate a second ownership certificate based on the seventh sub-feature set.

[0167] In another embodiment, after receiving the sixth sub-feature set sent by the right application agent, the first anti-forgery data right confirmation device 500 further comprises a second transmission unit, specifically configured to: in the case that the discrimination degree between the features in the sixth sub-feature set and the feature set library of the right data does not meet the discrimination degree condition and the number of right application times sent by the right application agent does not exceed the number threshold, send the fourth unpassed features in the sixth sub-feature set that do not meet the discrimination degree condition to the right application agent; receive the eighth sub-feature set sent by the right application agent; wherein the eighth sub-feature set is obtained by the right application agent based on a seventh feature extraction algorithm for feature extraction on the second data to be right confirmed, and the seventh feature extraction algorithm is different from the second feature extraction algorithm and the fifth feature extraction algorithm; or, receive the eighth sub-feature set sent by the right application agent, and send the third insertion rule and the third insertion content to the right application agent; wherein the eighth sub-feature set is obtained by the right application agent based on an eighth feature extraction algorithm for feature extraction on the fourth data to be right confirmed, and the fourth data to be right confirmed is obtained by replacing the content of the object corresponding to the eighth sub-feature set in the third data to be right confirmed with the third insertion content according to the third insertion rule; and the eighth feature extraction algorithm can be the same as or different from the second feature extraction algorithm.

[0168] In another embodiment, the second determination module 540 is specifically configured to: in the case that the first right certificate and the second right certificate are the same, send the first right certificate determined as the target right certificate to the right application agent; and in the case that the first right certificate and the second right certificate are different, send the second right certificate determined as the target right certificate to the right application agent. In another embodiment, the setting form of the first / second / third insertion content and the first / second / third insertion rule comprises at least one of the following: rule, configuration file, button, circle, check, mark, key, scroll wheel, menu, voice, video, eye contact, gesture, text, bioelectric signal, and virtual reality.

[0169] Figure 7 FIG. 2 is a structural schematic diagram of the anti-forgery data right confirmation device provided by the present application, as shown in the figure, the anti-forgery data right confirmation device 500 comprises: Figure 7 A third determination module 610 is configured to determine the first data to be right confirmed. A first extraction module 620 is configured to perform feature extraction on the first data to be right confirmed based on a first feature extraction algorithm to obtain a first feature set. A second extraction module 630 is configured to perform feature extraction on the second data to be right confirmed based on a second feature extraction algorithm to obtain a second feature set. The second transmission module 630 is configured to transmit the first feature set to the right system, and receive first insertion rules and corresponding first insertion contents corresponding to the first feature set transmitted by the right system; the first insertion rules and the first insertion contents are generated by the right system based on a degree of distinction between each feature in the first feature set and a feature set library of the right data; The insertion module 640 is configured to insert the first insertion contents into corresponding positions in the first data to be righted based on the first insertion rules, to obtain second data to be righted; The second extraction module 650 is configured to extract features from the second data to be righted based on a second feature extraction algorithm, to obtain a second feature set; The third transmission module 660 is configured to transmit the second feature set to the right system, and receive a target right certificate corresponding to the first data to be righted transmitted by the right system; the right certificate is determined by the right system based on a degree of distinction between each feature in the second feature set and the feature set library of the right data.

[0170] In another embodiment, the third transmission module 660 is specifically configured to: transmit the second feature set to the right system, and receive a first failed feature transmitted by the right system; select a feature different from the first failed feature as a second sub-feature set, or re-extract a new feature value corresponding to the first failed feature from the first data to be righted by using a third feature extraction algorithm as the second sub-feature set; transmit the second sub-feature set to the right system, and receive a right certificate transmitted by the right system; the right certificate is generated by the right system based on a passed feature in the second sub-feature set that meets the degree of distinction condition.

