Multi-source privacy computing data circulation control method and system based on block chain

Abstract

The invention discloses a multi-source privacy computing data circulation control method and system based on a block chain, and relates to the technical field. The multi-source privacy computing data circulation control method based on the block chain comprises the steps of block chain key anchoring analysis, multi-source privacy computing data circulation judgment, multi-source privacy computing data circulation control evaluation and block chain full-node audit measurement. According to the method, whether to perform block chain key anchoring analysis optimization or not is judged by executing block chain key anchoring, multi-source privacy computing data circulation judgment is executed, and then multi-source privacy computing data circulation control evaluation is executed to obtain a multi-source privacy computing data circulation control evaluation result. And executing block chain full-node audit measurement to obtain a block chain full-node audit measurement result, thereby realizing improvement of multi-source privacy computing data circulation control security, and solving the technical problem of low security of block chain-based multi-source privacy computing data circulation control in the prior art.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field, in particular to a multi-source privacy computing data flow control method and system based on a blockchain. BACKGROUND

[0002] In order to realize the security of the multi-source privacy computing data flow control process on the blockchain, the prior art first integrates original computing data from different industries and different types, such as enterprise operation data and health management data, through a data flow control system, cleanses and formats the original computing data, and then synchronously generates data hash values and writes them into a blockchain distributed ledger using encryption technology, while labeling the data with a "privacy label" such as sensitivity level and authorized range, forming standardized multi-source privacy computing data. Next, the data flow control system uses a secure transmission protocol such as SSL (Secure Sockets Layer) or TLS (Transport Layer Security) to generate a key, and the identity information of the blockchain transmission node, the transmission time, and the data hash value are stored in real time on the chain, and the risk assessment model built-in the data flow control system combines the historical flow records on the blockchain, such as past risk events and node credit scores, to determine the risk level from the dimensions of data sensitivity, flow range, and use purpose, and based on real-time on-chain data such as abnormal access frequency and permission change records to predict data leakage and misuse of authority, trigger an early warning mechanism to interrupt high-risk operations. Next, since the data flow control system deploys a smart contract on the blockchain, it prewrites core rules for data flow, including data use range, use period, transaction counterparty, privacy protection requirements, etc. When there is a data use request, the smart contract automatically checks the requester's identity, permissions, and risk assessment results, and only allows multi-source privacy computing data that meets the rules to pass. The transactions involved in the flow of multi-source privacy computing data, such as data usage rights transactions, are automatically executed by the smart contract, and the transaction records are stored in real time on the chain. Finally, when the multi-source privacy computing data flow is complete, the blockchain records the full-link logs of the data flow, including cloud service providers, data owners, and audit initiators, to ensure the security of multi-source privacy computing data and information, and to support post-traceability and auditing. Once a security problem occurs, the responsible party can be quickly located, the multi-source privacy computing data after the flow is desensitized, the secure multi-party computing result is obtained, and the storage state of the multi-source privacy computing data is continuously monitored to resist security threats. Based on the secure multi-party computing result and security threats, the smart contract rules and risk assessment model are iteratively updated to protect multi-source privacy computing data and information.

[0003] For example, the Chinese invention patent application with publication number CN120561952A discloses a data flow safety supervision platform based on blockchain, which relates to the field of blockchain technology, and includes: collecting basic information in the data flow process, preprocessing data and calculating data hash value; by implicit data identification features and blockchain technology, the preprocessed data hash value and implicit data identification features are stored in the blockchain to generate blockchain data evidence; according to the blockchain data evidence, combined with user behavior analysis, dynamically adjust access rights and data compliance review; compare the hash value stored in the blockchain to verify data integrity; according to the blockchain data evidence and data integrity detection results, analyze whether there is abnormal risk in the data flow process, and trigger the early warning mechanism.

[0004] The above-mentioned technology at least has the following technical problems:

[0005] In the existing multi-source privacy computing data flow scene, although the existing technology has used a secure transmission protocol to ensure the security of multi-source privacy computing data transmission, there is still room for optimization in key management. The key needs to be updated dynamically with the change of authority, such as authorization expiration and node exit, to maintain the effectiveness of access control. However, in the process of multi-source privacy computing data cross-node collaborative computing, since the generation, update and revocation of core keys are controlled by a single management node or a small number of node clusters, on the one hand, the core key used for node identity identification and root trust anchor may not pass the consistency verification through the blockchain consensus mechanism in the consensus layer, and only takes effect in part of the nodes, which may lead to identity trust failure between nodes, causing multi-source privacy computing data transmission decryption failure or computing task interruption, directly affecting the correctness of secure multi-party computing results. On the other hand, the key fragments may be restored by splicing due to key fragment leakage, which may cause the smart contract to mistakenly attribute the accuracy problem of the privacy computing protocol itself to key synchronization exception. This misjudgment may cause deviation in risk assessment in the process of multi-source privacy computing data flow, resulting in inaccurate multi-source privacy computing data, further leading to inaccurate risk assessment and danger prediction in the process of multi-source privacy computing data flow, and low security of multi-source privacy computing data flow control. SUMMARY

[0006] In order to solve the technical problem of low security of multi-source privacy computing data flow control based on blockchain in the existing technology, the embodiments of the present application provide a multi-source privacy computing data flow control method and system based on blockchain. The technical scheme is as follows:

[0007] In one aspect, a blockchain-based multi-source privacy computing data flow control method is provided, comprising the following steps: in the process of multi-source privacy computing data flow control, performing blockchain key anchoring analysis, obtaining the results of the blockchain key anchoring analysis, and then determining whether to perform blockchain key anchoring analysis optimization according to the results of the blockchain key anchoring analysis, the blockchain key anchoring analysis optimization being used to improve the consistency and accuracy of blockchain key consensus; after the blockchain key anchoring analysis is qualified, performing multi-source privacy computing data flow determination, obtaining the results of the multi-source privacy computing data flow determination, and then determining whether to perform multi-source privacy computing data flow measurement according to the results of the multi-source privacy computing data flow determination, the multi-source privacy computing data flow measurement being used to evaluate the delay degree of the duration of blockchain permission change; after the multi-source privacy computing data flow determination is completed, performing multi-source privacy computing data flow control evaluation, obtaining the results of the multi-source privacy computing data flow control evaluation, and then determining whether to perform multi-source privacy computing data flow control optimization according to the results of the multi-source privacy computing data flow control evaluation, the multi-source privacy computing data flow control optimization being used to improve the consistency of key states between blockchain nodes; after the multi-source privacy computing data flow control evaluation is qualified, performing blockchain full node audit measurement, obtaining the results of the blockchain full node audit measurement, and then determining whether to perform multi-source privacy computing data verification according to the results of the blockchain full node audit measurement, the multi-source privacy computing data verification being used to improve the security of multi-source privacy computing data in the auditing process and the accuracy of multi-source privacy computing data risk assessment.

[0008] In another aspect, a blockchain-based multi-source privacy computing data flow control system is provided, comprising the following modules: a blockchain key anchoring analysis module, a multi-source privacy computing data flow determination module, a multi-source privacy computing data flow control evaluation and a blockchain full node audit measurement module.

