WO2022022252A1 - 一种数据共享方法、装置及设备 - Google Patents

一种数据共享方法、装置及设备 Download PDF

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WO2022022252A1
WO2022022252A1 PCT/CN2021/105148 CN2021105148W WO2022022252A1 WO 2022022252 A1 WO2022022252 A1 WO 2022022252A1 CN 2021105148 W CN2021105148 W CN 2021105148W WO 2022022252 A1 WO2022022252 A1 WO 2022022252A1
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data
blockchain
user
transaction
precipitation
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PCT/CN2021/105148
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English (en)
French (fr)
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娄思源
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支付宝(杭州)信息技术有限公司
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Publication of WO2022022252A1 publication Critical patent/WO2022022252A1/zh

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    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
    • G06F16/20—Information retrieval; Database structures therefor; File system structures therefor of structured data, e.g. relational data
    • G06F16/24—Querying
    • G06F16/245—Query processing
    • G06F16/2458—Special types of queries, e.g. statistical queries, fuzzy queries or distributed queries
    • G06F16/2465—Query processing support for facilitating data mining operations in structured databases
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q20/00—Payment architectures, schemes or protocols
    • G06Q20/38—Payment protocols; Details thereof
    • G06Q20/40—Authorisation, e.g. identification of payer or payee, verification of customer or shop credentials; Review and approval of payers, e.g. check credit lines or negative lists
    • G06Q20/401—Transaction verification
    • G06Q20/4016—Transaction verification involving fraud or risk level assessment in transaction processing
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
    • G06F16/20—Information retrieval; Database structures therefor; File system structures therefor of structured data, e.g. relational data
    • G06F16/27—Replication, distribution or synchronisation of data between databases or within a distributed database system; Distributed database system architectures therefor
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q20/00—Payment architectures, schemes or protocols
    • G06Q20/02—Payment architectures, schemes or protocols involving a neutral party, e.g. certification authority, notary or trusted third party [TTP]
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q20/00—Payment architectures, schemes or protocols
    • G06Q20/38—Payment protocols; Details thereof
    • G06Q20/389—Keeping log of transactions for guaranteeing non-repudiation of a transaction
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q20/00—Payment architectures, schemes or protocols
    • G06Q20/38—Payment protocols; Details thereof
    • G06Q20/40—Authorisation, e.g. identification of payer or payee, verification of customer or shop credentials; Review and approval of payers, e.g. check credit lines or negative lists
    • G06Q20/401—Transaction verification
    • G06Q20/4014—Identity check for transactions
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q40/00—Finance; Insurance; Tax strategies; Processing of corporate or income taxes
    • G06Q40/04—Trading; Exchange, e.g. stocks, commodities, derivatives or currency exchange
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F2216/00—Indexing scheme relating to additional aspects of information retrieval not explicitly covered by G06F16/00 and subgroups
    • G06F2216/03—Data mining
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q2220/00—Business processing using cryptography

Definitions

  • This specification relates to the field of blockchain technology, and in particular, to a data sharing method, device, and device.
  • the embodiments of the present specification provide a data sharing method, device and device, so that intra-enterprise data can be exchanged and shared across organizations, so as to reduce the difficulty and cost of enterprise informatization construction and improve data utilization.
  • the embodiments of this specification adopt the following technical solutions: the embodiments of this specification provide a data sharing method, including: when a transaction request initiated by a user is received, determining whether there is precipitation data corresponding to the user in the blockchain, the The precipitation data is used to characterize whether the user's transaction request is industry experience data of suspicious transactions; when it is determined that the precipitation data does not exist in the blockchain, the data is broadcast to the blockchain nodes in the blockchain Query request, the data query request contains the user information of the user; receive the transaction link data returned by the blockchain node in response to the data query request, the transaction link data is where the user information is stored The link data of the corresponding transaction data in the blockchain node is mined; the precipitation data corresponding to the user is mined according to the transaction link data.
  • the embodiment of this specification also provides a data sharing device, including: a determination module, when receiving a transaction request initiated by a user, determining whether there is precipitation data corresponding to the user in the blockchain, and the precipitation data is used to represent all the precipitation data.
  • the broadcast module when the determination module determines that the precipitation data does not exist in the blockchain, broadcast to the blockchain nodes in the blockchain a data query request, where the data query request includes the user information of the user; a receiving module receives the transaction link data returned by the blockchain node in response to the data query request, and the transaction link data is the The link data of the transaction data corresponding to the user information in the blockchain node; the mining module mines the precipitation data corresponding to the user according to the transaction link data.
  • Embodiments of this specification also provide an electronic device for data sharing, comprising: at least one processor; and a memory communicatively connected to the at least one processor; wherein the memory stores data that can be used by the at least one processor.
  • Instructions executed by the processor the instructions are executed by the at least one processor, so that the at least one processor can: when a transaction request initiated by a user is received, determine whether there is a user-initiated transaction request in the blockchain Precipitation data, the precipitation data is used to indicate whether the user's transaction request is industry experience data of suspicious transactions; when it is determined that the precipitation data does not exist in the blockchain, it is sent to the district in the blockchain.
  • the blockchain node broadcasts a data query request, and the data query request includes the user information of the user; receives the transaction link data returned by the blockchain node in response to the data query request, and the transaction link data is all link data of the transaction data corresponding to the user information in the blockchain node; mining the precipitation data corresponding to the user according to the transaction link data.
  • the above-mentioned at least one technical solution adopted in the embodiments of this specification can achieve the following beneficial effects: by forming a data sharing alliance with institutional participants who need to undertake preset obligations and are willing to share data, use the shared fragmented data to form industry precipitation data, alleviate data
  • the isolated island provides a way to share industry experience, which can greatly reduce the operating cost of institutional participants assuming preset obligations, reduce the compliance business risks of institutional participants, and improve the supervision efficiency of third-party authoritative institutions.
  • FIG. 1 is a schematic structural diagram of a data sharing application solution provided by an embodiment of the present specification.
  • FIG. 2 is a flowchart of a data sharing method according to an embodiment of the present specification.
  • FIG. 3 is a schematic diagram of a smart contract in a data sharing method provided by an embodiment of the present specification.
  • FIG. 4 is a schematic diagram of a data structure of precipitation data in a data sharing method according to an embodiment of the present specification.
  • FIG. 5 is a schematic structural diagram of block data in a data sharing method provided by an embodiment of the present specification.
  • FIG. 6 is a schematic structural diagram of a data storage layer in a data sharing method provided by an embodiment of the present specification.
  • FIG. 7 is a logical schematic diagram of an incentive mechanism in a data sharing method provided by an embodiment of the present specification.
  • FIG. 8 is a schematic diagram of the logic of a supervisory node performing punishment in a data sharing method provided by an embodiment of the present specification.
  • FIG. 9 is a schematic diagram of a blockchain architecture for data sharing in a data sharing method provided by an embodiment of the present specification.
  • FIG. 10 is a schematic structural diagram of a business application layer in a blockchain structure in a data sharing method provided by an embodiment of this specification.
  • FIG. 11 is a schematic structural diagram of a data sharing apparatus according to an embodiment of the present specification.
  • transaction data is often highly confidential data of enterprises and users (such as certificate number, bank card number, transaction flow, transaction object, delivery address, etc.), but in reality, it is difficult to eliminate the problem of mutual trust between enterprises.
  • users such as certificate number, bank card number, transaction flow, transaction object, delivery address, etc.
  • input-output ratio of information construction is more than concerns, so the motivation of enterprises to exchange and share data is significantly insufficient. Therefore, improving the willingness of enterprises is even more prominent than overcoming the difficulties of technical difficulties.
  • the inventor has explored a set of solutions for data exchange and sharing across institutions through technical analysis, and achieved cross-organizational data exchange and sharing among various institutions in the industry by building a sharing alliance and establishing an industry experience precipitation system. And it can allow enterprises to conduct in-depth customer identification in a low-cost way, so as to save huge investment costs for enterprises, improve the ability of enterprises to meet regulatory requirements, and contribute to the fight against illegal transactions in the whole society.
  • FIG. 1 is a schematic structural diagram of a data sharing application solution provided by an embodiment of the present specification.
  • the institution that receives the transaction request initiated by the user first inquires in the current blockchain whether the user has corresponding precipitation data, wherein the precipitation data is used to indicate whether the user's transaction request is an industry of suspicious transactions
  • the industry experience data is the data that institutions in the industry accumulate their own experience and share them in the blockchain.
  • the precipitation data cannot be used to determine whether the user's transaction request is a suspicious transaction, the institution will report to the sharing alliance.
  • Other members (for the sake of simplicity, only organization members A, B, and C are identified in the figure) broadcast data query requests, and each member node that receives the query request can respond to the query request, and then report the user's existing data in this node.
  • the existing data can be the link data of the transaction involving the user in the institution, such as the transaction link data of the user in institution A, the transaction link data in institution B, and the transaction link data in institution C. transaction link data, etc.; then use smart contracts to process the fragmented data shared by various institutions (such as cleaning, processing, etc.), and splicing a transaction link involving the user; finally, according to industry experience rules, such as running a pre- Defined rules of thumb, where the rules of thumb can be smart contracts composed of industry experience, to find out whether the user in the query request has suspicious risks of illegal transactions.
  • the blockchain used may be a consortium chain, wherein each block chain node in the consortium chain may include preset obligations (such as combating illegal transaction obligations, supervision obligations) Institutional participants who are willing to form a data sharing alliance, and each newly joined node needs to be verified and audited to ensure that each node has the obligation and willingness to participate in data sharing.
  • preset obligations such as combating illegal transaction obligations, supervision obligations
  • an embodiment of this specification provides a data sharing method, which can be applied to the first blockchain node.
  • the data sharing method may include the following steps: Step S102: When receiving a transaction request initiated by a user, Determine whether there is precipitation data corresponding to the user in the blockchain.
  • the precipitation data is industry experience data used to characterize whether the user's transaction request is a suspicious transaction.
  • the first blockchain node is the first node when the user conducts a transaction.
  • the first blockchain node can be the transfer bank, and the first blockchain node can be the first node of the transaction.
  • the existing precipitation data in the blockchain determine whether the user's transaction request may be a suspicious transaction.
  • the user's transaction request can be processed accordingly. For example, when it is a suspicious transaction, the user's transaction request can be intercepted, traced, recorded and tracked. , reporting and other operations, if it is a non-suspicious transaction, the user's transaction will be released directly, that is, the user's transaction request will be completed.
