CN117201196B - Intelligent high-speed data storage method and system based on double-chain fusion - Google Patents
Intelligent high-speed data storage method and system based on double-chain fusion Download PDFInfo
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Abstract
The invention discloses a smart high-speed data storage method and system based on double-chain fusion, wherein the method comprises the following steps: constructing a light chain polymerization platform according to the enterprise chain and the industry chain; user registration and verification are carried out through a light chain aggregation platform, and privacy data to be stored, which are uploaded by a user, are received; acquiring the data quantity of the private data to be stored, and selecting a target data storage mode according to the data quantity; and processing and storing the private data to be stored in a target data storage mode. The light chain aggregation platform is constructed by the industry chain of the group and the enterprise chains of all enterprises, and the direct data interaction butt joint between the enterprises and the groups can be realized through the constructed platform, so that the groups can check the data before uploading the data in the storage enterprises, the accuracy and the authenticity of the data are ensured, the data transmission efficiency can be greatly improved by using the double-block chain for data transmission, the data transmission cost can be maximally reduced, and the practicability and the experience of users are improved.
Description
Technical Field
The invention relates to the technical field of blockchain, in particular to an intelligent high-speed data storage method and system based on double-chain fusion.
Background
At present, along with the perfection of the expressway infrastructure in the province of China, the intelligent expressway is the next target of the expressway development in the province of China, a high-speed group is taken as a main construction management unit to accumulate a large amount of construction, management, charging and customer privacy data, how to ensure the safety and traceability of the data is an important factor of the intelligent expressway development, the existing intelligent expressway data storage method is generally that each enterprise uploads the data to a data storage platform through a fixed data uploading channel, and then the high-speed group performs statistics and classified storage, so that the following problems exist: because the existence of the transfer platform causes that each enterprise cannot directly interact with the group so as to not guarantee the accuracy and the authenticity of the data, the data uploading cost is high, and the use experience of both parties is reduced.
Disclosure of Invention
Aiming at the problems shown in the prior art, the invention provides an intelligent high-speed data storage method and system based on double-chain fusion, which are used for solving the problems that in the background art, due to the existence of a transfer platform, each enterprise cannot directly interact with a group, so that the accuracy and the authenticity of data cannot be ensured, meanwhile, the data uploading cost is high, and the use experience of both parties is reduced.
A smart high-speed data storage method based on double-chain fusion comprises the following steps:
constructing a light chain polymerization platform according to the enterprise chain and the industry chain;
user registration and verification are carried out through a light chain aggregation platform, and privacy data to be stored, which are uploaded by a user, are received;
acquiring the data quantity of the private data to be stored, and selecting a target data storage mode according to the data quantity;
and processing and storing the private data to be stored in a target data storage mode.
Preferably, the construction of the light chain polymerization platform according to the enterprise chain and the industry chain comprises the following steps:
respectively acquiring respective data exchange criteria of an enterprise chain and an industry chain;
constructing an interactive decision model of the enterprise chain and the industry chain according to respective data exchange criteria of the enterprise chain and the industry chain;
acquiring platform design parameters and platform demand parameters;
and constructing a light chain polymerization platform according to the platform design parameters and the platform demand parameters and combining the enterprise chain and an interactive decision model of the industry chain.
Preferably, the user registration and authentication by the light chain aggregation platform and receiving the privacy data to be stored uploaded by the user include:
receiving a registration request of a user through a light chain aggregation platform, and acquiring identity information, contact information, bank card information and face input information of an authorized user according to the registration request;
the identity information, the contact information, the bank card information and the face input information of the user are stored in an associated mode;
receiving a real-time login request of a user, verifying the user according to stored identity information, and obtaining a verification result;
and if the verification result is that the verification is passed, activating an enterprise chain data uploading channel of the light chain aggregation platform and receiving the privacy data to be stored, which is uploaded by the user, according to the enterprise chain data uploading channel.
Preferably, the obtaining the data amount of the private data to be stored, and selecting the target data storage mode according to the data amount, includes:
evaluating the data quantity of the private data to be stored through a data evaluation component;
comparing the data quantity of the privacy data to be stored with a preset data quantity reference threshold value to obtain a comparison result;
if the comparison result shows that the data volume of the private data to be stored is smaller than or equal to the preset data volume reference threshold value, selecting the target data storage mode as a single-chain storage mode;
and if the comparison result shows that the data volume of the private data to be stored is larger than the preset data volume reference threshold value, selecting the target data storage mode as a double-chain storage mode.
