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WO2022179008A1 - Supply chain finance ai daas algorithm warehouse platform based on blockchain - Google Patents

Supply chain finance ai daas algorithm warehouse platform based on blockchain Download PDF

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Publication number
WO2022179008A1
WO2022179008A1 PCT/CN2021/101105 CN2021101105W WO2022179008A1 WO 2022179008 A1 WO2022179008 A1 WO 2022179008A1 CN 2021101105 W CN2021101105 W CN 2021101105W WO 2022179008 A1 WO2022179008 A1 WO 2022179008A1
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algorithm
data
module
visualization
blockchain
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PCT/CN2021/101105
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French (fr)
Chinese (zh)
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刘天琼
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深圳市爱云信息科技有限公司
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Publication of WO2022179008A1 publication Critical patent/WO2022179008A1/en

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    • GPHYSICS
    • G06COMPUTING; CALCULATING OR COUNTING
    • G06FELECTRIC DIGITAL DATA PROCESSING
    • G06F16/00Information retrieval; Database structures therefor; File system structures therefor
    • G06F16/20Information retrieval; Database structures therefor; File system structures therefor of structured data, e.g. relational data
    • G06F16/27Replication, distribution or synchronisation of data between databases or within a distributed database system; Distributed database system architectures therefor
    • GPHYSICS
    • G06COMPUTING; CALCULATING OR COUNTING
    • G06FELECTRIC DIGITAL DATA PROCESSING
    • G06F16/00Information retrieval; Database structures therefor; File system structures therefor
    • G06F16/20Information retrieval; Database structures therefor; File system structures therefor of structured data, e.g. relational data
    • G06F16/21Design, administration or maintenance of databases
    • G06F16/215Improving data quality; Data cleansing, e.g. de-duplication, removing invalid entries or correcting typographical errors
    • GPHYSICS
    • G06COMPUTING; CALCULATING OR COUNTING
    • G06FELECTRIC DIGITAL DATA PROCESSING
    • G06F16/00Information retrieval; Database structures therefor; File system structures therefor
    • G06F16/20Information retrieval; Database structures therefor; File system structures therefor of structured data, e.g. relational data
    • G06F16/26Visual data mining; Browsing structured data
    • GPHYSICS
    • G06COMPUTING; CALCULATING OR COUNTING
    • G06FELECTRIC DIGITAL DATA PROCESSING
    • G06F9/00Arrangements for program control, e.g. control units
    • G06F9/06Arrangements for program control, e.g. control units using stored programs, i.e. using an internal store of processing equipment to receive or retain programs
    • G06F9/46Multiprogramming arrangements
    • G06F9/54Interprogram communication
    • G06F9/545Interprogram communication where tasks reside in different layers, e.g. user- and kernel-space
    • GPHYSICS
    • G06COMPUTING; CALCULATING OR COUNTING
    • G06FELECTRIC DIGITAL DATA PROCESSING
    • G06F9/00Arrangements for program control, e.g. control units
    • G06F9/06Arrangements for program control, e.g. control units using stored programs, i.e. using an internal store of processing equipment to receive or retain programs
    • G06F9/46Multiprogramming arrangements
    • G06F9/54Interprogram communication
    • G06F9/547Remote procedure calls [RPC]; Web services
    • GPHYSICS
    • G06COMPUTING; CALCULATING OR COUNTING
    • G06QINFORMATION 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
    • G06Q10/00Administration; Management
    • G06Q10/04Forecasting or optimisation specially adapted for administrative or management purposes, e.g. linear programming or "cutting stock problem"
    • GPHYSICS
    • G06COMPUTING; CALCULATING OR COUNTING
    • G06QINFORMATION 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
    • G06Q40/00Finance; Insurance; Tax strategies; Processing of corporate or income taxes
    • G06Q40/04Trading; Exchange, e.g. stocks, commodities, derivatives or currency exchange
    • YGENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y02TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02PCLIMATE CHANGE MITIGATION TECHNOLOGIES IN THE PRODUCTION OR PROCESSING OF GOODS
    • Y02P80/00Climate change mitigation technologies for sector-wide applications
    • Y02P80/10Efficient use of energy, e.g. using compressed air or pressurized fluid as energy carrier

Definitions

  • the invention relates to the field of supply chain finance of blockchain, in particular to a supply chain finance AI DaaS algorithm warehouse platform based on blockchain.
  • DaaS Data as a Service
  • DaaS provides a new way for enterprises to share data with other enterprises through centralized management of data resources and scene-based data; in today's era of data explosion, no enterprise can collect With the DaaS service, you can purchase all the data you need from other companies, and improve the competitiveness of the enterprise through division of labor and collaboration.
  • the financial AI DaaS algorithm warehouse platform solves the problem of algorithm integration and sharing of blockchain supply chain finance.
  • the purpose of the present invention is to provide a blockchain-based supply chain finance AI DaaS algorithm warehouse platform to solve the problem of algorithm fusion and sharing of blockchain-based supply chain finance.
  • the present invention provides a supply chain finance AI DaaS algorithm warehouse platform based on blockchain, including an application layer, an open interface layer, an algorithm warehouse service layer, A data layer and an infrastructure layer, the application layer is used to provide blockchain-based supply chain financial services, the open interface layer is used to provide the application layer with a service connecting the algorithm warehouse service layer, the data The layer is used to provide data service support for the algorithm warehouse service layer, and the infrastructure layer is used to provide development support for the data layer;
  • the application layer includes a letter of credit module, a non-recourse financing module, a supply chain finance module, a smart retail module, a link management module, a smart contract script module, a smart contract template module, and a smart contract management platform. It is used to provide a letter of credit business function, the non-recourse financing module is used to provide a non-recourse financing business function, the supply chain financial module is used to provide support services for trusted credit transfer, and the smart retail module is used for In order to provide smart retail business functions, the link management module is used to provide data link management functions, the smart contract script module is used to provide the automatic writing function of smart contract scripts, and the smart contract template module is used to provide intelligent The function of the contract, the smart contract management platform is used to provide the management function of the smart contract;
  • the open interface layer includes a chain code protocol interface, a blockchain API service interface, an identity authentication service interface, and a light client interface.
  • the chain code protocol interface is a blockchain access interface
  • the blockchain API service interface uses
  • the identity authentication service interface is used to provide the function of verifying user information
  • the light client interface is used to Provide users with a secure and decentralized way to access and interact with the blockchain without synchronizing the entire blockchain;
  • the algorithm warehouse service layer includes a data visualization algorithm module, a KYC verification algorithm module, a trusted identity system algorithm module, a consensus mechanism algorithm module, a privacy protection algorithm module, and a ledger maintenance algorithm module, and the data visualization algorithm module is used for data visualization algorithms.
  • the KYC verification algorithm module is used for the storage and application of the KYC verification algorithm
  • the trusted identity system algorithm module is used for the storage and application of the trusted identity system algorithm
  • the consensus mechanism algorithm module is used for consensus
  • the privacy protection algorithm module is used for the storage and application of the privacy protection algorithm
  • the account book maintenance algorithm module is used for the storage and application of the account book maintenance algorithm;
  • the data layer includes a block data sharing module, a block data governance module, and a block data development module.
  • the block data sharing module is used to provide data sharing functions for different modules
  • the block data governance module is used to provide different modules.
  • Data governance function, the block data development module is used to provide data development function for different modules;
  • the infrastructure layer includes Docker, Docker-compose, K8S
  • the Docker is an open source application container engine
  • the Docker-compose is an application tool for defining and running multi-container Docker
  • the K8S is a container-based cluster management
  • the platform is used to manage Docker and containers.
  • the data visualization algorithm includes a parallel visualization algorithm, an in-situ visualization algorithm, and a time series data visualization algorithm;
  • the parallel visualization algorithm includes a task parallel algorithm, a pipeline parallel algorithm, and a data parallel algorithm; the task parallel algorithm divides the visualization process into independent subtasks, and there is no data dependency between the running subtasks; the pipeline The parallel algorithm uses streaming to read data fragments, divides the visualization process into multiple stages, and executes each stage in parallel by the computer to speed up the processing process; the data parallel algorithm is a single-program multiple-data method, which divides the data into multiple subsets, and then use the subset as the granularity to execute the program in parallel to process the different subsets;
  • the in-situ visualization algorithm is to generate visualization in the process of numerical simulation and is used to alleviate the output bottleneck of large-scale numerical simulation, including image in-situ visualization algorithm, distributed data in-situ visualization algorithm, compressed data in-situ visualization algorithm and feature in-situ visualization.
  • the in-situ visualization algorithm of the image is to map the data into visualization during the numerical simulation process and save it as an image; the in-situ visualization algorithm of the distribution data is calculated according to the statistical index defined by the user during the numerical simulation Statistical indicators are saved, followed by statistical data visualization; the in-situ visualization of the compressed data adopts a compression algorithm to reduce the output scale of the numerical simulation data, and the compressed data is used as the input of the subsequent visualization processing; the feature in-situ visualization algorithm is in the numerical simulation process. Extract features and save them, and use feature data as input for subsequent visualization processing;
  • the time series data visualization algorithm is used to establish a prediction model, perform predictive analysis and user behavior analysis, including an area chart algorithm, a bubble chart algorithm, a Gantt chart algorithm, a heat map algorithm, a histogram algorithm, a line chart algorithm, and a spiral chart algorithm.
  • stacked area chart algorithm quantitative waveform chart algorithm
  • the area chart algorithm is used to display the change and development of the quantitative value within a specified time period
  • the bubble chart algorithm sets the variable of one of the axes to time or the data variable Animated over time
  • the Gantt chart algorithm is used as an organizational tool for project management
  • the heat map algorithm is used to display data by color changes
  • the histogram algorithm is used to display data at successive intervals or at specified times the distribution of data within segments
  • the line chart algorithm for displaying quantitative values over successive intervals or time spans to show trends and relationships
  • the helix chart algorithm for plotting time-based data along an Archimedes spiral
  • the stacking The quantized area chart algorithm works on the same principle as the simple area chart algorithm to display multiple data series at the same time, and the quantized waveform chart algorithm is used to display changes in different categories of data over time.
  • the KYC verification algorithm used in the process of verifying the identity of customers and customers before or during the conduct of business, uses AI-OCR tools to automatically capture, extract and create editable and searchable copies of customer data .
  • the trusted identity system algorithm uses Ethereum for key distribution and management, IPFS for content addressing, ENS for human-readable information analysis, and whisper for secure data transmission channels.
  • the consensus mechanism algorithm includes a workload proof algorithm, an equity proof algorithm, a share authorization proof mechanism algorithm, a Ripple consensus algorithm, and a practical Byzantine fault-tolerant algorithm;
  • the proof-of-work algorithm calculates a random number that satisfies the rules through AND-OR operation, that is, obtains the accounting right this time, sends out the data that needs to be recorded in this round, and stores it together after verification by other nodes in the entire network;
  • the proof-of-stake algorithm uses proof of equity to replace the proof of computing power, and the accounting right is obtained by the node with the highest equity, not the node with the highest computing power, thereby speeding up the speed of finding random numbers;
  • the said share authorization proof mechanism algorithm votes to select relatively reliable nodes through the proportion of assets, which can greatly reduce the number of nodes participating in verification and accounting, and can achieve consensus verification at the second level;
  • the Ripple consensus algorithm occurs between verification nodes.
  • Each verification node is preconfigured with a list of trusted nodes. The nodes on the trusted node list vote for transaction completion, and each verification node will continue to receive messages from the network. After the sent transactions are verified with the local ledger data, the illegal transactions are directly discarded, and the legal transactions will be aggregated into a transaction candidate set.
  • Each verification node sends its own transaction candidate set as a proposal to other verification nodes. After the verification node receives the proposal from other nodes, if it is not from the node on the trusted node list, it will ignore the proposal. If it is Nodes from the list of trusted nodes will compare the transaction in the proposal with the local candidate set of transactions. If there is the same transaction, the transaction will get one vote.
  • the transaction In a certain period of time, when the transaction receives more than 50% of the votes. When there are more than 50% of the votes, the transaction will enter the next round. If there are no more than 50% of the transactions, it will be confirmed by the next consensus process.
  • the verification node will send the transaction with more than 50% of the votes to other nodes as a proposal, and at the same time increase the threshold of the required number of votes. To 60%, repeat the calculation of proposals received by the verification node from other nodes until the threshold reaches 80%, and the verification node officially writes the transactions confirmed by the nodes in the 80% trusted node list into the local ledger data , called the last closed ledger, that is, the final state of the ledger;
  • the practical Byzantine fault-tolerant algorithm is a state machine replica replication algorithm, that is, a service is modeled as a state machine, and the state machine is replicated in different nodes of the distributed system. Each copy of the state machine holds the state of the service and also implements the operation of the service.
