A blockchain-based data asset right confirmation method and system

Abstract

The application discloses a kind of data asset right confirmation method and system based on blockchain, it is related to data asset right confirmation management technical field.The data asset right confirmation method based on blockchain includes the following steps: malicious request interference monitoring;Time consumption and resource consumption processing determination;Right confirmation security verification.The present application determines and generates determination result by carrying out malicious request interference influence determination, and judges whether to carry out malicious request interference influence evaluation based on determination result, if carrying out malicious request interference influence evaluation, then after malicious request interference influence evaluation is ended, consensus efficiency verification analysis is carried out, otherwise directly send malicious request interference qualified prompt to preset management center, after consensus efficiency verification analysis is ended, right confirmation record security verification is carried out, reach the effect of improving the record security and timeliness of right confirmation result, solve the technical problems that the record security of right confirmation result is low in prior art, and the timeliness is poor.

Description

Technical Field

[0001] This invention relates to the field of data asset ownership confirmation and management technology, and in particular to a data asset ownership confirmation method and system based on blockchain. Background Technology

[0002] To ensure the security of data assets, data asset ownership confirmation is typically used to prevent data loss, protect the security of data asset owners, and reduce the risk of data asset loss or misappropriation. Existing methods first package the metadata of the data asset (such as hash value, creator, timestamp, ownership statement, etc.) into a verifiable digital fingerprint and write it to the blockchain via a smart contract. Then, multiple authorized nodes cross-validate this digital fingerprint using a predetermined consensus algorithm, such as RaFT (Reliable Replicated Redundant And Fault-Tolerant), to reach a consensus result, ensuring that the data has not been tampered with and that ownership is unique. Subsequently, the consensus result is packaged into a new block, generating an immutable and publicly auditable ownership confirmation record on the chain. Any subsequent transactions or authorization actions must be triggered by a smart contract and reach consensus again, forming a traceable on-chain flow log. Simultaneously, off-chain storage and zero-knowledge proof technology are combined to protect the privacy of the original data, achieving a secure closed loop of on-chain ownership confirmation and off-chain controllable sharing.

[0003] For example, the Chinese invention patent with publication number CN119048090A discloses a method and system for confirming and trading enterprise data assets, which includes: collecting enterprise data asset identification information; constructing a hierarchical identification information database based on the enterprise data asset information identification; constructing an identification resolution model; inputting the enterprise data asset identification information into the identification resolution model for training to obtain the optimal identification resolution model; inputting the enterprise data asset identification information to be resolved into the optimal identification resolution model to obtain the identification resolution result corresponding to the enterprise data asset identification information to be resolved; and conducting smart contract transactions based on the identification resolution result.

[0004] For example, Chinese invention patent CN116308903A discloses a blockchain-based method for digital asset ownership protection, which includes: storing rights allocation information pre-agreed by at least two rights holders on the blockchain; when receiving digital assets uploaded by rights holders, allocating rights to the digital assets to form asset rights allocation data; generating multi-party signature certificates based on the asset rights allocation data and corresponding timestamps and storing them on the blockchain; when receiving a preset processing action to be performed on the digital assets, reminding the rights holders corresponding to the scope of rights involved in the preset processing action to obtain their authorization; after receiving the authorization from the rights holders, executing the preset processing action; further, when the preset processing action generates fund flows, allocating the fund flows according to the asset rights allocation data and generating a corresponding asset ownership ledger; encrypting the asset ownership ledger based on the rights holders' shared key and storing it on the blockchain.

[0005] The above-mentioned technology has at least the following technical problems: During the process of authorized nodes cross-validating digital fingerprints and reaching consensus, the existing Raft consensus algorithm relies on the master node to allocate tasks. If the master node is attacked or compromised, the entire network consensus process may be obstructed or manipulated. When a malicious attack attempts to disrupt the consensus process, it will send a large number of invalid requests to participate in cross-validation. To avoid being overwhelmed by malicious requests, authorized nodes will passively trigger abnormal defense logic (such as duplicate verification). This will force authorized nodes to consume excessive computing and bandwidth resources for cross-validation, leading to a decrease in consensus efficiency or even stagnation. In addition, when computing and bandwidth resources are consumed excessively, the verification task of legitimate digital fingerprints may time out and be retransmitted, further extending the time for generating consensus results. As consensus latency increases, the timeliness of writing the confirmation results generated based on the consensus results into new blocks may decrease, and there is a possibility of tampering due to consensus failure, resulting in low security and poor timeliness of the confirmation results record. Summary of the Invention

[0006] To address the technical problems of low security and poor timeliness in recording ownership confirmation results in existing technologies, this invention provides a data asset ownership confirmation method and system based on blockchain. The technical solution is as follows: On the one hand, a data asset ownership confirmation method based on blockchain is provided. This method includes: during the cross-validation of data assets based on blockchain, a malicious request interference impact judgment is performed to measure the malicious request interference on the blockchain, and a judgment result is generated. Based on the judgment result, it is determined whether to conduct a malicious request interference impact assessment on the time consumption and resource consumption of authorized nodes. If a malicious request interference impact assessment is conducted, based on the generated malicious request interference impact assessment result, it is determined whether to improve the parallel management capabilities of authorized nodes by processing the time consumption and resource consumption of authorized nodes to reduce memory fragmentation. Otherwise, a malicious request interference qualified prompt is directly sent to a preset management center. After the malicious request interference impact assessment is completed, a consensus efficiency verification analysis is performed to measure the efficiency of cross-validation. After the consensus efficiency verification analysis is completed, a ownership confirmation record security verification is performed to assess the security management of the ownership confirmation result generation.

[0007] On the other hand, a blockchain-based data asset ownership confirmation system is provided, which applies a blockchain-based data asset ownership confirmation method, including: a malicious request interference monitoring module, a time consumption and resource consumption processing judgment module, and an ownership confirmation security verification module. The malicious request interference monitoring module is used during the cross-validation of data assets based on the blockchain to determine the impact of malicious request interference on the blockchain and generate a judgment result. Based on the judgment result, it determines whether to conduct a malicious request interference impact assessment on the time consumption and resource consumption of authorized nodes. The time consumption and resource consumption processing judgment module is used to determine whether to improve the parallel management capabilities of authorized nodes and reduce memory fragmentation based on the generated malicious request interference impact assessment result if a malicious request interference impact assessment is conducted. Otherwise, it directly sends a malicious request interference qualified prompt to a preset management center. The ownership confirmation security verification module is used to conduct consensus efficiency verification analysis to measure the efficiency of cross-validation after the malicious request interference impact assessment is completed, and to conduct ownership confirmation record security verification after the consensus efficiency verification analysis is completed to assess the security management of the generated ownership confirmation result.

