CN112581129A

CN112581129A - Block chain transaction data management method and device, computer equipment and storage medium

Info

Publication number: CN112581129A
Application number: CN202011506055.1A
Authority: CN
Inventors: 罗梅琴; 郭林海; 张琛; 万化
Original assignee: Shanghai Pudong Development Bank Co Ltd
Current assignee: Shanghai Pudong Development Bank Co Ltd
Priority date: 2020-12-18
Filing date: 2020-12-18
Publication date: 2021-03-30

Abstract

The present disclosure relates to the field of blockchain technologies, and in particular, to a method and an apparatus for managing blockchain transaction data, a computer device, and a storage medium. The method comprises the steps of receiving transaction data broadcasted in a block chain network; verifying the transaction data based on a blockchain network, and performing risk analysis on the transaction data except for the blockchain network; when the transaction data passes the verification and the risk analysis, generating a block comprising the transaction data after passing consensus with other nodes. Through the embodiment of the text, the transaction data can be automatically identified and intervened according to the characteristics of the mechanism where each node is located, and the safety and the treatment convenience of the transaction data in the block chain network are improved.

Description

Block chain transaction data management method and device, computer equipment and storage medium

Technical Field

The present disclosure relates to the field of blockchain technologies, and in particular, to a method and an apparatus for managing blockchain transaction data, a computer device, and a storage medium.

Background

In a narrow sense, the blockchain is a distributed account book which is a chain data structure formed by combining data blocks in a sequential connection mode according to a time sequence and is guaranteed in a cryptographic mode and cannot be tampered and forged. Broadly, the blockchain technique is a decentralized distributed infrastructure and computing paradigm that stores data using a chained, tree, or graph blockchain data structure, generates, updates, and synchronizes data using a distributed node consensus algorithm, secures data transmission and access using cryptography, and programs and manipulates data using automation scripts (intelligent contracts). A reliable and difficult-to-tamper account book record is maintained by using the block chain technology, so that the trust risk can be reduced, and the maintenance cost of cooperation of many participants can be effectively reduced. Therefore, the block chain network constructed based on the block chain technology has the characteristics of anonymity, tamper resistance, traceability and the like.

With the falling of a large amount of applications of the block chain technology, the large-scale deployment of the block chain nodes enables a large number of users to be possible to open the block chain transactions through the block chain nodes, the user quantity of the block chain network is suddenly increased, many malicious users are generated on the network, and the illegal phenomena such as a large number of invalid transactions, deployment of ultra-long intelligent contracts (or illegal intelligent contracts) or release of offensive speeches and the like are sent.

There is a need for a solution that can automate the handling of violations in blockchain network transaction data.

Disclosure of Invention

In order to solve the problems of insufficient supervision and control strength and poor control effect of transaction data in the prior art, the embodiment of the invention provides a block chain transaction data control method and device, which can automatically identify and intervene in transaction data according to the characteristics of the mechanism where each node is located, and improve the security and control convenience of the transaction data in a block chain network.

The embodiment of the present disclosure provides a method for managing blockchain transaction data, including,

receiving transaction data broadcasted in a blockchain network;

verifying the transaction data based on a blockchain network, and performing risk analysis on the transaction data except for the blockchain network;

when the transaction data passes the verification and the risk analysis, generating a block comprising the transaction data after passing consensus with other nodes.

Embodiments herein also provide a blockchain transaction data governance device, including,

a receiving unit, configured to receive transaction data broadcasted in a blockchain network;

the verification unit is used for verifying the transaction data based on a block chain consensus algorithm and an intelligent contract;

a risk analysis unit, configured to perform risk analysis outside the blockchain network on the transaction data;

and the consensus unit is used for generating a block comprising the transaction data after the transaction data passes the verification and the risk analysis and passes the consensus with other nodes.

Embodiments herein also provide a computer device comprising a memory, a processor and a computer program stored on the memory and executable on the processor, the processor implementing the above-mentioned method when executing the computer program.

Embodiments herein also provide a computer-readable storage medium having stored thereon computer instructions, which when executed by a processor, implement the above-described method.

By utilizing the embodiment, the transaction data can be automatically identified and intervened according to the characteristics of the mechanism where each node is located, so that the safety and the treatment convenience of the transaction data in the block chain network are improved; the method can be used for carrying out automatic risk analysis on transaction data, different risk analysis results can be generated according to local databases of different nodes aiming at specific transaction data, and the transaction data which are already subjected to chain dropping or the transaction data and an account can be treated and intervened according to the risk analysis results, namely, the scheme of the embodiment can be used for treating the transaction data which are already subjected to chain dropping in the block chain network according to real-time public opinion, news, internal regulation and the like, so that the spread of malicious transactions, illegal intelligent contracts or illegal information in the block chain network can be reduced; the labor cost and the management cost for monitoring the transaction data in the blockchain network are greatly reduced.

Drawings

In order to more clearly illustrate the embodiments or technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described below, and it is obvious that the drawings in the following description are only some embodiments of the present invention, and it is obvious for those skilled in the art that other drawings can be obtained according to the drawings without creative efforts.

FIG. 1 is a schematic diagram of a blockchain transaction data governance system according to an embodiment of the present disclosure;

FIG. 2 is a flow chart of a method for managing blockchain transaction data according to an embodiment of the present disclosure;

FIG. 3 is a schematic structural diagram of a blockchain transaction data governance device according to an embodiment of the present disclosure;

fig. 4 is a schematic structural diagram of a block chain transaction data governance device according to an embodiment of the present disclosure;

FIG. 5 is a flow chart illustrating a method for risk analysis of blockchain transaction data according to an embodiment of the present disclosure;

FIG. 6a is a schematic diagram of a client-side user interface operating in a user terminal according to an embodiment of the present disclosure;

fig. 6b is a schematic diagram illustrating a client sending transaction data to a blockchain network through node a according to an embodiment of the present disclosure;

FIG. 6c is a schematic diagram illustrating the administration of transaction data in consensus verification according to an embodiment herein;

FIG. 7 is a flow chart illustrating a method for verification of blockchain transaction data and risk analysis according to an embodiment of the present disclosure;

FIG. 8 is a flow chart of a method for block chain transaction data governance proposal according to an embodiment of the present disclosure;

fig. 9 is a schematic structural diagram of a blockchain transaction data governance device according to an embodiment of the present disclosure.

