Rural digital property security information sharing method based on blockchain consensus mechanism

Abstract

The application relates to the technical field of blockchain consensus mechanism, in particular to a rural digital property security information sharing method based on a blockchain consensus mechanism, which comprises the following steps: acquiring the basic credibility of each node, and combining the online stability, data validity and network contribution of each node at each moment to determine the weight of each node at each moment; determining the consensus participation probability of each node based on the weight of each node at the current moment, so as to select a master node; and determining whether to trigger transaction submission or view switching based on the proportion of the weight of all nodes that submit transaction preparation information to the master node at the current moment in the total weight of all nodes in the blockchain. The application solves the problem of consensus failure of the traditional consensus mechanism caused by the small number of nodes and the offline of the farmer nodes in the rural blockchain, and improves the efficiency and continuity of the rural blockchain consensus.

Description

Technical Field

[0001] This application relates to the field of blockchain consensus mechanism technology, specifically to a method for sharing secure information on rural digital property rights based on a blockchain consensus mechanism. Background Technology

[0002] Rural digital property rights security information sharing refers to the secure management and cross-entity sharing of property rights information such as rural land contractual management rights, homestead use rights, and agricultural asset ownership through digital technology. This ensures the reliable flow of ownership data among government departments, village collectives, financial institutions, and farmers, solving problems such as data silos, tampering risks, and low sharing efficiency in traditional models. It facilitates the efficient operation of property rights registration, transactions, and financing. The blockchain consensus mechanism, a core component of blockchain technology, refers to a rule system in a distributed network where nodes reach consensus on data records through specific algorithms. Its role is to ensure data consistency, immutability, and reliability in decentralized or multi-centralized environments, enabling all participants to jointly maintain a trusted ledger without relying on a central institution. This provides underlying trust support for the secure sharing of rural digital property rights, ensuring transparency and security in the verification, storage, and updating of property rights information.

[0003] In rural blockchain applications, network nodes typically consist of a small number of entities, including government departments, village collectives, financial institutions, and farmers, resulting in a significantly smaller node scale compared to traditional consortium blockchain environments. Under these conditions, when using traditional consensus mechanisms such as Practical Byzantine Fault Tolerance (PBFT), consensus is easily disrupted because PBFT requires more than two-thirds of the nodes to be online and reach a consensus. If a node goes offline due to network instability or suffers a malicious attack, the number of active online nodes can easily fall below the threshold required for consensus, leading to consensus process stagnation and transaction interruptions. This reduces the efficiency and continuity of rural blockchain consensus. Summary of the Invention

[0004] To address the aforementioned technical issues, this application provides a method for sharing secure information on rural digital property rights based on a blockchain consensus mechanism, thereby resolving the existing problems.

[0005] The rural digital property rights security information sharing method based on blockchain consensus mechanism proposed in this application adopts the following technical solution:

[0006] One embodiment of this application provides a method for sharing rural digital property rights security information based on a blockchain consensus mechanism, the method comprising the following steps:

[0007] In the blockchain of rural digital property rights scenarios, the online stability of each node at each moment is determined by analyzing the proportion of the online time of each node within the preset time period before each moment.

[0008] Obtain the total number of data submitted by each node before each time point, the total number of data that passed verification, and the dispute resolution time caused by each data error. By analyzing the proportion of the total number of data that passed verification to the total number of data submitted under each node, and the proportion of the dispute resolution time caused by each data error to the total number of data submitted, determine the data validity of each node at each time point.

[0009] By analyzing the difference between the distance of each node to the nearest edge server and the distance distribution among all nodes in the blockchain, the distance weight of each node is determined. The number of consensus participations and the number of correct consensuses of each node before each time point are counted to determine the network contribution of each node at each time point. The basic credibility of each node is obtained, and combined with the online stability, data validity and network contribution of each node at each time point, the weight of each node at each time point is determined.

[0010] Based on the weight of each node at the current moment, the consensus participation probability of each node at the current moment is determined to select the master node. Based on the proportion of the weight of all nodes that submit transaction preparation information to the master node at the current moment in the total weight of all nodes in the blockchain, it is determined whether to trigger transaction submission or view switching.

[0011] Preferably, the expression for the online stability of each node at each time point is: In the formula, , Let i represent the online stability of node i at time t and time t-1, respectively. hour, ; , These represent the online duration of node i at time t and the length of the preset duration, respectively. This indicates the preset weighting coefficient.

[0012] Preferably, the expression for the data validity of each node at each time point is: In the formula, This indicates the validity of the data at node i at time t; , These represent the total number of data entries verified and the total number of data entries submitted by node i before time t, respectively. This indicates the duration of dispute resolution caused by the nth data error at node i before time t; This represents the total number of data errors at node i before time t; This indicates the preset penalty coefficient.

[0013] Preferably, the distance weight of each node is the ratio of the distance from each node to the nearest edge server to the average distance between all nodes in the blockchain.

