WO2020238533A1 - 基于区块链的数据管理方法、装置、介质及电子设备 - Google Patents

基于区块链的数据管理方法、装置、介质及电子设备 Download PDF

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WO2020238533A1
WO2020238533A1 PCT/CN2020/087469 CN2020087469W WO2020238533A1 WO 2020238533 A1 WO2020238533 A1 WO 2020238533A1 CN 2020087469 W CN2020087469 W CN 2020087469W WO 2020238533 A1 WO2020238533 A1 WO 2020238533A1
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data
uploader
weight value
target
credit
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French (fr)
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赵达悦
王梦寒
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OneConnect Smart Technology Co Ltd
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OneConnect Smart Technology Co Ltd
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    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; 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
    • G06Q30/00—Commerce
    • G06Q30/06—Buying, selling or leasing transactions
    • G06Q30/0601—Electronic shopping [e-shopping]
    • G06Q30/0609—Qualifying participants for shopping transactions
    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; 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
    • G06Q50/00—Information and communication technology [ICT] specially adapted for implementation of business processes of specific business sectors, e.g. utilities or tourism
    • G06Q50/10—Services
    • G06Q50/26—Government or public services

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  • This application relates to the field of blockchain technology, and in particular to a data management method based on blockchain, a data management device based on blockchain, computer readable media and electronic equipment.
  • an authorized economic operator (AEO) certified by the customs needs to record their import and export activities in a timely, accurate and true manner so that the customs can inspect them.
  • each enterprise side can be a manufacturer, importer, exporter, customs broker, carrier, and tally. , Intermediaries, ports and airports, cargo terminal operators, general operators, warehousing operators and distributors, etc.; further, information submitted by the enterprise side that has been confirmed to be legal is filtered to obtain filtered imports/ Export necessary information, such as product information, factory information, production qualification certificate, destination and origin, etc.; then, verify the consistency of the necessary import/export information, and if the consistency is lower than a certain threshold, the batch of goods is determined to be For abnormal goods, if the consistency is higher than a certain threshold, the batch of goods will be released. It can be seen that the inspection process for the above-mentioned customs to inspect the import and export activities of enterprises is relatively complicated and takes a long time, which will reduce the efficiency of the review.
  • the purpose of the embodiments of this application is to provide a blockchain-based data management method, a blockchain-based data management device, computer-readable media, and electronic equipment, so as to overcome at least to a certain extent the complicated inspection process and inspection The problem of reduced audit efficiency caused by the long time required.
  • the first aspect of the embodiments of the present application provides a blockchain-based data management method, including: determining the total number of uploaders that upload the same data for the target field according to the data credit of the uploader of each blockchain node Data credit score; determine the sum result of all the total data credit score; use the ratio of the total data credit score and the sum result as the credibility weight value; determine the target data from the data uploaded by the uploader according to the credibility weight value ; Among them, the target data corresponds to the target field.
  • a data management device based on blockchain including: a data credit score determining unit, configured to determine the upload of the same data for the target field according to the data credit score of each uploader The total data credit score of the party; the sum result determination unit is used to determine the sum result of all the total data credit scores; the ratio determination unit is used to use the ratio of the total data credit score and the sum result as the credibility weight value; The target data determining unit is used to determine target data from the data uploaded by the uploader according to the credibility weight value; wherein the target data corresponds to the target field.
  • a computer-readable medium on which a computer program is stored, and when the program is executed by a processor, the blockchain-based data as described in the first aspect of the above-mentioned embodiment is realized Management methods.
  • an electronic device including: one or more processors; a storage device, used to store one or more programs, when one or more programs are processed by one or more When the processor executes, one or more processors are allowed to implement the blockchain-based data management method as described in the first aspect of the above-mentioned embodiments.
  • the buyer node, seller node, middleman node, and logistics party node if there are four blockchain nodes, such as buyer node, seller node, middleman node, and logistics party node, and the buyer node, seller node, middleman node and logistics
  • the data credits corresponding to the square nodes are 80, 80, 60, and 10 respectively.
  • the buyer node, the seller node, the middleman node, and the logistics party node respectively input data for the target field (for example, the name of the goods) as apple, apple, pear, and pear.
  • the buyer node and the seller node upload the same data apple for the product name
  • the middleman node and the logistics party node upload the same data apple for the product name.
  • the server/terminal device can determine that the total data credit of the uploader whose upload data is Apple is divided into the data of the buyer node and the seller node according to the data credits corresponding to the buyer node, the seller node, the middleman node, and the logistics party node.
  • the sum of credit points is 160.
  • the total data credit of the uploader whose uploaded data is pear is 70.
  • Fig. 1 schematically shows a flowchart of a blockchain-based data management method according to an embodiment of the present application
  • Fig. 2 schematically shows a block diagram of a block chain-based data management device according to an embodiment of the present application
  • Fig. 3 shows a schematic structural diagram of a computer system suitable for implementing an electronic device according to an embodiment of the present application.
  • FIG. 1 schematically shows a flowchart of a blockchain-based data management method according to an embodiment of the present application.
  • the data management method may be implemented by a server or a terminal device.
  • the blockchain-based data management method includes the following steps: step S110, step S120, step S130, and step S140. The steps are described in detail below.
  • step S110 according to the data credit of the uploader of each blockchain node, the total data credit of the uploader who uploaded the same data for the target field is determined.
  • the data credit corresponding to the uploader is used to indicate the credibility of the data uploaded by the uploader. For example, if the data credit score corresponding to uploader A is lower than the data credit threshold (for example, 60 points), it means that the credibility of the data uploaded by uploader A is low, which can also be understood as uploading in the historical record Party A has uploaded a lot of wrong data; if the data credit score corresponding to uploader B is higher than the data credit score threshold, it means that the data uploaded by uploader B has a high credibility, which can also be understood as uploading in the historical record Party B has uploaded less incorrect data.
  • the data credit threshold for example, 60 points
  • the uploading party can be a manufacturer, importer, exporter, customs broker, carrier, tally, middleman, port, airport, cargo terminal operator, comprehensive operator, and warehouse operator Or distributors, etc., the embodiments of this application are not limited.
  • the target field may be a field such as the name of the product, the order number, or the quantity of the product, which is not limited in the embodiment of the present application.
  • each blockchain node corresponds to an uploader, and uploader A and uploader B of the four uploaders upload apples, Uploader C and uploader D upload snake fruit.
  • the total data credits of uploader A and uploader B that upload the same data for the target field product name is the sum of the data credits corresponding to uploader A and the data credits corresponding to uploader B; for the target
  • the total data credit scores of uploader C and uploader D that upload the same data snake fruit in the field product name is the sum of the data credits corresponding to uploader C and the data credits corresponding to uploader D.
