A blockchain-based art digital asset right confirmation and circulation system

Abstract

The application relates to a blockchain-based art digital asset right confirmation circulation system, which comprises a data layer, a network layer, a consensus layer, a contract layer and an application layer arranged in sequence from bottom to top, and provides a decentralized right confirmation and circulation means for digital art on the network. The right confirmation of the art is completed by casting NFT as a digital certificate, the data layer adopts a dual storage mode of ''on-chain + off-chain'', thereby reducing the overall storage load of the blockchain and improving the operation efficiency of the system; through a multi-NFT aggregation casting scheme, the IPFS hash values corresponding to the NFTs of multiple users are continuously hashed by using a Merkle Tree, finally an NFT aggregation tree of a full binary tree type is obtained, then the root node hash value of the tree is saved to the blockchain, casting is completed, and energy consumption is reduced; NFT is audited through deep learning technology, chain-on NFT casting and chain-off AI auditing credible intercommunication are realized, and efficient and accurate similarity detection is carried out on the NFT cast by all users.

Description

Technical Field

[0001] This invention relates to the field of blockchain technology, and in particular to a blockchain-based system for the confirmation and circulation of digital assets related to artworks. Background Technology

[0002] In modern Chinese society, with its ever-developing economy, people's demands for a better life are constantly increasing. Material abundance also inspires people's pursuit of spiritual fulfillment. In today's popular investment and trading sectors, besides economically related areas such as real estate and stocks, art, which possesses not only economic value but also cultural value, is increasingly attracting attention. On the one hand, people value its monetary worth; on the other hand, the aesthetic and other sensual aspects of art provide immense spiritual satisfaction. In today's era of advanced information technology, art transactions based on the internet have begun to develop. Compared to traditional trading methods, online art transactions are characterized by speed, convenience, transparency, and international integration.

[0003] The NFT industry currently faces the following pressing issues: First, speculation. The limited issuance and scarcity of NFTs easily trigger speculation and price bubbles. Second, the inability to confirm ownership of native assets. While blockchain technology can trace the information of digital content already on the chain, ensuring its authenticity and ownership, there are loopholes in the asset ownership confirmation process before the digital content is minted into NFTs. Minting platforms cannot verify the copyright ownership of digital content. Third, energy consumption. The surge in NFT products and transaction volume consumes a large amount of energy. Summary of the Invention

[0004] This invention provides a blockchain-based digital asset ownership confirmation and circulation system for artworks, which can effectively solve the problems in the background technology.

[0005] To achieve the above objectives, the technical solution adopted by the present invention is as follows:

[0006] A blockchain-based digital asset ownership confirmation and circulation system for artworks includes, from bottom to top, a data layer, a network layer, a consensus layer, a contract layer, and an application layer.

[0007] The data layer adopts a dual storage mode of on-chain and off-chain, including a database blockchain, an interplanetary file system, and a data management system.

[0008] The network layer includes a P2P network, a propagation mechanism, and a verification mechanism, and encapsulates the networking method and message propagation protocol of the Ethereum blockchain.

[0009] The consensus layer adopts the Proof-of-Work (PoW) consensus algorithm mechanism in Ethereum, and the contract layer is used to run the system's script code, algorithms, and protocols.

[0010] The application layer provides a human-computer interaction interface and interacts with smart contracts and backend databases.

[0011] The data layer, consensus layer, contract layer, and application layer are all located in the same blockchain network.

[0012] Furthermore, the on-chain storage mode adopts a decentralized distributed database blockchain to store the metadata corresponding to the casting of digital artworks;

[0013] The off-chain storage mode stores the complete content of digital artworks through the InterPlanetary File System, and the data management system uses MySQL as the backend database.

[0014] Furthermore, the contract layer includes NFTOracle, OneRingNFT, and NFTMarketPlace. The NFTOracle interfaces the on-chain NFTs to be minted with the off-chain detection module.