[0014] Preferably, the expression for the network contribution of each node at each time point is: In the formula, This represents the network contribution of node i at time t. , Let represent the total number of consensus participations and the number of correct consensuses before time t, respectively; The distance weight of node i is represented; This represents the distance from node i to the nearest edge server before time t; This indicates the preset distance factor.

[0015] Preferably, obtaining the basic trustworthiness of each node includes:

[0016] In the blockchain of rural digital property rights scenario, all nodes include three categories: government nodes, village committee nodes, and farmer nodes. The basic trust level of all government nodes is set to a preset first value, the basic trust level of all village committee nodes is set to a preset second value, and the basic trust level of all farmer nodes is set to a preset third value. The preset first value is greater than the preset third value, and the preset second value is between the preset first value and the preset third value.

[0017] Preferably, the method for determining the weight of each node at each time point is as follows:

[0018] The online stability, data validity, network contribution, and basic credibility of each node at each time point are positively integrated and denoted as the weighted feature value of each node at each time point.

[0019] If node m is an offline node, then the weight of node m The expression is: In the formula, This represents the weighted feature value when node m is offline; This represents the offline time of node m; This indicates the preset attenuation coefficient; exp() represents an exponential function with the natural constant as the base.

[0020] If node m is not an offline node, then the weight of node m at each time step is the weight feature value of node m at each time step. By traversing all nodes, the weight of each node at each time step can be obtained.

[0021] Preferably, the consensus participation probability of each node at the current moment is the ratio of the weight of each node at the current moment to the total weight of all nodes in the blockchain.

[0022] Preferably, the master node is the node with the highest probability of participating in consensus among all nodes in the blockchain at the current moment.

[0023] Preferably, determining whether to trigger a transaction submission or view switching includes:

[0024] If the weight of all nodes that submit transaction preparation information to the master node at the current moment accounts for a greater than a preset value in the total weight of all nodes in the blockchain, then the transaction submission is triggered.

[0025] If the current master node fails to initiate a transaction proposal within a preset time period or if more than a preset proportion of nodes report the master node as malicious, a view switch will be triggered.

[0026] This application has at least the following beneficial effects:

[0027] This application calculates online stability by quantifying the proportion of online time of nodes, dynamically assessing the ability of nodes to continuously participate in consensus. This is particularly suitable for scenarios with unstable rural networks, helping to adjust node weights based on actual reliability, incentivizing stable nodes and constraining unstable nodes, thereby improving the efficiency and continuity of rural blockchain consensus. Furthermore, this application constructs a data validity score by analyzing the effective proportion of data submitted by nodes and the cost of disputes caused by errors. This data validity score dynamically assesses the quality of nodes as data sources, helping to identify reliable and unreliable data providers, incentivizing nodes to improve data accuracy, reducing the burden of manual verification, and thus ensuring the credibility and sharing efficiency of property rights data on rural blockchains. Finally, this application dynamically adjusts node weights based on online stability, data validity, and network contribution. This approach constrains nodes that are unstable online, have poor data quality, or contribute little to the network, reducing their adverse impact on consensus and network status. It effectively incentivizes nodes to improve their performance, enhancing the continuity and sharing efficiency of property rights data on rural blockchains. Furthermore, this application uses dynamic weighting to calculate consensus participation probabilities and elects master nodes. During the consensus verification phase, after the master node collects transaction proposals, other nodes execute the verification. The submission phase requires approval from at least two-thirds of the total weight, rather than being solely determined by the number of nodes. When switching views, highly stable nodes are re-elected, effectively constraining the participation of low-quality nodes, incentivizing high-quality nodes, and solving the problem of consensus failure caused by the small number of nodes and the tendency for farmer nodes to go offline in rural blockchains. This improves the efficiency and continuity of consensus in rural blockchains. Attached Figure Description

[0028] To more clearly illustrate the technical solutions and advantages in the embodiments of this application 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 of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0029] Figure 1 A flowchart illustrating the steps of a rural digital property rights security information sharing method based on a blockchain consensus mechanism, as provided in one embodiment of this application;

[0030] Figure 2 This is a schematic diagram of the node weight extraction process provided in one embodiment of this application. Detailed Implementation

[0031] To further illustrate the technical means and effects adopted by this application to achieve its intended purpose, the following, in conjunction with the accompanying drawings and preferred embodiments, details the specific implementation, structure, features, and effects of the rural digital property rights security information sharing method based on a blockchain consensus mechanism proposed in this application. In the following description, different "one embodiment" or "another embodiment" do not necessarily refer to the same embodiment. Furthermore, specific features, structures, or characteristics in one or more embodiments can be combined in any suitable form.

[0032] 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 application pertains.

[0033] The following, in conjunction with the accompanying drawings, details the specific scheme of the rural digital property rights security information sharing method based on blockchain consensus mechanism provided in this application.