  • determining the total data credit score of the uploader that uploads the same data for the target field may include the following steps: uploading the same data for the target field The data uploader is determined to be the same category; the total data credit corresponding to each category is determined; the total data credit is divided into the sum of the data credit of the uploader of the blockchain node uploading the same data for the target field.
  • the uploaders who upload the same data for the target field are determined to be in the same category, which can also be understood as grouping the uploaders who upload the same data for the target field into one category. Quoting the above example, because uploader A and uploader B upload data for the target field product name are all apples, then uploader A and uploader B can be classified as category 1; because uploader C and uploader D are targeting The data uploaded by the target field product name is snake fruit, then uploader C and uploader D can be classified into category 2; where, the labels 1 and 2 in category 1 and category 2 are only used to distinguish the two categories. Furthermore, the total data credit score corresponding to category 1 is the sum of the data credit points of uploader A and uploader B, and the total data credit score corresponding to category 2 is the sum of the data credit points of uploader C and uploader D.
  • this optional implementation manner can facilitate the calculation of the total data credit score of each category, thereby improving the review efficiency of various government or non-government agencies for reviewing information.
  • step S120 the sum result of all the total data credits is determined.
  • the sum of all total data credits is the total data credits; if the number of total data credits is greater than 1, then all total data credits The sum of the data credits is the sum of all the total data credits.
  • the data management method may further include the following steps: according to the comparison of the credibility weight value and the preset weight value, Adjust the data credit score corresponding to each uploader.
  • the method of adjusting the data credit score corresponding to each uploader may be specifically as follows:
  • the server/terminal device compares each credibility weight value with the preset weight value. If the credibility weight value is greater than the preset weight value, then the credibility weight value corresponds to the data credit score of all uploaders. Increase; if the credibility weight value is not greater than the preset weight value, the credibility weight value will be adjusted down corresponding to the data credits of all uploaders.
  • the server/terminal device can increase the data credit score of each uploader corresponding to the credibility weight value of 0.7 10 points; or, according to the adjustment range to which the credibility weight value 0.7 belongs, the data credit scores of all uploaders corresponding to the credibility weight value are increased, if the credibility weight value 0.7 belongs to the adjustment range 0.6-0.7, The adjustment range corresponding to this adjustment range is 5 points, so the server/terminal device can increase the data credit score of each uploader corresponding to the credibility weight value of 0.7 by 5 points.
  • the server/terminal device can lower the data credit score of each uploader corresponding to the credibility weight value of 0.5 by 10 points; Or, according to the adjustment range of the credibility weight value 0.5, the credibility weight value corresponding to the data credit score of all uploaders is lowered, if the credibility weight value 0.5 belongs to the adjustment range 0.5-0.6, and the adjustment range The corresponding adjustment range is 5 points, then the server/terminal device can lower the data credit score of each uploader corresponding to the credibility weight value of 0.5 by 5 points.
  • determining the total data credit of the uploader that uploads the same data for the target field may include the following steps: The data credit score of the uploader of the chain node determines the scale factor corresponding to each uploader that uploads the same data for the target field; the sum of the multiplication results of the scale factor corresponding to all uploaders and the data credit score corresponding to the uploader, As the total data credit corresponding to the uploader who uploaded the same data.
  • the proportional coefficient is used to indicate the valid part of the data credit score corresponding to the uploader.
  • the valid part can be added to the valid part corresponding to other uploaders, and the valid part corresponding to all uploaders uploading the same data
  • the sum result of is the total data credits mentioned above.
  • the terminal The device/server can determine the respective scale factors corresponding to uploader A and uploader B according to the preset scale factor judgment range; among them, uploader A’s data credit score 80 belongs to the scale factor judgment range 80-100, uploader B’s data The credit score of 20 belongs to the scale coefficient judgment range 0-20.
  • step S130 the ratio of the total data credits to the sum result is used as the credibility weight value.
  • the credibility weight value is used to indicate the credibility of the data corresponding to the total data credit score.
  • the data management method may further include the following steps: detecting whether there is a credibility weight value higher than the preset weight value; if it does not exist, determining that the transaction corresponding to the target field is at risk, and reporting it Risk information.
  • step S140 if it is detected that there is a credibility weight value higher than the preset weight value, step S140 is executed. If it is detected that there is no credibility weight value higher than the preset weight value, it means that the goods in the transaction corresponding to the target field may be dangerous goods, or a certain uploader has fraudulent behavior, etc. Therefore, based on the current situation, the server/terminal The device can report risk information that indicates that the transaction is at risk, and promptly remind the reviewer to manually inspect the transaction.
  • step S140 the target data is determined from the data uploaded by the uploader according to the credibility weight value; the target data corresponds to the target field.
  • determining the target data from the data uploaded by the uploader according to the credibility weight value may include the following steps: determining the credibility of the target higher than the preset weight value from the credibility weight value Degree weight value; from the data uploaded by the uploader, the data corresponding to the target credibility weight value is determined as the target data.
  • the terminal device/server can use the data apple uploaded by uploader A and uploader B as the target data, that is, the target field (e.g., goods Name) is the data uploaded by the uploader (ie, Apple).
  • the target field e.g., goods Name
  • the data management method may further include the following steps: if a spot check instruction is received, read and output historical transaction information corresponding to the spot check instruction; wherein, the historical transaction information includes the corresponding field in the historical transaction The data uploaded by the uploader.
  • the spot check instruction is used to indicate that the reviewer needs to perform spot checks on transactions that have been verified by the server/terminal device; among them, the transaction contains one or more target fields.
  • the server/terminal device receives the spot check instruction, it can read and output the information corresponding to the spot check instruction from the historical transaction information, so that the auditor can check it.
  • this optional implementation manner can re-inspect certain goods that have been screened by data credit by means of random checks by the auditors, reducing the risk caused by non-compliance of transactions.
  • the implementation of the blockchain-based data management method shown in Figure 1 can improve the review efficiency of various government or non-government organizations to review information; and, it can adjust (or iterate) the data credit score corresponding to the uploader. ) To improve the audit accuracy of various government or non-government institutions; and to report risk information in a timely manner when there is a risk in the transaction, so that various government or non-government institutions can handle the audit information in a timely manner for manual inspection and reduce the risk The probability of occurrence.
  • FIG. 2 schematically shows a block diagram of a block chain-based data management device according to an embodiment of the present application.