[ description of reference ]

100. A block chain network;

101. a node;

102. a local database;

103. transaction data;

104. treatment and proposal;

301. a receiving unit;

302. a verification unit;

303. a risk analysis unit;

3031. a first local resource;

3032. a first risk analysis module;

3033. a second local resource;

3034. a second risk analysis module;

3035. a transaction history state data acquisition module;

3036. a third risk analysis module;

304. a consensus unit;

305. an interface unit;

306. a client interface unit;

307. a recording unit;

308. an intervention unit;

309. a treatment proposal unit;

601. a node;

602. a terminal;

603. a verification unit;

604. a risk analysis unit;

902. a computing device;

904. a processing device;

906. a storage resource;

908. a drive mechanism;

910. an input/output module;

912. an input device;

914. an output device;

916. a presentation device;

918. a graphical user interface;

920. a network interface;

922. a communication link;

924. a communication bus.

Detailed Description

The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments herein without making any creative effort, shall fall within the scope of protection.

Fig. 1 is a schematic structural diagram of a block chain transaction data governance system according to an embodiment of the present disclosure, in this figure, it is described that in a blockchain network 100, a plurality of nodes 101 are provided, and the nodes 101 may be desktop computers or servers of organizations, or may be server clusters, in each node or in some nodes there is a local database 102 for that node, which local database 102 may be in the form of a relational database, a distributed database or the like, and when the node 101 receives the transaction data 103, a risk analysis is performed on the transaction data 103 in connection with the local database 102, wherein data such as risk analysis condition parameters which can be updated in real time are stored for risk analysis of transaction data, when the consensus verification according to a consensus algorithm such as POW or POS passes, the transaction data 103 is added to a block (block), and then a chain is dropped (written into a shared account book of the block chain). When the node 101 fails in risk analysis, an abatement proposal 104 for the transaction data 103 may be initiated, the abatement proposal 104 may be audited by means of an intelligent contract, and after the consensus in the blockchain network is verified, various operations may be performed on the transaction data 103 or a transaction party account related to the transaction data 103.

The intelligent contract is a program, and realizes program automation processing in a computer instruction mode. The intelligent contract is a section of code which triggers execution when trading on the blockchain, and the section of code is the intelligent contract. The intelligent contract program is not only a computer program capable of being automatically executed, but also a system participant, responds to the received information, and can receive and store the value and send the information and the value to the outside. The intelligent contract is suitable for characteristics of decentralized, non-falsifiable, transparent and traceable process and the like of the block chain technology, and is one of characteristics of the block chain technology.

The transaction data includes various transaction data in the blockchain network, such as text, pictures, video, audio, etc. data that may be included in the transaction. The transaction data is at risk, which means that the transaction data includes, but is not limited to, yellow-related data, advertisement, prohibited data related to politics, riot and terrorism, nonsense characters, repetitive information, and the like.

According to the embodiment, automatic risk analysis can be performed on transaction data, different risk analysis results can be generated according to local databases of different nodes aiming at specific transaction data, and the transaction data which have fallen into a chain or accounts related to the transaction data can be treated according to the risk analysis results, that is, the transaction data which have fallen into a chain in a block chain network can be treated according to real-time public opinion, news, internal regulation and the like through the scheme of the embodiment, so that the spread of malicious transactions, illegal intelligent contracts or illegal information in the block chain network can be reduced; the labor cost and the management cost for monitoring the transaction data in the blockchain network are greatly reduced.

Fig. 2 is a flow chart of a method for governing block chain transaction data in a transaction of a block chain network according to an embodiment of the present invention, where the method for governing transaction data in a transaction of a block chain network is described in this figure, and may be applied to various block chain networks such as a public chain, a private chain, and a federation chain. The method of the embodiment can detect transaction data aiming at a local database of the node, detect the transaction data by combining different risk detection rules of each node, process the detected risk transaction data, and operate the risk transaction data after the risk transaction data falls into a chain, so that illegal transactions and information in a block chain network can be quickly and flexibly eliminated, and the method specifically comprises the following steps:

step 201, receiving transaction data broadcasted in a block chain network;

step 202, verifying the transaction data based on a blockchain network, and performing risk analysis on the transaction data except for the blockchain network;

and step 203, when the transaction data passes the verification and the risk analysis, generating a block comprising the transaction data after passing the consensus with other nodes.

In the above embodiments, the node in this embodiment performs verification and risk analysis on transaction data, so that risk analysis rules in the local database may be applied to perform risk analysis on the transaction data, so that the node may detect the transaction data according to the risk analysis rules in the local database, and if the transaction data conforms to both verification and risk analysis rules of the blockchain network, and after most nodes in the blockchain network pass consensus, add a block including the transaction data, the transaction risk analysis rules, and the transaction verification results into the shared account book of the blockchain network, and then perform synchronization of the shared account book in the whole blockchain network, so that the shared account book in the blockchain network remains consistent. The risk analysis rules meeting the respective requirements may be updated in real time in the local databases of the nodes, that is, for example, the risk analysis rules stored in the local databases of the node a and the node B may be different, and the node a and the node B may have different risk analysis results for the same transaction data.

According to one embodiment herein, before performing blockchain network-based validation on the transaction data and performing risk analysis outside of blockchain network on the transaction data,

and sending the transaction data to a risk analysis unit of the node for risk analysis.

In this step, the verification based on the blockchain network refers to verification based on combination of a blockchain network consensus algorithm and an intelligent contract, in the prior art, a blockchain network node verifies received broadcast transaction data, verification rules are all arranged in advance in the blockchain network in a manner of the intelligent contract and the consensus algorithm, and all nodes verify the transaction data by using the same verification rules. In this embodiment, performing risk analysis on the transaction data outside the blockchain network means that each node may have its own unique risk analysis rule, and these risk analysis rules may be stored locally in the node or stored in a locally specified remote database, which may be different from the validation rules in the blockchain network.

In this embodiment, the node and the risk analysis unit may implement communication through an Application Programming Interface (API), or the function of the risk analysis unit in this document may be implemented in the form of a Software Development Kit (SDK), so that the block chain program of the node may call the function in the risk analysis unit to perform risk analysis on the transaction data.