  • the first blockchain node can generate a data query request according to the user's transaction request, so as to request data from other blockchain nodes (ie, other institutions) in the blockchain.
  • industry experience data may be industry experience data accumulated in combating illegal transactions, which may be determined according to actual application scenarios.
  • industry experience data may be industry rules and experience used to combat money laundering.
  • the first blockchain node can determine whether the user's transaction request is a suspicious transaction according to the precipitation data in the blockchain.
  • the first blockchain node can determine whether the user's transaction request is a suspicious transaction according to a smart contract, wherein the smart contract can integrate corresponding contract rules, and the contract rules are used to determine whether the user's transaction request is suspicious. transaction risk.
  • Step S104 when it is determined that the precipitation data does not exist in the blockchain, broadcast a data query request to other blockchain nodes in the blockchain, where the data query request includes the user information of the user .
  • the data query request may be generated according to the user's transaction request.
  • the data query request may include user information of the user, and may also include transaction objects, transaction links, and other information.
  • the user information may include the identification of the user in various institutions, such as an ID number, a business license number, an account, and the like.
  • Step S106 Receive transaction link data returned by the other blockchain nodes, where the transaction link data is the link data of the transaction data corresponding to the user information in the other blockchain nodes.
  • each blockchain node in the blockchain that is, the first blockchain node and other blockchain nodes, both undertake preset obligations (such as the obligation to crack down on illegal transactions) and are willing to form a data sharing alliance institutional participants.
  • each newly added node needs to undergo identity verification such as verification, audit, etc., to ensure that each node added to the sharing can undertake preset obligations and are willing to participate in the data sharing.
  • Step S108 mining the precipitation data corresponding to the user according to industry experience rules.
  • the industry rule of thumb may be a rule formed based on the experience of cracking down on illegal transactions in the industry, through which the fragmented data shared by various institutions can be quickly processed to identify the user's transaction may be suspicious. Risk level, and form the precipitation data corresponding to the user, which is deposited in the blockchain.
  • the precipitation data is the industry experience data obtained by mining according to the fragment data shared by various institutions, that is, the precipitation data is obtained by splicing the shared data fragments and then performing risk mining again, the precipitation data already includes various institutions. Precipitated empirical data such as strategies, rules, and models.
  • the precipitation data can be combined with the smart contract, that is, the industry experience rules for judging suspicious transactions are integrated in the smart contract, so that the computer-programmed rules can be used automatically to quickly determine whether the user's transaction request is a suspicious transaction. .
  • the smart contracts implemented by ether since the smart contracts implemented by ether already have Turing-complete programming language functions and can support the definition of arbitrarily complex contract rules in practice, the smart contracts implemented by ether can be used for reference to share data
  • the industry experience data (such as experience, rules, etc.) in the alliance are defined as contract rules for smart contracts.
  • the overall architecture diagram of the smart contract may be shown in FIG. 3 .
  • the industry experience data used to define the corresponding contract rules may include industry policy rules, machine learning models, etc., as well as subject information, transaction frequency or length (real-time) in the transaction data.
  • the smart contracts are committed to reflecting the sharing and precipitation of industry data (such as experience knowledge), so that when obtaining the data shared by various institutional participants, smart contracts can be used from various Precipitation data is mined from the fragmented data shared by institutional participants, and corresponding contract rules are formed, which can quickly determine transaction risks.
  • smart contracts can be defined with reference to the smart contracts of Ethereum and specific application scenarios, and no specific restrictions are made here.
  • the user information of the user can be used as a data identifier in the precipitation data, and then the precipitation data can be stored in the blockchain by using the data identifier, so as to facilitate quick data query according to the user information.
  • the user data constructed by each institution involves user information, so the data identifier of the precipitation data can be the user information of the user, or in the data construction of each institution, when constructing user data, the The data identification of the precipitation data is included in the user data, so that the blockchain can process the precipitation of the fragmented data shared by various institutions.
  • the certificate number when each institution constructs user data, it usually involves the user's certificate number, and the certificate number usually uniquely corresponds to the natural person and enterprise in the real life scene, so the user information in the precipitation data can use the user's certificate number.
  • the certificate number can be the ID number, passport number, social security number, business license number, institution code, etc.
  • the current account system is often designed so that one certificate number (ie, natural person, enterprise) can apply for opening multiple intra-organization accounts.
  • a natural person can use the same ID
  • opening multiple bank accounts in the same bank such as opening multiple bank cards
  • suspects engaged in illegal trading activities often obtain batches of certificate numbers from upstream black companies, and use these certificate numbers to register numerous trading accounts, so that even if a certain account is blocked in illegal transactions, illegal transactions can still be processed. Quickly switch to a new account (or register a new account quickly).
  • the trace work in the data sharing alliance can be unified to the data processing granularity of the certificate number, which is conducive to efficiently identifying whether the newly registered account related to the certificate number exists.
  • the possibility of suspicious transactions is also conducive to the large-scale convergence of the data volume for trace work.
  • the certificate number can be used as the data identification of the precipitation data, and then the precipitation data can be implemented into the granularity of the "document number”.
  • the data structure of the precipitation data finally deposited on the blockchain may adopt the data structure shown in FIG. 4 .
  • idcard_hash can correspond to the HASH (hash) value of the certificate number (indicated by an asterisk in the figure), so as to ensure the privacy and security of the data by encrypting the certificate number; timestamp can be a timestamp, such as The UNIXTIME timestamp is used to indicate the generation time of the data record; query_org_name can be the name of the institution that initiated the query; answer_org_name can be the name of the institution responding to the information, so there can be multiple answer_org_names, which can be stored in a list; aml_suspicious_info can be used as a suspicious The trace information of the transaction is an open data item in the embodiment of this specification, which can store the risk records and punishment actions performed by each institution for the certificate number, and can also be the conclusion that each institution clearly identifies as a suspicious transaction.
  • the granularity of data processing can be unified to the same granularity, such as the certificate number, and then the unified granularity data can be formed into precipitation data, so as to store the precipitation data in the blockchain. , it is convenient to query the precipitation data from the blockchain.
  • the precipitation data can be formed into blocks and uploaded into the blockchain.
  • the block data shown in FIG. 5 can be used and the block chain shown in FIG. 6 can be formed.
  • the block data may include a block header and a block body.
  • the block header is used to store various identifiers that identify the block data
  • the block body is used to store data.
  • Index can be used to identify the number of the block data
  • Previous_hash can be connected to the HASH of the previous block (ie Merkle_root)
  • Timestamp can be a timestamp, used to identify the generation time of the block
  • Nonce can be used to identify Data state changes, such as incentive points; the block body can use the aforementioned data structure (see Figure 4).
  • each of the aforementioned blocks can be put on the chain to realize the formation of a blockchain from block to chain, that is, to form a data storage layer in the blockchain.
  • the Previous_hash of the next block can be connected to the Merkle_root of the previous block, thereby forming a data storage layer in the blockchain.
  • a corresponding data structure can be set in the precipitation data, and the contribution value of each institution can be reflected by the value of the data, wherein the contribution value can be obtained according to the contribution of each institution to the shared alliance (ie, blockchain), It will form incentives for all parties involved in data sharing, ensure that sharing can continue to operate, and have practical social application value.
  • the embodiment of the contribution value may adopt the "point coin", for example, current_coin may be added to the aforementioned data structure (see Figure 4) to record the current situation of the point coin.
  • the contribution value can be used as the "equity" of each institutional participant in the sharing platform, and this equity can be used to constrain and regulate the usage behavior of each institutional participant, and improve the willingness of each institutional participant to share data .
  • the contribution value can be used as the equity to formulate the sharing operation mechanism, and the corresponding incentive mechanism can be designed separately for two different types of blockchain nodes.
  • corresponding integration logic can be designed for the integration incentives of different types of blockchain nodes.
  • the operating mechanism logic of the rights when reading can be as follows: if (institution A's credit coin > default credit value) ⁇ query(idcard_hash) ⁇ else ⁇ return"Insufficient credit coin " ⁇ .
  • the preset integral value in the aforementioned read logic can be set according to the actual application, for example, set to 0; in addition, the preset incremental value in the write logic can also be set according to the actual application, such as setting is N, 2*N, etc.
  • the incentive logic may adopt the schematic diagram shown in FIG. 7 for the point coins of each institutional participant.
  • the credit coins of institution A can include the credit coins obtained when writing and the credit coins obtained when the data is read (that is, the data shared by organization A is referenced by other institutions).
  • the number N of rules written in the smart contract can increase by 2*N (ie 2N) of credits (ie rights and interests).
  • the credits can be increased by N accordingly.
  • the source of regulatory pressure currently faced by institutional participants is mainly the compliance supervision of third-party authoritative organizations (ie, regulators), so the regulators can be incorporated into the sharing consortium as blockchain nodes in the sharing consortium , so that regulators can see the industry contributions of institutional participants, so that industry contributions can be used as reference information during supervision, and institutional participants can be exchanged for certain policy space in supervision to further motivate institutional participants.
  • regulators third-party authoritative organizations
  • the supervisory logic of the supervisory party may adopt the schematic logic shown in FIG. 8 .
  • the supervisor when making a punishment decision, the supervisor can judge whether the punished institutional participant in the blockchain meets the preset conditions according to the contribution of the penalized institution to the sharing alliance, and the preset conditions can be used to represent Whether the institution actively participates in the willingness of the sharing alliance, such as whether the institution's current blockchain credit is greater than the preset threshold (the preset threshold is N in the figure), where the preset threshold indicates that the institution belongs to the threshold of actively participating in sharing , if so, the penalty amount can be reduced, and the reduced penalty amount can be set to the amount obtained by the function f(X), where X is the value of the institution's current point currency, and the function f(X) represents the current point currency X according to the institution To adjust the function of the penalty amount, the function f(X) can be set according to the actual application scenario. For example, f(X) is a linear function, which is not specifically limited here; otherwise, the original penalty decision will be executed.
  • the manifestation of its benefits can include the following:
  • the manifestation of its benefits can include the following:
  • the work of sanction control can be deployed more efficiently, and the ID number of the personnel to be sanctioned can be directly written into the blockchain, so that the participants of each institution can be informed in time, and the lag of the management of the list of the participants of each institution can be reduced. with the risk of omission.
  • the blockchain of the sharing consortium can be designed in layers, and the blockchain architecture of data sharing can adopt the schematic diagram shown in FIG. 9 .
  • the blockchain architecture can include data storage layer, network protocol layer, consensus/incentive layer, smart contract layer and business application layer, and in the architecture design of each layer in the blockchain, the Customize the industry characteristics to combat illegal transactions.
