CN114155081A - Consensus and transaction separation system and method based on five Merkle tree structures - Google Patents
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Abstract
The invention provides a consensus and transaction separation system based on five Merkle tree structures, which comprises: bank system, settlement system, transaction layer, consensus layer and five Merkle tree structures, wherein five Merkle tree structures include: the system comprises a consensus event Merkle tree, a transaction event Merkle tree, a temporary settlement Merkle tree, an anti-money laundering data Merkle tree and a bank settlement Merkle tree, wherein a consensus layer realizes a consensus mechanism, a transaction layer realizes a transaction mechanism, a settlement system realizes a temporary settlement mechanism and an anti-money laundering mechanism, a bank system realizes a bank settlement mechanism, and the consensus mechanism supports the transaction mechanism, the temporary settlement mechanism, the anti-money laundering mechanism and a final settlement mechanism; the five Merkle trees are independently established and maintained, but are referenced to each other. A consensus and transaction separation method based on five Merkle tree structures comprises the following steps: five Merkle trees are referenced to each other; and performing distributed real-time analysis and auditing.
Description
Technical Field
The invention belongs to the technical field of block chains, in particular relates to a block chain model based on consensus and transaction separation and 5 Merkle tree structures on the block chain model, and particularly relates to a system and a method for consensus and transaction separation based on five Merkle tree structures.
Background
Conventional blockchain systems use a Merkle tree and consider consensus as transaction, and consensus completion as transaction completion, which also represents settlement completion. However, the following technical defects exist:
(1) because the consensus is that the transaction is completed, if money washing phenomenon is found, the fund cannot be recovered; or if a problem is subsequently discovered with the transaction, the funds or assets cannot be recovered because they have already been settled.
(2) In addition to the risk of money laundering, reliability is also problematic. If the number of transactions per transaction is large, the probability of transaction failure is high. In fact, a transaction with a large data volume will almost certainly fail, for example, a transaction data block contains ten thousand transactions, and most of the ten thousand transactions will fail (the specific failure reason may include insufficient account balance or insufficient gas, etc.), and as long as one transaction occurs in the ten thousand transactions, the consensus failure will be caused, resulting in the failure of the entire ten thousand transactions, thereby causing a reliability risk.
(3) In addition, the transaction system based on the block chain needs to be supervised, and the supervision mechanisms should be fused with the block chain system. However, few such designs are currently available.
The current solutions and problems mainly include:
(1) reducing the number of transactions contained in the data block, for example, changing ten thousand transactions into one hundred or one thousand transactions, so that even if the consensus fails, only one hundred or one thousand transactions fail, but such a mechanism causes a slow transaction speed and still causes the case that the transaction which should be successful is determined to fail; and. However, the above solution corresponds to settlement on the blockchain system, and the modern financial transaction system needs settlement at banks or financial institutions, so the settlement on the blockchain system is only "temporary settlement" and not final settlement.
(2) The recent development is to separate the transaction and settlement and use 2 Merkle trees, one for managing transaction and one for managing settlement, which is designed based on the american facebook stable currency item, and the settlement system FastPay proposed by the facebook stable currency system can settle in the financial institution, but has the following serious problems: the blockchain system is not used, although the blockchain technology is used, the blockchain system is not used; without the support of the Merkle tree data structure, the facebook system FastPay has many problems even though the blockchain system is relatively complete.
(3) The traditional block chain system has only one tree with different contents, but all information exists together, so that the query is complex. The facebook blockchain system has two trees and can support various different transactions, but the facebook system does not take the anti-money laundering and settlement mechanism as the necessary mechanism of the blockchain system, and modern financial transactions must have the functions of settlement and anti-money laundering at the same time, and the settlement mechanism is complex and needs multiple financial institutions to participate, so the 2-tree structure of facebook cannot solve the problems.
Disclosure of Invention
The invention provides a consensus and transaction separation system and method based on five Merkle tree structures in order to solve one or more technical problems in the prior art, wherein the data structures of the five Merkle tree structures support:
(1) a mechanism to separate consensus from transaction;
(2) mechanisms for transaction and temporary settlement separation;
(3) a mechanism for transient settlement and anti-money laundering (AML) segregation;
(4) mechanism for temporal settlement and (final) settlement segregation.
The invention aims to provide a consensus and transaction separation system based on five Merkle tree structures, which comprises:
the system comprises a bank system, a settlement system, a transaction layer, a consensus layer and five Merkle tree structures, wherein the five Merkle tree structures comprise: the system comprises a consensus event Merkle tree, a transaction event Merkle tree, a temporary settlement Merkle tree, an anti-money laundering data Merkle tree and a bank settlement Merkle tree, wherein the consensus layer realizes a consensus mechanism, the transaction layer realizes a transaction mechanism, the settlement system realizes a temporary settlement mechanism and an anti-money laundering mechanism, the bank system realizes a bank settlement mechanism, and the consensus mechanism supports the transaction mechanism, the temporary settlement mechanism, the anti-money laundering mechanism and a final settlement mechanism;
the five Merkle trees are independently established and maintained, but are referenced to each other, including:
the relationship between the consensus event Merkle tree and the transaction event Merkle tree is as follows: the data unique identifier in the transaction event can find a correspondence in a successful consensus event;
the relationship of the transaction event Merkle tree and the temporary settlement Merkle tree: the temporary settlement Merkle tree at the time t1 and the temporary settlement Merkle tree at the time t2 can obtain the temporary settlement Merkle tree at the time t2 by calculating the transaction event between the time t1 and the time t2, and mutual authentication is carried out, so that the data or system errors are prevented from being tampered by someone;
the relationship of the transaction event Merkle tree and the bank settlement Merkle tree is as follows: the bank system counts out cross-bank transaction data by reading data of the transaction event Merkle tree species, and then carries out settlement among banks according to the cross-bank transaction data to generate a final bank settlement Merkle tree;
the relationship between the transaction event Merkle tree and the anti-money laundering data Merkle tree: and reading data from the transaction event Merkle tree, counting transaction information and account information related to anti-money laundering in parallel, and obtaining a final anti-money laundering data Merkle tree.