  • the privacy protection algorithm includes a differential privacy algorithm, an Apriori algorithm, and a k-anonymity algorithm;
  • the differential privacy algorithm is a mathematical model that quantifies the privacy loss in the data set when data is released;
  • the Apriori algorithm is used to detect rare The original data is added with noise to form data, and then the algorithm code is added to submit it to an untrusted external platform, and the algorithm is used to eliminate the noise when it is finally returned;
  • the k-anonymous algorithm is implemented by generalization technology and concealment technology.
  • the generalization technique refers to a more general and abstract description of the data, making it impossible to distinguish specific values.
  • the concealment technique refers to not publishing certain information, and by reducing the accuracy of the published data, each record is at least as good as other K in the data table. -1 records have exactly the same quasi-identifier attribute value, thereby reducing the risk of privacy leakage caused by chaining attacks.
  • the ledger maintenance algorithm includes an endorsement stage, a sorting stage and a verification stage;
  • the endorsement node checks the legitimacy of the transaction plan sent by the client, simulates the execution of the chain code to obtain the transaction result, and finally judges whether the transaction plan is supported according to the set endorsement logic; if the endorsement logic decides to support the transaction plan, The signature of the plan will be sent back to the client; by default, the endorsement logic of the endorsement node is to support the plan and sign, but the endorsement node can set the endorsement logic according to the business rules, so as to enter the team to serve the business needs.
  • the transaction is endorsed; if the endorsement node determines that the transaction is not supported, an error message is returned to the client;
  • the sorting stage sorts the transactions for the sorting service and determines the time sequence relationship between the transactions; the sorting service sorts the transactions received within a period of time, and then packs the transactions after the transaction into blocks, and then divides the transactions into blocks.
  • the block is broadcast to the members in the channel, thus ensuring the consistency of the data of all nodes;
  • the verification phase is to confirm that the node performs a series of verifications on the sorted transactions, including the integrity check of the transaction data, whether the transaction is repeated, whether the endorsement signature meets the requirements of the endorsement policy, and whether the transaction read-write set meets the multi-version control. All confirmation nodes verify transactions in the same order, and write legal transactions into the ledger at one time.
  • the Docker is an advanced container engine based on LXC
  • the source code is hosted on Github, based on the go language and open sourced in compliance with the Apache2.0 protocol.
  • the K8S includes a master node and a computing node;
  • the master node includes API Server, Scheduler, Controller manager, and the API Server is the external interface of the entire system for client and other components to call, and the Scheduler is responsible for The resources inside the cluster are scheduled, and the Controller manager is responsible for managing the controller;
  • the computing node includes the Docker, kubelet, kube-proxy, Fluentd, and Pod, and the Pod is the most basic operation unit of the K8S.
  • Pod represents a process running in the cluster and encapsulates one or more closely related containers.
  • the Kubelet is responsible for monitoring the Pod assigned to the computing node where the Kubelet is located, including creating, modifying, monitoring, Delete, etc., the Kube-proxy is used to provide a proxy for the Pod, and the Fluentd is used for log collection, storage and query.
  • the beneficial effect of the present invention is that the blockchain-based supply chain finance AI DaaS algorithm warehouse platform provided by the present invention includes an application layer, an open interface layer, an algorithm warehouse service layer, and a data layer that are connected in sequence.
  • the application layer is used to provide supply chain financial services based on blockchain
  • the open interface layer is used to provide the application layer with services to connect the algorithm warehouse service layer
  • the data layer is used to provide data service support for the algorithm warehouse service layer.
  • the infrastructure layer is used to provide development support for the data layer; the invention solves the problem of algorithm fusion and sharing of the supply chain finance of the blockchain. .
  • FIG. 1 is a system structure diagram of a blockchain-based supply chain finance AI DaaS algorithm warehouse platform provided by an embodiment of the present invention.
  • the blockchain-based supply chain finance AI DaaS algorithm warehouse platform includes an application layer, an open interface layer, an algorithm warehouse service layer, a data layer and an infrastructure layer that are sequentially connected.
  • the open interface layer is used to provide the application layer with the service of connecting the algorithm warehouse service layer
  • the data layer is used to provide data for the algorithm warehouse service layer.
  • service support the infrastructure layer is used to provide development support for the data layer;
  • the application layer includes a letter of credit module, a non-recourse financing module, a supply chain finance module, a smart retail module, a link management module, a smart contract script module, a smart contract template module, and a smart contract management platform. It is used to provide a letter of credit business function, the non-recourse financing module is used to provide a non-recourse financing business function, the supply chain financial module is used to provide support services for trusted credit transfer, and the smart retail module is used for In order to provide smart retail business functions, the link management module is used to provide data link management functions, the smart contract script module is used to provide the automatic writing function of smart contract scripts, and the smart contract template module is used to provide intelligent The function of the contract, the smart contract management platform is used to provide the management function of the smart contract;
  • the open interface layer includes a chain code protocol interface, a blockchain API service interface, an identity authentication service interface, and a light client interface.
  • the chain code protocol interface is a blockchain access interface
  • the blockchain API service interface uses
  • the identity authentication service interface is used to provide the function of verifying user information
  • the light client interface is used to Provide users with a secure and decentralized way to access and interact with the blockchain without synchronizing the entire blockchain;
  • the algorithm warehouse service layer includes a data visualization algorithm module, a KYC verification algorithm module, a trusted identity system algorithm module, a consensus mechanism algorithm module, a privacy protection algorithm module, and a ledger maintenance algorithm module, and the data visualization algorithm module is used for data visualization algorithms.
  • the KYC verification algorithm module is used for the storage and application of the KYC verification algorithm
  • the trusted identity system algorithm module is used for the storage and application of the trusted identity system algorithm
  • the consensus mechanism algorithm module is used for consensus
  • the privacy protection algorithm module is used for the storage and application of the privacy protection algorithm
  • the account book maintenance algorithm module is used for the storage and application of the account book maintenance algorithm;
  • the data layer includes a block data sharing module, a block data governance module, and a block data development module.
  • the block data sharing module is used to provide data sharing functions for different modules
  • the block data governance module is used to provide different modules.
  • Data governance function, the block data development module is used to provide data development function for different modules;
  • the infrastructure layer includes Docker, Docker-compose, K8S
  • the Docker is an open source application container engine
  • the Docker-compose is an application tool for defining and running multi-container Docker
  • the K8S is a container-based cluster management
  • the platform is used to manage Docker and containers.
  • the blockchain-based supply chain finance AI DaaS algorithm warehouse platform provided by the above technical solution includes an application layer, an open interface layer, an algorithm warehouse service layer, a data layer and an infrastructure layer that are connected in sequence.
  • the supply chain financial service of the chain, the open interface layer is used to provide the application layer with the service of connecting the algorithm warehouse service layer
  • the data layer is used to provide data service support for the algorithm warehouse service layer
  • the infrastructure layer is used to provide development support for the data layer;
  • the invention solves the problem of algorithm fusion and sharing of supply chain finance of block chain.
  • the data visualization algorithm includes a parallel visualization algorithm, an in-situ visualization algorithm, and a time series data visualization algorithm;
  • the parallel visualization algorithm includes a task parallel algorithm, a pipeline parallel algorithm, and a data parallel algorithm; the task parallel algorithm divides the visualization process into independent subtasks, and there is no data dependency between the running subtasks; the pipeline The parallel algorithm uses streaming to read data fragments, divides the visualization process into multiple stages, and executes each stage in parallel by the computer to speed up the processing process; the data parallel algorithm is a single-program multiple-data method, which divides the data into multiple subsets, and then use the subset as the granularity to execute the program in parallel to process the different subsets;
  • the in-situ visualization algorithm is to generate visualization in the process of numerical simulation and is used to alleviate the output bottleneck of large-scale numerical simulation, including image in-situ visualization algorithm, distributed data in-situ visualization algorithm, compressed data in-situ visualization algorithm and feature in-situ visualization.
  • the in-situ visualization algorithm of the image is to map the data into visualization during the numerical simulation process and save it as an image; the in-situ visualization algorithm of the distribution data is calculated according to the statistical index defined by the user during the numerical simulation Statistical indicators are saved, followed by statistical data visualization; the in-situ visualization of the compressed data adopts a compression algorithm to reduce the output scale of the numerical simulation data, and the compressed data is used as the input of the subsequent visualization processing; the feature in-situ visualization algorithm is in the numerical simulation process. Extract features and save them, and use feature data as input for subsequent visualization processing;
  • the time series data visualization algorithm is used to establish a prediction model, perform predictive analysis and user behavior analysis, including an area chart algorithm, a bubble chart algorithm, a Gantt chart algorithm, a heat map algorithm, a histogram algorithm, a line chart algorithm, and a spiral chart algorithm.
  • stacked area chart algorithm quantitative waveform chart algorithm
  • the area chart algorithm is used to display the change and development of the quantitative value within a specified time period
  • the bubble chart algorithm sets the variable of one of the axes to time or the data variable Animated over time
  • the Gantt chart algorithm is used as an organizational tool for project management
  • the heat map algorithm is used to display data by color changes
  • the histogram algorithm is used to display data at successive intervals or at specified times the distribution of data within segments
  • the line chart algorithm for displaying quantitative values over successive intervals or time spans to show trends and relationships
  • the helix chart algorithm for plotting time-based data along an Archimedes spiral
  • the stacking The quantized area chart algorithm works on the same principle as the simple area chart algorithm to display multiple data series at the same time, and the quantized waveform chart algorithm is used to display changes in different categories of data over time.
  • the KYC verification algorithm is used in the process of verifying customers and customer identities before or during the conduct of business, and the KYC verification algorithm uses AI-OCR tools to automatically capture, extract and create editable and Searchable copy of customer data.
  • the trusted identity system algorithm uses Ethereum for key distribution and management, IPFS for content addressing, ENS for human-readable information parsing, and whisper as a secure data transmission channel.
  • the consensus mechanism algorithm includes a workload proof algorithm, a rights proof algorithm, a share authorization proof mechanism algorithm, a Ripple consensus algorithm, and a practical Byzantine fault-tolerant algorithm;
  • the proof-of-work algorithm calculates a random number that satisfies the rules through AND-OR operation, that is, obtains the accounting right this time, sends out the data that needs to be recorded in this round, and stores it together after verification by other nodes in the entire network;
  • the proof-of-stake algorithm uses proof of equity to replace the proof of computing power, and the accounting right is obtained by the node with the highest equity, not the node with the highest computing power, thereby speeding up the speed of finding random numbers;
  • the said share authorization proof mechanism algorithm votes to select relatively reliable nodes through the proportion of assets, which can greatly reduce the number of nodes participating in verification and accounting, and can achieve consensus verification at the second level;
  • the Ripple consensus algorithm occurs between verification nodes.
  • Each verification node is preconfigured with a list of trusted nodes. The nodes on the trusted node list vote for transaction completion, and each verification node will continue to receive messages from the network. After the sent transactions are verified with the local ledger data, the illegal transactions are directly discarded, and the legal transactions will be aggregated into a transaction candidate set.
  • Each verification node sends its own transaction candidate set as a proposal to other verification nodes. After the verification node receives the proposal from other nodes, if it is not from the node on the trusted node list, it will ignore the proposal. If it is Nodes from the list of trusted nodes will compare the transaction in the proposal with the local candidate set of transactions. If there is the same transaction, the transaction will get one vote.
  • the transaction In a certain period of time, when the transaction receives more than 50% of the votes. When there are more than 50% of the votes, the transaction will enter the next round. If there are no more than 50% of the transactions, it will be confirmed by the next consensus process.
  • the verification node will send the transaction with more than 50% of the votes to other nodes as a proposal, and at the same time increase the threshold of the required number of votes. To 60%, repeat the calculation of proposals received by the verification node from other nodes until the threshold reaches 80%, and the verification node officially writes the transactions confirmed by the nodes in the 80% trusted node list into the local ledger data , called the last closed ledger, that is, the final state of the ledger;
  • the practical Byzantine fault-tolerant algorithm is a state machine replica replication algorithm, that is, a service is modeled as a state machine, and the state machine is replicated in different nodes of the distributed system. Each copy of the state machine holds the state of the service and also implements the operation of the service.
  • the privacy protection algorithm includes a differential privacy algorithm, an Apriori algorithm, and a k-anonymity algorithm;
  • the differential privacy algorithm is a mathematical model that quantifies the privacy loss in a data set when data is released;
  • the The Apriori algorithm is used to detect rare data classes, add noise to the original data to form data, then add the algorithm code and submit it to an untrusted external platform, and use the algorithm to eliminate the noise when it finally returns;
  • the k-anonymous algorithm uses generalization technology and It is realized by concealment technology.