  • the data management device includes: a data credit determination unit 210, a sum result determination unit 220, a ratio determination unit 230, and a target data determination unit 240, wherein:
  • the data credit determination unit 210 is used to determine the total data credit of the uploader that uploads the same data for the target field according to the data credit of each uploader; the addition result determination unit 220 is used to determine the addition of all the total data credits And the result; the ratio determining unit 230 is configured to use the ratio of the total data credits to the sum result as the credibility weight value; the target data determining unit 240 is configured to determine the target from the data uploaded by the uploader according to the credibility weight value Data; Among them, the target data corresponds to the target field.
  • the data credit score determining unit 210 determines the total data credit score of the uploader who uploads the same data for the target field according to the data credit score of each uploader, specifically: data credit score determination The unit 210 determines the uploader who uploads the same data for the target field as the same category; the data credit determination unit 210 determines the total data credit corresponding to each category; wherein the total data credit is divided into the area where the same data is uploaded for the target field. The sum of the data credits of the uploader of the blockchain node.
  • this optional implementation manner can facilitate the calculation of the total data credit score of each category, thereby improving the review efficiency of various government or non-government agencies for reviewing information.
  • the target data determining unit 240 determines the target data from the data uploaded by the uploader according to the credibility weight value: the target data determining unit 240 determines the target data from the credibility weight value.
  • the target credibility weight value is higher than the preset weight value; the data credit determination unit 210 determines the data corresponding to the target credibility weight value from the data uploaded by the uploader as the target data.
  • the data management device may further include data credit adjustment Unit (not shown), where:
  • the data credit adjustment unit is used to adjust the data credit corresponding to each uploader according to the comparison between the credibility weight value and the preset weight value.
  • the data management apparatus may further include a credibility weight value detection unit (not shown) and a risk information reporting unit (not shown), wherein:
  • the credibility weight value detection unit is used to detect whether there is a credibility weight value higher than the preset weight value; the risk information reporting unit is used to detect that the credibility weight value detection unit does not exist higher than all After the credibility weight value of the preset weight value is described, it is determined that the transaction corresponding to the target field is at risk, and the risk information is reported.
  • the target data determining unit 240 is specifically configured to determine from the data uploaded by the uploader according to the credibility weight value after the credibility weight value detecting unit detects that there is a credibility weight value higher than the preset weight value Out target data.
  • the data management device may further include a spot check instruction detection unit (not shown) and a historical transaction information reading unit (not shown), wherein:
  • the spot check instruction detection unit is used to detect whether the spot check instruction is received; the historical transaction information reading unit is used to read and output the historical transaction information corresponding to the spot check instruction after the spot check instruction detection unit detects that the spot check instruction is received; where ,
  • the historical transaction information includes the data uploaded by the uploader corresponding to each field in the historical transaction.
  • this optional implementation manner can re-inspect certain goods that have been screened by data credit by means of random checks by the auditors, reducing the risk caused by non-compliance of transactions.
  • the data credit score determination unit 210 determines the total data credit score of the uploader who uploads the same data for the target field according to the data credit score of each uploader, specifically: data credit score The determining unit 210 determines the scale factor corresponding to each uploader that uploads the same data for the target field according to the data credit score of the uploader of each blockchain node; the data credit score determining unit 210 compares the scale factors corresponding to all uploaders with The sum of the multiplication results of the data credits corresponding to the uploader is used as the total data credits corresponding to the uploader who uploads the same data.
  • each functional module of the block chain-based data management device of the exemplary embodiment of the present application corresponds to the steps of the exemplary embodiment of the above-mentioned block chain-based data management method, the details that are not disclosed in the device embodiment of the present application Please refer to the embodiment of the blockchain-based data management method mentioned above in this application.
  • FIG. 3 shows a schematic structural diagram of a computer system 300 suitable for implementing an electronic device according to an embodiment of the present application.
  • the computer system 300 of the electronic device shown in FIG. 3 is only an example, and should not bring any limitation to the functions and scope of use of the embodiments of the present application.
  • the computer system 300 includes a central processing unit (CPU) 301, which can be based on a program stored in a read-only memory (ROM) 302 or a program loaded from a storage portion 308 into a random access memory (RAM) 303 And perform various appropriate actions and processing.
  • ROM read-only memory
  • RAM random access memory
  • various programs and data required for system operation are also stored.
  • the CPU 301, ROM 302, and RAM 303 are connected to each other through a bus 304.
  • An input/output (I/O) interface 305 is also connected to the bus 304.
  • the following components are connected to the I/O interface 305: an input part 306 including a keyboard, a mouse, etc.; an output part 307 including a cathode ray tube (CRT), a liquid crystal display (LCD), etc., and a speaker; a storage part 308 including a hard disk, etc. ; And a communication section 309 including a network interface card such as a LAN card, a modem, etc.
  • the communication section 309 performs communication processing via a network such as the Internet.
  • the driver 310 is also connected to the I/O interface 305 as needed.
  • the process described above with reference to the flowchart can be implemented as a computer software program.
  • the embodiments of the present application include a computer program product, which includes a computer program carried on a computer-readable medium, and the computer program contains program code for executing the method shown in the flowchart.
  • the computer program may be downloaded and installed from the network through the communication part 309, and/or installed from the removable medium 311.
  • the central processing unit (CPU) 301 the above-mentioned functions defined in the system of the present application are executed.
  • the computer-readable medium shown in this application may be a computer-readable signal medium or a computer-readable storage medium or any combination of the two.
  • the computer-readable storage medium may be, for example, but not limited to, an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, device, or device, or any combination of the above. More specific examples of computer-readable storage media may include, but are not limited to: electrical connections with one or more wires, portable computer disks, hard disks, random access memory (RAM), read-only memory (ROM), erasable Programmable read only memory (EPROM or flash), optical fiber, portable compact disk read only memory (CD-ROM), optical storage device, magnetic storage device, or any suitable combination of the above.
  • the computer-readable storage medium may be any tangible medium that contains or stores a program, and the program may be used by or in combination with an instruction execution system, apparatus, or device.
  • a computer-readable signal medium may include a data signal propagated in a baseband or as a part of a carrier wave, and a computer-readable program code is carried therein. This propagated data signal can take many forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination of the foregoing.
  • the computer-readable signal medium may also be any computer-readable medium other than the computer-readable storage medium.
  • the computer-readable medium may send, propagate, or transmit the program for use by or in combination with the instruction execution system, apparatus, or device .
  • the program code contained on the computer-readable medium can be transmitted by any suitable medium, including but not limited to: wireless, wire, optical cable, RF, etc., or any suitable combination of the above.