[0008] The beneficial effects of the technical solutions provided in the embodiments of the present invention include at least the following: 1. By determining the impact of malicious requests and generating a judgment result, and then deciding whether to conduct a malicious request interference impact assessment based on the judgment result, resources can be focused on situations with potential interference risks, reducing decision-making bias. If a malicious request interference impact assessment is conducted, consensus efficiency verification analysis is performed after the assessment. Otherwise, a malicious request interference qualified prompt is directly sent to the preset management center, which helps ensure that consensus verification is more targeted, avoids the occupation of node resources by assessment and verification operations in low-risk scenarios, and ensures the daily operation efficiency of the network. After the consensus efficiency verification analysis is completed, a rights confirmation record security verification is performed, which helps prevent malicious requests from causing data disagreements between nodes, ensures that key information such as data asset ownership and permissions cannot be tampered with, and thus helps to improve the security and timeliness of rights confirmation record recording, solving the technical problems of low security and poor timeliness of rights confirmation record recording in existing technologies.

[0009] 2. By harmonizing and averaging the request management time assessment results and the pending processing time assessment results to obtain the harmonized authorized node time assessment result, and by harmonizing and averaging the request management resource consumption assessment results and the pending processing resource consumption assessment results to obtain the harmonized resource consumption assessment result, compared with the single-dimensional assessment of existing technologies which is prone to resource skew bias, this method helps to achieve a comprehensive assessment of the degree of unqualified authorized node time and the degree of unqualified authorized node resource consumption. This is conducive to optimizing node layout and improving the overall anti-interference ability of the blockchain to generate confirmation results.

[0010] 3. When the consensus efficiency data does not meet the preset consensus analysis qualification conditions, the degree of query factor is judged. When the cross-validation query factor is not less than the consensus generation query factor, the cross-validation process optimization and consensus generation result qualification optimization are performed in sequence. Otherwise, only the consensus generation result qualification optimization is performed. This helps to reduce the validation divergence rate and improve the validation coverage, reduce the consumption of node computing power and bandwidth by invalid operations, improve the consensus efficiency recovery speed, and thus reduce the indirect interference of consensus optimization on the security of rights confirmation, and ensure the security of core data assets.

[0011] 4. By processing the authorized node time consumption when the reconciled authorized node time consumption assessment result is greater than the preset reconciled authorized node time consumption assessment result, it is helpful to accurately improve the processing efficiency of authorized nodes and avoid reducing consensus speed due to node time consumption. By processing the authorized node resource consumption when the reconciled resource consumption assessment result is greater than the preset reconciled resource consumption assessment result, it is helpful to optimize resource allocation efficiency and improve the management capability of blockchain for efficient operation. Attached Figure Description

[0012] To more clearly illustrate the technical solutions in the embodiments of the present invention, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0013] Figure 1 This is a flowchart of a data asset ownership confirmation method based on blockchain provided in an embodiment of the present invention; Figure 2 This is a general overview diagram of a blockchain-based data asset ownership confirmation method provided by an embodiment of the present invention; Figure 3 This is a schematic diagram illustrating the determination of query factor degree in a blockchain-based data asset ownership confirmation method provided by an embodiment of the present invention; Figure 4 This is a schematic diagram of the structure of a blockchain-based data asset ownership confirmation system provided in an embodiment of the present invention; Figure 5 This is an interface diagram of an enterprise-wide digital operation platform for a data asset ownership confirmation method based on blockchain provided in an embodiment of the present invention. Detailed Implementation

[0014] The technical solution of the present invention will now be described with reference to the accompanying drawings.

[0015] In embodiments of the present invention, words such as "exemplarily," "for example," etc., are used to indicate that something is an example, illustration, or description. Any embodiment or design described as "exemplary" in the present invention should not be construed as being more preferred or advantageous than other embodiments or designs. Specifically, the use of the word "exemplary" is intended to present the concept in a concrete manner. Furthermore, in embodiments of the present invention, the meaning expressed by "and / or" can be both, or either one.

[0016] In the embodiments of this invention, the terms "image" and "picture" may sometimes be used interchangeably. It should be noted that, without emphasizing the distinction between them, they convey the same meaning. Similarly, the terms "of," "corresponding (relevant)," and "corresponding" may sometimes be used interchangeably. It should be noted that, without emphasizing the distinction between them, they convey the same meaning.

[0017] In this embodiment of the invention, sometimes a subscript such as W1 may be written in a non-subscript form such as W1. When the difference is not emphasized, the meaning they express is the same.

[0018] To make the technical problems, technical solutions and advantages of the present invention clearer, a detailed description will be given below in conjunction with the accompanying drawings and specific embodiments.

[0019] This invention provides a method for confirming data asset ownership based on blockchain. For example... Figure 1 The flowchart shown is a data asset ownership confirmation method based on blockchain. The processing flow of this method may include the following steps: Malicious Request Interference Monitoring: During the cross-validation of data assets based on blockchain, a malicious request interference impact assessment is performed to measure the extent of malicious request interference on the blockchain and generate a judgment result. Based on the judgment result, it is determined whether to conduct a malicious request interference impact assessment on the time consumption and resource consumption of authorized nodes. Through malicious request interference monitoring, in the early stages of blockchain data asset cross-validation, by quantitatively judging the extent of malicious request interference, illegal requests (such as false verification requests and high-frequency attack requests) can be detected in a timely manner, thereby reducing invalid resource consumption and optimizing the efficiency of the verification process.

[0020] Time and resource consumption handling determination: If a malicious request interference impact assessment is performed, the assessment results will determine whether to implement time and resource consumption handling to improve the parallel management capabilities of authorized nodes and reduce memory fragmentation. Otherwise, a qualified malicious request interference notification will be sent directly to the preset management center. Time handling is used to allocate more tasks to different cores for parallel execution, thereby improving the parallel management capabilities of authorized nodes. Resource consumption handling is used to reduce memory fragmentation, thereby improving the matching and management capabilities of actual memory needs. By determining time and resource consumption handling, node load can be dynamically balanced, ensuring the stable operation of authorized nodes, while improving the anti-interference capabilities of authorized nodes and strengthening system resilience.

