Digital copyright confirmation system based on block chain analysis and use method thereof

Abstract

The invention discloses a block chain analysis-based digital copyright confirmation system and a use method thereof, and the system comprises a conversion module which is used for converting copyright into a block chain of a character or binary code; the selection module comprises a check box for character or binary coding key extraction information; the optimization algorithm comprises a self-adaptive unit for converting the selection content and the selection range of the check box, the self-adaptive unit actively learns and adjusts through a neural network, and the conversion module comprises a character conversion unit and a binary conversion unit. According to the digital copyright, the digital copyright is converted into a mixed hash value with numbers and English letters through a character conversion unit. The invention relates to the technical field of block chain right confirmation. According to the method, the block chain is deeply analyzed, different items and the same item in the block chain set are obtained, and the block chain is concluded and classified again, so that the required authentication result is conveniently and quickly searched, and the search efficiency of the right confirmation result is improved.

Description

Technical Field

[0001] The present invention relates to the field of blockchain rights confirmation technology, and specifically to a digital copyright confirmation system based on blockchain analysis and a method of using the same. Background Art

[0002] Blockchain is a specific distributed database technology. Its essence is a decentralized data recording technology. Its main features are data immutability, transparency and security. Blockchain has the following key features and principles:

[0003] Decentralization: The blockchain database does not rely on a centralized management agency, but instead maintains and verifies the integrity of the data through multiple nodes in the network.

[0004] Distributed ledger: Data records in the blockchain are distributed and stored on multiple nodes of the network, rather than being centrally stored on a single central server.

[0005] Unalterable records: Blockchain uses cryptography technology to ensure the security and immutability of data. Once the data is recorded and confirmed, it is almost impossible to modify it.

[0006] Transparency and anonymity: All transaction records and data in the blockchain are publicly accessible, but the identities of the participants can be anonymous, depending on the specific blockchain design.

[0007] Therefore, blockchain technology has potential application value in multiple industries due to its characteristics of decentralization, security and transparency, and is gradually being widely explored and adopted.

[0008] The patent with publication number CN112651052A discloses a data rights confirmation method and system based on blockchain technology. The patent specifically discloses that "the present application discloses a data rights confirmation method and system based on blockchain technology, including initializing and verifying digital certificates; generating user DID and data DID and uploading them to the chain; calculating the hash value of the data to be confirmed and signing it to obtain the hash value and signature; applying for an authoritative timestamp based on the hash value of the data to be confirmed; generating a data certificate for the data to be confirmed based on the user DID, data DID, timestamp, hash value and signature on the chain, verifying the data certificate and calculating its hash value, and signing the hash value of the data certificate to obtain a signature certificate" The technical solution realizes "uploading the verified data certificate and signature certificate to the chain, obtaining the chain hash of the confirmation record and returning it to the client. The present application adopts a decentralized digital identity DID to store the data confirmation information of the data to be confirmed in the blockchain in the form of a verifiable certificate, which not only realizes the confirmation function of the data to be confirmed, but also ensures the verifiability, traceability, and tamper-proof characteristics of the data confirmation information."

[0009] However, although this technology has achieved blockchain title confirmation during actual use, it is difficult for the device to find the title confirmation results in the face of a huge blockchain database, and it is also unable to summarize and organize the title confirmation results found, so there is room for improvement. Summary of the invention

[0010] The purpose of the present invention is to provide a digital copyright confirmation system based on blockchain analysis and a method of using the same to solve the problems raised in the above-mentioned background technology.

[0011] To achieve the above-mentioned purpose, the present invention provides the following technical solutions: a digital copyright confirmation system based on blockchain analysis, comprising a conversion module, which is used to convert copyright into a character or binary-coded blockchain; a selection module, which comprises a selection box for character or binary-coded key extraction information respectively; and an optimization algorithm, which comprises an adaptive unit for transforming the selection content and selection range of the selection box, and the adaptive unit is actively learned and adjusted through a neural network.

[0012] Digital copyright confirmation system based on blockchain analysis and its use method, including

[0013] Step S1: The neural network performs preliminary inductive analysis on the pooling layer and convolution layer;

[0014] Step S2: The pooling layer and convolution layer are further attributed to obtain different items;

[0015] Step S3: The neural network extracts the same items among the different items;

[0016] Step S4: split different items again and filter out identical items in a loop;

[0017] Step S5: different item sets are merged into the reverse tracing library blockchain;

[0018] Step S6: The library blockchain is summarized and forms a new title confirmation library

[0019] As a further solution of the present invention: a digital copyright confirmation system based on blockchain analysis, the conversion module includes a character conversion unit and a binary conversion unit, the digital copyright is converted into a mixed hash value with numbers and English letters through the character conversion unit, and the digital copyright is converted into a binary code that conforms to computer logic through the binary conversion unit.

[0020] As a further solution of the present invention: the digital copyright confirmation system based on blockchain analysis also includes a confirmation library, which has a database unit for differentiating and identifying authentication types. The database unit automatically classifies digital copyright types through neural network intervention, comparison and extraction of hash values ​​and binary information.