Preferably, the double-chain storage mode is a data storage mode of combining a public chain and a private chain;
the public chain is used for storing the hash value and the block header of the private chain;
the private chain is used for storing the complete private data to be stored.
Preferably, the processing and storing the private data to be stored in the target data storage mode includes:
determining the privacy degree of the private data to be stored, and selectively encrypting the data to be stored according to the privacy degree;
determining the data type of the private data to be stored, and selecting a data storage protocol for the private data to be stored according to the data type;
and storing the private data to be stored or the encrypted private data to be stored according to the data storage protocol.
Preferably, the method further comprises:
acquiring enterprise qualification information and business information of a plurality of suppliers, and screening out a second number of adapted target supplier evaluation indexes from the first number of supplier evaluation indexes according to the enterprise qualification information and the business information;
constructing an initial credit assessment system of the provider by using the second number of target provider assessment indexes;
acquiring process state data of historical business of each provider and training an initial credit evaluation system of the provider by using the process state data to acquire a target credit evaluation system of the provider;
determining enterprise business requirements and business project parameters according to privacy data to be stored, which are uploaded by a user;
selecting a first provider with an adaptive service from a plurality of providers according to enterprise service requirements and service item parameters;
carrying out credit evaluation on each first provider by using a target credit evaluation system of the provider to obtain an evaluation result;
and selecting a second provider with the reliability of the first three according to the evaluation result, and displaying and recommending enterprise information of the second provider through the light chain aggregation platform.
Preferably, the method further comprises:
determining a desired provider selected by a user, and generating an electronic contract according to the service contract detail content uploaded by the user;
uploading the electronic contract signing and signing to an electronic contract signing window of the light chain aggregation platform and enabling a user and an expected provider to sign up online;
generating a notarization report and a digital certificate according to the signed electronic contract;
and (5) carrying out uplink storage on the signed electronic contract and notarization report and the digital certificate.
Preferably, the constructing an initial credit assessment system of the provider using the second number of target provider assessment indexes includes:
acquiring an associated individual label and an associated composite label of each target provider evaluation index;
determining the corresponding relation between the associated individual label and the associated composite label of each target provider evaluation index;
selecting a target label from the associated individual label and the associated composite label of each target provider evaluation index according to the corresponding relation between the associated individual label and the associated composite label of each target provider evaluation index as a model label of the target provider evaluation index;
retrieving relevant formatted data samples of the model tags for each target provider evaluation index;
carrying out business logic analysis on the related formatted data samples of the model labels of the evaluation indexes of each target provider to obtain an analysis result;
determining credit description behavior variables of each target provider evaluation index according to the analysis result;
determining macro economic index factors and micro risk index factors of each target provider evaluation index based on credit descriptive behavior variables of the target provider evaluation index;
acquiring respective target field characteristic quantities of macro economic index factors and micro risk index factors of each target provider evaluation index;
calculating intersection of the target field feature quantities of the macro economic index factor and the micro risk index factor of each target provider evaluation index, and determining economic feature vectors, risk feature vectors and public feature vectors of each target provider evaluation index according to calculation results;
generating a feature mapping matrix according to the economic feature vector and the risk feature vector of each target provider evaluation index and the public feature vector;
constructing a credit evaluation mixed model of the provider according to the characteristic mapping matrix of each target provider evaluation index;
determining an input sample of the credit evaluation hybrid model, determining a data format according to the input sample, and selecting a format conversion protocol according to the data format;
an initial credit assessment hierarchy for the provider is constructed based on the format conversion protocol and the credit assessment hybrid model.
An intelligent high-speed data storage system based on double-chain fusion, the system comprising:
the construction module is used for constructing a light chain polymerization platform according to the enterprise chain and the industry chain;
the receiving module is used for carrying out user registration and verification through the light chain aggregation platform and receiving the privacy data to be stored, which are uploaded by the user;
the selecting module is used for acquiring the data volume of the private data to be stored and selecting a target data storage mode according to the data volume;
and the storage module is used for processing and storing the privacy data to be stored in a target data storage mode.
Through the technical means, the invention has the following beneficial effects:
1) The light chain aggregation platform is constructed by the industry chain of the group and the enterprise chains of all enterprises, and the direct data interaction butt joint between the enterprises and the groups can be realized through the constructed platform, so that the groups can check the data before uploading the data by the storage enterprises, the accuracy and the authenticity of the data are ensured, and further, the data transmission efficiency can be greatly improved and the data transmission cost can be maximally reduced by using the double-block chain for data transmission, and the practicability and the experience of users are improved.