[0009] The blockchain key anchoring analysis module is used to perform blockchain key anchoring analysis during the multi-source privacy computing data circulation control process. It first obtains the blockchain key anchoring analysis results, and then determines whether to optimize the blockchain key anchoring analysis based on these results. The multi-source privacy computing data circulation judgment module is used to perform multi-source privacy computing data circulation judgment after the blockchain key anchoring analysis is deemed successful. It first obtains the multi-source privacy computing data circulation judgment results, and then determines whether to proceed with the multi-source privacy computing data circulation judgment. The multi-source privacy computing data circulation control evaluation module is used to perform multi-source privacy computing data circulation control evaluation after the multi-source privacy computing data circulation judgment is completed. It first obtains the multi-source privacy computing data circulation control evaluation results, and then determines whether to optimize the multi-source privacy computing data circulation control based on these results. The blockchain full-node audit measurement module is used to perform blockchain full-node audit measurement after the multi-source privacy computing data circulation control evaluation is deemed successful. It first obtains the blockchain full-node audit measurement results, and then determines whether to perform multi-source privacy computing data verification based on these results.

[0010] The beneficial effects of the technical solutions provided in the embodiments of the present invention include at least the following:

[0011] 1. By performing blockchain key anchoring analysis, the results can be obtained to accurately assess the consistency of consensus among blockchain nodes involved in key generation regarding the core key, thereby enhancing the security and trustworthiness of blockchain key management and improving the reliability of multi-source privacy computing data circulation. Similarly, by performing multi-source privacy computing data circulation judgment, the results can be obtained to accurately assess the qualification of nodes updating keys on the blockchain, improving the qualification and stability of multi-source privacy computing data circulation on the blockchain and ensuring the security of multi-source privacy computing data circulation control. Furthermore, by performing multi-source privacy computing data circulation control assessment, the results can be obtained to accurately assess the integrity of the entire lifecycle of key fragment transfer records, improving the access control and anti-leakage capabilities of multi-source privacy computing data circulation control and enhancing its security and controllability. Finally, by performing full-node audit measurement, the results can be obtained to accurately assess the integrity of multi-source privacy computing data transmitted via key fragments, improving the integrity and transparency of blockchain consensus and thus enhancing the credibility and traceability of multi-source privacy computing data verification.

[0012] 2. Optimizing blockchain key anchoring analysis helps to alleviate the congestion problem of data flow in multi-source privacy computing. Compared with the prior art, since there is still optimization space for key management, the key needs to be updated dynamically with the change of authority, such as authorization expiration and node exit, to maintain the effectiveness of access control. However, in the process of multi-source privacy computing data cross-node collaborative computing, the generation, update and revocation of core keys are controlled by a single management node or a few node clusters, which leads to unqualified core key anchoring. The present scheme helps to strengthen the core key trust root and reduce the verification redundancy of multi-source privacy computing data, thereby improving the reliability of multi-source privacy computing data flow control.

[0013] 3. Optimizing multi-source privacy computing data flow control helps to reduce single node misjudgment. Compared with the prior art, since the generation, update and revocation of core keys are controlled by a single management node or a few node clusters, it may cause the core key used for node identity identification and root trust anchoring to fail to pass the consistency verification through the blockchain consensus mechanism in the consensus layer, and only take effect in part of the nodes, which may lead to invalidation of identity trust between nodes, causing multi-source privacy computing data transmission decryption failure or computing task interruption. The present scheme helps to reduce the interference of single node misjudgment on the stability of multi-source privacy computing data flow, avoid local nodes on the blockchain maintaining incorrect trust anchoring due to information lag, and thereby improve the stability of multi-source privacy computing data.

[0014] 4. By performing multi-source privacy computing data verification, compared with the prior art, due to key fragment leakage being spliced and restored, the smart contract automatically checks the accuracy of the privacy computing protocol itself due to key synchronization exception. This misjudgment may cause risk assessment deviation in the process of multi-source privacy computing data flow, resulting in inaccurate multi-source privacy computing data, leading to inaccurate risk assessment and danger prediction in the process of multi-source privacy computing data flow. The present scheme helps to ensure the accuracy of multi-source privacy computing data in circulation and the effectiveness of risk control, thereby improving the eligibility of multi-source privacy computing data control. BRIEF DESCRIPTION OF DRAWINGS

[0015] Figure 1 Flowchart of the method for controlling multi-source privacy computing data flow based on blockchain provided by the embodiments of the present application;

[0016] Figure 2 Blockchain key anchoring analysis and multi-source privacy computing data flow determination of the method for controlling multi-source privacy computing data flow based on blockchain provided by the embodiments of the present application;

[0017] Figure 3 Multi-source privacy computing data flow control evaluation architecture schematic diagram of the method for controlling multi-source privacy computing data flow based on blockchain provided by the embodiments of the present application;

[0018] Figure 4 A blockchain full node audit measurement architecture schematic diagram of the multi-source privacy computing data flow control method based on a blockchain provided in the embodiments of the present application is shown in the figure.

[0019] Figure 5 A blockchain key anchoring analysis optimization framework schematic diagram of the multi-source privacy computing data flow control method based on a blockchain provided in the embodiments of the present application is shown in the figure.

[0020] Figure 6 A structure schematic diagram of a multi-source privacy computing data flow control system based on a blockchain provided in the embodiments of the present application is shown in the figure. DETAILED DESCRIPTION

[0021] The technical solutions in the present application will be described below with reference to the drawings.

[0022] In the embodiments of the present application, the words such as "example", "for example" are used to represent as an example, illustration or description. Any embodiment or design scheme described as "example" in the present application should not be interpreted as more preferred or more advantageous than other embodiments or design schemes. Rather, the word "example" is intended to present the concept in a specific manner. In addition, in the embodiments of the present application, the meaning expressed by "and / or" can be both, or can be one of the two options.

[0023] In the embodiments of the present application, "image" and "picture" can be used interchangeably at times. It should be pointed out that when the distinction is not emphasized, the meanings expressed are consistent. "Of", "corresponding" and "corresponding" can be used interchangeably at times. It should be pointed out that when the distinction is not emphasized, the meanings expressed are consistent.

[0024] To make the technical problems, technical solutions and advantages of the present application clearer, specific embodiments will be described in detail below with reference to the drawings.

[0025] The embodiments of the present application provide a multi-source privacy computing data flow control method and system based on a blockchain, as shown in the structure schematic diagram of the multi-source privacy computing data flow control method and system based on a blockchain. Figure 1 The structure schematic diagram of the multi-source privacy computing data flow control method and system based on a blockchain includes the following steps:

[0026] The blockchain key anchoring analysis is performed to obtain a blockchain key anchoring analysis result, and it is determined whether to perform blockchain key anchoring analysis optimization. If the blockchain key anchoring analysis result meets the blockchain key anchoring analysis qualified condition, multi-source privacy computing data flow circulation determination is performed. Otherwise, the blockchain key anchoring analysis optimization is performed, which helps to improve the security and credibility of the key management of the blockchain to improve the reliability of the multi-source privacy computing data flow circulation.

[0027] The multi-source privacy computing data flow circulation determination is performed to obtain a multi-source privacy computing data flow circulation determination result, and it is determined whether to perform multi-source privacy computing data flow circulation measurement. If the multi-source privacy computing data flow circulation determination result meets the multi-source privacy computing data flow circulation qualified condition, multi-source privacy computing data flow circulation control evaluation is performed. Otherwise, the multi-source privacy computing data flow circulation measurement is performed, which helps to improve the eligibility and stability of the multi-source privacy computing data circulation on the blockchain to ensure the security of the multi-source privacy computing data flow circulation control.

[0028] The multi-source privacy computing data flow circulation control evaluation is performed to obtain a multi-source privacy computing data flow circulation control evaluation result, and it is determined whether to perform multi-source privacy computing data flow circulation control optimization. If the multi-source privacy computing data flow circulation control evaluation result is greater than or equal to a preset multi-source privacy computing data flow circulation control evaluation result, blockchain full node audit measurement is performed. Otherwise, the multi-source privacy computing data flow circulation control optimization is performed, which improves the authority control and anti-leakage capability of the multi-source privacy computing data flow circulation control to enhance the security and controllability in the multi-source privacy computing data flow circulation control.