[0015] The OneRingNFT process handles the creation, querying, and management of artworks, while the NFTMarketPlace process handles the trading, display, and auctioning of artworks.

[0016] Furthermore, an NFT verification module based on a blockchain oracle is set up to facilitate data interaction between the on-chain NFT minting contract and the off-chain detection system.

[0017] Furthermore, the NFT verification module includes an on-chain part and an off-chain part. The on-chain part includes the OneRingNFT and the NFTOracle, and the off-chain part includes a detection system.

[0018] The OneRingNFT contract receives a minting request and, while calling the NFTOracle contract, passes in the NFT information to be reviewed. The NFTOracle contract adds the NFT information and triggers the off-chain detection system. After the detection system completes the detection, it writes the result back to the chain.

[0019] Furthermore, the detection system employs an NFT similarity detection method based on deep learning object detection, comprising the following steps:

[0020] First, acquire artwork image data and extract local features of the images using SIFT; second, quantify the local features of the images through clustering to construct visual words; then construct a visual word frequency histogram of the images and use dynamic distance measurement to achieve similar and repeating image detection; finally, output images similar to the image data.

[0021] Furthermore, the casting process for artwork NFTs includes the following steps:

[0022] Users upload artwork to IPFS and obtain the corresponding IPFS hash value, denoted as tokenUrl;

[0023] The user calls the safeMint() function in OneRingNFT and passes tokenUrl as a parameter. The tokenUrlPassed function is used to determine whether the NFT has passed the backend review.

[0024] If tokenUrlPassed returns a result indicating that the review failed, then the casting process has failed.

[0025] If tokenUrlPassed returns a result indicating approval, afeMint() is successfully called, and the user is notified to pay the casting fee.

[0026] Furthermore, during the casting process, a multi-user NFT aggregation casting method is employed, including the following steps:

[0027] S1: Upload each NFT to the InterPlanetary File System and obtain the corresponding hash value. Several hash values ​​constitute the leaf nodes of the tree.

[0028] S2: Perform a hash calculation on the values ​​of two adjacent leaf nodes to obtain the value of the parent node;

[0029] S3: Repeat step S2 to further aggregate all parent nodes and finally obtain the unique root node;

[0030] S4: Finally, the root node hash value is published to the blockchain via a smart contract to complete the minting process.

[0031] A computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the aforementioned blockchain-based digital asset ownership confirmation and circulation system for artworks.

[0032] A terminal includes: one or more processors and a memory, and one or more applications; wherein the one or more applications are stored in the memory and configured to be executed by the one or more processors, and the one or more applications are configured to execute the aforementioned blockchain-based digital asset ownership confirmation and circulation system for artworks.

[0033] The beneficial effects of this invention are as follows:

[0034] In this invention, a multi-NFT aggregation casting scheme is designed. MerkleTree is used to continuously perform hash calculations on the IPFS hash values ​​corresponding to the NFTs of multiple users, and finally obtains a complete binary tree-type NFT aggregation tree. Then, the hash value of the root node of the tree is saved to the blockchain to complete the casting. This reduces the user's casting fees and solves the serious energy consumption problem caused by blockchain and other technologies.

[0035] This invention utilizes deep learning object detection technology combined with blockchain oracle technology to achieve trusted interoperability between on-chain NFT creation and off-chain AI verification. It enables efficient and accurate similarity detection of all user-created NFTs, preventing plagiarism and other acts of plagiarism, and solving the problem of unauthorized ownership of native art assets.