[0021] As a further solution of the present invention: a digital copyright confirmation system based on blockchain analysis, the confirmation library selects the library blockchain of the comprehensive association information of hash value strings or the comprehensive association information of binary code strings through a neural network.

[0022] As a further solution of the present invention: the digital copyright confirmation system based on blockchain analysis also includes a crawling unit, which is used to crawl source information of hash value strings or binary code strings.

[0023] As a further solution of the present invention: a digital copyright confirmation system based on blockchain analysis, the neural network includes an RNN convolution algorithm, and the RNN convolution algorithm uses common items in the library blockchain as a convolution layer and associated information as a pooling layer to perform convolution learning to determine the authentication scope.

[0024] As a further solution of the present invention: a digital copyright confirmation system based on blockchain analysis, the neural network pools and analyzes the same items or different items in the library blockchain, and the neural network establishes a classified confirmation library based on different items.

[0025] Compared with the prior art, the present invention has the following beneficial effects:

[0026] This application conducts in-depth analysis of the blockchain, obtains different items and identical items in the blockchain collection, and then reclassifies the blockchain, so as to facilitate quick search for the required authentication results and improve the search efficiency of the confirmation results. BRIEF DESCRIPTION OF THE DRAWINGS

[0027] Figure 1 This is a schematic diagram of the digital copyright confirmation system based on blockchain analysis and its use method of the present invention. DETAILED DESCRIPTION

[0028] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0029] In the description of the present invention, it should be noted that, for those skilled in the art, the specific meanings of the above terms in the present invention can be understood in specific situations. The following describes an embodiment of the present invention based on its overall structure.

[0030] In an embodiment of the present invention, a digital copyright confirmation system based on blockchain analysis and a method for using the same include a conversion module, wherein the conversion module is used to convert copyright into a character or binary-coded blockchain;

[0031] A selection module, the selection module includes a selection box for extracting character or binary code key information respectively; and an optimization algorithm, the optimization algorithm includes an adaptive unit for transforming the selection content and selection range of the selection box, and the adaptive unit is actively learned and adjusted through a neural network.

[0032] Other embodiments of the present invention: The conversion module includes a character conversion unit and a binary conversion unit. The character conversion unit converts the digital copyright into a mixed hash value with numbers and English letters, and the binary conversion unit converts the digital copyright into a binary code that conforms to computer logic.

[0033] In the embodiment, if the digital copyright converts the confirmation object into a hash value string such as 1A...c2d, n2...ghg through the character conversion unit, the digital copyright can also convert the confirmation object into a binary code composed of 0 and 1 through the binary conversion unit.

[0034] Other embodiments of the present invention also include a title confirmation library and a crawling unit, wherein the title confirmation library is provided with a database unit for differentiating and identifying authentication types, and the database unit automatically classifies digital copyright types by intervening, comparing and extracting hash values ​​and binary information through a neural network. The title confirmation library selects a library blockchain of comprehensive associated information of hash value strings or comprehensive associated information of binary code strings through a neural network, and the crawling unit crawls source information of hash value strings or binary code strings.

[0035] In the embodiment, in hash value strings such as 1A2d...c2d, n2...ghg, 1A2n...ghg, 2d...bcbd, etc., the neural network will intervene and compare the hash value strings, and extract common items (such as 1A2d...c2d and 1A2n...ghg have a common item of 1A, and n2...ghg and 1A2n...ghg have a common item of ghg), and then the neural network will crawl and convert the blockchain information of the string through python, crawl out the related information such as the name, submission time, property owner, and place of conclusion in the digital copyright, and then use the library blockchain of common items + related information (such as 1A+(submission time, property owner, place of conclusion) or ghg+(property owner, place of conclusion)).

[0036] Similarly, in binary code strings such as 0101111…101, 01100111000…111000111, etc., the neural network also intervenes and compares the binary code strings, but the difference is that the code length of the binary code string is related to the size of the information content (because the content size of digital copyrights of the same type is similar, the digital copyrights are preliminarily selected by limiting the code length of the binary code string to narrow the selection range). Therefore, the neural network unit will first limit a code string with a specified upper and lower floating range (such as the number of 01s in the code string is N, and the number of codes allowed in the upper and lower floating interval is m, then the allowed length of the code string is N±m), and crawl out the common items and the number of cycles of the common items, as well as the title confirmation information before the binary code string conversion according to the crawling logic of the hash value string, and then use the library blockchain of the common items (111 (item) + number of cycles) + related information (submission time, property owner, and place of conclusion) in the same way.

[0037] In other embodiments of the present invention, the neural network includes an RNN convolution algorithm, which performs convolution learning using common items in the library blockchain as a convolution layer and associated information as a pooling layer to determine the authentication scope.