  • each block in the flowchart or block diagram may represent a module, program segment, or part of code, and the above-mentioned module, program segment, or part of code contains one or more for realizing the specified logic function Executable instructions.
  • the functions marked in the block may also occur in a different order from the order marked in the drawings. For example, two blocks shown in succession can actually be executed substantially in parallel, and they can sometimes be executed in the reverse order, depending on the functions involved.
  • each block in the block diagram or flowchart, and the combination of blocks in the block diagram or flowchart can be implemented by a dedicated hardware-based system that performs the specified function or operation, or can be It is realized by a combination of dedicated hardware and computer instructions.
  • the units involved in the embodiments described in the present application can be implemented in software or hardware, and the described units can also be provided in a processor. Among them, the names of these units do not constitute a limitation on the unit itself under certain circumstances.
  • the present application also provides a computer-readable medium.
  • the computer-readable storage medium may be non-volatile or volatile.
  • the computer-readable medium may be included in the electronic device described in the above embodiment; or it may exist alone without being assembled into the electronic device.
  • the above-mentioned computer-readable medium carries one or more programs, and when the above-mentioned one or more programs are executed by an electronic device, the electronic device realizes the blockchain-based data management method as described in the above-mentioned embodiment.
  • the electronic device can realize the following: step S110, according to the data credit score of the uploader of each blockchain node, determine the total data credit score of the uploader that uploads the same data for the target field Step S120, determine the sum result of all the total data credits; step S130, use the ratio of the total data credits and the sum result as the credibility weight value; step S140, upload from the uploader according to the credibility weight value
  • the target data is determined from the data; among them, the target data corresponds to the target field.
  • the exemplary embodiments described herein can be implemented by software, or can be implemented by combining software with necessary hardware. Therefore, the technical solution according to the embodiments of the present application can be embodied in the form of a software product, which can be stored in a non-volatile storage medium (can be a CD-ROM, U disk, mobile hard disk, etc.) or on the network , Including several instructions to make a computing device (which can be a personal computer, a server, a touch terminal, or a network device, etc.) execute the method according to the embodiment of the present application.
  • a computing device which can be a personal computer, a server, a touch terminal, or a network device, etc.