[0036] This invention system relies on Ethereum and IPFS decentralized storage. The immutability of decentralized storage and blockchain together ensures that the content of digital assets is immutable. Smart contracts control the ownership and transfer of digital assets. By minting NFTs, artworks are digitized and made into assets. The decentralized approach also fundamentally changes the relationship between creators and end consumers, reducing the commission and share taken by intermediaries. Attached Figure Description

[0037] To more clearly illustrate the technical solutions in the embodiments of the present 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 only some embodiments recorded in the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0038] Figure 1 This is a schematic diagram of the system architecture in an embodiment of the present invention;

[0039] Figure 2 This is a schematic diagram of the overall system operation process in an embodiment of the present invention;

[0040] Figure 3 This is a schematic diagram illustrating the logical principle of NFT in an embodiment of the present invention;

[0041] Figure 4 This is a schematic diagram of an NFT verification module based on a blockchain oracle in an embodiment of the present invention;

[0042] Figure 5 This is a schematic diagram of the NFT casting process in an embodiment of the present invention;

[0043] Figure 6 This is a schematic diagram of the NFT aggregation process in an embodiment of the present invention. Detailed Implementation

[0044] The technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments.

[0045] It should be noted that when an element is referred to as being "fixed to" another element, it can be directly attached to the other element or there may be an intervening element. When an element is referred to as being "connected to" another element, it can be directly connected to the other element or there may be an intervening element. The terms "vertical," "horizontal," "left," "right," and similar expressions used herein are for illustrative purposes only and do not represent the only possible implementation.

[0046] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention pertains. The terminology used herein in the description of the invention is for the purpose of describing particular embodiments only and is not intended to be limiting of the invention. The term "and / or" as used herein includes any and all combinations of one or more of the associated listed items.

[0047] like Figures 1 to 6 The illustrated blockchain-based digital asset ownership confirmation and circulation system for artworks includes, from bottom to top, a data layer, a network layer, a consensus layer, a contract layer, and an application layer. The data layer adopts a dual storage mode combining on-chain and off-chain storage, including a database blockchain, an interplanetary file system, and a data management system.

[0048] The network layer includes a P2P network, propagation mechanism, and verification mechanism, and encapsulates the networking method and message propagation protocol of the Ethereum blockchain; the consensus layer adopts the PoW consensus algorithm mechanism in Ethereum; the contract layer is used to run the system's script code, algorithms, and protocols; the application layer provides a human-computer interaction interface and interacts with smart contracts and backend databases; the data layer, consensus layer, contract layer, and application layer are all located in the same blockchain network.

[0049] Furthermore, in this application, the on-chain storage mode adopts a decentralized distributed database blockchain to store the metadata corresponding to the minted digital artworks; the off-chain storage mode stores the complete content of the digital artworks through the InterPlanetary File System, and the data management system uses MySQL as the backend database of the system.

[0050] The contract layer includes NFTOracle, OneRingNFT, and NFTMarketPlace. NFTOracle connects the on-chain NFTs to be minted with the off-chain detection module; OneRingNFT handles the minting, querying, and management information of artworks; and NFTMarketPlace handles the trading, display, and auction information of artworks.

[0051] like Figure 1 The diagram shows the system architecture of the solution described in this invention. Specifically, the data layer adopts a dual storage mode of "on-chain + off-chain," thereby reducing the overall storage load of the blockchain and improving the system's operating efficiency. The on-chain layer uses a decentralized distributed database blockchain, storing only the metadata corresponding to the minted digital artworks, while the complete content of the digital artworks is stored off-chain in IPFS (InterPlanetary File System). MySQL (data management system) serves as the system's backend database, used to store user data and pre-cache the NFT content of the entire system, thereby improving the user experience.

[0052] Furthermore, the network layer includes P2P networks, propagation mechanisms, and verification mechanisms. This layer encapsulates the networking method and message propagation protocol of the Ethereum blockchain. When a user publishes a transaction to the Ethereum network, Ethereum miners will package it into a block locally. If the miner successfully mines the block, they gain the right to record the transaction.

[0053] The consensus layer adopts the Proof-of-Work (PoW) consensus algorithm mechanism currently used by Ethereum, and Ethereum will be able to transition to the PoS consensus algorithm in the future.