[0034] This application provides an embodiment of a method for sharing secure information on rural digital property rights based on a blockchain consensus mechanism. Specifically, the method is described below. Please refer to [link to relevant documentation]. Figure 1 The method includes the following steps:

[0035] Step S1: In the blockchain of rural digital property rights scenario, the online stability of each node at each time point is determined by analyzing the proportion of the online time of each node within the preset time period before each time point.

[0036] In rural blockchain scenarios, node types are diverse and exhibit significant differences in stability. Government nodes bear the core responsibility for supervision, village collective nodes are responsible for grassroots data verification, while farmer nodes, limited by network environment and operational capabilities, suffer from frequent offline issues and inconsistent data submission quality. Traditional consensus mechanisms, employing fixed weights, cannot adapt to these dynamic changes, easily leading to two extremes: the system stagnates when highly trusted nodes go offline, or low-trust nodes over-participate due to their weights, causing security risks.

[0037] This embodiment assigns dynamic weights to different nodes, quantifies the credibility, activity, data quality, and network contribution of nodes in real time, and constructs a consensus system that matches rights and responsibilities. While ensuring the government's leading role in supervision, it incentivizes farmers to actively participate and constrains their behavior, ultimately solving the technical problems of consensus fragility and high data verification costs in rural blockchain with small node scale.

[0038] The blockchain network nodes in this embodiment include high-trust nodes, such as government departments, township-level organizations, and abnormal financial institutions; medium-trust nodes, such as village committees, agricultural cooperatives, and village collective economic organizations; and low-trust nodes, such as farmers, family farm owners, and rural micro-enterprises.

[0039] Nodes are prone to intermittent disconnections or prolonged periods of inactivity due to weak network infrastructure and irregular device usage, leading to fluctuations in consensus participation rates, transaction confirmation delays, and even network partitioning risks. Therefore, it is necessary to quantify the ability of nodes to continuously participate in consensus through online stability indicators, dynamically adjust their weights, incentivize node online status, and prevent consensus mechanism failure caused by an excessively high proportion of offline nodes. This ensures the real-time and continuous verification of rural data property rights. The specific process is as follows:

[0040] In the blockchain context of rural digital property rights, this embodiment determines the online stability of each node at each moment by analyzing the proportion of each node's online time within a preset time period before each moment. Specifically:

[0041] As one implementation method, in this embodiment, the online stability of node i at time t is... The expression is: In the formula, , Let represent the online stability of node i at time t and time t-1, respectively, where , where, when hour, ; , These represent the online duration of node i at time t and the length of the preset duration, respectively. This indicates the preset weighting coefficient.

[0042] It should be noted that the preset weight coefficient is set manually, and the value of the preset weight coefficient ranges from 0 to 1. In this embodiment, the preset weight coefficient is set to 0.6. In actual applications, as other implementation methods, implementers can also set it themselves according to specific circumstances. This embodiment does not impose any special restrictions. In addition, the preset duration is also set manually. In this embodiment, the preset duration is set to 1 day. In actual applications, implementers can also set it themselves according to specific circumstances. This embodiment does not impose any special restrictions.

[0043] It should be noted that in this embodiment, the online stability is multiplied by 100 to avoid the online stability being too high and to keep the value of the online stability between 0 and 100.

[0044] Based on the online stability of each node at each time point, it can be understood that if the online time of node i is within the preset time period, the larger the proportion, the higher the online continuity and reliability of node i, and the greater the corresponding online stability. This indicates that node i can better overcome difficulties such as network instability, maintain its connection with the blockchain network, and contribute to the stable operation of the network. Conversely, if the online time of node i is within the preset time period, the smaller the proportion, the more unstable the online state of node i is, and it is frequently offline. Node i may be affected by a poor network environment, and its contribution continuity and reliability are relatively low, which may affect the consensus efficiency of the blockchain.

[0045] Thus, this embodiment calculates online stability by quantifying the proportion of online time of nodes, dynamically assessing the ability of nodes to continuously participate in consensus. It is particularly suitable for scenarios with unstable rural networks, and helps to adjust the weight of nodes according to their actual reliability, incentivizing stable nodes and constraining unstable nodes, thereby improving the efficiency and continuity of rural blockchain consensus.

[0046] Step S2: Obtain the total number of data submitted by each node before each time point, the total number of data that passed verification, and the dispute resolution time caused by each data error. By analyzing the proportion of the total number of data that passed verification to the total number of data submitted by each node, and the proportion of the dispute resolution time caused by each data error to the total number of data submitted, determine the data validity of each node at each time point.

