Power grid data governance method and device based on blockchain database platform, and computer device

Abstract

The application relates to a power grid data management method and device based on a blockchain database platform and a computer device. When it is necessary to perform node election, initial reputation values of multiple blockchain nodes are obtained; the reputation values are sorted based on the initial reputation values to determine consensus nodes and supervision nodes; the supervision nodes access message copies received by local logs of the consensus nodes and message copies previously received by the supervision nodes from the consensus nodes for comparison; when there are multiple trusted consensus nodes, the highest-scored consensus node is determined as an execution node based on J=b*C*[a*(1 / T)], wherein T is a waiting time corresponding to a random number of the consensus node, C is a reputation value corresponding to the consensus node, b is a reputation value influence factor coefficient, a is a waiting time influence factor coefficient, and J is a score. Under the premise of ensuring overall safety, the communication complexity of the consensus process is reduced, the consensus effectiveness is improved, and the collaborative management of multiple roles under large power grid data is facilitated.

Description

Technical Field

[0001] This application relates to the field of blockchain technology, and in particular to a method, apparatus, and computer equipment for power grid data governance based on a blockchain database platform. Background Technology

[0002] With the continuous advancement of power grid informatization, various asset management systems have been completed and put into use. However, as the application of these systems deepens, data quality issues are becoming increasingly prominent, including problems related to data integrity, standardization, consistency, and accuracy, posing challenges to the safe, stable operation and efficient management of the power grid.

[0003] To address this challenge, the power grid has introduced blockchain technology to store data on the blockchain, but there is still room for improvement in data governance. Summary of the Invention

[0004] Therefore, it is necessary to provide a power grid data governance method, device, and computer equipment based on a blockchain database platform that is conducive to collaborative management of multiple roles under the large data volume of the power grid, in order to address the above-mentioned technical problems.

[0005] Firstly, this application provides a power grid data governance method based on a blockchain database platform, the method comprising:

[0006] When it is necessary to conduct node election, determine the initial reputation values ​​of multiple blockchain nodes involved in the blockchain database platform;

[0007] The consensus nodes and supervisory nodes are determined by ranking the initial reputation values. The consensus nodes are the top K blockchain nodes with the highest reputation values, and the supervisory nodes are the blockchain nodes with the most support votes among all non-consensus nodes.

[0008] Each consensus node generates a random number and writes the message containing the random number to its local log. It also copies the message to obtain a message copy and broadcasts the message copy to the supervisory node.

[0009] The supervisory node accesses the local logs of each consensus node and compares the received message copy with the locally stored message copy;

[0010] If message replicas from multiple consensus nodes are found to be consistent, the consensus node with the highest score is determined as the execution node based on the following scoring model:

[0011] J = b * C * [a * (1 / T)]

[0012] Where T is the waiting time corresponding to the random number of the consensus node, C is the reputation value corresponding to the consensus node, b is the influence factor coefficient of the reputation value, a is the influence factor coefficient of the waiting time, and J is the score.

[0013] In one embodiment, determining the initial reputation values ​​of multiple blockchain nodes involved in the blockchain database platform includes:

[0014] Obtain the historical behavior of each blockchain node, including the number of times it participated in consensus, the proportion of correct blocks submitted, and the number of complaints received.

[0015] The initial reputation value of a blockchain node is determined based on its historical behavior.

[0016] In one embodiment, after the step of the supervisory node accessing the local logs of each consensus node and comparing the received message copy with the locally stored message copy, the method further includes:

[0017] If the comparison results are inconsistent, the consensus node is determined to be a malicious node and added to the malicious node set.

[0018] In one embodiment, the steps for determining the scoring model include:

[0019] Establish initial scoring models corresponding to the influence factor coefficients of different reputation values ​​and different waiting times;

[0020] Based on each initial scoring model, the execution node is determined;

[0021] Based on the determined execution nodes, power grid asset data is tested to obtain performance test scores.

[0022] Based on the performance test scores, the initial scoring model with the highest performance test score is selected as the scoring model.