After receiving transaction data broadcasted in a block chain network, the node extracts the transaction data and sends the transaction data to a risk analysis unit in the node when executing an intelligent contract, wherein the risk analysis unit can be realized in a computer mode, and the computer of the risk analysis unit can be connected with a computer where the node is located and forms a communication channel, so that the risk analysis unit can obtain the transaction data; or the risk analysis unit can be realized in a software mode, the risk analysis unit and the functional module for performing block chain verification run on a computer where the node is located, and the transaction data is transmitted through a communication interface between programs. The risk analysis unit can call a local database, a local function module, an algorithm, a local hardware and the like of a computer where the node is located to realize risk analysis on the transaction data, or can access a designated address (URL) in the Internet to obtain a risk analysis rule and perform risk analysis on the transaction data by using the risk analysis rule. Different nodes represent a certain organization (such as a large bank, an enterprise and public institution, a third party organization with public trust, and the like), each organization may be configured with different risk analysis rules, and the risk analysis unit may perform risk analysis on transaction data in real time, dynamically, and individually by calling a local risk analysis rule or calling a risk analysis rule configured in a network.

Consensus in embodiments herein may follow prior art consensus protocols, examples of which include, but are not limited to, proof of work (POW), proof of rights of interest (POS), proof of authority (POA), and the varietal Byzantine Fault tolerant Algorithm (BFT), POW being further referenced herein as a non-limiting example.

According to one embodiment herein, conducting a risk analysis on the transaction data outside of the blockchain network further comprises,

and carrying out risk analysis on the transaction data according to the local resources of the current node.

In this step, the transaction data is broadcast in the blockchain network, received by all nodes, and risk analysis is performed on the transaction data by using local resources of the node on the current node receiving the transaction data. The local resources of the nodes comprise data resources and algorithm resources which are local to the nodes, for example, data resources such as a real-time updated database for storing public sentiments, a real-time updated keyword matching table, respective black and white lists of the nodes and the like are utilized, and/or algorithm resources such as an image analysis algorithm module based on deep learning, an audio and video analysis algorithm module based on deep learning, a natural language analysis algorithm module and the like are utilized. The local resources of each node may be different, that is, may be partially the same, or may be completely different, for example, a node may update a public opinion database related to a mechanism corresponding to the node in real time, and public opinions of mechanisms not related to the node may be updated slowly, or a training sample used by a natural language analysis algorithm module based on deep learning is related to the mechanism corresponding to the node, so that the recognition effect of the natural language analysis algorithm module obtained by training is different from that of natural language analysis algorithm modules of other nodes, which is just an example of this document, and the local resources (algorithm resources or data resources) of the current node are all related to the mechanism corresponding to the node.

According to one embodiment of the present disclosure, before receiving the transaction data broadcasted in the blockchain network, the method further includes receiving the transaction data sent by the client;

In the step, a user initiates a transaction by using a client, the transaction is sent to a node connected with the client for preprocessing, and after risk analysis of the current node, the transaction is broadcasted by the blockchain network, so that a large amount of illegal transaction data can be avoided, risk analysis of the transaction data by all nodes in the blockchain network is avoided, and network resources and computing resources of the nodes are saved.

According to one embodiment herein, risk analyzing the transaction data based on local resources of the current node further comprises,

performing first risk analysis on the transaction data according to a first local resource of the current node; and/or

Performing a second risk analysis on the transactional data according to a second local resource of the current node.

In this step, the first local resource of the current node may include algorithm modules such as an information analysis algorithm module based on deep learning, a natural language analysis algorithm (NLP) module, and the like, and perform a first risk analysis on the transaction data through the algorithm modules, where the first risk analysis may be a risk analysis performed on the content of the transaction data, for example, when the transaction data is information, whether the information includes politically sensitive words, nonsense words, and the like; if the transaction data is a picture, whether the picture includes violation content; if the transaction data is the audio and video, whether illegal contents are included in the audio and video; and if the transaction data is a numerical value, counting whether the transaction numerical value is high risk or not according to the big data, such as exceeding the normal transaction numerical value of the account at ordinary times.

The second local resource of the current node may include data information such as a public opinion database, a client black and white list, and the like, and the second risk analysis is performed on the transaction data through the comparison module, where the second risk analysis may be to compare the transaction data with data in the public opinion database and the client black and white list, and obtain a risk analysis result according to a comparison result, for example, when a piece of data proved to be false information is newly added to the public opinion database, information included in the transaction data is just the false information, and the risk analysis result of the transaction data is a high risk after the transaction data is compared with the data in the public opinion database.

acquiring transaction history state data associated with the transaction data in a local shared account book;

and combining the transaction data and the transaction historical state data to perform risk analysis.

In this step, each node in the blockchain network synchronizes to a shared account book, which may refer to a shared account book in the prior art, and all transaction data and all transaction history status data are stored in the shared account book, where the transaction history status data refers to a history calculation value of the transaction data, the history calculation value refers to a mathematical operation result of a numerical value when the transaction data is the numerical value, and the history calculation value refers to a result of processing, such as splicing, filtering, and operation, of the data when the transaction data is in a form of text, picture, video, audio, and the like.

The risk analysis is performed after the transaction data and the transaction history state data are associated, for example, if the transaction data is the text information "medium", and the transaction history state data associated with the transaction data is "country", the transaction data and the transaction history state data are associated to form the text "china", and if the word "china" is a word which should not appear, the risk analysis result is a high risk or a medium risk.

According to one embodiment herein, said combining said transaction data and said transaction historical state data for risk analysis further comprises,

merging the transaction data with the transaction historical state data within a predetermined time period; and/or the presence of a gas in the gas,

merging the transaction data with transaction historical state data of the same account; and/or the presence of a gas in the gas,

merging the transaction data with transaction historical state data in the same block;

and carrying out risk analysis on the combined result.