  • the generalization technology refers to a more general and abstract description of the data, making it impossible to distinguish specific values.
  • the concealment technology means that certain information is not released, and by reducing the accuracy of the released data, each record is at least as good as the one.
  • the other K-1 records in the data table have exactly the same quasi-identifier attribute value, thereby reducing the risk of privacy leakage caused by chaining attacks.
  • the ledger maintenance algorithm includes an endorsement phase, a sorting phase, and a verification phase;
  • the endorsement node checks the legitimacy of the transaction plan sent by the client, simulates the execution of the chain code to obtain the transaction result, and finally judges whether the transaction plan is supported according to the set endorsement logic; if the endorsement logic decides to support the transaction plan, The signature of the plan will be sent back to the client; by default, the endorsement logic of the endorsement node is to support the plan and sign, but the endorsement node can set the endorsement logic according to the business rules, so as to enter the team to serve the business needs.
  • the transaction is endorsed; if the endorsement node determines that the transaction is not supported, an error message is returned to the client;
  • the sorting stage sorts the transactions for the sorting service and determines the time sequence relationship between the transactions; the sorting service sorts the transactions received within a period of time, and then packs the transactions after the transaction into blocks, and then divides the transactions into blocks.
  • the block is broadcast to the members in the channel, thus ensuring the consistency of the data of all nodes;
  • the verification phase is to confirm that the node performs a series of verifications on the sorted transactions, including the integrity check of the transaction data, whether the transaction is repeated, whether the endorsement signature meets the requirements of the endorsement policy, and whether the transaction read-write set meets the multi-version control. All confirmation nodes verify transactions in the same order, and write legal transactions into the ledger at one time.
  • the Docker is an advanced container engine based on LXC
  • the source code is hosted on Github, based on the go language and open sourced in compliance with the Apache2.0 protocol.
  • the K8S includes a master node and a computing node;
  • the master node includes an API Server, a Scheduler, and a Controller manager, and the API Server is the external interface of the entire system, which is called by clients and other components, and the Scheduler is responsible for The resources inside the cluster are scheduled, and the Controller manager is responsible for managing the controller;
  • the computing node includes the Docker, kubelet, kube-proxy, Fluentd, and Pod, and the Pod is the most basic operation unit of the K8S.
  • Pod represents a process running in the cluster and encapsulates one or more closely related containers.
  • the Kubelet is responsible for monitoring the Pod assigned to the computing node where the Kubelet is located, including creating, modifying, monitoring, Delete, etc., the Kube-proxy is used to provide a proxy for the Pod, and the Fluentd is used for log collection, storage and query.
  • the functions and business processes of all modules involved in the present invention adopt existing and public functions and business processes; the architectures of all modules involved in the present invention adopt existing and public architectures.

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Abstract

A supply chain finance AI DaaS algorithm warehouse platform based on a blockchain, the supply chain finance AI DaaS algorithm warehouse platform based on a blockchain comprising an application layer, an open interface layer, an algorithm warehouse service layer, a data layer and an infrastructure layer, which are connected in sequence, wherein the application layer is used for providing a supply chain finance service based on a blockchain; the open interface layer is used for providing, to the application layer, a service for connecting to the algorithm warehouse service layer; the data layer is used for providing data service support to the algorithm warehouse service layer; and the infrastructure layer is used for providing development support to the data layer. The problems of algorithm fusion and sharing of supply chain finance based on a blockchain can be solved.

Description

基于区块链的供应链金融AI DaaS算法仓库平台Blockchain-based supply chain finance AI DaaS algorithm warehouse platform 技术领域technical field
本发明涉及区块链的供应链金融领域,具体涉及一种基于区块链的供应链金融AI DaaS算法仓库平台。The invention relates to the field of supply chain finance of blockchain, in particular to a supply chain finance AI DaaS algorithm warehouse platform based on blockchain.
背景技术Background technique
DaaS(Data as a Service,数据即服务)是一种以可预测的每用户成本提供和管理多个强大桌面配置的有效方式。它带来的灵活性和敏捷性使远程人员、正式员工和临时员工、甚至是拥有多台PC的用户,都能够获得所需的访问和应用程序,无论他们身在何处。DaaS (Data as a Service) is an efficient way to provide and manage multiple powerful desktop configurations at a predictable per-user cost. The flexibility and agility it brings enables remote workers, regular and temporary employees, and even users with multiple PCs, to get the access and applications they need, no matter where they are.
由于DaaS通过对数据资源的集中化管理,并把数据场景化,从而为企业自身和其他企业的数据共享提供了一种新的方式;在如今的数据大爆炸时代,没有任何一家企业能收集到自己需要的所有数据,有了DaaS服务,就可以向其他公司购买所需数据,通过分工协作提升企业竞争力。Because DaaS provides a new way for enterprises to share data with other enterprises through centralized management of data resources and scene-based data; in today's era of data explosion, no enterprise can collect With the DaaS service, you can purchase all the data you need from other companies, and improve the competitiveness of the enterprise through division of labor and collaboration.
随着AI算法的发展和普及,由于现有的区块链的供应链金融的算法不能融合和共享,给供应链金融造成了发展受阻严重,因此,迫切需要一种基于区块链的供应链金融AI DaaS算法仓库平台,解决区块链的供应链金融的算法融合和共享的问题。With the development and popularization of AI algorithms, since the existing blockchain supply chain finance algorithms cannot be integrated and shared, the development of supply chain finance is seriously hindered. Therefore, a blockchain-based supply chain is urgently needed. The financial AI DaaS algorithm warehouse platform solves the problem of algorithm integration and sharing of blockchain supply chain finance.
发明内容SUMMARY OF THE INVENTION
本发明的目的是提供基于区块链的供应链金融AI DaaS算法仓库平台,解决区块链的供应链金融的算法融合和共享的问题。The purpose of the present invention is to provide a blockchain-based supply chain finance AI DaaS algorithm warehouse platform to solve the problem of algorithm fusion and sharing of blockchain-based supply chain finance.
为了达到上述目的,本发明所采用的技术方案是:本发明提供了一种基于区块链的供应链金融AI DaaS算法仓库平台,包括依次连接的应用层、开放接口层、算法仓库服务层、数据层以及基础设施层,所述应用层用于提供基于区块链的供应链金融服务,所述开放接口层用于为所述应用层提供连接所述算法仓库服务层的服务,所述数据层用于为所述算法仓库服务层提供数据服务支持,所述基础设施层用于为所述数据层提供开发支持;In order to achieve the above purpose, the technical solution adopted in the present invention is as follows: the present invention provides a supply chain finance AI DaaS algorithm warehouse platform based on blockchain, including an application layer, an open interface layer, an algorithm warehouse service layer, A data layer and an infrastructure layer, the application layer is used to provide blockchain-based supply chain financial services, the open interface layer is used to provide the application layer with a service connecting the algorithm warehouse service layer, the data The layer is used to provide data service support for the algorithm warehouse service layer, and the infrastructure layer is used to provide development support for the data layer;
所述应用层包括信用证模块、无追索权融资模块、供应链金融模块、智慧零售模块、链路管理模块、智能合约脚本模块、智能合约模板模块、智能合约管理平台,所述信用证模块用于提供信用证业务功能,所述无追索权融资模块用于提供无追索权融资业务功能,所述供应链金融模块用于提供可信信用传递的支持服务,所述智慧零售模块用于提供智慧零售业务功能,所述链路管理模块用于提供数据链路管理功能,所述智能合约脚本模块用于提供智能合约脚本的自动编写功能,所述智能合约模板模块用于提供生成智能合约的功能,所述智能合约管理平台用于提供智能合约的管理功能;The application layer includes a letter of credit module, a non-recourse financing module, a supply chain finance module, a smart retail module, a link management module, a smart contract script module, a smart contract template module, and a smart contract management platform. It is used to provide a letter of credit business function, the non-recourse financing module is used to provide a non-recourse financing business function, the supply chain financial module is used to provide support services for trusted credit transfer, and the smart retail module is used for In order to provide smart retail business functions, the link management module is used to provide data link management functions, the smart contract script module is used to provide the automatic writing function of smart contract scripts, and the smart contract template module is used to provide intelligent The function of the contract, the smart contract management platform is used to provide the management function of the smart contract;
所述开放接口层包括链码协议接口、区块链API服务接口、身份认证服务接口、轻客户端接口,所述链码协议接口为区块链访问接口,所述区块链API服务接口用于提供区块链相关的所有功能以使应用系统仅需调用相关接口即可变成区块链应用,所述身份认证服务接口用于提供核验用户信息的功能,所述轻客户端接口用于为用户提供以安全和去中心化的方式访问并与区块链交互而无需同步整个区块链;The open interface layer includes a chain code protocol interface, a blockchain API service interface, an identity authentication service interface, and a light client interface. The chain code protocol interface is a blockchain access interface, and the blockchain API service interface uses In order to provide all the functions related to the blockchain so that the application system only needs to call the relevant interface to become a blockchain application, the identity authentication service interface is used to provide the function of verifying user information, and the light client interface is used to Provide users with a secure and decentralized way to access and interact with the blockchain without synchronizing the entire blockchain;
所述算法仓库服务层包括数据可视化算法模块、KYC验证算法模块、可信身份体系算法模块、共识机制算法模块、隐私保护算法模块、账本维护算法模块,所述数据可视化算法模块用于数据可视化算法的存储及应用,所述KYC验 证算法模块用于KYC验证算法的存储及应用,所述可信身份体系算法模块用于可信身份体系算法的存储及应用,所述共识机制算法模块用于共识机制算法的存储及应用,所述隐私保护算法模块用于隐私保护算法的存储及应用,所述账本维护算法模块用于账本维护算法的存储及应用;The algorithm warehouse service layer includes a data visualization algorithm module, a KYC verification algorithm module, a trusted identity system algorithm module, a consensus mechanism algorithm module, a privacy protection algorithm module, and a ledger maintenance algorithm module, and the data visualization algorithm module is used for data visualization algorithms. The KYC verification algorithm module is used for the storage and application of the KYC verification algorithm, the trusted identity system algorithm module is used for the storage and application of the trusted identity system algorithm, and the consensus mechanism algorithm module is used for consensus The storage and application of the mechanism algorithm, the privacy protection algorithm module is used for the storage and application of the privacy protection algorithm, and the account book maintenance algorithm module is used for the storage and application of the account book maintenance algorithm;
所述数据层包括块数据共享模块、块数据治理模块、块数据开发模块,所述块数据共享模块用于为不同的模块提供数据共享功能,所述块数据治理模块用于为不同的模块提供数据治理功能,所述块数据开发模块用于为不同的模块提供数据开发功能;The data layer includes a block data sharing module, a block data governance module, and a block data development module. The block data sharing module is used to provide data sharing functions for different modules, and the block data governance module is used to provide different modules. Data governance function, the block data development module is used to provide data development function for different modules;
所述基础设施层包括Docker、Docker-compose、K8S,所述Docker为开源的应用容器引擎,所述Docker-compose为定义和运行多容器Docker的应用程序工具,所述K8S为基于容器的集群管理平台用于对Docker及容器进行管理。The infrastructure layer includes Docker, Docker-compose, K8S, the Docker is an open source application container engine, the Docker-compose is an application tool for defining and running multi-container Docker, and the K8S is a container-based cluster management The platform is used to manage Docker and containers.