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Abstract

本申请的实施例提供了一种基于区块链的数据管理方法、基于区块链的数据管理装置、计算机可读介质及电子设备，涉及区块链技术领域。该方法包括：根据每个区块链节点的上传方的数据信用分，确定针对目标字段上传相同数据的上传方的总数据信用分；确定所有总数据信用分的加和结果；将总数据信用分与加和结果的比值作为可信度权重值；根据可信度权重值从上传方上传的数据中确定出目标数据；其中，目标数据与目标字段相对应。本申请实施例的技术方案能够在一定程度上克服由于检查流程较为复杂以及检查所需时间较长而造成的审核效率降低的问题。

Description

基于区块链的数据管理方法、装置、介质及电子设备 技术领域
本申请要求于2019年5月24日提交中国专利局、申请号为201910441367.X，发明名称为“基于区块链的数据管理方法、装置、介质及电子设备”的中国专利申请的优先权，其全部内容通过引用结合在本申请中。
本申请涉及区块链技术领域，具体而言，涉及一种基于区块链的数据管理方法、基于区块链的数据管理装置、计算机可读介质及电子设备。
背景技术
通常，经海关认证的经营者(Authorized Economic Operator，AEO)需要及时、准确、真实地对其进出口活动进行纪录，以便海关对其进行检查。
具体地，海关对企业进出口活动进行检查的方式为：确认提交信息的各企业端的合法性；其中；各企业端可以为生产商、进口商、出口商、报关行、承运商、理货人、中间商、口岸和机场、货站经营者、综合经营者、仓储业经营者和分销商等；进而，对确认过合法性的企业端提交的信息进行信息过滤，以得到过滤后的进口/出口必要信息，如货品信息、出厂信息、生产合格证明、目的地以及始发地等；进而，再核实各进口/出口必要信息的一致性，如果一致性低于某阈值则判定该批货物为异常货物，如果一致性高于某阈值则对该批货物实施放行。可见，上述海关对企业进出口活动进行检查的检查流程较为复杂，所需时间较长，这样会降低审核效率。
需要说明的是，在上述背景技术部分公开的信息仅用于加强对本申请的背景的理解，因此可以包括不构成对本领域普通技术人员已知的现有技术的信息。
发明概述
技术问题
问题的解决方案
技术解决方案
本申请实施例的目的在于提供一种基于区块链的数据管理方法、基于区块链的 数据管理装置、计算机可读介质及电子设备，进而至少在一定程度上克服由于检查流程较为复杂以及检查所需时间较长而造成的审核效率降低的问题。
本申请实施例的第一方面提供了一种基于区块链的数据管理方法，包括：根据每个区块链节点的上传方的数据信用分，确定针对目标字段上传相同数据的上传方的总数据信用分；确定所有总数据信用分的加和结果；将总数据信用分与加和结果的比值作为可信度权重值；根据可信度权重值从上传方上传的数据中确定出目标数据；其中，目标数据与目标字段相对应。
本申请实施例的第二方面，提供一种基于区块链的数据管理装置，包括：数据信用分确定单元，用于根据每个上传方的数据信用分，确定针对目标字段上传相同数据的上传方的总数据信用分；加和结果确定单元，用于确定所有总数据信用分的加和结果；比值确定单元，用于将总数据信用分与加和结果的比值作为可信度权重值；目标数据确定单元，用于根据可信度权重值从上传方上传的数据中确定出目标数据；其中，目标数据与目标字段相对应。
根据本申请实施例的第三方面，提供了一种计算机可读介质，其上存储有计算机程序，程序被处理器执行时实现如上述实施例中第一方面所述的基于区块链的数据管理方法。
根据本申请实施例的第四方面，提供了一种电子设备，包括：一个或多个处理器；存储装置，用于存储一个或多个程序，当一个或多个程序被一个或多个处理器执行时，使得一个或多个处理器实现如上述实施例中第一方面所述的基于区块链的数据管理方法。
本申请实施例提供的技术方案可以包括以下有益效果：
在本申请的一些实施例所提供的技术方案中，若存在四个区块链节点，如买方节点、卖方节点、中间商节点以及物流方节点，并且买方节点、卖方节点、中间商节点以及物流方节点对应的数据信用分分别为80、80、60以及10。此外，如果买方节点、卖方节点、中间商节点以及物流方节点针对目标字段(如，货品名称)分别输入的数据为苹果、苹果、梨以及梨。那么，由上可知，买方节点和卖方节点针对货品名称上传的是相同数据苹果，中间商节点和物流方节点针对货品名称上传的是相同数据梨。因此，服务器/终端设备可以根据买方节点 、卖方节点、中间商节点以及物流方节点分别对应的数据信用分，确定出上传数据为苹果的上传方的总数据信用分为买方节点和卖方节点的数据信用分之和，即160，同理，上传数据为梨的上传方的总数据信用分为70。进而，服务器/终端设备还可以确定出上传数据为苹果的上传方的总数据信用分，与上传数据为梨的上传方的总数据信用分的加和结果，即160+70＝230。进而，服务器/终端设备还可以将总数据信用分与加和结果的比值作为可信度权重值，即上传数据为苹果的上传方的总数据信用分对应的可信度权重值为160/230＝0.7，上传数据为梨的上传方的总数据信用分对应的可信度权重值为70/230＝0.3。进而，服务器/终端设备还可以根据上述可信度权重值0.7和0.3从上传方上传的数据中确定出目标数据(即，梨或苹果)。依据上述方案描述，本申请一方面能够提高各类机构对于待审核信息的审核效率。另一方面，相较传统复杂的检查流程，能够一定程度上为待审核业务的通行提供更多的便利性。
发明的有益效果
对附图的简要说明
附图说明
图1示意性示出了根据本申请实施例的基于区块链的数据管理方法的流程图；
图2示意性示出了根据本申请实施例的基于区块链的数据管理装置的结构框图；
图3示出了适于用来实现本申请实施例的电子设备的计算机系统的结构示意图。
发明实施例
本发明的实施方式
请参阅图1，图1示意性示出了根据本申请实施例的基于区块链的数据管理方法的流程图，该数据管理方法可以由服务器或终端设备来实现。如图1所示，基于区块链的数据管理方法，包括如下步骤：步骤S110、步骤S120、步骤S130以及步骤S140，以下对各步骤进行详细说明。
在步骤S110中，根据每个区块链节点的上传方的数据信用分，确定针对目标字 段上传相同数据的上传方的总数据信用分。
在本申请实施例中，上传方对应的数据信用分用于表示该上传方上传的数据的可信度。举例来说，如果上传方A对应的数据信用分低于数据信用分阈值(如，60分)，则说明上传方A上传的数据的可信度较低，也可以理解为在历史记录中上传方A上传过较多的错误数据；如果上传方B对应的数据信用分高于数据信用分阈值，则说明上传方B上传的数据的可信度较高，也可以理解为在历史记录中上传方B上传过较少的错误数据。
在本申请实施例中，上传方可以为生产商、进口商、出口商、报关行、承运商、理货人、中间商、口岸、机场、货站经营者、综合经营者、仓储业经营者或分销商等，本申请实施例不作限定。
在本申请实施例中，目标字段可以为货品名称、订单号或货品数量等字段，本申请实施例不作限定。
举例来说，如果目标字段为货品名称，且存在四个区块链节点，每个区块链节点对应一个上传方，而四个上传方中的上传方A和上传方B上传的是苹果，上传方C和上传方D上传的是蛇果。那么，针对目标字段货品名称上传了相同数据苹果的上传方A和上传方B的总数据信用分，则为上传方A对应的数据信用分与上传方B对应的数据信用分之和；针对目标字段货品名称上传了相同数据蛇果的上传方C和上传方D的总数据信用分，则为上传方C对应的数据信用分与上传方D对应的数据信用分之和。