[0023] In one embodiment, the steps for determining the performance test score include:

[0024] Acquire historical power grid asset data and store the historical power grid asset data on the blockchain based on different initial scoring models;

[0025] Simulate data tampering attacks and determine and record the data integrity and confidentiality under different initial scoring models when facing attacks;

[0026] The performance test score is determined based on data integrity and confidentiality. The initial value of the performance test score is 100. One point is deducted for each incomplete data entry and one point is deducted for each data leak.

[0027] Secondly, a power grid data governance device based on a blockchain database platform is provided, the device comprising:

[0028] The initial reputation value determination module is used to determine the initial reputation values ​​of multiple blockchain nodes involved in the blockchain database platform when it is necessary to conduct execution node election;

[0029] The consensus node and supervisory node determination module is used to sort the reputation values ​​based on the initial reputation value and determine the consensus nodes and supervisory nodes. The consensus nodes are the top K blockchain nodes with the highest reputation values, and the supervisory nodes are the blockchain nodes with the largest number of support votes among all non-consensus nodes.

[0030] The message copy sending module is used by each consensus node to generate random numbers, write messages including random numbers to local logs, copy messages to obtain message copies, and broadcast message copies to supervisory nodes;

[0031] The message replica comparison module is used to access the local logs of each consensus node based on the supervisory node, and compare the received message replicas with the locally stored message replicas;

[0032] The execution node determination module is used to determine the consensus node with the highest score as the execution node when message replicas from multiple consensus nodes are consistent, based on the following scoring model:

[0033] J = b * C * [a * (1 / T)]

[0034] Where T is the waiting time corresponding to the random number of the consensus node, C is the reputation value corresponding to the consensus node, b is the influence factor coefficient of the reputation value, a is the influence factor coefficient of the waiting time, and J is the score.

[0035] In one embodiment, the initial reputation value determination module includes:

[0036] The historical behavior data acquisition unit is used to acquire the historical behavior of each blockchain node. The historical behavior includes the number of times it participated in consensus, the proportion of correct blocks submitted, and the number of complaints received.

[0037] The initial reputation value determination unit is used to determine the initial reputation value of a blockchain node based on its historical behavior.

[0038] In one embodiment, the above-mentioned apparatus further includes:

[0039] The malicious node recording module is used to identify the consensus node as a malicious node and add it to the malicious node set when the comparison results are inconsistent.

[0040] In one embodiment, the above-mentioned apparatus further includes:

[0041] The initial scoring model building module is used to build initial scoring models corresponding to the influence factor coefficients of different reputation values ​​and different waiting times;

[0042] The initial scoring model execution module is used to determine the execution nodes based on each initial scoring model;

[0043] The scoring module is used to test power grid asset data based on a defined execution node and obtain performance test scoring results.

[0044] The scoring model determination module is used to determine the initial scoring model with the highest performance test score as the scoring model based on the performance test scoring results.

[0045] Thirdly, a computer device is provided, including a memory and a processor, wherein the memory stores a computer program, and the processor executes the computer program to implement the steps of the above-described method.

[0046] The above-mentioned power grid data governance method, apparatus, and computer equipment are based on a blockchain database platform. The method involves determining the initial reputation values ​​of multiple blockchain nodes involved in the blockchain database platform when an execution node election is required; then, based on the initial reputation values, ranking the reputation values ​​to determine consensus nodes and supervisory nodes. The consensus nodes are the top K blockchain nodes with the highest reputation values, and the supervisory nodes are the blockchain nodes with the largest number of support votes among all non-consensus nodes. Next, the supervisory node compares the message copies received from the local logs of each consensus node with the message copies it previously received from the consensus nodes. If multiple consensus nodes have identical message copies, the consensus node with the highest score is determined as the execution node based on the following scoring model: J = b * C * [a * (1 / T)], where T is the waiting time corresponding to the random number of the consensus node, C is the reputation value of the consensus node, b is the influence factor coefficient of the reputation value, a is the influence factor coefficient of the waiting time, and J is the score. By adding supervisory nodes, improving the selection method for execution nodes, and building a trust model for nodes, the communication complexity of the consensus process is reduced and the effectiveness of consensus is improved while ensuring overall security. This is beneficial for the collaborative management of multiple roles under the large data volume of the power grid. Attached Figure Description

[0047] To more clearly illustrate the technical solutions in the embodiments of this application or related technologies, the drawings used in the description of the embodiments of this application or related technologies will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other related drawings can be obtained based on these drawings without creative effort.