  • the data structure in the previous embodiment can be used (see Figure 4), the fragment data shared by various institutions can be converted into precipitation data, and the blocks of precipitation data (see Figure 5) can be put on the chain to form a blockchain.
  • the data storage layer (see Figure 6) will not be described here.
  • the blockchain in the network protocol layer, can use a distributed network of P2P (Peer-to-peer, point-to-point transmission) type, which can include network types such as pure distributed, hybrid, and structured P2P networks.
  • P2P Peer-to-peer, point-to-point transmission
  • a structured P2P network based on DHT distributed hash table
  • DHT distributed hash table
  • the core idea is to establish indexes of resource data and node data respectively, so as to efficiently locate which part of the data is stored in which On the block node, the principle is consistent with the Kademlia algorithm used by Ethereum, that is, according to the unique ID index value of each node, a binary prefix tree is established to achieve fast data indexing.
  • the ID index value can be set to the certificate number in the foregoing embodiment, and details are not repeated here.
  • the TCP/IP network protocol can be used, which will not be described further.
  • the network protocol layer may also include functions related to network verification for nodes.
  • Network verification can be performed when the node organization accesses the network, and illegal network nodes are excluded from the sharing alliance to avoid Illegal nodes enter the later stage of business.
  • consensus contents such as verification, auditing and authorization for newly added nodes can be set, and the incentive mechanism for blockchain nodes can be set.
  • the consensus for nodes can refer to the existing blockchain consensus.
  • Several consensus mechanisms currently mainstream in the industry include PoW, PoS, DPoS, BFT, PBFT, RAFT and so on.
  • the data sharing solution provided by the embodiments of this specification adopts the consortium chain blockchain, and the institutional participants can be institutions that need to undertake preset obligations, such as financial institutions or third-party payment institutions that combat illegal transaction obligations. Therefore, institutional participants are subjective The probability of intentional fraud is extremely low.
  • DPoS Delegated Proof of Stake
  • the incentive mechanism of the contribution value (ie, point coins) in the foregoing embodiment may be adopted, which will not be repeated here.
  • the smart contract in the previous embodiment can be used to reflect the precipitation and sharing of industry experience and knowledge through the smart contract layer, which will not be described further.
  • institutional participants and third-party authorities can access the blockchain of the shared alliance through the business application layer.
  • institutional participants can apply for joining, certification, etc. in the business application layer, and the supervisor can view the contribution value of each institution through the business application layer, make penalties, and assist in judging the degree of responsibility of each institution.
  • the system architecture shown in FIG. 10 may be adopted, and a RESTful interface is provided in the business application layer, and each blockchain node, such as institutional participants (such as financial institutions), third-party authorities (such as regulatory agencies), Authenticate through the RESTful interface, access log records in log storage, and upload/exit the consortium chain.
  • institutional participants such as financial institutions
  • third-party authorities such as regulatory agencies
  • RESTful is a design style and development method of network applications. It is based on HTTP and can be defined in XML format or JSON format.
  • the function of the resource, the action type is to add, change, and delete the called resource. It does not require institutional participants to change their existing data interfaces, and it is convenient for institutions to access the shared alliance platform.
  • a partial sharing system can be developed, and multiple partial platforms can also be integrated into a larger sharing platform, which can build alliance chains for data sharing in different scopes to ensure that the data sharing platform has good scalability.
  • it can greatly reduce the KYC, STR and other compliance operation costs of institutional participants, reduce the risk of compliance business and the risk of being punished, and also improve the efficiency of regulatory agencies in combating illegal transactions (such as anti-money laundering).
  • the embodiments of this specification also provide an apparatus for data sharing, an electronic device, and a non-volatile computer storage medium.
  • FIG. 11 is a schematic structural diagram of a data sharing apparatus further provided by an embodiment of the present specification.
  • the data sharing apparatus 1100 may include: a determination module 1101 , when receiving a transaction request initiated by a user, determining whether there is precipitation data corresponding to the user in the blockchain, and the precipitation data is used to characterize all the precipitation data.
  • the broadcast module 1102 when the determination module 1101 determines that the precipitation data does not exist in the blockchain, broadcast to the blockchain nodes in the blockchain
  • the data query request includes the user information of the user
  • the receiving module 1103 receives the transaction link data returned by the blockchain node in response to the data query request, and the transaction link data is the link data of the transaction data corresponding to the user information in the blockchain node
  • the mining module 1104 mines the precipitation data corresponding to the user according to the transaction link data.
  • determining whether there is precipitation data corresponding to the user in the blockchain includes: using a first smart contract to determine whether precipitation data corresponding to the user exists in the blockchain.
  • the data sharing apparatus 1100 may further include: a verification module, which performs identity verification on the blockchain nodes newly added to the blockchain.
  • mining the precipitation data corresponding to the user according to the transaction link data includes: mining the precipitation data corresponding to the user by using a second smart contract according to the transaction link data.
  • the user information of the user includes the certificate number of the user; mining out the precipitation data corresponding to the user according to the transaction link data, including: obtaining the certificate number from the transaction link data ; Take the certificate number as the data processing granularity, mine the corresponding precipitation data of the user from the transaction link data.
  • the data sharing apparatus 1100 may further include: a data generation module, which forms block data from the precipitation data, the block data includes a block header and a block body, and the block header is used to store and identify the area The identifier of the block data, the block body is used to store the precipitation data; the chaining module is used to upload the block data to the chain.
  • a data generation module which forms block data from the precipitation data
  • the block data includes a block header and a block body
  • the block header is used to store and identify the area The identifier of the block data
  • the block body is used to store the precipitation data
  • the chaining module is used to upload the block data to the chain.
  • the data sharing apparatus 1100 may further include: a contribution identification module, for setting a contribution identification corresponding to the blockchain node in the blockchain according to the contribution of the blockchain node to the blockchain , and the contribution identifier is used to record the contribution degree of the blockchain node to the blockchain.
  • a contribution identification module for setting a contribution identification corresponding to the blockchain node in the blockchain according to the contribution of the blockchain node to the blockchain , and the contribution identifier is used to record the contribution degree of the blockchain node to the blockchain.
  • the data sharing apparatus 1100 may further include: a first contribution value adjustment module, when the first blockchain node writes the precipitation data into the blockchain, the first blockchain node corresponds to the The value of the contribution flag is incremented by the first amount value.
  • the data sharing apparatus 1100 may further include: a second contribution value adjustment module, when the precipitation data written into the blockchain by the second blockchain node is read by other blockchain nodes, The value of the contribution identifier corresponding to the second blockchain node is increased by the second quantity value.
  • a second contribution value adjustment module when the precipitation data written into the blockchain by the second blockchain node is read by other blockchain nodes, The value of the contribution identifier corresponding to the second blockchain node is increased by the second quantity value.
  • the data sharing apparatus 1100 may further include: a third contribution value adjustment module, when the third blockchain node does not write the precipitation data into the blockchain within a preset time period, the third The value of the contribution identifier corresponding to the blockchain node is deducted by the third quantity value.
  • a third contribution value adjustment module when the third blockchain node does not write the precipitation data into the blockchain within a preset time period, the third The value of the contribution identifier corresponding to the blockchain node is deducted by the third quantity value.
  • the data sharing device 1100 may further include: a penalty adjustment module, when the fourth blockchain node makes a penalty decision on the penalized blockchain node, according to the contribution identifier corresponding to the penalized blockchain node. The value of adjusts the penalty content of the penalty resolution.
  • Embodiments of this specification also provide an electronic device for data sharing, comprising: at least one processor; and a memory communicatively connected to the at least one processor; wherein the memory stores data that can be used by the at least one processor.
  • Instructions executed by the processor the instructions are executed by the at least one processor, so that the at least one processor can: when a transaction request initiated by a user is received, determine whether there is a user-initiated transaction request in the blockchain Precipitation data, the precipitation data is used to indicate whether the user's transaction request is industry experience data of suspicious transactions; when it is determined that the precipitation data does not exist in the blockchain, it is sent to the district in the blockchain.
  • the blockchain node broadcasts a data query request, and the data query request includes the user information of the user; receives the transaction link data returned by the blockchain node in response to the data query request, and the transaction link data is all link data of the transaction data corresponding to the user information in the blockchain node; mining the precipitation data corresponding to the user according to the transaction link data.
  • the embodiments of this specification also provide a non-volatile computer storage medium for data sharing, which stores computer-executable instructions, and the computer-executable instructions are configured to: when a transaction request initiated by a user is received, determine a block Whether there is precipitation data corresponding to the user in the chain, the precipitation data is used to indicate whether the user's transaction request is industry experience data of suspicious transactions; when it is determined that the precipitation data does not exist in the blockchain, Broadcast a data query request to the blockchain nodes in the blockchain, where the data query request includes the user information of the user; receive the transaction link data returned by the blockchain node in response to the data query request , the transaction link data is the link data of the transaction data corresponding to the user information in the blockchain node; the precipitation data corresponding to the user is mined according to the transaction link data.
  • the system, device, device, non-volatile computer storage medium and method provided by the embodiments of this specification are corresponding, and they also have beneficial technical effects similar to those of the corresponding methods, because the beneficial technical effects of the methods have been described in detail above. Therefore, the beneficial technical effects of the corresponding system, apparatus, device, and non-volatile computer storage medium will not be repeated here.
  • a Programmable Logic Device (such as a Field Programmable Gate Array (FPGA)) is an integrated circuit whose logic function is determined by user programming of the device.
  • HDL Hardware Description Language
  • ABEL Advanced Boolean Expression Language
  • AHDL Altera Hardware Description Language
  • HDCal JHDL
  • Lava Lava
  • Lola MyHDL
  • PALASM RHDL
  • VHDL Very-High-Speed Integrated Circuit Hardware Description Language
  • Verilog Verilog
  • the controller may be implemented in any suitable manner, for example, the controller may take the form of eg a microprocessor or processor and a computer readable medium storing computer readable program code (eg software or firmware) executable by the (micro)processor , logic gates, switches, application specific integrated circuits (ASICs), programmable logic controllers and embedded microcontrollers, examples of controllers include but are not limited to the following microcontrollers: ARC 625D, Atmel AT91SAM, Microchip PIC18F26K20 and Silicon Labs C8051F320, the memory controller can also be implemented as part of the control logic of the memory.