[0021] Security verification of ownership confirmation: After the assessment of the impact of malicious requests, a consensus efficiency verification analysis is conducted to measure the efficiency of cross-validation. After the consensus efficiency verification analysis, a security verification of ownership confirmation records is conducted to assess the security management of the generated ownership confirmation results. Through security verification of ownership confirmation, the security of ownership confirmation results is secured, directly ensuring the immutability of data asset ownership and preventing malicious requests from indirectly affecting the security of ownership confirmation results.

[0022] Before designing the blockchain-based data asset ownership confirmation method provided in this application, a database is established to store various types of set data. The database includes, but is not limited to, preset trigger repeated verification times, preset maximum authorized node processing time, etc., and the various values ​​are directly set by technical personnel.

[0023] like Figure 2The diagram shown is a general overview of a blockchain-based data asset ownership confirmation method provided in this application embodiment. Figure 2 It can be seen that: the malicious request interference impact judgment result is obtained through malicious request interference impact judgment. When the malicious request interference impact judgment result is not greater than the preset malicious request interference impact judgment result, a second malicious request interference judgment is performed. Otherwise, authorized node time consumption assessment is performed to obtain the reconciled authorized node time consumption assessment result, and authorized node resource consumption assessment is performed to obtain the reconciled resource consumption assessment result. When the monitored reconciled authorized node time consumption assessment result is greater than the preset reconciled authorized node time consumption assessment result, authorized node time consumption processing is performed. Otherwise, consensus efficiency verification analysis is performed. When the monitored reconciled resource consumption assessment result is greater than the preset reconciled resource consumption assessment result, authorized node resource consumption processing is performed. Otherwise, consensus efficiency verification analysis is performed. Consensus efficiency verification analysis is performed to obtain consensus efficiency data. If the consensus efficiency data meets the preset consensus analysis qualification conditions, a rights confirmation result will be generated. Otherwise, after obtaining the cross-validation query factor and consensus generation query factor, a rights confirmation record security verification is performed.

[0024] In this embodiment, the malicious request interference monitoring, time consumption and resource consumption processing judgment, and rights confirmation security verification work together and are interconnected to help form a logical chain from pre-monitoring (risk identification) to mid-stage decision-making (risk handling) and then to post-verification (security consolidation). This covers the entire lifecycle from before the risk occurs to after the risk is handled, avoiding the limitations of a single module (such as monitoring without handling leading to risk spread, or handling without verification leading to missed security risks). The combined effect of the three can ensure that data assets are not interfered with by malicious requests during the cross-verification process, nor will the efficiency be reduced due to processing interference. This helps to solidify the foundation for blockchain applications in the field of data assets.

[0025] For example, when enterprises manage product copyright confirmation services, a comprehensive security system can be created by monitoring malicious requests for interference, determining time and resource consumption, and verifying security during the confirmation process. This system's synergy effectively addresses the issues of risk identification, efficiency balance, and outcome security in copyright confirmation. The core of copyright confirmation is uploading core product information (such as software code, design drawings, and cultural and creative works) to a blockchain system to generate a unique confirmation certificate. This stage is prone to malicious attacks. Pre-emptive malicious request interference monitoring needs to focus on two types of risks and proactively identify them. Time and resource consumption determination, through dynamic decision-making, ensures that malicious requests do not waste resources, and that legitimate requests are not delayed due to insufficient resources. Through security verification, enterprises can promptly identify security vulnerabilities overlooked in the first two stages.

[0026] Furthermore, the specific process for determining the impact of malicious requests is as follows: Obtain the malicious request interference impact determination result, which reflects the degree of interference of malicious requests on the cross-validation process; monitor the number of times authorized nodes trigger repeated validation within a preset request time period using a counter, and use the ratio of this ratio to the preset number of repeated validation triggers as the malicious request interference impact determination result; the preset request time period represents the preset time period corresponding to the malicious request interference impact determination, and the preset number of repeated validation triggers is represented by the average number of times authorized nodes trigger repeated validations in historical time periods; make a determination based on the malicious request interference impact determination result: if the malicious request interference impact determination result is greater than the preset malicious request interference impact... The judgment results are used to mark the corresponding malicious request interference impact judgment results as malicious request interference results to be evaluated, and a malicious request interference impact assessment is performed. Otherwise, a second malicious request interference judgment is performed. The preset malicious request interference impact judgment result is represented by the average value of the malicious request interference impact judgment results over a historical time period. The second malicious request interference judgment process is as follows: it is determined whether the request sending anomaly value meets the request sending anomaly condition. If it does, a malicious request interference impact assessment is performed; otherwise, a malicious request interference qualified prompt is sent. The request sending anomaly value is represented by the total number of requests sent within a preset request time period. The request sending anomaly condition indicates that the request sending anomaly value is greater than the preset request sending anomaly value.

[0027] In this embodiment, by conducting a malicious request interference impact assessment when the malicious request interference impact determination result is greater than the preset malicious request interference impact determination result, it helps to quantify the actual harm of interference to authorized nodes, avoid ambiguous decision-making, and provide targeted directions for authorized nodes' time-consuming processing and resource consumption processing, thereby improving intervention efficiency. By conducting a secondary malicious request interference determination when the malicious request interference impact determination result is not greater than the preset malicious request interference impact determination result, it helps to improve the ability to balance security and efficiency in low-risk scenarios and avoid the contradiction between ineffective assessment and risk omission.

[0028] Furthermore, the assessment of the impact of malicious request interference includes an authorized node time consumption assessment to evaluate the time consumption of malicious request interference on authorized nodes and an authorized node resource consumption assessment to evaluate the resource consumption of malicious request interference on authorized nodes. The specific process of the authorized node time consumption assessment is as follows: The result of the malicious request interference to be assessed and a first malicious request harmonization factor used to reflect the degree of influence of the result of the malicious request interference on the authorized node time consumption assessment are weighted to obtain the request management time consumption assessment result, which reflects the degree of influence of malicious requests on the time consumption of authorized nodes; The authorized node time consumption result and a time consumption harmonization factor used to reflect the degree of influence of the authorized node time consumption result on the authorized node time consumption assessment are weighted to obtain the time consumption assessment result to be processed, which reflects the time consumption of authorized nodes; The authorized node time consumption result is represented by the result of the convergence assessment between the authorized node parsing time and the preset authorized node parsing time. The convergence assessment means that a ratio calculation is performed, and the preset authorized node parsing time is represented by the average value of the authorized node parsing time over a historical period; The timer monitors the authorized node on the blockchain from the time it receives the digital fingerprint cross-validation request from the network to the time consumption of authorized nodes. The average time required to successfully parse an authorization request is represented as the authorization node parsing time. The harmonic average of the request management time assessment result and the pending processing time assessment result yields the harmonic authorization node time assessment result, which reflects the authorization node time under malicious request interference. Harmonic averaging of the request management time assessment result and the pending processing time assessment result helps to quantify the impact of malicious requests on the authorization node time, as well as the comprehensive effect of the authorization node time. A larger request management time assessment result indicates more malicious... The greater the impact of the request on the authorization node's time consumption, the more severe the time consumption of the authorization node. The deviation between the reconciled authorization node time consumption assessment result and the preset reconciled authorization node time consumption assessment result is judged: if the reconciled authorization node time consumption assessment result is greater than the preset reconciled authorization node time consumption assessment result, authorization node time consumption processing is performed to improve the parallel processing efficiency of the authorization node for computing tasks; otherwise, consensus efficiency verification analysis is performed. The preset reconciled authorization node time consumption assessment result is obtained by querying the time consumption assessment result to be processed and the time consumption assessment result to be processed into the preset time consumption assessment query table.

