Distributed data compliance examination method and system

Abstract

The invention discloses a distributed data compliance review method and system, and relates to the technical field of data processing, and the method comprises the steps: deploying a unified compliance code for each node in a block chain, and carrying out the preliminary review of a transaction; billing nodes are selected through a consensus algorithm, and compliance review is carried out through a deployed compliance verification algorithm; if the transaction is not compliant, directly abandoning the transaction data, and if the transaction is compliant, packaging the compliant transaction data and the verification process log thereof into a block and then carrying out Hash calculation to generate a block Hash; and the accounting node broadcasts the constructed block to other nodes in the network, and judges whether to accept the block and continue to participate in the consensus process through a node mutual verification mechanism. According to the method, malicious nodes are prevented from behaving and skipping compliance verification behaviors; and meanwhile, overload of some nodes due to too high computing power can be prevented, and the stability and reliability of the whole block chain network are improved.

Description

Technical Field

[0001] The present invention relates to the field of data processing technology, and in particular to a distributed data compliance review method and system. Background Art

[0002] Distributed data processing systems, due to their complexity and multi-node characteristics, place higher demands on data compliance review. Traditional data compliance review methods are often applicable to static, limited data sets, while data in distributed systems is dynamic, continuous, and rapidly changing. How to ensure data compliance in a distributed environment, especially in the areas of data collection, storage, processing, transmission, and use, has become an urgent problem to be solved.

[0003] For example, an existing Chinese patent with publication number CN111783144A discloses a data processing method and device based on blockchain, wherein the blockchain includes a business platform node device, and the data processing method based on blockchain includes: the business platform node device obtains the pending business data generated by at least one business processor for business processing for a target user, extracts entities based on the pending business data, and generates shared pending business data according to the association relationship between the entities in the extraction result, and sends a first transaction to the blockchain, wherein the first transaction includes a first digital summary of the shared pending business data, so that the first transaction is stored in the distributed database of the blockchain after being verified by the blockchain consensus; uploading the pending business data to the blockchain in this way is conducive to ensuring the credibility of the pending business data in the process of conducting a compliance review of the business processor or business platform based on the pending business data.

[0004] However, this design often leads to slow transaction processing in the consensus mechanism of blockchain (such as proof of work, proof of equity, etc.), which may become a performance bottleneck, especially when processing a large amount of business data to be reviewed. The distributed database of blockchain may face efficiency problems when storing and retrieving large amounts of data, especially when a quick response to compliance review requests is required. To this end, the present invention provides a distributed data compliance review method and system. Summary of the invention

[0005] The purpose of the present invention is to provide a distributed data compliance review method and system to solve the existing problems raised in the above background technology.

[0006] To achieve the above object, the present invention provides the following technical solutions: In a first aspect, the present invention provides a distributed data compliance review method, comprising the following steps: S1. Deploy a unified compliance code for each node in the blockchain to conduct a preliminary review of transactions; S2. Elect accounting nodes through consensus algorithm and conduct compliance review through the deployed compliance verification algorithm; S3. If the transaction is compliant, the compliant transaction data and its verification process log are packaged into blocks. If the transaction is not compliant, the transaction data is directly discarded. S4. Perform hash calculation on the block obtained in S3 to generate a block hash, which is used as a unique identifier of the block. S5. The accounting node broadcasts the constructed block to other nodes in the network, and through the node mutual verification mechanism, determines whether to accept the block and continue to participate in the consensus process.

[0007] The present invention is further improved in that the node mutual verification mechanism includes: after the accounting node completes the construction of the block, the constructed block and its corresponding hash value are broadcasted to all other nodes in the network through the network; When the receiving node receives a block and its hash value, it first uses the same hash algorithm as the sending node to calculate the received block content to obtain a new hash value; then, it compares the new hash value with the hash value of the parent in the block. If the two are the same, the independent compliance review strategy is run. If they are not the same, the block will be rejected.