In this step, the transaction data is merged with the transaction historical state data in a preset time period, a result after the transaction data are merged in a period of time can be obtained, when the transaction data are numerical values, the transaction amount possibly exceeds a threshold value in a period of time, the transaction requests and transaction participants can be identified as high risks through risk analysis, when the transaction data are characters, pictures and audio and video data, the transaction data are merged with the transaction historical state data in a shared account book in a period of time, complete characters, pictures, audio and video and other results can be obtained, and whether the transaction data in a period of time form the high risks or not can be identified through risk analysis in the modes of character identification, natural language identification, picture identification, account black and white lists, opinion and the like;

the transaction data and the transaction history state data of the same account are combined, in this embodiment, the transaction history state data of the same account can be searched across blocks, or the transaction history state data of the same account can be searched in the same block, so that a numerical total or complete text, picture, audio and video data and the like from one account when transacting with other accounts are obtained, and whether the account belongs to a high-risk account can be identified through risk analysis in the modes of text identification, natural language identification, picture identification, account black and white lists, public opinions and the like;

the transaction data and the transaction history state data in the same block are merged, and in this embodiment, the transaction history state data in the same block can be searched, so that the numerical total value obtained by merging the transaction data and the transaction history state data in the same block or complete text, picture, audio and video data and the like can be obtained, and whether the account belongs to a high-risk account can be identified through risk analysis in the modes of text identification, natural language identification, picture identification, account black and white list, public opinion and the like.

According to one embodiment herein, performing risk analysis on the transaction data outside of the blockchain network further comprises,

transaction data that failed the risk analysis is recorded.

In this step, the risk analysis fails to include transaction data identified by a machine learning algorithm as a risk level such as high risk, medium risk, etc., or transaction data existing in a public opinion database local to the node or in a customer blacklist, and records an identifier, such as an ID, a hash value of the transaction, etc., of the transaction data for which the risk analysis fails.

In this embodiment, it is assumed that most nodes can pass the verification in the prior art, for example, whether transaction data in the transaction, such as data of balance, text, and picture, exists in an account of a party involved in the transaction, whether an account address of a transaction initiator and an account address of a transaction receiver are legal, and the like are judged; however, since the risk analysis on the transaction data in the embodiment of the present disclosure is based on local resources of each node, different nodes may have different risk analysis results for the same transaction data, although some nodes may fail the risk analysis, most other nodes pass the risk analysis, and the nodes that do not pass the risk analysis record the ID of the transaction data for which the node fails the risk analysis, according to a minority of principles that obey majority, for example, the number of nodes that pass the verification and risk analysis exceeds 51% of the number of nodes in the blockchain network, a block may be generated by using a POW consensus protocol in the embodiment, and written into the shared account book of the blockchain network. The node generating the block is not necessarily the node performing the above method in the embodiments herein, and the node generating the block is the node generating the block determined according to the POW consensus protocol, for example.

According to one embodiment herein, generating the block including the transaction data further comprises,

carrying out consensus verification on the treatment proposal according to the received treatment proposal;

intervening in the treatment proposal which passes the consensus verification.

In this step, when the transaction data undergoes verification and risk analysis of all nodes in the blockchain network, although the risk analysis of some nodes does not pass, most nodes pass the risk analysis, and the transaction data is identified in the blockchain network. Some or some nodes propose a governance proposal aiming at transaction data at which risks are identified in risk analysis, after the nodes meeting a predetermined number of nodes pass the consensus verification of the governance proposal, the consensus verification can refer to the consensus verification in the prior art, such as whether the format of the governance proposal is correct, whether the content is legal, whether the content of the proposal meets the rules of an intelligent contract, and the like, and after the verification is legal, whether other nodes in the block chain network pass the verification is judged, and when the number of the nodes passing the verification exceeds a predetermined threshold value, the consensus verification passes, and each node can execute intervention actions specified by the intelligent contract, such as modifying, shielding and the like on corresponding transaction historical state data.

According to one embodiment herein, prior to consensus validation of the abatement proposal according to the abatement proposal further comprises,

and (5) proposing a treatment proposal aiming at the transaction data which does not pass the risk analysis.

In this step, some nodes in the blockchain network propose an abatement proposal for the transaction data according to the identifier of the recorded transaction data which does not pass risk analysis, wherein the abatement proposal can be proposed by any node, the abatement proposal is broadcast in the blockchain network, after receiving the abatement proposal, other nodes call a corresponding intelligent contract to perform consensus verification on the abatement proposal, and after the consensus verification passes, the intelligent contract performs an intervention operation indicated in the abatement proposal or performs an intervention operation specified in the intelligent contract.

According to one embodiment herein, the abatement proposal comprises an identifier of the transaction data, and at least one of:

risk content of the transaction data, intelligent contracts corresponding to the transaction data and intervention operation.

In this step, the identifier of the transaction data includes an ID or a hash value of the transaction data, and the transaction history state data associated with the transaction data can be uniquely determined in the shared account book by the identifier of the transaction data; the risk content of the transaction data refers to that a node indicates which field or fields of the transaction data that do not pass the risk analysis of the node are considered to be risky, for example, which information in text fields is false information, violation information is included in an image, and the like; the intelligent contract corresponding to the transaction data indicates that the intelligent contract related to the transaction data, which is considered to fail the risk analysis, has a violation condition, and may further include an ID indicating the intelligent contract or specific violation processing; the intervention operation refers to what operation needs to be performed on the transaction history state data associated with the transaction data which does not pass risk analysis by the node, for example, transaction state information is deleted, the state information is modified, and a hash value query function for shielding the transaction data is performed.

According to one embodiment herein, intervening in the abatement proposal validated by the consensus further comprises,

deleting, modifying and covering transaction historical state data related to the transaction data involved in the governance proposal; and/or

Shielding and inquiring the transaction data in the treatment proposal; and/or

Freezing or thawing the account to which the transaction data relates.

In this step, deleting the transaction history state data associated with the transaction data related to the administration proposal means deleting the transaction history state data; modifying the transaction history state data associated with the transaction data involved in the governance proposal means that the transaction history state data is modified; covering the transaction history state data related to the transaction data related to the treatment proposal means that the new transaction history state data is used for covering the original transaction history state data; the step of shielding the inquiry of the transaction data in the treatment proposal means that the inquiry of the transaction data is forbidden; freezing or unfreezing the account to which the transaction data relates means that the account to which the transaction data relates cannot be used again as the initiator or the receiver of the transaction, or the account to which the transaction data relates is allowed to be used as the initiator or the receiver of the transaction. When the intervention operation is successful, the shared accounts book of all nodes in the blockchain network will remain consistent.