2) The model is constructed to accurately control the block chain data interaction stability between the enterprise chain and the industry chain, so that a foundation is laid for a subsequent construction platform, and the stability and the practicability are further improved.
3) The identity security of the user of the control platform can be strictly ensured by carrying out multidimensional identity verification on the user, so that important privacy data disclosure is avoided, and the safety and privacy of a poem are improved.
Additional features and advantages of the invention will be set forth in the description which follows, and in part will be obvious from the description, or may be learned by practice of the invention. The objectives and other advantages of the invention may be realized and attained by the structure particularly pointed out in the written description and drawings.
The technical scheme of the invention is further described in detail through the drawings and the embodiments.
Drawings
The accompanying drawings are included to provide a further understanding of the invention and are incorporated in and constitute a part of this specification, illustrate the invention and together with the embodiments of the invention, serve to explain the invention.
FIG. 1 is a flowchart of a smart high-speed data storage method based on double-chain fusion.
FIG. 2 is another workflow diagram of a smart high-speed data storage method based on double-chain fusion according to the present invention.
FIG. 3 is a flowchart of a smart high-speed data storage method based on double-chain fusion according to the present invention.
FIG. 4 is a schematic diagram of a smart high-speed data storage system based on double-chain fusion according to the present invention.
Detailed Description
Reference will now be made in detail to exemplary embodiments, examples of which are illustrated in the accompanying drawings. When the following description refers to the accompanying drawings, the same numbers in different drawings refer to the same or similar elements, unless otherwise indicated. The implementations described in the following exemplary examples are not representative of all implementations consistent with the present disclosure. Rather, they are merely examples of apparatus and methods consistent with some aspects of the present disclosure as detailed in the accompanying claims.
At present, along with the perfection of the expressway infrastructure in the province of China, the intelligent expressway is the next target of the expressway development in the province of China, a high-speed group is taken as a main construction management unit to accumulate a large amount of construction, management, charging and customer privacy data, how to ensure the safety and traceability of the data is an important factor of the intelligent expressway development, the existing intelligent expressway data storage method is generally that each enterprise uploads the data to a data storage platform through a fixed data uploading channel, and then the high-speed group performs statistics and classified storage, so that the following problems exist: because the existence of the transfer platform causes that each enterprise cannot directly interact with the group so as to not guarantee the accuracy and the authenticity of the data, the data uploading cost is high, and the use experience of both parties is reduced. In order to solve the above problems, the present embodiment discloses a smart high-speed data storage method based on double-chain fusion.
A smart high-speed data storage method based on double-chain fusion, as shown in figure 1, comprises the following steps:
s101, constructing a light chain polymerization platform according to an enterprise chain and an industry chain;
step S102, user registration and verification are carried out through a light chain aggregation platform, and privacy data to be stored, uploaded by a user, are received;
step S103, acquiring the data volume of the private data to be stored, and selecting a target data storage mode according to the data volume;
and step S104, processing and storing the privacy data to be stored in a target data storage mode.
The working principle of the technical scheme is as follows: constructing a light chain polymerization platform according to the enterprise chain and the industry chain; user registration and verification are carried out through a light chain aggregation platform, and privacy data to be stored, which are uploaded by a user, are received; acquiring the data quantity of the private data to be stored, and selecting a target data storage mode according to the data quantity; and processing and storing the private data to be stored in a target data storage mode.
In this embodiment, the enterprise chain is represented as an enterprise-specific blockchain, and the industry chain is represented as a specific blockchain of an industry large group;
in this embodiment, the light chain aggregation platform is represented as a network platform for performing double-chain data transmission;
in this embodiment, the target data storage mode is represented as a data storage mode for private data to be stored, and the selectable storage modes include a single-chain storage mode and a multi-chain storage mode.
The beneficial effects of the technical scheme are as follows: the light chain aggregation platform is constructed by the industry chain of the group and the enterprise chain of each enterprise, and the direct data interaction butt joint between the enterprises and the groups can be realized through the constructed platform, so that the groups can check the data before uploading the data in the storage enterprises, the accuracy and the authenticity of the data are ensured, further, the data transmission efficiency can be greatly improved by using the double-block chain for data transmission, the data transmission cost can be maximally reduced, the practicability and the experience of users are improved, and the problems that the data cannot be ensured due to the fact that each enterprise cannot directly interact with the group due to the existence of the transfer platform in the prior art are solved, the accuracy and the authenticity of the data are relatively high, and the use experience of both sides is reduced.
