A cross-platform city service credit evaluation method based on blockchain

Abstract

The present invention particularly relates to a cross-platform city service credit evaluation method based on blockchain. The cross-platform city service credit evaluation method based on blockchain publishes cross-platform credit evaluation information, credit metadata information of each credit subject and credit evaluation indicators to the blockchain network, and registers to the credit smart governance basic platform after review; calls the credit indicator conflict detection smart contract to detect the credit evaluation indicators and form a report output; calls the credit indicator fusion smart contract to calculate and fuse to generate public credit evaluation indicators, calls the credit score calculation contract to calculate the credit score and store it in the blockchain network; each credit evaluation platform obtains the comprehensive credit evaluation of the credit subject from the blockchain network. The cross-platform city service credit evaluation method based on blockchain solves the problem of non-mutual recognition of credit evaluations of various platforms during cross-platform operations, realizes the unified and comprehensive evaluation of credit subjects, and thus avoids the problems of corporate credit evaluation caused by cross-platform operations.

Description

Technical Field

[0001] The present invention relates to the field of cloud computing and edge computing technology, and in particular to a cross-platform city service credit evaluation method based on blockchain. Background Art

[0002] At present, the national credit information sharing platform, which includes "one database, one platform, two websites, and four systems", has been built and put into use, and has basically realized the cross-platform collection and sharing of public credit information in various regions and departments. The construction of a unified social credit code system based on citizen ID numbers and organizational codes has been comprehensively promoted; relevant "red and black list" information has been made public to the society through the "Credit China" website, and corporate credit reports have been widely queried and used in bidding, government procurement and other processes. However, the credit information sharing platform only provides basic credit data and public credit evaluation of urban credit entities, which cannot meet the needs of local governments for comprehensive credit assessment of urban credit entities and graded supervision based on credit evaluation.

[0003] In order to better apply credit to urban management, various cities have issued standardized methods for credit evaluation of urban credit entities based on public credit evaluation, and have conducted more comprehensive credit evaluation and credit management of local credit entities. For example, in terms of credit evaluation of landscaping enterprises, City A issued the implementation method for credit evaluation of landscaping construction enterprises, and City B issued the implementation method for credit grading and classification evaluation of landscaping enterprises. Various cities conduct credit evaluation of local enterprises based on the evaluation method, and manage various aspects such as market access of enterprises based on credit evaluation.

[0004] In actual operation, since the credit evaluations on various platforms are not mutually recognized, the independent credit evaluations have brought great inconvenience to the cross-platform operation of urban credit entities. At the same time, the independent service credit evaluation systems in various places cannot fully and accurately portray the credit status of credit entities. Therefore, there is an urgent need for a method and system for realizing cross-platform credit evaluation of credit entities to achieve a unified and comprehensive evaluation of the credit of urban credit entities and shield the problems of corporate credit evaluation caused by cross-platform operation.

[0005] Based on the above situation, the present invention proposes a cross-platform urban service credit evaluation method based on blockchain. Summary of the invention

[0006] In order to make up for the shortcomings of the prior art, the present invention provides a simple and efficient cross-platform city service credit evaluation method based on blockchain.

[0007] The present invention is achieved through the following technical solutions:

[0008] A cross-platform city service credit evaluation method based on blockchain, characterized in that it includes the following steps:

[0009] Step 1: The credit smart governance basic platform publishes the cross-platform credit evaluation information to the blockchain network, and forms blocks synchronously across the entire network;

[0010] Step 2: Each credit subject publishes metadata information to the blockchain network through the credit data interface; the credit smart governance basic platform receives the metadata information, registers the metadata information to the credit smart governance basic platform after review, and synchronizes it to the blockchain network;

[0011] Step 3: Each credit evaluation platform collects credit evaluation indicators based on cross-platform credit evaluation information, and publishes the collected credit evaluation indicators to the blockchain network through the connected credit evaluation and assessment pre-system. The credit evaluation indicators of each credit evaluation platform are synchronously formed into blocks across the entire network;

[0012] Step 4: The credit smart governance basic platform collects the credit evaluation indicators of various credit evaluation platforms, and passes the collected credit evaluation indicators to the credit indicator conflict detection smart contract, calls the credit indicator conflict detection smart contract module to detect the credit evaluation indicators, and generates a report output;

