CN111127047A - Whole-process traceability supervision method for ticket payment flow three-chain cross verification product security - Google Patents
Whole-process traceability supervision method for ticket payment flow three-chain cross verification product security Download PDFInfo
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- CN111127047A CN111127047A CN202010020352.9A CN202010020352A CN111127047A CN 111127047 A CN111127047 A CN 111127047A CN 202010020352 A CN202010020352 A CN 202010020352A CN 111127047 A CN111127047 A CN 111127047A
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Abstract
The invention discloses a whole-process traceability supervision method for verifying product security by ticket payment flow three-chain cross, which comprises the steps of utilizing authoritative public credibility of electronic invoices, taking fund flow and logistics data of a product transaction/circulation process as cross verification means, establishing a collaborative data platform of a block-chained electronic invoice chain, a financial payment chain and a logistics supply chain, establishing a high-efficiency mode of longitudinal traceability and transverse interoperability of a three-chain whole-process big data cluster, establishing a cross verification calculation model of the three-chain whole-process big data cluster, extracting, analyzing and cross verifying consistency and authenticity of three-chain collaborative data by utilizing an artificial intelligence technology, establishing a security management and control algorithm model, carrying out traceability and cross verification on data cluster information, intelligently identifying potential illegal scenes, and forming a reliable three-chain collaborative block chain security management and control system. The invention utilizes the block chain technology to get through the data channel from point to network, thus realizing the penetrating safety monitoring and scientific and efficient management of food, medicine, dangerous products and the like.
Description
Technical Field
The invention belongs to the technical field of safety management, and particularly relates to a whole-process traceability supervision method for ticket payment flow three-chain cross verification of product safety.
Background
The quality safety and effective supervision of food, medicine and dangerous goods are great matters about the national civilization. However, the great safety accidents represented by melamine, the vinca vaccine and the Tianjin harbor dangerous goods explosion accident occur occasionally, and the life health and the life and property safety of the people are seriously damaged.
Although the national food and drug administration has adopted safety supervision measures such as 'requiring enterprises to install electronic eyes', 'requiring high-volume reward of reporting of employees in the industry' and the like, and the national emergency management department requires that dangerous goods have a regulation and regulation system with unified production planning and strict management, the products such as food, drugs, dangers and the like are large in scale and complex in system, and supervision of related departments and society is far from sufficient.
The information storage of the traditional anti-counterfeiting (trademark, bar code, two-dimensional code and the like) mode adopts a centralized database form, data is completely generated by an anti-counterfeiting company, the technical threshold and the counterfeiting cost are low, the stored information is easy to forge, copy and tamper, the authenticity of the data in each link of production, circulation, use and the like of products cannot be fundamentally distinguished, and therefore the effective prevention and accountability of the quality/safety accidents of foods, medicines and dangerous goods are difficult to realize.
The block chain is used as a technical tool, a centralized, non-tampering and traceable accounting mode is provided, and data tracing responsibility can be guaranteed by virtue of the technical advantages of data safety and non-tampering. If the multi-chain related data are subjected to cross validation, the consistency and the authenticity of the cooperative data can be distinguished, and the 'counterfeit removal and truthfulness' of the data on the chain can be really realized.
If the blockchain is used as a bottom layer technology, aiming at the quality safety and effective supervision problems of food, medicines and dangerous goods, a plurality of longitudinally-traceable and transversely-mutually-fused cooperative data chains are established, the consistency and the authenticity of the cooperative data on the chains are extracted, analyzed and cross verified by using an artificial intelligence technology, potential illegal scenes are intelligently identified, the effective supervision of the quality safety of the food, the medicines and the dangerous goods is realized, and the life health and the life and property safety of the nation are guaranteed.
Disclosure of Invention
Aiming at the defects of the prior art, the invention provides a whole-course traceability monitoring method for the safety of a ticket-payment flow three-chain cross verification product, which takes the information flow and the logistics data as cross verification means by means of the authoritative public credibility of an electronic invoice and utilizes the technical characteristics of centralization, non-tampering and traceability of a block chain to get through a data channel from a point to a network, so that the three-chain related data of the ticket-payment flow is longitudinally traceable and transversely mutually fused, and cross verification and artificial intelligence analysis are carried out, thereby realizing the penetrating safety monitoring and scientific and efficient management of food, medicines and dangerous goods.
