CN112131306A - Object recognition method, device and storage medium - Google Patents
Object recognition method, device and storage medium Download PDFInfo
- Publication number
- CN112131306A CN112131306A CN202010658847.4A CN202010658847A CN112131306A CN 112131306 A CN112131306 A CN 112131306A CN 202010658847 A CN202010658847 A CN 202010658847A CN 112131306 A CN112131306 A CN 112131306A
- Authority
- CN
- China
- Prior art keywords
- information
- evaluation
- transaction
- block chain
- economic
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Pending
Links
Images
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
- G06F16/20—Information retrieval; Database structures therefor; File system structures therefor of structured data, e.g. relational data
- G06F16/27—Replication, distribution or synchronisation of data between databases or within a distributed database system; Distributed database system architectures therefor
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F21/00—Security arrangements for protecting computers, components thereof, programs or data against unauthorised activity
- G06F21/60—Protecting data
- G06F21/64—Protecting data integrity, e.g. using checksums, certificates or signatures
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q20/00—Payment architectures, schemes or protocols
- G06Q20/38—Payment protocols; Details thereof
- G06Q20/382—Payment protocols; Details thereof insuring higher security of transaction
- G06Q20/3829—Payment protocols; Details thereof insuring higher security of transaction involving key management
Landscapes
- Engineering & Computer Science (AREA)
- Theoretical Computer Science (AREA)
- Physics & Mathematics (AREA)
- Computer Security & Cryptography (AREA)
- Business, Economics & Management (AREA)
- General Physics & Mathematics (AREA)
- Accounting & Taxation (AREA)
- Databases & Information Systems (AREA)
- General Engineering & Computer Science (AREA)
- Data Mining & Analysis (AREA)
- General Health & Medical Sciences (AREA)
- Computing Systems (AREA)
- Computer Hardware Design (AREA)
- Software Systems (AREA)
- Bioethics (AREA)
- Health & Medical Sciences (AREA)
- Finance (AREA)
- Strategic Management (AREA)
- General Business, Economics & Management (AREA)
- Management, Administration, Business Operations System, And Electronic Commerce (AREA)
Abstract
The invention provides an object identification method, device and storage medium, the method comprises: respectively acquiring authorization information of each candidate, and acquiring economic information of each candidate according to each authorization information; wherein the economic information comprises at least one of the following information of the corresponding candidate in the relevant period: family economic information, social security information, bank flow information, network platform bill information, shopping platform order information and house property information; respectively carrying out integrated calculation on each economic information to obtain the evaluation information of each candidate; and generating a first evaluation transaction according to each evaluation information and sending the first evaluation transaction to a block chain network so that block chain nodes execute the first evaluation transaction through a lean-right contract, determining a plurality of lean-right objects according to each evaluation information and a preset evaluation strategy, and recording the objects on the block chain. The invention ensures that the identification of the object is not influenced by any false information and unfair human factors.
Description
Technical Field
The present application relates to the field of internet technologies, and in particular, to a method, device, and storage medium for object recognition.
Background
In the current poverty-relieving work of the society, the screening of poverty-relieving objects is a difficult point, on one hand, the problems of dishonest candidates, false information submission and the like exist, and on the other hand, various factors cause unfairness of artificial selection, for example, the situation that a richter can occupy the poverty of poverty-relieving is frequently seen.
Disclosure of Invention
In view of the above-mentioned drawbacks and deficiencies of the prior art, it is desirable to provide an object identification method, apparatus and storage medium that ensure the accuracy and fairness of lean object identification.
In a first aspect, the present invention provides an object identification method suitable for a big data application end, where a block chain is configured with a lean-right contract, and the method includes:
respectively acquiring authorization information of each candidate, and acquiring economic information of each candidate according to each authorization information; wherein the economic information comprises at least one of the following information of the corresponding candidate in the relevant period: family economic information, social security information, bank flow information, network platform bill information, shopping platform order information and house property information;
respectively carrying out integrated calculation on each economic information to obtain the evaluation information of each candidate;
and generating a first evaluation transaction according to each evaluation information and sending the first evaluation transaction to a block chain network so that block chain nodes execute the first evaluation transaction through a lean-right contract, determining a plurality of lean-right objects according to each evaluation information and a preset evaluation strategy, and recording the objects on the block chain.