  • the controller may take the form of eg a microprocessor or processor and a computer readable medium storing computer readable program code (eg software or firmware) executable by the (micro)processor , logic gates, switches, application specific integrated circuits (ASICs), programmable logic controllers and embedded microcontrollers
  • ASICs application specific integrated circuits
  • controllers include but are not limited to
  • the controller in addition to implementing the controller in the form of pure computer-readable program code, the controller can be implemented as logic gates, switches, application-specific integrated circuits, programmable logic controllers and embedded devices by logically programming the method steps.
  • the same function can be realized in the form of a microcontroller, etc. Therefore, such a controller can be regarded as a hardware component, and the devices included therein for realizing various functions can also be regarded as a structure within the hardware component. Or even, the means for implementing various functions can be regarded as both a software module implementing a method and a structure within a hardware component.
  • a typical implementation device is a computer.
  • the computer can be, for example, a personal computer, a laptop computer, a cellular phone, a camera phone, a smart phone, a personal digital assistant, a media player, a navigation device, an email device, a game console, a tablet computer, a wearable device, or A combination of any of these devices.
  • embodiments of the present invention may be provided as a method, system, or computer program product. Accordingly, the present invention may take the form of an entirely hardware embodiment, an entirely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, the present invention may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, etc.) having computer-usable program code embodied therein.
  • computer-usable storage media including, but not limited to, disk storage, CD-ROM, optical storage, etc.
  • These computer program instructions may also be stored in a computer-readable memory capable of directing a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory result in an article of manufacture comprising instruction means, the instructions
  • the apparatus implements the functions specified in the flow or flow of the flowcharts and/or the block or blocks of the block diagrams.
  • a computing device includes one or more processors (CPUs), input/output interfaces, network interfaces, and memory.
  • processors CPUs
  • input/output interfaces network interfaces
  • memory volatile and non-volatile memory
  • Memory may include forms of non-persistent memory, random access memory (RAM) and/or non-volatile memory in computer readable media, such as read only memory (ROM) or flash memory (flash RAM). Memory is an example of a computer-readable medium.
  • RAM random access memory
  • ROM read only memory
  • flash RAM flash memory
  • Computer-readable media includes both persistent and non-permanent, removable and non-removable media, and storage of information may be implemented by any method or technology.
  • Information may be computer readable instructions, data structures, modules of programs, or other data.
  • Examples of computer storage media include, but are not limited to, phase-change memory (PRAM), static random access memory (SRAM), dynamic random access memory (DRAM), other types of random access memory (RAM), read only memory (ROM), Electrically Erasable Programmable Read Only Memory (EEPROM), Flash Memory or other memory technology, Compact Disc Read Only Memory (CD-ROM), Digital Versatile Disc (DVD) or other optical storage, Magnetic tape cartridges, magnetic tape-disk storage, or other magnetic storage devices, or any other non-transmission medium, may be used to store information that can be accessed by a computing device.
  • computer-readable media does not include transitory computer-readable media, such as modulated data signals and carrier waves.
  • the application may be described in the general context of computer-executable instructions, such as program modules, being executed by a computer.
  • program modules include routines, programs, objects, components, data structures, etc. that perform particular tasks or implement particular abstract data types.
  • the application may also be practiced in distributed computing environments where tasks are performed by remote processing devices that are linked through a communications network.
  • program modules may be located in both local and remote computer storage media including storage devices.

Abstract

本说明书实施例公开了一种数据共享方法、装置及设备。其中数据共享方案，包括：在接收到用户发起的交易请求时，当确定区块链中不存在沉淀数据时，向所述区块链中的其他区块链节点广播数据查询请求；接收所述其他区块链节点响应所述数据查询请求返回的交易链路数据；根据行业经验规则挖掘出所述用户对应的沉淀数据。

Description

一种数据共享方法、装置及设备 技术领域
本说明书涉及区块链技术领域，尤其涉及一种数据共享方法、装置及设备。