In one embodiment, the building a light chain aggregation platform from an enterprise chain and an industry chain comprises:
respectively acquiring respective data exchange criteria of an enterprise chain and an industry chain;
constructing an interactive decision model of the enterprise chain and the industry chain according to respective data exchange criteria of the enterprise chain and the industry chain;
acquiring platform design parameters and platform demand parameters;
and constructing a light chain polymerization platform according to the platform design parameters and the platform demand parameters and combining the enterprise chain and an interactive decision model of the industry chain.
In this embodiment, the data exchange criteria are expressed as blockchain configuration and operation criteria when the enterprise chain and the industry chain each exchange data;
in this embodiment, the interactive decision model is expressed as an automatic decision network model of the enterprise chain and the industry chain when data exchange is performed;
in this embodiment, the platform design parameters are expressed as code design parameters when designing a digital light chain aggregation platform;
in this embodiment, the platform requirements parameter is expressed as a functional requirements parameter for a digital light chain aggregation platform.
In this embodiment, an interactive decision model of the enterprise chain and the industry chain is constructed according to respective data exchange criteria of the enterprise chain and the industry chain, specifically:
determining the interaction decision of the enterprise chain and the industry chain according to the data exchange criteria of the enterprise chain and the industry chain;
and determining decision variables according to the interaction decision of the enterprise chain and the industry chain, and constructing an interaction decision model of the enterprise chain and the industry chain through a linear regression method based on the decision variables.
In this embodiment, a light chain aggregation platform is constructed according to a platform design parameter and a platform demand parameter in combination with an interactive decision model of an enterprise chain and an industry chain, specifically:
the platform is composed of a data source, a connection layer, an active layer, a logic layer and a service layer, wherein the data source provides bottom data support for the platform, the connection layer establishes connection between the data source and the active layer, so that the active layer can operate the data source, the active layer is generated through platform design parameters and platform demand parameters, operation support is provided for the whole platform system, the logic layer is generated through an interactive decision model of an enterprise chain and an industry chain and is used for carrying out logic decision on the data, and service is provided for a user through the service layer.
The beneficial effects of the technical scheme are as follows: the model is constructed to accurately control the block chain data interaction stability between the enterprise chain and the industry chain, so that a foundation is laid for a subsequent construction platform, and the stability and the practicability are further improved.
In one embodiment, the user registration and authentication by the light chain aggregation platform and receiving the privacy data to be stored uploaded by the user comprise:
receiving a registration request of a user through a light chain aggregation platform, and acquiring identity information, contact information, bank card information and face input information of an authorized user according to the registration request;
the identity information, the contact information, the bank card information and the face input information of the user are stored in an associated mode;
receiving a real-time login request of a user, verifying the user according to stored identity information, and obtaining a verification result;
and if the verification result is that the verification is passed, activating an enterprise chain data uploading channel of the light chain aggregation platform and receiving the privacy data to be stored, which is uploaded by the user, according to the enterprise chain data uploading channel.
The beneficial effects of the technical scheme are as follows: the identity security of the user of the control platform can be strictly ensured by carrying out multidimensional identity verification on the user, so that important privacy data disclosure is avoided, and the safety and privacy of a poem are improved.
In one embodiment, as shown in fig. 2, the obtaining the data volume of the private data to be stored, and selecting the target data storage mode according to the data volume includes:
step S201, evaluating the data quantity of the privacy data to be stored through a data evaluation component;
step S202, comparing the data volume of the privacy data to be stored with a preset data volume reference threshold value to obtain a comparison result;
step S203, if the comparison result shows that the data volume of the private data to be stored is less than or equal to the preset data volume reference threshold, selecting the target data storage mode as a single-chain storage mode;
step S204, if the comparison result is that the data volume of the private data to be stored is greater than the preset data volume reference threshold, selecting the target data storage mode as the double-chain storage mode.
In the present embodiment, the data evaluation component is represented as an applet component for performing data amount evaluation;
in this embodiment, the preset data amount reference threshold may be 20G.