In a second aspect, the present invention provides an object identification method suitable for a blockchain node, where a lean-right contract is configured on a blockchain, the method including:
and executing a first evaluation transaction through the lean-right contract, determining a plurality of lean-right objects according to each evaluation information and a preset evaluation strategy, and recording the objects on the block chain.
The first evaluation transaction is generated according to each evaluation information after acquiring the evaluation information of each candidate by the big data application end respectively acquiring the authorization information of each candidate, acquiring the economic information of each candidate according to each authorization information, and performing integration calculation on each economic information respectively;
the economic information includes at least one of the following information of the corresponding candidate within the relevant time frame: family economic information, social security information, bank flow information, network platform bill information, shopping platform order information and house property information.
In a third aspect, the present invention also provides an apparatus comprising one or more processors and a memory, wherein the memory contains instructions executable by the one or more processors to cause the one or more processors to perform a lean object identification method provided according to embodiments of the present invention.
In a fourth aspect, the present invention also provides a storage medium storing a computer program that causes a computer to execute the object recognition method provided according to the embodiments of the present invention.
According to the object identification method, the device and the storage medium provided by the embodiments of the invention, the economic information of the candidate is obtained by the big data application end, the integrated calculation is carried out, the calculated evaluation information is sent to the block chain network, and the lean-right contract is determined by the lean-right contract deployed on the block chain according to the evaluation information, so that the identification of the lean-right object is not influenced by any false information and unfair human factors, and the accuracy and the fairness are ensured;
the object identification method, the device and the storage medium provided by some embodiments of the present invention further ensure that the calculation of the big data application end is verifiable on the premise of not revealing the privacy of the candidate by storing the encrypted economic information on the block chain for the supervision authority to verify, thereby further ensuring the fairness;
the object identification method, the device and the storage medium provided by some embodiments of the present invention further improve fairness by configuring a notice period for receiving a report on a block chain and performing calculation and selection again according to the report information;
the object identification method, the device and the storage medium provided by some embodiments of the invention further ensure the relief right of the person to be reported by configuring and receiving the public period of the person to be reported submitting the certification material on the blockchain, and carrying out calculation and evaluation again according to the certification material.
Drawings
Other features, objects and advantages of the present application will become more apparent upon reading of the following detailed description of non-limiting embodiments thereof, made with reference to the accompanying drawings in which:
fig. 1 is a flowchart of an object identification method according to an embodiment of the present invention.
FIG. 2 is a flow diagram of a preferred embodiment of the method shown in FIG. 1.
FIG. 3 is a flow diagram of a preferred embodiment of the method shown in FIG. 1.
FIG. 4 is a flow chart of a preferred embodiment of the method shown in FIG. 3.
Fig. 5 is a flowchart of another object identification method according to an embodiment of the present invention.
FIG. 6 is a flow chart of a preferred embodiment of the method shown in FIG. 5.
FIG. 7 is a flow chart of a preferred embodiment of the method shown in FIG. 5.
FIG. 8 is a flow chart of a preferred embodiment of the method shown in FIG. 7.
Fig. 9 is a schematic structural diagram of an apparatus according to an embodiment of the present invention.
Detailed Description
The present application will be described in further detail with reference to the following drawings and examples. It is to be understood that the specific embodiments described herein are merely illustrative of the relevant invention and not restrictive of the invention. It should be noted that, for convenience of description, only the portions related to the present invention are shown in the drawings.
It should be noted that the embodiments and features of the embodiments in the present application may be combined with each other without conflict. The present application will be described in detail below with reference to the embodiments with reference to the attached drawings.
Fig. 1 is a flowchart of an object identification method according to an embodiment of the present invention.