[0171] The application further provides a data right system for anti-counterfeiting, comprising a right system and a right application agent, wherein: The right application agent is configured to determine first data to be righted, extract features from the first data to be righted based on a first feature extraction algorithm to obtain a first feature set, transmit the first feature set to the right system, insert first insertion contents into corresponding positions in the first data to be righted based on first insertion rules to obtain second data to be righted, extract features from the second data to be righted based on a second feature extraction algorithm to obtain a second feature set, and transmit the second feature set to the right system, and receive a target right certificate corresponding to the first data to be righted transmitted by the right system; The ownership confirmation system is configured to receive a first feature set sent by an ownership confirmation application agent; determine a first insertion rule and a first insertion content corresponding to the first data to be confirmed based on the distinguishability between each feature in the first feature set and the feature set library of confirmed data; send the first insertion rule and the first insertion content to the ownership confirmation application agent; receive a second feature set sent by the ownership confirmation application agent; and determine the target ownership certificate corresponding to the first data to be confirmed based on the distinguishability between each feature in the second feature set and the feature set library of confirmed data, and send it to the ownership confirmation application agent.

[0172] Figure 8 This is a schematic diagram of the structure of the electronic device provided by the present invention, such as... Figure 8 As shown, the electronic device may include: a processor 710, a communications interface 720, a memory 730, and a communications bus 740, wherein the processor 710, the communications interface 720, and the memory 730 communicate with each other through the communications bus 740. The processor 710 can call logical instructions in the memory 730 to execute a data ownership confirmation method for preventing counterfeiting. This method includes: receiving a first feature set sent by an ownership confirmation application agent; the first feature set is obtained by the ownership confirmation application agent extracting features from first data to be confirmed based on a first feature extraction algorithm; determining a first insertion rule and a first insertion content corresponding to the first data to be confirmed based on the distinguishability between each feature in the first feature set and a feature set library of confirmed data; sending the first insertion rule and the first insertion content to the ownership confirmation application agent; receiving a second feature set sent by the ownership confirmation application agent; the second feature set is obtained by the ownership confirmation application agent extracting features from second data to be confirmed based on a second feature extraction algorithm; the second data to be confirmed is obtained by the ownership confirmation application agent inserting the first insertion content into a corresponding position in the first data to be confirmed based on the first insertion rule; determining a target ownership certificate corresponding to the first data to be confirmed based on the distinguishability between each feature in the second feature set and / or the first feature set and a feature set library of confirmed data, and sending it to the ownership confirmation application agent.

[0173] In addition, the logic instructions in the memory 730 described above can be implemented in the form of software functional units and sold or used as independent products, and can be stored in a computer readable storage medium. Based on such understanding, the technical solutions of the present application essentially or the parts that contribute to the prior art or parts of the technical solutions can be embodied in the form of a software product. The computer software product is stored in a storage medium, and includes a number of instructions for causing a computer device (which can be a personal computer, a server, or a network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of the present application. The aforementioned storage medium includes: a U disk, a mobile hard disk, a read-only memory (ROM, Read-Only Memory), a random access memory (RAM, Random Access Memory), a magnetic disk or an optical disk, and various media that can store program codes.

[0174] In another aspect, the present application also provides a computer program product, which comprises a computer program, the computer program can be stored on a non-transitory computer readable storage medium, and the computer program is executed by a processor, so that the computer can execute the anti-counterfeiting data right method provided by the above-mentioned method, the method comprises the following steps: receiving the first feature set sent by the right application agent; the first feature set is obtained by the right application agent based on the first feature extraction algorithm and the feature extraction of the first to be right data; determining the first insertion rule corresponding to the first to be right data and the first insertion content corresponding to the first to be right data based on the discrimination degree between each feature in the first feature set and the feature set library of the right data; sending the first insertion rule and the first insertion content to the right application agent, receiving the second feature set sent by the right application agent, the second feature set is obtained by the right application agent based on the second feature extraction algorithm and the feature extraction of the second to be right data, the second to be right data is obtained by the right application agent based on the first insertion rule and inserting the first insertion content into the corresponding position of the first to be right data; determining the target right certificate corresponding to the first to be right data based on the discrimination degree between each feature in the second feature set and / or the first feature set and the feature set library of the right data and sending to the right application agent.