The beneficial effects of the technical scheme are as follows: by selecting a reasonable data storage mode according to the data quantity and a preset data quantity reference threshold value, the suitability of the data transmission mode can be ensured, meanwhile, the network data transmission burden can be effectively reduced, and the data transmission stability and reliability are further improved.
In one embodiment, the double-chain storage mode is a data storage mode of combining a public chain and a private chain;
the public chain is used for storing the hash value and the block header of the private chain;
the private chain is used for storing the complete private data to be stored.
The beneficial effects of the technical scheme are as follows: the method and the device can realize stable storage of the data, provide convenience for follow-up data query, and improve data query efficiency and experience of users.
In one embodiment, the processing and storing the private data to be stored in the target data storage mode includes:
determining the privacy degree of the private data to be stored, and selectively encrypting the data to be stored according to the privacy degree;
determining the data type of the private data to be stored, and selecting a data storage protocol for the private data to be stored according to the data type;
and storing the private data to be stored or the encrypted private data to be stored according to the data storage protocol.
In the present embodiment, the degree of privacy is expressed as an absolute level of privacy evaluation of data to be stored;
in the present embodiment, the data type is represented as a data composition type of the private data to be stored, for example: character type, string type, etc.
The beneficial effects of the technical scheme are as follows: the privacy and the security of the data can be further ensured by selectively encrypting the data to be stored, and further, the stability and the reliability of the process of storing the data to be stored can be ensured by selecting a data storage protocol,
in one embodiment, further comprising:
acquiring enterprise qualification information and business information of a plurality of suppliers, and screening out a second number of adapted target supplier evaluation indexes from the first number of supplier evaluation indexes according to the enterprise qualification information and the business information;
constructing an initial credit assessment system of the provider by using the second number of target provider assessment indexes;
acquiring process state data of historical business of each provider and training an initial credit evaluation system of the provider by using the process state data to acquire a target credit evaluation system of the provider;
determining enterprise business requirements and business project parameters according to privacy data to be stored, which are uploaded by a user;
selecting a first provider with an adaptive service from a plurality of providers according to enterprise service requirements and service item parameters;
carrying out credit evaluation on each first provider by using a target credit evaluation system of the provider to obtain an evaluation result;
and selecting a second provider with the reliability of the first three according to the evaluation result, and displaying and recommending enterprise information of the second provider through the light chain aggregation platform.
In this embodiment, the screening of the adapted second number of target provider evaluation indexes from the first number of provider evaluation indexes according to the enterprise qualification information and the business information specifically includes:
determining a plurality of business indexes based on the enterprise qualification information and the business operation information;
carrying out correlation evaluation on each service index and each provider evaluation index to obtain a correlation index;
and selecting the supplier evaluation index with the correlation index being greater than or equal to the preset index as the adapted second number of target supplier evaluation indexes.
In this embodiment, process state data of a historical service of each provider is obtained, and an initial credit evaluation system of the provider is trained by using the process state data, and a target credit evaluation system of the provider is obtained, which specifically includes:
cleaning and processing the process state data of the historical service of each provider to remove abnormal values and repeated data;
clustering and classifying the process state data of the historical business of each provider by using a machine learning algorithm, and determining the data type and the data calculation function of each provider;
modifying system functions in the initial credit assessment system according to the data type and the data calculation function of each provider;
training the corresponding modified initial credit assessment system of each provider by using the process state data of the historical service of the provider to obtain the target credit assessment system of the provider.
The beneficial effects of the technical scheme are as follows: the service processing method and the service processing system can recommend the adapted supply enterprises for the group so as to ensure the smooth operation of the service, improve the service processing efficiency and the service execution efficiency and further improve the practicability.
In one embodiment, as shown in fig. 3, further comprising:
step S301, determining a desired provider selected by a user, and generating an electronic contract according to the service contract detail content uploaded by the user;
step S302, uploading the electronic contract signing and signing to an electronic contract signing window of a light chain aggregation platform and enabling a user and an expected provider to sign up online;
step S303, generating a notarization report and a digital certificate according to the signed electronic contract;
and step S304, carrying out uplink storage on the signed electronic contract and notarization report and the digital certificate.
The beneficial effects of the technical scheme are as follows: the online signing of the service contract can be realized, the contract privacy is ensured, the unfair signing caused by artificial reasons can be avoided, and the practicability and the experience of the user are improved.