Preferably, the Merkle tree of the consensus event is generated by the consensus layer, and the consensus state is recorded; the common identification layer is only responsible for synchronous work of data among all nodes and transaction data uplink, namely, a data synchronization mechanism of transaction data among all nodes is provided, and all data are only linked regardless of transaction success and failure, and common identification events corresponding to the common identification event Merkle tree comprise common identification event marks, timestamps, common identification participating nodes, leader nodes and first associated common identification marks; the consensus event mark comprises a block chain identity card, and the associated consensus mark comprises the consensus marks of pre-transaction, in-transaction, pre-settlement, anti-money laundering and settlement; the unique identifier of the data block is the unique identifier of the transaction data needing to be identified, and the identification status comprises two statuses, namely successful identification and failed identification; and packaging all the consensus events in a period of time into a Merkle tree to form the consensus event Merkle tree.
Preferably, the transaction event Merkle tree is generated by the transaction layer and records failed transactions, successful transactions and reasons of transaction failure in one data block; the transaction layer is positioned above the consensus layer, only deals with the transaction which is successfully identified, namely, the transaction is successfully and synchronously processed at each data node, the transaction data is subject to the consensus and then is processed by a uniform transaction data processing program, the transaction layer processes all data blocks which are successfully identified in parallel by utilizing a big data technology, and whether the balance of each transaction account is sufficient or not and whether the gas value is sufficient or not are judged so as to judge the success or failure of the transaction; the structure of the transaction event comprises a transaction event mark, transaction data processing starting time, transaction data processing settlement time, a successful transaction set, a failed transaction set, a failure reason and an associated consensus identifier, wherein the associated consensus identifier comprises consensus identifiers of pre-transaction, in-transaction, pre-settlement, anti-money laundering and settlement.
Preferably, the temporary settlement Merkle tree is generated by a temporary settlement system and records the transaction and settlement information corresponding to the account, the transaction event Merkle tree records successful transactions and failed transactions, the temporary settlement system reads successful transactions in the transaction event Merkle tree for settlement of the transaction, and the temporary settlement system can settle the transaction in real time; the temporary settlement Merkle tree is similar to the structure of the consensus event Merkle tree and the transaction event Merkle tree, and a temporary settlement Merkle tree needs to be constructed for storage at intervals; each consensus data block needs a consensus event Merkle tree, and each transaction data block needs a transaction event Merkle tree; settling data in a Merkle tree of a transaction event for a period of time to form a temporary settlement Merkle tree, the temporary settlement event having a structure comprising: the method comprises the following steps of temporarily settling an event identifier, an account unique identifier, an associated transaction set, a balance before settlement, a balance after settlement, a timestamp, an associated transaction identifier and an associated consensus identifier, wherein the associated consensus identifier comprises a consensus identifier of pre-transaction, in-transaction, pre-settlement, anti-money laundering and settlement; the account unique identifier is a hash value of each account, the associated transaction set records all related transactions of the account within a period of time, the balance before settlement is provided by the settled balance of the corresponding account in the previous temporary settlement Merkle tree, and the settled balance is obtained by calculating the balance before calculation through the associated transactions; each account forms a data block and the settlement events for all accounts form a temporary settlement Merkle tree.
Preferably, the anti-money laundering data Merkle tree is generated by an AML analysis system, the AML analysis system reads data in the temporary settlement Merkle tree for anti-money laundering analysis, so as to obtain transaction and account information participating in money laundering, and the structure of the anti-money laundering data comprises: the system comprises an anti-money laundering event identifier, a timestamp, an associated money laundering transaction set, an associated account set, an associated pre-settlement identifier, an associated transaction identifier and an associated consensus identifier, wherein the associated consensus identifier comprises a participated consensus identifier of pre-transaction, in-transaction, pre-settlement and settlement; the temporary money laundering information for each time constitutes one anti-money laundering event, and a plurality of anti-money laundering events constitute one anti-money laundering data Merkle tree.
Preferably, the bank settlement Merkle tree is a tree structure of settlement data for settlement between banks, and generally, the settlement interval between banks is long, and the data structure of the bank settlement event includes: the system comprises a settlement event identifier, a timestamp, a pre-settlement balance, a post-settlement balance, an associated money laundering transaction set, an associated bank account set comprising cross-bank accounts, a related pre-settlement identifier, a related transaction identifier and a related consensus identifier, wherein the related consensus identifier comprises a participatory pre-transaction, in-transaction, pre-settlement and settlement consensus identifier. And the bank system counts transaction data, wherein the cross-bank transaction data are processed and counted in parallel, and cross-bank transactions associated with each bank are processed and counted finally.
Preferably, if the blockchain transaction system does not require a bank or financial institution to settle, the bank settlement Merkle tree may be reduced; if the transaction layer does not have an anti-money laundering mechanism, the anti-money laundering data Merkle tree can be omitted; if the system has a plurality of settlement systems, a plurality of the banks can settle the Merkle trees; one said bank settlement Merkle tree may interact with a plurality of said consensus event Merkle trees and a plurality of said transaction event Merkle trees; or one said bank settlement Merkle tree may interact with a plurality of said anti-money laundering data Merkle trees; the anti-money laundering system can cooperate with a plurality of settlement systems and also can cooperate with a plurality of blockchain trading systems, and the anti-money laundering tree can cooperate with a plurality of consensus trees, a plurality of trading trees and a plurality of settlement trees; and the Merkle tree includes a plurality of categories.