By the method of the embodiment, the transaction data in the block chain network can be automatically identified, the cost of finding the violation information by the existing block chain network is reduced, and the processing speed of the violation information is improved; risk analysis can be carried out on transaction data by each mechanism (node) according to respective characteristics, and the flexibility of consensus verification is improved; and a corresponding treatment proposal process is provided, and the remedial measures for the violation information in the block chain network can be further perfected.

Fig. 3 is a schematic structural diagram of a blockchain transaction data governance device according to an embodiment of the present disclosure, in which a governance device that may be embedded in or connected to an existing blockchain network node is described, and may be obtained by programming a general-purpose chip or a dedicated chip, or may be implemented in an electronic device with data processing capability in a software manner, where the software and hardware may be implemented in a computer or a computer cluster, and the device specifically includes:

a receiving unit 301, configured to receive transaction data broadcasted in a blockchain network;

a verification unit 302, configured to perform block chain network-based verification on the transaction data;

a risk analysis unit 303, configured to perform risk analysis outside the blockchain network on the transaction data;

a consensus unit 304, configured to generate a block including the transaction data after passing consensus with other nodes when the transaction data passes the verification and the risk analysis.

In the embodiment herein, the receiving unit 301 and the verifying unit 302 may both adopt a common structure of a blockchain network node in the prior art, the risk analyzing unit 303 and the consensus unit 304 operate on nodes of various organizations, perform risk analysis on transaction data in combination with local resources of current nodes, and after the transaction data passes through verification and risk analysis in the prior art, generate a block including the transaction data according to an existing consensus protocol, and add the block into the shared account book.

Referring to fig. 4, fig. 4 is a schematic diagram illustrating a specific structure of a blockchain transaction data governance device according to an embodiment of the present disclosure, where the specific structure of the governance device is described in detail in this figure, where each functional module may be implemented in a software or hardware manner, and specifically includes:

and the interface unit 305 is used for sending the transaction data to a risk analysis unit of the node for risk analysis.

A client interface unit 306, configured to receive the transaction data sent by the client before the receiving unit 301 receives the transaction data broadcasted in the blockchain network.

According to an embodiment herein, the risk analysis unit 303 is further configured to perform a risk analysis on the transaction data according to local resources of the current node.

According to one embodiment herein, the risk analysis unit 303 further comprises,

a first local resource 3031, a first risk analysis module 3032, a second local resource 3033, a second risk analysis module 3034,

the first risk analysis module 3032 is configured to perform a first risk analysis on the transaction data according to a first local resource 3031 of the current node;

the second risk analysis module 3034 is configured to perform a second risk analysis on the transaction data according to a second local resource 3033 of the current node.

According to an embodiment herein, the risk analysis unit 303 further comprises:

a transaction history status data obtaining module 3035, configured to obtain transaction history status data associated with the transaction data in a local shared account book;

a third risk analysis module 3036, configured to perform risk analysis by combining the transaction data and the transaction historical state data.

According to an embodiment herein, said third risk analysis module 3036 is further configured to,

and carrying out risk analysis on the combined result.

The third risk analysis module 3036 may invoke the first risk analysis module 3032 and the second risk analysis module 3034 to perform risk analysis on the combined result.

According to an embodiment herein, the apparatus further comprises a recording unit 307 for recording transaction data failing the risk analysis.

According to one embodiment herein, the consensus unit 304 is further configured to perform consensus verification on the abatement proposal according to the abatement proposal;

the apparatus also includes an intervention unit 308 for intervening on the abatement proposal validated by the consensus.

According to one embodiment herein, the apparatus further comprises an abatement proposal unit 309 for proposing an abatement proposal for the transaction data that does not pass the risk analysis.

According to one embodiment herein, the intervention unit 308 is further configured to,

Shielding and inquiring the transaction data in the treatment proposal; and/or

Freezing or thawing the account to which the transaction data relates.

By the device of the embodiment, the transaction data in the block chain network can be automatically identified, the cost of finding the violation information by the existing block chain network is reduced, and the processing speed of the violation information is improved; risk analysis can be carried out on transaction data by each mechanism (node) according to respective characteristics, and the flexibility of consensus verification is improved; and a corresponding treatment proposal process is provided, and the remedial measures for the violation information in the block chain network can be further perfected.

Fig. 5 is a flowchart of a method for risk analysis of blockchain transaction data according to an embodiment of the present disclosure, where risk analysis is performed on transaction data according to a risk analysis rule local to a node of each organization in the flowchart, so that real-time and flexible risk analysis can be performed independently of consensus verification of a blockchain network, for example, when a user a initiates a transaction, the transaction carries illegal text content, and a rule that identifies the text as the illegal text is not written into an intelligent contract in real time, so that the illegal transaction data cannot be identified in the existing consensus verification, and in the embodiment of the present disclosure, risk analysis may be performed according to the risk analysis rule local to the node, so that the transaction data includes the illegal transaction data. The method specifically comprises the following steps:

step 501, user a initiates a transaction data of the blockchain network on the client.

In this step, the user a may operate the client by using a mobile phone, a computer, a tablet computer, or the like, and input transaction data through a Graphical User Interface (GUI) of the client, as shown in fig. 6a, which is a schematic diagram of a user interface of the client operating in the user terminal according to the embodiment herein, where the schematic diagram includes an interface for providing the user a with transaction data input, and text verification may be performed on the transaction data input by the user a in the client, that is, format check may be performed on data in the form of a numeric value, a character string, or the like input by the user a, so as to determine whether the format of the input transaction data meets requirements, and whether the input transaction data carries sensitive words or not.

In step 502, the client sends the transaction data to node a.