In one embodiment, the constructing an initial credit assessment hierarchy for a vendor using a second number of target vendor valuation metrics comprises:
acquiring an associated individual label and an associated composite label of each target provider evaluation index;
determining the corresponding relation between the associated individual label and the associated composite label of each target provider evaluation index;
selecting a target label from the associated individual label and the associated composite label of each target provider evaluation index according to the corresponding relation between the associated individual label and the associated composite label of each target provider evaluation index as a model label of the target provider evaluation index;
retrieving relevant formatted data samples of the model tags for each target provider evaluation index;
carrying out business logic analysis on the related formatted data samples of the model labels of the evaluation indexes of each target provider to obtain an analysis result;
determining credit description behavior variables of each target provider evaluation index according to the analysis result;
determining macro economic index factors and micro risk index factors of each target provider evaluation index based on credit descriptive behavior variables of the target provider evaluation index;
acquiring respective target field characteristic quantities of macro economic index factors and micro risk index factors of each target provider evaluation index;
calculating intersection of the target field feature quantities of the macro economic index factor and the micro risk index factor of each target provider evaluation index, and determining economic feature vectors, risk feature vectors and public feature vectors of each target provider evaluation index according to calculation results;
generating a feature mapping matrix according to the economic feature vector and the risk feature vector of each target provider evaluation index and the public feature vector;
constructing a credit evaluation mixed model of the provider according to the characteristic mapping matrix of each target provider evaluation index;
determining an input sample of the credit evaluation hybrid model, determining a data format according to the input sample, and selecting a format conversion protocol according to the data format;
an initial credit assessment hierarchy for the provider is constructed based on the format conversion protocol and the credit assessment hybrid model.
In the present embodiment, the associated individual tag is represented as an evaluation-related data tag for each target provider evaluation index only;
in the present embodiment, the associated composite tag is represented as an evaluation-related data tag for a plurality of target provider evaluation indexes at the same time;
in the present embodiment, the model tag is represented as a tag for creating a credit evaluation model;
in the present embodiment, the relevant formatted data samples are represented as visual data samples of model tags for evaluating each target provider evaluation index;
in this embodiment, the service logic analysis is represented as performing a service-wise operation logic analysis on the data sample;
in the present embodiment, the credit behavior description variable is expressed as a theoretical variable range for evaluating each business behavior of credit data of each target provider evaluation index;
in the present embodiment, the target domain feature quantity is expressed as description vectors of macro economic index factors and micro risk index factors in their respective domains;
the beneficial effects of the technical scheme are as follows: the credit evaluation hybrid model of the suppliers is constructed to objectively and reasonably evaluate the credit based on the mapping feature vector of each target supplier evaluation index, thereby ensuring the evaluation of each target supplier evaluation index to be without omission and with high accuracy.
In one embodiment, the present embodiment further discloses a smart high-speed data storage system based on double-chain fusion, as shown in fig. 4, the system includes:
a construction module 401, configured to construct a light chain aggregation platform according to an enterprise chain and an industry chain;
the receiving module 402 is configured to perform user registration and verification through the light chain aggregation platform and receive privacy data to be stored uploaded by a user;
a selection module 403, configured to obtain a data amount of private data to be stored, and select a target data storage mode according to the data amount;
and the storage module 404 is used for processing and storing the privacy data to be stored in a target data storage mode.
The working principle and the beneficial effects of the above technical solution are described in the method claims, and are not repeated here.
Other embodiments of the disclosure will be apparent to those skilled in the art from consideration of the specification and practice of the disclosure disclosed herein. This application is intended to cover any adaptations, uses, or adaptations of the disclosure following, in general, the principles of the disclosure and including such departures from the present disclosure as come within known or customary practice within the art to which the disclosure pertains. It is intended that the specification and examples be considered as exemplary only, with a true scope and spirit of the disclosure being indicated by the following claims.
It is to be understood that the present disclosure is not limited to the precise arrangements and instrumentalities shown in the drawings, and that various modifications and changes may be effected without departing from the scope thereof. The scope of the present disclosure is limited only by the appended claims.