The invention also aims to provide a consensus and transaction separation method based on five Merkle tree structures, which comprises the following steps:
five Merkle trees are referenced to each other; and
and carrying out distributed real-time analysis and audit.
Preferably, the five Merkle trees are mutually referenced by including:
(1) the dependency relationship generated by a single transaction, wherein the five Merkle trees are mutually referenced, and the dependency relationship comprises the following steps for a transaction or a transaction data block:
each transaction event must have at least one consensus, and in the usual case, there are multiple consensus events; the timestamp of the transaction time and the consensus timestamp overlap;
each temporary settlement event corresponds to a specific transaction event or a group of transaction events; and these transaction events must occur at the same time as or before the temporary settlement event;
each anti-money laundering event corresponds to at least one transaction event or at least one transient settlement event;
each settlement event corresponds to a temporary settlement or transaction event and a money laundering event, the settlement events occurring prior to the settlement event; and
(2) the dependency relationship generated by multiple transactions in one block or different blocks, and the relationship of the five trees is complex due to the dependency relationship of the multiple transactions, including:
consensus events support all other events;
one transaction event is before the temporary settlement event, but the previous transaction must be completed first, so that the two-way dependency relationship is realized;
the transaction event must precede the anti-money-laundering event, but the previous anti-money-laundering event must be completed before the transaction, so that the transaction has a two-way dependency relationship;
the transaction event must be before the settlement event, but the previous settlement must be before the transaction event, so that the bidirectional dependency exists;
the temporary settlement event must precede the anti-money-laundering event, but the previous anti-money-laundering must be completed before the temporary settlement event, so that a two-way dependency exists;
preferably, the performing distributed real-time analysis and audit includes:
the method comprises the steps of analyzing different subsystems in real time according to the dependency relationship generated by multiple transactions, and further comprising integrity analysis, consistency analysis and time analysis, wherein the completeness of the system is inquired when one or more auditing subsystems run, so that whether the data on the five trees are consistent or not is always checked.
The invention has the beneficial effects that:
(1) on the basis of separation of consensus and transaction, a data structure with five Merkle tree structures is provided, so that the recording, query and rollback of the transaction can be facilitated, 5 trees can be mutually verified, and cheating of a certain layer of system is prevented. Since each Merkle tree uses a hash algorithm, the 5 trees cannot be easily changed, so that a complete auditing mechanism in the blockchain transaction system is established, the financial system conforms to modern financial transaction rules, and the blockchain transaction system is not evaded for supervision.
(2) The use of five different trees, operating independently and collaborating, can support many different large digital currency, digital asset transactions. The five-tree structure can be responsible for five subsystems, so that the five trees can be processed in parallel, and the speed is increased; and the five trees can be processed in parallel to perform integrity analysis, consistency analysis, time analysis and sequence analysis, and the data structure enables the blockchain system to support a plurality of different transaction modes and processes, including digital currency transaction, digital asset transaction, digital derivatives transaction and digital real estate transaction.
The above and other objects, advantages and features of the present invention will become more apparent to those skilled in the art from the following detailed description of specific embodiments thereof, taken in conjunction with the accompanying drawings.
Drawings
Some specific embodiments of the invention will be described in detail hereinafter, by way of illustration and not limitation, with reference to the accompanying drawings. The same reference numbers in the drawings identify the same or similar elements or components. Those skilled in the art will appreciate that the drawings are not necessarily drawn to scale. The objects and features of the present invention will become more apparent in view of the following description taken in conjunction with the accompanying drawings, in which:
FIG. 1 is a schematic diagram of a data blockchain transaction scheme according to a preferred embodiment of the present invention compared to a conventional blockchain scheme;
FIG. 2 is a diagram of a consensus and transaction separation system based on a five Merkle tree structure in accordance with a preferred embodiment of the present invention;
FIG. 3 is a Merkle tree model of the consensus and transaction separation system based on five Merkle tree structures according to the preferred embodiment of the present invention;
FIG. 4 is a five-tree relationship diagram of the consensus and transaction separation system based on five Merkle tree structures according to the preferred embodiment of the present invention
FIG. 5 is a diagram of a consensus event structure in a five Merkle tree based consensus and transaction separation system according to a preferred embodiment of the present invention;
FIG. 6 is a diagram of a transaction event structure in a five Merkle tree structure based consensus and transaction separation system according to a preferred embodiment of the present invention;
FIG. 7 is a diagram of a temporary settlement event structure in a five Merkle tree structure based consensus and transaction separation system according to a preferred embodiment of the present invention;
FIG. 8 is a diagram of a structure of an anti-money laundering event in a five Merkle tree structure based consensus and transaction separation system according to a preferred embodiment of the present invention;
FIG. 9 is a diagram illustrating a settlement event in a five Merkle tree structure based consensus and transaction separation system according to a preferred embodiment of the present invention;
FIG. 10 is a schematic diagram illustrating dependence of a five-tree relationship on a single transaction in a method for identifying and separating a common transaction based on five Merkle tree structures according to a preferred embodiment of the present invention;
FIG. 11 is a schematic diagram illustrating the dependency of the five-tree relationship of multiple transactions in the method for identifying and separating consensus and transactions based on five Merkle tree structures according to the preferred embodiment of the present invention;
fig. 12 is an overall transaction flow chart in the consensus and transaction separation method based on five Merkle tree structures according to the preferred embodiment of the present invention.