A whole-course tracing supervision method for ticket payment flow three-chain cross validation product security comprises the following steps:
s1: building a block chain bottom layer data platform;
s2: three data sub-chains which are parallel and parallel are built by utilizing a block chain technology, an interface technology, a bar code, an RFID technology and an intelligent contract: the system comprises an electronic invoice chain, a financial payment chain and a logistics supply chain, wherein the electronic invoice chain, the financial payment chain and the logistics supply chain are respectively used for storing, inquiring, tracing and analyzing electronic invoice data information, payment data information and logistics supply information of products;
s3: three data sub-chains are transversely opened through a block chain bottom interface technology to form a three-chain collaborative data cluster with cross-chain fusion, and a three-chain collaborative data platform is established;
s4: establishing a cross validation and multi-party collaborative calculation model of the three-chain full-flow big data cluster, and extracting, analyzing and cross-comparing and validating the consistency and the authenticity of the three-chain collaborative data by using an artificial intelligence technology;
s5: a safety control algorithm model of three-chain full-process big data cluster information is built, full-process tracing and cross verification of the data cluster information are achieved, potential illegal scenes are identified intelligently, and a reliable three-chain cooperative block chain safety control system is built.
Further, in step S2, the electronic invoice data information includes information of unit, amount and time of invoice, the payment data information includes information of payment user, payment method, payment amount and payment time, and the logistics supply information includes logistics information such as storage, transportation, receipt and the like of product.
Further, the three data sub-chains established in step S2 are provided with a common node capable of only longitudinally reading data information in the sub-chains and a supervisory node capable of reading all data information on the three data sub-chains.
On the basis of the above scheme, the step S4 specifically includes the following steps:
s41: analyzing and processing the full-process big data of the three-chain evidence storage by using artificial intelligence and machine learning technology;
s42: establishing an automatic algorithm model, and refining data information related to the same object on the three chains;
s43: and automatically comparing the amount, time and place of the payment bill, the logistics bill and the electronic invoice, analyzing the logical cooperative consistency of the time stamp and the geographic stamp characteristics, and verifying the authenticity of the three-chain data through cross comparison.
On the basis of the above scheme, the step S5 specifically includes the following steps:
s51: constructing a safety control algorithm model for the product and the production information;
s52: the basic production expenditure condition of the product in the production process is mastered through an invoice chain, and the quality and safety of the product are controlled from the source;
s53: the storage and transportation conditions of the products are monitored through a logistics supply chain, and the temperature and time factors of the transportation of the products are comprehensively and timely monitored;
s54: all payment information is combined through a financial payment chain and an invoice chain, and the circulation mode of assets is mastered;
s55: through three-chain collaborative cross-comparison verification, the reality and the effectiveness of data are ensured, and the whole-process traceability of asset information is realized;
s56: the weak part is intelligently identified and managed through artificial intelligence and a big data module, the source of safety risks is timely reminded, potential illegal scenes are intelligently identified, and penetrating safety supervision on food, medicines, dangerous goods and the like is realized.
The invention has the beneficial effects that:
1. solving the data barrier of the ticket/payment/stream three-chain, and getting through the digital channel of 'point-to-network';
2. the problem of low single-chain reliability is solved by using the cross validation of the ticket/payment/flow triple-chain;
3. the illegal scene and the reasonable scene are intelligently identified, and the penetrating safety monitoring of food/medicine/dangerous products is realized;
4. the current situation that food, medicine, dangerous goods and the like lack of effective supervision is changed;
5. plays an important role in promoting the controllability and traceability of products.
Drawings
FIG. 1 is a schematic diagram of a whole-course tracing and supervision method for three-chain cross validation of product security;
FIG. 2 is a schematic view of an electronic invoice chain;
FIG. 3 is a schematic view of a payment information chain;
FIG. 4 is a schematic view of a logistics information chain;
FIG. 5 is a block chain and artificial intelligence analysis, traceability and surveillance platform.
