Decentralized knowledge sharing method and system, electronic equipment and storage medium

Abstract

The invention discloses a decentralized knowledge sharing method and system, an electronic device and a storage medium, and the method comprises the steps: constructing a dynamic oracle network in a block chain platform, employing a K-Raft algorithm to verify the authenticity of knowledge content, abandoning centralized auditing, and employing distributed verification; the efficiency, pertinence and reliability of authenticity verification are improved, the K-Raft algorithm introduces a knowledge graph on the basis of an existing Raft consensus algorithm, verification content is associated with a wider knowledge background to assist each node of the dynamic oracle network in authenticity judgment, the accuracy and depth of authenticity verification are improved, and the reliability of authenticity verification is improved. The authenticity and credibility of knowledge and information on the knowledge sharing platform are effectively improved, and the digital assets are generated for the knowledge provider after the authenticity verification is passed, so that the user has the ownership and control right of the data, and the risk of data leakage and abuse is avoided.

Description

Technical Field

[0001] The present invention relates to the technical field of knowledge sharing, and in particular, to a decentralized knowledge sharing method and system, an electronic device, and a computer-readable storage medium. Background Art

[0002] Currently, centralized knowledge sharing platforms represented by Zhihu, CNKI, etc. are important channels for users to obtain information. These platforms are usually operated and managed by central institutions. After users publish content, the central institutions of the platforms have the management and review rights over the content. However, the existing centralized knowledge sharing platforms have the following disadvantages:

[0003] 1. It is difficult to guarantee the authenticity of information: Although the platform takes measures to review the content, due to the large number of users and the limited review ability of the central institution, it is difficult to completely prevent the spread of false and incorrect information. At the same time, the central institution lacks sufficient motivation to thoroughly identify the authenticity of all information because it will reduce the economic benefits of the central institution.

[0004] 2. The ownership and control of data belong to the platform: The ownership and control of the content contributed by users often belong to the platform, and users cannot fully control their own data.

[0005] 3. The incentive mechanism is insufficient: The incentives for content contributors by the platform are usually limited, and there is a lack of effective incentives for information authenticity verification behaviors. Summary of the Invention

[0006] The present invention provides a decentralized knowledge sharing method and system, an electronic device, and a computer-readable storage medium, which can effectively improve the authenticity and credibility of knowledge and information on the platform, and enable the uploading users to have the ownership and control of the data.

[0007] According to one aspect of the present invention, a decentralized knowledge sharing method is provided, including the following:

[0008] The knowledge provider node uploads the knowledge content to the knowledge sharing platform, where the knowledge sharing platform is a blockchain-based decentralized knowledge platform;

[0009] Construct a dynamic oracle network and verify the authenticity of the knowledge content based on the K-Raft algorithm, and write the authenticity verification result into the knowledge sharing platform and notify the knowledge provider node;

[0010] If the authenticity verification passes, the knowledge content is converted into the digital assets of the knowledge provider node.

[0011] Further, the process of constructing the dynamic oracle network includes the following:

[0012] Set screening conditions according to the professional tags of the content to be verified and the reputation values of each node in the knowledge sharing platform, and send invitations to the nodes in the knowledge sharing platform that meet the screening conditions in combination with a random selection mechanism. If the nodes that receive the invitations accept the invitations within the set response time, they will be used as response nodes. After the response time ends, a dynamic oracle network is constructed based on multiple response nodes.

[0013] Further, the process of verifying the authenticity of knowledge content based on the K-Raft algorithm includes the following:

[0014] The dynamic oracle network elects a leader node, and the remaining nodes are follower nodes;

[0015] The leader node constructs a knowledge graph after collecting information related to the content to be verified from multiple data sources, and sends the digital digest of the content to be verified and the knowledge graph to all follower nodes;

[0016] All follower nodes vote on the authenticity of the content to be verified according to the knowledge graph and then feedback to the leader node. The leader node determines the final authenticity verification result according to the voting results of all follower nodes. Among them, the types of voting results include true, false, and unable to judge.

[0017] Further, calculate the support rates for the voting result being true and the voting result being false based on the following formula:

[0018]

[0019] Among them, SUPPORT True represents the support rate for the voting result being true, m represents the number of nodes with the voting result being true, NodeReputation True，i represents the reputation value of the nodes with the voting result being true, SUPPORT False represents the support rate for the voting result being false, n represents the number of nodes with the voting result being false, NodeReputation False，i represents the reputation value of the nodes with the voting result being false, TotalReputation represents the comprehensive reputation value of all nodes in the dynamic oracle network. If SUPPORT True is greater than or equal to the threshold T, the authenticity verification passes. If SUPPORT False is greater than or equal to the threshold T, the authenticity verification fails. If SUPPORT True is less than the threshold T and SUPPORT False is less than the threshold T, the authenticity cannot be judged.

[0020] Further, after obtaining the authenticity verification result, the following also includes:

[0021] Reward or punish the knowledge provider node and the nodes participating in the authenticity verification according to the authenticity verification result.

[0022] Further, if the authenticity verification passes, reward the knowledge provider node and the nodes that vote as true with digital assets, and punish the nodes that vote as false with digital assets; if the authenticity verification fails, punish the knowledge provider node and the nodes that vote as true with digital assets, and reward the nodes that vote as false with digital assets.

[0023] Further, after obtaining the authenticity verification result, the following content is also included:

[0024] Update the reputation value according to the verification behavior and upload behavior of each node in the knowledge sharing platform.

[0025] In addition, the present invention also provides a decentralized knowledge sharing system, including:

[0026] A knowledge upload module for allowing a knowledge provider node to upload knowledge content to the knowledge sharing platform, where the knowledge sharing platform is a blockchain-based decentralized knowledge platform;

[0027] An authenticity verification module for constructing a dynamic oracle network and verifying the authenticity of the knowledge content based on the K-Raft algorithm, writing the authenticity verification result into the knowledge sharing platform and notifying the knowledge provider node;

[0028] A digital asset generation module for converting the knowledge content into digital assets of the knowledge provider node after the authenticity verification passes.

[0029] In addition, the present invention also provides an electronic device, including a processor and a memory, where a computer program is stored in the memory, and the processor is used to execute the steps of the method described above by calling the computer program stored in the memory.