Detailed Description
In order to make the present invention more comprehensible with respect to its gist, the present invention will be further described with reference to the accompanying drawings and examples. In the following description, numerous specific details and specific examples are set forth in order to provide a more thorough understanding of the present invention and to provide a thorough understanding of the present invention. While this invention is susceptible of embodiment in many different forms than that described herein, there will be many equivalents to those skilled in the art which incorporate such variations and modifications without departing from the spirit and scope of the invention as defined by the appended claims and their equivalents.
In the following description, numerous specific details and specific examples are set forth in order to provide a more thorough understanding of the present invention and to provide a thorough understanding of the present invention. While this invention is susceptible of embodiment in many different forms than that described herein, there will be many equivalents to those skilled in the art which incorporate such variations and modifications without departing from the spirit and scope of the invention as defined by the appended claims and their equivalents.
In this embodiment, based on the consensus and transaction separation system and method with five Merkle tree structures, the data structures of the five Merkle tree structures support:
(1) a mechanism to separate consensus from transaction;
(2) mechanisms for transaction and temporary settlement separation;
(3) a mechanism for transient settlement and anti-money laundering (AML) segregation;
(4) mechanism for temporal settlement and (final) settlement segregation.
The scheme of the conventional blockchain system is shown on the left side of fig. 1, and the scheme proposed by the present invention is shown on the right side. Because the mechanism separation mechanism can realize a fusion mechanism (only the separation mechanism needs to be carried out together), but the fusion mechanism cannot carry out the separation mechanism, the five Merkle tree structures can carry out a plurality of transaction flows, including a mechanism of consensus and transaction fusion, a mechanism of transaction and temporary settlement fusion, a mechanism of temporary settlement and money laundering fusion, and a mechanism of temporary settlement and settlement fusion.
Forming a new blockchain operation mode according to various mechanisms of five Merkle tree structures, comprising the following steps:
(1) the consensus mechanism is only responsible for data synchronization between each blockchain node, which is equivalent to regarding the consensus mechanism as a data synchronization mechanism, and the consensus mechanism can simultaneously support transaction, temporary settlement, anti-money laundering and settlement mechanisms.
(2) The transaction mechanism is responsible for software at a higher layer, and the transaction layer is responsible for processing whether the transaction which is commonly recognized to be successful can be successfully transacted or not (mainly responsible for verifying whether the balance is larger than the roll-out amount or not and whether the gas value is enough or not);
(3) the settlement mechanism comprises a temporary settlement mechanism and a bank settlement mechanism, is only responsible for settlement of successful transactions, and is once settled every short period of time, which is equivalent to real-time settlement, and the bank system is responsible for final settlement work and anti-money laundering analysis;
(4) the anti-money laundering mechanism is only responsible for anti-money laundering analysis.
As shown in fig. 2, the present invention provides a system for separating consensus and transaction based on five Merkle tree structures, comprising:
the system comprises a bank system, a settlement system, a transaction layer, a consensus layer and five Merkle tree structures, wherein the five Merkle tree structures comprise: a consensus event Merkle tree, a transaction event Merkle tree, a temporary settlement Merkle tree, an anti-money laundering data Merkle tree and a bank settlement Merkle tree, wherein the consensus layer implements a consensus mechanism, the transaction layer implements a transaction mechanism, the settlement system implements a temporary settlement mechanism and an anti-money laundering mechanism, the bank system implements a bank settlement mechanism, the consensus mechanism supports the transaction mechanism, the temporary settlement mechanism, the anti-money laundering mechanism and a final settlement mechanism, each mechanism requires one Merkle tree, and thus 5 Merkle trees are required, and the consensus tree, the transaction tree, the temporary settlement tree, the anti-money laundering tree and the settlement tree are used to represent the 5 Merkle trees in the following embodiments; where 5 Merkle trees are independently established and maintained, but referenced to each other. For example, a settled transaction must go through the anti-money laundering, and the settlement tree must reference the anti-money laundering tree.
The Merkle tree has the functions of quickly verifying whether data is tampered or not and quickly positioning the tampered data. However, the Merkle tree performs comparison among all data copies of the distributed system, and no function is found for data tampering or system errors at the upper layer, for example, the system has problems, and some data consensus fails and the transaction is successful. The five Merkle trees can mutually prove to prevent someone from tampering system data or system errors.
The relationship between the consensus event Merkle tree and the trade event Merkle tree is as follows: the unique identifier of the data in the transaction event must be able to find correspondence in the successful consensus event.
Relationship of transaction event Merkle tree and temporary settlement Merkle tree: the temporary settlement Merkle tree at the time t1 and the temporary settlement Merkle tree at the time t2 can obtain the temporary settlement Merkle tree at the time t2 by calculating the transaction event between the time t1 and the time t2, and mutual authentication is performed, so that data tampering or system errors can be prevented.
Relationship of transaction event Merkle tree and bank settlement Merkle tree: the bank system counts the cross-bank transaction data by reading the data of the transaction event Merkle tree species, and then carries out settlement between banks according to the cross-bank transaction data to generate a final bank settlement Merkle tree.
Relationship between transaction event Merkle tree and anti-money laundering data Merkle tree: through the method in the patent 'a real-time transaction and discovery money laundering algorithm', data can be read from a transaction event Merkle tree, transaction information and account information related to anti-money laundering are counted in parallel, and a final anti-money laundering data Merkle tree is obtained.