[0048] Figure 1 This is a flowchart illustrating a power grid data governance method based on a blockchain database platform in one embodiment.

[0049] Figure 2 This is a flowchart illustrating the steps involved in determining the initial reputation values ​​of multiple blockchain nodes in a blockchain database platform, as shown in one embodiment.

[0050] Figure 3 This is a flowchart illustrating the steps for determining the scoring model in one embodiment;

[0051] Figure 4 This is a flowchart illustrating the steps for determining performance test scores in one embodiment.

[0052] Figure 5 This is a structural block diagram of a power grid data governance device based on a blockchain database platform in one embodiment;

[0053] Figure 6 This is an internal structural diagram of a computer device in one embodiment. Detailed Implementation

[0054] To make the objectives, technical solutions, and advantages of this application clearer, the following detailed description is provided in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative and not intended to limit the scope of this application.

[0055] The blockchain database platform integrates the high throughput, low latency, and high scalability of traditional database technologies with the non-repudiation and immutability of blockchain technology. It provides a novel, secure, distributed, multi-active database system for data governance platforms, enabling them to achieve distributed, trusted storage, tamper-proof protection, and reliable traceability in IT asset data management. The method provided in this application embodiment is applied to the blockchain database platform.

[0056] In one exemplary embodiment, such as Figure 1 As shown, this application provides a first aspect: a power grid data governance method based on a blockchain database platform, the method comprising:

[0057] S101, When it is necessary to conduct an execution node election, determine the initial reputation values ​​of multiple blockchain nodes involved in the blockchain database platform. Situations requiring execution node election may include, but are not limited to, blockchain network startup, updates, or adjustments to node configurations. For example, if blockchain nodes are added or deleted, it is necessary to re-determine trusted execution nodes to ensure the secure operation of the blockchain network after node configuration.

[0058] S102: Based on the initial reputation value, the consensus nodes and supervisory nodes are determined by ranking the reputation values. The consensus nodes are the top K blockchain nodes with the highest reputation values, and the supervisory nodes are the blockchain nodes with the most support votes among all non-consensus nodes. Here, K is a value less than the total number of blockchain nodes. A smaller K value results in a more trustworthy execution node, requires fewer consensus nodes to be verified, and leads to a faster election process. However, if K is set too small, step S105 may fail, meaning there are no consensus nodes with consistent message replicas. Therefore, K can be dynamic. Initially, K is set to a relatively small value. If, based on a small K, steps S103-S105 fail to show consistent message replicas, K is increased, and step S103 is re-entered until multiple consensus nodes show consistent message replicas. A small initial K value, coupled with dynamic adjustment, balances the trustworthiness of the execution node with the election speed.

[0059] In step S103, each consensus node generates a random number and writes a message including the random number to its local log. It also copies the message to obtain a message copy and broadcasts the copy to the supervisory node. A vote is then held by non-consensus nodes (excluding the consensus nodes), and the blockchain node with the most votes is selected as the supervisory node to verify the consensus nodes.

[0060] S104, the supervisory node accesses the local logs of each consensus node and compares the received message copy with the locally stored message copy.

[0061] Supervisory nodes can access the local logs of each consensus node to obtain a copy of the message stored locally by the consensus node. They then compare this copy with the supervisory node's previous broadcasts of messages received from the consensus node. If they match, the consensus node is considered trustworthy; otherwise, it is considered untrustworthy and can be identified as a malicious node.

[0062] S105, if multiple consensus nodes have identical message replicas, the consensus node with the highest score is determined as the execution node based on the following scoring model:

[0063] J = b * C * [a * (1 / T)]

[0064] Where T is the waiting time corresponding to the random number of the consensus node, C is the reputation value corresponding to the consensus node, b is the influence factor coefficient of the reputation value, a is the influence factor coefficient of the waiting time, and J is the score.