[0013] Step 5: The credit smart governance basic platform selects a credit indicator fusion smart contract based on the report, calls the credit indicator fusion smart contract to calculate and fuse to generate public credit evaluation indicators, and forms a cross-platform credit evaluation indicator set;

[0014] The credit score calculation contract uses the credit data interface of each credit subject to calculate the credit score based on the cross-platform credit evaluation index set, and stores it in the blockchain network after the calculation is completed;

[0015] Step 6: Each credit evaluation platform obtains the comprehensive credit evaluation of the credit subject from the blockchain network and uses it for various credit usage scenarios on its respective platform.

[0016] The blockchain network is a credit governance alliance chain formed by the credit evaluation and assessment pre-systems of various credit evaluation platforms, the credit smart governance basic platform and the credit information service website. It is responsible for providing channels for data sharing and exchange among various credit evaluation and assessment pre-systems, and at the same time provides digital identity certificates for various credit evaluation and assessment pre-systems connected to the blockchain network to realize transaction verification and block generation. It realizes multi-party trust between various access nodes based on consensus algorithms and voting machines, and ensures that the behavior evidence of various credit evaluation and assessment pre-systems connected to the blockchain network cannot be tampered with.

[0017] The credit smart governance basic platform is added to the blockchain network as a node of the blockchain network, including blockchain SDK, system identity certificate, credit index governance module and credit data governance module;

[0018] The blockchain SDK and system identity certificate are tools and credentials for connecting to the blockchain network. As a senior node in the blockchain credit governance alliance, the credit smart governance basic platform has organizational management functions and is responsible for the review and admission of new nodes. New members who are authorized to join the alliance are ordinary nodes and have the authority to synchronize information sharing and provide / enjoy credit services.

[0019] The credit index governance module is responsible for managing the credit index conflict detection smart contract and the credit index fusion smart contract, calling the credit index conflict detection smart contract and the credit index fusion smart contract according to the situation of the credit data interface, and building a unified evaluation index;

[0020] The credit data governance module is responsible for managing the credit data of each credit subject accessed through the credit data interface.

[0021] The credit data interface uses an interface to connect the credit data of each credit subject to the blockchain network; before access, the interface is registered and published on the credit smart governance basic platform, and the blockchain network actively calls the credit data interface to obtain credit data when calculating credit points.

[0022] The credit index conflict detection smart contract adopts a cross-platform credit nonlinear structure model and establishes a knowledge rule base based on historical credit big data, including common sense rules and business-specific rules, to identify incorrect or abnormal values ​​of credit information;

[0023] Use time series analysis methods to establish a dynamic data model of the credit subject in the credit information time series, conduct correlation analysis and curve fitting on the dynamic data of the credit subject, and determine the credit information with abnormal changes in time series information;

[0024] Using clustering-based outlier detection methods and probability distribution-based outlier detection methods, we study the information conflicts between credit subjects, between subjects and groups, and between credit groups, and establish credit conflict judgment methods in different fields, platforms, scenarios, and ecosystems;

[0025] Combined with the federated learning method, a reasonable credit conflict threshold range is constructed at different levels, granularity and dimensions across platforms; the credit information correlation of multiple credit entities on different platforms is analyzed, and a multi-level, multi-dimensional and multi-granular blockchain smart contract is established across platforms and deployed on the blockchain network to receive credit evaluation indicators from various credit evaluation platforms and output credit indicator conflict reports.

[0026] The credit indicator fusion smart contract is based on a cross-platform credit nonlinear structure model, and establishes a cross-platform service credit fusion smart contract that combines cross-platform credit information at multiple levels, including data, indicators and credit subjects, horizontally and vertically, and integrates the credit evaluation indicators of various credit evaluation platforms into public credit evaluation indicators.

[0027] In order to solve the problem of incomplete modal data on different platforms of the same structure and field, based on the cross-platform credit transmission and credit migration method, the credit indicator fusion smart contract adopts the incomplete multi-source data fusion method under federated learning, constructs the core matrix of incomplete multi-source data, establishes the feature fusion model of each platform, and conducts multi-platform joint optimization learning based on horizontal and vertical federated learning methods to obtain a cross-platform deep shared feature space, thereby realizing isomorphic and cross-platform credit information fusion.