作为一种可选的实施方式，根据每个区块链节点的上传方的数据信用分，确定针对目标字段上传相同数据的上传方的总数据信用分可以包括以下步骤：将针对目标字段上传相同数据的上传方确定为同一个类别；确定每个类别对应的总数据信用分；其中，总数据信用分为针对目标字段上传相同数据的区块链节点的上传方的数据信用分之和。
在本申请实施例中，将针对目标字段上传相同数据的上传方确定为同一个类别，也可以理解为将针对目标字段上传相同数据的上传方归为一类。引用上述举例，由于上传方A和上传方B针对目标字段货品名称上传的数据均为苹果，那么，则可以将上传方A和上传方B归为类别1；由于上传方C和上传方D针对目标字 段货品名称上传的数据均为蛇果，那么，则可以将上传方C和上传方D归为类别2；其中，类别1和类别2中的标号1和2仅用作区分两个类别。进而，类别1对应的总数据信用分则为上传方A和上传方B的数据信用分之和，类别2对应的总数据信用分则为上传方C和上传方D的数据信用分之和。
可见，实施该可选的实施方式，能够便于计算每类的总数据信用分，进而提高各类政府或非政府机构对待审核信息的审核效率。
在步骤S120中，确定所有总数据信用分的加和结果。
在本申请实施例中，如果总数据信用分的数量为1，那么，所有总数据信用分的加和结果则为该总数据信用分；如果总数据信用分的数量大于1，那么，所有总数据信用分的加和结果则为所有总数据信用分的和。
作为一种可选的实施方式，确定出与目标可信度权重值对应的数据作为目标数据之后，数据管理方法还可以包括以下步骤：根据可信度权重值与预设权重值的比对，调整每个上传方对应的数据信用分。
在本申请实施例中，根据可信度权重值与预设权重值的比对，调整每个上传方对应的数据信用分的方式具体可以为：
服务器/终端设备分别将每个可信度权重值与预设权重值进行比对，如果可信度权重值大于预设权重值，则将可信度权重值对应所有上传方的数据信用分进行上调；如果可信度权重值不大于预设权重值，则将可信度权重值对应所有上传方的数据信用分进行下调。
举例来说，如果可信度权重值(如，0.7)大于预设权重值(如，0.6)，服务器/终端设备则可以将可信度权重值0.7对应的每个上传方的数据信用分上调10分；或者，根据可信度权重值0.7所属的调整范围对可信度权重值对应的所有上传方的数据信用分进行上调，如果可信度权重值0.7所属的调整范围为0.6-0.7，而该调整范围对应的调整幅度为5分，那么，服务器/终端设备则可以将可信度权重值0.7对应的每个上传方的数据信用分上调5分。如果可信度权重值(如，0.5)不大于预设权重值(如，0.6)，服务器/终端设备则可以将可信度权重值0.5对应的每个上传方的数据信用分下调10分；或者，根据可信度权重值0.5所属的调整范围对可信度权重值对应所有上传方的数据信用分进行下调，如果可信度权重 值0.5所属的调整范围为0.5-0.6，而该调整范围对应的调整幅度为5分，那么，服务器/终端设备则可以将可信度权重值0.5对应的每个上传方的数据信用分下调5分。
可见，实施该可选的实施方式，能够通过对上传方对应的数据信用分进行调整(或迭代)，提高各类政府或非政府机构的审核准确度。
作为另一种可选的实施方式，根据每个区块链节点的上传方的数据信用分，确定针对目标字段上传相同数据的上传方的总数据信用分可以包括以下步骤：根据每个区块链节点的上传方的数据信用分，确定针对目标字段上传相同数据的每个上传方对应的比例系数；将所有上传方对应的比例系数与上传方对应的数据信用分的相乘结果之和，作为上传相同数据的上传方对应的总数据信用分。
本申请实施例中，比例系数用于表示上传方对应的数据信用分中的有效部分，该有效部分可以与其他上传方对应的有效部分进行加和，上传相同数据的所有上传方对应的有效部分的加和结果即为上述的总数据信用分。
举例来说，如果上传方A和上传方B针对目标字段货品名称上传的数据均为苹果，而上传方A对应的数据信用分为80，上传方B对应的数据信用分为20，那么，终端设备/服务器可以根据预设的比例系数判定范围确定上传方A和上传方B分别对应的比例系数；其中，上传方A的数据信用分80属于比例系数判定范围80-100，上传方B的数据信用分20属于比例系数判定范围0-20。由于比例系数判定范围80-100对应的比例系数为80％，比例系数判定范围0-20对应的比例系数为20％，因此，上传方A对应的比例系数为80％，上传方B对应的比例系数为20％，上传相同数据的上传方对应的总数据信用分为80*80％+20*20％＝68。
可见，实施该可选的实施方式，能够通过上传方对应的数据信用分和比例系数相乘，最终计算得出更为准确的总数据信用分，提高了总数据信用分的数值精度，进而提高各类政府或非政府机构的审核准确度。
在步骤S130中，将总数据信用分与加和结果的比值作为可信度权重值。
在本申请实施例中，可信度权重值用于表示总数据信用分对应的数据的可信度。
举例来说，如果存在上传了相同数据苹果的上传方A和上传方B，以及上传了 相同数据蛇果的上传方C和上传方D，并且，上传方A和上传方B对应的总数据信用分为80，上传方C和上传方D对应的总数据信用分为20。那么，上传方A和上传方B对应的可信度权重值为80/(80+20)＝0.8，上传方C和上传方D对应的可信度权重值为20/(80+20)＝0.2。
作为一种可选的实施方式，数据管理方法还可以包括以下步骤：检测是否存在高于预设权重值的可信度权重值；如果不存在，则确定目标字段对应的交易存在风险，并上报风险信息。
在本申请实施例中，如果检测到存在高于预设权重值的可信度权重值，则执行步骤S140。如果检测到不存在高于预设权重值的可信度权重值，则说明目标字段对应的交易中的货品可能是危险品，或某上传方存在欺诈行为等，因此，基于当前情况服务器/终端设备可以上报用于表示交易存在风险的风险信息，以及时提醒审核人员对交易进行人工查验。
可见，实施该可选的实施方式，能够在交易存在风险的情况下，及时上报风险信息，以便各类政府或非政府机构及时对待审核信息进行人工查验，降低了风险的发生几率。
在步骤S140中，根据可信度权重值从上传方上传的数据中确定出目标数据；其中，目标数据与目标字段相对应。
作为一种可选的实施方式，根据可信度权重值从上传方上传的数据中确定出目标数据可以包括以下步骤：从可信度权重值中确定出高于预设权重值的目标可信度权重值；从上传方上传的数据中，确定出与目标可信度权重值对应的数据作为目标数据。
举例来说，如果存在上传了相同数据苹果的上传方A和上传方B，以及上传了相同数据蛇果的上传方C和上传方D，且上传方A和上传方B对应的可信度权重值0.8，上传方C和上传方D对应的可信度权重值0.2；其中，上传方A和上传方B对应的可信度权重值0.8高于预设权重值(如，0.6)，而上传方C和上传方D对应的可信度权重值0.2低于预设权重值，则终端设备/服务器可以将上传方A和上传方B上传的数据苹果作为目标数据，即目标字段(如，货品名称)为上传方上传的数据(即，苹果)。
可见，实施该可选的实施方式，能够提高各类政府或非政府机构对待审核信息的审核效率。
作为一种可选的实施方式，数据管理方法还可以包括以下步骤：如果接收到抽查指令，读取与抽查指令对应的历史交易信息并输出；其中，历史交易信息包括历史交易中每个字段对应的上传方上传的数据。