[0030] In addition, the present invention also provides a computer-readable storage medium for storing a computer program for decentralized knowledge sharing, and the computer program executes the steps of the method described above when running on a computer.

[0031] The present invention has the following beneficial effects:

[0032] The decentralized knowledge sharing method of the present invention, after uploading knowledge content to a blockchain-based decentralized knowledge platform, verifies the authenticity of the knowledge content by constructing a dynamic oracle network in the blockchain platform and adopting the K-Raft algorithm. It abandons centralized review and adopts distributed verification, improving the efficiency, pertinence, and reliability of authenticity verification. Moreover, the K-Raft algorithm introduces a knowledge graph on the basis of the existing Raft consensus algorithm, associates the verification content with a broader knowledge background to assist each node of the dynamic oracle network in making authenticity judgments, improving the accuracy and depth of authenticity verification, effectively enhancing the authenticity and credibility of knowledge and information on the knowledge sharing platform. And, after the authenticity verification passes, digital assets are generated for the knowledge provider, enabling users to have the ownership and control of the data, avoiding the risks of data leakage and abuse.

[0033] In addition, the decentralized knowledge sharing system of the present invention also has the above-mentioned advantages.

[0034] In addition to the purposes, features, and advantages described above, the present invention has other purposes, features, and advantages. The following will refer to the drawings for a further detailed description of the present invention. BRIEF DESCRIPTION OF THE DRAWINGS

[0035] The drawings constituting a part of this application are used to provide a further understanding of the present invention. The schematic embodiments of the present invention and their descriptions are used to explain the present invention and do not constitute an improper limitation of the present invention. In the drawings:

[0036] Figure 1 is a schematic flowchart of the decentralized knowledge sharing method according to a preferred embodiment of this application;

[0037] Figure 2 is Figure 1 a sub-flowchart of step S2 in

[0038] Figure 3 is another schematic flowchart of the decentralized knowledge sharing method according to a preferred embodiment of this application;

[0039] Figure 4 is yet another schematic flowchart of the decentralized knowledge sharing method according to a preferred embodiment of this application;

[0040] Figure 5 is a schematic network architecture diagram of the decentralized knowledge platform constructed according to a preferred embodiment of this application;

[0041] Figure 6 is a schematic module structure diagram of the decentralized knowledge sharing system according to another embodiment of this application. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0042] It should be noted that, without conflict, the embodiments in this application and the features in the embodiments may be combined with each other. The following will describe this application in detail with reference to the drawings and in combination with the embodiments.

[0043] Referring to Figure 1 , a preferred embodiment of this application provides a decentralized knowledge sharing method, including the following:

[0044] Step S1: The knowledge provider node uploads the knowledge content to the knowledge sharing platform, where the knowledge sharing platform is a blockchain-based decentralized knowledge platform;

[0045] Step S2: Construct a dynamic oracle network and verify the authenticity of the knowledge content based on the K-Raft algorithm, and write the authenticity verification result into the knowledge sharing platform and notify the knowledge provider node;

[0046] Step S3: If the authenticity verification passes, convert the knowledge content into the digital assets of the knowledge provider node.

[0047] It can be understood that for the decentralized knowledge sharing method of this embodiment, after uploading the knowledge content to the blockchain-based decentralized knowledge platform, by constructing a dynamic oracle network in the blockchain platform and using the K-Raft algorithm to verify the authenticity of the knowledge content, it abandons centralized review and adopts distributed verification, improving the efficiency, pertinence and reliability of authenticity verification. Moreover, the K-Raft algorithm introduces a knowledge graph on the basis of the existing Raft consensus algorithm, associates the verification content with a broader knowledge background to assist each node of the dynamic oracle network in making authenticity judgments, improving the accuracy and depth of authenticity verification, effectively improving the authenticity and credibility of knowledge and information on the knowledge sharing platform. And, after the authenticity verification passes, digital assets are generated for the knowledge provider, enabling users to have the ownership and control of the data, avoiding the risks of data leakage and abuse.

[0048] Among them, in step S1, the knowledge provider node uploads knowledge content through the knowledge sharing platform interface. The platform associates the content information, DID and off-chain storage address, and puts the key information on the chain, which is recorded in the blockchain account book by the smart contract. Specifically, the knowledge provider uses the knowledge provider interface provided by the platform to fill in the content information (such as title, summary, professional label, etc.), and upload the original content of the knowledge content. The platform calls the DID generation module according to the registration information of the knowledge provider, and associates the DID of the knowledge provider with the content uploaded this time. Then, the platform records the access address of the uploaded content stored off-chain, such as the CID of IPFS, and associates the address with the hash value of the content. At the same time, the hash value, summary and other information of the content are sent to the blockchain network. After the blockchain network receives the content information, the smart contract controls the content hash value, summary, author DID, professional label and other metadata to be recorded in the blockchain account book.

[0049] In addition, knowledge providers need to complete identity registration on the knowledge sharing platform. The specific registration process is as follows: the knowledge sharing platform provides a user interface to collect user registration information, such as username and password (hash encrypted storage), and can choose to integrate third-party login, such as MetaMask and other wallet login; the knowledge sharing platform adopts DID standards, such as DID:web or DID:ethr, to generate a unique decentralized identity DID for each user, and uses an asymmetric encryption algorithm (such as the ECDSA algorithm) to generate a key pair, associate the public key with the DID, and the private key is kept safely by the user. In addition, the knowledge sharing platform also has a three-layer professional tag library. The first-level tag list is built based on the UNESCO Classification of Science and Technology (FOS), and uses smart contracts to store the first-level tag list and provide a query interface. The second-level tag list is built based on the UNESCO FOS sub-disciplines, and is also stored using smart contracts and associated with the first-level tags. The third-level tag list is a user-defined tag, which is stored in the user's DID document or off-chain database. You can choose to use decentralized storage solutions such as IPFS or CeramicNetwork and associate it with the user's DID. After completing the DID identity registration, the user can set his own third-level tag. In addition, after the user completes the DID identity registration, the knowledge sharing platform will also allocate initial digital assets to the newly registered user, such as the initial number of tokens, and use smart contracts to implement the token staking function, supporting the locking of the number of tokens specified by the new user for a period of time, namely the observation period.