[0028] In order to solve the problems of insufficient and unshared credit information in heterogeneous, cross-domain and cross-platform environments, the credit indicator fusion smart contract adopts a multi-source credit information fusion method based on subspace learning under unsupervised learning. By projecting the data of a single platform into the same semantic shared subspace, the typical correlation analysis method is used to complete the clustering of data feature instances, and multi-platform joint optimization learning is performed based on the federated learning method to obtain a cross-platform, heterogeneous deep shared feature space, thereby realizing heterogeneous and cross-platform credit information fusion.

[0029] In view of the dynamic changes in multi-source credit information across platforms, the credit indicator fusion smart contract analyzes credit feature information based on time series, establishes an incremental feature fusion model for multi-source credit data, studies the co-clustering and fusion method of incremental multi-source data, and realizes cross-platform credit information fusion of incremental multi-source dynamic data.

[0030] The credit score calculation smart contract calculates the universal credit score based on the public credit evaluation index and calls the credit interface of each credit data source.

[0031] The credit evaluation and assessment pre-system joins the blockchain network as a common node and is a connector connecting various credit evaluation platforms with the blockchain network. It is used to collect credit evaluation indicators of various credit evaluation platforms and issue public credit evaluation indicators.

[0032] The beneficial effect of the present invention is that the cross-platform urban service credit evaluation method based on blockchain solves the problem that when various credit subjects in current urban management conduct cross-platform operations, the credit evaluations on various platforms are not mutually recognized, and the independent service credit evaluation systems in various places cannot fully and accurately portray the credit of the credit subjects. It realizes a unified and comprehensive evaluation of credit subjects in the field of urban services, thereby avoiding the problems of corporate credit evaluation caused by cross-platform operations. BRIEF DESCRIPTION OF THE DRAWINGS

[0033] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0034] Attached Figure 1 This is a schematic diagram of the cross-platform city service credit evaluation method based on blockchain in the present invention.

[0035] Attached Figure 2 It is a schematic diagram of information flow during the implementation of the present invention.

[0036] Attached Figure 3 This is a schematic diagram of the implementation steps of the cross-platform city service credit evaluation method based on blockchain of the present invention. DETAILED DESCRIPTION

[0037] In order to enable those skilled in the art to better understand the technical solutions in the present invention, the technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work should fall within the scope of protection of the present invention.

[0038] The cross-platform city service credit evaluation method based on blockchain includes the following steps:

[0039] Step 1: The credit smart governance basic platform publishes the cross-platform credit evaluation information to the blockchain network, and forms blocks synchronously across the entire network;

[0040] Step 2: Each credit subject publishes metadata information to the blockchain network through the credit data interface; the credit smart governance basic platform receives the metadata information, registers the metadata information to the credit smart governance basic platform after review, and synchronizes it to the blockchain network;

[0041] Step 3: Each credit evaluation platform collects credit evaluation indicators based on cross-platform credit evaluation information, and publishes the collected credit evaluation indicators to the blockchain network through the connected credit evaluation and assessment pre-system. The credit evaluation indicators of each credit evaluation platform are synchronously formed into blocks across the entire network;

[0042] Step 4: The credit smart governance basic platform collects the credit evaluation indicators of various credit evaluation platforms, and passes the collected credit evaluation indicators to the credit indicator conflict detection smart contract, calls the credit indicator conflict detection smart contract module to detect the credit evaluation indicators, and generates a report output;

[0043] Step 5: The credit smart governance basic platform selects a credit indicator fusion smart contract based on the report, calls the credit indicator fusion smart contract to calculate and fuse to generate public credit evaluation indicators, and forms a cross-platform credit evaluation indicator set;

[0044] The credit score calculation contract uses the credit data interface of each credit subject to calculate the credit score based on the cross-platform credit evaluation index set, and stores it in the blockchain network after the calculation is completed;

[0045] Step 6: Each credit evaluation platform obtains the comprehensive credit evaluation of the credit subject from the blockchain network and uses it for various credit usage scenarios on its respective platform.