[0008] A further improvement of the present invention is that the independent compliance review strategy includes: performing an independent compliance review by using the same verification logic and rules as the sending node for each transaction data in the block to check whether the transaction data complies with the compliance standards specified by the network; then verifying whether the summary in the block hash is consistent with the hash value of the verification process log provided by the sending node. If they are consistent, broadcasting the block to other nodes in the network through a consensus mechanism; after verifying the correctness and compliance of the block, other nodes add it to their own blockchain copies to reach a consensus.

[0009] A further improvement of the present invention is that the consensus mechanism is implemented through proof of work, firstly a difficulty target is obtained through a target difficulty search adjustment algorithm; the blockchain network finds a hash value that is less than or equal to the difficulty target; the nodes with the same hash value in the blockchain perform a hash operation on the block header information and a random number Nonce; if the calculated hash value does not meet the difficulty target, the Nonce value is adjusted and the hash operation is performed again until a hash value that meets the difficulty target is found.

[0010] The present invention is further improved in that the target difficulty search adjustment algorithm includes: recording the timestamp of each block being mined and the difficulty target within the past time T; selecting the past N blocks as the analysis window, calculating the average generation time of the blocks within the analysis window, analyzing the average generation time of the blocks within the historical analysis window through exponential smoothing technology, identifying the long-term trend of network computing power, and obtaining the network computing power level within the future time T and block generation time ; Set the target block generation time , an adjustment coefficient is obtained through a computing power dispersion strategy, and the adjustment coefficient is multiplied by the difficulty target to obtain a new difficulty target.

[0011] A further improvement of the present invention is that the computing power dispersion strategy includes: extracting the real-time load of the system and setting the target load, taking the ratio of the real-time load to the target load as the first adjustment coefficient, and taking the ratio of the product of the current network computing power level and the predicted block generation time to the product of the predicted network computing power level and the target block generation time as the second adjustment coefficient; the adjustment coefficient is calculated by multiplying the first adjustment coefficient by the second adjustment coefficient.

[0012] A further improvement of the present invention is that the specific steps of S2 include: a user or an external system submits transaction data through a blockchain, and a bookkeeping node elected by a consensus algorithm serves as a verifier for the current round and first receives the transaction data; the bookkeeping node loads and initializes a compliance verification algorithm deployed thereon; a sensitive vocabulary data set is created, and natural language processing technology is used to analyze the text content in the transaction data, and in combination with the sensitive vocabulary data set, it is determined whether there are sensitive words in the transaction data; if not, the transaction data is determined to be compliant and the transaction is continued to be processed; if so, the transaction data is determined to be non-compliant, the transaction is rejected, and relevant logs are recorded for subsequent audits.

[0013] In a second aspect, the present invention provides a distributed data compliance review system, comprising: The compliance verification code deployment module deploys a unified compliance code for each node in the blockchain and performs a preliminary review of transactions; The transaction data compliance review module elects accounting nodes through a consensus algorithm and conducts compliance review through a deployed compliance verification algorithm. If the transaction is compliant, the compliant transaction data and its verification process log are packaged into blocks. If the transaction is not compliant, the transaction data is directly discarded. The block construction and hash generation module performs hash calculation on the blocks obtained in the transaction data compliance review module to generate a block hash, which is used as the unique identifier of the block; In the inter-node verification and consensus module, the accounting node broadcasts the constructed block to other nodes in the network midpoint, and through the node mutual verification mechanism, determines whether to accept the block and continue to participate in the consensus process.

[0014] In a third aspect, the present invention provides an electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor implements the above-mentioned distributed data compliance review method when executing the computer program.

[0015] In a fourth aspect, the present invention provides a computer-readable storage medium having a computer program stored thereon, and when the computer program is executed by a processor, the above-mentioned distributed data compliance review method is implemented.