[0050] In addition, in step S2, the process of building a dynamic oracle network includes the following:

[0051] Set screening conditions according to the professional tags of the content to be verified and the reputation values of each node in the knowledge sharing platform, and send invitations to the nodes in the knowledge sharing platform that meet the screening conditions in combination with a random selection mechanism. If the nodes that receive the invitations accept the invitations within the set response time, they will be used as response nodes. After the response time ends, a dynamic oracle network is constructed based on multiple response nodes.

[0052] Specifically, when a knowledge provider node has a need to verify the authenticity of content, it can initiate a verification request to the nodes in the blockchain network through a smart contract. The request includes the digest of the content to be verified calculated using the private key of the knowledge provider, which is convenient for screening users participating in the verification. The knowledge sharing platform will set screening conditions according to the professional tags of the content to be verified and the reputation values of each node in the knowledge sharing platform, and send invitations to the nodes in the knowledge sharing platform that meet the screening conditions in combination with a random selection mechanism. The nodes that receive the invitations can decide whether to accept the invitations and respond within the specified time. If the nodes that receive the invitations accept the invitations within the set response time, they will be used as response nodes. If they do not accept the invitations or reject the invitations within the response time, they will not be used as response nodes. After the response time ends, a dynamic oracle network can be constructed based on multiple response nodes. Among them, the professional tags of the content to be verified are the three-layer professional tags selected by the knowledge provider node during DID identity registration. In addition, due to the massive requests initiated by different users in the blockchain network, the smart contract will put these verification requests into a message queue for asynchronous processing.

[0053] It can be understood that the present invention screens out a batch of user nodes with professional counterparts and good reputations according to the user's professional tags and reputation value requirements. These user nodes will form a temporary oracle network for this verification task to participate in the authenticity verification voting, realizing decentralized distributed verification and improving the efficiency, pertinence and reliability of the verification.

[0054] In addition, as Figure 2 shown, the process of verifying the authenticity of knowledge content based on the K-Raft algorithm includes the following contents:

[0055] Step S21: The dynamic oracle network elects a leader node, and the remaining nodes are used as follower nodes;

[0056] Step S22: After the leader node collects information related to the content to be verified from multiple data sources, it constructs a knowledge graph, and sends the digital digest of the content to be verified and the knowledge graph to all follower nodes;

[0057] Step S23: All follower nodes vote on the authenticity of the content to be verified according to the knowledge graph and then feedback to the leader node. The leader node determines the final authenticity verification result based on the voting results of all follower nodes. The voting result types include true, false, and unable to judge.

[0058] Specifically, after constructing a temporary dynamic oracle network, the nodes in the dynamic oracle network will obtain read-only permissions to access off-chain original content and permissions to call external data source interfaces provided by the platform. Then, the nodes in the dynamic oracle network start leader election based on the K-Raft consensus algorithm. The nodes vote for each other to select a leader node responsible for coordinating this verification. The leader node collects information related to the content to be verified from multiple data sources (such as authoritative knowledge bases, academic databases, industry reports, public APIs, etc.) and constructs a knowledge graph to provide a reference for subsequent verification. The leader node packages information such as the verification request sent by the user, the digital digest of the content to be verified, and the knowledge graph it constructs into a log entry and then sends it to all follower nodes in the dynamic oracle network. After receiving the log entry, all follower nodes conduct independent audits by combining their own professional knowledge, the knowledge graph, and the off-chain original content. After each follower node completes the audit, it forms its own authenticity verification opinion, that is, the voting result, including "true", "false", or "unable to judge", and sends a message containing the verification opinion to the leader node. The leader node collects the votes of all follower nodes and determines the final authenticity verification result, that is, "true", "false", or "unable to judge", according to the K-Raft algorithm rules and the weighted voting mechanism. Finally, the leader node will write information such as the final authenticity verification result, the nodes participating in the verification, and the voting details into the blockchain and notify the user of the authenticity verification result.

[0059] Among them, the support rates for the voting result being true and the voting result being false are specifically calculated based on the following formula:

[0060]

[0061] where SUPPORT True represents the support rate for the voting result being true, m represents the number of nodes with the voting result being true, NodeReputation True，i represents the reputation value of the nodes with the voting result being true, SUPPORT False represents the support rate for the voting result being false, n represents the number of nodes with the voting result being false, NodeReputation False，iRepresents the reputation value of nodes indicating false voting results, and TotalReputation represents the total sum of the reputation values of all nodes in the dynamic oracle network. If SUPPORT True is greater than or equal to the threshold T, the authenticity verification passes. If SUPPORT False is greater than or equal to the threshold T, the authenticity verification fails. If SUPPORT True is less than the threshold T and SUPPORT False is less than the threshold T, the authenticity cannot be judged. During the voting process, the reputation value of a node will be used as an important weight coefficient. The higher the reputation value of a node, the higher its voting weight, thus ensuring that high-reputation nodes play a greater role in the consensus decision-making.

[0062] It can be understood that based on the existing Raft consensus algorithm, the present invention introduces a knowledge graph and for the first time proposes the K-Raft consensus algorithm, which associates the verification content with a broader knowledge background to assist nodes in making authenticity judgments, further improving the accuracy and depth of authenticity verification.

[0063] Optionally, if the final authenticity verification result is "undetermined", a dispute arbitration strategy can also be adopted for relief. Specifically, an arbitration committee is invited to be composed of authoritative institutions or expert nodes in a specific field (i.e., the technical field to which the professional label belongs) in the consortium chain to conduct further expert review and adjudication on the controversial verification result. The adjudication result of the arbitration committee will be used as the final authenticity verification conclusion and recorded on the blockchain to ensure the fairness of the arbitration process and the authority of the result.

[0064] In addition, in step S3, if the authenticity verification of the uploaded content passes, NFT (i.e., non-fungible token) standards such as ERC-721 or ERC-1155 are adopted to mint the verified knowledge content and its metadata into NFTs to ensure their uniqueness, immutability, and traceability. Users can subsequently conduct NFT transactions, realizing the safe and convenient transaction of knowledge, promoting the value transfer of knowledge, enabling users to have the ownership and control of data, and avoiding the risks of data leakage and abuse. For the minted NFTs, their metadata, including the off-chain storage address of the original content, will be recorded on the blockchain. If the authenticity verification of the uploaded content fails, since it has been stored in the blockchain and the off-chain storage system during verification, the blockchain network will execute the smart contract to delete the false content from the state database, while the event records of the upload and verification of this false content still remain in the historical database, but the specific knowledge content has been deleted from the state database, so users cannot access it either.