[0065] Here, T represents the waiting time corresponding to the random number assigned or generated to a consensus node before or during the consensus process. A longer waiting time means that the node is more patient in the system or less susceptible to network attacks (such as denial-of-service attacks). The waiting time influence factor coefficient 'a' is used to adjust the weight of waiting time in the scoring model. The value of 'a' can be adjusted according to specific needs. A larger value of 'a' means that the waiting time has a greater impact on the score. In this case, the scoring model tends to select nodes with shorter waiting times to improve efficiency. The value of 'b' can also be adjusted according to specific needs. A larger value of 'b' means that the reputation value has a greater impact on the score. In this case, the scoring model tends to select nodes with higher reputation values ​​to improve security. The settings of 'a' and 'b' can be based on considerations of both efficiency and security in specific power grid asset data management scenarios.

[0066] Among the consensus nodes that match multiple message replicas, the consensus node with the highest score is selected as the execution node. The node's waiting time and reputation value are taken into account and adjusted by the influence factor coefficient to ensure that the selected execution node is both efficient and reliable, which helps to improve the overall performance and security of the blockchain network.

[0067] Specifically, when an execution node election is required, the initial reputation values ​​of multiple blockchain nodes involved in the blockchain database platform are determined. Then, based on these initial reputation values, the consensus nodes and supervisory nodes are determined by ranking the reputation values. The consensus nodes are the top K blockchain nodes with the highest reputation values, and the supervisory nodes are the blockchain nodes with the most support votes among all non-consensus nodes. Next, the message copies received by the supervisory nodes from the local logs of each consensus node are compared with the message copies previously received from the consensus nodes. If multiple consensus nodes have identical message copies, the consensus node with the highest score is determined as the execution node based on the following scoring model: J = b * C * [a * (1 / T)], where T is the waiting time corresponding to the random number of the consensus node, C is the reputation value of the consensus node, b is the influence factor coefficient of the reputation value, a is the influence factor coefficient of the waiting time, and J is the score. By adding supervisory nodes, improving the execution node selection method, and constructing a node trust model, the communication complexity of the consensus process is reduced and the effectiveness of consensus is improved while ensuring overall security. This is beneficial for the collaborative management of multiple roles under the large data volume of the power grid.

[0068] In one embodiment, after step S104, the above method further includes:

[0069] If there is a matching message copy of one consensus node or no matching message copy of any consensus node, then increase K and proceed to step S102.

[0070] If only one consensus node's message copy matches or no consensus node's message copy matches, it indicates that there are too few or no trusted nodes at this time, and the security and trustworthiness of the execution node cannot be guaranteed. Based on this, by increasing the value of K, more consensus nodes are generated, and a second election is conducted.

[0071] In one embodiment, such as Figure 2 As shown, the initial reputation values ​​of multiple blockchain nodes involved in the blockchain database platform are determined, including:

[0072] S201, obtain the historical behavior of each blockchain node, including the number of times it participated in consensus, the proportion of correct blocks submitted, and the number of complaints received.

[0073] S202, Determine the initial reputation value of the blockchain node based on its historical behavior.

[0074] The number of times a node participates in consensus reflects its activity and participation in the blockchain network. Nodes that are active and frequently participate in consensus are more likely to be responsible and more likely to maintain the stability of the system. Therefore, the more times a node participates in consensus, the higher its initial reputation value.

[0075] The proportion of correct blocks submitted directly reflects the quality of a node's work and its integrity. A high proportion of correct blocks means that the node has strong and reliable capabilities in data processing and verification. Therefore, the higher the proportion of correct blocks submitted, the higher the initial reputation value.

[0076] The number of complaints refers to the number of times each node is complained about by other nodes or administrators for improper behavior (such as submitting incorrect data, refusing to participate in consensus, or attempting double-spending attacks). Nodes with a high number of complaints may exhibit malicious behavior or instability, and their reputation score should be lowered accordingly. In other words, the more complaints a node receives, the lower its initial reputation score.

[0077] This data can be obtained through the blockchain network's own logs, monitoring tools, or dedicated reputation management systems.