[0029] It should be added that, in the embodiments of this application, several sets of mapping tables, query tables, and query sets pre-constructed by designated personnel and retrieved from the database are provided. These include a preset node time consumption mapping table, a preset time consumption evaluation query table, a preset CPU (Central Processing Unit) core count query set, a preset resource consumption mapping table, a preset memory granularity query set, a preset consensus efficiency impact mapping table, and a preset verification sampling query set. The mapping relationships are dynamic, supporting both one-to-one correspondence between single and single parameters, and many-to-one correspondence between many and single parameters. For example, by combining the results of malicious request interference to be evaluated and the authorized node time consumption results collected by the designated personnel over historical time periods, combining the results of pending processing time consumption evaluation and the results of pending processing time consumption evaluation, combining the pending processing time consumption evaluation value and the core operating frequency, combining the results of malicious request interference to be evaluated and the authorized node resource consumption results, and combining the pending processing resource consumption evaluation value and the memory occupied by the authorized node... The combinations of consensus efficiency data, consensus efficiency data, and data asset metadata are input into a machine learning model that reflects the importance of features, such as a decision tree model. Through feature splitting, corresponding weights or data are obtained, namely, the combination of the first malicious request reconciliation factor and the time consumption reconciliation factor, the preset reconciliation of authorized node time consumption evaluation results, the CPU core quantity processing factor, the combination of the second malicious request reconciliation factor and the node resource consumption reconciliation factor, the memory granularity processing factor, the combination of the cross-validation query factor and the consensus generation query factor, the validation sampling rate optimization factor, etc. The historical time period data and the corresponding weights or data are matched to obtain a mapping table, query table, and query set.

[0030] Specifically, this embodiment provides several sets of data reflecting the importance of features, including combinations of the results of malicious request interference to be evaluated and the results of authorized node time consumption, combinations of the results of processing time evaluation and the results of processing time evaluation, combinations of the processing time evaluation value and core operating frequency, combinations of the results of malicious request interference to be evaluated and the results of authorized node resource consumption, combinations of the processing resource consumption evaluation value and the memory occupied by authorized nodes, consensus efficiency data, and combinations of consensus efficiency data and the data volume corresponding to data asset metadata, etc., and establish one-to-one or many-to-one mapping relationships with the corresponding combinations of the first malicious request reconciliation factor and the time consumption reconciliation factor, the preset reconciled authorized node time consumption evaluation result, the CPU core number processing factor, the combination of the second malicious request reconciliation factor and the node resource consumption reconciliation factor, the memory granularity processing factor, the combination of the cross-validation query factor and the consensus generation query factor, the validation sampling rate optimization factor, etc.; by real-time collecting the combination of the results of malicious request interference to be evaluated and the results of authorized node time consumption, the processing time, etc. The combination of evaluation results and pending processing time evaluation results, the combination of pending processing time evaluation value and core operating frequency, the combination of pending malicious request interference results and authorized node resource consumption results, the combination of pending resource consumption evaluation value and authorized node memory usage, consensus efficiency data, and the combination of consensus efficiency data and data asset metadata corresponding data volume are input into the corresponding preset node time-consuming mapping table, preset time-consuming evaluation query table, preset CPU core quantity query set, preset resource consumption mapping table, preset memory granularity query set, preset consensus efficiency impact mapping table, preset verification sampling query set, etc. According to the preset mapping relationship, the corresponding combination of the first malicious request reconciliation factor and time-consuming reconciliation factor, the preset reconciled authorized node time-consuming evaluation result, CPU core quantity processing factor, the combination of the second malicious request reconciliation factor and node resource consumption reconciliation factor, memory granularity processing factor, the combination of cross-validation query factor and consensus generation query factor, verification sampling rate optimization factor, etc. are output, and the value range is limited to the interval between 0 and 1.

[0031] The specific process for handling the time consumption of authorized nodes is as follows: Within the next adjacent preset interference impact assessment time period, the time consumption assessment value to be processed and the core operating frequency monitored by the logic analyzer are input into a preset CPU core quantity query set to obtain a CPU core quantity processing factor. Using the magnitude corresponding to the CPU core quantity processing factor as the adjustment step size, the number of CPU cores is increased incrementally. By gradually matching task requirements, processing efficiency is improved, avoiding idle CPU resources or unbalanced load due to adding too many cores at once. This helps ensure the stability of the authorized node hardware system and prevents failures caused by sudden resource changes. The reconciled authorized node time consumption assessment result is continuously monitored. When the reconciled authorized node time consumption assessment result is not greater than the preset reconciled authorized node time consumption assessment result, authorized node time consumption processing stops. If the number of authorized node time consumption processing times (each increase in CPU cores is counted as one time) reaches the preset maximum number of authorized node time consumption processing times, the reconciled authorized node time consumption... If the time-based assessment result is still greater than the preset reconciled authorized node time-based assessment result, the corresponding authorized node is marked as an abnormal authorized node and abnormal authorized node processing is performed. The preset maximum number of authorized node time-based processing attempts is pre-set by preset personnel. Abnormal authorized node processing means sending abnormal node notifications to preset personnel to prevent the spread of malicious requests. The pending processing time-based assessment value is represented by the reconciled authorized node time-based assessment result that is greater than the preset reconciled authorized node time-based assessment result. The preset interference impact assessment time period represents the preset time period corresponding to the malicious request interference impact assessment. By performing abnormal authorized node processing when the number of authorized node time-based processing attempts reaches the preset maximum number of authorized node time-based processing attempts, and the reconciled authorized node time-based assessment result is still greater than the preset reconciled authorized node time-based assessment result, it helps to quickly locate and isolate abnormal nodes, prevent the risk from spreading to other authorized nodes, ensure the continuity of blockchain data asset cross-validation, and avoid the overall process interruption due to a single node abnormality.