[0029] The blockchain full node audit measurement is performed to obtain a blockchain full node audit measurement result, and it is determined whether to perform multi-source privacy computing data verification. If the blockchain full node audit measurement result meets the blockchain audit analysis qualified condition, a multi-source privacy computing data flow circulation control qualified prompt is sent to a preset person. Otherwise, the multi-source privacy computing data verification is performed based on the smart contract before the key fragment holding node receives the key fragment transmission, which helps to improve the integrity and transparency of the blockchain consensus to improve the eligibility of the multi-source privacy computing data audit.

[0030] As shown in Figure 2 Fig. 1 is a blockchain key anchoring analysis and multi-source privacy computing data flow circulation determination architecture schematic diagram of a multi-source privacy computing data flow circulation control method based on a blockchain provided by an embodiment of the present application, as shown in Figure 3The diagram illustrates the multi-source privacy computing data circulation control evaluation architecture of the blockchain-based multi-source privacy computing data circulation control method provided in this application embodiment. First, blockchain key anchoring analysis is performed to determine if the analysis result meets the blockchain key anchoring analysis qualification conditions. If it does, multi-source privacy computing data circulation determination is performed; otherwise, blockchain key anchoring analysis optimization is performed, and the re-obtained blockchain key anchoring analysis result is determined to meet the blockchain key anchoring analysis qualification conditions. If it does, multi-source privacy computing data circulation determination is performed; otherwise, a notification of blockchain key anchoring analysis optimization anomaly is sent to preset personnel. Next, multi-source privacy computing data circulation determination is performed to determine if the obtained multi-source privacy computing data circulation determination result meets the multi-source privacy computing data circulation qualification conditions. If it does, multi-source privacy computing data circulation control evaluation is performed. Conversely, if the data flow of multi-source privacy computing data is not satisfactory, a multi-source privacy computing data flow control assessment is performed. The assessment determines whether the obtained blockchain permission change duration measurement result meets the acceptable criteria for blockchain permission change analysis. If it does, a multi-source privacy computing data flow control assessment is executed. Otherwise, an abnormal multi-source privacy computing data flow judgment prompt is sent to designated personnel. Finally, a multi-source privacy computing data flow control assessment is performed to determine whether the assessment result is greater than or equal to the preset multi-source privacy computing data flow control assessment result. If it does, a full-node blockchain audit is performed. Otherwise, multi-source privacy computing data flow control optimization is performed. The assessment determines whether the re-obtained multi-source privacy computing data flow control assessment result after optimization is greater than or equal to the preset multi-source privacy computing data flow control assessment result. If it does, a full-node blockchain audit is performed. Otherwise, an abnormal multi-node cross-validation prompt is sent to designated personnel.

[0031] like Figure 4 The diagram shown illustrates the blockchain full-node audit and measurement architecture of the blockchain-based multi-source privacy computing data circulation control method provided in this application embodiment. The method performs a blockchain full-node audit and measurement, determining whether the results meet the blockchain audit analysis qualification criteria. If they do, a qualified multi-source privacy computing data circulation control notification is sent to preset personnel. Otherwise, multi-source privacy computing data verification is performed, and the verification result is checked against the value of 1. If the result is 1, a qualified multi-source privacy computing data notification is sent to preset personnel, and a circulation record is automatically generated. A data circulation control risk assessment is calculated. Otherwise, an abnormal blockchain full-node audit and measurement notification is sent to preset personnel.

[0032] In the multi-source privacy computing data flow control process, the blockchain consensus mechanism is used to solve the traditional cloud data public audit semi-trust problem, enhance the trust between data consumers and cloud service providers, protect the audit metadata provided by the data owner using a distributed ledger, prevent metadata invalidation from causing audit failure and audit credential reconstruction problems, and use the blockchain to store the audit records of data consumers and resist historical tampering. Multi-source privacy computing data refers to a data set that is gathered from two or more different sources, such as different institutions, different terminal devices, different business systems, or different data owners, under the privacy computing technology system, and supports multi-party collaborative computing under the principle of data availability and invisibility. It may include business data from different departments within an enterprise, such as complementary data from cross-industry cooperation institutions, patient diagnosis and treatment data from medical systems, and reimbursement data from medical insurance platforms. It may also include personal data authorized by end users, such as health data collected by smart devices and behavior data recorded by consumer platforms. These data have significant differences in format, dimension, and purpose, but need to participate in the same computing task to extract data value.

[0033] It should be noted that in this application, a database for storing various types of setting data is established before designing the multi-source privacy computing data flow control method based on the blockchain. The database includes but is not limited to preset blockchain key anchoring analysis results, preset multi-source privacy computing data flow determination results, preset multi-source privacy computing data flow control evaluation results, and preset blockchain full node audit measurement results, etc. The various numerical values in the database come from a variety of sources, including expert experience, industry standards, and practical summaries. The data structure is based on a relational type and is organized in layers and categories, such as blockchain key information collection and multi-source privacy computing judgment rule structured storage. The storage uses encryption to protect sensitive data, indexing to improve efficiency, and backup to ensure security. Technical personnel directly set many key values based on rigorous testing and demonstration, such as precision and strength parameters in blockchain key anchoring analysis, trust level standards and sharing ratio limits in multi-source privacy computing flow determination, security performance weights and efficiency target values in flow control evaluation, response time and error rate thresholds in full node audit, etc. to form a basic configuration system that supports the operation of the method.

[0034] In the embodiment, by performing the blockchain key anchoring analysis to obtain the blockchain key anchoring analysis result, and judging whether to perform the multi-source privacy computing data flow determination, it is helpful to reduce the inconsistency of multi-source privacy computing data or unauthorized access due to delay or blockage, enhance the confidentiality and integrity in the process of multi-source privacy computing data flow, ensure the security and stability of multi-source privacy computing data flow control on the blockchain, and perform the multi-source privacy computing data flow determination to obtain the multi-source privacy computing data flow determination result, and judge whether to perform the multi-source privacy computing data flow control evaluation, which is helpful to improve the auditability and attack resistance of the whole multi-source privacy computing data flow process, ensure the integrity and controllability of multi-source privacy computing data in the key links of sharding, updating and confirmation, perform the multi-source privacy computing data flow control evaluation to obtain the multi-source privacy computing data flow control evaluation result, and judge whether to perform the blockchain full node audit measurement, which is helpful to improve the consistency of node identity identification and root trust anchoring core key in the consensus layer, thereby improving the correctness of secure multi-party computing result, perform the blockchain full node audit measurement to obtain the blockchain full node audit measurement result, and judge whether to perform the multi-source privacy computing data verification, if the blockchain full node audit measurement result meets the blockchain audit analysis qualified condition, send the multi-source privacy computing data flow control qualified prompt to the preset personnel, otherwise, based on the smart contract, the multi-source privacy computing data verification is performed before the key fragment holding node receives the key fragment transmission, which is helpful to reduce the risk assessment deviation in the process of multi-source privacy computing data flow, and improve the accuracy of multi-source privacy computing data flow control.