As shown in fig. 1, in this embodiment, the present invention provides an object identification method suitable for a big data application, where a block chain is configured with a lean-right contract, and the method includes:
s11: respectively acquiring authorization information of each candidate, and acquiring economic information of each candidate according to each authorization information; wherein the economic information comprises at least one of the following information of the corresponding candidate in the relevant period: family economic information, social security information, bank flow information, network platform bill information, shopping platform order information and house property information;
s13: respectively carrying out integrated calculation on each economic information to obtain the evaluation information of each candidate;
s15: and generating a first evaluation transaction according to each evaluation information and sending the first evaluation transaction to a block chain network so that block chain nodes execute the first evaluation transaction through a lean-right contract, determining a plurality of lean-right objects according to each evaluation information and a preset evaluation strategy, and recording the objects on the block chain.
The method is exemplarily described below by taking the determination of poverty in class a of a university as an example, and in further embodiments, the method can also be applied to different poverty relief scenes such as precise poverty relief.
Each student in class a submits authorization information to the big data application, where the authorization information may include different authorization data respectively specified by several organizations (e.g., civil departments, banks, network platforms, shopping platforms, hostage bureaus, etc.), or may include only a portion of the authorization data (some students may be unwilling to authorize to provide certain information for various reasons).
In step S11, after acquiring the authorization information of each student in class a, the big data application acquires economic information of each student in class a according to each authorization information, for example, family economic information, bank flow information of each bank, campus card flow information, order information of each takeout platform, order information of each shopping platform, WeChat Payment Bill information, Paibao Bill information, house property information under personal name, and so on.
In step S13, the big data application end integrates and calculates the economic information of each student obtained in step S11, and generates the evaluation information for directly evaluating contracts deployed on the block chain according to a preset evaluation policy;
in step S15, the big data application generates a first election transaction tx1 according to each piece of election information calculated in step S13, and sends tx1 to the blockchain network.
After receiving the tx1, the blockchain nodes broadcast, pack and execute tx1 through the lean-right contract, determine a plurality of lean-right students of class A according to various evaluation information submitted by tx1 and preset evaluation strategies, and record the lean-right students on the blockchain.
In the embodiment, the economic information of the candidate is obtained by the big data application end and is integrated and calculated, the calculated evaluation information is sent to the block chain network, and the poverty-alleviation contract deployed on the block chain determines the poverty-alleviation contract according to the evaluation information, so that the identification of the poverty-alleviation object is not influenced by any false information and unfair human factors, and the accuracy and the fairness are ensured.
FIG. 2 is a flow diagram of a preferred embodiment of the method shown in FIG. 1. As shown in fig. 2, in a preferred embodiment, the method further comprises:
s161: encrypting each economic information through a public key of a supervision organization to generate economic evidence storage information;
s163: and generating evaluation, selection and deposit evidence transaction according to the economic deposit evidence information and sending the evaluation, selection and deposit evidence transaction to the block chain network so that the block chain nodes execute the evaluation, selection and deposit evidence transaction and deposit the economic deposit evidence information on the block chain.
The economic evidence information is used for the supervision institution to acquire and decrypt from the block chain so as to verify whether the calculation of each piece of evaluation information is correct or not.
Specifically, in the scheme shown in fig. 1, when a lawless person invades the big data application end to tamper data, or a worker maintaining the big data application end to tamper data, the problem of unfair selection can be caused.
For the problem, in this embodiment, after acquiring the economic information of each candidate, the big data application encrypts each economic information through the public key of the supervisory authority to generate economic deposit evidence information, generates a scoring deposit evidence transaction tx2 according to the economic deposit evidence information, and sends the scoring deposit evidence transaction tx2 to the blockchain network.
After receiving tx2, the blockchain node broadcasts, packages and executes tx2, and stores the economic certificate information on the blockchain.
And after obtaining the economic evidence storage information from the block chain, the monitoring mechanism obtains each economic information through decryption of a private key, and then verifies whether the calculation of each evaluation information is correct or not according to each economic information.
It should be noted that, in this embodiment, each piece of economic information of a candidate is signed by a corresponding organization, and if an illegal person tampers with one or more pieces of economic information, the economic information cannot pass signature verification.