[0065] Optionally, such as Figure 3As shown, after obtaining the authenticity verification result, the decentralized knowledge sharing method further includes the following:

[0066] Step S4: According to the authenticity verification result, conduct digital asset rewards or penalties on the knowledge provider node and the nodes participating in the authenticity verification.

[0067] Specifically, if the authenticity verification passes, conduct digital asset rewards (i.e., token rewards) on the knowledge provider node and the nodes that voted as true, and conduct digital asset penalties (i.e., token penalties) on the nodes that voted as false; if the authenticity verification fails, conduct digital asset penalties on the knowledge provider node and the nodes that voted as true, and conduct digital asset rewards on the nodes that voted as false.

[0068] Among them, the token reward for the upload behavior of the knowledge provider node is based on the following formula: UploaderReward = BaseUploaderReward * (1 + ReputationFactor), where UploaderReward represents the upload reward, BaseUploaderReward represents the base upload reward, which is a preset value, ReputationFactor represents the reputation value factor, and this factor is positively correlated with the reputation value of the upload node. The higher the reputation value of the node, the higher its upload reward. For example, ReputationFactor = α * Reputation, where α is an adjustable parameter representing the linear influence degree of the reputation value on the reward. The larger the value of α, the more obvious the improvement of the reputation value on the reward.

[0069] The token penalty for the upload behavior of the knowledge provider node is based on the following formula: UploaderPenalty = BaseUploaderPenalty * (1 + PenaltyFactor), where UploaderPenalty represents the upload penalty, BaseUploaderPenalty represents the base upload penalty, which is a preset value, PenaltyFactor represents the penalty factor, and it is positively correlated with the number of times the node uploads false content. The more times the node uploads false content, the larger the penalty factor, and the higher the upload penalty.

[0070] The token reward for the nodes participating in the authenticity verification is based on the following formula: EvaluatorReward = BaseEvaluatorReward * (1 + ReputationFactor), where EvaluatorReward represents the verification reward, BaseEvaluatorReward represents the base verification reward, which is a preset value, ReputationFactor represents the reputation value factor, and it is related to the reputation value of the node. The higher the reputation value, the higher the verification reward.

[0071] Token penalties are imposed on the nodes participating in the authenticity verification based on the following formula: EvaluatorPenalty = BaseEvaluatorPenalty * (1 + ErrorStreakFactor), where EvaluatorPenalty represents the verification penalty, BaseEvaluatorPenalty represents the basic verification penalty, which is a preset value, and ErrorStreakFactor represents the error record factor, which is positively correlated with the number of verification errors of the node. The more verification errors, the higher the error record factor, and the higher the verification penalty. For example, ErrorStreakFactor = β * ErrorStreak, where β is an adjustable parameter representing the linear influence degree of the consecutive verification times on the penalty. The larger the value of β, the more obvious the increase in the penalty caused by the consecutive verification times.

[0072] It can be understood that the present invention designs a token reward and penalty mechanism for the user's uploading behavior and verification behavior, which can enable content creators to obtain more rewards, stimulate their creative enthusiasm, and encourage nodes to actively participate in authenticity verification and punish malicious nodes, forming a virtuous cycle, and can well encourage users to actively participate in the management and knowledge production of the knowledge sharing platform, thereby overcoming the deficiencies in the incentive mechanism of the existing centralized knowledge sharing platform.

[0073] Optionally, as Figure 4 shown, after obtaining the authenticity verification result, the decentralized knowledge sharing method further includes the following:

[0074] Step S5: After obtaining the authenticity verification result, the following further includes:

[0075] Update the reputation value of each node in the knowledge sharing platform according to its verification behavior and uploading behavior.

[0076] Specifically, if a node conducts correct verification and uploads knowledge content, its reputation value is increased; if a node conducts incorrect verification and uploads false content, its reputation value is decreased. The reputation value of the node will affect the weight it occupies in the authenticity voting and the reputation value factor in token rewards. It can be understood that by constructing a dynamic reputation value mechanism, the present invention can encourage nodes to provide true and reliable votes and punish malicious nodes, forming a virtuous cycle.

[0077] Optionally, the knowledge sharing platform also sets a time decay mechanism for the reputation value. For example, the reputation value of a node decays by 1% every day, preventing high-reputation nodes from being inactive subsequently, and can better encourage user nodes to actively participate in the management and knowledge creation of the platform.

[0078] It can be understood that the decentralized knowledge sharing method of the present invention constructs a decentralized knowledge platform, which can convert the data submitted by users into trusted knowledge asset NFTs, and promote the healthy development of the platform and the effective circulation of knowledge through identity management, content verification, data storage, incentive mechanisms, and application interfaces. The decentralized knowledge platform can be regarded as a decentralized knowledge engine that can provide verified and trusted information for any given knowledge need. Its core functions include: knowledge NFTization and verification, converting the knowledge and materials provided by users into unique NFTs, and ensuring their authenticity through the platform's verification mechanism; value circulation and incentives, allowing users to trade the right to use knowledge NFTs, etc., and encouraging knowledge contribution and platform participation through token incentive mechanisms.