[0078] Specifically, a reputation score is calculated by weighting and summing the historical behavior data of each node. For example, the number of times a node participates in consensus can be multiplied by a positive weight, the proportion of correctly submitted blocks can be multiplied by a higher positive weight, and the number of complaints can be multiplied by a negative weight. Based on the calculated reputation score, each node is assigned an initial reputation value. The initial reputation value can be a specific numerical value (such as an integer or floating-point number between 0 and 100) or a rating (such as A, B, C, etc.).

[0079] Optionally, the reputation value can be dynamically adjusted as node behavior changes; that is, the above method also includes:

[0080] The reputation value of a blockchain node is adjusted based on its current behavior (including the number of times it participates in consensus, the proportion of correct block submissions, and the number of complaints received) to reflect the node's current state and reliability.

[0081] In one embodiment, after the step of the supervisory node accessing the local logs of each consensus node and comparing the received message copy with the locally stored message copy, the method further includes:

[0082] If the comparison results are inconsistent, the consensus node is determined to be a malicious node and added to the malicious node set.

[0083] By adding malicious nodes to the malicious node set, it is possible to effectively prevent them from continuing to participate in the consensus process, thereby reducing the risk of power grid asset data in the blockchain network being maliciously destroyed or tampered with. This allows the blockchain network to rely on more honest and reliable nodes to complete the consensus, thereby improving the overall stability and reliability of the power grid asset data management process.

[0084] Furthermore, adding malicious nodes to the malicious node set makes it easier for system administrators or smart contracts to take further action against these nodes, such as restricting their access permissions or permanently removing them from the system. This centralized management approach improves processing efficiency and accuracy.

[0085] In one embodiment, such as Figure 3 As shown, the steps for determining the scoring model include:

[0086] S301, establish the initial scoring model corresponding to the influence factor coefficients of different reputation values ​​and different waiting times.

[0087] Each model includes two main influencing factors: the node's reputation score and the node's waiting time. These two factors are represented by different coefficients, reflecting their respective importance in the corresponding scoring model. By adjusting these coefficients, multiple different scoring models can be generated.

[0088] S302, determine the execution node based on each initial scoring model. For each initial scoring model, executing steps S101 to S105 above will result in a corresponding execution node being selected.

[0089] S303, based on a defined execution node, performs tests on power grid asset data and obtains performance test scores.

[0090] S304. Based on the performance test scoring results, determine the initial scoring model with the highest performance test score as the scoring model.

[0091] With the operation of the blockchain-based database platform and the accumulation of data such as power grid asset data and logs, the scoring model can be re-evaluated and adjusted regularly to adapt to new environments and needs.

[0092] Through the above steps, the blockchain database platform can more effectively elect execution nodes that balance reputation and security, improve the efficiency and quality of power grid asset data processing, and thus optimize the performance and stability of the entire blockchain database platform.

[0093] In one embodiment, the steps for determining the performance test score are as follows: Figure 4 As shown, it includes:

[0094] S401: Acquire historical power grid asset data and store it on the blockchain based on different initial scoring models. Historical power grid asset data may include operating records, maintenance histories, and fault reports of power grid equipment. This historical power grid asset data will be stored on the blockchain. Before storage, the historical power grid asset data may need to be preprocessed, such as data cleaning, formatting, and encryption, to ensure data consistency and security.

[0095] Optionally, a separate blockchain network or on-chain partition can be configured for each initial scoring model for subsequent analysis and comparison.

[0096] S402 simulates data tampering attacks and determines and records the data integrity and confidentiality under different initial scoring models when facing an attack.

[0097] Simulated data tampering attacks are conducted on each blockchain network based on a different initial scoring model. These attacks may include attempting to modify data blocks on the blockchain, forging transaction records, or bypassing verification mechanisms. The data integrity and confidentiality demonstrated by the different initial scoring models under each attack scenario are recorded and evaluated. Optionally, logging, monitoring tools, and alerting systems can be used to track the attack process and record key events and data changes.

[0098] S403. Based on data integrity and confidentiality, determine the performance test score. The initial value of the performance test score is 100. One point is deducted for each incomplete data entry and one point is deducted for each data leak.