The embodiment further stores the encrypted economic information on the block chain for verification by a supervision organization, so that the calculation of the big data application end is guaranteed to be verifiable on the premise of not revealing the privacy of the candidate, and the fairness is further guaranteed.
FIG. 3 is a flow diagram of a preferred embodiment of the method shown in FIG. 1. As shown in fig. 3, in a preferred embodiment, the lean reduction contract is further configured to execute a reporting transaction within a first public period after the execution of the first evaluation transaction, and record reporting information for reporting the first candidate on the blockchain; the method further comprises the following steps:
s171: acquiring reporting information recorded on the block chain, and recalculating first evaluation information of the first candidate according to the reporting information;
s173: and generating a second evaluation transaction according to the first evaluation information and the evaluation information of other candidates, and sending the second evaluation transaction to a block chain network, so that block chain nodes execute the second evaluation transaction through the lean-care contract, re-determine a plurality of lean-care objects and record the second evaluation transaction on the block chain.
Specifically, in the scenario shown in fig. 1 or fig. 2, when a candidate has drilled the vulnerability of the selection mechanism, for example, a student with a wealthy family rarely uses a campus card or any other electronic payment channel and basically only uses cash, or the student uses only a bank card and an account number falsely using the identity of another person, the student may be mistakenly selected as a poor student.
In view of this problem, in this embodiment, after the first evaluation transaction is executed to determine a plurality of lean targets in the lean contract, a first public period of a predetermined duration is recorded on the blockchain, and in the first public period, anyone can submit a report message by sending a report transaction (after the first public period is exceeded, the report transaction will fail to be executed).
For example, after the user side of the first user sends a reporting transaction tx3 reporting a student B, the poverty relief contract execution tx3 succeeds, and reporting information of the first reporting transaction B is recorded on the blockchain;
when the big data application end monitors the reporting transaction tx3 on the blockchain, after the reporting information is obtained, the first evaluation information of the second is recalculated according to the reporting information (it needs to be stated that the big data application end can automatically process certain reporting information which can be confirmed to be valid or invalid without doubt, and the reporting information which can not be directly and automatically processed by other big data application ends needs to be processed by manual intervention first and then is calculated by the big data application end), and then the second evaluation transaction tx4 is generated and sent according to the first evaluation information and each evaluation information of other candidates.
The process of the blockchain node to execute tx4 is the same as that of tx1, and is not described in detail.
The embodiment further improves the fairness by configuring the announcement period for receiving the report on the block chain and carrying out calculation and evaluation again according to the report information.
FIG. 4 is a flow chart of a preferred embodiment of the method shown in FIG. 3. In a preferred embodiment, as shown in FIG. 4, the lean-right contract is further configured to execute the certification material submission transaction within a second public period after the execution of the reporting transaction, and to record the certification material submitted by the first candidate on the blockchain; the method further comprises the following steps:
s181: obtaining a certification material recorded on the block chain, and recalculating second evaluation information of the first candidate according to the certification material;
s183: and generating a third evaluation transaction according to the second evaluation information and the evaluation information of other candidates, and sending the third evaluation transaction to the block chain network so that the block chain nodes can execute the evaluation contract through the lean-care contract, re-determine a plurality of lean-care objects and record the objects on the block chain.
Specifically, the principle of the relief mechanism shown in fig. 4 is the same as that of the reporting mechanism shown in fig. 3, and the difference is only that the mechanism shown in fig. 3 is used for reporting and the mechanism shown in fig. 4 is used for relief, and the detailed process is not repeated.
The embodiment further ensures the relief right of the person to be reported by configuring and receiving the public period of the submitted proving material of the person to be reported on the blockchain and recalculating and selecting according to the proving material.
Fig. 5 is a flowchart of another object identification method according to an embodiment of the present invention. The method illustrated in fig. 5 may be performed in conjunction with the method illustrated in fig. 1.