进一步地,所述数据可视化算法包括并行可视化算法、原位可视化算法以及时序数据可视化算法;Further, the data visualization algorithm includes a parallel visualization algorithm, an in-situ visualization algorithm, and a time series data visualization algorithm;
所述并行可视化算法包括任务并行算法、流水线并行算法、数据并行算法;所述任务并行算法将可视化过程分为独立的子任务,且运行的所述子任务之间不存在数据依赖;所述流水线并行算法采用流式读取数据片段,将可视化过程分为多个阶段,由计算机并行执行各个阶段加速处理过程;所述数据并行算法为单程序多数据的方式,将数据划分为多个子集,然后以所述子集为粒度并行执行程序处理不同的所述子集;The parallel visualization algorithm includes a task parallel algorithm, a pipeline parallel algorithm, and a data parallel algorithm; the task parallel algorithm divides the visualization process into independent subtasks, and there is no data dependency between the running subtasks; the pipeline The parallel algorithm uses streaming to read data fragments, divides the visualization process into multiple stages, and executes each stage in parallel by the computer to speed up the processing process; the data parallel algorithm is a single-program multiple-data method, which divides the data into multiple subsets, and then use the subset as the granularity to execute the program in parallel to process the different subsets;
所述原位可视化算法为在数值模拟过程中生成可视化,用于缓解大规模数值模拟输出瓶颈,包括图像原位可视化算法、分布数据原位可视化算法、压缩数据原位可视化算法与特征原位可视化算法;所述图像原位可视化算法为在数值模拟过程中,将数据映射为可视化,并保存为图像;所述分布数据原位可视 化算法为根据使用者定义的统计指标,在数值模拟过程中计算统计指标并保存,后续进行统计数据可视化;所述压缩数据原位可视化采用压缩算法降低数值模拟数据输出规模,将压缩数据作为后续可视化处理的输入;所述特征原位可视化算法为在数值模拟过程中提取特征并保存,将特征数据作为后续可视化处理的输入;The in-situ visualization algorithm is to generate visualization in the process of numerical simulation and is used to alleviate the output bottleneck of large-scale numerical simulation, including image in-situ visualization algorithm, distributed data in-situ visualization algorithm, compressed data in-situ visualization algorithm and feature in-situ visualization. The in-situ visualization algorithm of the image is to map the data into visualization during the numerical simulation process and save it as an image; the in-situ visualization algorithm of the distribution data is calculated according to the statistical index defined by the user during the numerical simulation Statistical indicators are saved, followed by statistical data visualization; the in-situ visualization of the compressed data adopts a compression algorithm to reduce the output scale of the numerical simulation data, and the compressed data is used as the input of the subsequent visualization processing; the feature in-situ visualization algorithm is in the numerical simulation process. Extract features and save them, and use feature data as input for subsequent visualization processing;
所述时序数据可视化算法用于建立预测模型、进行预测性分析和用户行为分析,包括面积图算法、气泡图算法、甘特图算法、热图算法、直方图算法、折线图算法、螺旋图算法、堆叠式面积图算法、量化波形图算法,所述面积图算法用于显示指定的时间段内量化数值的变化和发展,所述气泡图算法将其中一条轴的变量设置为时间或者把数据变量随时间的变化制成动画来显示,所述甘特图算法用于项目管理的组织工具,所述热图算法通过色彩变化来显示数据,所述直方图算法用于显示在连续间隔或指定时间段内的数据分布,所述折线图算法于在连续间隔或时间跨度上显示定量数值以显示趋势和关系,所述螺旋图算法为沿阿基米德螺旋线绘制基于时间的数据,所述堆叠式面积图算法的原理与简单面积图算法相同以同时显示多个数据系列,所述量化波形图算法用于显示不同类别的数据随着时间的变化。The time series data visualization algorithm is used to establish a prediction model, perform predictive analysis and user behavior analysis, including an area chart algorithm, a bubble chart algorithm, a Gantt chart algorithm, a heat map algorithm, a histogram algorithm, a line chart algorithm, and a spiral chart algorithm. , stacked area chart algorithm, quantitative waveform chart algorithm, the area chart algorithm is used to display the change and development of the quantitative value within a specified time period, the bubble chart algorithm sets the variable of one of the axes to time or the data variable Animated over time, the Gantt chart algorithm is used as an organizational tool for project management, the heat map algorithm is used to display data by color changes, and the histogram algorithm is used to display data at successive intervals or at specified times the distribution of data within segments, the line chart algorithm for displaying quantitative values over successive intervals or time spans to show trends and relationships, the helix chart algorithm for plotting time-based data along an Archimedes spiral, the stacking The quantized area chart algorithm works on the same principle as the simple area chart algorithm to display multiple data series at the same time, and the quantized waveform chart algorithm is used to display changes in different categories of data over time.
进一步地,所述KYC验证算法用于在开展业务之前或过程中验证客户和客户身份的过程,所述KYC验证算法采用AI-OCR工具自动捕获、提取并创建可编辑和可搜索的客户数据副本。Further, the KYC verification algorithm used in the process of verifying the identity of customers and customers before or during the conduct of business, the KYC verification algorithm uses AI-OCR tools to automatically capture, extract and create editable and searchable copies of customer data .
进一步地,所述可信身份体系算法采用以太坊做密钥分发与管理,IPFS负责内容寻址,ENS做人类可读性信息的解析,whisper做安全的数据传输通道。Further, the trusted identity system algorithm uses Ethereum for key distribution and management, IPFS for content addressing, ENS for human-readable information analysis, and whisper for secure data transmission channels.
进一步地,所述共识机制算法包括工作量证明算法、权益证明算法、股份授权证明机制算法、瑞波共识算法、实用拜占庭容错算法;Further, the consensus mechanism algorithm includes a workload proof algorithm, an equity proof algorithm, a share authorization proof mechanism algorithm, a Ripple consensus algorithm, and a practical Byzantine fault-tolerant algorithm;
所述工作量证明算法通过与或运算,计算出一个满足规则的随机数,即获得本次记账权,发出本轮需要记录的数据,全网其它节点验证后一起存储;The proof-of-work algorithm calculates a random number that satisfies the rules through AND-OR operation, that is, obtains the accounting right this time, sends out the data that needs to be recorded in this round, and stores it together after verification by other nodes in the entire network;
所述权益证明算法采用权益证明来代替算力证明,记账权由最高权益的节点获得,而不是最高算力的节点,从而加快找随机数的速度;The proof-of-stake algorithm uses proof of equity to replace the proof of computing power, and the accounting right is obtained by the node with the highest equity, not the node with the highest computing power, thereby speeding up the speed of finding random numbers;
所述股份授权证明机制算法通过资产占比来投票选择相对可靠的节点,能够大幅缩小参与验证和记账节点的数量,可以达到秒级的共识验证;The said share authorization proof mechanism algorithm votes to select relatively reliable nodes through the proportion of assets, which can greatly reduce the number of nodes participating in verification and accounting, and can achieve consensus verification at the second level;
所述瑞波共识算法发生在验证节点之间,每个验证节点预先配置一份可信任节点名单,所述可信任节点名单上的节点对交易达成进行投票,每个验证节点会不断收到从网络发送过来的交易,通过与本地账本数据验证后,不合法的交易直接丢弃,合法的交易将汇总成交易候选集,所述交易候选集里面还包括之前共识过程无法确认而遗留下来的交易,每个验证节点把自己的交易候选集作为提案发送给其他验证节点,验证节点在收到其他节点发来的提案后,如果不是来自所述可信任节点名单上的节点,则忽略该提案,如果是来自所述可信任节点名单上的节点,就会对比提案中的交易和本地的交易候选集,如果有相同的交易,该交易就获得一票,在一定时间内,当交易获得超过50%的票数时,则该交易进入下一轮,没有超过50%的交易,将留待下一次共识过程去确认,验证节点把超过50%票数的交易作为提案发给其他节点,同时提高所需票数的阈值到60%,重复计算验证节点收到的其他节点发来的提案,直到所述阈值达到80%,验证节点把经过80%所述可信任节点名单的节点确认的交易正式写入本地的账本数据中,称为最后关闭账本,即账本最后的状态;The Ripple consensus algorithm occurs between verification nodes. Each verification node is preconfigured with a list of trusted nodes. The nodes on the trusted node list vote for transaction completion, and each verification node will continue to receive messages from the network. After the sent transactions are verified with the local ledger data, the illegal transactions are directly discarded, and the legal transactions will be aggregated into a transaction candidate set. Each verification node sends its own transaction candidate set as a proposal to other verification nodes. After the verification node receives the proposal from other nodes, if it is not from the node on the trusted node list, it will ignore the proposal. If it is Nodes from the list of trusted nodes will compare the transaction in the proposal with the local candidate set of transactions. If there is the same transaction, the transaction will get one vote. In a certain period of time, when the transaction receives more than 50% of the votes. When there are more than 50% of the votes, the transaction will enter the next round. If there are no more than 50% of the transactions, it will be confirmed by the next consensus process. The verification node will send the transaction with more than 50% of the votes to other nodes as a proposal, and at the same time increase the threshold of the required number of votes. To 60%, repeat the calculation of proposals received by the verification node from other nodes until the threshold reaches 80%, and the verification node officially writes the transactions confirmed by the nodes in the 80% trusted node list into the local ledger data , called the last closed ledger, that is, the final state of the ledger;
所述实用拜占庭容错算法为状态机副本复制算法,即服务作为状态机进行建模,状态机在分布式系统的不同节点进行副本复制。每个状态机的副本都保存了服务的状态,同时也实现了服务的操作。The practical Byzantine fault-tolerant algorithm is a state machine replica replication algorithm, that is, a service is modeled as a state machine, and the state machine is replicated in different nodes of the distributed system. Each copy of the state machine holds the state of the service and also implements the operation of the service.
进一步地,所述隐私保护算法包括差分隐私算法、Apriori算法、k-匿名算法;所述差分隐私算法是对数据发布时数据集中的隐私损失进行量化的数学模型;所述Apriori算法用于检测罕见的数据类,将原始数据添加噪声形成数据,随后添加算法代码提交给不可信的外部平台,最终返回的时候再使用算法消除噪声;所述k-匿名算法通过概括技术和隐匿技术来实现,所述概括技术指对数据进行更加概括、抽象的描述,使得无法区分具体数值,所述隐匿技术指不发布某些信息,通过降低发布数据的精度,使得每条记录至少与数据表中其他的K-1条记录具有完全相同的准标识符属性值,从而降低链接攻击所导致的隐私泄露风险。Further, the privacy protection algorithm includes a differential privacy algorithm, an Apriori algorithm, and a k-anonymity algorithm; the differential privacy algorithm is a mathematical model that quantifies the privacy loss in the data set when data is released; the Apriori algorithm is used to detect rare The original data is added with noise to form data, and then the algorithm code is added to submit it to an untrusted external platform, and the algorithm is used to eliminate the noise when it is finally returned; the k-anonymous algorithm is implemented by generalization technology and concealment technology. The generalization technique refers to a more general and abstract description of the data, making it impossible to distinguish specific values. The concealment technique refers to not publishing certain information, and by reducing the accuracy of the published data, each record is at least as good as other K in the data table. -1 records have exactly the same quasi-identifier attribute value, thereby reducing the risk of privacy leakage caused by chaining attacks.
进一步地,所述账本维护算法包括背书阶段、排序阶段以及校验阶段;Further, the ledger maintenance algorithm includes an endorsement stage, a sorting stage and a verification stage;
所述背书阶段为背书节点对客户端发来的交易预案进行合法性检验,模拟执行链码得到交易结果,最后根据设定的背书逻辑判断是否支持该交易预案;如果背书逻辑决定支持交易预案,则将把预案签名发回给客户端;缺省情况下,所述背书节点的背书逻辑是支持预案并签名,但是所述背书节点可以按照业务规则设定背书逻辑,从而进队服务业务需求的交易进行背书;如果所述背书节点判定不支持交易,则给客户端返回出错信息;In the endorsement stage, the endorsement node checks the legitimacy of the transaction plan sent by the client, simulates the execution of the chain code to obtain the transaction result, and finally judges whether the transaction plan is supported according to the set endorsement logic; if the endorsement logic decides to support the transaction plan, The signature of the plan will be sent back to the client; by default, the endorsement logic of the endorsement node is to support the plan and sign, but the endorsement node can set the endorsement logic according to the business rules, so as to enter the team to serve the business needs. The transaction is endorsed; if the endorsement node determines that the transaction is not supported, an error message is returned to the client;
所述排序阶段为排序服务对交易进行排序,确定交易之间的时序关系;所述排序服务把一段时间内收到的交易加以进行排序,然后把交易后的交易打包成区块,再把区块广播给通道中的成员,从而保证了所有节点数据的一致性;The sorting stage sorts the transactions for the sorting service and determines the time sequence relationship between the transactions; the sorting service sorts the transactions received within a period of time, and then packs the transactions after the transaction into blocks, and then divides the transactions into blocks. The block is broadcast to the members in the channel, thus ensuring the consistency of the data of all nodes;
所述校验阶段是确认节点对排序后的交易进行一系列的校验,包括交易数据的完整性检查、是否重复交易、背书签名是否符合背书策略的要求、交易读写集是否符合多版本控制的校验,所有的确认节点按照相同的顺序校验交易,并且把合法的交易一次写入账本中。The verification phase is to confirm that the node performs a series of verifications on the sorted transactions, including the integrity check of the transaction data, whether the transaction is repeated, whether the endorsement signature meets the requirements of the endorsement policy, and whether the transaction read-write set meets the multi-version control. All confirmation nodes verify transactions in the same order, and write legal transactions into the ledger at one time.
进一步地,所述Docker是基于LXC的高级容器引擎,源代码托管在Github 上,基于go语言并遵从Apache2.0协议开源。Further, the Docker is an advanced container engine based on LXC, the source code is hosted on Github, based on the go language and open sourced in compliance with the Apache2.0 protocol.