[0099] Based on the data integrity and confidentiality recorded in step S402, a performance test score is calculated for each initial scoring model. The initial score is set at 100 points. One point is deducted from the total score for each incomplete data point or data breach discovered. This method allows for a direct comparison of the performance of different scoring models in protecting the security of power grid asset data. The initial scoring model with the highest score is used as the scoring model for electing the execution node, ensuring the overall security of the blockchain database platform during the power grid asset data governance process.

[0100] It should be understood that although the steps in the flowcharts of the embodiments described above are shown sequentially according to the arrows, these steps are not necessarily executed in the order indicated by the arrows. Unless explicitly stated herein, there is no strict order restriction on the execution of these steps, and they can be executed in other orders. Moreover, at least some steps in the flowcharts of the embodiments described above may include multiple steps or multiple stages. These steps or stages are not necessarily completed at the same time, but can be executed at different times. The execution order of these steps or stages is not necessarily sequential, but can be performed alternately or in turn with other steps or at least some of the steps or stages of other steps.

[0101] Based on the same inventive concept, this application also provides a power grid data governance device based on a blockchain database platform for implementing the aforementioned power grid data governance method based on a blockchain database platform. The solution provided by this device is similar to the implementation scheme described in the above method. Therefore, the specific limitations of one or more embodiments of the power grid data governance device based on a blockchain database platform provided below can be found in the limitations of the power grid data governance method based on a blockchain database platform described above, and will not be repeated here.

[0102] In one exemplary embodiment, such as Figure 5 As shown, a power grid data governance device based on a blockchain database platform is provided. The device includes: an initial reputation value determination module 501, a consensus node and supervisory node determination module 502, a message replica sending module 503, a message replica comparison module 504, and an execution node determination module 505. Wherein:

[0103] The initial reputation value determination module is used to determine the initial reputation values ​​of multiple blockchain nodes involved in the blockchain database platform when it is necessary to conduct execution node election;

[0104] The consensus node and supervisory node determination module is used to sort the reputation values ​​based on the initial reputation value and determine the consensus nodes and supervisory nodes. The consensus nodes are the top K blockchain nodes with the highest reputation values, and the supervisory nodes are the blockchain nodes with the largest number of support votes among all non-consensus nodes.

[0105] The message copy sending module is used by each consensus node to generate random numbers, write messages including random numbers to local logs, copy messages to obtain message copies, and broadcast message copies to supervisory nodes;

[0106] The message replica comparison module is used to access the local logs of each consensus node based on the supervisory node, and compare the received message replicas with the locally stored message replicas;

[0107] The execution node determination module is used to determine the consensus node with the highest score as the execution node when message replicas from multiple consensus nodes are consistent, based on the following scoring model:

[0108] J = b * C * [a * (1 / T)]

[0109] Where T is the waiting time corresponding to the random number of the consensus node, C is the reputation value corresponding to the consensus node, b is the influence factor coefficient of the reputation value, a is the influence factor coefficient of the waiting time, and J is the score.

[0110] In one embodiment, the initial reputation value determination module includes:

[0111] The historical behavior data acquisition unit is used to acquire the historical behavior of each blockchain node. The historical behavior includes the number of times it participated in consensus, the proportion of correct blocks submitted, and the number of complaints received.

[0112] The initial reputation value determination unit is used to determine the initial reputation value of a blockchain node based on its historical behavior.

[0113] In one embodiment, the above-mentioned apparatus further includes:

[0114] The malicious node recording module is used to identify the consensus node as a malicious node and add it to the malicious node set when the comparison results are inconsistent.

[0115] In one embodiment, the above-mentioned apparatus further includes:

[0116] The initial scoring model building module is used to build initial scoring models corresponding to the influence factor coefficients of different reputation values ​​and different waiting times;

[0117] The initial scoring model execution module is used to determine the execution nodes based on each initial scoring model;

[0118] The scoring module is used to test power grid asset data based on a defined execution node and obtain performance test scoring results.

[0119] The scoring model determination module is used to determine the initial scoring model with the highest performance test score as the scoring model based on the performance test scoring results. Each module in the aforementioned power grid data governance device based on the blockchain database platform can be implemented entirely or partially through software, hardware, or a combination thereof. These modules can be embedded in or independent of the processor in a computer device in hardware form, or stored in the memory of a computer device in software form, so that the processor can call and execute the corresponding operations of each module.