[0016] Compared with the prior art, the present invention has the following beneficial effects: 1. The present invention firstly selects accounting nodes through consensus algorithm to process transactions, which reduces redundant work between nodes and improves the efficiency of transaction processing. At the same time, the combination of compliance review and block building process enables compliant transactions to be quickly packaged into blocks and broadcast to other nodes in the network; 2. The node mutual verification mechanism ensures the correctness and compliance of the block. The receiving node calculates the hash value of the block and compares it with the hash value provided by the sending node, and runs an independent compliance review strategy to effectively prevent malicious nodes or data tampering; 3. Based on the traditional blockchain consensus mechanism, a process of mutual verification of review results between nodes is introduced, which not only prevents malicious nodes from doing evil and skipping compliance verification, but also ensures that all nodes in the entire network unanimously recognize the compliance of transaction data; 4. The computing power dispersion strategy achieves reasonable distribution of computing power and load balancing by considering the real-time system load and target load, as well as the prediction of network computing power level and block generation time; it helps prevent some nodes from being overloaded due to excessive computing power, and improves the stability and reliability of the entire blockchain network. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] Figure 1 This is a flow chart of a distributed data compliance review method of the present invention; Figure 2 This is a flow chart of a node mutual verification mechanism of a distributed data compliance review method of the present invention; Figure 3 This is a framework diagram of a distributed data compliance review system of the present invention. DETAILED DESCRIPTION

[0018] The technical solution of the present invention is described in detail below through the accompanying drawings and specific embodiments. It should be understood that the embodiments of the present invention and the specific features in the embodiments are detailed descriptions of the technical solution of the present invention, rather than limitations on the technical solution of the present invention. The embodiments of the present invention and the technical features in the embodiments may be combined with each other unless there is a conflict.

[0019] The term "and / or" is only a description of the association relationship between related objects, indicating that there can be three relationships. For example, A and / or B can mean: A exists alone, A and B exist at the same time, and B exists alone. In addition, the character " / " generally indicates that the related objects are in an "or" relationship.

[0020] Example 1

[0021] Figure 1 A flow chart of a distributed data compliance review method disclosed in this embodiment is shown, and the steps are as follows: S1. Deploy a unified compliance code for each node in the blockchain to conduct a preliminary review of transactions; S2. The accounting nodes are elected through the consensus algorithm, and the compliance review is conducted through the deployed compliance verification algorithm. The specific steps include: the user or external system submits the transaction data through the blockchain, and the accounting node elected through the consensus algorithm serves as the verifier of the current round and first receives the transaction data; the accounting node loads and initializes the compliance verification algorithm deployed on it, prepares to review the transaction data, and configures the necessary computing resources, memory and storage space to ensure that the verification process can proceed smoothly; creates a sensitive vocabulary data set, uses natural language processing technology to analyze the text content in the transaction data, and combines the sensitive vocabulary data set to determine whether there are sensitive words in the transaction data. If not, the transaction data is judged to be compliant and the transaction continues to be processed; if so, the transaction data is judged to be non-compliant, the transaction is rejected, and relevant logs are recorded for subsequent audits.

[0022] S3. If the transaction is compliant, the compliant transaction data and its verification process log are packaged into blocks. If the transaction is not compliant, the transaction data is directly discarded. S4. Perform hash calculation on the block obtained in S3 to generate a block hash, which is used as a unique identifier of the block. S5. The accounting node broadcasts the constructed block to other nodes in the network, and through the node mutual verification mechanism, determines whether to accept the block and continue to participate in the consensus process.

[0023] Figure 2A flowchart of a node mutual verification mechanism of a distributed data compliance review method disclosed in this embodiment is shown, and the node mutual verification mechanism includes: after the accounting node completes the construction of the block, the constructed block and its corresponding hash value are broadcasted to all other nodes in the network through the network; When the receiving node receives a block and its hash value, it first uses the same hash algorithm as the sending node to calculate the received block content to obtain a new hash value; then, it compares the new hash value with the hash value of the parent in the block. If the two are the same, the independent compliance review strategy is run. If they are different, it indicates that the block content may have been tampered with and the block will be rejected.