[0032] In this embodiment, a reconciled authorized node time consumption assessment result is obtained by conducting a malicious request interference impact assessment. When the reconciled authorized node time consumption assessment result is greater than the preset reconciled authorized node time consumption assessment result, authorized node time consumption processing is performed. This helps to quickly bring the authorized node time consumption back to a safe threshold, avoid cross-validation process bottlenecks, avoid over-allocation or under-allocation of resources, and achieve a balance between time consumption and resources. By analyzing the mutual support between the malicious request interference impact assessment and authorized node time consumption processing, it helps to ensure the timeliness of data asset cross-validation, maintain the continuity of the rights confirmation process, and thus ensure the closed-loop nature of malicious request interference governance.

[0033] Furthermore, the specific process for assessing authorized node resource consumption is as follows: The malicious request interference result to be assessed and a second malicious request harmonization factor, used to reflect the impact of the malicious request interference result on the authorized node resource consumption assessment, are weighted to obtain a request management resource consumption assessment result reflecting the impact of malicious requests on authorized node resource consumption; the result of a convergence assessment between the authorized node resource consumption result and the preset resource consumption result is weighted with a node resource consumption harmonization factor, used to reflect the impact of the authorized node resource consumption result on the authorized node resource consumption assessment, to obtain a pending resource consumption assessment result reflecting the authorized node's resource consumption; the request management resource consumption assessment result and the pending resource consumption assessment result are harmonized and averaged to obtain a harmonized resource consumption assessment result reflecting the degree of non-compliance of authorized node resource consumption under malicious request interference; the request management resource consumption assessment result and the pending resource consumption assessment result are then ... under malicious request interference; the request management resource consumption assessment result and the pending resource consumption assessment result are Harmonized averaging of resource consumption assessment results helps to comprehensively evaluate the impact of malicious requests on authorized node resource consumption, as well as the combined effect of authorized node resource consumption. A higher resource consumption assessment result indicates a more severe impact of malicious requests on authorized node resource consumption, potentially leading to greater resource consumption. The total duration for which authorized node CPU utilization exceeds a preset reasonable utilization rate within a pre-defined interference impact assessment period, monitored by a timer, represents the authorized node resource consumption result. This preset reasonable utilization rate is pre-set by designated personnel. Deviation is determined based on the harmonized resource consumption assessment result and the preset harmonized resource consumption assessment result: if the harmonized result is greater than the preset harmonized result, authorized node resource consumption processing is performed; otherwise, consensus efficiency verification analysis is conducted. The preset harmonized resource consumption assessment result is represented by the average of harmonized resource consumption assessment results over historical time periods.

[0034] It should be added that the specific process for handling authorized node resource consumption is as follows: Within the next adjacent preset interference impact assessment time period, the memory granularity is gradually reduced by using the magnitude corresponding to the queried memory granularity processing factor as the adjustment step size; by smoothly optimizing resource matching, system oscillations are avoided, which helps to achieve accurate matching between memory resources and task requirements, reducing resource waste; the reconciled resource consumption assessment results are continuously monitored, and when the reconciled resource consumption assessment result is not greater than the preset reconciled resource consumption assessment result, authorized node resource consumption processing is stopped; if the number of authorized node resource consumption processing times (each smaller memory granularity is counted as one time) reaches the preset maximum number of authorized node resource consumption processing times set in advance by preset personnel, and the reconciled resource consumption assessment result is still greater than the preset reconciled resource consumption factor, then the authorized node resource consumption processing is stopped. The consumption assessment results mark the corresponding authorized nodes as abnormal authorized nodes and execute abnormal authorized node processing. The memory granularity processing factor represents the result obtained by inputting the resource consumption assessment value to be processed and the memory occupied by the authorized nodes monitored by memory debugging tools (such as Valgrind) into a preset memory granularity query set for querying. The resource consumption assessment value to be processed is represented by the harmonized resource consumption assessment result that is greater than the preset harmonized resource consumption assessment result. By executing abnormal authorized node processing when the number of authorized node resource consumption processing times reaches the maximum number of authorized node resource consumption processing times, and the harmonized resource consumption assessment result is still greater than the preset harmonized resource consumption assessment result, it helps to ensure the continuity of cross-validation of blockchain data assets and avoid business interruption due to single node abnormality.

[0035] In this embodiment, a reconciled resource consumption assessment result is obtained by performing an authorized node resource consumption assessment. When the reconciled resource consumption assessment result is greater than a preset reconciled resource consumption assessment result, authorized node resource consumption processing is performed. The authorized node resource consumption assessment is the decision basis for authorized node resource consumption processing, and the authorized node resource consumption processing is the means to implement the authorized node resource consumption assessment result. Through the interrelation and interaction between authorized node resource consumption assessment and authorized node resource consumption processing, it helps to optimize the utilization efficiency of authorized node resources and reduce the impact of memory fragmentation on core business.

[0036] like Figure 3 The diagram shown illustrates the determination of query factor degree in a blockchain-based data asset ownership confirmation method according to an embodiment of this application. Figure 3 It can be seen that: when consensus efficiency data is input into the preset consensus efficiency impact mapping table, the cross-validation query factor and consensus generation query factor are obtained. If the cross-validation query factor is not less than the consensus generation query factor, the cross-validation process optimization and consensus generation result qualification optimization are performed in sequence; otherwise, only the consensus generation result qualification optimization is performed.