[0046] The blockchain network is a credit governance alliance chain formed by the credit evaluation and assessment pre-systems of various credit evaluation platforms, the credit smart governance basic platform and the credit information service website. It is responsible for providing channels for data sharing and exchange among various credit evaluation and assessment pre-systems, and at the same time provides digital identity certificates for various credit evaluation and assessment pre-systems connected to the blockchain network to realize transaction verification and block generation. It realizes multi-party trust between various access nodes based on consensus algorithms and voting machines, and ensures that the behavior evidence of various credit evaluation and assessment pre-systems connected to the blockchain network cannot be tampered with.

[0047] The credit smart governance basic platform is added to the blockchain network as a node of the blockchain network, including blockchain SDK, system identity certificate, credit index governance module and credit data governance module;

[0048] The blockchain SDK and system identity certificate are tools and credentials for connecting to the blockchain network. As a senior node in the blockchain credit governance alliance, the credit smart governance basic platform has organizational management functions and is responsible for the review and admission of new nodes. New members who are authorized to join the alliance are ordinary nodes and have the authority to synchronize information sharing and provide / enjoy credit services.

[0049] The credit index governance module is responsible for managing the credit index conflict detection smart contract and the credit index fusion smart contract, calling the credit index conflict detection smart contract and the credit index fusion smart contract according to the situation of the credit data interface, and building a unified evaluation index;

[0050] The credit data governance module is responsible for managing the credit data of each credit subject accessed through the credit data interface.

[0051] The credit data interface uses an interface to connect the credit data of each credit subject to the blockchain network; before access, the interface is registered and published on the credit smart governance basic platform, and the blockchain network actively calls the credit data interface to obtain credit data when calculating credit points.

[0052] Differences in credit indicator calculations and false data for different levels of credit data, indicators, subjects, different granularity, different dimensional application scenarios and service needs will cause the credit of the credit subject to deviate from the credible range, the credit subject's related information to be missing, and other credit inconsistencies.

[0053] The credit index conflict detection smart contract adopts a cross-platform credit nonlinear structure model and establishes a knowledge rule base based on historical credit big data, including common sense rules and business-specific rules, to identify incorrect or abnormal values ​​of credit information;

[0054] Use time series analysis methods to establish a dynamic data model of the credit subject in the credit information time series, conduct correlation analysis and curve fitting on the dynamic data of the credit subject, and determine the credit information with abnormal changes in time series information;

[0055] Using clustering-based outlier detection methods and probability distribution-based outlier detection methods, we study the information conflicts between credit subjects, between subjects and groups, and between credit groups, and establish credit conflict judgment methods in different fields, platforms, scenarios, and ecosystems;

[0056] Combined with the federated learning method, a reasonable credit conflict threshold range is constructed at different levels, granularity and dimensions across platforms; the credit information correlation of multiple credit entities on different platforms is analyzed, and a multi-level, multi-dimensional and multi-granular blockchain smart contract is established across platforms and deployed on the blockchain network to receive credit evaluation indicators from various credit evaluation platforms and output credit indicator conflict reports.

[0057] Heterogeneous platforms have differences in platform structure, evaluation methods, credit subject relevance, credit modality, etc., which makes credit information inconsistent, asymmetric, incomplete, and non-standard. At the same time, there are problems such as incomplete modality, lack of real-time guarantee, and modality imbalance. This makes the cross-platform credit information integration face huge challenges in terms of efficiency, timeliness, and integrity, resulting in the inability to make objective, comprehensive, and fair judgments on credit subjects.

[0058] The credit indicator fusion smart contract is based on a cross-platform credit nonlinear structure model, and establishes a cross-platform service credit fusion smart contract that combines cross-platform credit information at multiple levels, including data, indicators and credit subjects, horizontally and vertically, and integrates the credit evaluation indicators of various credit evaluation platforms into public credit evaluation indicators.

[0059] In order to solve the problem of incomplete modal data on different platforms of the same structure and field, based on the cross-platform credit transmission and credit migration method, the credit indicator fusion smart contract adopts the incomplete multi-source data fusion method under federated learning, constructs the core matrix of incomplete multi-source data, establishes the feature fusion model of each platform, and conducts multi-platform joint optimization learning based on horizontal and vertical federated learning methods to obtain a cross-platform deep shared feature space, thereby realizing isomorphic and cross-platform credit information fusion.