[0175] In yet another aspect, the present application also provides a non-transitory computer-readable storage medium having stored thereon a computer program, which, when executed by a processor, implements the anti-counterfeiting data certification method provided by the above method, and the method comprises: receiving a first feature set sent by a certification application agent; the first feature set is obtained by the certification application agent based on a first feature extraction algorithm and performing feature extraction on first to-be-certified data; determining a first insertion rule corresponding to the first to-be-certified data and first insertion content corresponding to the first to-be-certified data based on a discrimination degree between each feature in the first feature set and a feature set library of certified data; sending the first insertion rule and the first insertion content to the certification application agent, receiving a second feature set sent by the certification application agent, the second feature set being obtained by the certification application agent based on a second feature extraction algorithm and performing feature extraction on second to-be-certified data, the second to-be-certified data being obtained by the certification application agent by inserting the first insertion content into a corresponding position in the first to-be-certified data based on the first insertion rule; determining a target ownership certificate corresponding to the first to-be-certified data based on a discrimination degree between each feature in the second feature set and / or the first feature set and the feature set library of certified data and sending to the certification application agent.

[0176] The device embodiments described above are merely illustrative, wherein the units illustrated as separate components can or can not be physically separate, and the components illustrated as units can or can not be physical units, i.e., can be located in one place, or can be distributed on multiple network units. Part or all of the modules can be selected to achieve the purpose of the embodiment according to actual needs. Those skilled in the art can understand and implement without creative labor.

[0177] From the above description of the embodiments, those skilled in the art can clearly understand that the embodiments can be realized by means of software and necessary universal hardware platforms, and of course can also be realized by hardware. Based on such understanding, the above technical solutions can be embodied in the form of a software product, which can be stored in a computer readable storage medium, such as a ROM / RAM, a magnetic disk, an optical disk, etc., and includes a plurality of instructions to make a computer device (which can be a personal computer, a server, or a network device, etc.) execute the methods described in each embodiment or some parts of the embodiments.

[0178] It should be pointed out finally that the above embodiments are only used to illustrate the technical solutions of the present application, but not to limit the same; and although the present application has been described in detail with reference to the foregoing embodiments, it should be appreciated by those skilled in the art that the technical solutions recorded in the foregoing embodiments can be modified, or some technical features thereof can be replaced equivalently; and these modifications or replacements do not make the essence of the corresponding technical solutions deviate from the spirit and scope of the technical solutions of the embodiments of the present application.

Claims

1. A method for preventing counterfeiting of data ownership, characterized in that, The data ownership confirmation method for preventing forgery, applied to the ownership confirmation system, includes: The first feature set is received by the agent for the application for confirmation of rights; the first feature set is obtained by the agent for the application for confirmation of rights from the first data to be confirmed of rights based on the first feature extraction algorithm. Based on the distinguishability between each feature in the first feature set and the feature set library of the confirmed data, the first insertion rule and the first insertion content corresponding to the first data to be confirmed are determined. The first insertion rule and the first insertion content are sent to the rights confirmation application agent, and the second feature set sent by the rights confirmation application agent is received. The second feature set is obtained by the rights confirmation application agent based on the second feature extraction algorithm to extract features from the second data to be confirmed. The second data to be confirmed is obtained by the rights confirmation application agent based on the first insertion rule to insert the first insertion content into the corresponding position in the first data to be confirmed. Based on the distinguishability between each feature in the second feature set and / or the first feature set and the feature set library of the confirmed data, the target ownership certificate corresponding to the first data to be confirmed is determined and sent to the confirmation application agent.

2. The data ownership confirmation method for preventing counterfeiting according to claim 1, characterized in that, The first insertion rule includes a first insertion sub-rule, and the first insertion content includes a first insertion sub-content. The step of determining the first insertion rule corresponding to the first data to be assigned rights and the first insertion content corresponding to the first data to be assigned rights based on the distinguishability between each feature in the first feature set and the feature set library of the already assigned rights data includes: Based on the distinguishability between each feature in the first feature set and the feature set library of the confirmed data, a first sub-feature set that satisfies the distinguishability condition in the first feature set is determined. Based on the first sub-feature set, the first insertion sub-rule and the first insertion sub-content are generated.