[0024] The independent compliance review strategy includes: conducting independent compliance review by using the same verification logic and rules as the sending node for each transaction data in the block to check whether the transaction data meets the compliance standards specified by the network; then verifying whether the summary in the block hash is consistent with the hash value of the verification process log provided by the sending node. If consistent, the block is broadcast to other nodes in the network through the consensus mechanism; after verifying the correctness and compliance of the block, other nodes will add it to their own blockchain copies to reach a consensus. Compliance codes are used to identify potential violations in transactions.

[0025] The consensus mechanism is implemented through proof of work. First, the difficulty target is obtained through the target difficulty search adjustment algorithm; the difficulty target determines the amount of calculation required to find a hash value that meets the conditions; the blockchain network finds a hash value that is less than or equal to the difficulty target; the implementation method is: the blockchain network will regularly adjust the difficulty target according to the current network computing power and block generation speed. This adjustment mechanism ensures that the block generation rate can remain relatively stable regardless of how the computing power changes.

[0026] The nodes with the same hash value in the blockchain perform hash operations on the block header information (including the hash value of the previous block, timestamp, transaction information, etc.) and a constantly changing random number (Nonce); if the calculated hash value does not meet the difficulty target, the Nonce value is adjusted and the hash operation is performed again until a hash value that meets the difficulty target is found.

[0027] The target difficulty search and adjustment algorithm includes: recording the timestamp of each block being mined and the difficulty target within the past time T; selecting the past N blocks as the analysis window, calculating the average block generation time within the analysis window, analyzing the average block generation time within the historical analysis window through exponential smoothing technology, identifying the long-term trend of network computing power, and obtaining the network computing power level within the future time T. and block generation time ; Set the target block generation time , an adjustment coefficient is obtained through a computing power dispersion strategy, and the adjustment coefficient is multiplied by the old difficulty target to obtain a new difficulty target.

[0028] The computing power dispersion strategy includes: extracting the real-time load of the system and setting the target load, taking the ratio of the real-time load to the target load as the first adjustment coefficient, taking the ratio of the product of the current network computing power level and the predicted block generation time to the product of the predicted network computing power level and the target block generation time as the second adjustment coefficient; the adjustment coefficient is calculated by multiplying the first adjustment coefficient by the second adjustment coefficient. In this embodiment, the higher the computing power, the shorter the generation time; the greater the difficulty, the longer the generation time.

[0029] The purpose of combining the computing power dispersion strategy with the adjustment coefficient factor is to optimize system performance, improve resource utilization, and cope with fluctuations in computing power demand by dynamically adjusting the allocation of computing power resources.

[0030] When the system load is too high, computing resources can be increased; when business demand decreases, computing resources can be reduced.

[0031] The threshold and weight may be set by default according to the present invention, or may be set by an operator.

[0032] Example 2

[0033] Figure 3 The framework diagram of a distributed data compliance review system of the present invention is shown. Based on the same inventive concept as that of Example 1, the present invention provides a distributed data compliance review system, including: The compliance verification code deployment module deploys a unified compliance code for each node in the blockchain and performs a preliminary review of transactions; The transaction data compliance review module elects accounting nodes through a consensus algorithm and conducts compliance review through a deployed compliance verification algorithm. If the transaction is compliant, the compliant transaction data and its verification process log are packaged into blocks. If the transaction is not compliant, the transaction data is directly discarded. The block construction and hash generation module performs hash calculation on the blocks obtained in the transaction data compliance review module to generate a block hash, which is used as the unique identifier of the block; In the inter-node verification and consensus module, the accounting node broadcasts the constructed block to other nodes in the network, and through the node mutual verification mechanism, determines whether to accept the block and continue to participate in the consensus process.