[0054] The contract layer comprises the smart contracts of the entire system, mainly consisting of three entities: NFTOracle, OneRingNFT, and NFTMarketPlace. NFTOracle is part of the system's blockchain oracle-based NFT verification module. As an on-chain contract, it interacts with the NFTOracle, connecting the on-chain NFTs to be minted with the off-chain deep learning-based object detection NFT similarity detection module, thereby verifying the digital artworks submitted by users. OneRingNFT is responsible for the minting, querying, and management of digital artworks. NFTMarketPlace is responsible for the trading, display, and auctioning of digital artworks.

[0055] The application layer primarily includes the system's main functions, such as NFT minting, listing, auctioning, trading, displaying, and recommending. The application layer interacts with smart contracts through interfaces such as web.js and JSON-RPC, and then exchanges data with the backend database using RESTful APIs, thus providing users with a user-friendly interface.

[0056] During the use of the above system, such as Figure 2 As shown, users log in to the system via their account and password on the front-end page. If the back-end detects the user information logged in from the front-end, it sends relevant data cached in the MySQL database, such as NFT data, transaction offers, and NFT minting status, to the front-end in JSON format. This eliminates the need to query from IPFS or the blockchain, improving the user experience. Furthermore, the back-end continuously caches and monitors events such as mints and offers occurring in the blockchain, downloading and caching them in advance.

[0057] If there are too many NFTs, users may experience fatigue when browsing them. Therefore, an art recommendation module based on a restricted Boltzmann machine can be proposed, which can show users NFTs that they might be interested in based on their information, thereby improving the user experience.

[0058] When a user wants to create digital artwork, after submitting the submission on the front-end page, the NFT's URL (i.e., the address where the NFT is stored in IPFS) is sent to the blockchain oracle's oracle contract. The oracle contract interacts with the off-chain trusted NFT similarity detection module to determine whether the user's created NFT is plagiarized or copied. If the review is approved, creation is allowed. After creation, the NFT can be managed, auctioned, and traded through the NFTMarketPlace contract.

[0059] In addition, considering the cost of on-chain storage and the energy consumption issues brought by blockchain, this invention proposes a dual storage mechanism of "on-chain + off-chain" and a multi-NFT aggregation casting scheme. The physical or digital content of the artwork is stored in the decentralized IPFS interplanetary file system. The metadata corresponding to the artwork, such as resource mapping, resource information names and attributes, is aggregated off-chain into a MerkleTree. The data on-chain is only the root node of the MerkleTree, thereby realizing the aggregation casting of multiple NFTs.

[0060] like Figure 3 The diagram illustrates the logical principle of NFTs in this application. It shows that NFTs are issued in the form of smart contracts. A single smart contract can issue one or more NFT assets, including physical assets such as collectibles and event tickets, and virtual assets such as images, music, and game items. One NFT asset can map to multiple NFTs. The NFT smart contract records the token ID, resource storage address, and other information for each NFT asset. While NFTs are stored on the blockchain, due to cost constraints, the physical or digital assets they map to are generally not on the blockchain but are stored in other centralized or decentralized storage systems, such as the IPFS interplanetary file system, and mapped to the blockchain via hash values ​​or URLs.

[0061] In this invention, an NFT verification module based on a blockchain oracle is used to facilitate data interaction between the on-chain NFT minting contract and the off-chain detection system. For example... Figure 4 The diagram shows the framework of the NFT verification module based on a blockchain oracle in this invention. The NFT verification module includes an on-chain part and an off-chain part. The on-chain part includes OneRingNFT and NFTOracle, and the off-chain part includes a detection system. The OneRingNFT contract receives a minting request, calls the NFTOracle contract, and passes in the NFT information to be verified. The NFTOracle contract adds the NFT information and triggers the off-chain detection system. After the detection system completes the verification, it writes the result back to the on-chain.