在本申请实施例中，抽查指令用于表示审核人员需要对已经由服务器/终端设备核验过的交易进行抽检；其中，交易包含一个或多个目标字段。当服务器/终端设备接收到抽查指令后，可以从历史交易信息中读取与抽查指令对应的信息并输出，以便审核人员对其进行核查。
可见，实施该可选的实施方式，能够通过审核人员抽查的方式，对某些已经经过数据信用分筛查的货品，进行再次查验，降低了由于交易不合规而造成的风险。
可见，实施图1所示的基于区块链的数据管理方法，能够提高各类政府或非政府机构对待审核信息的审核效率；以及，能够通过对上传方对应的数据信用分进行调整(或迭代)，提高各类政府或非政府机构的审核准确度；以及，能够在交易存在风险的情况下，及时上报风险信息，以便各类政府或非政府机构及时对待审核信息进行人工查验，降低了风险的发生几率。
请参阅图2，图2示意性示出了根据本申请实施例的基于区块链的数据管理装置的结构框图。如图2所示，根据本申请的一个实施例的数据管理装置包括：数据信用分确定单元210、加和结果确定单元220、比值确定单元230以及目标数据确定单元240，其中：
数据信用分确定单元210用于根据每个上传方的数据信用分，确定针对目标字段上传相同数据的上传方的总数据信用分；加和结果确定单元220用于确定所有总数据信用分的加和结果；比值确定单元230用于将总数据信用分与加和结果的比值作为可信度权重值；目标数据确定单元240用于根据可信度权重值从上传方上传的数据中确定出目标数据；其中，目标数据与目标字段相对应。
作为一种可选的实施方式，数据信用分确定单元210根据每个上传方的数据信用分，确定针对目标字段上传相同数据的上传方的总数据信用分的方式具体可 以为：数据信用分确定单元210将针对目标字段上传相同数据的上传方确定为同一个类别；数据信用分确定单元210确定每个类别对应的总数据信用分；其中，总数据信用分为针对目标字段上传相同数据的区块链节点的上传方的数据信用分之和。
可见，实施该可选的实施方式，能够便于计算每类的总数据信用分，进而提高各类政府或非政府机构对待审核信息的审核效率。
作为一种可选的实施方式，目标数据确定单元240根据可信度权重值从上传方上传的数据中确定出目标数据的方式具体可以为：目标数据确定单元240从可信度权重值中确定出高于预设权重值的目标可信度权重值；数据信用分确定单元210从上传方上传的数据中，确定出与目标可信度权重值对应的数据作为目标数据。
可见，实施该可选的实施方式，能够提高各类政府或非政府机构对待审核信息的审核效率。
作为一种可选的实施方式，数据信用分确定单元210从上传方上传的数据中，确定出与目标可信度权重值对应的数据作为目标数据之后，数据管理装置还可以包括数据信用分调整单元(未图示)，其中：
数据信用分调整单元，用于根据可信度权重值与预设权重值的比对，调整每个上传方对应的数据信用分。
可见，实施该可选的实施方式，能够通过对上传方对应的数据信用分进行调整(或迭代)，提高各类政府或非政府机构的审核准确度。
作为一种可选的实施方式，数据管理装置还可以包括可信度权重值检测单元(未图示)和风险信息上报单元(未图示)，其中：
可信度权重值检测单元，用于检测是否存在高于所述预设权重值的可信度权重值；风险信息上报单元，用于在可信度权重值检测单元检测出不存在高于所述预设权重值的可信度权重值之后，确定目标字段对应的交易存在风险，并上报风险信息。
目标数据确定单元240，具体用于在可信度权重值检测单元检测出存在高于所述预设权重值的可信度权重值之后，根据可信度权重值从上传方上传的数据中 确定出目标数据。
可见，实施该可选的实施方式，能够在交易存在风险的情况下，及时上报风险信息，以便各类政府或非政府机构及时对待审核信息进行人工查验，降低了风险的发生几率。
作为一种可选的实施方式，数据管理装置还可以包括抽查指令检测单元(未图示)和历史交易信息读取单元(未图示)，其中：
抽查指令检测单元，用于检测是否接收到抽查指令；历史交易信息读取单元，用于在抽查指令检测单元检测出接收到抽查指令之后，读取与抽查指令对应的历史交易信息并输出；其中，历史交易信息包括历史交易中每个字段对应的上传方上传的数据。
可见，实施该可选的实施方式，能够通过审核人员抽查的方式，对某些已经经过数据信用分筛查的货品，进行再次查验，降低了由于交易不合规而造成的风险。
作为另一种可选的实施方式，数据信用分确定单元210根据每个上传方的数据信用分，确定针对目标字段上传相同数据的上传方的总数据信用分的方式具体可以为：数据信用分确定单元210根据每个区块链节点的上传方的数据信用分，确定针对目标字段上传相同数据的每个上传方对应的比例系数；数据信用分确定单元210将所有上传方对应的比例系数与上传方对应的数据信用分的相乘结果之和，作为上传相同数据的上传方对应的总数据信用分。
可见，实施该可选的实施方式，能够通过上传方对应的数据信用分和比例系数相乘，最终计算得出更为准确的总数据信用分，提高了总数据信用分的数值精度，进而提高各类政府或非政府机构的审核准确度。
可见，实施图2所示的数据管理装置对应的操作，能够提高各类政府或非政府机构对待审核信息的审核效率；以及，能够通过对上传方对应的数据信用分进行调整(或迭代)，提高各类政府或非政府机构的审核准确度；以及，能够在交易存在风险的情况下，及时上报风险信息，以便各类政府或非政府机构及时对待审核信息进行人工查验，降低了风险的发生几率。
由于本申请的示例实施例的基于区块链的数据管理装置的各个功能模块与上述 基于区块链的数据管理方法的示例实施例的步骤对应，因此对于本申请装置实施例中未披露的细节，请参照本申请上述的基于区块链的数据管理方法的实施例。
请参阅图3，其示出了适于用来实现本申请实施例的电子设备的计算机系统300的结构示意图。图3示出的电子设备的计算机系统300仅是一个示例，不应对本申请实施例的功能和使用范围带来任何限制。
如图3所示，计算机系统300包括中央处理单元(CPU)301，其可以根据存储在只读存储器(ROM)302中的程序或者从存储部分308加载到随机访问存储器(RAM)303中的程序而执行各种适当的动作和处理。在RAM 303中，还存储有系统操作所需的各种程序和数据。CPU 301、ROM 302以及RAM 303通过总线304彼此相连。输入/输出(I/O)接口305也连接至总线304。
以下部件连接至I/O接口305：包括键盘、鼠标等的输入部分306；包括诸如阴极射线管(CRT)、液晶显示器(LCD)等以及扬声器等的输出部分307；包括硬盘等的存储部分308；以及包括诸如LAN卡、调制解调器等的网络接口卡的通信部分309。通信部分309经由诸如因特网的网络执行通信处理。驱动器310也根据需要连接至I/O接口305。可拆卸介质311，诸如磁盘、光盘、磁光盘、半导体存储器等等，根据需要安装在驱动器310上，以便于从其上读出的计算机程序根据需要被安装入存储部分308。
特别地，根据本申请的实施例，上文参考流程图描述的过程可以被实现为计算机软件程序。例如，本申请的实施例包括一种计算机程序产品，其包括承载在计算机可读介质上的计算机程序，该计算机程序包含用于执行流程图所示的方法的程序代码。在这样的实施例中，该计算机程序可以通过通信部分309从网络上被下载和安装，和/或从可拆卸介质311被安装。在该计算机程序被中央处理单元(CPU)301执行时，执行本申请的系统中限定的上述功能。