As shown in fig. 5, in this embodiment, the present invention further provides an object identification method applied to a blockchain node, where a lean-right contract is configured on a blockchain, the method including:
s21: and executing a first evaluation transaction through the lean-right contract, determining a plurality of lean-right objects according to each evaluation information and a preset evaluation strategy, and recording the objects on the block chain.
The first evaluation transaction is generated according to each evaluation information after acquiring the evaluation information of each candidate by the big data application end respectively acquiring the authorization information of each candidate, acquiring the economic information of each candidate according to each authorization information, and performing integration calculation on each economic information respectively;
the economic information includes at least one of the following information of the corresponding candidate within the relevant time frame: family economic information, social security information, bank flow information, network platform bill information, shopping platform order information and house property information.
The principle of the method shown in fig. 5 is the same as that of the method shown in fig. 1, and the description thereof is omitted.
FIG. 6 is a flow chart of a preferred embodiment of the method shown in FIG. 5. The method illustrated in fig. 6 may be performed in conjunction with the method illustrated in fig. 2.
As shown in fig. 6, in a preferred embodiment, the method further includes:
s23: and executing evaluation, selection and certificate storage transaction, and storing the economic certificate storage information on the block chain.
After the big data application end encrypts each economic information through a public key of a supervisory organization to generate economic deposit certificate information, the evaluation deposit certificate transaction is generated according to the economic deposit certificate information;
the economic evidence information is used for the supervision agency to acquire and decrypt from the block chain so as to verify whether the calculation of each piece of evaluation information is correct.
The principle of the method shown in fig. 6 is the same as that of the method shown in fig. 2, and the description thereof is omitted.
FIG. 7 is a flow chart of a preferred embodiment of the method shown in FIG. 5. The method illustrated in fig. 7 may be performed in conjunction with the method illustrated in fig. 3.
As shown in fig. 7, in a preferred embodiment, the method further includes:
s25: in a first public period after the first evaluation transaction is executed, the reporting transaction is executed through a lean-right contract, reporting information of a first candidate is recorded on a block chain so that a big data application end can obtain the reporting information, the first evaluation information of the first candidate is recalculated according to the reporting information, a second evaluation transaction is generated according to the first evaluation information and each piece of evaluation information of other candidates, and the second evaluation transaction is sent to the block chain network;
s26: and executing a second evaluation transaction through the lean-right contract, and re-determining a plurality of lean-right objects and recording the objects on the blockchain.
The principle of the method shown in fig. 7 is the same as that of the method shown in fig. 3, and the description thereof is omitted.
FIG. 8 is a flow chart of a preferred embodiment of the method shown in FIG. 7. The method illustrated in fig. 8 may be performed in conjunction with the method illustrated in fig. 4.
As shown in fig. 8, in a preferred embodiment, the method further includes:
s27: in a second public period after the reporting transaction is executed, executing a certification material submitting transaction through a lean-right contract, recording the certification material submitted by the first candidate on a block chain so that a big data application end can obtain the certification material, recalculating second evaluation information of the first candidate according to the certification material, generating a third evaluation transaction according to the second evaluation information and each evaluation information of other candidates, and sending the third evaluation transaction to a block chain network;
s28: and executing a third evaluation transaction through the lean-right contract, and re-determining a plurality of lean-right objects and recording the objects on the blockchain.
The principle of the method shown in fig. 8 is the same as that of the method shown in fig. 4, and the description thereof is omitted.
Fig. 9 is a schematic structural diagram of an apparatus according to an embodiment of the present invention.
As shown in fig. 9, as another aspect, the present application also provides an apparatus 900 including one or more Central Processing Units (CPUs) 901 that can perform various appropriate actions and processes according to a program stored in a Read Only Memory (ROM)902 or a program loaded from a storage section 908 into a Random Access Memory (RAM) 903. In the RAM903, various programs and data necessary for the operation of the apparatus 900 are also stored. The CPU901, ROM902, and RAM903 are connected to each other via a bus 904. An input/output (I/O) interface 905 is also connected to bus 904.