[0047] In rural digital property rights scenarios, due to the diverse data sources and high verification costs, issues such as data duplication, missing fields, and logical contradictions are prone to occur, leading to unreliable on-chain data and triggering property rights disputes or regulatory risks. Therefore, this embodiment analyzes the proportion of verified data at each node to the total number of submitted data, and the proportion of dispute duration caused by each data error to the total number of submitted data, to determine the data validity of each node at each time point, quantify the quality of data submitted by nodes, penalize the additional processing costs caused by erroneous data, incentivize nodes to improve data entry accuracy, reduce the pressure of manual verification, and safeguard the core value of rural blockchain as a trusted data source. Specifically:

[0048] In the blockchain of rural digital property rights scenario, the total number of data submitted by each node before each time point, the total number of data that has passed verification, and the dispute resolution time caused by each data error are obtained. The dispute resolution time is specifically the time period between the time node of dispute initiation and the time node of judgment reached, which is automatically recorded by the blockchain.

[0049] Furthermore, this embodiment determines the data validity of each node at each time point by analyzing the proportion of the total number of verified data points under each node to the total number of submitted data points, and the proportion of the dispute duration caused by each data error to the total number of submitted data points. Specifically:

[0050] As one implementation method, in this embodiment, the data validity of node i at time t is... The expression is: In the formula, , These represent the total number of data entries verified and the total number of data entries submitted by node i before time t, respectively. This indicates the duration of dispute resolution caused by the nth data error at node i before time t; This represents the total number of data errors at node i before time t; This indicates the preset penalty coefficient.

[0051] It should be noted that the preset penalty coefficient The value is set manually. In this embodiment, the preset penalty coefficient is 50. In actual application, as other implementation methods, the implementer can also set it according to the specific situation. This embodiment does not impose any special restrictions.

[0052] It should be noted that the various data obtained here, as well as the data involving each moment in the calculations below, are obtained within a different time period than the preset duration in step S1. The data analysis period here and below is from the start time of the blockchain operation to each moment.

[0053] Based on the data validity of each node at each time point, it can be understood that if the proportion of the total number of verified data entries of node i before time t is higher than the total number of submitted data entries, it indicates a high proportion of valid data that has passed verification. This suggests that the accuracy, completeness, and compliance of the data submitted by node i are good, making it a trustworthy data provider, and its behavior helps maintain the reliability of on-chain data. At the same time, if the data submitted by node i causes a low degree of controversy, i.e. The smaller the value, the shorter or almost non-existent the dispute resolution time caused by erroneous data under node i is. This indicates that the data submitted by the node is not only valid but also of stable quality, and is unlikely to cause subsequent disputes and additional management burdens, making it a reliable data source.

[0054] Conversely, if the proportion of the total number of verified data entries by node i before time t is smaller than the total number of submitted data entries, it indicates a low proportion of valid data that has passed verification. This suggests that the accuracy, completeness, and compliance of the data submitted by node i are poor, making it an untrustworthy data provider whose actions may compromise the reliability of on-chain data. Simultaneously, if the data submitted by node i causes a high degree of controversy, i.e. The larger the value, the longer the dispute resolution time caused by erroneous data under node i. This indicates that the data submitted by this node is not only of unstable quality, but also prone to subsequent disputes and additional management burdens, making it an unreliable data source.

[0055] Thus, this embodiment constructs a data validity system by analyzing the effective proportion of data submitted by nodes and the cost of disputes caused by errors. The data validity system dynamically evaluates the quality of nodes as data sources, helps to identify reliable and unreliable data providers, incentivizes nodes to improve data accuracy, reduces the burden of manual verification, and thereby ensures the credibility and sharing efficiency of property rights data on rural blockchains.

[0056] Step S3: By analyzing the difference between the distance of each node to the nearest edge server and the distance distribution among all nodes in the blockchain, determine the distance weight of each node, and count the number of consensus participations and correct consensuses of each node before each time point to determine the network contribution of each node at each time point; obtain the basic credibility of each node, and combine the online stability, data validity and network contribution of each node at each time point to determine the weight of each node at each time point.

[0057] While assigning weights to nodes based on their actual contributions to the blockchain network, the geographical distribution of farmer nodes and uneven network conditions mean that relying solely on contribution can lead to a few highly trusted nodes dominating consensus, weakening decentralization. Therefore, this embodiment analyzes the difference between the distance from each node to the nearest edge server and the distance distribution among all nodes in the blockchain to determine the distance weight of each node. It also calculates the number of consensus participations and correct consensuses for each node before each time point to determine the network contribution of each node at each time point. Furthermore, it obtains the basic trustworthiness of each node and combines it with the online stability, data validity, and network contribution of each node at each time point. In other words, by incorporating geographical compensation factors, it balances the power of different nodes, improving the centrality and stability of the blockchain network. Specifically:

[0058] As one implementation method, in this embodiment, the ratio of the distance from each node to the nearest edge server to the average distance between all nodes in the blockchain is used as the distance weight of each node.

[0059] Furthermore, the network contribution of node i at time t. The expression is: In the formula, , Let represent the total number of consensus participations and the number of correct consensuses before time t, respectively; The distance weight of node i is represented; This represents the distance from node i to the nearest edge server before time t; This indicates the preset distance factor.