[0037] Furthermore, the specific process of consensus efficiency verification analysis is as follows: Step 1, obtain the cross-validation value to reflect the unqualified situation of cross-validation efficiency when cross-validation is performed based on authorized nodes. The cross-validation value is represented by the average time taken by authorized nodes to verify the received digital fingerprints, as monitored by a timer. Step 2, obtain the consensus result verification value to reflect the unqualified situation of consensus result generation efficiency. The consensus result verification value is represented by the average time taken by authorized nodes to record the generated consensus results into the local database, as monitored by a timer. Step 3, determine whether the consensus efficiency data meets the preset consensus analysis qualification conditions. If it does, write the consensus result generated on the corresponding blockchain into a new block to generate the confirmation result. Otherwise, input the consensus efficiency data into the preset consensus efficiency impact mapping table to obtain the cross-validation query factor and the consensus generation query factor. The consensus efficiency data includes the cross-validation value and the consensus result verification value. The preset consensus analysis qualification conditions indicate that the cross-validation value is not greater than the preset cross-validation value, and the consensus result verification value is not greater than the preset consensus result verification value. The preset cross-validation value is represented by the average value of cross-validation values ​​over a historical time period, and the preset consensus result verification value is... The verification value is represented by the average of the verification values ​​of the consensus results over a historical time period. Step four involves determining the degree of the query factor: if the cross-validation query factor is not less than the consensus generation query factor, then sequentially perform cross-validation process optimization and consensus generation result qualification optimization; otherwise, only consensus generation result qualification optimization is performed. Cross-validation process optimization is used to dynamically adjust the verification sampling rate in the next adjacent preset verification analysis time period to increase redundant verification and obtain higher confidence and security. Consensus generation result qualification optimization is used to ensure the qualification of the consensus result generation, thereby ensuring the verification security of the digital fingerprint's ownership status. By sequentially performing cross-validation process optimization and consensus generation result qualification optimization when the cross-validation query factor is not less than the consensus generation query factor, the core bottleneck is addressed first, laying the foundation for secondary optimizations. This helps to achieve the superposition and amplification of optimization effects, avoids repeated adjustments, and thus ensures the maximum improvement of overall consensus efficiency. By only performing consensus generation result qualification optimization when the cross-validation query factor is less than the consensus generation query factor, it helps to quickly improve overall consensus efficiency with minimal resource investment, enabling rapid response to consensus efficiency issues and ensuring business continuity.

[0038] Specifically, the cross-validation process optimization process is as follows: The amplitude corresponding to the validation sampling rate optimization factor obtained from the query is used as the adjustment step size. The validation sampling rate is gradually reduced, which helps to ensure stable authorized node load while improving the efficiency of authorized node processing and optimizing resource utilization. This facilitates real-time verification and direction correction of the optimization effect, avoiding over-adjustment. When the consensus efficiency data meets the preset consensus analysis qualification conditions, the cross-validation process optimization stops, triggering the security verification of the rights confirmation record. When the number of cross-validation process optimizations (each reduction in the validation sampling rate is counted as one optimization) reaches the preset maximum number of cross-validation process optimizations set by preset personnel, if the consensus efficiency data still does not meet the preset consensus analysis qualification conditions, a cross-validation process optimization anomaly prompt is sent. The validation sampling rate optimization factor represents the result obtained by inputting the consensus efficiency data and the data asset metadata corresponding to the data monitored by the network traffic analyzer into the preset validation sampling query set for querying. The preset validation analysis time period represents the preset time period corresponding to the consensus efficiency validation analysis. The consensus generation result qualification optimization means that in the next adjacent preset validation analysis time period, the root hash of the digital fingerprint is written to the blockchain based on the hash tree algorithm.

[0039] In this embodiment, consensus efficiency data is obtained through consensus efficiency verification analysis. When the consensus efficiency data does not meet the preset consensus analysis qualification conditions, cross-validation query factors and consensus generation query factors are obtained to determine whether to optimize the cross-validation process and the consensus generation result qualification. This helps to realize the interrelation between consensus efficiency verification analysis, cross-validation process optimization, and consensus generation result qualification optimization, thereby achieving accurate positioning and targeted optimization of consensus efficiency issues. This helps to ensure the timeliness of data asset cross-validation and provides efficient support for the rights confirmation process.

[0040] Furthermore, the specific process for verifying the security of the rights confirmation record is as follows: Assess the deviation between the obtained unqualified value generated by the rights confirmation record and the preset unqualified value generated by the rights confirmation record; if the unqualified value generated by the rights confirmation record is greater than the preset unqualified value, the corresponding rights confirmation result is marked as an unqualified rights confirmation result and an abnormal rights confirmation result feedback is provided; otherwise, the corresponding rights confirmation result is marked as a qualified rights confirmation result and stored in the preset management center; the abnormal rights confirmation result feedback indicates that an abnormal rights confirmation result processing prompt is sent to preset personnel; the unqualified value generated by the rights confirmation record is represented by the average time taken to generate the rights confirmation result as monitored by a timer, used to reflect the degree of insecurity in the rights confirmation result generation process; wherein, the preset unqualified value generated by the rights confirmation record is represented by the average value of the unqualified values ​​generated by the rights confirmation record over a historical time period.

[0041] like Figure 4The diagram shown is a structural schematic of a blockchain-based data asset ownership confirmation system provided in an embodiment of this application. The blockchain-based data asset ownership confirmation system, applying a blockchain-based data asset ownership confirmation method, is characterized by comprising: a malicious request interference monitoring module, a time consumption and resource consumption processing and judgment module, and an ownership confirmation security verification module. The malicious request interference monitoring module is used during the cross-validation process of data assets based on the blockchain to perform a malicious request interference impact judgment to measure the malicious request interference situation on the blockchain and generate a judgment result. Based on the judgment result, it determines whether to allow malicious requests to interfere with the time consumption and resource consumption of authorized nodes. The interference impact assessment and time consumption processing judgment module is used to determine whether to improve the parallel management capabilities of authorized nodes and reduce memory fragmentation based on the generated malicious request interference impact assessment results if a malicious request interference impact assessment is conducted. Otherwise, a malicious request interference qualified prompt is sent directly to the preset management center, indicating that the malicious request has little impact on the process of generating the rights confirmation result. The rights confirmation security verification module is used to perform consensus efficiency verification analysis to measure the efficiency of cross-validation after the malicious request interference impact assessment is completed, and to perform rights confirmation record security verification after the consensus efficiency verification analysis is completed to evaluate the security management of the generated rights confirmation result.

[0042] In this embodiment, when the non-compliant value generated by the confirmation record is greater than the preset non-compliant value, the corresponding confirmation result is fed back to the preset personnel. This helps to quickly trace and locate the problem of non-compliant confirmation records, block the risk of non-compliant confirmation records, avoid the spread of errors, and ensure the accuracy of confirmation results. When the non-compliant value generated by the confirmation record is not greater than the preset non-compliant value, the corresponding confirmation result is marked as a qualified confirmation result and stored in the preset management center. This helps to securely archive qualified confirmation records, ensure immutability and traceability, realize a compliant closed loop in the confirmation process, complete the final implementation of data asset confirmation, and thus ensure the quality controllability of data asset confirmation records and the accuracy of data asset ownership.