3. The data ownership confirmation method for preventing counterfeiting according to claim 2, characterized in that, The first insertion rule includes a second insertion sub-rule, and the first insertion content includes the second insertion sub-content. The step of determining the first insertion rule and the first insertion content corresponding to the first data to be assigned rights based on the distinguishability between each feature in the first feature set and the feature set library of the already assigned rights data includes: If there is a feature in the first feature set whose distinguishability with the feature set library of the confirmed data does not meet the distinguishability condition and the number of ownership applications sent by the ownership application agent does not exceed the number threshold, the first unsuccessful feature in the first feature set that does not meet the distinguishability condition will be sent to the ownership application agent. The system receives a second sub-feature set sent by the agent of the rights confirmation application; wherein the second sub-feature set includes features that are different from the first failed feature, or new feature values ​​corresponding to the first failed feature that are re-extracted from the first rights confirmation data using a third feature extraction algorithm; the third feature extraction algorithm is different from the first feature extraction algorithm. Based on the distinguishability between each feature in the second sub-feature set and the feature set library of the weighted data, the second insertion sub-rule and the second insertion sub-content are generated.

4. The data ownership confirmation method for preventing counterfeiting according to claim 3, characterized in that, The generation of the second insertion sub-rule and the second insertion sub-content based on the distinguishability between each feature in the second sub-feature set and the feature set library of the weighted data includes: Based on the distinguishability between each feature in the second sub-feature set and the feature set library of the weighted data, a third sub-feature set that satisfies the distinguishability condition is determined in the second sub-feature set; Based on the third sub-feature set, the second insertion sub-rule and the second insertion sub-content are generated.

5. The data ownership confirmation method for preventing counterfeiting according to claim 3, characterized in that, The generation of the second insertion sub-rule and the second insertion sub-content based on the distinguishability between each feature in the second sub-feature set and the feature set library of the weighted data includes: If there is a feature in the second sub-feature set whose distinguishability with the feature set library of the confirmed data does not meet the distinguishability condition and the number of ownership applications sent by the ownership application agent does not exceed the number threshold, the second failed feature in the second sub-feature set that does not meet the distinguishability condition will be sent to the ownership application agent. The system receives a fourth sub-feature set sent by the agent of the rights confirmation application; wherein the fourth sub-feature set includes features that are different from the second failed feature, or new feature values ​​corresponding to the second failed feature that are re-extracted from the first rights confirmation data using a fourth feature extraction algorithm; the fourth feature extraction algorithm is different from the first feature extraction algorithm and the third feature extraction algorithm. Based on the distinguishability between each feature in the fourth sub-feature set and the feature set library of the weighted data, the second insertion sub-rule and the second insertion sub-content are generated.

6. The data ownership confirmation method for preventing counterfeiting according to claim 1, characterized in that, The step of determining the target ownership certificate corresponding to the first data to be confirmed based on the distinguishability between each feature in the second feature set and / or the first feature set and the feature set library of the confirmed data includes: Based on the distinguishability between each feature in the second feature set and / or the first feature set and the feature set library of the confirmed data, a fifth sub-feature set that meets the distinguishability condition is determined. Based on the fifth sub-feature set, a first ownership certificate corresponding to the first data to be determined is generated; Based on the first ownership certificate, the target ownership certificate is determined.

7. The data ownership confirmation method for preventing counterfeiting according to claim 6, characterized in that, After generating the first ownership certificate corresponding to the first data to be determined based on the fifth sub-feature set, the method further includes: If there is a feature in the second feature set and / or the first feature set whose distinguishability with the feature set library of the confirmed data does not meet the distinguishability condition and the number of ownership applications sent by the ownership application agent does not exceed the number threshold, the third unpassed feature that does not meet the distinguishability condition will be sent to the ownership application agent. The application agent receives a sixth sub-feature set; wherein the sixth sub-feature set is obtained by the application agent based on a fifth feature extraction algorithm to extract features from the second data to be confirmed, and the fifth feature extraction algorithm is different from the second feature extraction algorithm. or, The system receives the sixth sub-feature set sent by the rights confirmation application agent, and simultaneously sends the second insertion rule and the second insertion content to the rights confirmation application agent; wherein, the sixth sub-feature set is obtained by the rights confirmation application agent extracting features from the third data to be confirmed based on the sixth feature extraction algorithm, and the third data to be confirmed is obtained by replacing the content of the object corresponding to the sixth sub-feature set in the second data to be confirmed with the second insertion content according to the second insertion rule; the sixth feature extraction algorithm and the second feature extraction algorithm may be the same or different.