[0060] In order to solve the problems of insufficient and unshared credit information in heterogeneous, cross-domain and cross-platform environments, the credit indicator fusion smart contract adopts a multi-source credit information fusion method based on subspace learning under unsupervised learning. By projecting the data of a single platform into the same semantic shared subspace, the typical correlation analysis method is used to complete the clustering of data feature instances, and multi-platform joint optimization learning is performed based on the federated learning method to obtain a cross-platform, heterogeneous deep shared feature space, thereby realizing heterogeneous and cross-platform credit information fusion.

[0061] In view of the dynamic changes in multi-source credit information across platforms, the credit indicator fusion smart contract analyzes credit feature information based on time series, establishes an incremental feature fusion model for multi-source credit data, studies the co-clustering and fusion method of incremental multi-source data, and realizes cross-platform credit information fusion of incremental multi-source dynamic data.

[0062] The credit score calculation smart contract calculates the universal credit score based on the public credit evaluation index and calls the credit interface of each credit data source.

[0063] The credit evaluation and assessment pre-system joins the blockchain network as a common node and is a connector connecting various credit evaluation platforms with the blockchain network. It is used to collect credit evaluation indicators of various credit evaluation platforms and issue public credit evaluation indicators.

[0064] The embodiment described above is only one specific implementation of the present invention. Common changes and substitutions made by those skilled in the art within the scope of the technical solution of the present invention should be included in the protection scope of the present invention.

Claims

1. A cross-platform city service credit evaluation method based on blockchain, characterized by: The following steps are involved: Step 1: The credit smart governance basic platform publishes the cross-platform credit evaluation information to the blockchain network, and forms blocks synchronously across the entire network; Step 2: Each credit subject publishes metadata information to the blockchain network through the credit data interface; the credit smart governance basic platform receives the metadata information, registers the metadata information to the credit smart governance basic platform after review, and synchronizes it to the blockchain network; Step 3: Each credit evaluation platform collects credit evaluation indicators based on cross-platform credit evaluation information, and publishes the collected credit evaluation indicators to the blockchain network through the connected credit evaluation and assessment pre-system. The credit evaluation indicators of each credit evaluation platform are synchronously formed into blocks across the entire network; Step 4: The credit smart governance basic platform collects the credit evaluation indicators of various credit evaluation platforms, and passes the collected credit evaluation indicators to the credit indicator conflict detection smart contract, calls the credit indicator conflict detection smart contract module to detect the credit evaluation indicators, and generates a report output; The credit index conflict detection smart contract adopts a cross-platform credit nonlinear structure model, establishes a knowledge rule base based on historical credit big data, including common sense rules and business-specific rules to identify wrong values ​​or abnormal values ​​of credit information; uses time series analysis methods to establish a dynamic data model of the credit subject on the credit information time series, performs correlation analysis and curve fitting on the dynamic data of the credit subject, and determines the credit information with abnormal changes in time series information; Using clustering-based outlier detection methods and probability distribution-based outlier detection methods, we study the information conflicts between credit subjects, between subjects and groups, and between credit groups, and establish credit conflict judgment methods in different fields, platforms, scenarios, and ecosystems; Combined with the federated learning method, a reasonable credit conflict threshold range is constructed at different levels, granularity and dimensions across platforms; Analyze the credit information relevance of multiple credit entities on different platforms, establish a cross-platform multi-level, multi-dimensional and multi-granular blockchain smart contract, and deploy it on the blockchain network to receive credit evaluation indicators from various credit evaluation platforms and output credit indicator conflict reports; Step 5: The credit smart governance basic platform selects a credit indicator fusion smart contract based on the report, calls the credit indicator fusion smart contract to calculate and fuse to generate public credit evaluation indicators, and forms a cross-platform credit evaluation indicator set; The credit score calculation contract uses the credit data interface of each credit subject to calculate the credit score based on the cross-platform credit evaluation index set, and stores it in the blockchain network after the calculation is completed; Step 6: Each credit evaluation platform obtains the comprehensive credit evaluation of the credit subject from the blockchain network and uses it for various credit usage scenarios on its respective platform.