背景技术
企业出于成本、收益、数据敏感性、数据安全性等诸多考虑，无意愿将自身的业务数据与其他企业进行交换共享，因而在各行业中存在大量“数据孤岛”，或者说“信息孤岛”。
目前可跨组织进行数据共享的方案，常见的是第三方权威机构(比如法院)因特殊性原因(比如法院执行裁判需要)而建立的非对称数据查询方式，即企业向第三方权威机构开放数据查询服务，第三方权威机构基于该查询服务查询该企业存储的数据，而企业间仍无法进行数据交换共享。
因此，需要一种可以在企业间进行数据交换共享的方案。
发明内容
有鉴于此，本说明书实施例提供了一种数据共享方法、装置及设备，实现企业内数据可以跨组织进行交换共享，以降低企业信息化建设难度和成本，以及提高数据利用。
本说明书实施例采用下述技术方案：本说明书实施例提供一种数据共享方法，包括：当接收到用户发起的交易请求时，确定区块链中是否存在所述用户对应的沉淀数据，所述沉淀数据用于表征所述用户的交易请求是否为可疑交易的行业经验数据；当确定所述区块链中不存在所述沉淀数据时，向所述区块链中的区块链节点广播数据查询请求，所述数据查询请求中包含所述用户的用户信息；接收所述区块链节点响应所述数据查询请求返回的交易链路数据，所述交易链路数据为所述用户信息在所述区块链节点中对应的交易数据的链路数据；根据所述交易链路数据挖掘出所述用户对应的沉淀数据。
本说明书实施例还提供一种数据共享装置，包括：确定模块，当接收到用户发起的交易请求时，确定区块链中是否存在所述用户对应的沉淀数据，所述沉淀数据用于表征所述用户的交易请求是否为可疑交易的行业经验数据；广播模块，当所述确定模块确定所述区块链中不存在所述沉淀数据时，向所述区块链中的区块链节点广播数据查询请求，所述数据查询请求中包含所述用户的用户信息；接收模块，接收所述区块链节点响应所述数据查询请求返回的交易链路数据，所述交易链路数据为所述用户信息在所述区块链节点中对应的交易数据的链路数据；挖掘模块，根据所述交易链路数据挖掘出所述用户对应的沉淀数据。
本说明书实施例还提供一种用于数据共享的电子设备，包括：至少一个处理器；以 及，与所述至少一个处理器通信连接的存储器；其中，所述存储器存储有可被所述至少一个处理器执行的指令，所述指令被所述至少一个处理器执行，以使所述至少一个处理器能够：当接收到用户发起的交易请求时，确定区块链中是否存在所述用户对应的沉淀数据，所述沉淀数据用于表征所述用户的交易请求是否为可疑交易的行业经验数据；当确定所述区块链中不存在所述沉淀数据时，向所述区块链中的区块链节点广播数据查询请求，所述数据查询请求中包含所述用户的用户信息；接收所述区块链节点响应所述数据查询请求返回的交易链路数据，所述交易链路数据为所述用户信息在所述区块链节点中对应的交易数据的链路数据；根据所述交易链路数据挖掘出所述用户对应的沉淀数据。
本说明书实施例采用的上述至少一个技术方案能够达到以下有益效果：通过将需要承担预设义务并愿意数据共享的机构参与者结成数据共享联盟，利用共享的碎片数据形成行业沉淀数据，缓解数据孤岛，提供行业经验可共享方式，可大幅度降低机构参与者承担预设义务的运营成本，降低机构参与者的合规业务风险，提升第三方权威机构的监管效率。
附图说明
为了更清楚地说明本说明书实施例或现有技术中的技术方案，下面将对实施例或现有技术描述中所需要使用的附图作简单地介绍，显而易见地，下面描述中的附图仅仅是本说明书中记载的一些实施例，对于本领域普通技术人员来讲，在不付出创造性劳动性的前提下，还可以根据这些附图获得其他的附图。
图1为本说明书实施例提供的一种数据共享应用方案的结构示意图。
图2为本说明书实施例提供的一种数据共享方法的流程图。
图3为本说明书实施例提供的一种数据共享方法中智能合约的示意图。
图4为本说明书实施例提供的一种数据共享方法中沉淀数据的数据结构示意图。
图5为本说明书实施例提供的一种数据共享方法中区块数据的结构示意图。
图6为本说明书实施例提供的一种数据共享方法中数据存储层的结构示意图。
图7为本说明书实施例提供的一种数据共享方法中激励机制的逻辑示意图。
图8为本说明书实施例提供的一种数据共享方法中监管节点进行处罚的逻辑示意图。
图9为本说明书实施例提供的一种数据共享方法中数据共享的区块链架构示意图。
图10为本说明书实施例提供的一种数据共享方法中区块链结构中业务应用层的结构示意图。
图11为本说明书实施例提供的一种数据共享装置的结构示意图。
具体实施方式
为了使本技术领域的人员更好地理解本说明书中的技术方案，下面将结合本说明书实施例中的附图，对本说明书实施例中的技术方案进行清楚、完整地描述，显然，所描述的实施例仅仅是本申请一部分实施例，而不是全部的实施例。基于本说明书实施例，本领域普通技术人员在没有作出创造性劳动前提下所获得的所有其他实施例，都应当属于本申请保护的范围。
目前，进行违法交易的嫌疑人出于逃避监管的现实目的，往往有意识地将交易链路设计成跨多个金融机构、多个环节、多个主体的形态，比如将金融交易的资金横跨多个资金流通渠道，如银行、第三方支付、电商平台、线下当面交易等等，使得每个交易环节中的主体仅具有一部分切片数据，造成单凭每一个机构的交易数据都无法快速发现交易的可疑之处，更无法洞察整个交易数据所经链路，非常不利于高效率、精准地识别出可疑交易，而且等到机构发现端倪时，违法交易的资金早被成功转移，因而仍然有大量的违法交易行为由于隐蔽程度高，链路复杂，而无法被有效阻断。
这种情况在业界被称为“数据孤岛”现象。
发明人经深入分析，发现造成“数据孤岛”现象的主要原因有：
(1)跨组织进行数据交换共享的技术实现难度较大。
相比于普通的互联网数据(例如登陆、浏览、点击等)，企业对用户交易数据的存储、处理质量、接口均有差异，各企业的数据难以实现统一化输出，给数据交换共享增加不少困难。
(2)数据交换动力不足。
如交易数据往往是企业、用户的高度机密数据(例如证件号、银行卡号、交易流水、交易对象、收货地址等)，而现实中很难消除企业之间的相互信任问题，另外还有数据信息建设的投入产出比顾虑，因而企业进行数据交换共享的动力显著不足，所以提高企业意愿甚至比克服技术难度的困难更加突出。
(3)“冷启动”成本高。
如新成立机构，不仅需要从零开始积累，还可能因自身能力因素需要很长的时间积累数据和建设领域经验。
也就是说，很多企业(或者说组织机构)要么没有技术能力去识别出可疑的洗钱风险用户，要么出于成本收益等考虑，不愿意投入人力物力去进行信息建设，更无意愿与其他企业交换共享数据，导致各企业之间无法将自身数据和自身积累的行业经验沉淀共享，这样各企业不仅重复建设，建设成本高，数据利用率低，而且各企业在面对监管时，所面临的监管压力越来越大，可能受到处罚的风险也越来越高。
例如在金融行业中，目前对于KYC(know your customer，客户身份识别)、STR(suspicious traction report,可疑交易上报)等监管要求越来越高，因信息建设不足、未能识别违法交易等原因受到监管处罚的企业越来越多，如从监管部门公开的数据显示，2020年第1季度总处罚金额达1.74亿元，其中超百万的罚单有16个，其中100％涉及“未按规定履行客户身份识别义务”，56％涉及“与身份不明的客户进行交易”。
因此，鉴于金融交易行为复杂，且嫌疑人又故意将交易资金链路设计为跨机构、跨主体、多环节等，若单独依靠某一个机构积累的数据，将无法快速地发现可疑交易，因而对违法交易的识别有很大滞后性和遗漏。
有鉴于此，发明人通过技术分析，探索出一套可以跨机构进行数据交换共享方案，并通过构建共享同盟以及建立行业经验沉淀系统，实现在行业中各个机构之间跨组织的数据交换共享，并能够以低成本的方式让各企业进行客户深度识别，以节省各企业巨额投入成本，提高企业满足监管要求的能力，并为全社会打击违法交易贡献力量。
基于此，本说明书实施例提供一种新的数据共享方案。
图1为本说明书实施例提供的一种数据共享应用方案的结构示意图。
如图中所示，接收到用户发起交易请求的机构，先在当前区块链中查询该用户是否有对应的沉淀数据，其中沉淀数据用于表征所述用户的交易请求是否为可疑交易的行业经验数据，该行业经验数据为行业中的机构将自身经验沉淀并共享到区块链中的数据，当无法利用沉淀数据确定该用户的交易请求是否属于可疑交易时，该机构将向共享联盟内其他成员(为图示简洁，图中只标识出机构成员A、B、C)广播数据查询请求，接收到查询请求的各成员节点可响应该查询请求，进而将本节点中涉及该用户的已有数据共享出来，其中已有数据可为本机构内涉及该用户进行交易的链路数据，比如该用户在机构A内的交易链路数据、机构B内的交易链路数据、机构C内的交易链路数据等；然后利用智能合约对各机构共享的碎片数据进行数据处理(如清洗、加工等)，拼接出一幅涉及该用户的交易链路；最后根据行业经验规则，如运行一个事先定义好的经验规则，其中经验规则可为由行业经验构成的智能合约，挖掘出查询请求中的该用户是否存在违法交易的可疑风险。
本说明书实施例提供的一种数据共享方案，所采用的区块链可为联盟链，其中联盟链中的各个区块链节点可包括需要承担预设义务(比如打击违法交易义务、监管义务)且有意愿结成数据共享联盟的机构参与者，而且每个新加入的节点需要验证与审核，以保证各个节点都有义务和意愿参与到数据共享中。
以下结合附图，详细说明本申请各实施例提供的技术方案。
如图2所示，本说明书实施例提供一种数据共享方法，可应用于第一区块链节点，所述数据共享方法可包括如下步骤：步骤S102、当接收到用户发起的交易请求时，确定区块链中是否存在所述用户对应的沉淀数据。
其中，沉淀数据为用于表征所述用户的交易请求是否为可疑交易的行业经验数据。
具体实施中，第一区块链节点为用户进行交易时的第一个节点，比如用户在银行进行转账操作，这时第一区块链节点可为转账银行，第一区块链节点可先根据区块链中已有的沉淀数据，确定该用户的交易请求是否可能为可疑交易。
若根据沉淀数据能确定为可疑交易或者为非可疑交易，这时可对该用户的交易请求进行相应处理，比如为可疑交易时，可对该用户的交易请求进行拦截、留痕、记录、追踪、上报等若干操作，为非可疑交易时，直接放行该用户的交易，即完成用户的交易请求。
若无沉淀数据来确定该用户的交易是否属于可疑交易，即目前的区块链中没有能够确定用户的交易是否属于可疑交易的沉淀数据，还需要结合该用户在其他机构中的交易数据，才能进一步确定，这时第一区块链节点可根据用户的交易请求，生成数据查询请求，以向区块链中的其他区块链节点(即其他机构)请求数据。
需要说明的是，行业经验数据可为在打击违法交易中积累的行业经验数据，具体可根据实际应用场景确定，比如银行业中，行业经验数据可为用于打击洗钱的行业规则、经验等。
在一些实施方式中，第一区块链节点可根据区块链中的沉淀数据，判断该用户的交易请求是否为可疑交易。
在一些实施方式中，第一区块链节点可根据智能合约来确定该用户的交易请求是否为可疑交易，其中智能合约可集成有相应的合约规则，合约规则用于确定用户的交易请求属于可疑交易的风险。
步骤S104、当确定所述区块链中不存在所述沉淀数据时，向所述区块链中的其他区块链节点广播数据查询请求，所述数据查询请求中包含所述用户的用户信息。
具体实施中，数据查询请求可根据用户的交易请求生成，比如数据查询请求中可包括有用户的用户信息，还可包括有交易对象、交易链路等信息。
其中，通过用户信息，可将各个机构参与者的共享数据进行拼接。因此，用户信息可包括该用户在各机构中的标识，比如身份证件号码、营业执照号码、账户等。
步骤S106、接收所述其他区块链节点返回的交易链路数据，所述交易链路数据为所述用户信息在所述其他区块链节点中对应的交易数据的链路数据。