Wherein:
(1) the Merkle tree of the consensus event is generated by the consensus layer, and the consensus state is recorded; the consensus layer is only responsible for synchronous work of data among all nodes;
(2) the transaction event Merkle tree is generated by the transaction layer and records failed transactions, successful transactions and reasons of transaction failure in one data block; the transaction layer is mainly responsible for processing the successfully-identified data blocks in the consensus layer, processes all the successfully-identified data blocks in parallel by utilizing a big data technology, and judges whether the balance of each transaction account is sufficient or not and the gas value is sufficient or not so as to judge the success or failure of the transaction;
(3) the temporary settlement Merkle tree is generated by a temporary settlement system and records the corresponding transaction and settlement information of the account, the transaction event Merkle tree records the successful transaction and the failed transaction, the temporary settlement system reads the successful transaction in the transaction event Merkle tree to settle the transaction, and the temporary settlement system can settle the transaction in real time;
(4) the bank settles the Merkle tree in the bank system at a long interval, for example, once every one minute, once every 10 minutes, or once every 1 hour. Uk central row recommends that the digital currency settlement mechanism needs to be completed in 2 hours. And now the bank only settles once a day on the traditional currency system.
(3) The anti-money laundering data Merkle tree is generated by an AML analysis system that counts data in the temporary settlement Merkle tree, and a specific anti-money laundering analysis method is described in the applicant's earlier patent "a real-time transaction and discovery money laundering algorithm", and forms an anti-money laundering data Merkle tree storing anti-money laundering accounts and transactions after counting.
As a preferred embodiment, if the blockchain transaction system does not require a bank or financial institution to settle, one tree may be reduced, such as by using a settlement system or pre-settlement system instead.
As a preferred embodiment, the anti-money laundering tree may be omitted if the transaction layer does not have an anti-money laundering mechanism.
As a preferred embodiment, if the system has multiple accounting systems participating, there may be multiple accounting trees participating.
In a preferred embodiment, a settlement system may cooperate with a plurality of blockchain trading systems, such that a settlement tree may interact with a plurality of consensus trees and a plurality of trading trees.
As a preferred embodiment, one settlement system may cooperate with a plurality of anti-money laundering systems, such as an international anti-money laundering system, a domestic anti-money laundering system, and a local anti-money laundering system, so that one settlement tree may interact with a plurality of anti-money laundering trees.
In a preferred embodiment, an anti-money laundering system may cooperate with a plurality of settlement systems or a plurality of blockchain trading systems, such that an anti-money laundering tree may cooperate with a plurality of consensus trees, a plurality of trading trees, and a plurality of settlement trees.
In a preferred embodiment, the Merkle tree includes a plurality of categories, and Merkle Patricia trees, for example, are all optional Merkle trees.
As a preferred embodiment, the 5 Merkle trees are similar in structure, but different in data content, and the tree structure is as shown in fig. 3. The data flow relationship between the respective hierarchies is shown in fig. 4. The transaction data is from data which is known by the common identification layer, the transaction system generates transaction data only after processing data which is successfully known by the common identification layer, the temporary settlement data is obtained from the transaction data, the money laundering data is also obtained from the transaction data by analysis, and the bank settlement data can be obtained by collecting temporary settlement data in a period of time.
In a preferred embodiment, the Merkle tree is generated by the consensus layer, which is only responsible for transaction data uplink, i.e. a data synchronization mechanism for transaction data at each node is provided, and all data is only linked up regardless of transaction success and failure. The consensus event corresponding to the consensus event Merkle tree is composed of several parts shown in FIG. 5, including a consensus event mark, a timestamp, a consensus participating node, a leader node and a first associated consensus mark; the consensus event mark comprises a block chain identity card and the like, and the associated consensus marks comprise the consensus marks of pre-transaction, in-transaction, pre-settlement, anti-money laundering and settlement, for example; the unique identifier of the data block is the unique identifier of the transaction data needing to be identified, and the identification status comprises two statuses of successful identification and failed identification. And packaging all the consensus events in a period of time into a Merkle tree to form the consensus event Merkle tree.
As a preferred embodiment, the transaction event Merkle tree is generated by the transaction layer, the transaction layer is located above the consensus layer, the transaction layer only processes the transaction that is successfully identified, that is, the transaction is successfully synchronized at each data node, the transaction data is subject to transaction processing by a uniform transaction data processing program after consensus, and the processing flow may refer to a patent document "a real-time transaction and discovery money laundering algorithm". The transaction layer processes all data blocks with successful consensus in parallel by using a big data technology, and judges whether the balance of each transaction account is sufficient or not, so as to judge the success or failure of the transaction, the structure of the transaction event is shown in fig. 6 and comprises a transaction event mark, transaction data processing starting time, transaction data processing settlement time, a successful transaction set, a failed transaction set, a failure reason and associated consensus identifiers, wherein the associated consensus identifiers are, for example, consensus identifiers of pre-transaction, in-transaction, pre-settlement, anti-money laundering and settlement.
In a preferred embodiment, the temporary settlement Merkle tree is similar to the consensus event Merkle tree and the transaction event Merkle tree in structure, and a temporary settlement Merkle tree needs to be constructed and stored at intervals; each consensus data block needs a consensus event Merkle tree, and each transaction data block needs a transaction event Merkle tree; the temporary settlement Merkle tree is formed by settling data in the Merkle tree of the transaction events for a period of time, and the structure of the temporary settlement events is shown in fig. 7 and includes: temporary settlement event identification, account unique identifier, associated transaction set, balance before settlement, balance after settlement, timestamp, associated transaction identification, and associated consensus identification, such as those involved in pre-transaction, in-transaction, pre-settlement, anti-money laundering, settlement; the account unique identifier is a hash value of each account, the associated transaction set records all related transactions of the account within a period of time, the balance before settlement is provided by the settled balance of the corresponding account in the previous temporary settlement Merkle tree, and the settled balance is obtained by calculating the balance before calculation through the associated transactions; each account forms a data block and the settlement events for all accounts form a temporary settlement Merkle tree.