8. The data ownership confirmation method for preventing counterfeiting according to claim 7, characterized in that, After receiving the sixth sub-feature set sent by the rights confirmation application agent, the method further includes: Based on the distinguishability between each feature in the sixth sub-feature set and the feature set library of the confirmed data, a seventh sub-feature set that satisfies the distinguishability condition in the sixth sub-feature set is determined. A second ownership certificate is generated based on the seventh sub-feature set.

9. The data ownership confirmation method for preventing counterfeiting according to claim 7, characterized in that, After receiving the sixth sub-feature set sent by the rights confirmation application agent, the method further includes: If, in the sixth sub-feature set, there exists a feature whose distinguishability with the feature set library of the confirmed data does not meet the distinguishability condition, and the number of ownership applications sent by the ownership application agent does not exceed the number threshold, then the fourth unsuccessful feature in the sixth sub-feature set that does not meet the distinguishability condition will be sent to the ownership application agent. The eighth sub-feature set sent by the rights confirmation application agent is received; wherein the eighth sub-feature set is obtained by the rights confirmation application agent based on the seventh feature extraction algorithm to extract features from the second data to be confirmed, and the seventh feature extraction algorithm is different from the second feature extraction algorithm and the fifth feature extraction algorithm. or, The system receives the eighth sub-feature set sent by the rights confirmation application agent, and simultaneously sends the third insertion rule and the third insertion content to the rights confirmation application agent; wherein, the eighth sub-feature set is obtained by the rights confirmation application agent extracting features from the fourth data to be confirmed based on the eighth feature extraction algorithm, and the fourth data to be confirmed is obtained by replacing the content of the object corresponding to the eighth sub-feature set in the third data to be confirmed with the third insertion content according to the third insertion rule; the eighth feature extraction algorithm and the second feature extraction algorithm may be the same or different.

10. The data ownership confirmation method for preventing counterfeiting according to claim 8, characterized in that, The step of determining the target ownership certificate based on the first ownership certificate includes: If the first ownership certificate and the second ownership certificate are the same, the first ownership certificate will be identified as the target ownership certificate and sent to the ownership confirmation application agent. If the first ownership certificate and the second ownership certificate are different, the second ownership certificate is identified as the target ownership certificate and sent to the ownership confirmation application agent.

11. The data ownership confirmation method for preventing counterfeiting according to claim 9, characterized in that, The setting forms of the first / second / third inserted content and the first / second / third inserted rules include at least one of the following: rule-based, configuration file, button, circle, checkmark, mark, key, scroll wheel, menu, voice, video, eye contact, gesture, text, bioelectrical signal, and virtual reality.

12. A method for preventing data forgery, characterized in that, Applied to the agency of rights confirmation application, the anti-counterfeiting data rights confirmation method includes: Identify the first data to be confirmed; Based on the first feature extraction algorithm, feature extraction is performed on the first data to be confirmed, resulting in a first feature set; The first feature set is sent to the rights confirmation system, and the system receives the first insertion rule and the corresponding first insertion content for the first feature set sent by the rights confirmation system. The first insertion rule and the first insertion content are generated by the rights confirmation system based on the distinguishability between each feature in the first feature set and the feature set library of confirmed data. Based on the first insertion rule, the first insertion content is inserted into the corresponding position in the first data to be confirmed, to obtain the second data to be confirmed; Based on the second feature extraction algorithm, features are extracted from the second data to be determined to obtain a second feature set; The second feature set is sent to the ownership confirmation system, and the target ownership certificate corresponding to the first data to be confirmed is received from the ownership confirmation system. The target ownership certificate is determined by the ownership confirmation system based on the distinguishability between each feature in the second feature set and / or the first feature set and the feature set library of the confirmed data.

13. The data ownership confirmation method for preventing counterfeiting according to claim 12, characterized in that, The step of sending the second feature set to the ownership confirmation system and receiving the target ownership certificate corresponding to the first ownership data to be confirmed from the ownership confirmation system includes: The second feature set is sent to the rights confirmation system, and the first failed feature sent by the rights confirmation system is received. Select features that are different from the first failed feature as the second sub-feature set, or use a third feature extraction algorithm to re-extract the new feature values ​​corresponding to the first failed feature from the first data to be confirmed as the second sub-feature set; The second sub-feature set is sent to the ownership confirmation system, and the target ownership certificate sent by the ownership confirmation system is received. The target ownership certificate is generated by the ownership confirmation system based on the features in the second sub-feature set that meet the distinguishability condition.