In this step, as shown in fig. 6B, a schematic diagram of the client sending transaction data to the blockchain network through the node a according to the embodiment of the present invention is shown, where the schematic diagram includes a plurality of nodes 601, one or more terminals 602 connected to the node 601 for operating the client, and the nodes a, B, C, D, E, and N are all nodes set up by a large organization, or nodes set up by a trusted organization, such as a government agency, a court, a well-reputable enterprise, and the like, where node numbers in the diagram are only schematic and do not limit the specific number of nodes in the blockchain network, the node N represents an nth node, N is an integer, and a connection relationship diagram between the nodes is only schematic and does not limit the connection relationship between the nodes. Each terminal 602 for operating the client is connected with a corresponding node 601 through a network, each node 601 is connected with a plurality of terminals 602 for operating the client, and transaction data initiated by the client is broadcasted in a blockchain network formed by all nodes through the corresponding node A after risk analysis of the node A.

In step 503, the node a sends the received transaction data to the risk analysis unit.

In this step, the node a receives the transaction data sent by the client through the blockchain system, and sends the transaction data to the risk analysis unit of the node a through the application program interface, where the risk analysis unit may be implemented in an SDK manner.

And step 504, the risk analysis unit of the node A carries out risk analysis on the transaction data.

In this step, the risk analysis unit of the node a performs risk analysis on the content of the transaction data through the algorithm resources, for example, whether the transaction data includes political sensitive words, nonsense words, and the like when the transaction data is information, by using the algorithm resources such as a local deep learning-based information analysis algorithm module, a natural language analysis algorithm (NLP) module, a word vector model, and the like.

As an alternative embodiment, the risk analysis unit of the node a may also perform comparison analysis on the transaction data by using data resources such as a local public opinion database, a client black and white list, and the like, and when a new piece of data proved to be false information is added to the public opinion database of the node a, or a false message about an organization of the node a in the internet is updated in the public opinion database, the information included in the transaction data is just the false information, and the risk analysis result of the transaction data is high risk after comparing the transaction data with the data in the public opinion database.

Of course, if the public opinion database of the node a does not store the information corresponding to the transaction data, or the algorithm module does not recognize that the transaction data includes the violation content, the risk analysis result is low risk or no risk.

And 505, feeding the risk analysis result back to the node A by the risk analysis unit of the node A.

In this step, the risk analysis unit of the node a feeds back the risk analysis result to the node a through an application program interface, and if the risk analysis result is high risk or illegal transaction data, the transaction data is discarded and fed back to corresponding client transaction failure information through a blockchain network; if the risk analysis result is low risk or no illegal transaction data is found, the transaction data is broadcasted in the blockchain network, that is, the transaction data is broadcasted through the node a as shown in fig. 6 b.

Figure 7 is a flow chart of a method for verification of blockchain transaction data and risk analysis according to an embodiment of the present disclosure, in this figure, it is described that, after transaction data is broadcast in the blockchain network, a certain node receives the transaction data, the node performs verification and risk analysis on the transaction data by combining a verification rule in the blockchain network and a risk analysis rule in the local resource, when both the verification and the risk analysis pass, the transaction data passing the detection is signed under a consensus mechanism, when the verification or risk analysis fails, the transaction data that failed the detection is not signed, forming a consensus to determine whether to write the transaction data into the block according to the detection results of other nodes in the blockchain network, discarding the transaction data if no consensus is formed, the generated block not including the transaction data, the method comprising:

in step 701, the node B receives the broadcasted transaction data.

In this step, referring to fig. 6c, a schematic diagram of processing transaction data in consensus verification according to an embodiment herein is shown, in which broadcast transaction data sent by a node a is received by a node B in a blockchain network, the node B sends the transaction data to a verification unit 603 for verification based on the blockchain network, and also sends the transaction data to a risk analysis unit 604 via an application program interface for risk analysis based on local resources, and then when both the risk analysis and the verification pass, the transaction data is signed to indicate that detection by the node B passes. Similar methods are performed by other nodes in the blockchain network, and when the detection results of most of all nodes are passed, the transaction data is written into the block and the block is added into the shared account book, wherein the node algorithm for generating the block can refer to the consensus algorithm in the prior art.

In step 702, the node B verifies the transaction data using the verification rule of the blockchain network.

The verification in this step refers to the verification of the blockchain network node on the received broadcast transaction data in the prior art, the verification combines an intelligent contract and a consensus algorithm of the blockchain network, the verification rules are all arranged in advance in the blockchain network in the mode of the intelligent contract or the consensus algorithm, and all the nodes verify the transaction data by adopting the same verification rule.

Step 703, the transaction data is sent to the risk analysis unit of the node B through the application program interface.

In this step, the blockchain system of the node B receives the transaction data, verifies the transaction data by the verification method in the blockchain system, extracts the transaction data, and sends the transaction data to the risk analysis unit of the node B through the application program interface, where the risk analysis unit may be an independent computer connected to the computer of the node B or a part of the computer of the node B.

In step 704, the risk analysis unit of the node B performs risk analysis based on algorithm resources and data resources on the transaction data.

In this step, the risk analysis unit of the node B performs risk analysis on the content of the transaction data by using local algorithm resources such as an information analysis algorithm module based on deep learning, a natural language analysis algorithm (NLP) module, and a word vector model, for example, when the transaction data is information, whether the information includes political sensitive words, nonsense words, and the like; and when the transaction data are numerical values, analyzing whether the numerical values are inconsistent with the normal behaviors of the user through an information analysis algorithm module based on deep learning, and if not, identifying the transaction data as high risk.

The risk analysis unit of the node B also utilizes local public opinion database, client black and white list and other data resources to compare and analyze with the transaction data, when a false message about the mechanism of the node B in the internet is updated in the public opinion database of the node B, the false message may not be updated in the public opinion databases of other nodes, at the moment, the information included in the transaction data is just the false information, and after the transaction data is compared with the data in the public opinion database, the risk analysis result of the transaction data is high risk.

Of course, if the public opinion database of the node B does not store the information corresponding to the transaction data, or the algorithm module does not recognize that the transaction data includes the violation content, the risk analysis result is low risk or no risk.

Step 705, the risk analysis unit of the node B combines the transaction data and the transaction historical state data to perform risk analysis.

In this step, the node B obtains transaction history status data associated with transaction data in a locally stored shared book, wherein the transaction history status data records transaction data history calculation values.

The transaction data and the transaction historical state data in a preset time period are merged, for example, the transaction data are character information, the transaction historical state data in one hour in a shared account book are taken out, the transaction historical state data and the received transaction data are spliced to obtain complete character information, and then whether the complete character information is illegal transaction data or not is judged through local algorithm resources and data resources.