[0079] Specifically, such as Figure 5As shown in the figure, the decentralized knowledge platform specifically includes an identity layer, a data layer, a verification layer, an incentive layer, and an application layer. The identity layer is responsible for user identity verification and the setting and management of professional tags. The identity layer is a prerequisite for users to enter the platform. Users log in through DID, and the platform manages users' DID information. Users set their professional tags here, including standardized first-level and second-level tags referring to UNESCO subject classifications, as well as user-defined tags. The setting of professional tags has corresponding requirements for users' professional qualifications, and users need to submit supporting documents, such as degree certificates, vocational qualification certificates, etc. The data layer is responsible for storing various data in the platform, such as users' content to be verified, NFTs, DID registration information, etc. The data layer is the storage center of the platform's knowledge assets, involving both blockchain storage and off-chain storage. For example, the hash value of the knowledge to be verified is stored on the blockchain, while its specific content is stored off-chain. At the same time, relevant metadata, such as content summaries, tags, etc., are also recorded on the chain for convenient retrieval and display. The verification layer is mainly composed of a dynamic oracle network and the K-Raft consensus algorithm, and is responsible for verifying the authenticity of the content submitted by users to ensure the credibility of the platform's knowledge content. The verification layer is the core quality assurance link of the platform. The content to be verified is sent from the data layer, and the smart contracts deployed by the platform nodes use message queues to handle a large number of verification requests. The dynamic oracle network is the main mechanism for verifying content authenticity. The oracle itself consists of a node network, and each node participates in the authenticity review of the knowledge to be verified. The final result is determined through the K-Raft consensus mechanism. The K-Raft algorithm, that is, the KnowledgeRaft algorithm, is a consensus algorithm that improves and innovates on the basis of the existing Raft algorithm for the specific scenario of oracle verifying knowledge authenticity. The existing Raft algorithm itself can only ensure data consistency and is not very suitable for this application scenario. Therefore, this invention modifies it on this basis and designs the K-Raft algorithm. The incentive layer is responsible for rewarding and punishing users according to verification results and platform rules. The incentive layer aims to drive users to actively participate in platform construction. For knowledge verified as "true", its uploader will receive token rewards, while users who give false content will be punished. Users' reputation values will be updated according to the verification results of the uploaded content, and the platform's tokens will be distributed according to preset rules. The application layer consists of various users interacting with the platform, including knowledge providers, knowledge consumers, and a large number of NFT transactions. The application layer is the place where users interact with the platform. The participants in the application layer are generally divided into two categories, namely knowledge providers and knowledge consumers. Users can browse the content on the platform here and conduct NFT transactions. At the same time, NFT owners can manage their NFT assets and view their sales situations, etc.

[0080] Specifically, the identity layer includes a user registration module, a DID generation module, a professional label management module, a token staking module, a key management module, and a DID resolver. Among them, the user registration module is used to provide a user interface, collect user registration information, such as username, password (stored in hash encryption), and optionally integrate third-party logins, such as wallet logins like MetaMask. The function of this module is to process user account registration and call the DID generation module. The DID generation module adopts DID standards, such as DID:web or DID:ethr, to generate a unique decentralized identity identifier DID for each user, and uses an asymmetric encryption algorithm, such as ECDSA, to generate a key pair. The public key is associated with the DID, and the private key is securely kept by the user. The function of this module is to create and return the user's DID and bind the DID to the user account. The professional label management module sets up a three-level professional label system. It constructs a first-level label list based on the UNESCO Field of Science and Technology Classification (FOS) and stores it using a smart contract, and provides a query interface to support limited modification and extension by the community through proposals and voting; it constructs a second-level label list based on the sub-disciplines of UNESCO FOS, also stores it using a smart contract, and establishes an association with the first-level labels, supporting limited modification and extension by the community through proposals and voting; the third-level labels are custom labels, stored in the user DID document or an off-chain database, and can choose to use decentralized storage solutions such as IPFS or Ceramic Network, and are associated with the user's DID, providing interfaces for users to add, delete, and modify custom labels; the function of this module is to manage the user's three-level professional label system and provide functions for adding, deleting, modifying, and querying labels. The token staking module uses a smart contract to implement the token staking function, supporting locking a specified amount of tokens for a new user for a period of time, i.e., the observation period. Parameters such as the duration of the observation period and the amount of staked tokens can be adjusted through the governance module. The function of this module is to process the token staking and unstaking operations of new users and record the staking status. The key management module provides a user-friendly key management tool, which can be a wallet integrated into the platform or guide users to use a third-party wallet, such as MetaMask. The key management tool needs to support the generation, backup, recovery, and use of DID keys. The function of this module is to help users securely generate, store, and manage their DID keys. The DID resolver implements the DID resolution protocol, queries the corresponding DID document according to the DID. The DID document can be stored on the blockchain or off-chain and is pointed to by the serviceEndpoint in the DID document. The function of this module is to resolve the DID, obtain the DID document, and thus obtain the user's public information, such as professional labels, etc.

[0081] The data layer includes a blockchain storage module, an off-chain storage module, a data retrieval module, and an NFT minting module. Among them, the blockchain storage module is a consortium blockchain built based on FISCO BCOS, which is used to store the metadata of the content to be verified and NFTs, DID registration information, professional tag libraries, verification results, incentives obtained by users, the status of the incentive pool, NFT transaction records, etc. The consortium blockchain is jointly maintained and operated by the organization behind the platform and its partners. Each participating organization runs one or more nodes to jointly maintain the ledger data. The function of this module is to provide data immutability, transparency, and traceability, while taking into account performance and controllability. The off-chain storage module uses decentralized storage networks such as IPFS or Ceramic Network to store large files, such as the complete knowledge content, high-definition pictures, videos, etc. uploaded by users. It works in conjunction with the blockchain storage module to ensure data integrity and accessibility. The function of this module is to store larger data files and relieve the storage pressure on the blockchain. The data retrieval module is used to build an indexing service, which supports retrieving NFTs according to conditions such as keywords, professional tags, author DID, etc. It can use decentralized indexing protocols such as TheGraph or build its own indexing service. The function of this module is to provide efficient data retrieval functions to facilitate users to find the required NFTs. The NFT minting module adopts NFT standards such as ERC-721 or ERC-1155 to mint the verified content and its metadata into NFTs, and uses smart contracts to implement operations such as the creation, transfer, and destruction of NFTs. The function of this module is to mint the verified content into NFTs and associate them with the DID of the content creator.

[0082] The verification layer includes a verification request module, a content upload module, a content review module, and a dispute arbitration module. Among them, the verification request module provides a user interface that allows knowledge providers to initiate content verification requests. Users need to submit the summary of the content to be verified and select whether they need verification services. To manage a large number of requests, the platform uses message queue technology for asynchronous processing to ensure the orderliness and efficiency of requests. For the content that needs to be verified, the content upload module will record its metadata such as hash value on the blockchain to ensure data traceability and immutability. At the same time, to reduce the storage pressure on the blockchain, the original data of the content will be stored in an off-chain storage system such as IPFS. The content upload module will record the access address of the content in the off-chain storage and associate this address with the hash value of the content, thus establishing a reliable mapping relationship between on-chain and off-chain data. The content review module is the core of the verification layer and is responsible for executing the key processes of content authenticity review. Its internal operation logic is mainly divided into the following stages:

[0083] ① Dynamic oracle network construction and node screening: When the platform receives a content verification request, the content review module first initiates the construction process of the dynamic oracle network. The content review module will, based on the professional tags of the content to be verified, and comprehensively considering multiple factors such as the reputation value, professional background, and historical verification performance of platform users, use intelligent algorithms to screen out a group of user nodes with appropriate specialties and good reputations. These nodes will form a temporary oracle network for this verification task. The content review module will send verification invitations to the selected nodes, inviting them to participate in the authenticity review of the content.