[0035] Further, blockchain key anchoring analysis is performed. First, the results of the blockchain key anchoring analysis are obtained. Then, based on these results, it is determined whether blockchain key anchoring analysis optimization should be performed. The specific process is as follows: Blockchain key anchoring analysis is performed to evaluate the qualification level of the blockchain core key generation. The key generation consensus achievement rate is monitored through the node server log system and compared with a preset key generation consensus achievement rate. This ratio is used to obtain the blockchain key consensus achievement result, which measures the degree of consistency in the consensus of blockchain nodes participating in key generation regarding the core key. The preset key generation consensus achievement rate is represented by the average value of the key generation consensus achievement rate over historical time periods. The blockchain write latency is compared with the blockchain write latency monitored by the blockchain node client to obtain the blockchain write time result, which reflects the transmission speed from core key generation to on-chain storage. The preset blockchain write latency is represented by the average value of the blockchain write latency over historical time periods. The core key represents the set of keys used to perform the most fundamental security functions in the blockchain. It is then determined whether the blockchain key anchoring analysis results, including the blockchain key consensus achievement result and the blockchain write time result, meet the qualification conditions for blockchain key anchoring analysis. The qualification conditions for blockchain key anchoring analysis refer to the qualification conditions for blockchain key consensus achievement. Furthermore, the blockchain write time meets the qualification condition; the blockchain key consensus meeting qualification condition means that the blockchain key consensus result is greater than the preset blockchain key consensus result, which is represented by the average of the blockchain key consensus results over a historical period; the blockchain write time meeting qualification condition means that the blockchain write time result is greater than the preset blockchain write time result, which is represented by the average of the blockchain write time results over a historical period; the key generation consensus achievement rate is represented by the ratio between the number of nodes that successfully verified and confirmed the core key and the number of participating nodes, which is used to reflect the qualification degree of the core key consensus; the blockchain write latency represents the time required for the core key to be generated and stored on the blockchain; the number of participating nodes represents the total number of nodes participating in the generation of the core key; if the blockchain key anchoring analysis result meets the qualification condition of the blockchain key anchoring analysis, the multi-source privacy computing data circulation judgment used to evaluate the qualification degree of multi-source privacy computing data circulation is executed; otherwise, the blockchain key anchoring analysis optimization is performed; the blockchain key anchoring analysis optimization means performing blockchain sharding operations to alleviate the blocking problem of data circulation in multi-source privacy computing and asynchronous multi-source privacy computing data write operations to reduce the blocking situation when uploading the core key.

[0036] In the embodiment, by performing the blockchain key anchoring analysis, the qualified degree of key generation consensus can be effectively measured, the consistency and timeliness of the core key in the generation and storage stage are ensured, the security of multi-source privacy computing data circulation is improved, the multi-source privacy computing data circulation blockage and key uploading delay problems are effectively alleviated, the multi-source privacy computing data circulation is interfered due to low synchronization efficiency of the blockchain node or network congestion, the reliability and attack resistance of the key anchoring process on the blockchain are enhanced, and the integrity and controllability of the multi-source privacy computing data are ensured.

[0037] Further, the specific process of the blockchain key anchor analysis optimization is as follows: judging whether the capacity utilization rate of each parallel subchain is not more than the preset parallel subchain capacity utilization rate; if the capacity utilization rate of each parallel subchain is not more than the preset parallel subchain capacity utilization rate, the corresponding parallel subchain is marked as a low-capacity parallel subchain, and the low-capacity parallel subchains are sorted in ascending order according to the corresponding parallel subchain capacity utilization rate; the preset parallel subchain capacity utilization rate is represented by the average value of the historical time period parallel subchain capacity utilization rate; otherwise, the corresponding parallel subchain is marked as a high-capacity parallel subchain, and a parallel subchain capacity abnormal prompt is sent to the preset personnel; wherein, the capacity utilization rate of the parallel subchain is monitored in real time by the node exporter; the parallel subchain capacity analysis is used to evaluate the capacity utilization degree of each parallel subchain; the blockchain sharding operation refers to splitting the blockchain network into parallel subchains based on the blockchain sharding method and the blockchain segmentation ratio, and sequentially storing the core keys in the low-capacity parallel subchains in ascending order according to the parallel subchain capacity utilization rate; the blockchain segmentation ratio is obtained by monitoring the blockchain capacity through the full node client, and then performing difference calculation and ratio processing on the difference between the blockchain capacity and the blockchain usage capacity; wherein, the blockchain sharding method specifically refers to splitting the overall data and transaction processing tasks of the blockchain into independent shards according to a preset rule, such as a hash value, a transaction address, etc., and each shard is only responsible for maintaining and verifying the transactions and data within the shard; if the reacquired blockchain key anchor analysis result after the blockchain sharding operation meets the blockchain key anchor analysis qualified condition, the multi-source privacy computing data flow circulation judgment is performed, otherwise, the multi-source privacy computing data asynchronous write operation is performed; the multi-source privacy computing data asynchronous write operation specifically refers to first judging whether the core key transmission result temporarily stored in the low-capacity parallel subchain is less than or equal to the preset core key transmission result, and the preset core key transmission result is represented by the average value of the historical time period core key transmission result; if the core key transmission result is less than or equal to the preset core key transmission result, it is marked as a low-priority key, otherwise, it is marked as a high-priority key, and a core key abnormal prompt is sent to the preset personnel; for the low-priority key, it is temporarily stored in the memory buffer pool, and when the blockchain capacity does not exceed the preset blockchain capacity, the corresponding core key is uploaded in batches, otherwise, a blockchain capacity abnormal prompt is sent to the preset personnel; the blockchain capacity represents the total amount of data for synchronizing and verifying the storage of the entire blockchain historical data; the core key transmission result represents the number of nodes of the blockchain that transmit the core key; if the reacquired blockchain key anchor analysis result after the multi-source privacy computing data asynchronous write operation meets the blockchain key anchor analysis qualified condition, the multi-source privacy computing data flow circulation judgment is performed; if the reacquired blockchain key anchor analysis result does not meet the blockchain key anchor analysis qualified condition, a prompt of the blockchain key anchor analysis optimization abnormality is sent to the preset personnel.

[0038] It needs to be supplemented that, asFigure 5 As shown, the blockchain key anchoring analysis optimization framework diagram provided by the embodiment of the present application is a blockchain key anchoring analysis optimization framework diagram of the multi-source privacy computing data flow control method based on blockchain provided by the embodiment of the present application, the blockchain key anchoring analysis is performed, whether the blockchain key anchoring analysis result meets the blockchain key anchoring analysis qualified condition is judged, if the multi-source privacy computing data flow control is met, otherwise, the blockchain key anchoring analysis optimization is performed, whether the capacity utilization rate of each parallel subchain does not exceed the preset parallel subchain capacity utilization rate is judged, if it does not meet, the corresponding parallel subchain is marked as a high-capacity parallel subchain, otherwise, the corresponding parallel subchain is marked as a low-capacity parallel subchain, the multi-source privacy computing data asynchronous write operation is performed, whether the blockchain key anchoring analysis result reacquired after the multi-source privacy computing data asynchronous write operation meets the blockchain key anchoring analysis qualified condition is judged, if it meets, the multi-source privacy computing data flow control is executed, otherwise, the prompt of the blockchain key anchoring analysis optimization exception is sent to the preset personnel.

[0039] In the embodiment, by performing the blockchain key anchoring analysis optimization, the multi-source privacy computing data flow control congestion problem caused by the congestion on the blockchain is reduced, the efficiency of the key uploading process and the overall throughput capacity of the data flow control system are improved, the influence of the single node overload on the key anchoring security is effectively avoided, the impact of the multi-source privacy computing data real-time write on the blockchain node is relieved, and the controllability and reliability of the key in the generation, transmission and storage links are strengthened.