The following components are connected to the I/O interface 905: an input portion 906 including a keyboard, a mouse, and the like; an output section 907 including components such as a Cathode Ray Tube (CRT), a Liquid Crystal Display (LCD), and the like, and a speaker; a storage portion 908 including a hard disk and the like; and a communication section 909 including a network interface card such as a LAN card, a modem, or the like. The communication section 909 performs communication processing via a network such as the internet. The drive 910 is also connected to the I/O interface 905 as necessary. A removable medium 911 such as a magnetic disk, an optical disk, a magneto-optical disk, a semiconductor memory, or the like is mounted on the drive 910 as necessary, so that a computer program read out therefrom is mounted into the storage section 908 as necessary.
In particular, according to an embodiment of the present disclosure, the method described in any of the above embodiments may be implemented as a computer software program. For example, embodiments of the present disclosure include a computer program product comprising a computer program tangibly embodied on a machine-readable medium, the computer program comprising program code for performing any of the methods described above. In such an embodiment, the computer program may be downloaded and installed from a network through the communication section 909, and/or installed from the removable medium 911.
As yet another aspect, the present application also provides a computer-readable storage medium, which may be the computer-readable storage medium included in the apparatus of the above-described embodiment; or it may be a separate computer readable storage medium not incorporated into the device. The computer readable storage medium stores one or more programs for use by one or more processors in performing the methods described in the present application.
The flowchart and block diagrams in the figures illustrate the architecture, functionality, and operation of possible implementations of systems, methods and computer program products according to various embodiments of the present invention. In this regard, each block in the flowchart or block diagrams may represent a module, segment, or portion of code, which comprises one or more executable instructions for implementing the specified logical function(s). It should also be noted that, in some alternative implementations, the functions noted in the block may occur out of the order noted in the figures. For example, two blocks shown in succession may, in fact, be executed substantially concurrently, or the blocks may sometimes be executed in the reverse order, depending upon the functionality involved. It will also be noted that each block of the block diagrams and/or flowchart illustration, and combinations of blocks in the block diagrams and/or flowchart illustration, can be implemented by special purpose hardware-based systems which perform the specified functions or acts, or combinations of special purpose hardware and computer instructions.
The units or modules described in the embodiments of the present application may be implemented by software or hardware. The described units or modules may also be provided in a processor, for example, each unit may be a software program provided in a computer or a mobile intelligent device, or may be a separately configured hardware device. Wherein the designation of a unit or module does not in some way constitute a limitation of the unit or module itself.
The above description is only a preferred embodiment of the application and is illustrative of the principles of the technology employed. It will be appreciated by those skilled in the art that the scope of the invention herein disclosed is not limited to the particular combination of features described above, but also encompasses other arrangements formed by any combination of the above features or their equivalents without departing from the spirit of the present application. For example, the above features may be replaced with (but not limited to) features having similar functions disclosed in the present application.
Claims (10)
1. An object identification method is characterized in that a block chain is provided with a lean-right contract, the method is suitable for a big data application end, and the method comprises the following steps:
respectively acquiring authorization information of each candidate, and acquiring economic information of each candidate according to the authorization information; wherein the economic information comprises at least one of the following information of the corresponding candidate within the relevant time limit: family economic information, social security information, bank flow information, network platform bill information, shopping platform order information and house property information;
respectively carrying out integrated calculation on each economic information to obtain the evaluation information of each candidate;
and generating a first evaluation transaction according to the evaluation information and sending the first evaluation transaction to a block chain network so that block chain nodes execute the first evaluation transaction through the lean-care contract, determining a plurality of lean-care objects according to the evaluation information and a preset evaluation strategy, and recording the objects on the block chain.
2. The method of claim 1, further comprising:
encrypting each economic information through a public key of a supervision organization to generate economic evidence storage information;
generating evaluation, selection and deposit evidence transaction according to the economic deposit evidence information and sending the evaluation, selection and deposit evidence transaction to a block chain network so that block chain nodes execute the evaluation, selection and deposit evidence transaction and store the economic deposit evidence information on a block chain;
the economic evidence information is used for the supervision agency to acquire and decrypt from the blockchain so as to verify whether the calculation of each piece of evaluation information is correct or not.