[0120] In one exemplary embodiment, a computer device is provided, which may be a server, and its internal structure diagram may be as follows: Figure 6 As shown, the computer device includes a processor, memory, input / output (I / O) interfaces, and a communication interface. The processor, memory, and I / O interfaces are connected via a system bus, and the communication interface is also connected to the system bus via the I / O interfaces. The processor provides computational and control capabilities. The memory includes non-volatile storage media and internal memory. The non-volatile storage media stores the operating system, computer programs, and a database. The internal memory provides the environment for the operating system and computer programs stored in the non-volatile storage media. The database stores data such as scoring models. The I / O interfaces are used for exchanging information between the processor and external devices. The communication interface is used for communicating with external terminals via a network. When the computer program is executed by the processor, it implements a power grid data governance method based on a blockchain database platform.

[0121] Those skilled in the art will understand that Figure 6 The structure shown is merely a block diagram of a portion of the structure related to the present application and does not constitute a limitation on the computer device to which the present application is applied. Specific computer devices may include more or fewer components than those shown in the figure, or combine certain components, or have different component arrangements.

[0122] In one exemplary embodiment, a computer device is provided, including a memory and a processor, wherein the memory stores a computer program, and the processor executes the computer program to implement the above-described steps of power grid data governance based on a blockchain database platform.

[0123] In one embodiment, a computer-readable storage medium is provided having a computer program stored thereon, which, when executed by a processor, implements the above-described steps of power grid data governance based on a blockchain database platform.

[0124] In one embodiment, a computer program product is provided, including a computer program that, when executed by a processor, implements the above-described steps of power grid data governance based on a blockchain database platform.

[0125] Those skilled in the art will understand that all or part of the processes in the methods of the above embodiments can be implemented by a computer program instructing related hardware. The computer program can be stored in a non-volatile computer-readable storage medium, and when executed, it can include the processes of the embodiments of the above methods. Any references to memory, databases, or other media used in the embodiments provided in this application can include at least one of non-volatile memory and volatile memory. Non-volatile memory can include read-only memory (ROM), magnetic tape, floppy disk, flash memory, optical memory, high-density embedded non-volatile memory, resistive random access memory (ReRAM), magnetic random access memory (MRAM), ferroelectric random access memory (FRAM), phase change memory (PCM), graphene memory, etc. Volatile memory can include random access memory (RAM) or external cache memory, etc. By way of illustration and not limitation, RAM can take many forms, such as Static Random Access Memory (SRAM) or Dynamic Random Access Memory (DRAM). The databases involved in the embodiments provided in this application may include at least one type of relational database and non-relational database. Non-relational databases may include, but are not limited to, blockchain-based distributed databases. The processors involved in the embodiments provided in this application may be general-purpose processors, central processing units, graphics processing units, digital signal processors, programmable logic devices, quantum computing-based data processing logic devices, artificial intelligence (AI) processors, etc., and are not limited to these.

[0126] The technical features of the above embodiments can be combined in any way. For the sake of brevity, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this application.

[0127] The embodiments described above are merely illustrative of several implementation methods of this application, and while the descriptions are specific and detailed, they should not be construed as limiting the scope of this patent application. It should be noted that those skilled in the art can make various modifications and improvements without departing from the concept of this application, and these all fall within the protection scope of this application. Therefore, the protection scope of this application should be determined by the appended claims.