Or, the transaction data and the transaction history state data of the same account can be merged, the transaction history state data which are the same as the initiator in the shared account book are found out according to the initiator of the transaction data, the transaction history state data and the received transaction data are counted, then whether the counting result exceeds a preset threshold value or not is judged, and if the number of transactions initiated by the initiator exceeds the preset threshold value, the transaction data initiated by the initiator is judged to be illegal transaction data.

Or merging the transaction data with transaction historical state data in the same block, splicing the transaction data with the transaction historical state data of the same user serving as an initiator in the same block, judging whether the obtained complete transaction data is illegal transaction data, and if the spliced complete transaction data comprises sensitive words, judging that the transaction data initiated by the initiator is illegal transaction data.

Step 705 may also be combined with step 704, where the risk analysis unit performs risk analysis by combining the transaction history state data in the local shared account book when performing risk analysis by using the local resource, or performs risk analysis by calling the local resource after acquiring the transaction history state data.

At step 706, transaction data that fails the risk analysis is recorded.

In this step, an identifier of the transaction data that fails the risk analysis, such as an ID or a hash value of the transaction data, is recorded.

In step 707, the risk analysis unit feeds back the risk analysis result to the node B.

In step 708, the node B determines whether the detection is passed according to the verification result and the risk analysis result.

The node B determines whether to sign the transaction data according to the verification result of the step 702 and the risk analysis result obtained in the step 707, that is, determines whether the transaction data passes the detection of the node B, if the transaction data passes the detection of the node B, the node B proceeds to step 710 to sign the transaction data, and if the transaction data does not pass the detection of the node B, the node B proceeds to step 709 to discard the transaction data.

In step 711, other nodes in the blockchain network perform the above steps 701-710 on the transaction data.

In this step, the blockchain system needs to determine whether other nodes also pass the detection, and if the number of passing detections exceeds a predetermined threshold value, that is, the consensus is passed, the blockchain system generates a block including the transaction data through the consensus; otherwise, the transaction data is discarded.

At step 712, the block generated to include the transaction data is written into a shared account book.

Fig. 8 is a flow chart of a method for processing block chain transaction data governance proposal according to an embodiment of the present disclosure, and a processing procedure of a institution node C for processing a governance proposal for transaction data that has fallen into a chain and subsequently intervening the transaction data is described in the present drawing. Any node may determine that the transaction data is illegal transaction data in the detection process shown in fig. 7, but other nodes pass the detection and make the transaction data fall into a chain, in order to correct the error, a node that fails the detection may propose a governance proposal for the transaction data, and intervene in the transaction data after obtaining consensus of other nodes in the blockchain network, specifically including:

step 801, node C proposes a governance proposal for the target transaction data.

In this step, the target transaction data is the transaction data that is not detected by the node C in the transaction data detection process, for example, the content in the transaction data is a false message that negatively affects the corresponding organization of the node C, and other nodes do not recognize the false message in the detection process of the transaction data (possibly because the public opinion database is updated slowly, the algorithm resource does not address the business situation of the corresponding organization of the node C), so the node C proposes a governance proposal for the transaction data.

The governing proposal can be conventional transaction data in a block chain network, wherein the conventional transaction data comprises ID of target transaction data, and contents such as intelligent contract ID related to the transaction data, specific content of risk occurrence of the target transaction data, specific intervention operation and the like. The ID of the smart contract means that the target transaction data is at risk, and may be that the smart contract needs to be modified or disabled because of a problem with the smart contract. The specific content of the risk occurrence of the target transaction data may include a field name, a value of the risk occurrence, characters, pictures, video clips and the like. The specific intervention operation includes an operation performed on the target transaction data, for example, prohibiting querying the hash value of the target transaction data, that is, shielding a query instruction for the target transaction data in the blockchain network, and returning a null value or returning an unsearched result when the user queries the hash value of the target transaction data; or deleting, modifying and covering the transaction history state data in the shared account book corresponding to the target transaction data; alternatively, the transaction data may be a freeze or thaw instruction for the participant account of the target transaction data, i.e., an initiator or recipient account of the target transaction data is frozen or thawed.

Step 802, broadcasting the abatement proposal in a blockchain network.

Step 803, the other nodes verify the abatement proposal.

In this step, the other nodes may adopt the verification method in the foregoing method to verify the governance proposal, and when the governance proposal conforms to the provisions of the intelligent contract and the consensus algorithm, the governance proposal is signed to indicate that the node passes the detection, and if the governance proposal does not conform to the provisions of the intelligent contract and the consensus algorithm, the governance proposal is discarded.

Step 804, the blockchain network identifies the abatement proposal.

In this step, if the number of nodes passing the verification of the treatment proposal exceeds the predetermined threshold, the treatment proposal is added to the block by consensus, and if the number of nodes passing the verification of the treatment proposal is lower than the predetermined threshold, the process proceeds to step 806.

At step 805, each node performs an intervention operation in the abatement proposal.

In this step, each node may, for example, block the query for the target transaction data, so that the target transaction data cannot be queried any more in the blockchain network, thereby limiting propagation of violation information in the blockchain network.

Step 806, discarding the abatement proposal and feeding back a report to the node C which proposed the abatement proposal

As shown in fig. 9, which is a schematic structural diagram of a blockchain transaction data governance apparatus according to an embodiment of the present disclosure, in this embodiment, functions performed by a blockchain transaction data governance method may all be executed on a device in this embodiment, which is referred to as a computing device in this embodiment, and the computing device 902 may include one or more processing devices 904, such as one or more Central Processing Units (CPUs), each of which may implement one or more hardware threads. Computing device 902 may also include any storage resources 906 for storing any kind of information, such as code, settings, data, and the like. For example, without limitation, storage resources 906 may include any one or more of the following in combination: any type of RAM, any type of ROM, flash memory devices, hard disks, optical disks, etc. More generally, any storage resource may use any technology to store information. Further, any storage resource may provide volatile or non-volatile reservation of information. Further, any storage resources may represent fixed or removable components of computing device 902. In one case, when processing device 904 executes associated instructions that are stored in any storage resource or combination of storage resources, computing device 902 can perform any of the operations of the associated instructions. The computing device 902 also includes one or more drive mechanisms 908, such as a hard disk drive mechanism, an optical disk drive mechanism, or the like, for interacting with any storage resource.