[0084] ② Node invitation and response: The content review module sends verification invitations to the screened nodes through smart contracts, and clearly specifies the detailed information and response time limit of the verification task in the invitation. After receiving the verification invitation on the client side, the user node can choose whether to accept the invitation according to its own situation. If the node accepts the invitation, it needs to respond within the specified time. Failure to respond within the time limit is regarded as a rejection of the invitation. The nodes that successfully accept the invitation will officially join the dynamic oracle network of this verification task.

[0085] ③ K-Raft consensus-driven oracle network review: After the dynamic oracle network is constructed, the content review module will initiate the content review process based on the K-Raft consensus algorithm. First, the oracle network will conduct a Leader election to elect a Leader node from the participating nodes, which is responsible for coordinating and organizing subsequent verification work. After the Leader node is elected, it will actively collect supporting information related to the content to be verified from multiple trusted data sources such as authoritative knowledge bases, academic databases, industry reports, and public APIs, and construct a knowledge graph based on the collected information to provide a multi-dimensional reference basis for subsequent content authenticity judgment. The Leader node will distribute the knowledge graph it constructs to other Follower nodes in the network as an important tool for auxiliary verification.

[0086] ④ Review and reputation-weighted voting: For each node in the oracle network, after the Leader node distributes the knowledge graph, the Follower can start reviewing the original content stored off-chain. The participating nodes need to independently judge the authenticity of the content by combining their own professional knowledge, the knowledge graph provided by the Leader node, and other auxiliary information, and give a clear verification opinion. The verification opinion usually includes options such as "true", "false", or "unable to judge". After the node completes the review, it needs to submit the verification opinion to the content review module. After the content review module collects the opinions of all participating verification nodes, it will conduct a weighted summary of the verification opinions according to the K-Raft consensus algorithm. During the weighting process, the reputation value of the node will be used as an important weight coefficient. The higher the reputation value of the node, the higher its voting weight, so as to ensure that high-reputation nodes play a greater role in the consensus decision-making.

[0087] ⑤ Consensus result determination: After the Leader collects the opinions of all participating verification nodes, it will perform weighted aggregation on the verification opinions according to the requirements of the K-Raft consensus algorithm and make a determination based on the aggregation result. If SUPPORT True ≥ T, it is determined that the content verification passes and is confirmed as "true" content; if SUPPORT False ≥ T, it is determined that the content verification fails and is confirmed as "false" content; if SUPPORT True < T and SUPPORT False < T, it means that the current voting result has not reached a consensus, and the dispute arbitration process will be triggered. T is a configurable parameter representing the minimum weighted support rate required to reach a consensus. The platform can dynamically adjust the T value through the governance module. The final consensus result, whether it is "true", "false" or "trigger dispute arbitration", will be recorded by the content review module in the blockchain network as an important basis for content NFT minting and subsequent applications. At the same time, information such as the participating verification nodes, voting details, weight details, and timestamps will also be recorded together to ensure the transparency and traceability of the verification process.

[0088] When the content review module cannot make a clear determination on the authenticity of the content through the K-Raft consensus algorithm, the dispute arbitration module will be launched. This module is responsible for inviting authoritative institutions or expert nodes in specific fields in the consortium chain to form an arbitration committee to conduct further expert review and adjudication on the controversial verification results. The adjudication result of the arbitration committee will be used as the final verification conclusion and recorded in the blockchain to ensure the fairness of the arbitration process and the authority of the result.

[0089] The incentive layer includes a reward and punishment mechanism module, a reputation management module, a token allocation module, a token model management module, and an incentive pool management module. The function of the reward and punishment mechanism module is to issue token rewards to users who give correct verification opinions or upload real content, and to punish users who give incorrect verification opinions or upload false content with tokens. The issuance of rewards and punishments are all executed by the relevant smart contracts deployed by the platform. The reputation management module updates the reputation of the user according to the verification and upload behavior of the user. Correct verification and uploading of knowledge content increase the reputation value, and incorrect verification and uploading of incorrect content reduce the reputation value. A time decay mechanism is introduced, such as a 1% decay per day, to prevent high-reputation nodes from subsequent inaction. The reputation value of the node is stored in the blockchain. The aspects involved in the token allocation module are: ① Dynamic adjustment: dynamically adjust the basic incentive and penalty values ​​according to the token balance of the incentive pool and the overall activity of the platform; ② Alliance member node rewards: extract a certain proportion of the transaction fee and allocate it to member nodes that participate in consensus and maintain the alliance chain, such as rewarding nodes that maintain the stable operation of the blockchain and provide computing resources, and inject the remaining part into the incentive pool; ③ Incentive pool replenishment: when the number of tokens in the incentive pool is lower than the preset threshold, the platform reserved funds are automatically replenished, which can be managed by the alliance chain governance organization; ④ Field differentiation: set different reward and penalty coefficients according to different knowledge fields, such as giving higher rewards for verification in popular fields; the function of this module is to manage the allocation of tokens, including rewards, penalties, and fee allocation. The token model management module designs smart contracts, and calculates the total value of products in the NFT market by imitating the real-world method of calculating economic volume. According to the difference between this value and the current token circulation, the supply of tokens is automatically adjusted. It can be issued or repurchased, and a cooperative relationship is reached with the bank, and included in the alliance chain. When the token is issued or repurchased, the on-chain operation and the bank's special account funds are transferred synchronously through the API interface. Key parameters can be adjusted by the alliance governance body. The function of this module is to stabilize the token price, ensure that there is no large fluctuation by automatically adjusting the token supply, and use the API to automatically synchronize the on-chain token operation with the bank funds, providing a stable transaction medium for the NFT market. All operations are recorded on the chain to improve transparency, and finally realize the automatic management of the token model and reduce manual intervention. The incentive pool management module uses smart contracts deployed on the alliance chain to manage the incentive pool, record the token balance of the incentive pool, and carry out the inflow and outflow of funds according to the instructions of the token allocation module. The funds in the incentive pool can be linked to real-world currencies, such as establishing an association with the legal currency reserves in the bank account. The function of this module is to maintain the adequacy and dynamic balance of the funds in the incentive pool and ensure the sustainability of the reward mechanism.