[0034] The inter-node verification and consensus module includes an independent compliance review unit and a target difficulty search adjustment algorithm unit. The independent compliance review unit is used to verify whether the summary in the block hash is consistent with the hash value of the verification process log provided by the sending node. If they are consistent, the block is broadcast to other nodes in the network through the consensus mechanism; after verifying the correctness and compliance of the block, other nodes will add it to their own blockchain copies to reach a consensus; the target difficulty search adjustment algorithm unit is used to adaptively obtain the difficulty target through a computing power dispersion strategy.

[0035] Example 3

[0036] This embodiment discloses an electronic device, including a power supply, an interface, a memory, a central processing unit, and a computer program stored in the memory and executable on the central processing unit. When the central processing unit executes the computer program, a distributed data compliance review provided by the above methods is implemented. The interface includes a network interface and a data interface. The network interface includes a wired or wireless interface, and the data interface includes an input or output interface.

[0037] Since the electronic device introduced in this embodiment is an electronic device used to implement a distributed data compliance review in the embodiment of this application, based on a distributed data compliance review method introduced in the embodiment of this application, a person skilled in the art can understand the specific implementation of the electronic device of this embodiment and its various variations, so how the electronic device implements the method in the embodiment of this application is not described in detail here. As long as a person skilled in the art implements an electronic device used in a distributed data compliance review in the embodiment of this application, it belongs to the scope of protection of this application.

[0038] Example 4

[0039] This embodiment discloses a computer-readable storage medium, on which a computer program is stored. When the computer program is executed, the above-mentioned distributed data compliance review method is implemented.

[0040] It will be appreciated by those skilled in the art that embodiments of the present invention may be provided as methods, systems, or computer program products. Therefore, the present invention may take the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware. Furthermore, the present invention may take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0041] The present invention is described with reference to flowcharts and / or block diagrams of methods, devices (systems), and computer program products according to embodiments of the present invention. It should be understood that each process and / or block in the flowchart and / or block diagram, as well as the combination of processes and / or blocks in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 A process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0042] These computer program instructions may also be stored in a computer readable memory capable of directing a computer or other programmable data processing device to operate in a specific manner, so that the instructions stored in the computer readable memory produce an article of manufacture including an instruction device, which implements the process Figure 1 A process or multiple processes and / or boxes Figure 1 A function specified in one or more boxes.

[0043] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operating steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing instructions for implementing the process in the computer or other programmable device. Figure 1 A process or multiple processes and / or boxes Figure 1 The steps for the functions specified in one or more boxes.

[0044] The embodiments of the present invention are described above in conjunction with the accompanying drawings, but the present invention is not limited to the above-mentioned specific implementation methods. The above-mentioned specific implementation methods are merely illustrative and not restrictive. Under the enlightenment of the present invention, ordinary technicians in this field can also make many forms without departing from the scope of protection of the purpose of the present invention and the claims, which all fall within the protection of the present invention.

Claims

1. A distributed data compliance review method, characterized by: The following steps are involved: S1. Deploy a unified compliance code for each node in the blockchain to conduct a preliminary review of transactions; S2. Elect accounting nodes through consensus algorithm and conduct compliance review through the deployed compliance verification algorithm; S3. If the transaction is compliant, the compliant transaction data and its verification process log are packaged into blocks. If the transaction is not compliant, the transaction data is directly discarded. S4. Perform hash calculation on the block obtained in S3 to generate a block hash, which is used as a unique identifier of the block. S5. The accounting node broadcasts the constructed block to other nodes in the network, and through the node mutual verification mechanism, determines whether to accept the block and continue to participate in the consensus process.

2. A distributed data compliance review method according to claim 1, characterized in that: The node mutual verification mechanism includes: after the accounting node completes the construction of the block, the constructed block and its corresponding hash value are broadcasted to all other nodes in the network through the network; When the receiving node receives a block and its hash value, it first uses the same hash algorithm as the sending node to calculate the received block content to obtain a new hash value; then, it compares the new hash value with the hash value of the parent in the block. If the two are the same, the independent compliance review strategy is run. If they are different, the block will be rejected.