[0040] Further, the specific process of performing the multi-source privacy computing data flow determination is as follows: the multi-source privacy computing data flow determination result is obtained by performing ratio processing on the key update on-chain node quantity and the preset key update on-chain node quantity, to reflect the eligibility of the key update on-chain node, and the preset key update on-chain node quantity is represented by the average value of the key update on-chain node quantity in the historical time period; it is judged whether the obtained multi-source privacy computing data flow determination result meets the multi-source privacy computing data flow qualified condition; the key update on-chain node quantity represents the number of nodes that complete the sharding update of the multi-source privacy computing data and submit the confirmation to the smart contract, which is monitored through the node client; the multi-source privacy computing data flow qualified condition means that the multi-source privacy computing data flow determination result is greater than the preset multi-source privacy computing data flow determination result, and the preset multi-source privacy computing data flow determination result is represented by the average value of the multi-source privacy computing data flow determination result in the historical time period; based on the obtained multi-source privacy computing data flow determination result, it is judged whether to perform the multi-source privacy computing data flow control evaluation for evaluating the accuracy of the multi-source privacy computing data flow control, if the multi-source privacy computing data flow determination result meets the multi-source privacy computing data flow qualified condition, then the evaluation is performed, otherwise, the multi-source privacy computing data flow measurement is performed; the multi-source privacy computing data flow measurement means the evaluation of the multi-source privacy computing data for the next multi-source privacy computing data flow determination.

[0041] In the embodiment, by performing the multi-source privacy computing data flow determination, the extent to which the nodes participating in the multi-source privacy computing data update phase are extensive and consistent can be effectively measured and evaluated, ensuring that the key update process has sufficient decentralized verification basis, reducing the security problems caused by node manipulation or tampering of multi-source privacy computing data on the blockchain, and enhancing the dynamic perception and feedback adjustment capability of the multi-source privacy computing data flow state.

[0042] Further, the specific process of performing the multi-source privacy computing data flow measurement is as follows: it is judged whether the obtained blockchain permission change duration measurement result meets the blockchain permission change analysis qualified condition; the blockchain permission change duration measurement result represents the time required from the blockchain permission change taking effect to the completion of the core key update, which is monitored by the node local key manager; the blockchain permission change analysis qualified condition means that the blockchain permission change duration measurement result is less than the preset blockchain permission change duration measurement result and greater than 0, and the preset blockchain permission change duration measurement result is represented by the average value of the blockchain permission change duration measurement result in the historical time period; if the blockchain permission change duration measurement result meets the blockchain permission change analysis qualified condition, the multi-source privacy computing data flow control evaluation is performed, otherwise, a multi-source privacy computing data flow determination exception prompt is sent to the preset personnel.

[0043] In the embodiment, the delay degree from the change of the blockchain permission into effect to the completion of the core key update can be effectively measured by performing the multi-source privacy computing data flow measurement, and the change of the core key permission operation can be ensured to be timely and accurately in effect in the key management, thereby reducing the multi-source privacy computing data loss caused by the delay or failure of the permission update, improving the real-time controllability of the multi-source privacy computing data flow and the consistency of the security policy, ensuring the strict correspondence between the operation permission and the core key use, and enhancing the reliability and security of the overall data flow framework.

[0044] Further, the specific process of performing the multi-source privacy computing data flow control evaluation is as follows: the key fragment transfer traceability rate reflecting the qualified degree of the key fragment transfer record is obtained by ratio processing the number of key fragments with complete query transfer records and the total number of key fragments; the multi-source privacy computing data flow control evaluation result for measuring the integrity degree of the key fragment full life cycle transfer record is obtained by ratio processing the key fragment transfer traceability rate and the preset key fragment transfer traceability rate; the preset key fragment transfer traceability rate is represented by the average value of the historical time period key fragment transfer traceability rate; the number of key fragments with complete query transfer records is monitored through the node management interface, and ratio processing is performed on the number of key fragments with complete query transfer records and the total number of key fragments in the node local database to obtain the multi-source privacy computing data flow control evaluation result for reflecting the qualified degree of the key fragment transfer record; whether to perform the blockchain full node audit measurement for evaluating the audit qualified degree of the multi-source privacy computing data flow is judged based on the obtained multi-source privacy computing data flow control evaluation result, if the multi-source privacy computing data flow control evaluation result is greater than or equal to the preset multi-source privacy computing data flow control evaluation result, the evaluation is performed, otherwise, the multi-source privacy computing data flow control optimization is performed, and the preset multi-source privacy computing data flow control evaluation result is represented by the average value of the historical time period multi-source privacy computing data flow control evaluation result.

[0045] In the embodiment, the key fragment flow traceability rate and the proportion of key fragments with complete query records can be effectively measured by performing the multi-source privacy computing data flow control evaluation, the integrity of the monitoring of the key in the fragmentation, transmission and recombination can be ensured, the possibility of tampering, loss or unauthorized access of the key fragments in the flow process can be reduced, the continuity and reliability based on the blockchain audit can be ensured, the transparency and accountability of the data flow in the multi-source privacy computing environment can be strengthened, so that any abnormal flow behavior can be quickly found and located, and the security resilience and trust level of the multi-source privacy computing data are enhanced.

[0046] Further, the specific process of multi-source privacy computing data flow control optimization is as follows: judging whether the core key consensus duration result is within the preset core key consensus duration result range, the preset core key consensus duration result range being represented by the interval between the maximum value and the minimum value of the historical time period, and including the two endpoints of the maximum value and the minimum value; if yes, marking the corresponding core key consensus duration result as a qualified core key consensus duration result, and performing blockchain full node audit measurement, otherwise, marking the corresponding core key consensus duration result as an abnormal core key consensus duration result, and performing multi-node cross verification for reducing single node misjudgment; the core key consensus duration result represents the time required from the moment when the core key generation transmission to the blockchain consensus network ends to the moment when the node participating in the consensus completes the verification of the operation proposal; the multi-node cross verification means that after updating the multi-source privacy computing data corresponding to the abnormal core key consensus duration result to the protocol exception feature library, the multi-source privacy computing data flow control evaluation is re-performed; if the multi-source privacy computing data flow control evaluation result re-acquired after the multi-node cross verification is greater than or equal to the preset multi-source privacy computing data flow control evaluation result, the blockchain full node audit measurement is performed, otherwise, an multi-node cross verification exception prompt is sent to the preset personnel; the protocol exception feature library is used for accurately identifying the structured feature set of the smart contract protocol itself defects, is specially designed for the abnormal patterns that may occur in the design, execution, interaction, permission control and other life cycle stages of the privacy computing protocol, such as syntax defects, logic conflicts, communication format mismatch, etc., is stored in the form of rule library and dynamically expanded, provides judgment basis for smart contract verification, can effectively distinguish smart contract problems and key synchronization exceptions, reduce misjudgment risk, support verification accuracy improvement, and at the same time provides data support for protocol iteration optimization.

[0047] In the embodiment, by performing multi-source privacy computing data flow control optimization, the efficiency abnormality or potential malicious interference of the blockchain consensus link is identified, the reliability and tamper resistance of the consensus mechanism itself are maintained, the misjudgment caused by smart contract logic errors or inconsistent execution environment is reduced, the diagnosis accuracy of multi-source privacy computing data is improved, the security of the smart contract protocol itself is strengthened, and thus the adaptive ability and long-term stability of the data flow control system are enhanced.