Claims (9)
1. The intelligent high-speed data storage method based on double-chain fusion is characterized by comprising the following steps of:
constructing a light chain polymerization platform according to the enterprise chain and the industry chain;
user registration and verification are carried out through a light chain aggregation platform, and privacy data to be stored, which are uploaded by a user, are received;
acquiring the data quantity of the private data to be stored, and selecting a target data storage mode according to the data quantity;
processing and storing the private data to be stored in a target data storage mode;
the construction of the light chain polymerization platform according to the enterprise chain and the industry chain comprises the following steps:
respectively acquiring respective data exchange criteria of an enterprise chain and an industry chain;
constructing an interactive decision model of the enterprise chain and the industry chain according to respective data exchange criteria of the enterprise chain and the industry chain;
acquiring platform design parameters and platform demand parameters;
constructing a light chain aggregation platform according to the platform design parameters and the platform demand parameters and combining an interactive decision model of the enterprise chain and the industry chain;
according to the data exchange criteria of the enterprise chain and the industry chain, an interactive decision model of the enterprise chain and the industry chain is constructed, specifically:
determining the interaction decision of the enterprise chain and the industry chain according to the data exchange criteria of the enterprise chain and the industry chain;
determining decision variables according to the interaction decision of the enterprise chain and the industry chain, and constructing an interaction decision model of the enterprise chain and the industry chain through a linear regression method based on the decision variables;
according to the platform design parameters and platform demand parameters, combining the interactive decision model of the enterprise chain and the industry chain to construct a light chain polymerization platform, specifically:
the platform is composed of a data source, a connection layer, an active layer, a logic layer and a service layer, wherein the data source provides bottom data support for the platform, the connection layer establishes connection between the data source and the active layer, so that the active layer can operate the data source, the active layer is generated through platform design parameters and platform demand parameters, operation support is provided for the whole platform system, the logic layer is generated through an interactive decision model of an enterprise chain and an industry chain and is used for carrying out logic decision on the data, and service is provided for a user through the service layer.
2. The smart high-speed data storage method based on double-chain fusion according to claim 1, wherein the steps of performing user registration and authentication through a light chain aggregation platform and receiving the privacy data to be stored uploaded by the user comprise:
receiving a registration request of a user through a light chain aggregation platform, and acquiring identity information, contact information, bank card information and face input information of the user according to the registration request;
the identity information, the contact information, the bank card information and the face input information of the user are stored in an associated mode;
receiving a real-time login request of a user, verifying the user according to stored identity information, and obtaining a verification result;
and if the verification result is that the verification is passed, activating an enterprise chain data uploading channel of the light chain aggregation platform and receiving the privacy data to be stored, which is uploaded by the user, according to the enterprise chain data uploading channel.
3. The smart high-speed data storage method based on double-chain fusion according to claim 1, wherein the obtaining the data volume of the private data to be stored and selecting the target data storage mode according to the data volume comprise:
evaluating the data quantity of the private data to be stored through a data evaluation component;
comparing the data quantity of the privacy data to be stored with a preset data quantity reference threshold value to obtain a comparison result;
if the comparison result shows that the data volume of the private data to be stored is smaller than or equal to the preset data volume reference threshold value, selecting the target data storage mode as a single-chain storage mode;
and if the comparison result shows that the data volume of the private data to be stored is larger than the preset data volume reference threshold value, selecting the target data storage mode as a double-chain storage mode.
4. The intelligent high-speed data storage method based on double-chain fusion according to claim 3, wherein the double-chain storage mode is a data storage mode of combining public chains and private chains;
the public chain is used for storing the hash value and the block header of the private chain;
the private chain is used for storing the complete private data to be stored.
5. The smart high-speed data storage method based on double-chain fusion according to claim 1, wherein the processing and storing the private data to be stored by the target data storage mode comprises the following steps:
determining the privacy degree of the private data to be stored, and selectively encrypting the data to be stored according to the privacy degree;
determining the data type of the private data to be stored, and selecting a data storage protocol for the private data to be stored according to the data type;
and storing the private data to be stored or the encrypted private data to be stored according to the data storage protocol.
6. The smart high-speed data storage method based on double-chain fusion according to claim 1, further comprising:
acquiring enterprise qualification information and business information of a plurality of suppliers, and screening out a second number of adapted target supplier evaluation indexes from the first number of supplier evaluation indexes according to the enterprise qualification information and the business information;
constructing an initial credit assessment system of the provider by using the second number of target provider assessment indexes;
acquiring process state data of historical business of each provider and training an initial credit evaluation system of the provider by using the process state data to acquire a target credit evaluation system of the provider;
determining enterprise business requirements and business project parameters according to privacy data to be stored, which are uploaded by a user;
selecting a first provider with an adaptive service from a plurality of providers according to enterprise service requirements and service item parameters;
carrying out credit evaluation on each first provider by using a target credit evaluation system of the provider to obtain an evaluation result;
and selecting a second provider with the reliability of the first three according to the evaluation result, and displaying and recommending enterprise information of the second provider through the light chain aggregation platform.