Computing device 902 may also include input/output module 910(I/O) for receiving various inputs (via input device 912) and for providing various outputs (via output device 914)). One particular output mechanism may include a presentation device 916 and an associated Graphical User Interface (GUI) 918. Computing device 902 may also include one or more network interfaces 920 for exchanging data with other devices via one or more communication links 922. One or more communication buses 924 couple the above-described components together.

Communication link 922 may be implemented in any manner, such as over a local area network, a wide area network (e.g., the Internet), a point-to-point connection, etc., or any combination thereof. Communication link 922 may include any combination of hardwired links, wireless links, routers, gateway functions, name servers, etc., governed by any protocol or combination of protocols.

Embodiments herein also provide a computer device comprising a memory, a processor, and a computer program stored on the memory and executable on the processor, the processor implementing the following steps when executing the computer program:

receiving transaction data broadcasted in a blockchain network;

The computer device provided by the embodiment can also implement the methods in fig. 2, fig. 5 and fig. 8.

Corresponding to the methods in fig. 2, 5-8, the embodiments herein also provide a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, performs the steps of the above-mentioned method.

Embodiments herein also provide computer readable instructions, wherein when executed by a processor, a program thereof causes the processor to perform the methods as shown in fig. 2, 5-8.

It should be understood that, in various embodiments herein, the sequence numbers of the above-mentioned processes do not mean the execution sequence, and the execution sequence of each process should be determined by its function and inherent logic, and should not constitute any limitation to the implementation process of the embodiments herein.

It should also be understood that, in the embodiments herein, the term "and/or" is only one kind of association relation describing an associated object, meaning that three kinds of relations may exist. For example, a and/or B, may represent: a exists alone, A and B exist simultaneously, and B exists alone. In addition, the character "/" herein generally indicates that the former and latter related objects are in an "or" relationship.

Those of ordinary skill in the art will appreciate that the elements and algorithm steps of the examples described in connection with the embodiments disclosed herein may be embodied in electronic hardware, computer software, or combinations of both, and that the components and steps of the examples have been described in a functional general in the foregoing description for the purpose of illustrating clearly the interchangeability of hardware and software. Whether such functionality is implemented as hardware or software depends upon the particular application and design constraints imposed on the implementation. Skilled artisans may implement the described functionality in varying ways for each particular application, but such implementation decisions should not be interpreted as causing a departure from the scope of the present disclosure.

It is clear to those skilled in the art that, for convenience and brevity of description, the specific working processes of the above-described systems, apparatuses and units may refer to the corresponding processes in the foregoing method embodiments, and are not described herein again.

In the several embodiments provided herein, it should be understood that the disclosed system, apparatus, and method may be implemented in other ways. For example, the above-described apparatus embodiments are merely illustrative, and for example, the division of the units is only one logical division, and other divisions may be realized in practice, for example, a plurality of units or components may be combined or integrated into another system, or some features may be omitted, or not executed. In addition, the shown or discussed mutual coupling or direct coupling or communication connection may be an indirect coupling or communication connection through some interfaces, devices or units, and may also be an electric, mechanical or other form of connection.

The units described as separate parts may or may not be physically separate, and parts displayed as units may or may not be physical units, may be located in one place, or may be distributed on a plurality of network units. Some or all of the units can be selected according to actual needs to achieve the purposes of the embodiments herein.

In addition, functional units in the embodiments herein may be integrated into one processing unit, or each unit may exist alone physically, or two or more units are integrated into one unit. The integrated unit can be realized in a form of hardware, and can also be realized in a form of a software functional unit.

The integrated unit, if implemented in the form of a software functional unit and sold or used as a stand-alone product, may be stored in a computer readable storage medium. Based on such understanding, the technical solutions of the present invention may be implemented in a form of a software product, which is stored in a storage medium and includes several instructions for causing a computer device (which may be a personal computer, a server, or a network device) to execute all or part of the steps of the methods described in the embodiments of the present invention. And the aforementioned storage medium includes: various media capable of storing program codes, such as a usb disk, a removable hard disk, a Read-Only Memory (ROM), a Random Access Memory (RAM), a magnetic disk, or an optical disk.

The principles and embodiments of this document are explained herein using specific examples, which are presented only to aid in understanding the methods and their core concepts; meanwhile, for the general technical personnel in the field, according to the idea of this document, there may be changes in the concrete implementation and the application scope, in summary, this description should not be understood as the limitation of this document.

Claims

1. A block chain transaction data governance method is characterized by comprising the following steps,

receiving transaction data broadcasted in a blockchain network;

2. The method of claim 1, wherein conducting a risk analysis on the transaction data outside of a blockchain network further comprises,

3. The method of claim 1, further comprising, prior to receiving transaction data broadcast in a blockchain network,

receiving transaction data sent by a client;

4. The method of claim 2 or 3, wherein performing a risk analysis on the transaction data based on local resources of a current node further comprises,

5. The method according to claim 2 or 3,

performing risk analysis on the transaction data based on local resources of the current node further comprises,

6. The method of claim 5, wherein said combining the transaction data and the transaction historical state data for risk analysis further comprises,

and carrying out risk analysis on the combined result.

7. The method of claim 1, wherein performing a risk analysis on the transaction data outside of a blockchain network further comprises,

transaction data that failed the risk analysis is recorded.

8. The method of claim 1, further comprising, after generating the block including the transaction data,

intervening in the treatment proposal which passes the consensus verification.

9. The method of claim 8, wherein intervening on an abatement proposal validated by the consensus further comprises,

Shielding and inquiring the transaction data in the treatment proposal; and/or

Freezing or thawing the account to which the transaction data relates.

10. A block chain transaction data governance device is characterized in that,

the verification unit is used for verifying the transaction data based on a block chain network;

11. A computer device comprising a memory, a processor and a computer program stored on the memory and executable on the processor, characterized in that the processor implements the method of any of the preceding claims 1-9 when executing the computer program.

12. A computer-readable storage medium having computer instructions stored thereon, wherein the computer instructions, when executed by a processor, implement the method of any of the preceding claims 1-9.