[0060] It should be noted that the preset distance factor is 5, and the unit is kilometers. In actual application, as other implementation methods, implementers can also set it according to specific circumstances. This embodiment does not impose any special restrictions.

[0061] It should be noted that, Multiplying by 2 means that the weight increase from each correct consensus action is twice that of ordinary participation, which helps to suppress malicious or low-quality nodes and allows stable, reliable nodes that correctly participate in consensus to receive greater weight rewards. Furthermore, the exponent is set to 1.1 because 1.1 is a base greater than 1. The core idea behind this is to provide additional weight compensation to nodes that are geographically remote, have higher network access costs, and face greater difficulty in participating in consensus. In this embodiment, a preset distance factor is set. The value of 5 indicates that for nodes located in remote areas with high network access costs and difficulty in participating in consensus, the network contribution increases by 10% for every 5 kilometers increase in the distance to the nearest edge server. This is to balance the differences in participation costs caused by physical distance, encourage network resources to be tilted towards grassroots and remote areas, and ensure the broad participation and distributed characteristics of the rural blockchain network.

[0062] The process of obtaining the consensus parameter count and the correct consensus count are well-known technologies, and the specific acquisition principle will not be elaborated here.

[0063] It should be noted that edge servers are a well-known technology, and their specific concepts will not be elaborated upon here.

[0064] Based on the network contribution of each node at each time point, it can be understood that if the total number of consensus participations of node i before time t is larger, it indicates that node i has participated more actively in the consensus process of the blockchain network. Whether as a validator or in other roles, its activity level is high, and it has contributed basic participation labor to the network operation, resulting in a relatively large network contribution. At the same time, if the number of correct consensuses of node i before time t is larger, it indicates that node i is not only active, but also that its participation is of high quality. The consensus opinions contributed by node i are correct and effective, indicating that node i's contribution to the network is greater, and therefore, its corresponding network contribution is greater. In addition, if the ratio of the distance of node i to the nearest edge server to the average distance between all nodes in the blockchain is larger, that is, the distance weight is larger, it indicates that node i's geographical location is relatively remote, far from the network core and service nodes. In the calculation process, its contribution is further amplified through subsequent exponential addition, reflecting geographical compensation for nodes in remote areas, thereby encouraging broader geographical coverage and participation. The larger the value, the greater the additional nonlinear compensation for remote nodes, which greatly increases the weight of remote nodes. This is intended to balance the participation inequality caused by physical distance and ensure that network resources are tilted towards the edge areas.

[0065] Conversely, if the total number of consensus participations by node i before time t is smaller, it indicates that node i's activity in the blockchain network consensus process is low, its contribution to the basic participation labor of network operation is relatively small, and its corresponding network contribution is relatively small. At the same time, if the number of correct consensuses by node i before time t is smaller, it indicates that although node i may have participated in the consensus, the quality of its contribution is not high, and the consensus opinions it provides may be erroneous or invalid, indicating that node i's contribution to the reliability of the network is low, and therefore, its corresponding network contribution is also relatively small. In addition, if the ratio of the distance from node i to the nearest edge server to the average distance between all nodes in the blockchain is smaller, that is, the distance weight is smaller, it indicates that node i's geographical location is relatively close to the network core and service nodes, the physical obstacles to participating in network interaction are smaller, the geographical compensation it receives in the calculation process is also smaller, and the amplification effect of geographical factors on its contribution is limited. The smaller the value, the less additional nonlinear compensation is given to remote nodes. Their weight is determined more by the number and quality of their consensus participation, and the additional weight bias brought about by geographical distance is not obvious.

[0066] Furthermore, since the inherent trust foundations of different types of nodes differ significantly, this embodiment assigns different basic trust levels to different types of nodes to establish a consensus starting point that aligns with real-world governance structures, specifically:

[0067] As one implementation method, in this embodiment, in the blockchain of the rural digital property rights scenario, all nodes include three categories: government nodes, village committee nodes, and farmer nodes. The basic trust level of all government nodes is set to a preset first value, the basic trust level of all village committee nodes is set to a preset second value, and the basic trust level of all farmer nodes is set to a preset third value. The preset first value is greater than the preset third value, and the preset second value is between the preset first value and the preset third value.

[0068] It should be noted that the preset first value, preset second value, and preset third value are set manually. In this embodiment, the preset first value is 100, the preset second value is 60, and the preset third value is 20. In actual applications, as other implementation methods, implementers can also set them according to specific circumstances. This embodiment does not impose any special restrictions.

[0069] Furthermore, since farmer nodes may be offline for extended periods due to farmers working away from home, online stability only reflects their recent online status and cannot reduce other weights. If offline nodes are not addressed, their weights may be wasted on resources, causing active nodes to bear more workload without receiving corresponding benefits. Therefore, this embodiment determines the weight of each node at each time point based on its basic trustworthiness, combined with its online stability, data validity, and network contribution. It uses a decay mechanism to quantify the negative impact of offline duration, adjusting node weights based on offline duration to avoid slowing down consensus efficiency due to individual node offlineness. This optimizes resource allocation and ensures the long-term fairness and efficiency of the consensus mechanism. Specifically:

[0070] As one implementation method, in this embodiment, the online stability, data validity, network contribution, and basic credibility of each node at each time point are positively integrated and recorded as the weighted feature value of each node at each time point.