具体实施中，区块链中的各个区块链节点，即第一区块链节点和其他区块链节点均为承担预设义务(比如打击违法交易的义务)且有意愿结成数据共享联盟的机构参与者。
在一些实施方式中，新加入的每个节点均需要经过验证、审核等身份核验，确保加入到共享中的各个节点能够承担预设义务和有意愿参与到数据共享中。
步骤S108、根据行业经验规则挖掘出所述用户对应的沉淀数据。
具体实施中，行业经验规则可为根据行业中打击违法交易的经验形成的规则，通过该行业规则可快速地将各个机构共享的碎片数据进行数据处理，以识别出用户的交易可能为可疑交易的风险程度，并形成该用户对应的沉淀数据，沉淀于区块链中。
通过上述步骤S102～S108，通过立足于应用领域的行业特点，结合可疑交易的专家经验，将愿意承担打击违法交易义务又有意愿共享数据的机构参与者结成数据共享联盟，进而基于联盟链的区块链，有针对性地设计数据共享、经验共享的系统，使得体系内的数据针对性更强，使用效率更高，对于整个行业在应对可疑交易的识别时，将起到降本增效的作用，对新成立的机构参与者，也可大幅度降低自身积累行业经验的财务成本、时间成本。
在一些实施方式中，鉴于沉淀数据为根据各个机构共享的片段数据挖掘所得的行业经验数据，即沉淀数据为利用共享的数据碎片拼接后重新进行风险挖掘所得，因而沉淀数据中已包括了各机构沉淀下来的策略、规则、模型等经验数据。
具体实施中，可将沉淀数据结合智能合约，即在智能合约中集成有判断可疑交易的行业经验规则，从而可自动化地使用计算机程序化的规则，快速地确定出用户的交易请求是否为可疑交易。
在一些实施方式中，鉴于以太币实现的智能合约已经具备图灵完备的编程语言功能，并在实操上可以支持定义任意复杂的合约规则，因而可借鉴以太币实现的智能合约，将数据共享联盟中的行业经验数据(比如经验、规则等)定义为智能合约的合约规则。
通过采用智能合约，既方便将行业经验数据进行沉淀，又方便第一区块链节点在接收到用户的交易请求时，基于区块链的智能合约快速地确定出用户的交易请求属于可疑交易的可能性。
在一些实施方式中，智能合约的整体架构图可如图3所示。
如图中所示，在智能合约的结构中，用于定义相应合约规则的行业经验数据，可包括行业的策略规则、机器学习模型等，以及交易数据中的主题信息、交易频率或者长度(即时长)、交易对手、交易金额等各机构所共享的机构内交易链路数据，比如机构A内交易链路、机构B内交易链路、机构C内交易链路。
通过将这些行业数据定义为相应的合约规则形成智能合约，使得智能合约致力于体现行业数据(如经验知识)的共享和沉淀，从而在获得各个机构参与者共享的数据，可以利用智能合约从各个机构参与者共享的碎片数据中挖掘出沉淀数据，并形成相应合约规则，可快速地确定交易风险。
需要说明的是，智能合约可参照以太币的智能合约和具体应用场景进行定义，这里不做具体限定。
在一些实施方式中，沉淀数据中可采用该用户的用户信息作为数据标识，进而利用该数据标识将沉淀数据存储于区块链中，以方便根据该用户信息来快速查询数据。
在一些实施方式中，各机构所建设的用户数据中，均涉及到用户信息，因而沉淀数据的数据标识可为用户的用户信息，或者说各机构的数据建设中，在建设用户数据时，可在用户数据中包含有沉淀数据的数据标识，以方便区块链对各个机构共享的碎片数据进行沉淀处理。
具体实施中，各机构在建设用户数据时，通常涉及用户的证件号，而且证件号通常也唯一地对应于现实生活场景中的自然人、企业，因而沉淀数据中的用户信息可采用用户的证件号，比如根据用户身份，证件号可身份证件号码、护照证件号码、社会保障号码、营业执照号码、机构代码等。
但现实中，各个机构处于各种考虑，在数据建设中常常并非以证件号为数据处理粒度。
例如，对于参与到数据共享的机构来说，目前账号体系的设计常常为一个证件号(即自然人、企业)可以申请开设多个机构内账号，比如银行业中，一个自然人可以使用同一身份证件在同一银行中开设多个银行账户，如开设多张银行卡，因而很难采用证件号作为数据处理粒度。
例如，机构内部在风险策略、规则、模型等数据建设中，仍是基于账号、交易维度等作为处理粒度，目前这样做的原因，一部分是仅依靠一个企业的数据，在自然人粒度上很难保证高精度，另一部分是出于企业自身的业务目标考虑，而不愿意在证件号的粒度上进行处理。
例如，从事违法交易活动的嫌疑人，往往还会从上游黑产中获取批量的证件号，并利用这些证件号注册众多的交易账号，这样违法交易中即使某一个账号被查封，违法交易仍可以快速切换到新的账号上(或者是迅速注册新账号)。
因此，在对各机构共享的碎片数据进行留痕处理时，若未统一到相同数据处理粒度上，数据量将非常庞大和复杂，更不利于数据交换共享的统一和存储。
具体实施中，可鉴于账号背后的证件号不变，可将数据共享联盟中的留痕工作统一到证件号的数据处理粒度上，有利于高效识别该证件号相关的、新注册的账号是否存在可疑交易的可能，也有利于留痕工作的数据量得到大规模收敛。
本说明书实施例提供的数据共享方案中，可采用证件号作为沉淀数据的数据标识，进而将沉淀数据落实到“证件号”的颗粒度上。
在一些实施方式中，在将共享数据的处理统一到证件号后，最终沉淀到区块链上的沉淀数据的数据结构可以采用如图4所示的数据结构。
如图中所示，idcard_hash可对应为证件号的HASH(哈希)值(图中以星号示意)， 从而通过将证件号进行加密以保证数据的隐私和安全；timestamp可为时间戳，比如采用UNIXTIME时间戳，用于表示该数据记录的生成时间；query_org_name可为发起查询的机构名称；answer_org_name可为信息响应的机构名称，因而answer_org_name可以有多个，可采用列表存储；aml_suspicious_info可用于作为可疑交易的留痕信息，本说明书实施例中为一个开放式的数据项，可以存储各机构对该证件号进行的风险记录、处罚动作等，也可以是各机构明确认定为可疑交易的结论等。
因此，在获取到各机构共享的数据后，可将数据处理的颗粒度统一到相同颗粒度，比如证件号，进而将统一颗粒度的数据形成沉淀数据，从而将沉淀数据存储到区块链中，方便从区块链中查询该沉淀数据。
需要说明的是，数据结构可根据实际应用场景的数据进行设计，这里不做具体限定。
在一些实施方式中，可将沉淀数据形成区块并上链到区块链中。
具体实施中，可采用如图5所示的区块数据和形成如图6所示的区块链。
如图5所示，区块数据可包括区块头和区块体。
其中，区块头用于存储标识该区块数据的各种标识，区块体用于存储数据。
例如，区块头中，Index可用于标识区块数据的编号，Previous_hash可连接到前一个区块的HASH(即Merkle_root)，Timestamp可为时间戳，用于标识区块的生成时间，Nonce可用于标识数据状态变更，比如激励的积分；区块体可采用前述数据结构(可见图4)。
如图6所示，可将前述各个区块上链，实现从块到链形成区块链，即形成区块链中的数据存储层。
具体实施中，可将后一个区块的Previous_hash连接到前一个区块的Merkle_root，进而形成区块链中的数据存储层。
在一些实施方式中，鉴于很多跨领域、多主体参与的应用技术在现实中无法得到有效利用，并非全是技术上的落地困难，更多是因为没有提前设计一套对使用者的激励、反馈机制，无法吸引各个参与者有愿意继续使用，造成空有技术平台而无实际价值，这也是造成目前各行业中大量数据孤岛的原因之一。
因此，本说明书实施例提供的数据共享方案中，引入机构的贡献值。
具体实施中，可在沉淀数据中设置相应的数据结构，通过该数据的值来体现各个机构的贡献值，其中贡献值可根据每个机构对共享联盟(即区块链)的贡献而得到，对参与数据共享的各方形成激励作用，保障共享能持续运转下去，具有现实的社会落地应用价值。
具体实施中，贡献值的体现形式可采用“积分币”，比如可在前述数据结构(见图4) 中增加current_coin，用于记录当前积分币的情况。
在一些实施方式中，可将贡献值作为各个机构参与者在共享平台中的“权益”，并以此权益来约束和规范各个机构参与者的使用行为，提高各个机构参与者进行数据共享的意愿。
具体实施中，可将贡献值作为权益来制定共享运作机制，具体可针对两类不同的区块链节点可分别设计相应的激励机制。
具体实施中，可对于不同类型的各个区块链节点的积分激励，设计相应的积分逻辑。
例如，对于查询数据的区块链节点，在读取时，可先判断验证发起查询的机构是否仍有积分可以使用，如果没有则报错。
因此，针对查询数据的节点(比如机构A)，读取时权益的运行机制逻辑可以如下：if(机构A的积分币>预设积分值){query(idcard_hash)}else{return"积分币不足"}。
例如，对于写入数据的区块链节点，在写入时，向该机构对应的区块里增加贡献该数据的积分。
因此，针对写入数据的节点(比如机构A)，写入时权益的运行机制逻辑可以如下：if(写入有效)then积分币(机构A)＝积分币(机构A)+预设增量值。
需要说明的是，前述读取逻辑中的预设积分值可根据实际应用而设置，比如设置为0；还有，写入逻辑中的预设增量值也可根据实际应用进行设置，比如设置为N、2*N等。
在一些实施方式中，针对各个机构参与者的积分币，激励逻辑可采用如图7所示的示意图。
如图中所示，机构A的积分币可包括写入时获得的积分币和被读取数据(即机构A所共享数据被其他机构引用数据)时获得的积分币，比如写入时，根据智能合约写入规则的数量N，积分币(即权益)可相依地增加2*N(即2N)个，比如根据被其他机构引用数据的次数N，积分币可相应地增加N个。
另外，若长时间无贡献，可扣减相应积分币，以更好地激励各个机构贡献数据的积极性。比如机构A持续3个月无数据贡献，这时机构A的积分币可被扣减M个，即机构A的积分币＝当前积分币-M。
因此，通过引入激励机制，而且针对节点的不同贡献进行相应激励，更突出机构参与者对智能合约规则的贡献，更好地体现机构参与者自身行业经验、知识的沉淀和共享，体现共享联盟中更有价值的分享。
在一些实施方式中，机构参与者目前面临的监管压力来源主要为第三方权威机构(即监管方)的合规监管，因而可将监管方纳入到共享联盟中作为共享联盟中的区块链节点，以便监管方可以看到机构参与者的行业贡献，从而可将行业贡献，作为监管时的参考信息，并可在监管中为机构参与者换取一定的政策空间，进一步激励机构参与者。
具体实施中，监管方的监管逻辑可采用如图8所示的示意逻辑。
如图中所示，监管方在作出处罚决议时，可以根据被处罚机构对共享联盟的贡献，即判断区块链中被处罚的机构参与者是否满足预设条件，其中预设条件可用于表征机构是否积极参与到共享联盟的意愿的条件，比如该机构当前的区块链积分币是否大于预设阈值(如图中预设阈值为N)，其中预设阈值表征机构属于积极参与共享的阈值，若是则可降低处罚金额，降低的处罚金额可设置为按函数f(X)获得的金额，其中X为机构的当前积分币的数值，函数f(X)表示根据该机构的当前积分币X进行调整处罚金额的函数，函数f(X)可根据实际应用场景进行设定，比如f(X)为线性函数，这里不做具体限定；若否则执行原处罚决议。
因此，通过激励机制，使得监管方和机构参与者都能从中获取收益，也能够更好地激励各方积极使用共享平台，提高平台落地后的使用价值。
例如，对于机构参与者的区块链节点，其收益的体现可包括如下：
(1)通过查询区块链中已积累的沉淀数据，比如沉淀数据为用户风险的留痕信息，可以快速弥补自身数据建设不足，降低数据建设投入成本和内部运营成本，也能快速、准确地做好合规检查，比如KYC、STR等，有助于降低合规风险；