3. A distributed data compliance review method according to claim 2, characterized in that: The independent compliance review strategy includes: conducting an independent compliance review by using the same verification logic and rules as the sending node for each transaction data in the block to check whether the transaction data complies with the compliance standards specified by the network; then verifying whether the summary in the block hash is consistent with the hash value of the verification process log provided by the sending node. If they are consistent, the block is broadcast to other nodes in the network through a consensus mechanism; after verifying the correctness and compliance of the block, other nodes add it to their own blockchain copies to reach a consensus.

4. A distributed data compliance review method according to claim 3, characterized in that: The consensus mechanism is implemented through proof of work. First, the difficulty target is obtained through the target difficulty search adjustment algorithm; the blockchain network finds a hash value less than or equal to the difficulty target; the nodes with the same hash value in the blockchain perform hash operations on the block header information and a random number Nonce; if the calculated hash value does not meet the difficulty target, the Nonce value is adjusted and the hash operation is performed again until a hash value that meets the difficulty target is found.

5. A distributed data compliance review method according to claim 4, characterized in that: The target difficulty search and adjustment algorithm includes: recording the timestamp of each block being mined and the difficulty target within the past time T; selecting the past N blocks as the analysis window, calculating the average block generation time within the analysis window, analyzing the average block generation time within the historical analysis window through exponential smoothing technology, identifying the long-term trend of network computing power, and obtaining the network computing power level within the future time T. and block generation time ; Set the target block generation time , an adjustment coefficient is obtained through a computing power dispersion strategy, and the adjustment coefficient is multiplied by the difficulty target to obtain a new difficulty target.

6. A distributed data compliance review method according to claim 5, characterized in that: The computing power dispersion strategy includes: extracting the real-time load of the system and setting the target load, taking the ratio of the real-time load to the target load as the first adjustment coefficient, and taking the ratio of the product of the current network computing power level and the predicted block generation time to the product of the predicted network computing power level and the target block generation time as the second adjustment coefficient; the adjustment coefficient is calculated by multiplying the first adjustment coefficient by the second adjustment coefficient.

7. A distributed data compliance review method according to claim 1, characterized in that: The specific steps of S2 include: the user or external system submits transaction data through the blockchain, and the accounting node elected by the consensus algorithm serves as the validator of the current round and first receives the transaction data; the accounting node loads and initializes the compliance verification algorithm deployed on it; creates a sensitive vocabulary data set, uses natural language processing technology to analyze the text content in the transaction data, and combines the sensitive vocabulary data set to determine whether there are sensitive words in the transaction data. If not, the transaction data is judged to be compliant and the transaction continues to be processed; if so, the transaction data is judged to be non-compliant, the transaction is rejected, and relevant logs are recorded for subsequent audits.

8. A distributed data compliance review system, used to execute a distributed data compliance review method according to any one of claims 1 to 7, characterized in that: include: The compliance verification code deployment module deploys a unified compliance code for each node in the blockchain and performs a preliminary review of transactions; The transaction data compliance review module elects accounting nodes through a consensus algorithm and conducts compliance review through a deployed compliance verification algorithm. If the transaction is compliant, the compliant transaction data and its verification process log are packaged into blocks. If the transaction is not compliant, the transaction data is directly discarded. The block construction and hash generation module performs hash calculation on the blocks obtained in the transaction data compliance review module to generate a block hash, which is used as the unique identifier of the block; In the inter-node verification and consensus module, the accounting node broadcasts the constructed block to other nodes in the network, and through the node mutual verification mechanism, determines whether to accept the block and continue to participate in the consensus process.

9. An electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein: When the processor executes the computer program, a distributed data compliance review method according to any one of claims 1 to 7 is implemented.

10. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, a distributed data compliance review method according to any one of claims 1 to 7 is implemented.

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