14. A data ownership verification device for preventing forgery, characterized in that, The anti-counterfeiting data ownership verification device includes: The first receiving module is used to receive a first feature set sent by the rights confirmation application agent; the first feature set is obtained by the rights confirmation application agent based on a first feature extraction algorithm to extract features from the first data to be confirmed. The first determining module is used to determine the first insertion rule and the first insertion content corresponding to the first data to be determined based on the distinguishability between each feature in the first feature set and the feature set library of the data to be determined; The first transmission module is used to send the first insertion rule and the first insertion content to the rights confirmation application agent, and to receive the second feature set sent by the rights confirmation application agent; the second feature set is obtained by the rights confirmation application agent to extract features from the second data to be confirmed based on the second feature extraction algorithm, and the second data to be confirmed is obtained by the rights confirmation application agent to insert the first insertion content into the corresponding position of the first data to be confirmed based on the first insertion rule; The second determining module is used to determine the target ownership certificate corresponding to the first ownership data to be confirmed based on the distinguishability between each feature in the second feature set and / or the first feature set and the feature set library of the confirmed ownership data, and send it to the ownership application agent.

15. A data ownership verification device for preventing forgery, characterized in that, The anti-counterfeiting data ownership verification device includes: The third determining module is used to determine the first data to be confirmed. The first extraction module is used to extract features from the first data to be confirmed based on the first feature extraction algorithm to obtain a first feature set; The second transmission module is used to send the first feature set to the rights confirmation system and receive the first insertion rule and the corresponding first insertion content sent by the rights confirmation system for the first feature set; the first insertion rule and the first insertion content are generated by the rights confirmation system based on the distinguishability between each feature in the first feature set and the feature set library of confirmed data. An insertion module is used to insert the first insertion content into the corresponding position in the first data to be confirmed based on the first insertion rule, so as to obtain the second data to be confirmed. The second extraction module is used to extract features from the second data to be determined based on the second feature extraction algorithm to obtain a second feature set. The third transmission module is used to send the second feature set to the rights confirmation system and receive the target ownership certificate corresponding to the first data to be confirmed sent by the rights confirmation system. The target ownership certificate is determined by the rights confirmation system based on the distinguishability between each feature in the second feature set and the feature set library of the confirmed data.

16. A data ownership confirmation system to prevent forgery, characterized in that, This includes the land ownership confirmation system and land ownership confirmation application agents, among which: The rights confirmation application agent is used to determine the first data to be confirmed; based on a first feature extraction algorithm, features are extracted from the first data to be confirmed to obtain a first feature set; the first feature set is sent to the rights confirmation system, and based on a first insertion rule, the first insertion content is inserted into the corresponding position in the first data to be confirmed to obtain the second data to be confirmed; based on a second feature extraction algorithm, features are extracted from the second data to be confirmed to obtain a second feature set; the second feature set is sent to the rights confirmation system, and the agent receives the target ownership certificate corresponding to the first data to be confirmed from the rights confirmation system. The ownership confirmation system is configured to receive a first feature set sent by an ownership confirmation application agent; determine a first insertion rule and a first insertion content corresponding to the first data to be confirmed based on the distinguishability between each feature in the first feature set and the feature set library of confirmed data; send the first insertion rule and the first insertion content to the ownership confirmation application agent; receive a second feature set sent by the ownership confirmation application agent; and determine the target ownership certificate corresponding to the first data to be confirmed based on the distinguishability between each feature in the second feature set and the feature set library of confirmed data, and send it to the ownership confirmation application agent.

17. An electronic device comprising a memory, a processor, and a computer program stored in the memory and running on the processor, characterized in that, When the processor executes the computer program, it implements the data ownership confirmation method against counterfeiting as described in any one of claims 1 to 13.

18. A non-transitory computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by a processor, it implements the data ownership confirmation method against counterfeiting as described in any one of claims 1 to 13.

19. A computer program product, comprising a computer program, characterized in that, When the computer program is executed by a processor, it implements the data ownership confirmation method against counterfeiting as described in any one of claims 1 to 13.

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