[0038] In the embodiment, the input information of several library blockchains (including common direction + associated information) is divided into RNN processing items including common item A + associated information B, where the common item A as the convolution layer can be divided into convolution pools adapted to the QR code string or the binary code string.

[0039] Step S1: including string contents such as 1A2d...c2d, 1A2n...ghg, n2...ghg or 1A2n...ghg, and then searching for common items 1A and ghg from the string according to the method of the above embodiment, wherein 1A and ghg are associated with the associated information in the pooling layer, and 1A is matched with the submission time, the property owner, the place of conclusion, etc., so that the neural network first defaults to 1A = the determined submission time, the property owner, the place of conclusion information, and ghg = the result of the property owner and the place of conclusion;

[0040] Step S2: 1A or ghg is then split. Specifically, the neural network will also integrate other hash value strings and related information, such as (under the default 1A = determined submission time, property party, and conclusion location information condition) items with the same related information (submission time, property party, and conclusion location information) but different hash values ​​2C are recorded;

[0041] Step S3: Split the different hash values ​​2C, then compare 2C with 1A or ghg, filter out the same items in 2C, 1A or ghg, and also filter out the associated information containing the same items (for example, if the same items are submission time and property rights party, they are filtered out together, leaving 1A with a place of conclusion that 2C and ghg do not have, 2C has a separate third party, ghg has a separate title confirmation plan, etc.), and extract the different items;

[0042] Step S4: The neural network splits different items (such as 2C, 1A or ghg) again and assigns the accompanying associated information to other hash value strings or binary code strings in the library blockchain. After filtering out the same items through circular pooling, all different items are collected;

[0043] Step S5: The neural network aggregates the different items and traces the associated information of the different items (i.e., the nature of the individual rights, including the confirmation path, confirmation time, right holder, right method, etc.), and then takes the different items as the first item and traces back the library blockchain;

[0044] Step S6: reverse analysis of the library blockchain, generating a blockchain title confirmation library with the associated information as the first item and the different items as the second item (this step is divided into categories based on the nature of the rights), and recycling it to the title confirmation library for reference.

[0045] The working principle of the present invention is: the present application conducts in-depth analysis of the blockchain, obtains different items and identical items in the blockchain set, and then reclassifies the blockchain, so as to facilitate rapid search for the required authentication results and improve the search efficiency of the confirmation results.

[0046] What is described above is only a preferred specific implementation manner of the present invention, but the protection scope of the present invention is not limited thereto. Any technician familiar with the technical field can make equivalent replacements or changes according to the technical scheme and inventive concept of the present invention within the technical scope disclosed by the present invention, which should be covered by the protection scope of the present invention.

Claims

1. A digital copyright confirmation system based on blockchain analysis, characterized by: A conversion module is included, wherein the conversion module is used to convert the copyright into a character or binary coded blockchain; A selection module, the selection module comprising selection boxes for character or binary coded key extraction information respectively; as well as An optimization algorithm includes an adaptive unit for transforming the selection content and selection range of a selection box, and the adaptive unit is actively learned and adjusted through a neural network.

2. The digital copyright confirmation system based on blockchain analysis according to claim 1 is characterized in that: The conversion module includes a character conversion unit and a binary conversion unit. The character conversion unit converts the digital copyright into a mixed hash value with numbers and English letters, and the binary conversion unit converts the digital copyright into a binary code that conforms to computer logic.

3. The digital copyright confirmation system based on blockchain analysis according to claim 2 is characterized in that: It also includes a rights confirmation library, which has a database unit for differentiating and identifying authentication types. The database unit automatically classifies digital copyright types by intervening, comparing and extracting hash values ​​and binary information through neural network.

4. The digital copyright confirmation system based on blockchain analysis according to claim 3 is characterized in that: The title confirmation library selects the library blockchain of the comprehensive associated information of the hash value string or the comprehensive associated information of the binary code string through a neural network.

5. The digital copyright confirmation system based on blockchain analysis according to claim 4 is characterized in that: It also includes a crawling unit, which is used to crawl source information of hash value strings or binary code strings.

6. The digital copyright confirmation system based on blockchain analysis according to claim 5 is characterized in that: The neural network includes an RNN convolution algorithm, which performs convolution learning with common items in the library blockchain as a convolution layer and associated information as a pooling layer to determine the authentication scope.

7. The digital copyright confirmation system based on blockchain analysis according to claim 6 is characterized in that: The neural network pools and analyzes the same items or different items in the library blockchain, and the neural network establishes a classified title confirmation library based on the different items.

8. The digital copyright confirmation system based on blockchain analysis and its use method according to claim 7 is characterized in that: include Step S1: The neural network performs preliminary inductive analysis on the pooling layer and convolution layer; Step S2: The pooling layer and convolution layer are further attributed to obtain different items; Step S3: The neural network extracts the same items among the different items; Step S4: split different items again and filter out identical items in a loop; Step S5: different item sets are merged into the reverse tracing library blockchain; Step S6: The library blockchain is summarized and forms a new title confirmation library.

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