In a preferred embodiment, the anti-money laundering data Merkle tree is generated by an AML analysis system, the AML analysis system reads data in the temporary settlement Merkle tree for anti-money laundering analysis, and the anti-money laundering parallel analysis method is provided by the patent "a real-time transaction and discovery money laundering algorithm", and transaction and account information participating in money laundering can be obtained through analysis. The structure of the anti-money laundering data is shown in fig. 8, and includes: an anti-money laundering event identifier, a timestamp, an associated money laundering transaction set, an associated account set, an associated pre-settlement identifier, an associated transaction identifier, and an associated consensus identifier, such as a pre-engaged, in-transaction, pre-settlement, settlement consensus identifier. The temporary money laundering information for each time constitutes one anti-money laundering event, and a plurality of anti-money laundering events constitute one anti-money laundering data Merkle tree.
As a preferred embodiment, the bank settlement Merkle tree is a tree structure of settlement data for settlement between banks, and generally settlement between banks may be performed for a long time, for example, for one day, the tree structure of the Merkle tree is the same as the above structure, where stored data is different, and the data structure of the bank settlement event is as shown in fig. 9, and includes: settlement event identification, timestamp, pre-settlement balance, post-settlement balance, associated money laundering transaction collection, associated bank including inter-bank account collection, associated pre-settlement identification, associated transaction identification, and associated consensus identification, such as pre-transaction, in-transaction, pre-settlement, settlement consensus identification for participation. And the bank system counts transaction data, wherein the cross-bank transaction data are processed and counted in parallel, and cross-bank transactions associated with each bank are processed and counted finally.
The invention also aims to provide a consensus and transaction separation method based on five Merkle tree structures, which comprises the following steps:
five Merkle trees are referenced to each other; and
and carrying out distributed real-time analysis and audit.
As a preferred embodiment, the five Merkle trees are mutually referenced including:
(1) the dependency relationship generated by a single transaction, in which the five Merkle trees are mutually referenced, and for a transaction or a transaction data block, the reference relationship between the five Merkle trees is shown in fig. 10, and includes:
each transaction event must have at least one consensus, and in the usual case, there are multiple consensus events; the timestamp of the transaction time and the consensus timestamp overlap;
each temporary settlement event corresponds to a specific transaction event or a group of transaction events; and these transaction events must occur at the same time as or before the temporary settlement event;
each anti-money laundering event corresponds to at least one transaction event or at least one transient settlement event;
each settlement event corresponds to a temporary settlement or transaction event and a money laundering event, both of which occur prior to the settlement event.
(2) The dependency relationship generated by multiple transactions in one block or different blocks, and the relationship of the five trees is complex due to the dependency relationship of the multiple transactions, including:
consensus events support all other events;
one transaction event is before the temporary settlement event, but the previous transaction must be completed first, so that the two-way dependency relationship is realized;
the transaction event must precede the anti-money-laundering event, but the previous anti-money-laundering event must be completed before the transaction, so that the transaction has a two-way dependency relationship;
the transaction event must be before the settlement event, but the previous settlement must be before the transaction event, so that the bidirectional dependency exists;
the temporary settlement event must precede the anti-money-laundering event, but the previous anti-money-laundering must be completed before the temporary settlement event, so that a two-way dependency exists;
FIG. 11 shows a dependency graph of the above multi-transaction 5 tree.
The new type of transaction will generate different dependencies, and the above is only to show the possible scenes of the general transaction. For a new transaction mode, a novel dependency relationship can be found according to the characteristics of the new transaction mode.
As a preferred embodiment, distributed real-time analysis and auditing is performed
The dependency relationships generated according to the multiple transactions can be analyzed in real time in different subsystems. The above relationships can be classified as integrity analysis (e.g., one transaction event is required for each temporary settlement event), Consistency analysis (e.g., one settlement event can only correspond to one transaction event, not 2 transaction events), temporal analysis (e.g., temporary settlement must occur before or at the same time as the transaction). Because the five trees can be handed to different subsystems for parallel processing, one or more auditing subsystems can inquire the completeness of the system during operation, and therefore whether the data on the five trees are consistent is always checked.
As a preferred embodiment, if more complex transactions later occur and more Merkle trees are needed, a new tree can be built out of five trees.
As a preferred embodiment, different transaction modes may have different dependencies, the general case described above. Other special cases may find dependencies for their special cases.
Example (b):
the five trees are controlled by different subsystems and are mutually quoted, and the data structure can support a plurality of different transaction modes, including international large-scale cross-border payment, participation of multi-country financial institutions, participation of a plurality of blockchain systems, participation of a plurality of anti-money laundering institutions and complex transaction mechanisms. The digital currency system of the morgan major bank, for example, includes 20 major banks, 400 financial institutions, and 78 countries. The large-scale digital currency platform needs a large amount of transaction, audit, anti-money laundering and settlement mechanisms to be processed in a parallel and cooperative mode.
The data block consensus and transaction settlement and anti-money laundering process is as follows:
firstly, the consensus of the consensus data block is carried out on the consensus layer, then the consensus event Merkle tree is generated, the transaction layer reads the data which is successfully agreed to carry out transaction analysis, the specific method can refer to a patent 'a real-time transaction and money laundering algorithm', then the transaction layer generates the transaction event Merkle tree, and the temporary settlement Merkle tree is generated by the settlement system at intervals. And after reading the transaction event Merkle tree, performing parallel processing to settle accounts, generating the anti-money laundering data Merkle tree by a settlement system, and reporting the generated anti-money laundering data Merkle tree to a bank system, wherein the bank system can perform corresponding account freezing operation and generate the bank settlement Merkle tree. The relationship between 4 hierarchies and 5 trees is shown in fig. 12.