[0043] like Figure 5 The image shown is an interface diagram of an enterprise-wide digital operation platform for a data asset ownership confirmation method based on blockchain provided in an embodiment of the present invention. Figure 5 As can be seen, the navigation bar of the enterprise-wide digital operation platform interface diagram provided in this application includes Homepage, Organization and Human Resources Management, Business Process Management, Financial Management, Asset and Equipment Management, Project Management, Procurement and Supply Chain, Sales and Customer Management, Knowledge and Document Management, Data Asset Ownership Confirmation, Compliance and Risk Control, and System Management and Integration; by Figure 5As can be seen, in the data asset ownership confirmation section, the ownership confirmation monitoring progress is 50%, and all current abnormal warnings are lit in red. This can be adjusted through optimization settings (time consumption optimization settings and resource consumption optimization).

[0044] In summary, this application embodiment, by determining the impact of malicious request interference and generating a determination result, and based on the determination result, decides whether to conduct a malicious request interference impact assessment. This helps to focus resources on situations with potential interference risks, reducing decision-making bias. If a malicious request interference impact assessment is conducted, consensus efficiency verification analysis is performed after the assessment. Otherwise, a malicious request interference pass notification is directly sent to the preset management center. This helps to ensure that consensus verification is more targeted, avoids the occupation of node resources by assessment and verification operations in low-risk scenarios, and ensures the daily operation efficiency of the network. After the consensus efficiency verification analysis is completed, a rights confirmation record security verification is performed. This helps to prevent malicious requests from causing data disagreements between nodes, ensures that key information such as data asset ownership and permissions cannot be tampered with, and thus helps to improve the security and timeliness of rights confirmation record recording, solving the technical problems of low security and poor timeliness of rights confirmation record recording in the prior art.

[0045] The above are merely specific embodiments of the present invention, but the scope of protection of the present invention is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the technical scope disclosed in the present invention should be included within the scope of protection of the present invention. Therefore, the scope of protection of the present invention should be determined by the scope of the claims.

Claims

1. A method for confirming data asset ownership based on blockchain, characterized in that, The method includes: In the process of cross-validation of data assets based on blockchain, the impact of malicious request interference is determined to measure the situation of malicious request interference on the blockchain and a determination result is generated. Based on the determination result, it is determined whether to conduct an impact assessment of malicious request interference on the time consumption and resource consumption of authorized nodes. If a malicious request interference impact assessment is performed, the assessment results will be used to determine whether to improve the parallel management capabilities of authorized nodes by handling the time consumption and resource consumption of authorized nodes to reduce memory fragmentation. Otherwise, a malicious request interference qualified prompt will be sent directly to the preset management center. After the assessment of the impact of malicious requests, a consensus efficiency verification analysis is conducted to measure the efficiency of cross-validation. After the consensus efficiency verification analysis, a security verification of the rights confirmation record is performed to assess the security management of the rights confirmation results.

2. The method for confirming data asset ownership based on blockchain according to claim 1, characterized in that, The specific process for determining the interference effect of malicious requests is as follows: Obtain the results of the malicious request interference assessment, which reflect the degree of interference of malicious requests on the cross-validation process; The determination is based on the influence of malicious requests on the judgment results: If the malicious request interference impact determination result is greater than the preset malicious request interference impact determination result, the corresponding malicious request interference impact determination result is marked as a malicious request interference result to be evaluated, and the malicious request interference impact evaluation is performed; otherwise, a second malicious request interference determination is performed. The specific process for determining the secondary malicious request interference is as follows: determine whether the abnormal value of the request sending meets the abnormal conditions for request sending. If it does, perform an assessment of the impact of malicious request interference; otherwise, send a notification that the malicious request interference is qualified. The abnormal value of request transmission is represented by the total number of requests sent within a preset request time period; The request sending exception condition indicates that the request sending exception value is greater than the preset request sending exception value.

3. The data asset ownership confirmation method based on blockchain according to claim 2, characterized in that, The assessment of the impact of malicious request interference includes assessment of the time consumed by the authorized node and assessment of the resource consumption of the authorized node; The specific process for evaluating the time consumption of the authorized node is as follows: The malicious request interference result to be evaluated and the first malicious request harmonization factor, which is used to reflect the degree of influence of the malicious request interference result on the authorized node time consumption evaluation, are weighted to obtain the request management time consumption evaluation result, which is used to reflect the degree of influence of malicious requests on the authorized node time consumption. The authorized node time consumption result and the time consumption harmonic factor, which reflects the degree of influence of the authorized node time consumption result on the authorized node time consumption assessment, are weighted to obtain the time consumption assessment result to be processed, which is used to reflect the time consumption of the authorized node. The harmonic average of the request management time assessment result and the pending processing time assessment result is used to obtain the harmonic authorized node time assessment result. The harmonic authorized node time assessment result is used to reflect the authorized node time under malicious request interference. If the reconciled authorized node time consumption assessment result is greater than the preset reconciled authorized node time consumption assessment result, authorized node time consumption processing is performed to improve the parallel processing efficiency of authorized nodes for computing tasks; otherwise, consensus efficiency verification analysis is performed. The preset harmonized authorized node time consumption evaluation result is obtained by querying the pending time consumption evaluation result and the pending time consumption evaluation result into the preset time consumption evaluation query table.

4. The data asset ownership confirmation method based on blockchain according to claim 3, characterized in that, The specific process of processing the authorization node's time consumption is as follows: Input the estimated processing time and core operating frequency into the preset CPU core count query set to obtain the CPU core count processing factor. The number of CPU cores is increased step by step, with the magnitude of the CPU core count processing factor as the adjustment step size. When the time consumption evaluation result of the reconciled authorized node is not greater than the preset time consumption evaluation result of the reconciled authorized node, the processing of authorized node time consumption is stopped. If the number of authorized node processing times reaches the preset maximum number of authorized node processing times, and the reconciled authorized node time evaluation result is still greater than the preset reconciled authorized node time evaluation result, the corresponding authorized node will be marked as an abnormal authorized node and abnormal authorized node processing will be performed. The abnormal authorization node handling means sending abnormal node prompts to preset personnel to prevent the spread of malicious requests; The time consumption assessment value to be processed is represented by the time consumption assessment result of the authorized node that is greater than the preset harmonized time consumption assessment result of the authorized node.