3. The method of claim 1 or 2, wherein the lean contract is further used for executing a reporting transaction within a first public period after executing the first evaluation transaction, and reporting information of a first candidate is recorded on a blockchain;
the method further comprises the following steps:
acquiring the reporting information recorded on the block chain, and recalculating first evaluation information of the first candidate according to the reporting information;
and generating a second evaluation transaction according to the first evaluation information and the evaluation information of other candidates, and sending the second evaluation transaction to a block chain network, so that block chain nodes execute the lean-care contract through the lean-care contract, re-determine a plurality of lean-care objects and record the objects on the block chain.
4. The method of claim 3, wherein the lean contract is further used to execute a certification material submission transaction within a second public period after the reporting transaction is executed, recording the certification material submitted by the first candidate on a blockchain;
the method further comprises the following steps:
obtaining the certification material recorded on the blockchain, and recalculating second evaluation information of the first candidate according to the certification material;
and generating a third evaluation transaction according to the second evaluation information and the evaluation information of other candidates, and sending the third evaluation transaction to a block chain network, so that block chain nodes execute the lean-care contract, re-determine a plurality of lean-care objects and record the objects on the block chain.
5. An object identification method, wherein a block chain is configured with a lean-right contract, the method is applied to a block chain node, and the method comprises the following steps:
executing a first evaluation transaction through the lean-right contract, determining a plurality of lean-right objects according to each evaluation information and a preset evaluation strategy, and recording the lean-right objects on a block chain;
the first selection transaction is generated according to the selection information of the candidates after acquiring the authorization information of the candidates by a big data application end, acquiring the economic information of the candidates according to the authorization information, performing integrated calculation on the economic information respectively, and acquiring the selection information of the candidates;
the economic information includes at least one of the following information of the corresponding candidate within the relevant time limit: family economic information, social security information, bank flow information, network platform bill information, shopping platform order information and house property information.
6. The method of claim 5, further comprising:
performing evaluation, selection and deposit certificate transaction, and depositing the economic deposit certificate information on a block chain;
the big data application end encrypts each economic information through a public key of a monitoring mechanism to generate economic evidence storing information, and then generates the economic evidence storing transaction according to the economic evidence storing information;
the economic evidence information is used for the supervision agency to acquire and decrypt from the block chain so as to verify whether the calculation of each piece of evaluation information is correct.
7. The method of claim 5 or 6, further comprising:
in a first public period after the first evaluation transaction is executed, executing a reporting transaction through the poverty relief contract, recording reporting information of a first candidate to be reported on a block chain so that the big data application end can acquire the reporting information, recalculating the first evaluation information of the first candidate according to the reporting information, generating a second evaluation transaction according to the first evaluation information and each evaluation information of other candidates, and sending the second evaluation transaction to a block chain network;
and executing the second evaluation transaction through the lean-right contract, and re-determining a plurality of lean-right objects and recording the objects on the block chain.
8. The method of claim 7, further comprising:
in a second public period after the reporting transaction is executed, executing a certification material submitting transaction through the poverty relief contract, recording the certification material submitted by the first candidate on a block chain so that the big data application end can obtain the certification material, recalculating second evaluation information of the first candidate according to the certification material, generating a third evaluation transaction according to the second evaluation information and each evaluation information of other candidates, and sending the third evaluation transaction to a block chain network;
and executing the third evaluation transaction through the lean-right contract, and re-determining a plurality of lean-right objects and recording the objects on the block chain.
9. An apparatus, characterized in that the apparatus comprises:
one or more processors;
a memory for storing one or more programs,
the one or more programs, when executed by the one or more processors, cause the one or more processors to perform the method recited in any of claims 1-8.