Detailed Description
As shown in fig. 1, a whole-process traceability monitoring method for three-chain cross validation of product security in ticket payment flow is characterized by comprising the following steps:
s1: building a block chain bottom layer data platform;
s2: three data sub-chains which are parallel and parallel are built by utilizing a block chain technology, an interface technology, a bar code, an RFID technology and an intelligent contract: the system comprises an electronic invoice chain, a financial payment chain and a logistics supply chain, wherein the electronic invoice chain, the financial payment chain and the logistics supply chain are respectively used for storing, inquiring, tracing and analyzing electronic invoice data information, payment data information and logistics supply information of products;
s3: three data sub-chains are transversely opened through a block chain bottom interface technology to form a three-chain collaborative data cluster with cross-chain fusion, and a three-chain collaborative data platform is established;
s4: establishing a cross validation and multi-party collaborative calculation model of the three-chain full-flow big data cluster, and extracting, analyzing and cross-comparing and validating the consistency and the authenticity of the three-chain collaborative data by using an artificial intelligence technology;
s5: a safety control algorithm model of three-chain full-process big data cluster information is built, full-process tracing and cross verification of the data cluster information are achieved, potential illegal scenes are identified intelligently, and a reliable three-chain cooperative block chain safety control system is built.
As shown in fig. 2, 3 and 4, in step S2, the electronic invoice data information includes information of unit, amount and time of invoice, the payment data information includes information of payment user, payment method, payment amount and payment time, and the logistics supply information includes storage and transportation logistics information of product.
The three data sub-chains established in the step S2 are provided with a common node capable of only longitudinally reading data information in the sub-chain and a supervisory node capable of reading all data information on the three data sub-chains.
Each subchain realizes accurate storage, query, tracing and analysis of respective longitudinal data; the sub-chains are isolated from each other, and a common node can only read the data of the sub-chain where the node is located, but cannot read the data and transactions of other sub-chains, so that the privacy and the safety of the data are guaranteed.
And utilizing a cross-chain technology to transversely open the three-chain data to form a cross-chain fused three-chain cooperative data group.
And (3) getting through a data channel from a point to a network, and realizing a free high-efficiency mode of longitudinal traceability and transverse mutual fusion of the three-chain full-flow big data cluster.
As shown in fig. 5, the step S4 specifically includes the following steps:
s41: analyzing and processing the full-process big data of the three-chain evidence storage by using artificial intelligence and machine learning technology;
s42: establishing an automatic algorithm model, and refining data information related to the same object on the three chains;
s43: and automatically comparing the amount, time and place of the payment bill, the logistics bill and the electronic invoice, analyzing the logical cooperative consistency of the time stamp and the geographic stamp characteristics, and verifying the authenticity of the three-chain data through cross comparison.
The authenticity of the cochain data is guaranteed, and an ecological chain for connecting production, logistics, sales and after-sale full life cycle is opened.
Further, the step S5 specifically includes the following steps:
s51: constructing a safety control algorithm model for the product and the production information;
s52: the basic production expenditure condition of the product in the production process is mastered through an invoice chain, and the quality and safety of the product are controlled from the source;
s53: the storage and transportation conditions of the products are monitored through a logistics supply chain, and the temperature and time factors of the transportation of the products are comprehensively and timely monitored;
s54: all payment information is combined through a financial payment chain and an invoice chain, and the circulation mode of assets is mastered;
s55: through three-chain collaborative cross-comparison verification, the reality and the effectiveness of data are ensured, and the whole-process traceability of asset information is realized;
s56: the weak part is intelligently identified and managed through artificial intelligence and a big data module, the source of safety risks is timely reminded, potential illegal scenes are intelligently identified, and penetrating safety supervision on food, medicines, dangerous goods and the like is realized.
And when problems occur, the problem links can be quickly positioned, and the tasks are quickly traced and the bugs are repaired.