5. A method for confirming data asset ownership based on blockchain according to claim 3, characterized in that, The specific process for assessing the resource consumption of authorized nodes is as follows: The malicious request interference result to be evaluated and the second malicious request harmonization factor, which is used to reflect the degree of influence of the malicious request interference result on the resource consumption evaluation of the authorized node, are weighted to obtain the request management resource consumption evaluation result, which reflects the degree of influence of malicious requests on the resource consumption of the authorized node. The results of the convergence assessment between the authorized node resource consumption results and the preset resource consumption results are weighted with the node resource consumption harmonization factor, which reflects the influence of the authorized node resource consumption results on the authorized node resource consumption assessment, to obtain the unprocessed resource consumption assessment results that reflect the authorized node resource consumption status. The resource consumption assessment results of request management and pending resource consumption assessment results are harmonized and averaged to obtain a harmonized resource consumption assessment result that reflects the degree of non-compliance of authorized node resource consumption under malicious request interference. If the reconciled resource consumption assessment result is greater than the preset reconciled resource consumption assessment result, authorized node resource consumption processing will be performed; otherwise, consensus efficiency verification analysis will be performed.

6. The method for confirming data asset ownership based on blockchain according to claim 5, characterized in that, The specific process for handling the resource consumption of the authorized node is as follows: In the next adjacent preset interference impact assessment time period, the memory granularity is gradually reduced by using the magnitude of the memory granularity processing factor obtained from the query as the adjustment step size. Continuously monitor the resource consumption assessment results of the reconciliation. When the resource consumption assessment results of the reconciliation are not greater than the preset resource consumption assessment results of the reconciliation, stop processing the resource consumption of the authorized nodes. If the number of authorized node resource consumption processing times reaches the preset maximum number of authorized node resource consumption processing times, and the reconciled resource consumption assessment result is still greater than the preset reconciled resource consumption assessment result, the corresponding authorized node will be marked as an abnormal authorized node and abnormal authorized node processing will be performed. The memory granularity processing factor represents the result obtained by inputting the resource consumption assessment value to be processed and the memory occupied by the authorized node into a preset memory granularity query set for querying. The resource consumption assessment value to be processed is represented by a harmonized resource consumption assessment result that is greater than a preset harmonized resource consumption assessment result.

7. A method for confirming data asset ownership based on blockchain according to claim 5, characterized in that, The specific process of the consensus efficiency verification analysis is as follows: Step 1: Obtain a cross-validation value that reflects the failure of cross-validation efficiency when cross-validation is performed based on authorized nodes. The cross-validation value is represented by the average time taken for authorized nodes to verify the received digital fingerprint. Step 2: Obtain a consensus result verification value to reflect the efficiency of consensus result generation. The consensus result verification value is represented by the average time it takes for authorized nodes to record the generated consensus results into the local database. Step 3: Determine whether the consensus efficiency data meets the preset consensus analysis qualification conditions. If it does, write the consensus result generated on the corresponding blockchain into a new block to generate the confirmation result. Otherwise, input the consensus efficiency data into the preset consensus efficiency impact mapping table to obtain the cross-validation query factor and consensus generation query factor. The consensus efficiency data includes cross-validation values ​​and consensus result validation values; The preset consensus analysis qualification condition means that the cross-validation value is not greater than the preset cross-validation value, and the consensus result verification value is not greater than the preset consensus result verification value. Step 4: If the cross-validation query factor is not less than the consensus generation query factor, perform cross-validation process optimization and consensus generation result qualification optimization in sequence; otherwise, only perform consensus generation result qualification optimization. The cross-validation process optimization is used to dynamically adjust the validation sampling rate in the next adjacent preset validation analysis time period, thereby increasing redundant validation in exchange for higher confidence and security. The consensus generation result qualification optimization is used to ensure the qualification of the consensus result generation, thereby ensuring the verification security of the digital fingerprint's ownership status.

8. A method for confirming data asset ownership based on blockchain according to claim 7, characterized in that, The specific process for optimizing the cross-validation process is as follows: The validation sampling rate optimization factor obtained from the query is used as the adjustment step size to gradually reduce the validation sampling rate. When the consensus efficiency data is detected to meet the preset consensus analysis qualification conditions, the cross-validation process optimization is stopped and the security verification of the rights confirmation record is triggered. When the number of cross-validation process optimizations reaches the preset maximum number of cross-validation process optimizations, if the consensus efficiency data still does not meet the preset consensus analysis qualification conditions, a cross-validation process optimization anomaly prompt will be sent. The verification sampling rate optimization factor represents the result obtained by inputting the data volume corresponding to consensus efficiency data and data asset metadata into a preset verification sampling query set for querying. The consensus generation result qualification optimization means that the root hash of the digital fingerprint will be written into the blockchain in the next adjacent preset verification analysis time period.

9. A method for confirming data asset ownership based on blockchain according to claim 8, characterized in that, The specific process for the security verification of the ownership confirmation record is as follows: If the number of unqualified records generated by the confirmation of rights is greater than the preset number of unqualified records generated by the confirmation of rights, the corresponding confirmation result will be marked as an unqualified confirmation result and feedback of abnormal confirmation result will be provided; otherwise, the corresponding confirmation result will be marked as a qualified confirmation result and stored in the preset management center. The abnormal rights confirmation result feedback indicates that an abnormal rights confirmation result processing prompt is sent to a preset person; The non-compliance value generated by the confirmation record is represented by the average time taken to generate the confirmation result, which is used to reflect the degree of insecurity in the process of generating the confirmation result.

10. A blockchain-based data asset ownership confirmation system, employing the blockchain-based data asset ownership confirmation method as described in any one of claims 1-9, characterized in that, include: Malicious request interference monitoring module, time consumption and resource consumption processing and judgment module, and rights confirmation security verification module; The malicious request interference monitoring module is used to determine the impact of malicious request interference during the cross-validation of data assets based on blockchain, and generate a determination result to measure the situation of malicious request interference on the blockchain. Based on the determination result, it is determined whether to conduct a malicious request interference impact assessment on the time consumption and resource consumption of the authorized node. The time consumption and resource consumption processing judgment module is used to determine whether to perform authorized node time consumption processing and authorized node resource consumption processing to reduce memory fragmentation based on the generated malicious request interference impact assessment results if a malicious request interference impact assessment is performed. Otherwise, a malicious request interference qualified prompt is sent directly to the preset management center. The rights confirmation security verification module is used to perform consensus efficiency verification analysis to measure the efficiency of cross-validation after the assessment of the impact of malicious request interference is completed, and to perform rights confirmation record security verification after the consensus efficiency verification analysis is completed to evaluate the security management of the rights confirmation results.

Images