[0062] In this embodiment, a deep learning-based artwork similarity detection system is designed to address the inefficiency of manual review methods. Specifically, refer to... Figure 4 As shown, when a user initiates a minting request to the OneRingNFT contract, the OneRingNFT contract calls the NFTOracle contract and passes in the information of the digital artwork the user wants to mint. Then, whenever a new NFT awaiting review appears in the NFTOracle contract, the detection algorithm of the off-chain deep learning-based similarity detection system is triggered. Next, after the off-chain detection system completes the detection, it writes the result back to the blockchain. Finally, the NFTOracle contract returns the result to the minting contract, thereby determining whether the digital artwork uploaded by the user has passed the review.

[0063] Furthermore, the detection system employs an NFT similarity detection method based on deep learning object detection, including the following steps:

[0064] First, acquire artwork image data and extract local features of the images using SIFT; second, quantify the local features of the images through clustering to construct visual words; then construct a visual word frequency histogram of the images and use dynamic distance measurement to achieve similar and repeating image detection; finally, output images similar to the image data.

[0065] Specifically, SIFT feature extraction involves five processes: 1) constructing a scale space; 2) detecting spatial extrema; 3) accurately determining extrema; 4) assigning keypoint orientations; and 5) describing features. After an image undergoes SIFT processing, many local feature points are generated, each of which is a 128-dimensional feature vector.

[0066] The mapping from SIFT visual features to visual words can be achieved through k-means clustering. The final cluster centers are the visual words to be obtained, and the number of cluster centers is the size of the codebook vector. k-means is a simple clustering algorithm, and it is widely used because of its theoretical reliability and fast convergence speed.

[0067] The k-means algorithm employs an iterative update approach. First, it loads the SIFT feature data of the image database to be clustered into memory. Then, it randomly selects K objects to initialize the cluster centers with c1, c2, ..., c... k —Initialization process; then for each of the remaining objects x i (i = 1, 2, 3, ..., n) Assign it to the nearest cluster based on its distance from each cluster center (m is the dimension of the feature data) — Allocation process:

[0068]

[0069] Then recalculate the mean of each cluster as the cluster center for the next iteration—update the cluster centers:

[0070]

[0071] Where N j For the j-th cluster S j The number of objects in the cluster. The two processes of assigning and updating cluster centers are repeated continuously until all cluster centers no longer change. The final cluster centers are the visual words required by the Bag-of-words model. In this embodiment, the number of cluster centers is set to 500.

[0072] In constructing the visual word frequency histogram for an image, the distance between each SIFT vector in each image and all visual words is calculated. If a vector is closest to a certain visual word, the height of the bin corresponding to that visual word is increased by 1, until all SIFT descriptor vectors have been assigned. In this way, each image can be represented by a histogram the size of a visual word sequence. Thus, each image can be represented by a 500-dimensional feature vector.

[0073] First, there's PCA transformation. PCA aims to recombine P correlated features into a new set of independent composite features to replace the original features. Mathematically, this involves linearly combining the original P features to create the new composite feature. The classic approach is to express this using the variance of F1 (the first selected linear combination, i.e., the first composite feature). A larger Var(F1) indicates more information contained in F1. Therefore, F1 should have the largest variance among all linear combinations, hence it's called the first principal component. If the first principal component is insufficient to represent the information of the original P features, then F2 (the second linear combination) is considered. To effectively reflect the original information, information already present in F1 doesn't need to appear in F2. Mathematically, this means Cov(F1, F2) = 0, then F2 is called the second principal component. This process continues to construct the third, fourth, ..., nth principal components. Through principal component analysis, dimensionality reduction of high-dimensional feature data can be achieved. For the purpose of subsequent hash encoding, PCA needs to be used to reduce the 500-dimensional features of the image to 32 dimensions.

[0074] Then, hash encoding is performed. Representing the dimensionality-reduced feature vector as a hash value is essentially the process of vector quantization. The vector quantization method used in this project is as follows:

[0075]

[0076] Among them: H i G is the k-th dimension encoding of image i. i It is the k-th dimension feature of the feature vector of image i, mean k Let K be the k-th dimension mean of all image features in the image database. Therefore, the K-dimensional feature values ​​are quantized into K bits, and this K-bit ordered binary string is called the hash value of the image.