(2)通过向区块链中写入数据、写入数据被其他机构引用等，可积累在共享联盟中的积分币，以及通过已积累的积分币，可以让监管方感知到机构参与者对行业的贡献，有助于降低被处罚风险，或者减小被处理的力度，减小运营风险和节约运营成本。
例如，对于监管方的区块链节点，其收益的体现可包括如下：
(1)提升各机构参与者对于打击违法交易工作的重视程度，并可以量化各机构参与者的贡献度，以及在进行合规检查、处罚时可将贡献度作为参考信息；
(2)可以更高效地部署制裁控制类的工作，直接将需要被制裁的人员证件号写入区块链，使得各机构参与者能及时获知，降低各机构参与者自身名单管理工作的滞后性与遗漏风险。
在一些实施方式中，可将共享联盟的区块链进行分层设计，数据共享的区块链架构可采用如图9所示的示意图。
如图中所示，区块链架构中可包括数据存储层、网络协议层、共识/激励层、智能合约层和业务应用层，并在区块链中的每一层架构设计中，可针对打击违法交易的行业特性进行定制。
具体实施中，可采用前述实施方式中的数据结构(见图4)，将各个机构共享的碎片数据落地成沉淀数据，并将沉淀数据的区块(见图5)上链形成区块链中的数据储存层(见图6)，这里不再展开说明。
具体实施中，网络协议层中，区块链可使用P2P(Peer-to-peer，点对点传输)类型的分布式网络，可包括纯分布式、混和式、结构化P2P网络等网络类型。
在一些实施方式中，网络协议层中可采用基于DHT(分布式哈希表)的结构化P2P网络，其核心思想就是分别建立资源数据、节点数据的索引，便于高效定位哪一部分数据存储在哪个区块节点上，其原理与以太坊所使用的Kademlia算法保持一致，即根据每个节点所具有的唯一ID索引值，建立一个二叉前缀树，实现数据的快速索引。这里，ID索引值可设置为前述实施例中的证件号，不再赘述。
在通信协议上，可采用TCP/IP网络协议，不再展开说明。
在一些实施方式中，网络协议层中，还可包括针对节点进行网络验证的相关功能，可在节点机构接入到网络时就能进行网络验证，将违法的网络节点剔除出共享联盟中，避免违法节点进入后期业务中。
具体实施中，在共识/激励层设计中，可设置针对新加入的节点进行验证、审核、授权等共识内容，以及可设置针对区块链节点的激励机制。
其中，针对节点的共识可参照现有区块链共识，当前业界主流的几种共识机制包括PoW，PoS，DPoS，BFT、PBFT，RAFT等等。
本说明书实施例提供的数据共享方案采用联盟链区块链，而且机构参与者可为需要承担预设义务的机构，比如打击违法交易义务的金融机构或第三方支付机构，因而机构参与者存在主观故意欺诈的概率极低。
因此，可采用更简洁的DPoS(委托权益证明)共识机制，有效减少联盟链的成员数量，这样委托节点的成员数量进一步缩减，比如可以缩减到11个。
针对激励机制，可采用前述实施例中的贡献值(即积分币)激励机制，这里不赘述。
具体实施中，可采用前述实施方式中的智能合约(见图3)，通过智能合约层体现行业经验知识的沉淀、共享，不再展开说明。
具体实施中，在业务应用层设计中，机构参与者和第三方权威机构(如监管方)可通过业务应用层接入到共享联盟的区块链中。
例如，机构参与者可在在业务应用层中提出加入申请、认证等，监管方可通过业务应用层查看各个机构的贡献值、作出处罚、辅助判断各机构承担义务的尽责程度等。
在一些实施方式中，可采用如图10所示的系统架构，业务应用层中提供RESTful 接口，各区块链节点，比如机构参与者(比如金融机构)、第三方权威机构(比如监管机构)，通过RESTful接口进行鉴权、访问日志存储中的日志记录、上链/出链联盟链。
其中，RESTful是一种网络应用程序的设计风格和开发方式，基于HTTP，可以使用XML格式定义或JSON格式定义，可适用于移动互联网厂商作为业务使能接口的场景，实现第三方OTT调用移动网络资源的功能，动作类型为新增、变更、删除所调用资源，可无需机构参与者更改自身已有数据接口，可方便机构接入到共享联盟平台中。
通过采用前述实施例中的区块链架构，在业界区块链技术的基础上，结合行业中合规业务的特点，有针对性进行架构调整与个性化定制，既可以在一部分机构之间建立出局部的共享体系，也可以将多个局部平台融合成一个更大的共享平台，可在不同范围内建设数据共享的联盟链，保证数据共享平台具有良好的拓展性。实施后，可大幅度降低机构参与者的KYC、STR等合规运营成本，降低合规业务风险和被处罚风险，也可提升监管机构打击违法交易的(比如反洗钱)的效率。
基于同一个发明构思，本说明书实施例还提供用于数据共享的装置、电子设备以及非易失性计算机存储介质。
图11为本说明书实施例还提供的一种数据共享装置的结构示意图。
如图11所示，数据共享装置1100可包括：确定模块1101，当接收到用户发起的交易请求时，确定区块链中是否存在所述用户对应的沉淀数据，所述沉淀数据用于表征所述用户的交易请求是否为可疑交易的行业经验数据；广播模块1102，当确定模块1101确定所述区块链中不存在所述沉淀数据时，向所述区块链中的区块链节点广播数据查询请求，所述数据查询请求中包含所述用户的用户信息；接收模块1103，接收所述区块链节点响应所述数据查询请求返回的交易链路数据，所述交易链路数据为所述用户信息在所述区块链节点中对应的交易数据的链路数据；挖掘模块1104，根据所述交易链路数据挖掘出所述用户对应的沉淀数据。
可选地，确定区块链中是否存在所述用户对应的沉淀数据，包括：利用第一智能合约确定区块链中是否存在所述用户对应的沉淀数据。
可选地，数据共享装置1100还可包括：核验模块，对新加入所述区块链的区块链节点进行身份核验。
可选地，根据所述交易链路数据挖掘出所述用户对应的沉淀数据，包括：根据所述交易链路数据，利用第二智能合约挖掘出所述用户对应的沉淀数据。
可选地，所述用户的用户信息包括所述用户的证件号；根据所述交易链路数据挖掘出所述用户对应的沉淀数据，包括：从所述交易链路数据中获取所述证件号；以所述证件号为数据处理粒度，从所述交易链路数据挖掘出所述用户对应的沉淀数据。
可选地，数据共享装置1100还可包括：数据生成模块，将所述沉淀数据形成区 块数据，所述区块数据包括区块头和区块体，所述区块头用于存储标识所述区块数据的标识，所述区块体用于存储所述沉淀数据；上链模块，将所述区块数据上链。
可选地，数据共享装置1100还可包括：贡献标识模块，根据所述区块链节点对所述区块链的贡献，在所述区块链中设置所述区块链节点对应的贡献标识，所述贡献标识用于记录所述区块链节点对所述区块链的贡献程度。
可选地，数据共享装置1100还可包括：第一贡献值调整模块，当第一区块链节点将所述沉淀数据写入所述区块链时，将所述第一区块链节点对应的贡献标识的值增加第一数量值。
可选地，数据共享装置1100还可包括：第二贡献值调整模块，当第二区块链节点写入到所述区块链的沉淀数据被其他区块链节点读取时，将所述第二区块链节点对应的贡献标识的值增加第二数量值。
可选地，数据共享装置1100还可包括：第三贡献值调整模块，当第三区块链节点在预设时长内无所述沉淀数据写入所述区块链时，将所述第三区块链节点对应的贡献标识的值扣减第三数量值。
可选地，数据共享装置1100还可包括：处罚调整模块，当第四区块链节点对被处罚的区块链节点作出处罚决议时，根据所述被处罚的区块链节点对应的贡献标识的值调整所述处罚决议的处罚内容。
本说明书实施例还提供一种用于数据共享的电子设备，包括：至少一个处理器；以及，与所述至少一个处理器通信连接的存储器；其中，所述存储器存储有可被所述至少一个处理器执行的指令，所述指令被所述至少一个处理器执行，以使所述至少一个处理器能够：当接收到用户发起的交易请求时，确定区块链中是否存在所述用户对应的沉淀数据，所述沉淀数据用于表征所述用户的交易请求是否为可疑交易的行业经验数据；当确定所述区块链中不存在所述沉淀数据时，向所述区块链中的区块链节点广播数据查询请求，所述数据查询请求中包含所述用户的用户信息；接收所述区块链节点响应所述数据查询请求返回的交易链路数据，所述交易链路数据为所述用户信息在所述区块链节点中对应的交易数据的链路数据；根据所述交易链路数据挖掘出所述用户对应的沉淀数据。
本说明书实施例还提供一种用于数据共享的非易失性计算机存储介质，存储有计算机可执行指令，所述计算机可执行指令设置为：当接收到用户发起的交易请求时，确定区块链中是否存在所述用户对应的沉淀数据，所述沉淀数据用于表征所述用户的交易请求是否为可疑交易的行业经验数据；当确定所述区块链中不存在所述沉淀数据时，向所述区块链中的区块链节点广播数据查询请求，所述数据查询请求中包含所述用户的用户信息；接收所述区块链节点响应所述数据查询请求返回的交易链路数据，所述交易链路数据为所述用户信息在所述区块链节点中对应的交易数据的链路数据；根据所述交 易链路数据挖掘出所述用户对应的沉淀数据。
上述对本说明书特定实施例进行了描述。其它实施例在所附权利要求书的范围内。在一些情况下，在权利要求书中记载的动作或步骤可以按照不同于实施例中的顺序来执行并且仍然可以实现期望的结果。另外，在附图中描绘的过程不一定要求示出的特定顺序或者连续顺序才能实现期望的结果。在某些实施方式中，多任务处理和并行处理也是可以的或者可能是有利的。
本说明书中的各个实施例均采用递进的方式描述，各个实施例之间相同相似的部分互相参见即可，每个实施例侧重说明的都是与其他实施例的不同之处。尤其，对于系统、装置、设备、非易失性计算机存储介质实施例而言，由于其与方法是对应的，描述比较简单，相关之处参见方法实施例的部分说明即可。
本说明书实施例提供的系统、装置、设备、非易失性计算机存储介质与方法是对应的，它们也具有与对应方法类似的有益技术效果，由于上面已经对方法的有益技术效果进行了详细说明，因此，这里不再赘述对应的系统、装置、设备、非易失性计算机存储介质的有益技术效果。
在20世纪90年代，对于一个技术的改进可以很明显地区分是硬件上的改进(例如，对二极管、晶体管、开关等电路结构的改进)还是软件上的改进(对于方法流程的改进)。然而，随着技术的发展，当今的很多方法流程的改进已经可以视为硬件电路结构的直接改进。设计人员几乎都通过将改进的方法流程编程到硬件电路中来得到相应的硬件电路结构。因此，不能说一个方法流程的改进就不能用硬件实体模块来实现。例如，可编程逻辑器件(Programmable Logic Device，PLD)(例如现场可编程门阵列(Field Programmable Gate Array，FPGA))就是这样一种集成电路，其逻辑功能由用户对器件编程来确定。由设计人员自行编程来把一个数字系统“集成”在一片PLD上，而不需要请芯片制造厂商来设计和制作专用的集成电路芯片。而且，如今，取代手工地制作集成电路芯片，这种编程也多半改用“逻辑编译器(logic compiler)”软件来实现，它与程序开发撰写时所用的软件编译器相类似，而要编译之前的原始代码也得用特定的编程语言来撰写，此称之为硬件描述语言(Hardware Description Language，HDL)，而HDL也并非仅有一种，而是有许多种，如ABEL(Advanced Boolean Expression Language)、AHDL(Altera Hardware Description Language)、Confluence、CUPL(Cornell University Programming Language)、HDCal、JHDL(Java Hardware Description Language)、Lava、Lola、MyHDL、PALASM、RHDL(Ruby Hardware Description Language)等，目前最普遍使用的是VHDL(Very-High-Speed Integrated Circuit Hardware Description Language)与Verilog。本领域技术人员也应该清楚，只需要将方法流程用上述几种硬件描述语言稍作逻辑编程并编程到集成电路中，就可以很容易得到实现该逻辑方法流程的硬件电路。