进一步地,所述K8S包括主节点和计算节点;所述主节点包括API Server、Scheduler、Controller manager,所述API Server是整个系统的对外接口,供客户端和其它组件调用,所述Scheduler负责对集群内部的资源进行调度,所述Controller manager负责管理控制器;所述计算节点包括所述Docker、kubelet、kube-proxy、Fluentd、Pod,所述Pod是所述K8S最基本的操作单元,所述Pod代表着集群中运行的一个进程且内部封装了一个或多个紧密相关的容器,所述Kubelet负责监视指派到所述Kubelet所在所述计算节点上的所述Pod,包括创建、修改、监控、删除等,所述Kube-proxy用于为所述Pod提供代理,所述Fluentd用于日志收集、存储与查询。Further, the K8S includes a master node and a computing node; the master node includes API Server, Scheduler, Controller manager, and the API Server is the external interface of the entire system for client and other components to call, and the Scheduler is responsible for The resources inside the cluster are scheduled, and the Controller manager is responsible for managing the controller; the computing node includes the Docker, kubelet, kube-proxy, Fluentd, and Pod, and the Pod is the most basic operation unit of the K8S. Pod represents a process running in the cluster and encapsulates one or more closely related containers. The Kubelet is responsible for monitoring the Pod assigned to the computing node where the Kubelet is located, including creating, modifying, monitoring, Delete, etc., the Kube-proxy is used to provide a proxy for the Pod, and the Fluentd is used for log collection, storage and query.
与现有技术相比,本发明的有益效果在于,本发明提供的基于区块链的供应链金融AI DaaS算法仓库平台,包括依次连接的应用层、开放接口层、算法仓库服务层、数据层以及基础设施层,应用层用于提供基于区块链的供应链金融服务,开放接口层用于为应用层提供连接算法仓库服务层的服务,数据层用于为算法仓库服务层提供数据服务支持,基础设施层用于为数据层提供开发支持;本发明解决了区块链的供应链金融的算法融合和共享的问题。。Compared with the prior art, the beneficial effect of the present invention is that the blockchain-based supply chain finance AI DaaS algorithm warehouse platform provided by the present invention includes an application layer, an open interface layer, an algorithm warehouse service layer, and a data layer that are connected in sequence. As well as the infrastructure layer, the application layer is used to provide supply chain financial services based on blockchain, the open interface layer is used to provide the application layer with services to connect the algorithm warehouse service layer, and the data layer is used to provide data service support for the algorithm warehouse service layer. , the infrastructure layer is used to provide development support for the data layer; the invention solves the problem of algorithm fusion and sharing of the supply chain finance of the blockchain. .
附图说明Description of drawings
为了更清楚地说明本发明实施例中的技术方案,下面将对实施例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发明的一些实施例,对于本领域普通技术人员来讲,在不付出创造性劳动的前提下,还可以根据这些附图获得其他的附图。In order to illustrate the technical solutions in the embodiments of the present invention more clearly, the following briefly introduces the drawings required in the embodiments. Obviously, the drawings in the following description are only some embodiments of the present invention. For those of ordinary skill in the art, other drawings can also be obtained from these drawings without any creative effort.
图1是本发明实施例提供的基于区块链的供应链金融AI DaaS算法仓库平 台的系统结构图。1 is a system structure diagram of a blockchain-based supply chain finance AI DaaS algorithm warehouse platform provided by an embodiment of the present invention.
具体实施方式Detailed ways
为了使本发明的目的、技术方案及优点更加清楚明白,以下结合附图及实施例,对本发明进行进一步详细说明。应当理解,此处所描述的具体实施例仅仅用以解释本发明,并不用于限定本发明。In order to make the objectives, technical solutions and advantages of the present invention clearer, the present invention will be further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present invention, but not to limit the present invention.
本实施例的附图中相同或相似的标号对应相同或相似的部件;在本发明的描述中,需要理解的是,若有术语“上”、“下”、“左”、“右”等指示的方位或位置关系为基于附图所示的方位或位置关系,仅是为了便于描述本发明和简化描述,而不是指示或暗示所指的装置或元件必须具有特定的方位、以特定的方位构造和操作,因此附图中描述位置关系的用语仅用于示例性说明,不能理解为对本专利的限制,对于本领域的普通技术人员而言,可以根据具体情况理解上述术语的具体含义。The same or similar numbers in the drawings of this embodiment correspond to the same or similar components; in the description of the present invention, it should be understood that if there are terms such as "upper", "lower", "left", "right", etc. The indicated orientation or positional relationship is based on the orientation or positional relationship shown in the accompanying drawings, which is only for the convenience of describing the present invention and simplifying the description, rather than indicating or implying that the indicated device or element must have a specific orientation or a specific orientation. structure and operation, so the terms describing the positional relationship in the accompanying drawings are only used for exemplary illustration, and should not be construed as a limitation on this patent, and those of ordinary skill in the art can understand the specific meanings of the above terms according to specific situations.
以下结合附图与具体实施例,对本发明的技术方案做详细的说明。The technical solutions of the present invention will be described in detail below with reference to the accompanying drawings and specific embodiments.
参照图1,本发明提供的基于区块链的供应链金融AI DaaS算法仓库平台,包括依次连接的应用层、开放接口层、算法仓库服务层、数据层以及基础设施层,所述应用层用于提供基于区块链的供应链金融服务,所述开放接口层用于为所述应用层提供连接所述算法仓库服务层的服务,所述数据层用于为所述算法仓库服务层提供数据服务支持,所述基础设施层用于为所述数据层提供开发支持;Referring to Figure 1, the blockchain-based supply chain finance AI DaaS algorithm warehouse platform provided by the present invention includes an application layer, an open interface layer, an algorithm warehouse service layer, a data layer and an infrastructure layer that are sequentially connected. In order to provide supply chain financial services based on blockchain, the open interface layer is used to provide the application layer with the service of connecting the algorithm warehouse service layer, and the data layer is used to provide data for the algorithm warehouse service layer. service support, the infrastructure layer is used to provide development support for the data layer;
所述应用层包括信用证模块、无追索权融资模块、供应链金融模块、智慧零售模块、链路管理模块、智能合约脚本模块、智能合约模板模块、智能合约管理平台,所述信用证模块用于提供信用证业务功能,所述无追索权融资模块 用于提供无追索权融资业务功能,所述供应链金融模块用于提供可信信用传递的支持服务,所述智慧零售模块用于提供智慧零售业务功能,所述链路管理模块用于提供数据链路管理功能,所述智能合约脚本模块用于提供智能合约脚本的自动编写功能,所述智能合约模板模块用于提供生成智能合约的功能,所述智能合约管理平台用于提供智能合约的管理功能;The application layer includes a letter of credit module, a non-recourse financing module, a supply chain finance module, a smart retail module, a link management module, a smart contract script module, a smart contract template module, and a smart contract management platform. It is used to provide a letter of credit business function, the non-recourse financing module is used to provide a non-recourse financing business function, the supply chain financial module is used to provide support services for trusted credit transfer, and the smart retail module is used for In order to provide smart retail business functions, the link management module is used to provide data link management functions, the smart contract script module is used to provide the automatic writing function of smart contract scripts, and the smart contract template module is used to provide intelligent The function of the contract, the smart contract management platform is used to provide the management function of the smart contract;
所述开放接口层包括链码协议接口、区块链API服务接口、身份认证服务接口、轻客户端接口,所述链码协议接口为区块链访问接口,所述区块链API服务接口用于提供区块链相关的所有功能以使应用系统仅需调用相关接口即可变成区块链应用,所述身份认证服务接口用于提供核验用户信息的功能,所述轻客户端接口用于为用户提供以安全和去中心化的方式访问并与区块链交互而无需同步整个区块链;The open interface layer includes a chain code protocol interface, a blockchain API service interface, an identity authentication service interface, and a light client interface. The chain code protocol interface is a blockchain access interface, and the blockchain API service interface uses In order to provide all the functions related to the blockchain so that the application system only needs to call the relevant interface to become a blockchain application, the identity authentication service interface is used to provide the function of verifying user information, and the light client interface is used to Provide users with a secure and decentralized way to access and interact with the blockchain without synchronizing the entire blockchain;
所述算法仓库服务层包括数据可视化算法模块、KYC验证算法模块、可信身份体系算法模块、共识机制算法模块、隐私保护算法模块、账本维护算法模块,所述数据可视化算法模块用于数据可视化算法的存储及应用,所述KYC验证算法模块用于KYC验证算法的存储及应用,所述可信身份体系算法模块用于可信身份体系算法的存储及应用,所述共识机制算法模块用于共识机制算法的存储及应用,所述隐私保护算法模块用于隐私保护算法的存储及应用,所述账本维护算法模块用于账本维护算法的存储及应用;The algorithm warehouse service layer includes a data visualization algorithm module, a KYC verification algorithm module, a trusted identity system algorithm module, a consensus mechanism algorithm module, a privacy protection algorithm module, and a ledger maintenance algorithm module, and the data visualization algorithm module is used for data visualization algorithms. The KYC verification algorithm module is used for the storage and application of the KYC verification algorithm, the trusted identity system algorithm module is used for the storage and application of the trusted identity system algorithm, and the consensus mechanism algorithm module is used for consensus The storage and application of the mechanism algorithm, the privacy protection algorithm module is used for the storage and application of the privacy protection algorithm, and the account book maintenance algorithm module is used for the storage and application of the account book maintenance algorithm;
所述数据层包括块数据共享模块、块数据治理模块、块数据开发模块,所述块数据共享模块用于为不同的模块提供数据共享功能,所述块数据治理模块用于为不同的模块提供数据治理功能,所述块数据开发模块用于为不同的模块提供数据开发功能;The data layer includes a block data sharing module, a block data governance module, and a block data development module. The block data sharing module is used to provide data sharing functions for different modules, and the block data governance module is used to provide different modules. Data governance function, the block data development module is used to provide data development function for different modules;
所述基础设施层包括Docker、Docker-compose、K8S,所述Docker为开源 的应用容器引擎,所述Docker-compose为定义和运行多容器Docker的应用程序工具,所述K8S为基于容器的集群管理平台用于对Docker及容器进行管理。The infrastructure layer includes Docker, Docker-compose, K8S, the Docker is an open source application container engine, the Docker-compose is an application tool for defining and running multi-container Docker, and the K8S is a container-based cluster management The platform is used to manage Docker and containers.
上述技术方案提供的基于区块链的供应链金融AI DaaS算法仓库平台,包括依次连接的应用层、开放接口层、算法仓库服务层、数据层以及基础设施层,应用层用于提供基于区块链的供应链金融服务,开放接口层用于为应用层提供连接算法仓库服务层的服务,数据层用于为算法仓库服务层提供数据服务支持,基础设施层用于为数据层提供开发支持;本发明解决了区块链的供应链金融的算法融合和共享的问题。The blockchain-based supply chain finance AI DaaS algorithm warehouse platform provided by the above technical solution includes an application layer, an open interface layer, an algorithm warehouse service layer, a data layer and an infrastructure layer that are connected in sequence. The supply chain financial service of the chain, the open interface layer is used to provide the application layer with the service of connecting the algorithm warehouse service layer, the data layer is used to provide data service support for the algorithm warehouse service layer, and the infrastructure layer is used to provide development support for the data layer; The invention solves the problem of algorithm fusion and sharing of supply chain finance of block chain.