[0048] Further, the specific process of performing the blockchain full node audit measurement is as follows: the node trust state consistency rate is obtained by ratio processing between the number of audited nodes and the total number of full nodes to reflect the eligibility of the uniformity of the trust basis of the entire network; the number of audited nodes represents the number of nodes participating in multi-source privacy computing data audit on the blockchain, monitored by the blockchain node; the total number of full nodes represents the total number of nodes on the blockchain, monitored by the smart contract; the blockchain full node audit measurement result is obtained by ratio processing between the node trust state consistency rate and the preset node trust state consistency rate to measure the matching degree of the blockchain full node key, and the preset node trust state consistency rate is represented by the average value of the historical period node trust state consistency rate; based on the obtained blockchain full node audit measurement result, it is judged whether to perform multi-source privacy computing data verification; when the blockchain full node audit measurement result meets the blockchain audit analysis qualified condition, a multi-source privacy computing data flow control qualified prompt is sent to the preset personnel; the blockchain audit analysis qualified condition means that the blockchain full node audit measurement result is greater than the preset blockchain full node audit measurement result; when the blockchain full node audit measurement result does not meet the blockchain audit analysis qualified condition, the multi-source privacy computing data verification for improving the security of multi-source privacy computing data is performed based on the smart contract before the key fragment holding node receives the key fragment transmission.

[0049] In the embodiment, by performing the blockchain full node audit measurement, the consensus uniformity of the blockchain full node in the key state can be effectively measured, the eligibility of the core key matching and the multi-source privacy computing data transmission is ensured, the inconsistency of the multi-source privacy computing data caused by the node state difference is reduced, the accuracy of identifying the abnormal situation of the blockchain audit is improved, the reliability and attack resistance of the multi-source privacy computing data flow environment are enhanced, and thus the overall security and integrity of the multi-source privacy computing data flow control are comprehensively improved.

[0050] Further, the specific process of multi-source privacy computing data verification is as follows: the number of transmitted key fragments is monitored by the quantum key randomness detection device, and the number of received key fragments is monitored by the quantum key randomness detection device. The ratio processing is carried out to obtain the multi-source privacy computing data verification result to reflect the completeness of the key fragment transmission multi-source privacy computing data, wherein the number of transmitted key fragments refers to the total number of key fragments sent by the blockchain to the data flow control system to realize key recovery; the number of received key fragments refers to the total number of key fragments successfully received and held by the data flow control system and can be used for key recovery; whether the obtained multi-source privacy computing data verification result is equal to 1 is judged; if the multi-source privacy computing data verification result is equal to 1, the corresponding multi-source privacy computing data is marked as qualified multi-source privacy computing data, and a multi-source privacy computing data qualified prompt is sent to the preset personnel to automatically generate a flow record, and a computing data flow control risk evaluation is carried out; if the multi-source privacy computing data verification result is not equal to 1, the corresponding multi-source privacy computing data is marked as abnormal multi-source privacy computing data, and a blockchain full node audit measurement abnormality prompt is sent to the preset personnel; the specific process of computing data flow control risk evaluation is as follows: whether the obtained data flow control risk evaluation result for evaluating the risk level of multi-source privacy computing data is within the preset data flow control risk evaluation result range is judged, the preset data flow control risk evaluation result range is represented by the interval between the maximum value and the minimum value of the historical time period data flow control risk evaluation result, and the preset data flow control risk evaluation result range includes the maximum value and the minimum value; if it is less than the minimum value within the preset data flow control risk evaluation result range, the corresponding multi-source privacy computing data is marked as low-risk computing data; if it is within the preset data flow control risk evaluation result range, the corresponding multi-source privacy computing data is marked as medium-risk computing data; if it is greater than the maximum value within the preset data flow control risk evaluation result range, the corresponding multi-source privacy computing data is marked as high-risk computing data.

[0051] In the embodiment, the multi-source privacy computing data verification is performed to improve the security of multi-source privacy computing data, and the integrity of the multi-source privacy computing data in the flow process is accurately verified, which effectively prevents the multi-source privacy computing data from being tampered with or lost in the transmission link, thereby ensuring the end-to-end authenticity and consistency of the multi-source privacy computing data, enhancing the transparency and auditability of the multi-source privacy computing data track, and strengthening the credibility and security of the multi-source privacy computing data based on the blockchain.

[0052] Among them, the specific acquisition method of the data flow control risk evaluation result R is as follows:

[0053]

[0054] It is necessary to supplement that E is the transmission error rate, which is represented by the ratio of the number of error bytes in the multi-source privacy calculation data to the total number of transmission bytes, monitored by the network protocol analyzer; S is the data transmission volume, representing the total amount of data transmission of multi-source privacy calculation data, monitored by the flow monitoring tool, with the unit of byte; V is the data processing speed, representing the speed of the blockchain processing multi-source privacy calculation data, monitored by the server performance monitoring tool, with the unit of byte per second; F is the number of verification failures, representing the number of smart contract audit failures, monitored by the smart contract audit tool, with the unit of times; T is the transmission time, representing the time required for multi-source privacy calculation data transmission, monitored by the network delay monitoring tool, with the unit of second, H is the total number of verifications, representing the total number of smart contract audits, monitored by the smart contract audit tool, with the unit of times, and T0 is the time for calculating the data flow control risk evaluation, monitored by the network flow analyzer, with the unit of second.

[0055] In this formula, each parameter is not independent, but is related to each other. The larger the data transmission volume, the greater the proportion of multi-source privacy calculation data errors, the greater the risk of data integrity being destroyed, the larger the data transmission volume, the greater the impact range once an error occurs, and the larger the multi-source privacy calculation data volume, the more potential risks such as transmission time consumption, resulting in a larger data flow control risk evaluation result, the faster the data processing speed, the faster the receiving party or processing node can process multi-source privacy calculation data, and the more the total number of verifications. Since the multi-source privacy calculation data is short of time in the transmission and processing link, the risk exposure opportunity is less, the more the number of verification failures, the higher the probability of multi-source privacy calculation data source or integrity anomaly, the greater the security risk of data flow, and the data flow control risk evaluation result also rises accordingly. The longer the transmission time, the longer the data is exposed in the network, the probability of being tampered with or lost increases, and at the same time, it may also cause more process problems due to timeout, thereby increasing the data flow control risk evaluation result.

[0056] Further, as Figure 6As shown, it is a structural schematic diagram of a multi-source privacy computing data flow control system based on a blockchain provided by the embodiment of the application, a blockchain key anchoring analysis module, a multi-source privacy computing data flow determination module, a multi-source privacy computing data flow control evaluation, and a blockchain full node audit measurement module; the blockchain key anchoring analysis module is used to perform blockchain key anchoring analysis in the process of multi-source privacy computing data flow control, first obtain the blockchain key anchoring analysis result, and then judge whether to perform blockchain key anchoring analysis optimization according to the blockchain key anchoring analysis result; the multi-source privacy computing data flow determination module is used to perform multi-source privacy computing data flow determination after the blockchain key anchoring analysis is qualified, first obtain the multi-source privacy computing data flow determination result, and then judge whether to perform multi-source privacy computing data flow determination according to the multi-source privacy computing data flow determination result; the multi-source privacy computing data flow control evaluation module is used to perform multi-source privacy computing data flow control evaluation after the multi-source privacy computing data flow determination is completed, first obtain the multi-source privacy computing data flow control evaluation result, and then judge whether to perform multi-source privacy computing data flow control optimization according to the multi-source privacy computing data flow control evaluation result; the blockchain full node audit measurement module is used to perform blockchain full node audit measurement after the multi-source privacy computing data flow control evaluation is qualified, first obtain the blockchain full node audit measurement result, and then judge whether to perform multi-source privacy computing data verification according to the blockchain full node audit measurement result.