2. The cross-platform city service credit evaluation method based on blockchain according to claim 1 is characterized in that: The blockchain network is a credit governance alliance chain formed by the credit evaluation and assessment pre-systems of various credit evaluation platforms, the credit smart governance basic platform and the credit information service website. It is responsible for providing channels for data sharing and exchange among various credit evaluation and assessment pre-systems, and at the same time provides digital identity certificates for various credit evaluation and assessment pre-systems connected to the blockchain network to realize transaction verification and block generation. It realizes multi-party trust between various access nodes based on consensus algorithms and voting machines, and ensures that the behavior evidence of various credit evaluation and assessment pre-systems connected to the blockchain network cannot be tampered with.

3. The cross-platform city service credit evaluation method based on blockchain according to claim 2 is characterized in that: The credit smart governance basic platform is added to the blockchain network as a node of the blockchain network, including blockchain SDK, system identity certificate, credit index governance module and credit data governance module; The blockchain SDK and system identity certificate are tools and credentials for connecting to the blockchain network. As a senior node in the blockchain credit governance alliance, the credit smart governance basic platform has organizational management functions and is responsible for the review and admission of new nodes. New members who are authorized to join the alliance are ordinary nodes and have the authority to synchronize information sharing and provide / enjoy credit services. The credit index governance module is responsible for managing the credit index conflict detection smart contract and the credit index fusion smart contract, calling the credit index conflict detection smart contract and the credit index fusion smart contract according to the situation of the credit data interface, and building a unified evaluation index; The credit data governance module is responsible for managing the credit data of each credit subject accessed through the credit data interface.

4. The cross-platform city service credit evaluation method based on blockchain according to claim 2 is characterized in that: The credit data interface uses an interface to connect the credit data of each credit subject to the blockchain network; before access, the interface is registered and published on the credit smart governance basic platform, and the blockchain network actively calls the credit data interface to obtain credit data when calculating credit points.

5. The cross-platform city service credit evaluation method based on blockchain according to claim 3 is characterized by: The credit index fusion smart contract is based on a cross-platform credit nonlinear structure model, and establishes a cross-platform service credit fusion smart contract that combines cross-platform credit information at multiple levels, including data, indicators and credit subjects, horizontally and vertically, and integrates the credit evaluation indicators of various credit evaluation platforms into public credit evaluation indicators; The credit score calculation smart contract calculates the universal credit score by calling the credit interfaces of various credit data sources based on the public credit evaluation indicators.

6. The cross-platform city service credit evaluation method based on blockchain according to claim 5 is characterized in that: In order to solve the problem of incomplete modal data under the same structure and different platforms in the same field, the credit index fusion smart contract adopts the incomplete multi-source data fusion method under federated learning, constructs the core matrix of incomplete multi-source data, establishes the feature fusion model of each platform, and conducts multi-platform joint optimization learning based on horizontal and vertical federated learning methods to obtain a cross-platform deep shared feature space, thus realizing the fusion of isomorphic and cross-platform credit information; In order to solve the problem of insufficient and unshared credit information under heterogeneous cross-domain and cross-platform, the credit index fusion smart contract adopts a multi-source credit information fusion method based on subspace learning under unsupervised learning, projects the data of a single platform into the same semantic shared subspace, and uses the canonical correlation analysis method to complete the clustering of data feature instances; Based on the federated learning method, multi-platform joint optimization learning is carried out to obtain a cross-platform, heterogeneous deep shared feature space, and realize the integration of heterogeneous and cross-platform credit information; In view of the dynamic changes in multi-source credit information across platforms, the credit indicator fusion smart contract analyzes credit feature information based on time series, establishes an incremental feature fusion model for multi-source credit data, studies the co-clustering and fusion method of incremental multi-source data, and realizes cross-platform credit information fusion of incremental multi-source dynamic data.

7. The cross-platform city service credit evaluation method based on blockchain according to claim 2 is characterized in that: The credit evaluation and assessment pre-system joins the blockchain network as a common node and is a connector connecting various credit evaluation platforms with the blockchain network. It is used to collect credit evaluation indicators of various credit evaluation platforms and issue public credit evaluation indicators.

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