作为本发明的一种实施方式,所述数据可视化算法包括并行可视化算法、原位可视化算法以及时序数据可视化算法;As an embodiment of the present invention, the data visualization algorithm includes a parallel visualization algorithm, an in-situ visualization algorithm, and a time series data visualization algorithm;
所述并行可视化算法包括任务并行算法、流水线并行算法、数据并行算法;所述任务并行算法将可视化过程分为独立的子任务,且运行的所述子任务之间不存在数据依赖;所述流水线并行算法采用流式读取数据片段,将可视化过程分为多个阶段,由计算机并行执行各个阶段加速处理过程;所述数据并行算法为单程序多数据的方式,将数据划分为多个子集,然后以所述子集为粒度并行执行程序处理不同的所述子集;The parallel visualization algorithm includes a task parallel algorithm, a pipeline parallel algorithm, and a data parallel algorithm; the task parallel algorithm divides the visualization process into independent subtasks, and there is no data dependency between the running subtasks; the pipeline The parallel algorithm uses streaming to read data fragments, divides the visualization process into multiple stages, and executes each stage in parallel by the computer to speed up the processing process; the data parallel algorithm is a single-program multiple-data method, which divides the data into multiple subsets, and then use the subset as the granularity to execute the program in parallel to process the different subsets;
所述原位可视化算法为在数值模拟过程中生成可视化,用于缓解大规模数值模拟输出瓶颈,包括图像原位可视化算法、分布数据原位可视化算法、压缩数据原位可视化算法与特征原位可视化算法;所述图像原位可视化算法为在数值模拟过程中,将数据映射为可视化,并保存为图像;所述分布数据原位可视化算法为根据使用者定义的统计指标,在数值模拟过程中计算统计指标并保存,后续进行统计数据可视化;所述压缩数据原位可视化采用压缩算法降低数值模拟数据输出规模,将压缩数据作为后续可视化处理的输入;所述特征原位可视 化算法为在数值模拟过程中提取特征并保存,将特征数据作为后续可视化处理的输入;The in-situ visualization algorithm is to generate visualization in the process of numerical simulation and is used to alleviate the output bottleneck of large-scale numerical simulation, including image in-situ visualization algorithm, distributed data in-situ visualization algorithm, compressed data in-situ visualization algorithm and feature in-situ visualization. The in-situ visualization algorithm of the image is to map the data into visualization during the numerical simulation process and save it as an image; the in-situ visualization algorithm of the distribution data is calculated according to the statistical index defined by the user during the numerical simulation Statistical indicators are saved, followed by statistical data visualization; the in-situ visualization of the compressed data adopts a compression algorithm to reduce the output scale of the numerical simulation data, and the compressed data is used as the input of the subsequent visualization processing; the feature in-situ visualization algorithm is in the numerical simulation process. Extract features and save them, and use feature data as input for subsequent visualization processing;
所述时序数据可视化算法用于建立预测模型、进行预测性分析和用户行为分析,包括面积图算法、气泡图算法、甘特图算法、热图算法、直方图算法、折线图算法、螺旋图算法、堆叠式面积图算法、量化波形图算法,所述面积图算法用于显示指定的时间段内量化数值的变化和发展,所述气泡图算法将其中一条轴的变量设置为时间或者把数据变量随时间的变化制成动画来显示,所述甘特图算法用于项目管理的组织工具,所述热图算法通过色彩变化来显示数据,所述直方图算法用于显示在连续间隔或指定时间段内的数据分布,所述折线图算法于在连续间隔或时间跨度上显示定量数值以显示趋势和关系,所述螺旋图算法为沿阿基米德螺旋线绘制基于时间的数据,所述堆叠式面积图算法的原理与简单面积图算法相同以同时显示多个数据系列,所述量化波形图算法用于显示不同类别的数据随着时间的变化。The time series data visualization algorithm is used to establish a prediction model, perform predictive analysis and user behavior analysis, including an area chart algorithm, a bubble chart algorithm, a Gantt chart algorithm, a heat map algorithm, a histogram algorithm, a line chart algorithm, and a spiral chart algorithm. , stacked area chart algorithm, quantitative waveform chart algorithm, the area chart algorithm is used to display the change and development of the quantitative value within a specified time period, the bubble chart algorithm sets the variable of one of the axes to time or the data variable Animated over time, the Gantt chart algorithm is used as an organizational tool for project management, the heat map algorithm is used to display data by color changes, and the histogram algorithm is used to display data at successive intervals or at specified times the distribution of data within segments, the line chart algorithm for displaying quantitative values over successive intervals or time spans to show trends and relationships, the helix chart algorithm for plotting time-based data along an Archimedes spiral, the stacking The quantized area chart algorithm works on the same principle as the simple area chart algorithm to display multiple data series at the same time, and the quantized waveform chart algorithm is used to display changes in different categories of data over time.
作为本发明的一种实施方式,所述KYC验证算法用于在开展业务之前或过程中验证客户和客户身份的过程,所述KYC验证算法采用AI-OCR工具自动捕获、提取并创建可编辑和可搜索的客户数据副本。As an embodiment of the present invention, the KYC verification algorithm is used in the process of verifying customers and customer identities before or during the conduct of business, and the KYC verification algorithm uses AI-OCR tools to automatically capture, extract and create editable and Searchable copy of customer data.
作为本发明的一种实施方式,所述可信身份体系算法采用以太坊做密钥分发与管理,IPFS负责内容寻址,ENS做人类可读性信息的解析,whisper做安全的数据传输通道。As an embodiment of the present invention, the trusted identity system algorithm uses Ethereum for key distribution and management, IPFS for content addressing, ENS for human-readable information parsing, and whisper as a secure data transmission channel.
作为本发明的一种实施方式,所述共识机制算法包括工作量证明算法、权益证明算法、股份授权证明机制算法、瑞波共识算法、实用拜占庭容错算法;As an embodiment of the present invention, the consensus mechanism algorithm includes a workload proof algorithm, a rights proof algorithm, a share authorization proof mechanism algorithm, a Ripple consensus algorithm, and a practical Byzantine fault-tolerant algorithm;
所述工作量证明算法通过与或运算,计算出一个满足规则的随机数,即获得本次记账权,发出本轮需要记录的数据,全网其它节点验证后一起存储;The proof-of-work algorithm calculates a random number that satisfies the rules through AND-OR operation, that is, obtains the accounting right this time, sends out the data that needs to be recorded in this round, and stores it together after verification by other nodes in the entire network;
所述权益证明算法采用权益证明来代替算力证明,记账权由最高权益的节点获得,而不是最高算力的节点,从而加快找随机数的速度;The proof-of-stake algorithm uses proof of equity to replace the proof of computing power, and the accounting right is obtained by the node with the highest equity, not the node with the highest computing power, thereby speeding up the speed of finding random numbers;
所述股份授权证明机制算法通过资产占比来投票选择相对可靠的节点,能够大幅缩小参与验证和记账节点的数量,可以达到秒级的共识验证;The said share authorization proof mechanism algorithm votes to select relatively reliable nodes through the proportion of assets, which can greatly reduce the number of nodes participating in verification and accounting, and can achieve consensus verification at the second level;
所述瑞波共识算法发生在验证节点之间,每个验证节点预先配置一份可信任节点名单,所述可信任节点名单上的节点对交易达成进行投票,每个验证节点会不断收到从网络发送过来的交易,通过与本地账本数据验证后,不合法的交易直接丢弃,合法的交易将汇总成交易候选集,所述交易候选集里面还包括之前共识过程无法确认而遗留下来的交易,每个验证节点把自己的交易候选集作为提案发送给其他验证节点,验证节点在收到其他节点发来的提案后,如果不是来自所述可信任节点名单上的节点,则忽略该提案,如果是来自所述可信任节点名单上的节点,就会对比提案中的交易和本地的交易候选集,如果有相同的交易,该交易就获得一票,在一定时间内,当交易获得超过50%的票数时,则该交易进入下一轮,没有超过50%的交易,将留待下一次共识过程去确认,验证节点把超过50%票数的交易作为提案发给其他节点,同时提高所需票数的阈值到60%,重复计算验证节点收到的其他节点发来的提案,直到所述阈值达到80%,验证节点把经过80%所述可信任节点名单的节点确认的交易正式写入本地的账本数据中,称为最后关闭账本,即账本最后的状态;The Ripple consensus algorithm occurs between verification nodes. Each verification node is preconfigured with a list of trusted nodes. The nodes on the trusted node list vote for transaction completion, and each verification node will continue to receive messages from the network. After the sent transactions are verified with the local ledger data, the illegal transactions are directly discarded, and the legal transactions will be aggregated into a transaction candidate set. Each verification node sends its own transaction candidate set as a proposal to other verification nodes. After the verification node receives the proposal from other nodes, if it is not from the node on the trusted node list, it will ignore the proposal. If it is Nodes from the list of trusted nodes will compare the transaction in the proposal with the local candidate set of transactions. If there is the same transaction, the transaction will get one vote. In a certain period of time, when the transaction receives more than 50% of the votes. When there are more than 50% of the votes, the transaction will enter the next round. If there are no more than 50% of the transactions, it will be confirmed by the next consensus process. The verification node will send the transaction with more than 50% of the votes to other nodes as a proposal, and at the same time increase the threshold of the required number of votes. To 60%, repeat the calculation of proposals received by the verification node from other nodes until the threshold reaches 80%, and the verification node officially writes the transactions confirmed by the nodes in the 80% trusted node list into the local ledger data , called the last closed ledger, that is, the final state of the ledger;
所述实用拜占庭容错算法为状态机副本复制算法,即服务作为状态机进行建模,状态机在分布式系统的不同节点进行副本复制。每个状态机的副本都保存了服务的状态,同时也实现了服务的操作。The practical Byzantine fault-tolerant algorithm is a state machine replica replication algorithm, that is, a service is modeled as a state machine, and the state machine is replicated in different nodes of the distributed system. Each copy of the state machine holds the state of the service and also implements the operation of the service.
作为本发明的一种实施方式,所述隐私保护算法包括差分隐私算法、Apriori算法、k-匿名算法;所述差分隐私算法是对数据发布时数据集中的隐私损失进行 量化的数学模型;所述Apriori算法用于检测罕见的数据类,将原始数据添加噪声形成数据,随后添加算法代码提交给不可信的外部平台,最终返回的时候再使用算法消除噪声;所述k-匿名算法通过概括技术和隐匿技术来实现,所述概括技术指对数据进行更加概括、抽象的描述,使得无法区分具体数值,所述隐匿技术指不发布某些信息,通过降低发布数据的精度,使得每条记录至少与数据表中其他的K-1条记录具有完全相同的准标识符属性值,从而降低链接攻击所导致的隐私泄露风险。As an embodiment of the present invention, the privacy protection algorithm includes a differential privacy algorithm, an Apriori algorithm, and a k-anonymity algorithm; the differential privacy algorithm is a mathematical model that quantifies the privacy loss in a data set when data is released; the The Apriori algorithm is used to detect rare data classes, add noise to the original data to form data, then add the algorithm code and submit it to an untrusted external platform, and use the algorithm to eliminate the noise when it finally returns; the k-anonymous algorithm uses generalization technology and It is realized by concealment technology. The generalization technology refers to a more general and abstract description of the data, making it impossible to distinguish specific values. The concealment technology means that certain information is not released, and by reducing the accuracy of the released data, each record is at least as good as the one. The other K-1 records in the data table have exactly the same quasi-identifier attribute value, thereby reducing the risk of privacy leakage caused by chaining attacks.
作为本发明的一种实施方式,所述账本维护算法包括背书阶段、排序阶段以及校验阶段;As an embodiment of the present invention, the ledger maintenance algorithm includes an endorsement phase, a sorting phase, and a verification phase;
所述背书阶段为背书节点对客户端发来的交易预案进行合法性检验,模拟执行链码得到交易结果,最后根据设定的背书逻辑判断是否支持该交易预案;如果背书逻辑决定支持交易预案,则将把预案签名发回给客户端;缺省情况下,所述背书节点的背书逻辑是支持预案并签名,但是所述背书节点可以按照业务规则设定背书逻辑,从而进队服务业务需求的交易进行背书;如果所述背书节点判定不支持交易,则给客户端返回出错信息;In the endorsement stage, the endorsement node checks the legitimacy of the transaction plan sent by the client, simulates the execution of the chain code to obtain the transaction result, and finally judges whether the transaction plan is supported according to the set endorsement logic; if the endorsement logic decides to support the transaction plan, The signature of the plan will be sent back to the client; by default, the endorsement logic of the endorsement node is to support the plan and sign, but the endorsement node can set the endorsement logic according to the business rules, so as to enter the team to serve the business needs. The transaction is endorsed; if the endorsement node determines that the transaction is not supported, an error message is returned to the client;
所述排序阶段为排序服务对交易进行排序,确定交易之间的时序关系;所述排序服务把一段时间内收到的交易加以进行排序,然后把交易后的交易打包成区块,再把区块广播给通道中的成员,从而保证了所有节点数据的一致性;The sorting stage sorts the transactions for the sorting service and determines the time sequence relationship between the transactions; the sorting service sorts the transactions received within a period of time, and then packs the transactions after the transaction into blocks, and then divides the transactions into blocks. The block is broadcast to the members in the channel, thus ensuring the consistency of the data of all nodes;
所述校验阶段是确认节点对排序后的交易进行一系列的校验,包括交易数据的完整性检查、是否重复交易、背书签名是否符合背书策略的要求、交易读写集是否符合多版本控制的校验,所有的确认节点按照相同的顺序校验交易,并且把合法的交易一次写入账本中。The verification phase is to confirm that the node performs a series of verifications on the sorted transactions, including the integrity check of the transaction data, whether the transaction is repeated, whether the endorsement signature meets the requirements of the endorsement policy, and whether the transaction read-write set meets the multi-version control. All confirmation nodes verify transactions in the same order, and write legal transactions into the ledger at one time.