7. The intelligent high-speed data storage method based on double-chain fusion according to claim 6, further comprising:
determining a desired provider selected by a user, and generating an electronic contract according to the service contract detail content uploaded by the user;
uploading the electronic contract signing and signing to an electronic contract signing window of the light chain aggregation platform and enabling a user and an expected provider to sign up online;
generating a notarization report and a digital certificate according to the signed electronic contract;
and (5) carrying out uplink storage on the signed electronic contract and notarization report and the digital certificate.
8. The smart high-speed data storage method based on double-chain fusion according to claim 6, wherein constructing an initial credit assessment system of a vendor by using a second number of target vendor assessment indexes comprises:
acquiring an associated individual label and an associated composite label of each target provider evaluation index;
determining the corresponding relation between the associated individual label and the associated composite label of each target provider evaluation index;
selecting a target label from the associated individual label and the associated composite label of each target provider evaluation index according to the corresponding relation between the associated individual label and the associated composite label of each target provider evaluation index as a model label of the target provider evaluation index;
retrieving relevant formatted data samples of the model tags for each target provider evaluation index;
carrying out business logic analysis on the related formatted data samples of the model labels of the evaluation indexes of each target provider to obtain an analysis result;
determining credit description behavior variables of each target provider evaluation index according to the analysis result;
determining macro economic index factors and micro risk index factors of each target provider evaluation index based on credit descriptive behavior variables of the target provider evaluation index;
acquiring respective target field characteristic quantities of macro economic index factors and micro risk index factors of each target provider evaluation index;
calculating intersection of the target field feature quantities of the macro economic index factor and the micro risk index factor of each target provider evaluation index, and determining economic feature vectors, risk feature vectors and public feature vectors of each target provider evaluation index according to calculation results;
generating a feature mapping matrix according to the economic feature vector and the risk feature vector of each target provider evaluation index and the public feature vector;
constructing a credit evaluation mixed model of the provider according to the characteristic mapping matrix of each target provider evaluation index;
determining an input sample of the credit evaluation hybrid model, determining a data format according to the input sample, and selecting a format conversion protocol according to the data format;
an initial credit assessment hierarchy for the provider is constructed based on the format conversion protocol and the credit assessment hybrid model.
9. An intelligent high-speed data storage system based on double-chain fusion, which is characterized in that the system comprises:
the construction module is used for constructing a light chain polymerization platform according to the enterprise chain and the industry chain;
the receiving module is used for carrying out user registration and verification through the light chain aggregation platform and receiving the privacy data to be stored, which are uploaded by the user;
the selecting module is used for acquiring the data volume of the private data to be stored and selecting a target data storage mode according to the data volume;
the storage module is used for processing and storing the privacy data to be stored in a target data storage mode;
the construction of the light chain polymerization platform according to the enterprise chain and the industry chain comprises the following steps:
respectively acquiring respective data exchange criteria of an enterprise chain and an industry chain;
constructing an interactive decision model of the enterprise chain and the industry chain according to respective data exchange criteria of the enterprise chain and the industry chain;
acquiring platform design parameters and platform demand parameters;
constructing a light chain aggregation platform according to the platform design parameters and the platform demand parameters and combining an interactive decision model of the enterprise chain and the industry chain;
according to the data exchange criteria of the enterprise chain and the industry chain, an interactive decision model of the enterprise chain and the industry chain is constructed, specifically:
determining the interaction decision of the enterprise chain and the industry chain according to the data exchange criteria of the enterprise chain and the industry chain;
determining decision variables according to the interaction decision of the enterprise chain and the industry chain, and constructing an interaction decision model of the enterprise chain and the industry chain through a linear regression method based on the decision variables;
according to the platform design parameters and platform demand parameters, combining the interactive decision model of the enterprise chain and the industry chain to construct a light chain polymerization platform, specifically:
the platform is composed of a data source, a connection layer, an active layer, a logic layer and a service layer, wherein the data source provides bottom data support for the platform, the connection layer establishes connection between the data source and the active layer, so that the active layer can operate the data source, the active layer is generated through platform design parameters and platform demand parameters, operation support is provided for the whole platform system, the logic layer is generated through an interactive decision model of an enterprise chain and an industry chain and is used for carrying out logic decision on the data, and service is provided for a user through the service layer.
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