While the present invention has been described with reference to the particular illustrative embodiments, it is not to be restricted by the embodiments but only by the appended claims. It will be understood by those skilled in the art that variations and modifications of the embodiments of the present invention can be made without departing from the scope and spirit of the invention.
Claims (10)
1. A consensus and transaction separation system based on a five Merkle tree structure, comprising:
the system comprises a bank system, a settlement system, a transaction layer, a consensus layer and five Merkle tree structures, wherein the five Merkle tree structures comprise: the system comprises a consensus event Merkle tree, a transaction event Merkle tree, a temporary settlement Merkle tree, an anti-money laundering data Merkle tree and a bank settlement Merkle tree, wherein the consensus layer realizes a consensus mechanism, the transaction layer realizes a transaction mechanism, the settlement system realizes a temporary settlement mechanism and an anti-money laundering mechanism, the bank system realizes a bank settlement mechanism, and the consensus mechanism supports the transaction mechanism, the temporary settlement mechanism, the anti-money laundering mechanism and a final settlement mechanism;
the five Merkle trees are independently established and maintained, but are referenced to each other, including:
the relationship between the consensus event Merkle tree and the transaction event Merkle tree is as follows: the data unique identifier in the transaction event can find a correspondence in a successful consensus event;
the relationship of the transaction event Merkle tree and the temporary settlement Merkle tree: the temporary settlement Merkle tree at the time t1 and the temporary settlement Merkle tree at the time t2 can obtain the temporary settlement Merkle tree at the time t2 by calculating the transaction event between the time t1 and the time t2, and mutual authentication is carried out, so that the data or system errors are prevented from being tampered by someone;
the relationship of the transaction event Merkle tree and the bank settlement Merkle tree is as follows: the bank system counts out cross-bank transaction data by reading data of the transaction event Merkle tree species, and then carries out settlement among banks according to the cross-bank transaction data to generate a final bank settlement Merkle tree;
the relationship between the transaction event Merkle tree and the anti-money laundering data Merkle tree: and reading data from the transaction event Merkle tree, counting transaction information and account information related to anti-money laundering in parallel, and obtaining a final anti-money laundering data Merkle tree.
2. The system of claim 1, wherein the Merkle tree is generated by the consensus layer and records the status of consensus; the common identification layer is only responsible for synchronous work of data among all nodes and transaction data uplink, namely, a data synchronization mechanism of transaction data among all nodes is provided, and all data are only linked regardless of transaction success and failure, and common identification events corresponding to the common identification event Merkle tree comprise common identification event marks, timestamps, common identification participating nodes, leader nodes and first associated common identification marks; the consensus event mark comprises a block chain identity card, and the associated consensus mark comprises the consensus marks of pre-transaction, in-transaction, pre-settlement, anti-money laundering and settlement; the unique identifier of the data block is the unique identifier of the transaction data needing to be identified, and the identification status comprises two statuses, namely successful identification and failed identification; and packaging all the consensus events in a period of time into a Merkle tree to form the consensus event Merkle tree.
3. The system of claim 1, wherein the Merkle tree of transaction events is generated by the transaction layer and records failed transactions, successful transactions, and reasons for failure of transactions in a data block; the transaction layer is positioned above the consensus layer, only deals with the transaction which is successfully identified, namely, the transaction is successfully and synchronously processed at each data node, the transaction data is subject to the consensus and then is processed by a uniform transaction data processing program, the transaction layer processes all data blocks which are successfully identified in parallel by utilizing a big data technology, and whether the balance of each transaction account is sufficient or not and whether the gas value is sufficient or not are judged so as to judge the success or failure of the transaction; the structure of the transaction event comprises a transaction event mark, transaction data processing starting time, transaction data processing settlement time, a successful transaction set, a failed transaction set, a failure reason and an associated consensus identifier, wherein the associated consensus identifier comprises consensus identifiers of pre-transaction, in-transaction, pre-settlement, anti-money laundering and settlement.
4. The consensus and transaction separation system based on five Merkle tree structures as claimed in claim 1, wherein the temporary settlement Merkle tree is generated by a temporary settlement system and records the transaction and settlement information corresponding to the account, the transaction event Merkle tree records the successful transaction and the failed transaction, the temporary settlement system reads the successful transaction in the transaction event Merkle tree for transaction settlement, and the temporary settlement system can settle the transaction in real time; the temporary settlement Merkle tree is similar to the structure of the consensus event Merkle tree and the transaction event Merkle tree, and a temporary settlement Merkle tree needs to be constructed for storage at intervals; each consensus data block needs a consensus event Merkle tree, and each transaction data block needs a transaction event Merkle tree; settling data in a Merkle tree of a transaction event for a period of time to form a temporary settlement Merkle tree, the temporary settlement event having a structure comprising: the method comprises the following steps of temporarily settling an event identifier, an account unique identifier, an associated transaction set, a balance before settlement, a balance after settlement, a timestamp, an associated transaction identifier and an associated consensus identifier, wherein the associated consensus identifier comprises a consensus identifier of pre-transaction, in-transaction, pre-settlement, anti-money laundering and settlement; the account unique identifier is a hash value of each account, the associated transaction set records all related transactions of the account within a period of time, the balance before settlement is provided by the settled balance of the corresponding account in the previous temporary settlement Merkle tree, and the settled balance is obtained by calculating the balance before calculation through the associated transactions; each account forms a data block and the settlement events for all accounts form a temporary settlement Merkle tree.