具体地,所述Docker是基于LXC的高级容器引擎,源代码托管在Github上, 基于go语言并遵从Apache2.0协议开源。Specifically, the Docker is an advanced container engine based on LXC, the source code is hosted on Github, based on the go language and open sourced in compliance with the Apache2.0 protocol.
具体地,所述K8S包括主节点和计算节点;所述主节点包括API Server、Scheduler、Controller manager,所述API Server是整个系统的对外接口,供客户端和其它组件调用,所述Scheduler负责对集群内部的资源进行调度,所述Controller manager负责管理控制器;所述计算节点包括所述Docker、kubelet、kube-proxy、Fluentd、Pod,所述Pod是所述K8S最基本的操作单元,所述Pod代表着集群中运行的一个进程且内部封装了一个或多个紧密相关的容器,所述Kubelet负责监视指派到所述Kubelet所在所述计算节点上的所述Pod,包括创建、修改、监控、删除等,所述Kube-proxy用于为所述Pod提供代理,所述Fluentd用于日志收集、存储与查询。Specifically, the K8S includes a master node and a computing node; the master node includes an API Server, a Scheduler, and a Controller manager, and the API Server is the external interface of the entire system, which is called by clients and other components, and the Scheduler is responsible for The resources inside the cluster are scheduled, and the Controller manager is responsible for managing the controller; the computing node includes the Docker, kubelet, kube-proxy, Fluentd, and Pod, and the Pod is the most basic operation unit of the K8S. Pod represents a process running in the cluster and encapsulates one or more closely related containers. The Kubelet is responsible for monitoring the Pod assigned to the computing node where the Kubelet is located, including creating, modifying, monitoring, Delete, etc., the Kube-proxy is used to provide a proxy for the Pod, and the Fluentd is used for log collection, storage and query.
优选地,本发明所述涉及的所有模块的功能及业务流程,均采用已有的、公开的功能及业务流程;本发明所述涉及的所有模块的架构方式,均采用已有的、公开的架构方式;本发明所述涉及的所有模块的实现方式均采用公开的、成熟的、开源的程序架构及程序代码,本领域的技术人员根据本技术方案描述的功能可以轻易采用已有的、公开的程序架构及程序代码实现。Preferably, the functions and business processes of all modules involved in the present invention adopt existing and public functions and business processes; the architectures of all modules involved in the present invention adopt existing and public architectures. Architecture mode; the implementation modes of all modules involved in the present invention adopt open, mature, open source program architecture and program codes, and those skilled in the art can easily adopt existing, open source, and open source programs according to the functions described in this technical solution. The program architecture and program code implementation.
以上对本发明的实施例进行了详细的说明,但本发明的创造并不限于本实施例,熟悉本领域的技术人员在不违背本发明精神的前提下,还可以做出许多同等变型或替换,这些同等变型或替换均包含在本申请的权利要求所限定的保护范围内。The embodiments of the present invention have been described in detail above, but the creation of the present invention is not limited to the present embodiment. Those skilled in the art can also make many equivalent modifications or substitutions without departing from the spirit of the present invention. These equivalent modifications or substitutions are all included within the protection scope defined by the claims of the present application.

Claims (9)

  1. 基于区块链的供应链金融AI DaaS算法仓库平台,其特征在于,包括依次连接的应用层、开放接口层、算法仓库服务层、数据层以及基础设施层,所述应用层用于提供基于区块链的供应链金融服务,所述开放接口层用于为所述应用层提供连接所述算法仓库服务层的服务,所述数据层用于为所述算法仓库服务层提供数据服务支持,所述基础设施层用于为所述数据层提供开发支持;The blockchain-based supply chain finance AI DaaS algorithm warehouse platform is characterized in that it includes an application layer, an open interface layer, an algorithm warehouse service layer, a data layer and an infrastructure layer that are connected in sequence. The supply chain financial service of the blockchain, the open interface layer is used to provide the application layer with the service of connecting the algorithm warehouse service layer, the data layer is used to provide data service support for the algorithm warehouse service layer, so The infrastructure layer is used to provide development support for the data layer;
    所述应用层包括信用证模块、无追索权融资模块、供应链金融模块、智慧零售模块、链路管理模块、智能合约脚本模块、智能合约模板模块、智能合约管理平台,所述信用证模块用于提供信用证业务功能,所述无追索权融资模块用于提供无追索权融资业务功能,所述供应链金融模块用于提供可信信用传递的支持服务,所述智慧零售模块用于提供智慧零售业务功能,所述链路管理模块用于提供数据链路管理功能,所述智能合约脚本模块用于提供智能合约脚本的自动编写功能,所述智能合约模板模块用于提供生成智能合约的功能,所述智能合约管理平台用于提供智能合约的管理功能;The application layer includes a letter of credit module, a non-recourse financing module, a supply chain finance module, a smart retail module, a link management module, a smart contract script module, a smart contract template module, and a smart contract management platform. It is used to provide a letter of credit business function, the non-recourse financing module is used to provide a non-recourse financing business function, the supply chain financial module is used to provide support services for trusted credit transfer, and the smart retail module is used for In order to provide smart retail business functions, the link management module is used to provide data link management functions, the smart contract script module is used to provide the automatic writing function of smart contract scripts, and the smart contract template module is used to provide intelligent The function of the contract, the smart contract management platform is used to provide the management function of the smart contract;
    所述开放接口层包括链码协议接口、区块链API服务接口、身份认证服务接口、轻客户端接口,所述链码协议接口为区块链访问接口,所述区块链API服务接口用于提供区块链相关的所有功能以使应用系统仅需调用相关接口即可变成区块链应用,所述身份认证服务接口用于提供核验用户信息的功能,所述轻客户端接口用于为用户提供以安全和去中心化的方式访问并与区块链交互而无需同步整个区块链;The open interface layer includes a chain code protocol interface, a blockchain API service interface, an identity authentication service interface, and a light client interface. The chain code protocol interface is a blockchain access interface, and the blockchain API service interface uses In order to provide all the functions related to the blockchain so that the application system only needs to call the relevant interface to become a blockchain application, the identity authentication service interface is used to provide the function of verifying user information, and the light client interface is used to Provide users with a secure and decentralized way to access and interact with the blockchain without synchronizing the entire blockchain;
    所述算法仓库服务层包括数据可视化算法模块、KYC验证算法模块、可信身份体系算法模块、共识机制算法模块、隐私保护算法模块、账本维护算法模块,所述数据可视化算法模块用于数据可视化算法的存储及应用,所述KYC验证算法模块用于KYC验证算法的存储及应用,所述可信身份体系算法模块用于 可信身份体系算法的存储及应用,所述共识机制算法模块用于共识机制算法的存储及应用,所述隐私保护算法模块用于隐私保护算法的存储及应用,所述账本维护算法模块用于账本维护算法的存储及应用;The algorithm warehouse service layer includes a data visualization algorithm module, a KYC verification algorithm module, a trusted identity system algorithm module, a consensus mechanism algorithm module, a privacy protection algorithm module, and a ledger maintenance algorithm module, and the data visualization algorithm module is used for data visualization algorithms. The KYC verification algorithm module is used for the storage and application of the KYC verification algorithm, the trusted identity system algorithm module is used for the storage and application of the trusted identity system algorithm, and the consensus mechanism algorithm module is used for consensus The storage and application of the mechanism algorithm, the privacy protection algorithm module is used for the storage and application of the privacy protection algorithm, and the account book maintenance algorithm module is used for the storage and application of the account book maintenance algorithm;
    所述数据层包括块数据共享模块、块数据治理模块、块数据开发模块,所述块数据共享模块用于为不同的模块提供数据共享功能,所述块数据治理模块用于为不同的模块提供数据治理功能,所述块数据开发模块用于为不同的模块提供数据开发功能;The data layer includes a block data sharing module, a block data governance module, and a block data development module. The block data sharing module is used to provide data sharing functions for different modules, and the block data governance module is used to provide different modules. Data governance function, the block data development module is used to provide data development function for different modules;
    所述基础设施层包括Docker、Docker-compose、K8S,所述Docker为开源的应用容器引擎,所述Docker-compose为定义和运行多容器Docker的应用程序工具,所述K8S为基于容器的集群管理平台用于对Docker及容器进行管理。The infrastructure layer includes Docker, Docker-compose, K8S, the Docker is an open source application container engine, the Docker-compose is an application tool for defining and running multi-container Docker, and the K8S is a container-based cluster management The platform is used to manage Docker and containers.
  2. 根据权利要求1所述的基于区块链的供应链金融AI DaaS算法仓库平台,其特征在于,所述数据可视化算法包括并行可视化算法、原位可视化算法以及时序数据可视化算法;The blockchain-based supply chain finance AI DaaS algorithm warehouse platform according to claim 1, wherein the data visualization algorithm comprises a parallel visualization algorithm, an in-situ visualization algorithm and a time series data visualization algorithm;
    所述并行可视化算法包括任务并行算法、流水线并行算法、数据并行算法;所述任务并行算法将可视化过程分为独立的子任务,且运行的所述子任务之间不存在数据依赖;所述流水线并行算法采用流式读取数据片段,将可视化过程分为多个阶段,由计算机并行执行各个阶段加速处理过程;所述数据并行算法为单程序多数据的方式,将数据划分为多个子集,然后以所述子集为粒度并行执行程序处理不同的所述子集;The parallel visualization algorithm includes a task parallel algorithm, a pipeline parallel algorithm, and a data parallel algorithm; the task parallel algorithm divides the visualization process into independent subtasks, and there is no data dependency between the running subtasks; the pipeline The parallel algorithm uses streaming to read data fragments, divides the visualization process into multiple stages, and executes each stage in parallel by the computer to speed up the processing process; the data parallel algorithm is a single-program multiple-data method, which divides the data into multiple subsets, and then use the subset as the granularity to execute the program in parallel to process the different subsets;
    所述原位可视化算法为在数值模拟过程中生成可视化,用于缓解大规模数值模拟输出瓶颈,包括图像原位可视化算法、分布数据原位可视化算法、压缩数据原位可视化算法与特征原位可视化算法;所述图像原位可视化算法为在数值模拟过程中,将数据映射为可视化,并保存为图像;所述分布数据原位可视 化算法为根据使用者定义的统计指标,在数值模拟过程中计算统计指标并保存,后续进行统计数据可视化;所述压缩数据原位可视化采用压缩算法降低数值模拟数据输出规模,将压缩数据作为后续可视化处理的输入;所述特征原位可视化算法为在数值模拟过程中提取特征并保存,将特征数据作为后续可视化处理的输入;The in-situ visualization algorithm is to generate visualization in the process of numerical simulation and is used to alleviate the output bottleneck of large-scale numerical simulation, including image in-situ visualization algorithm, distributed data in-situ visualization algorithm, compressed data in-situ visualization algorithm and feature in-situ visualization. The in-situ visualization algorithm of the image is to map the data into visualization during the numerical simulation process and save it as an image; the in-situ visualization algorithm of the distribution data is calculated according to the statistical index defined by the user during the numerical simulation Statistical indicators are saved, followed by statistical data visualization; the in-situ visualization of the compressed data adopts a compression algorithm to reduce the output scale of the numerical simulation data, and the compressed data is used as the input of the subsequent visualization processing; the feature in-situ visualization algorithm is in the numerical simulation process. Extract features and save them, and use feature data as input for subsequent visualization processing;
    所述时序数据可视化算法用于建立预测模型、进行预测性分析和用户行为分析,包括面积图算法、气泡图算法、甘特图算法、热图算法、直方图算法、折线图算法、螺旋图算法、堆叠式面积图算法、量化波形图算法,所述面积图算法用于显示指定的时间段内量化数值的变化和发展,所述气泡图算法将其中一条轴的变量设置为时间或者把数据变量随时间的变化制成动画来显示,所述甘特图算法用于项目管理的组织工具,所述热图算法通过色彩变化来显示数据,所述直方图算法用于显示在连续间隔或指定时间段内的数据分布,所述折线图算法于在连续间隔或时间跨度上显示定量数值以显示趋势和关系,所述螺旋图算法为沿阿基米德螺旋线绘制基于时间的数据,所述堆叠式面积图算法的原理与简单面积图算法相同以同时显示多个数据系列,所述量化波形图算法用于显示不同类别的数据随着时间的变化。The time series data visualization algorithm is used to establish a prediction model, perform predictive analysis and user behavior analysis, including an area chart algorithm, a bubble chart algorithm, a Gantt chart algorithm, a heat map algorithm, a histogram algorithm, a line chart algorithm, and a spiral chart algorithm. , stacked area chart algorithm, quantitative waveform chart algorithm, the area chart algorithm is used to display the change and development of the quantitative value within a specified time period, the bubble chart algorithm sets the variable of one of the axes to time or the data variable Animated over time, the Gantt chart algorithm is used as an organizational tool for project management, the heat map algorithm is used to display data by color changes, and the histogram algorithm is used to display data at successive intervals or at specified times the distribution of data within segments, the line chart algorithm for displaying quantitative values over successive intervals or time spans to show trends and relationships, the helix chart algorithm for plotting time-based data along an Archimedes spiral, the stacking The quantized area chart algorithm works on the same principle as the simple area chart algorithm to display multiple data series at the same time, and the quantized waveform chart algorithm is used to display changes in different categories of data over time.