控制器可以按任何适当的方式实现，例如，控制器可以采取例如微处理器或处 理器以及存储可由该(微)处理器执行的计算机可读程序代码(例如软件或固件)的计算机可读介质、逻辑门、开关、专用集成电路(Application Specific Integrated Circuit，ASIC)、可编程逻辑控制器和嵌入微控制器的形式，控制器的例子包括但不限于以下微控制器：ARC 625D、Atmel AT91SAM、Microchip PIC18F26K20以及Silicone Labs C8051F320，存储器控制器还可以被实现为存储器的控制逻辑的一部分。本领域技术人员也知道，除了以纯计算机可读程序代码方式实现控制器以外，完全可以通过将方法步骤进行逻辑编程来使得控制器以逻辑门、开关、专用集成电路、可编程逻辑控制器和嵌入微控制器等的形式来实现相同功能。因此这种控制器可以被认为是一种硬件部件，而对其内包括的用于实现各种功能的装置也可以视为硬件部件内的结构。或者甚至，可以将用于实现各种功能的装置视为既可以是实现方法的软件模块又可以是硬件部件内的结构。
上述实施例阐明的系统、装置、模块或单元，具体可以由计算机芯片或实体实现，或者由具有某种功能的产品来实现。一种典型的实现设备为计算机。具体的，计算机例如可以为个人计算机、膝上型计算机、蜂窝电话、相机电话、智能电话、个人数字助理、媒体播放器、导航设备、电子邮件设备、游戏控制台、平板计算机、可穿戴设备或者这些设备中的任何设备的组合。
为了描述的方便，描述以上装置时以功能分为各种单元分别描述。当然，在实施本申请时可以把各单元的功能在同一个或多个软件和/或硬件中实现。
本领域内的技术人员应明白，本发明的实施例可提供为方法、系统、或计算机程序产品。因此，本发明可采用完全硬件实施例、完全软件实施例、或结合软件和硬件方面的实施例的形式。而且，本发明可采用在一个或多个其中包含有计算机可用程序代码的计算机可用存储介质(包括但不限于磁盘存储器、CD-ROM、光学存储器等)上实施的计算机程序产品的形式。
本发明是参照根据本发明实施例的方法、设备(系统)、和计算机程序产品的流程图和/或方框图来描述的。应理解可由计算机程序指令实现流程图和/或方框图中的每一流程和/或方框、以及流程图和/或方框图中的流程和/或方框的结合。可提供这些计算机程序指令到通用计算机、专用计算机、嵌入式处理机或其他可编程数据处理设备的处理器以产生一个机器，使得通过计算机或其他可编程数据处理设备的处理器执行的指令产生用于实现在流程图一个流程或多个流程和/或方框图一个方框或多个方框中指定的功能的装置。
这些计算机程序指令也可存储在能引导计算机或其他可编程数据处理设备以特定方式工作的计算机可读存储器中，使得存储在该计算机可读存储器中的指令产生包括指令装置的制造品，该指令装置实现在流程图一个流程或多个流程和/或方框图一个方框或多个方框中指定的功能。
这些计算机程序指令也可装载到计算机或其他可编程数据处理设备上，使得在计算机或其他可编程设备上执行一系列操作步骤以产生计算机实现的处理，从而在计算机或其他可编程设备上执行的指令提供用于实现在流程图一个流程或多个流程和/或方框图一个方框或多个方框中指定的功能的步骤。
在一个典型的配置中，计算设备包括一个或多个处理器(CPU)、输入/输出接口、网络接口和内存。
内存可能包括计算机可读介质中的非永久性存储器，随机存取存储器(RAM)和/或非易失性内存等形式，如只读存储器(ROM)或闪存(flash RAM)。内存是计算机可读介质的示例。
计算机可读介质包括永久性和非永久性、可移动和非可移动媒体可以由任何方法或技术来实现信息存储。信息可以是计算机可读指令、数据结构、程序的模块或其他数据。计算机的存储介质的例子包括，但不限于相变内存(PRAM)、静态随机存取存储器(SRAM)、动态随机存取存储器(DRAM)、其他类型的随机存取存储器(RAM)、只读存储器(ROM)、电可擦除可编程只读存储器(EEPROM)、快闪记忆体或其他内存技术、只读光盘只读存储器(CD-ROM)、数字多功能光盘(DVD)或其他光学存储、磁盒式磁带、磁带式磁盘存储或其他磁性存储设备或任何其他非传输介质，可用于存储可以被计算设备访问的信息。按照本文中的界定，计算机可读介质不包括暂存电脑可读媒体(transitory media)，如调制的数据信号和载波。
还需要说明的是，术语“包括”、“包含”或者其任何其他变体意在涵盖非排他性的包含，从而使得包括一系列要素的过程、方法、商品或者设备不仅包括那些要素，而且还包括没有明确列出的其他要素，或者是还包括为这种过程、方法、商品或者设备所固有的要素。在没有更多限制的情况下，由语句“包括一个……”限定的要素，并不排除在包括所述要素的过程、方法、商品或者设备中还存在另外的相同要素。
本申请可以在由计算机执行的计算机可执行指令的一般上下文中描述，例如程序模块。一般地，程序模块包括执行特定任务或实现特定抽象数据类型的例程、程序、对象、组件、数据结构等等。也可以在分布式计算环境中实践本申请，在这些分布式计算环境中，由通过通信网络而被连接的远程处理设备来执行任务。在分布式计算环境中，程序模块可以位于包括存储设备在内的本地和远程计算机存储介质中。
以上所述仅为本申请的实施例而已，并不用于限制本申请。对于本领域技术人员来说，本申请可以有各种更改和变化。凡在本申请的精神和原理之内所作的任何修改、等同替换、改进等，均应包含在本申请的权利要求范围之内。

Claims (18)

  1. 一种数据共享方法，包括：
    当接收到用户发起的交易请求时，确定区块链中是否存在所述用户对应的沉淀数据，所述沉淀数据用于表征所述用户的交易请求是否为可疑交易的行业经验数据；
    当确定所述区块链中不存在所述沉淀数据时，向所述区块链中的区块链节点广播数据查询请求，所述数据查询请求中包含所述用户的用户信息；
    接收所述区块链节点响应所述数据查询请求返回的交易链路数据，所述交易链路数据为所述用户信息在所述区块链节点中对应的交易数据的链路数据；
    根据所述交易链路数据挖掘出所述用户对应的沉淀数据。
  2. 如权利要求1所述的方法，确定区块链中是否存在所述用户对应的沉淀数据，包括：
    利用第一智能合约确定区块链中是否存在所述用户对应的沉淀数据。
  3. 如权利要求1所述的方法，所述方法还包括：对新加入所述区块链的区块链节点进行身份核验。
  4. 如权利要求1所述的方法，根据所述交易链路数据挖掘出所述用户对应的沉淀数据，包括：
    根据所述交易链路数据，利用第二智能合约挖掘出所述用户对应的沉淀数据。
  5. 如权利要求1所述的方法，所述用户的用户信息包括所述用户的证件号；
    根据所述交易链路数据挖掘出所述用户对应的沉淀数据，包括：
    从所述交易链路数据中获取所述证件号；
    以所述证件号为数据处理粒度，从所述交易链路数据挖掘出所述用户对应的沉淀数据。
  6. 如权利要求1所述的方法，所述方法还包括：
    将所述沉淀数据形成区块数据，所述区块数据包括区块头和区块体，所述区块头用于存储标识所述区块数据的标识，所述区块体用于存储所述沉淀数据；
    将所述区块数据上链。
  7. 如权利要求1所述的方法，所述方法还包括：
    根据所述区块链节点对所述区块链的贡献，在所述区块链中设置所述区块链节点对应的贡献标识，所述贡献标识用于记录所述区块链节点对所述区块链的贡献程度。
  8. 如权利要求7所述的方法，所述方法还包括：
    当第一区块链节点将所述沉淀数据写入所述区块链时，将所述第一区块链节点对应的贡献标识的值增加第一数量值。
  9. 如权利要求7所述的方法，所述方法还包括：
    当第二区块链节点写入到所述区块链的沉淀数据被其他区块链节点读取时，将所述第二区块链节点对应的贡献标识的值增加第二数量值。
  10. 如权利要求7所述的方法，所述方法还包括：
    当第三区块链节点在预设时长内无所述沉淀数据写入所述区块链时，将所述第三区块链节点对应的贡献标识的值扣减第三数量值。
  11. 如权利要求7所述的方法，所述方法还包括：当第四区块链节点对被处罚的区块链节点作出处罚决议时，根据所述被处罚的区块链节点对应的贡献标识的值调整所述处罚决议的处罚内容。
  12. 一种数据共享装置，包括：
    确定模块，当接收到用户发起的交易请求时，确定区块链中是否存在所述用户对应的沉淀数据，所述沉淀数据用于表征所述用户的交易请求是否为可疑交易的行业经验数据；
    广播模块，当所述确定模块确定所述区块链中不存在所述沉淀数据时，向所述区块链中的区块链节点广播数据查询请求，所述数据查询请求中包含所述用户的用户信息；
    接收模块，接收所述区块链节点响应所述数据查询请求返回的交易链路数据，所述交易链路数据为所述用户信息在所述区块链节点中对应的交易数据的链路数据；
    挖掘模块，根据所述交易链路数据挖掘出所述用户对应的沉淀数据。
  13. 如权利要求12所述的装置，确定区块链中是否存在所述用户对应的沉淀数据，包括：
    利用第一智能合约确定区块链中是否存在所述用户对应的沉淀数据。
  14. 如权利要求12所述的装置，根据所述交易链路数据挖掘出所述用户对应的沉淀数据，包括：
    根据所述交易链路数据，利用第二智能合约挖掘出所述用户对应的沉淀数据。
  15. 如权利要求12所述的装置，所述用户的用户信息包括所述用户的证件号；
    根据所述交易链路数据挖掘出所述用户对应的沉淀数据，包括：
    从所述交易链路数据中获取所述证件号；
    以所述证件号为数据处理粒度，从所述交易链路数据挖掘出所述用户对应的沉淀数据。
  16. 如权利要求12所述的装置，所述装置还包括：
    贡献标识模块，根据所述区块链节点对所述区块链的贡献，在所述区块链中设置所述区块链节点对应的贡献标识，所述贡献标识用于记录所述区块链节点对所述区块链的贡献程度。
  17. 如权利要求16所述的装置，所述装置还包括：
    处罚调整模块，当第四区块链节点对被处罚的区块链节点作出处罚决议时，根据所述被处罚的区块链节点对应的贡献标识的值调整所述处罚决议的处罚内容。
  18. 一种用于数据共享的电子设备，包括：
    至少一个处理器；以及，
    与所述至少一个处理器通信连接的存储器；其中，
    所述存储器存储有可被所述至少一个处理器执行的指令，所述指令被所述至少一个 处理器执行，以使所述至少一个处理器能够：
    当接收到用户发起的交易请求时，确定区块链中是否存在所述用户对应的沉淀数据，所述沉淀数据用于表征所述用户的交易请求是否为可疑交易的行业经验数据；
    当确定所述区块链中不存在所述沉淀数据时，向所述区块链中的区块链节点广播数据查询请求，所述数据查询请求中包含所述用户的用户信息；
    接收所述区块链节点响应所述数据查询请求返回的交易链路数据，所述交易链路数据为所述用户信息在所述区块链节点中对应的交易数据的链路数据；
    根据所述交易链路数据挖掘出所述用户对应的沉淀数据。
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