[0077] Dynamic distance measurement automatically selects multiple metric spaces based on the visual features of different images. For a query image, it is first transformed by scaling, brightness adjustment, and rotation, and the transformed images are saved in an image database. Then, PCA is used to find a space where samples can be distinguished to the greatest extent. The distance between the query image and each transformed image is calculated in this space, and the largest distance is selected as a threshold. Images within this threshold are retained, as are the transformed images; images outside the threshold are filtered out. In the next iteration, the most discriminative projection space is found in the retained image set, and the same operation is performed. This iterative process continues until no images are filtered out, at which point the iteration stops. The images ultimately retained are those similar to the query image.

[0078] The detection of similar and duplicate artwork images using dynamic distance metrics can be divided into the following processes:

[0079] Step 1: Perform various random transformations on the query image.

[0080] Step 2: Select the feature space k with the highest discriminative power and calculate the image similarity threshold ε. ε is the maximum Hamming distance between the query image and the transformed image. ε = max||P qj -P q(l)j ||, where q(l)j is the l-th random transformation.

[0081] Step 3: If an image and the query image satisfy: and If the image is similar to the query image, it is included in the next iteration. This requires the first L bits to have the same binary value, while allowing small errors in the remaining (KL) bits (where L is 24). P is a projection matrix, H() is the hash encoding function, and the distance is calculated using Hamming distance.

[0082] Step 4: Repeat Step 2 and Step 3 until the retained dataset no longer changes, and finally leave it in the retained dataset.

[0083] The images in the dataset are those that are similar to the query image.

[0084] In this invention, see Figure 5 As shown, the casting process of an artwork NFT includes the following steps:

[0085] The user uploads the artwork to IPFS and obtains the corresponding IPFS hash value, denoted as tokenUrl. The user calls the safeMint() function in OneRingNFT, passing tokenUrl as a parameter. The safeMint() function checks whether the NFT has passed the backend review by passing tokenUrlPassed. If tokenUrlPassed returns a result indicating that the review has failed, the minting fails. If tokenUrlPassed returns a result indicating that the review has passed, safeMint() is successfully called, and the user is notified to pay the minting fee.

[0086] Furthermore, during the casting process, a multi-user NFT aggregation casting method is employed, including the following steps:

[0087] S1: Upload each NFT to the InterPlanetary File System and obtain the corresponding hash value. Several hash values ​​constitute the leaf nodes of the tree. S2: Calculate the hash value of two adjacent leaf nodes to obtain the value of the parent node. S3: Repeat step S2 to further aggregate all the parent nodes and finally obtain the unique root node. S4: Finally, publish the root node hash value to the blockchain through a smart contract to complete the minting.

[0088] Currently, there are issues with the high gas fees and slow confirmation speeds for uploading NFTs to the blockchain. Figure 6 As shown, this invention proposes a multi-user NFT aggregation and minting scheme. It uses MerkleTree to continuously perform hash calculations on the IPFS hash values ​​corresponding to the NFTs of multiple users, and finally obtains a complete binary tree type NFT aggregation tree. Then, the hash value of the root node of the tree is saved to the blockchain to complete the minting.

[0089] After multiple NFTs are forged, each NFT corresponds to a set of verification parameters used to verify the authenticity and credibility of the NFT. For an "NFT forging tree" of height n+1, the verification parameter set corresponding to each NFT has n items, i.e., param i ={t0,t1,t2,t3,t4,...,t n}, where t1 is the sibling node of hash value i, t2 is the sibling node of the parent node of hash value i, and so on.