[0071] It should be understood that positive fusion refers to combining two or more indicators through addition or multiplication to obtain a comprehensive indicator, thereby more comprehensively and accurately assessing a phenomenon or problem. This fusion method is not limited to simple arithmetic operations, but can also include more complex statistical models and analytical methods. Implementers can choose according to specific circumstances, and this embodiment does not impose any special restrictions.

[0072] Preferably, in this embodiment, the sum of the online stability, data validity, network contribution, and basic credibility of each node at each time point is used as the weight feature value of each node at each time point.

[0073] If node m is an offline node, then the weight of node m The expression is: In the formula, This represents the weighted feature value when node m is offline; This represents the offline time of node m; This indicates the preset attenuation coefficient; exp() represents an exponential function with the natural constant as the base.

[0074] If a node is not an offline node, then the weight of node m at each time step is the weight feature value of node m at each time step. By traversing all nodes, the weight of each node at each time step can be obtained.

[0075] Preferably, the node weight extraction process provided in this embodiment is illustrated in the following diagram: Figure 2 As shown.

[0076] Based on the weight of each node at each time point, it can be understood that the greater the online stability of the current node, the stronger its ability to continuously participate in network activities, the more reliable its behavior, and the more sustained its contribution to network connectivity, thus corresponding to a larger weight. At the same time, the greater the data validity of the current node, the higher the quality of the data submitted by the current node, which helps maintain the overall reliability of on-chain data, thus assigning the current node a larger weight value. In addition, the greater the network contribution of the current node, the greater the quality of the current node's participation in the consensus process, and the more likely it has overcome geographical inconveniences, making significant contributions to the operation and decentralized characteristics of the entire network, thus corresponding to a larger weight value for the node.

[0077] Conversely, a lower online stability of a node indicates a weaker ability to remain online and participate stably in network activities, making its behavior less reliable and its contribution to network connectivity unstable or even interrupted. Therefore, its corresponding weight is lower, reducing the likelihood of the node being elected as a master node or its vote being included in the consensus result, thus mitigating its adverse impact on the network state. Simultaneously, a lower data validity of a node reflects lower quality data submissions that are inaccurate, non-compliant, or prone to controversy. This damages the overall reliability of on-chain data and increases the cost of subsequent verification and correction. Therefore, a smaller weight value is needed to limit the impact of its misconduct on the network and protect the credibility of on-chain data. Furthermore, a lower network contribution indicates low activity in the consensus process or low-quality participation, and the node may not have effectively overcome geographical barriers to participate. This means its contribution to the stable operation and decentralized nature of the entire network is limited, and it may even drag down consensus efficiency. Therefore, the corresponding node's weight value will also be smaller to prevent its inefficient or harmful participation from affecting the entire network's decision-making process.

[0078] It should be noted that the preset attenuation coefficient is set manually. In this embodiment, the preset attenuation coefficient is set to 0.05. In actual applications, as other implementation methods, implementers can also set it according to specific circumstances. This embodiment does not impose any special restrictions.

[0079] Additionally, when a node returns to online, the system can use a reverse model, that is... become , The weight of online time is gradually restored until it reaches the weight it had when it was offline, thus avoiding permanent penalties due to short-term offline time and balancing fault tolerance and incentives.

[0080] Thus, this embodiment uses dynamic weight adjustment to constrain nodes that are unstable online, have poor data quality, or contribute little to the network, thereby reducing their adverse impact on consensus and network status, effectively incentivizing nodes to improve their performance, and ensuring the security and data reliability of the rural blockchain network.

[0081] Step S4: Based on the weight of each node at the current moment, determine the consensus participation probability of each node at the current moment in order to select the master node. Based on the proportion of the weight of all nodes that submit transaction preparation information to the master node at the current moment in the total weight of all nodes in the blockchain, determine whether to trigger transaction submission or view switching.

[0082] Consensus participation probability refers to the probability that a node will be selected to participate in transaction verification, block generation, or master node election in a blockchain consensus mechanism. Essentially, it is a quantified allocation of a node's influence within the network. In rural blockchain scenarios, this probability is determined by the node's dynamic weight; nodes with higher weights have a greater probability of obtaining the right to record transactions or verify data, thus dominating key aspects of the consensus process. In this embodiment, the ratio of each node's weight at the current moment to the total weight of all nodes in the blockchain is used as the consensus participation probability of each node at the current moment.