[0057] In summary, by performing blockchain key anchoring analysis to obtain the blockchain key anchoring analysis result, the embodiment of the application helps to accurately evaluate the consistency degree of the core key approval of the blockchain node participating in the key generation, improves the security and credibility of the key management of the blockchain, thereby improving the reliability of the multi-source privacy computing data flow, by performing multi-source privacy computing data flow determination to obtain the multi-source privacy computing data flow determination result, helps to accurately evaluate the qualification degree of the key update on-chain node, improves the qualification and stability of the multi-source privacy computing data flow on the blockchain, ensures the security of the multi-source privacy computing data flow control, by performing multi-source privacy computing data flow control evaluation to obtain the multi-source privacy computing data flow control evaluation result, helps to accurately evaluate the integrity degree of the key fragment full life cycle circulation record, improves the authority control and anti-leakage ability of the multi-source privacy computing data flow control, enhances the security and controllability in the multi-source privacy computing data flow control, by performing blockchain full node audit measurement to obtain the blockchain full node audit measurement result, helps to accurately evaluate the integrity degree of the key fragment transmission multi-source privacy computing data, improves the integrity and transparency of the blockchain consensus, thereby improving the public credibility and traceability of the multi-source privacy computing data verification.

[0058] The above merely provides the specific implementation of the present application, but the protection scope of the present application is not limited thereto, any person skilled in the art can easily think of the change or replacement within the technical range disclosed by the present application, which should be covered in the protection scope of the present application. Therefore, the protection scope of the present application should be subject to the protection scope of the claims.

Claims

1. A blockchain-based multi-source privacy computing data flow control method, characterized in that, The method comprises the following steps: In the multi-source privacy computing data flow control process, the blockchain key anchoring analysis is performed, the blockchain key anchoring analysis result is obtained, and it is judged whether the blockchain key anchoring analysis optimization is performed according to the blockchain key anchoring analysis result, the blockchain key anchoring analysis optimization is used to improve the consistency and accuracy of the blockchain key consensus; After the blockchain key anchoring analysis is qualified, the multi-source privacy computing data flow determination is performed, the multi-source privacy computing data flow determination result is obtained, and it is judged whether the multi-source privacy computing data flow measurement is performed according to the multi-source privacy computing data flow determination result, the multi-source privacy computing data flow measurement is used to evaluate the delay degree of the blockchain permission change time length; After the multi-source privacy computing data flow determination is completed, the multi-source privacy computing data flow control evaluation is performed, the multi-source privacy computing data flow control evaluation result is obtained, and it is judged whether the multi-source privacy computing data flow control optimization is performed according to the multi-source privacy computing data flow control evaluation result, the multi-source privacy computing data flow control optimization is used to improve the consistency degree of the key state between the blockchain nodes; After the multi-source privacy computing data flow control evaluation is qualified, the blockchain full node audit measurement is performed, the blockchain full node audit measurement result is obtained, and it is judged whether the multi-source privacy computing data verification is performed according to the blockchain full node audit measurement result, the multi-source privacy computing data verification is used to improve the security of the multi-source privacy computing data in the audit process and the accuracy of the multi-source privacy computing data risk evaluation. 2.The blockchain-based multi-source privacy computing data flow circulation control method according to claim 1, characterized in that, The execution of the blockchain key anchoring analysis, the blockchain key anchoring analysis result is obtained, and it is judged whether the blockchain key anchoring analysis optimization is performed according to the blockchain key anchoring analysis result, the specific process is as follows: The execution of the blockchain key anchoring analysis is used to evaluate the qualified degree of the generation of the blockchain core key; The ratio of the key generation consensus achievement rate to the preset key generation consensus achievement rate is processed to obtain the blockchain key consensus achievement result for measuring the consistency degree of the core key approval of the blockchain node participating in the key generation; The ratio of the preset blockchain write delay to the blockchain write delay is processed to obtain the blockchain write time length result for reflecting the transmission speed of the core key from generation to on-chain storage; It is judged whether the blockchain key anchoring analysis result including the blockchain key consensus achievement result and the blockchain write time length result meets the blockchain key anchoring analysis qualified condition; The blockchain key anchoring analysis qualified condition refers to the blockchain key consensus achievement qualified condition and the blockchain write time length achievement qualified condition; The blockchain key consensus achievement qualified condition indicates that the blockchain key consensus achievement result is greater than the preset blockchain key consensus achievement result; The blockchain write time length achievement qualified condition indicates that the blockchain write time length result is greater than the preset blockchain write time length result; The key generation consensus achievement rate is represented by the ratio of the number of nodes that successfully verify and confirm the core key to the number of participating nodes, which is used to reflect the qualified degree of the core key consensus achievement. If the blockchain key anchoring analysis result meets the blockchain key anchoring analysis qualified condition, a multi-source privacy computing data flow circulation judgment for evaluating the qualified degree of multi-source privacy computing data flow circulation is performed, otherwise, a blockchain key anchoring analysis optimization is performed. The blockchain key anchoring analysis optimization means that the blockchain sharding operation for relieving the blocking problem of multi-source privacy computing data flow circulation and the multi-source privacy computing data asynchronous writing operation for reducing the blocking situation during core key uploading are performed in sequence. 3.The blockchain-based multi-source privacy computing data flow circulation control method according to claim 2, characterized in that, The specific process of the blockchain key anchoring analysis optimization is as follows: It is judged whether the capacity utilization rate of each parallel subchain is not more than the preset parallel subchain capacity utilization rate; If the capacity utilization rate of each parallel subchain is not more than the preset parallel subchain capacity utilization rate, the corresponding parallel subchain is marked as a low-capacity parallel subchain, and the low-capacity parallel subchains are sorted in ascending order according to the corresponding parallel subchain capacity utilization rate, otherwise, the corresponding parallel subchain is marked as a high-capacity parallel subchain, and a parallel subchain capacity abnormal prompt is sent to the preset personnel; The parallel subchain capacity analysis is used to evaluate the capacity utilization degree of each parallel subchain; The blockchain sharding operation means that the blockchain network is split into parallel subchains based on a blockchain sharding method and a blockchain segmentation ratio, and the core keys are sequentially stored in the low-capacity parallel subchains in ascending order according to the parallel subchain capacity utilization rate; The blockchain segmentation ratio is obtained by difference calculation of the blockchain capacity and the blockchain used capacity, and then by ratio processing of the blockchain capacity; If the blockchain key anchoring analysis result obtained after the blockchain sharding operation meets the blockchain key anchoring analysis qualified condition, the multi-source privacy computing data flow circulation judgment is performed, otherwise, the multi-source privacy computing data asynchronous writing operation is performed; The multi-source privacy computing data asynchronous writing operation specifically includes that it is first judged whether the core key transmission result temporarily stored in the low-capacity parallel subchain is less than or equal to the preset core key transmission result; If the core key transmission result is less than or equal to the preset core key transmission result, it is marked as a low-priority key, otherwise, it is marked as a high-priority key, and a core key abnormal prompt is sent to the preset personnel; For the low-priority key, it is temporarily stored in the memory buffer pool, and when the blockchain capacity is not more than the preset blockchain capacity, the corresponding core key is uploaded in batches; If the blockchain key anchoring analysis result obtained after the multi-source privacy computing data asynchronous writing operation meets the blockchain key anchoring analysis qualified condition, the multi-source privacy computing data flow circulation judgment is performed; If the obtained blockchain key anchoring analysis result does not meet the blockchain key anchoring analysis qualified condition, a blockchain key anchoring analysis optimization abnormal prompt is sent to the preset personnel.