[0090] For example, the verification parameter set of NFT1 is hash value 2, hash value 34, and hash value 5678. When verifying, NFT1 is uploaded to IPFS to calculate the corresponding hash value 1. Then, it is forward hashed with hash value 2, hash value 34, and hash value 5678 respectively, and the resulting values ​​stored in the blockchain are compared. Therefore, the hash function has one-way and collision-resistant properties, so if the two values ​​are equal, it can be proven that the NFT is real and valid.

[0091] A second aspect of this application provides a computer-readable storage medium having a computer program stored thereon, characterized in that, when the program is executed by a processor, it implements the aforementioned blockchain-based digital asset ownership confirmation and circulation system for artworks.

[0092] In this embodiment of the invention, if the above-mentioned digital asset ownership confirmation and circulation system for artworks is implemented in the form of software functional modules and sold or used as an independent product, it can also be stored in a computer-readable storage medium.

[0093] Based on this understanding, the technical solutions of the embodiments of the present invention, or the parts that contribute to the prior art, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the methods described in the various embodiments of the present invention. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), magnetic disks, or optical disks. Thus, the embodiments of the present invention are not limited to any specific hardware and software combination.

[0094] A third aspect of this application provides a terminal, characterized in that it includes: one or more processors and a memory, and one or more application programs; wherein the one or more application programs are stored in the memory and configured to be executed by the one or more processors, and the one or more application programs are configured to execute the aforementioned blockchain-based digital asset ownership confirmation and circulation system for artworks.

[0095] In most implementations, those skilled in the art use at least one network to support communication using any of the various commercial protocols such as TCP / IP, OSI, FTP, UPnP, NFS, CIFS, and AppleTalk. The network can be, for example, a local area network (LAN), a wide area network (WAN), a virtual private network (VPN), the Internet, an intranet, an extranet, the public switched telephone network (PSTN), an infrared network, a wireless network, or any combination thereof.

[0096] In implementations utilizing web servers, the web server can run any of a variety of server or middleware applications, including HTTP servers, FTP servers, CGI servers, data servers, Java servers, and business application servers.

[0097] One or more servers may also be able to execute programs or scripts in response to requests from user devices, such as by executing one or more applications, which may be implemented as one or more scripts or programs written in any programming language such as C, C# or C++ or any scripting language such as Perl, Python or TCL and combinations thereof.

[0098] One or more servers may also include database servers, including but not limited to those that are commercially available.

[0099] Such programs can also be encoded and transmitted using carrier signals adapted for transmission via wired, optical, and / or wireless networks conforming to various protocols, including the Internet. Similarly, computer-readable media according to embodiments of the invention can be created using data signals encoded by such programs. Computer-readable media encoded with program code can be packaged with compatible devices or provided independently of other devices (e.g., downloaded via the Internet). Any such computer-readable media can be present or located within a single computer product (e.g., a hard disk drive, CD, or an entire computer system) and can be present or located within different computer products within a system or network. A computer system may include a monitor, printer, or other suitable display for providing any results mentioned herein to a user.

[0100] In conclusion, the existing art asset securitization model is still a traditional centralized approach. However, due to the complexity of the asset securitization process, the large number of participants, and the existence of problems such as information asymmetry and distrust between the transacting parties, effectively solving these problems is the primary direction for promoting the effective development of the asset securitization market and better controlling asset risks.

[0101] Based on this, this invention addresses the pain points and difficulties in information sharing in art asset securitization. Relying on the development of blockchain technology, it proposes a distributed information sharing platform and a collateral information sharing system for art asset securitization products using smart contracts, thereby reducing risks and improving security.

[0102] The above description is merely an embodiment of the present invention and does not limit the patent scope of the present invention. Any equivalent structural or procedural transformations made based on the content of the present invention's specification and drawings, or direct or indirect applications in other related technical fields, are similarly included within the patent protection scope of the present invention.