The invention uses the authority credibility of the electronic invoice, takes the fund flow and logistics data of the transaction/circulation process of food/medicine/dangerous products as a cross validation means, establishes a collaborative data platform of a block chain electronic invoice chain, a financial payment chain and a logistics supply chain, establishes a high-efficiency mode of longitudinal traceability and transverse interoperability of a ticket/payment/flow three-chain full-flow big data cluster, establishes a cross validation calculation model of the ticket/payment/flow three-chain full-flow big data cluster, extracts, analyzes and cross validates the consistency and the authenticity of the three-chain collaborative data by using an artificial intelligence technology, establishes a safety control algorithm model, conducts traceability and cross validation on data cluster information, intelligently identifies potential illegal scenes, and forms a reliable three-chain collaborative block chain safety control system. The invention utilizes the block chain technology to get through the data channel from point to network, thus realizing the penetrating safety monitoring and scientific and efficient management of food, medicine, dangerous products and the like.
It will be appreciated that although embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that changes, modifications, substitutions and alterations can be made in these embodiments without departing from the principles and spirit of the invention, the scope of which is defined in the appended claims and their equivalents.
Claims (5)
1. A whole-course tracing supervision method for ticket payment flow three-chain cross validation product security is characterized by comprising the following steps:
s1: building a block chain bottom layer data platform;
s2: three data sub-chains which are parallel and parallel are built by utilizing a block chain technology, an interface technology, a bar code, an RFID technology and an intelligent contract: the system comprises an electronic invoice chain, a financial payment chain and a logistics supply chain, wherein the electronic invoice chain, the financial payment chain and the logistics supply chain are respectively used for storing, inquiring, tracing and analyzing electronic invoice data information, payment data information and logistics supply information of products;
s3: three data sub-chains are transversely opened through a block chain bottom interface technology to form a three-chain collaborative data cluster with cross-chain fusion, and a three-chain collaborative data platform is established;
s4: establishing a cross validation and multi-party collaborative calculation model of the three-chain full-flow big data cluster, and extracting, analyzing and cross-comparing and validating the consistency and the authenticity of the three-chain collaborative data by using an artificial intelligence technology;
s5: a safety control algorithm model of three-chain full-process big data cluster information is built, full-process tracing and cross verification of the data cluster information are achieved, potential illegal scenes are identified intelligently, and a reliable three-chain cooperative block chain safety control system is built.
2. The method for supervising the whole tracing of the ticket payment stream three-chain cross validation product security as claimed in claim 1, wherein in step S2, the electronic invoice data information includes information of unit, amount and time of invoice, the payment data information includes information of payment user, payment method, payment amount and payment time, and the logistics supply information includes logistics information of storage, transportation, sign-off and the like of product.
3. The method for supervising the whole tracing of the ticket payment flow three-chain cross validation product security as claimed in claim 1, wherein the three data sub-chains established in step S2 are provided with a common node capable of only longitudinally reading the data information in the sub-chains and a supervising node capable of reading all the data information on the three data sub-chains.
4. The method for full-process traceability supervision of ticket payment flow triple-chain cross validation product security as claimed in claim 1, wherein said step S4 specifically comprises the following steps:
s41: analyzing and processing the full-process big data of the three-chain evidence storage by using artificial intelligence and machine learning technology;
s42: establishing an automatic algorithm model, and refining data information related to the same object on the three chains;
s43: and automatically comparing the amount, time and place of the payment bill, the logistics bill and the electronic invoice, analyzing the logical cooperative consistency of the time stamp and the geographic stamp characteristics, and verifying the authenticity of the three-chain data through cross comparison.
5. The method for full-process traceability supervision of ticket payment flow triple-chain cross validation product security as claimed in claim 1, wherein said step S5 specifically comprises the following steps:
s51: constructing a safety control algorithm model for the product and the production information;
s52: the basic production expenditure condition of the product in the production process is mastered through an invoice chain, and the quality and safety of the product are controlled from the source;
s53: the storage and transportation conditions of the products are monitored through a logistics supply chain, and the temperature and time factors of the transportation of the products are comprehensively and timely monitored;
s54: all payment information is combined through a financial payment chain and an invoice chain, and the circulation mode of assets is mastered;
s55: through three-chain collaborative cross-comparison verification, the reality and the effectiveness of data are ensured, and the whole-process traceability of asset information is realized;
s56: the weak part is intelligently identified and managed through artificial intelligence and a big data module, the source of safety risks is timely reminded, potential illegal scenes are intelligently identified, and penetrating safety supervision on food, medicines, dangerous goods and the like is realized.
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