4. The blockchain-based multi-source privacy computing data flow circulation control method according to claim 3, characterized in that, The specific process of performing the multi-source privacy computing data flow circulation judgment is as follows: The multi-source privacy computing data flow circulation judgment result is obtained by ratio processing of the key update on-chain node number and the preset key update on-chain node number to reflect the qualification of the key update on-chain node; It is judged whether the obtained multi-source privacy computing data flow circulation judgment result meets the multi-source privacy computing data flow circulation qualified condition; The key update chain node quantity indicates the number of nodes that complete the sharding update of multi-source privacy computing data and submit confirmation to the smart contract; The multi-source privacy computing data circulation qualified condition indicates that the multi-source privacy computing data circulation judgment result is greater than a preset multi-source privacy computing data circulation judgment result; Based on the obtained multi-source privacy computing data circulation judgment result, it is judged whether to perform multi-source privacy computing data circulation control evaluation for evaluating the accuracy of multi-source privacy computing data circulation control. If the multi-source privacy computing data circulation judgment result meets the multi-source privacy computing data circulation qualified condition, it is executed, otherwise, multi-source privacy computing data circulation measurement is performed. 5.The blockchain-based multi-source privacy computing data flow circulation control method according to claim 4, characterized in that, The specific process of performing multi-source privacy computing data circulation measurement is as follows: It is judged whether the obtained blockchain permission change duration measurement result meets the blockchain permission change analysis qualified condition; The blockchain permission change duration measurement result indicates the time required from the monitoring of the blockchain permission change effective time by the node local key manager to the completion of the core key update; If the blockchain permission change duration measurement result meets the blockchain permission change analysis qualified condition, multi-source privacy computing data circulation control evaluation is performed, otherwise, a multi-source privacy computing data circulation judgment exception prompt is sent to the preset personnel; The blockchain permission change analysis qualified condition indicates that the blockchain permission change duration measurement result is less than a preset blockchain permission change duration measurement result and greater than 0.

6. The blockchain-based multi-source privacy computing data flow circulation control method according to claim 5, characterized in that, The specific process of performing multi-source privacy computing data circulation control evaluation is as follows: The key fragment transfer traceability rate reflecting the qualified degree of key fragment transfer record is obtained by ratio processing of the number of key fragments that can be completely queried and transferred and the total number of key fragments; The multi-source privacy computing data circulation control evaluation result for measuring the integrity degree of the whole life cycle transfer record of the key fragment is obtained by ratio processing of the key fragment transfer traceability rate and a preset key fragment transfer traceability rate; Based on the obtained multi-source privacy computing data circulation control evaluation result, it is judged whether to perform blockchain full node audit measurement for evaluating the qualified degree of multi-source privacy computing data circulation audit. If the multi-source privacy computing data circulation control evaluation result is greater than or equal to a preset multi-source privacy computing data circulation control evaluation result, it is executed, otherwise, multi-source privacy computing data circulation control optimization is performed.

7. The blockchain-based multi-source privacy computing data flow circulation control method according to claim 6, characterized in that, The specific process of performing multi-source privacy computing data circulation control optimization is as follows: It is judged whether the core key consensus duration result is within the preset core key consensus duration result range; If it is, the corresponding core key consensus duration result is marked as a qualified core key consensus duration result, and the blockchain full node audit measurement is performed, otherwise, the corresponding core key consensus duration result is marked as an abnormal core key consensus duration result, and multi-node cross verification for reducing single node misjudgment is performed; The multi-node cross verification indicates that after the multi-source privacy computing data corresponding to the abnormal core key consensus duration result is updated to the protocol exception feature library, the multi-source privacy computing data circulation control evaluation is re-executed; The specific process of performing multi-source privacy computing data circulation control optimization is as follows: If the multi-source privacy computing data flow control evaluation result re-acquired after multi-node cross verification is greater than or equal to the preset multi-source privacy computing data flow control evaluation result, a blockchain full node audit measurement is performed, otherwise, a multi-node cross verification exception prompt is sent to the preset personnel. 8.The blockchain-based multi-source privacy computing data flow circulation control method according to claim 7, characterized in that, The specific process of performing the blockchain full node audit measurement is as follows: The node trust state consistency rate is obtained by ratio processing between the number of audited nodes and the total number of full nodes to reflect the uniformity of the trust basis of the entire network; The blockchain full node audit measurement result is obtained by ratio processing between the node trust state consistency rate and the preset node trust state consistency rate to measure the matching degree of the blockchain full node key; Based on the obtained blockchain full node audit measurement result, it is judged whether to perform multi-source privacy computing data verification; When the blockchain full node audit measurement result meets the blockchain audit analysis qualified condition, a multi-source privacy computing data flow control qualified prompt is sent to the preset personnel; The blockchain audit analysis qualified condition means that the blockchain full node audit measurement result is greater than the preset blockchain full node audit measurement result; When the blockchain full node audit measurement result does not meet the blockchain audit analysis qualified condition, before the key fragment holding node receives the key fragment transmission, the multi-source privacy computing data verification for improving the security of multi-source privacy computing data is performed based on the smart contract. 9.The blockchain-based multi-source privacy computing data flow circulation control method according to claim 8, characterized in that, The specific process of the multi-source privacy computing data verification is as follows: The multi-source privacy computing data verification result is obtained by ratio processing between the number of transmitted key fragments and the number of received key fragments to reflect the completeness of the key fragment transmission multi-source privacy computing data; Based on the obtained multi-source privacy computing data verification result, it is judged whether it is equal to 1; If the multi-source privacy computing data verification result is equal to 1, the corresponding multi-source privacy computing data is marked as qualified multi-source privacy computing data, and a multi-source privacy computing data qualified prompt is sent to the preset personnel to automatically generate a flow record and perform a computing data flow control risk evaluation; If the multi-source privacy computing data verification result is not equal to 1, the corresponding multi-source privacy computing data is marked as abnormal multi-source privacy computing data, and a blockchain full node audit measurement exception prompt is sent to the preset personnel; The specific process of the computing data flow control risk evaluation is as follows: It is judged whether the data flow control risk evaluation result obtained for evaluating the risk level of multi-source privacy computing data is within the preset data flow control risk evaluation result range; If it is less than the minimum value within the preset data flow control risk evaluation result range, the corresponding multi-source privacy computing data is marked as low-risk computing data; If it is within the preset data flow control risk evaluation result range, the corresponding multi-source privacy computing data is marked as medium-risk computing data; If it is greater than the maximum value within the preset data flow control risk evaluation result range, the corresponding multi-source privacy computing data is marked as high-risk computing data.

10. A blockchain-based multi-source privacy computing data flow control system, applying the blockchain-based multi-source privacy computing data flow control method of any one of claims 1-9, characterized in that, It includes: A blockchain key anchoring analysis module, a multi-source privacy computing data flow determination module, a multi-source privacy computing data flow control evaluation and a blockchain full node audit measurement module; The blockchain key anchoring analysis module is configured to perform blockchain key anchoring analysis in the multi-source privacy computing data flow control process, obtain a blockchain key anchoring analysis result, and determine whether to perform blockchain key anchoring analysis optimization according to the blockchain key anchoring analysis result; The multi-source privacy computing data flow determination module is configured to perform multi-source privacy computing data flow determination after the blockchain key anchoring analysis is qualified, obtain a multi-source privacy computing data flow determination result, and determine whether to perform multi-source privacy computing data flow determination according to the multi-source privacy computing data flow determination result; The multi-source privacy computing data flow control evaluation module is configured to perform multi-source privacy computing data flow control evaluation after the multi-source privacy computing data flow determination ends, obtain a multi-source privacy computing data flow control evaluation result, and determine whether to perform multi-source privacy computing data flow control optimization according to the multi-source privacy computing data flow control evaluation result; The blockchain full node audit measurement module is configured to perform blockchain full node audit measurement after the multi-source privacy computing data flow control evaluation is qualified, obtain a blockchain full node audit measurement result, and determine whether to perform multi-source privacy computing data verification according to the blockchain full node audit measurement result.

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