Claims

1. A blockchain-based digital asset ownership confirmation and circulation system for artworks, characterized in that, It includes, from bottom to top, the data layer, network layer, consensus layer, contract layer, and application layer; The data layer adopts a dual storage mode of on-chain and off-chain, including a database blockchain, an interplanetary file system, and a data management system. The network layer includes a P2P network, a propagation mechanism, and a verification mechanism, and encapsulates the networking method and message propagation protocol of the Ethereum blockchain. The consensus layer adopts the Proof-of-Work (PoW) consensus algorithm mechanism in Ethereum, and the contract layer is used to run the system's script code, algorithms, and protocols. The application layer provides a human-computer interaction interface and interacts with smart contracts and backend databases. The data layer, consensus layer, contract layer, and application layer are located in the same blockchain network; By setting up an NFT verification module based on a blockchain oracle, data interaction is achieved between the on-chain NFT minting contract and the off-chain detection system; The NFT verification module includes an on-chain part and an off-chain part. The on-chain part includes the OneRingNFT and the NFTOracle, and the off-chain part includes a detection system. The OneRingNFT contract receives a minting request, calls the NFTOracle contract, and passes in the NFT information to be reviewed. The NFTOracle contract adds the NFT information and triggers the off-chain detection system. After the detection system completes the detection, it writes the result back to the chain. The detection system employs an NFT similarity detection method based on deep learning object detection, including the following steps: First, acquire artwork image data and extract local features using SIFT. Second, quantify the local features of the image through clustering to construct visual words. Then, construct a visual word frequency histogram for the image and use dynamic distance measurement to detect similar and repeating images. Finally, output an image similar to the image data.

2. The blockchain-based digital asset ownership confirmation and circulation system for artworks according to claim 1, characterized in that, The on-chain storage mode uses a decentralized distributed database blockchain to store the metadata corresponding to the casting of digital artworks; The off-chain storage mode stores the complete content of digital artworks through the InterPlanetary File System, and the data management system uses MySQL as the backend database.

3. The blockchain-based digital asset ownership confirmation and circulation system for artworks according to claim 2, characterized in that, The contract layer includes NFTOracle, OneRingNFT, and NFTMarketPlace. The NFTOracle interfaces the on-chain NFTs to be minted with the off-chain detection module. The OneRingNFT process handles the creation, querying, and management of artworks, while the NFTMarketPlace process handles the trading, display, and auctioning of artworks.

4. The blockchain-based digital asset ownership confirmation and circulation system for artworks according to claim 1, characterized in that, The creation process of an artwork NFT includes the following steps: Users upload artwork to IPFS and obtain the corresponding IPFS hash value, denoted as tokenUrl; The user calls the safeMint() function in OneRingNFT and passes tokenUrl as a parameter. The tokenUrlPassed function is used to determine whether the NFT has passed the backend review. If tokenUrlPassed returns a result indicating that the review failed, then the casting process has failed. If tokenUrlPassed returns a result indicating approval, afeMint() is successfully called, and the user is notified to pay the casting fee.

5. The blockchain-based digital asset ownership confirmation and circulation system for artworks according to claim 4, characterized in that, The casting process employs a multi-user NFT aggregation casting method, which includes the following steps: S1: Upload each NFT to the InterPlanetary File System and obtain the corresponding hash value. Several hash values ​​constitute the leaf nodes of the tree. S2: Perform a hash calculation on the values ​​of two adjacent leaf nodes to obtain the value of the parent node; S3: Repeat step S2 to further aggregate all parent nodes and finally obtain the unique root node; S4: Finally, the root node hash value is published to the blockchain via a smart contract to complete the minting process.

6. A computer-readable storage medium having a computer program stored thereon, characterized in that, When executed by the processor, the program implements the blockchain-based digital asset ownership confirmation and circulation system for artworks as described in any one of claims 1-5.

7. A terminal, characterized in that, include: One or more processors and memory, and one or more applications; wherein the one or more applications are stored in the memory and configured to be executed by the one or more processors, and the one or more applications are configured to execute the blockchain-based digital asset ownership confirmation and circulation system for artworks according to any one of claims 1 to 5.

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