10. A storage medium storing a computer program, characterized in that the program, when executed by a processor, implements the method according to any one of claims 1-8.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202010658847.4A CN112131306A (en) | 2020-07-09 | 2020-07-09 | Object recognition method, device and storage medium |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202010658847.4A CN112131306A (en) | 2020-07-09 | 2020-07-09 | Object recognition method, device and storage medium |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN112131306A true CN112131306A (en) | 2020-12-25 |
Family
ID=73850221
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202010658847.4A Pending CN112131306A (en) | 2020-07-09 | 2020-07-09 | Object recognition method, device and storage medium |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN112131306A (en) |
Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN109711201A (en) * | 2018-12-29 | 2019-05-03 | 百度在线网络技术（北京）有限公司 | Poverty alleviation processing method, device, equipment and medium based on block chain |
| CN109711200A (en) * | 2018-12-29 | 2019-05-03 | 百度在线网络技术（北京）有限公司 | Accurate poverty alleviation method, apparatus, equipment and medium based on block chain |
| CN110276706A (en) * | 2019-06-20 | 2019-09-24 | 山西清众科技股份有限公司 | An On-Demand Matching Precision Poverty Alleviation Information Publicity System |
| CN110706098A (en) * | 2018-07-09 | 2020-01-17 | 普天信息技术有限公司 | Accurate poverty alleviation system and method based on block chain |
-
2020
- 2020-07-09 CN CN202010658847.4A patent/CN112131306A/en active Pending
Patent Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN110706098A (en) * | 2018-07-09 | 2020-01-17 | 普天信息技术有限公司 | Accurate poverty alleviation system and method based on block chain |
| CN109711201A (en) * | 2018-12-29 | 2019-05-03 | 百度在线网络技术（北京）有限公司 | Poverty alleviation processing method, device, equipment and medium based on block chain |
| CN109711200A (en) * | 2018-12-29 | 2019-05-03 | 百度在线网络技术（北京）有限公司 | Accurate poverty alleviation method, apparatus, equipment and medium based on block chain |
| CN110276706A (en) * | 2019-06-20 | 2019-09-24 | 山西清众科技股份有限公司 | An On-Demand Matching Precision Poverty Alleviation Information Publicity System |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| US11630808B2 (en) | Proof of lottery (PoL) blockchain | |
| US11144918B2 (en) | Method, apparatus and electronic device for blockchain transactions | |
| CN110383757B (en) | System and method for secure processing of electronic identities | |
| Li et al. | Eunomia: Anonymous and secure vehicular digital forensics based on blockchain | |
| CN109840771A (en) | A kind of block chain intimacy protection system and its method based on homomorphic cryptography | |
| US11321716B2 (en) | Identity-based transaction processing | |
| CN111898148A (en) | Information supervision method and device based on block chain | |
| CN112000744B (en) | Signature method and related equipment | |
| CN105519070A (en) | Certificating authority trust evaluation | |
| CN109858911A (en) | Qualification verification method, device, system, equipment and readable storage medium storing program for executing | |
| CN111125245A (en) | Blockchain-based data processing method, device and storage medium | |
| Mansoor et al. | A review of blockchain approaches for kyc | |
| CN110213251B (en) | Method for anonymously reporting reward distribution, method for obtaining reward, equipment and storage medium | |
| CN106101092A (en) | A kind of information evaluation processing method and first instance | |
| CN113347008B (en) | Loan information storage method adopting addition homomorphic encryption | |
| Foy et al. | Blockchain-based governance models for COVID-19 digital health certificates: A legal, technical, ethical and security requirements analysis | |
| CN113486407A (en) | Deposit receipt management system and method based on block chain | |
| US11997103B2 (en) | Graduated accounts using assertions | |
| Bhatti et al. | Impact of blockchain technology in modern banking sector to exterminate the financial scams | |
| CN110351081A (en) | Monetary assets management method and system | |
| CN112131306A (en) | Object recognition method, device and storage medium | |
| US20220271949A1 (en) | Guaranteed control method, information processing device, and storage medium | |
| CN113498592B (en) | Method and system for digital property authentication and management | |
| CN114329610A (en) | Block chain privacy identity protection method, device, storage medium and system | |
| CN111402037A (en) | User data processing method and device |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| WD01 | Invention patent application deemed withdrawn after publication |
Application publication date: 20201225 |
|
| WD01 | Invention patent application deemed withdrawn after publication |