Claims

1. A power grid data governance method based on a blockchain database platform, characterized in that, The method includes: When it is necessary to conduct node election, determine the initial reputation values ​​of multiple blockchain nodes involved in the blockchain database platform; Based on the initial reputation value, the reputation values ​​are sorted to determine the consensus nodes and supervisory nodes. The consensus nodes are the top K blockchain nodes with the highest reputation values, and the supervisory nodes are the blockchain nodes with the largest number of support votes among all non-consensus nodes. Each consensus node generates a random number, writes a message including the random number into its local log, copies the message to obtain a message copy, and broadcasts the message copy to the supervisory node. The supervisory node accesses the local logs of each consensus node and compares the received message copy with the locally stored message copy. If message replicas from multiple consensus nodes are found to be consistent, the consensus node with the highest score is determined as the execution node based on the following scoring model: J = b * C * [a * (1 / T)] Where T is the waiting time corresponding to the random number of the consensus node, C is the reputation value corresponding to the consensus node, b is the influence factor coefficient of the reputation value, a is the influence factor coefficient of the waiting time, and J is the score; The determination of the initial reputation values ​​of multiple blockchain nodes involved in the blockchain database platform includes: Obtain the historical behavior of each blockchain node, including the number of times it participated in consensus, the proportion of correct blocks submitted, and the number of complaints received; The initial reputation value of the blockchain node is determined based on its historical behavior. The steps for determining the scoring model include: Establish initial scoring models corresponding to the influence factor coefficients of different reputation values ​​and different waiting times; The execution node is determined based on each initial scoring model; Based on the determined execution nodes, power grid asset data is tested to obtain performance test scores. Based on the performance test scores, the initial scoring model with the highest performance test score is determined as the scoring model.

2. The method according to claim 1, characterized in that, After the step of the supervisory node accessing the local logs of each consensus node and comparing the received message copy with the locally stored message copy, the method further includes: If the comparison results are inconsistent, the consensus node is determined to be a malicious node and added to the malicious node set.

3. The method according to claim 1, characterized in that, The steps for determining the performance test score include: Historical power grid asset data is acquired and stored on the blockchain based on different initial scoring models. Simulate data tampering attacks and determine and record the data integrity and confidentiality under different initial scoring models in the face of the attacks; The performance test score is determined based on data integrity and confidentiality. The initial value of the performance test score is 100. One point is deducted for each incomplete data entry and one point is deducted for each data leak.

4. A power grid data governance device based on a blockchain database platform, characterized in that, The device includes: The initial reputation value determination module is used to determine the initial reputation values ​​of multiple blockchain nodes involved in the blockchain database platform when it is necessary to conduct execution node election; The consensus node and supervisory node determination module is used to sort the reputation values ​​based on the initial reputation value and determine the consensus nodes and supervisory nodes, wherein the consensus nodes are the top K blockchain nodes with the highest reputation values, and the supervisory nodes are the blockchain nodes with the largest number of support votes among all non-consensus nodes; The message copy sending module is used to generate random numbers for each consensus node, write messages including the random numbers into local logs, copy the messages to obtain message copies, and broadcast the message copies to the supervisory nodes. The message replica comparison module is used to access the local logs of each consensus node based on the supervisory node, and compare the received message replicas with the locally stored message replicas; The execution node determination module is used to determine the consensus node with the highest score as the execution node when message replicas from multiple consensus nodes are consistent, based on the following scoring model: J = b * C * [a * (1 / T)] Where T is the waiting time corresponding to the random number of the consensus node, C is the reputation value corresponding to the consensus node, b is the influence factor coefficient of the reputation value, a is the influence factor coefficient of the waiting time, and J is the score; The initial reputation value determination module includes: The historical behavior data acquisition unit is used to acquire the historical behavior of each blockchain node, including the number of times it participated in consensus, the proportion of correct blocks submitted, and the number of complaints received. An initial reputation value determination unit is used to determine the initial reputation value of the blockchain node based on the historical behavior of the blockchain node. The power grid data governance device based on the blockchain database platform also includes: The initial scoring model building module is used to build initial scoring models corresponding to the influence factor coefficients of different reputation values ​​and different waiting times; The initial scoring model execution module is used to determine the execution node based on each initial scoring model; The scoring module is used to test power grid asset data based on a defined execution node and obtain performance test scoring results. The scoring model determination module is used to determine the initial scoring model with the highest performance test score as the scoring model based on the performance test scoring results.

5. The apparatus according to claim 4, characterized in that, The device further includes: The malicious node recording module is used to determine that the consensus node is a malicious node and add it to the malicious node set when the comparison results are inconsistent.

6. A computer device comprising a memory and a processor, wherein the memory stores a computer program, characterized in that, When the processor executes the computer program, it implements the steps of the method according to any one of claims 1 to 3.

Images