  3. 根据权利要求1所述的基于区块链的供应链金融AI DaaS算法仓库平台,其特征在于,所述KYC验证算法用于在开展业务之前或过程中验证客户和客户身份的过程,所述KYC验证算法采用AI-OCR工具自动捕获、提取并创建可编辑和可搜索的客户数据副本。The blockchain-based supply chain finance AI DaaS algorithm warehouse platform according to claim 1, wherein the KYC verification algorithm is used for the process of verifying the identity of customers and customers before or during the conduct of business, and the KYC verification algorithm Validation algorithms employ AI-OCR tools to automatically capture, extract and create editable and searchable copies of customer data.
  4. 根据权利要求1所述的基于区块链的供应链金融AI DaaS算法仓库平台,其特征在于,所述可信身份体系算法采用以太坊做密钥分发与管理,IPFS负责内容寻址,ENS做人类可读性信息的解析,whisper做安全的数据传输通道。The blockchain-based supply chain finance AI DaaS algorithm warehouse platform according to claim 1, wherein the trusted identity system algorithm adopts Ethereum for key distribution and management, IPFS is responsible for content addressing, and ENS is responsible for For human-readable information parsing, whisper acts as a secure data transmission channel.
  5. 根据权利要求1所述的基于区块链的供应链金融AI DaaS算法仓库平台,其特征在于,所述共识机制算法包括工作量证明算法、权益证明算法、股份授权证明机制算法、瑞波共识算法、实用拜占庭容错算法;The blockchain-based supply chain finance AI DaaS algorithm warehouse platform according to claim 1, wherein the consensus mechanism algorithm includes a workload proof algorithm, a rights proof algorithm, a share authorization proof mechanism algorithm, a Ripple consensus algorithm, Practical Byzantine fault-tolerant algorithm;
    所述工作量证明算法通过与或运算,计算出一个满足规则的随机数,即获得本次记账权,发出本轮需要记录的数据,全网其它节点验证后一起存储;The proof-of-work algorithm calculates a random number that satisfies the rules through AND-OR operation, that is, obtains the accounting right this time, sends out the data that needs to be recorded in this round, and stores it together after verification by other nodes in the entire network;
    所述权益证明算法采用权益证明来代替算力证明,记账权由最高权益的节点获得,而不是最高算力的节点,从而加快找随机数的速度;The proof-of-stake algorithm uses proof of equity to replace the proof of computing power, and the accounting right is obtained by the node with the highest equity, not the node with the highest computing power, thereby speeding up the speed of finding random numbers;
    所述股份授权证明机制算法通过资产占比来投票选择相对可靠的节点,能够大幅缩小参与验证和记账节点的数量,可以达到秒级的共识验证;The said share authorization proof mechanism algorithm votes to select relatively reliable nodes through the proportion of assets, which can greatly reduce the number of nodes participating in verification and accounting, and can achieve consensus verification at the second level;
    所述瑞波共识算法发生在验证节点之间,每个验证节点预先配置一份可信任节点名单,所述可信任节点名单上的节点对交易达成进行投票,每个验证节点会不断收到从网络发送过来的交易,通过与本地账本数据验证后,不合法的交易直接丢弃,合法的交易将汇总成交易候选集,所述交易候选集里面还包括之前共识过程无法确认而遗留下来的交易,每个验证节点把自己的交易候选集作为提案发送给其他验证节点,验证节点在收到其他节点发来的提案后,如果不是来自所述可信任节点名单上的节点,则忽略该提案,如果是来自所述可信任节点名单上的节点,就会对比提案中的交易和本地的交易候选集,如果有相同的交易,该交易就获得一票,在一定时间内,当交易获得超过50%的票数时,则该交易进入下一轮,没有超过50%的交易,将留待下一次共识过程去确认,验证节点把超过50%票数的交易作为提案发给其他节点,同时提高所需票数的阈值到60%,重复计算验证节点收到的其他节点发来的提案,直到所述阈值达到80%,验证节点把经过80%所述可信任节点名单的节点确认的交易正式写入本地的账本数据中,称为最后关闭账本,即账本最后的状态;The Ripple consensus algorithm occurs between verification nodes. Each verification node is preconfigured with a list of trusted nodes. The nodes on the trusted node list vote for transaction completion, and each verification node will continue to receive messages from the network. After the sent transactions are verified with the local ledger data, the illegal transactions are directly discarded, and the legal transactions will be aggregated into a transaction candidate set. Each verification node sends its own transaction candidate set as a proposal to other verification nodes. After the verification node receives the proposal from other nodes, if it is not from the node on the trusted node list, it will ignore the proposal. If it is Nodes from the list of trusted nodes will compare the transaction in the proposal with the local candidate set of transactions. If there is the same transaction, the transaction will get one vote. In a certain period of time, when the transaction receives more than 50% of the votes. When there are more than 50% of the votes, the transaction will enter the next round. If there are no more than 50% of the transactions, it will be confirmed by the next consensus process. The verification node will send the transaction with more than 50% of the votes to other nodes as a proposal, and at the same time increase the threshold of the required number of votes. To 60%, repeat the calculation of proposals received by the verification node from other nodes until the threshold reaches 80%, and the verification node officially writes the transactions confirmed by the nodes in the 80% trusted node list into the local ledger data , called the last closed ledger, that is, the final state of the ledger;
    所述实用拜占庭容错算法为状态机副本复制算法,即服务作为状态机进行建模,状态机在分布式系统的不同节点进行副本复制。每个状态机的副本都保存了服务的状态,同时也实现了服务的操作。The practical Byzantine fault-tolerant algorithm is a state machine replica replication algorithm, that is, a service is modeled as a state machine, and the state machine is replicated in different nodes of the distributed system. Each copy of the state machine holds the state of the service and also implements the operation of the service.
  6. 根据权利要求1所述的基于区块链的供应链金融AI DaaS算法仓库平台,其特征在于,所述隐私保护算法包括差分隐私算法、Apriori算法、k-匿名算法;所述差分隐私算法是对数据发布时数据集中的隐私损失进行量化的数学模型;所述Apriori算法用于检测罕见的数据类,将原始数据添加噪声形成数据,随后添加算法代码提交给不可信的外部平台,最终返回的时候再使用算法消除噪声;所述k-匿名算法通过概括技术和隐匿技术来实现,所述概括技术指对数据进行更加概括、抽象的描述,使得无法区分具体数值,所述隐匿技术指不发布某些信息,通过降低发布数据的精度,使得每条记录至少与数据表中其他的K-1条记录具有完全相同的准标识符属性值,从而降低链接攻击所导致的隐私泄露风险。The blockchain-based supply chain finance AI DaaS algorithm warehouse platform according to claim 1, wherein the privacy protection algorithm includes a differential privacy algorithm, an Apriori algorithm, and a k-anonymity algorithm; the differential privacy algorithm is a pair of Mathematical model for quantifying the privacy loss in the data set when the data is released; the Apriori algorithm is used to detect rare data classes, add noise to the original data to form data, and then add the algorithm code and submit it to an untrusted external platform, and when the final return Then use an algorithm to eliminate noise; the k-anonymous algorithm is realized by generalization technology and concealment technology. The generalization technology refers to a more general and abstract description of the data, so that the specific values cannot be distinguished. For some information, by reducing the precision of the published data, each record has at least the same quasi-identifier attribute value as other K-1 records in the data table, thereby reducing the risk of privacy leakage caused by link attacks.
  7. 根据权利要求1所述的基于区块链的供应链金融AI DaaS算法仓库平台,其特征在于,所述账本维护算法包括背书阶段、排序阶段以及校验阶段;The blockchain-based supply chain finance AI DaaS algorithm warehouse platform according to claim 1, wherein the ledger maintenance algorithm includes an endorsement stage, a sorting stage and a verification stage;
    所述背书阶段为背书节点对客户端发来的交易预案进行合法性检验,模拟执行链码得到交易结果,最后根据设定的背书逻辑判断是否支持该交易预案;如果背书逻辑决定支持交易预案,则将把预案签名发回给客户端;缺省情况下,所述背书节点的背书逻辑是支持预案并签名,但是所述背书节点可以按照业务规则设定背书逻辑,从而进队服务业务需求的交易进行背书;如果所述背书节点判定不支持交易,则给客户端返回出错信息;In the endorsement stage, the endorsement node checks the legitimacy of the transaction plan sent by the client, simulates the execution of the chain code to obtain the transaction result, and finally judges whether the transaction plan is supported according to the set endorsement logic; if the endorsement logic decides to support the transaction plan, The signature of the plan will be sent back to the client; by default, the endorsement logic of the endorsement node is to support the plan and sign, but the endorsement node can set the endorsement logic according to the business rules, so as to enter the team to serve the business needs. The transaction is endorsed; if the endorsement node determines that the transaction is not supported, an error message is returned to the client;
    所述排序阶段为排序服务对交易进行排序,确定交易之间的时序关系;所述排序服务把一段时间内收到的交易加以进行排序,然后把交易后的交易打包成区块,再把区块广播给通道中的成员,从而保证了所有节点数据的一致性;The sorting stage sorts the transactions for the sorting service and determines the time sequence relationship between the transactions; the sorting service sorts the transactions received within a period of time, and then packs the transactions after the transaction into blocks, and then divides the transactions into blocks. The block is broadcast to the members in the channel, thus ensuring the consistency of the data of all nodes;
    所述校验阶段是确认节点对排序后的交易进行一系列的校验,包括交易数据的完整性检查、是否重复交易、背书签名是否符合背书策略的要求、交易读写集是否符合多版本控制的校验,所有的确认节点按照相同的顺序校验交易,并且把合法的交易一次写入账本中。The verification phase is to confirm that the node performs a series of verifications on the sorted transactions, including the integrity check of the transaction data, whether the transaction is repeated, whether the endorsement signature meets the requirements of the endorsement policy, and whether the transaction read-write set meets the multi-version control. All confirmation nodes verify transactions in the same order, and write legal transactions into the ledger at one time.
  8. 根据权利要求1所述的基于区块链的供应链金融AI DaaS算法仓库平台,其特征在于,所述Docker是基于LXC的高级容器引擎,源代码托管在Github上,基于go语言并遵从Apache2.0协议开源。The blockchain-based supply chain finance AI DaaS algorithm warehouse platform according to claim 1, wherein the Docker is an LXC-based advanced container engine, and the source code is hosted on Github, based on go language and complies with Apache2. 0 protocol open source.
  9. 根据权利要求1所述的基于区块链的供应链金融AI DaaS算法仓库平台,其特征在于,所述K8S包括主节点和计算节点;所述主节点包括API Server、Scheduler、Controller manager,所述API Server是整个系统的对外接口,供客户端和其它组件调用,所述Scheduler负责对集群内部的资源进行调度,所述Controller manager负责管理控制器;所述计算节点包括所述Docker、kubelet、kube-proxy、Fluentd、Pod,所述Pod是所述K8S最基本的操作单元,所述Pod代表着集群中运行的一个进程且内部封装了一个或多个紧密相关的容器,所述Kubelet负责监视指派到所述Kubelet所在所述计算节点上的所述Pod,包括创建、修改、监控、删除等,所述Kube-proxy用于为所述Pod提供代理,所述Fluentd用于日志收集、存储与查询。The blockchain-based supply chain finance AI DaaS algorithm warehouse platform according to claim 1, wherein the K8S includes a master node and a computing node; the master node includes an API Server, a Scheduler, and a Controller manager, and the API Server is the external interface of the entire system, which is called by clients and other components. The Scheduler is responsible for scheduling the resources inside the cluster, and the Controller manager is responsible for managing the controller; the computing nodes include the Docker, kubelet, kube -proxy, Fluentd, Pod. The Pod is the most basic operation unit of the K8S. The Pod represents a process running in the cluster and encapsulates one or more closely related containers. The Kubelet is responsible for monitoring assignments To the Pod on the computing node where the Kubelet is located, including creation, modification, monitoring, deletion, etc., the Kube-proxy is used to provide a proxy for the Pod, and the Fluentd is used for log collection, storage and query .
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