[0083] Master node election is a core component of consensus mechanisms, coordinating node collaboration. Its core objective is to determine a unique transaction order and proposal initiator within a distributed network, preventing consensus chaos caused by parallel operations from multiple nodes. In a blockchain system, the master node is responsible for collecting transactions, generating block proposals, and distributing them to other nodes for verification. This role significantly improves consensus efficiency and reduces communication complexity. Especially in scenarios requiring rapid consensus, the master node reduces latency, avoids resource waste, and simplifies trust games among nodes through centralized coordination.

[0084] Traditional Byzantine Fault Tolerance (PBFT) algorithms typically employ a fixed-round master node election method. The drawback of this mechanism is that master node eligibility is unrelated to the actual capabilities of the nodes, which may lead to low-reliability or unstable nodes becoming master nodes, causing consensus delays or even forks. This is especially true in rural network environments, where the fixed-order election method is difficult to adapt to dynamically changing node states.

[0085] Therefore, this embodiment selects a master node based on the consensus participation probability of each node at the current moment. It then determines whether to trigger a transaction submission or view switching based on the proportion of the weights of all nodes submitting transaction preparation information to the master node at the current moment within the total weight of all nodes in the blockchain. This process is equivalent to performing node consensus verification. The specific consensus verification steps are as follows:

[0086] Preparatory phase: First, a master node is elected. In this embodiment, the node with the highest probability of consensus participation among all nodes in the blockchain at the current moment is selected as the master node in the blockchain at the current moment. Further, the master node generates a proposal containing transaction data, block hash, and current view number, and sends it to other nodes.

[0087] Preparation Phase: After receiving the proposal, other nodes verify the transfer conditions through smart contracts and query the ownership status across chains using the real estate registration system. The verification steps are based on publicly known technology, and the specific details will not be elaborated here. After successful verification, the node broadcasts a preparation message to the entire network, along with its own weighted signature, to prevent malicious nodes from forging consensus.

[0088] Submission Phase: If the weight of all nodes submitting transaction preparation information to the master node at the current moment accounts for a greater than a preset value in the total weight of all nodes in the blockchain, then the transaction submission is triggered. Upon submission, the smart contract automatically executes the transfer of ownership, updates the on-chain registration information, and triggers the synchronization of the real estate registration system.

[0089] It should be noted that the preset value is set manually, and in this embodiment, the preset value is 2 / 3.

[0090] It should be further explained that traditional methods require a prepared message from more than 2 / 3 of the nodes to be submitted, with all nodes having equal voting weight. This embodiment, however, uses a weighted calculation based on the dynamic weights of the nodes, requiring a total weight of more than 2 / 3 for submission. This gives the consensus opinions of highly trustworthy nodes higher decision-making weight, ensuring the rigidity of administrative supervision for core businesses such as rural property rights registration, while also preventing low-trustworthy nodes from dragging down consensus efficiency through weight differentiation. Furthermore, it avoids situations where consensus cannot be reached due to a small number of nodes.

[0091] Compared to traditional methods, this approach is more aligned with the top-down oversight and bottom-up participation governance structure in rural areas. It upgrades the fault tolerance capability in the submission phase from fault tolerance based on the number of nodes to fault tolerance based on weight and value, effectively improving consensus reliability in unstable network scenarios.

[0092] View Switching: If the master node fails to initiate a transaction proposal within a preset time period, or if more than a preset proportion of nodes report the master node as malicious, a view switching is triggered. A new master node is re-elected based on its current dynamic weight, prioritizing nodes that are online, stable, and have high data validity. During the switching process, the system automatically freezes disputed transactions until the new master node generates a checkpoint block containing historical weight records, ensuring consensus continuity and avoiding fork risks caused by node offline or malicious behavior.

[0093] It should be noted that the length of the preset time period and the preset ratio are both set manually. In this embodiment, the length of the preset time period is 30 seconds and the preset ratio is 1 / 3. In actual applications, as other implementation methods, implementers can also set them according to specific circumstances. This embodiment does not impose any special restrictions.

[0094] View switching is a well-known technology, and its specific principles and processes will not be elaborated here.

[0095] Thus, this embodiment, through a dynamic weighting mechanism, adjusts the weights of nodes based on their online stability, data validity, and network contribution, effectively constraining the participation of low-quality nodes, incentivizing high-quality nodes, and improving the efficiency and continuity of rural blockchain consensus.

[0096] It should be noted that the order of the embodiments described above is merely for descriptive purposes and does not represent the superiority or inferiority of the embodiments. Furthermore, specific embodiments of this specification have been described above. Additionally, the processes depicted in the accompanying drawings do not necessarily require a specific or sequential order to achieve the desired results. In some implementations, multitasking and parallel processing are possible or may be advantageous.

[0097] The various embodiments in this specification are described in a progressive manner. The same or similar parts between the various embodiments can be referred to each other. Each embodiment focuses on describing the differences from other embodiments.

[0098] The above-described embodiments are only used to illustrate the technical solutions of this application, and are not intended to limit them; modifications to the technical solutions described in the foregoing embodiments, or equivalent substitutions of some of the technical features, do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of the embodiments of this application, and should all be included within the protection scope of this application.