5. The system of claim 1, wherein the Merkle tree is generated by an AML analysis system, the AML analysis system reading the data in the temporary settlement Merkle tree for anti-money laundering analysis to obtain the transaction and account information participating in money laundering, and the structure of the anti-money laundering data comprises: the system comprises an anti-money laundering event identifier, a timestamp, an associated money laundering transaction set, an associated account set, an associated pre-settlement identifier, an associated transaction identifier and an associated consensus identifier, wherein the associated consensus identifier comprises a participated consensus identifier of pre-transaction, in-transaction, pre-settlement and settlement; the temporary money laundering information for each time constitutes one anti-money laundering event, and a plurality of anti-money laundering events constitute one anti-money laundering data Merkle tree.
6. The system of claim 1, wherein the bank settlement Merkle tree is a tree structure of settlement data between banks, and the settlement interval between banks is generally long, and the data structure of the bank settlement event comprises: the system comprises a settlement event identifier, a timestamp, a balance before settlement, a balance after settlement, an associated money laundering transaction set, an associated bank comprising an account set across banks, a related pre-settlement identifier, a related transaction identifier and a related consensus identifier, wherein the related consensus identifier comprises a consensus identifier of pre-transaction, in-transaction, pre-settlement and settlement;
and the bank system counts transaction data, wherein the cross-bank transaction data are processed and counted in parallel, and cross-bank transactions associated with each bank are processed and counted finally.
7. The system of claim 1, wherein if the blockchain transaction system does not require banking or financial institution settlement, the banking settlement Merkle tree can be reduced; if the transaction layer does not have an anti-money laundering mechanism, the anti-money laundering data Merkle tree can be omitted; if the system has a plurality of settlement systems, a plurality of the banks can settle the Merkle trees; one said bank settlement Merkle tree may interact with a plurality of said consensus event Merkle trees and a plurality of said transaction event Merkle trees; or one said bank settlement Merkle tree may interact with a plurality of said anti-money laundering data Merkle trees; the anti-money laundering system can cooperate with a plurality of settlement systems and also can cooperate with a plurality of blockchain trading systems, and the anti-money laundering tree can cooperate with a plurality of consensus trees, a plurality of trading trees and a plurality of settlement trees; and the Merkle tree includes a plurality of categories.
8. A consensus and transaction separation method for a system for consensus and transaction separation based on five Merkle tree structures according to any one of claims 1 to 7, comprising:
five Merkle trees are referenced to each other; and
and carrying out distributed real-time analysis and audit.
9. The method of claim 8, wherein the five Merkle trees are mutually referenced by comprising:
(1) the dependency relationship generated by a single transaction, wherein the five Merkle trees are mutually referenced, and the dependency relationship comprises the following steps for a transaction or a transaction data block:
each transaction event must have at least one consensus, and in the usual case, there are multiple consensus events; the timestamp of the transaction time and the consensus timestamp overlap;
each temporary settlement event corresponds to a specific transaction event or a group of transaction events; and these transaction events must occur at the same time as or before the temporary settlement event;
each anti-money laundering event corresponds to at least one transaction event or at least one transient settlement event;
each settlement event corresponds to a temporary settlement or transaction event and a money laundering event, the settlement events occurring prior to the settlement event; and
(2) the dependency relationship generated by multiple transactions in one block or different blocks, and the relationship of the five trees is complex due to the dependency relationship of the multiple transactions, including:
consensus events support all other events;
one transaction event is before the temporary settlement event, but the previous transaction must be completed first, so that the two-way dependency relationship is realized;
the transaction event must precede the anti-money-laundering event, but the previous anti-money-laundering event must be completed before the transaction, so that the transaction has a two-way dependency relationship;
the transaction event must be before the settlement event, but the previous settlement must be before the transaction event, so that the bidirectional dependency exists;
the temporary settlement event must precede the anti-money laundering event, but the previous anti-money laundering must be completed before the temporary settlement event, so that there is a two-way dependency.
10. The method of claim 8, wherein the performing distributed real-time analysis and auditing comprises:
the method comprises the steps of analyzing different subsystems in real time according to the dependency relationship generated by multiple transactions, and further comprising integrity analysis, consistency analysis and time analysis, wherein the completeness of the system is inquired when one or more auditing subsystems run, so that whether the data on the five trees are consistent or not is always checked.
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Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20190103973A1 (en) * | 2017-09-29 | 2019-04-04 | R3 Ltd. | Hash subtrees for grouping components by component type |
| CN111724156A (en) * | 2020-03-30 | 2020-09-29 | 江苏荣泽信息科技股份有限公司 | Payment system based on block chain |
| CN112927072A (en) * | 2021-01-20 | 2021-06-08 | 北京航空航天大学 | Block chain-based anti-money laundering arbitration method, system and related device |
-
2021
- 2021-10-04 CN CN202111167336.3A patent/CN114155081B/en active Active
Patent Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20190103973A1 (en) * | 2017-09-29 | 2019-04-04 | R3 Ltd. | Hash subtrees for grouping components by component type |
| CN111724156A (en) * | 2020-03-30 | 2020-09-29 | 江苏荣泽信息科技股份有限公司 | Payment system based on block chain |
| CN112927072A (en) * | 2021-01-20 | 2021-06-08 | 北京航空航天大学 | Block chain-based anti-money laundering arbitration method, system and related device |
Non-Patent Citations (2)
| Title |
|---|
| 蔡维德 等: "基于区块链的应用系统开发方法研究", 《软件学报》 * |
| 蔡维德 等: "面向大数据的区块链在清算系统中的应用", 《大数据》 * |
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