[0090] The application layer includes a knowledge provider interface, a knowledge consumer interface, an NFT trading module, and a community governance module. Among them, the knowledge provider interface provides a Web interface or a mobile APP, allowing knowledge providers to manage their NFTs, such as viewing, listing, and delisting, and also allowing them to view information such as their own earnings and reputation values. The function of this module is to provide functions such as content publishing and NFT management for knowledge providers. The knowledge consumer interface provides a Web interface or a mobile APP, allowing knowledge consumers to browse, search for, and purchase NFTs, and view the detailed information of NFTs, including metadata and TEE certificate hashes, etc. The function of this module is to provide functions such as content browsing and NFT purchase for knowledge consumers. The NFT trading module provides an NFT trading market, supporting the buying and selling of NFTs between users, and using smart contracts to handle trading logic to ensure the security and atomicity of transactions. The function of this module is to provide a venue for NFT trading for platform users, and NFT trading provides a basis for the value circulation of trusted information and knowledge. The community governance module provides an interface for user groups to participate in platform management, and the functions that can be realized are as follows: ① Node proposal: Community members can initiate node proposals, including: a. Modifying platform parameters: For example, adjusting the observation period duration of verification nodes, the quantity of staked tokens, the reputation value threshold, the verification consensus threshold T, the reward coefficient, the penalty coefficient, the incentive pool replenishment threshold, etc.; b. Upgrading platform functions: For example, introducing new NFT standards, optimizing the DID parsing protocol, enhancing the data retrieval function, etc.; c. Adjusting the professional tag library: Making limited modifications and expansions to the primary and secondary professional tag libraries; d. Deciding whether to adopt new academic institutions or authoritative organizations: Making them become nodes with authoritative certification in the consortium chain and participating in dispute arbitration. ② Community voting: Community members can vote on proposals, and the voting weight can be determined according to factors such as the quantity of tokens they hold or their reputation value. For example, using mechanisms such as quadratic voting to prevent large whale users from manipulating the voting results. ③ Parameter configuration: Proposals passed by community voting will automatically update the parameter configuration of the platform. For example, if the community votes to pass a proposal to modify the verification consensus threshold T, the smart contract will automatically update the value of T. ④ Permission control: Implementing fine-grained permission management based on consortium chain technology. For example, using the permission governance system of FISCO BCOS, the governance committee can manage the deployment of contracts and the interface call permissions of contracts through voting, and can control at the platform level which user groups can participate in specific types of proposals or voting, and even can control the access permissions of specific smart contracts. For example, only users authorized by community voting can call the smart contract for modifying the professional tag library.

[0091] In addition, as Figure 6 shown, another embodiment of the present invention also provides a decentralized knowledge sharing system, including:

[0092] A knowledge upload module for allowing a knowledge provider node to upload knowledge content to a knowledge sharing platform, where the knowledge sharing platform is a blockchain-based decentralized knowledge platform;

[0093] An authenticity verification module for constructing a dynamic oracle network and verifying the authenticity of knowledge content based on the K-Raft algorithm, writing the authenticity verification result to the knowledge sharing platform, and notifying the knowledge provider node;

[0094] A digital asset generation module for converting knowledge content into digital assets of the knowledge provider node after the authenticity verification passes.

[0095] It can be understood that in the decentralized knowledge sharing system of this embodiment, after uploading knowledge content to the blockchain-based decentralized knowledge platform, by constructing a dynamic oracle network in the blockchain platform and using the K-Raft algorithm to verify the authenticity of the knowledge content, it abandons centralized review and adopts distributed verification, improving the efficiency, pertinence, and reliability of authenticity verification. Moreover, the K-Raft algorithm introduces a knowledge graph on the basis of the existing Raft consensus algorithm, associates the verification content with a broader knowledge background to assist each node of the dynamic oracle network in making authenticity judgments, improving the accuracy and depth of authenticity verification, effectively improving the authenticity and credibility of knowledge and information on the knowledge sharing platform. And after the authenticity verification passes, digital assets are generated for the knowledge provider, enabling users to have ownership and control of the data, avoiding the risks of data leakage and abuse.

[0096] In addition, the decentralized knowledge sharing system further includes:

[0097] A digital asset reward and punishment module for rewarding or punishing the knowledge provider node and the nodes participating in the authenticity verification according to the authenticity verification result.

[0098] In addition, the decentralized knowledge sharing system further includes:

[0099] A reputation value update module for updating the reputation value according to the verification behavior and upload behavior of each node in the knowledge sharing platform.

[0100] It can be understood that each module of the system embodiment of this system corresponds to each step of the method embodiment above. Therefore, the specific working principles of each module will not be elaborated, and reference can be made to each step of the method embodiment above.

[0101] In addition, another embodiment of the present invention further provides an electronic device, including a processor and a memory, where a computer program is stored in the memory, and the processor is used to execute the steps of the method as described above by calling the computer program stored in the memory.

[0102] In addition, another embodiment of the present invention further provides a computer-readable storage medium for storing a computer program for decentralized knowledge sharing. When the computer program runs on a computer, it executes the steps of the method described above.

[0103] The forms of common computer-readable storage media include: floppy disks, flexible disks, hard disks, magnetic tapes, any other magnetic media, CD-ROMs, any other optical media, punch cards, paper tapes, any other physical media with a pattern of holes, random access memories (RAMs), programmable read-only memories (PROMs), erasable programmable read-only memories (EPROMs), flash erasable programmable read-only memories (FLASH-EPROMs), any other memory chips or cartridges, or any other media readable by a computer. The instructions can further be transmitted or received by a transmission medium. The term transmission medium can include any tangible or intangible medium that can be used to store, encode, or carry instructions for execution by a machine, and includes digital or analog communication signals or the intangible media that facilitate the communication of the above instructions. The transmission medium includes coaxial cables, copper wires, and optical fibers, which include the wires of a bus used to transmit a computer data signal.