Claims

1. A method for sharing secure information on rural digital property rights based on a blockchain consensus mechanism, characterized in that: The method includes the following steps: In the blockchain of rural digital property rights scenarios, the online stability of each node at each moment is determined by analyzing the proportion of the online time of each node within the preset time period before each moment. Obtain the total number of data submitted by each node before each time point, the total number of data that passed verification, and the dispute resolution time caused by each data error. By analyzing the proportion of the total number of data that passed verification to the total number of data submitted under each node, and the proportion of the dispute resolution time caused by each data error to the total number of data submitted, determine the data validity of each node at each time point. By analyzing the difference between the distance of each node to the nearest edge server and the distance distribution among all nodes in the blockchain, the distance weight of each node is determined. The number of consensus participations and the number of correct consensuses of each node before each time point are counted to determine the network contribution of each node at each time point. The basic credibility of each node is obtained, and combined with the online stability, data validity and network contribution of each node at each time point, the weight of each node at each time point is determined. Based on the weight of each node at the current moment, the consensus participation probability of each node at the current moment is determined to select the master node. Based on the proportion of the weight of all nodes that submit transaction preparation information to the master node at the current moment in the total weight of all nodes in the blockchain, it is determined whether to trigger transaction submission or view switching.

2. The method for sharing rural digital property rights security information based on blockchain consensus mechanism as described in claim 1, characterized in that, The expression for the online stability of each node at each time point is: In the formula, , Let i represent the online stability of node i at time t and time t-1, respectively. hour, ; , These represent the online duration of node i at time t and the length of the preset duration, respectively. This indicates the preset weighting coefficient.

3. The method for sharing rural digital property rights security information based on blockchain consensus mechanism as described in claim 1, characterized in that, The expression for the data validity of each node at each time point is: In the formula, This indicates the validity of the data at node i at time t; , These represent the total number of data entries verified and the total number of data entries submitted by node i before time t, respectively. This indicates the duration of dispute resolution caused by the nth data error at node i before time t; This represents the total number of data errors at node i before time t; This indicates the preset penalty coefficient.

4. The method for sharing rural digital property rights security information based on blockchain consensus mechanism as described in claim 1, characterized in that, The distance weight of each node is the ratio of the distance from each node to the nearest edge server to the average distance between all nodes in the blockchain.

5. The method for sharing secure information on rural digital property rights based on a blockchain consensus mechanism as described in claim 1, characterized in that, The expression for the network contribution of each node at each time point is: In the formula, This represents the network contribution of node i at time t. , Let represent the total number of consensus participations and the number of correct consensuses before time t, respectively; The distance weight of node i is represented; This represents the distance from node i to the nearest edge server before time t; This indicates the preset distance factor.

6. The method for sharing rural digital property rights security information based on blockchain consensus mechanism as described in claim 1, characterized in that, The process of obtaining the basic trustworthiness of each node includes: In the blockchain of rural digital property rights scenario, all nodes include three categories: government nodes, village committee nodes, and farmer nodes. The basic trust level of all government nodes is set to a preset first value, the basic trust level of all village committee nodes is set to a preset second value, and the basic trust level of all farmer nodes is set to a preset third value. The preset first value is greater than the preset third value, and the preset second value is between the preset first value and the preset third value.

7. The method for sharing rural digital property rights security information based on blockchain consensus mechanism as described in claim 1, characterized in that, The method for determining the weight of each node at each time point is as follows: The online stability, data validity, network contribution, and basic credibility of each node at each time point are positively integrated and denoted as the weighted feature value of each node at each time point. If node m is an offline node, then the weight of node m The expression is: In the formula, This represents the weighted feature value when node m is offline; This represents the offline time of node m; This indicates the preset attenuation coefficient; exp() represents an exponential function with the natural constant as the base. If node m is not an offline node, then the weight of node m at each time step is the weight feature value of node m at each time step. By traversing all nodes, the weight of each node at each time step can be obtained.

8. The method for sharing rural digital property rights security information based on blockchain consensus mechanism as described in claim 1, characterized in that, The consensus participation probability of each node at the current moment is the ratio of the weight of each node at the current moment to the total weight of all nodes in the blockchain.

9. The method for sharing rural digital property rights security information based on blockchain consensus mechanism as described in claim 1, characterized in that, The master node is the node with the highest probability of participating in consensus among all nodes in the blockchain at the current moment.

10. The method for sharing rural digital property rights security information based on blockchain consensus mechanism as described in claim 1, characterized in that, The process of determining whether to trigger a transaction submission or view switch includes: If the weight of all nodes that submit transaction preparation information to the master node at the current moment accounts for a greater than a preset value in the total weight of all nodes in the blockchain, then the transaction submission is triggered. If the current master node fails to initiate a transaction proposal within a preset time period or if more than a preset proportion of nodes report the master node as malicious, a view switch will be triggered.

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