[0104] Those skilled in the art should understand that the embodiments of the present application can be provided as methods, systems, or computer program products. Therefore, the present application can take the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware aspects. Moreover, the present application can take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk memories, CD-ROMs, optical memories, etc.) containing computer-usable program code. The solutions in the embodiments of the present application can be implemented in various computer languages. For example, object-oriented programming languages such as Java and interpreted scripting languages such as JavaScript.

[0105] The present application is described with reference to the flowcharts and / or block diagrams of methods, apparatuses (systems), and computer program products according to the embodiments of the present application. It should be understood that each flow and / or block in the flowcharts and / or block diagrams, and the combination of flows and / or blocks in the flowcharts and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to the processors of general-purpose computers, special-purpose computers, embedded processors, or other programmable data processing devices to generate a machine, such that the instructions executed by the processors of the computer or other programmable data processing devices generate for implementation in the process Figure 1one or more processes and / or blocks Figure 1 means for the functions specified in one or more blocks

[0106] These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to operate in a particular manner, such that the instructions stored in the computer-readable memory produce a manufacture including an instruction means that implements the functions in the process Figure 1 one or more processes and / or blocks Figure 1 the functions specified in one or more blocks

[0107] These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus, such that a series of operational steps are performed on the computer or other programmable apparatus to produce a computer-implemented process, whereby the instructions executed on the computer or other programmable apparatus provide steps for implementing the functions in the process Figure 1 one or more processes and / or blocks Figure 1 the functions specified in one or more blocks

[0108] Although the preferred embodiments of the present application have been described, additional changes and modifications can be made by those skilled in the art once they learn of the basic inventive concept. Therefore, the appended claims are intended to be construed to cover the preferred embodiments as well as all changes and modifications falling within the scope of the present application

[0109] Obviously, those skilled in the art can make various changes and modifications to the present application without departing from the spirit and scope of the present application. Thus, if these modifications and variations of the present application fall within the scope of the claims of the present application and their equivalent technologies, the present application is also intended to include these modifications and variations

[0110] The above are only the preferred embodiments of the present invention and are not intended to limit the present invention. For those skilled in the art, the present invention can have various changes and modifications. Any modifications, equivalent replacements, improvements, etc. made within the spirit and principles of the present invention shall be included within the protection scope of the present invention

Claims

1. A decentralized knowledge sharing method, characterized in that, It includes the following: The knowledge provider node uploads the knowledge content to the knowledge sharing platform, where the knowledge sharing platform is a blockchain-based decentralized knowledge platform; Build a dynamic oracle network and verify the authenticity of the knowledge content based on the K-Raft algorithm, and write the authenticity verification result into the knowledge sharing platform and notify the knowledge provider node; If the authenticity verification passes, the knowledge content will be converted into the digital assets of the knowledge provider node.

2. The decentralized knowledge sharing method according to claim 1, wherein The process of building the dynamic oracle network includes the following: Set the screening conditions according to the professional tags of the content to be verified and the reputation values of each node in the knowledge sharing platform, and send invitations to the nodes in the knowledge sharing platform that meet the screening conditions in combination with the random selection mechanism. If the invited nodes accept the invitation within the set response time, they will be used as response nodes. After the response time ends, build a dynamic oracle network based on multiple response nodes.

3. The decentralized knowledge sharing method according to claim 2, characterized in that, The process of verifying the authenticity of the knowledge content based on the K-Raft algorithm includes the following: The dynamic oracle network elects a leader node, and the remaining nodes are follower nodes; The leader node constructs a knowledge graph after collecting information related to the content to be verified from multiple data sources, and sends the digital digest of the content to be verified and the knowledge graph to all follower nodes; All follower nodes vote on the authenticity of the content to be verified according to the knowledge graph and feedback to the leader node. The leader node determines the final authenticity verification result according to the voting results of all follower nodes, where the voting result types include true, false, and unable to judge.

4. The decentralized knowledge sharing method according to claim 3, wherein Calculate the support rates for the voting results of true and false based on the following formula: Among them, SUPPORT True represents the true support rate of the voting result, m represents the true number of nodes in the voting result, and NodeReputation True，i represents the reputation value of the nodes with true voting results, SUPPORT False represents the false support rate of the voting result, n represents the number of nodes with false voting results, and NodeReputation False，i represents the reputation value of the nodes with false voting results. TotalReputation represents the comprehensive reputation value of all nodes in the dynamic oracle network. If SUPPORT True is greater than or equal to the threshold T, the authenticity verification passes. If SUPPORT False is greater than or equal to the threshold T, the authenticity verification fails. If SUPPORT True is less than the threshold T and SUPPORT False is less than the threshold T, the authenticity cannot be determined.

5. The decentralized knowledge sharing method according to claim 3, wherein After obtaining the authenticity verification result, it also includes the following: Reward or punish the knowledge provider node and the nodes participating in the authenticity verification according to the authenticity verification result.

6. The decentralized knowledge sharing method according to claim 5, wherein, If the authenticity verification passes, reward the knowledge provider node and the nodes that vote true with digital assets, and punish the nodes that vote false with digital assets; if the authenticity verification fails, punish the knowledge provider node and the nodes that vote true with digital assets, and reward the nodes that vote false with digital assets.

7. The decentralized knowledge sharing method according to claim 3, wherein After obtaining the authenticity verification result, it also includes the following: Update the reputation values of each node in the knowledge sharing platform according to the verification behavior and upload behavior of each node.

8. A decentralized knowledge sharing system, characterized in that, It includes: A knowledge upload module for the knowledge provider node to upload the knowledge content to the knowledge sharing platform, where the knowledge sharing platform is a blockchain-based decentralized knowledge platform; An authenticity verification module for building a dynamic oracle network and verifying the authenticity of the knowledge content based on the K-Raft algorithm, and writing the authenticity verification result into the knowledge sharing platform and notifying the knowledge provider node; A digital asset generation module for converting the knowledge content into the digital assets of the knowledge provider node after the authenticity verification passes.

9. An electronic device, characterized in that, It includes a processor and a memory. The memory stores a computer program. The processor is used to execute the steps of the method according to any one of claims 1 to 7 by calling the computer program stored in the memory.

10. A computer-readable storage medium for storing a computer program for decentralized knowledge sharing, characterized in that, When the computer program runs on a computer, it executes the steps of the method according to any one of claims 1 to 7.

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