需要说明的是，本申请所示的计算机可读介质可以是计算机可读信号介质或者计算机可读存储介质或者是上述两者的任意组合。计算机可读存储介质例如可以是——但不限于——电、磁、光、电磁、红外线、或半导体的系统、装置或器件，或者任意以上的组合。计算机可读存储介质的更具体的例子可以包括但 不限于：具有一个或多个导线的电连接、便携式计算机磁盘、硬盘、随机访问存储器(RAM)、只读存储器(ROM)、可擦式可编程只读存储器(EPROM或闪存)、光纤、便携式紧凑磁盘只读存储器(CD-ROM)、光存储器件、磁存储器件、或者上述的任意合适的组合。在本申请中，计算机可读存储介质可以是任何包含或存储程序的有形介质，该程序可以被指令执行系统、装置或者器件使用或者与其结合使用。而在本申请中，计算机可读的信号介质可以包括在基带中或者作为载波一部分传播的数据信号，其中承载了计算机可读的程序代码。这种传播的数据信号可以采用多种形式，包括但不限于电磁信号、光信号或上述的任意合适的组合。计算机可读的信号介质还可以是计算机可读存储介质以外的任何计算机可读介质，该计算机可读介质可以发送、传播或者传输用于由指令执行系统、装置或者器件使用或者与其结合使用的程序。计算机可读介质上包含的程序代码可以用任何适当的介质传输，包括但不限于：无线、电线、光缆、RF等等，或者上述的任意合适的组合。
附图中的流程图和框图，图示了按照本申请各种实施例的系统、方法和计算机程序产品的可能实现的体系架构、功能和操作。在这点上，流程图或框图中的每个方框可以代表一个模块、程序段、或代码的一部分，上述模块、程序段、或代码的一部分包含一个或多个用于实现规定的逻辑功能的可执行指令。也应当注意，在有些作为替换的实现中，方框中所标注的功能也可以以不同于附图中所标注的顺序发生。例如，两个接连地表示的方框实际上可以基本并行地执行，它们有时也可以按相反的顺序执行，这依所涉及的功能而定。也要注意的是，框图或流程图中的每个方框、以及框图或流程图中的方框的组合，可以用执行规定的功能或操作的专用的基于硬件的系统来实现，或者可以用专用硬件与计算机指令的组合来实现。
描述于本申请实施例中所涉及到的单元可以通过软件的方式实现，也可以通过硬件的方式来实现，所描述的单元也可以设置在处理器中。其中，这些单元的名称在某种情况下并不构成对该单元本身的限定。
作为另一方面，本申请还提供了一种计算机可读介质，计算机可读存储介质可以是非易失性，也可以是易失性。该计算机可读介质可以是上述实施例中描述 的电子设备中所包含的；也可以是单独存在，而未装配入该电子设备中。上述计算机可读介质承载有一个或者多个程序，当上述一个或者多个程序被一个该电子设备执行时，使得该电子设备实现如上述实施例中所述的基于区块链的数据管理方法。
例如，所述的电子设备可以实现如图1中所示的：步骤S110，根据每个区块链节点的上传方的数据信用分，确定针对目标字段上传相同数据的上传方的总数据信用分；步骤S120，确定所有总数据信用分的加和结果；步骤S130，将总数据信用分与加和结果的比值作为可信度权重值；步骤S140，根据可信度权重值从上传方上传的数据中确定出目标数据；其中，目标数据与目标字段相对应。
通过以上的实施方式的描述，本领域的技术人员易于理解，这里描述的示例实施方式可以通过软件实现，也可以通过软件结合必要的硬件的方式来实现。因此，根据本申请实施方式的技术方案可以以软件产品的形式体现出来，该软件产品可以存储在一个非易失性存储介质(可以是CD-ROM，U盘，移动硬盘等)中或网络上，包括若干指令以使得一台计算设备(可以是个人计算机、服务器、触控终端、或者网络设备等)执行根据本申请实施方式的方法。
应当理解的是，本申请并不局限于上面已经描述并在附图中示出的精确结构，并且可以在不脱离其范围进行各种修改和改变。本申请的范围仅由所附的权利要求来限制。

Claims (20)

  1. 一种基于区块链的数据管理方法，其中，包括：
    根据每个区块链节点的上传方的数据信用分，确定针对目标字段上传相同数据的上传方的总数据信用分；
    确定所有所述总数据信用分的加和结果；
    将所述总数据信用分与所述加和结果的比值作为可信度权重值；
    根据所述可信度权重值从所述上传方上传的数据中确定出目标数据；其中，所述目标数据与所述目标字段相对应。
  2. 根据权利要求1所述的方法，其中，所述根据每个区块链节点的上传方的数据信用分，确定针对目标字段上传相同数据的上传方的总数据信用分包括：
    将针对目标字段上传相同数据的上传方确定为同一个类别；
    确定每个类别对应的总数据信用分；其中，所述总数据信用分为针对目标字段上传相同数据的区块链节点的上传方的数据信用分之和。
  3. 根据权利要求2所述的方法，其中，所述根据所述可信度权重值从所述上传方上传的数据中确定出目标数据包括：
    从所述可信度权重值中确定出高于预设权重值的目标可信度权重值；
    从所述上传方上传的数据中，确定出与所述目标可信度权重值对应的数据作为目标数据。
  4. 根据权利要求3所述的方法，其中，所述确定出与所述目标可信度权重值对应的数据作为目标数据之后，所述方法还包括：
    根据所述可信度权重值与所述预设权重值的比对，调整每个所述上传方对应的数据信用分。
  5. 根据权利要求4所述的方法，其中，所述方法还包括：
    检测是否存在高于所述预设权重值的可信度权重值；
    如果不存在，则确定所述目标字段对应的交易存在风险，并上报 风险信息。
  6. 根据权利要求5所述的方法，其中，所述方法还包括：
    如果接收到抽查指令，读取与所述抽查指令对应的历史交易信息并输出；其中，所述历史交易信息包括历史交易中每个字段对应的上传方上传的数据。
  7. 根据权利要求1所述的方法，其中，所述根据每个区块链节点的上传方的数据信用分，确定针对目标字段上传相同数据的上传方的总数据信用分包括：
    根据每个区块链节点的上传方的数据信用分，确定针对目标字段上传相同数据的每个上传方对应的比例系数；
    将所有所述上传方对应的比例系数与所述上传方对应的数据信用分的相乘结果之和，作为上传相同数据的所述上传方对应的总数据信用分。
  8. 一种基于区块链的数据管理装置，其中，包括：
    数据信用分确定单元，用于根据每个上传方的数据信用分，确定针对目标字段上传相同数据的上传方的总数据信用分；
    加和结果确定单元，用于确定所有所述总数据信用分的加和结果；
    比值确定单元，用于将所述总数据信用分与所述加和结果的比值作为可信度权重值；
    目标数据确定单元，用于根据所述可信度权重值从所述上传方上传的数据中确定出目标数据；其中，所述目标数据与所述目标字段相对应。
  9. 一种电子设备，其中，包括：
    一个或多个处理器；
    存储装置，用于存储一个或多个程序，当所述一个或多个程序被所述一个或多个处理器执行时，使得所述一个或多个处理器实现基于区块链的数据管理方法，所述基于区块链的数据管理方法， 具体包括如下步骤：
    根据每个区块链节点的上传方的数据信用分，确定针对目标字段上传相同数据的上传方的总数据信用分；
    确定所有所述总数据信用分的加和结果；
    将所述总数据信用分与所述加和结果的比值作为可信度权重值；
    根据所述可信度权重值从所述上传方上传的数据中确定出目标数据；其中，所述目标数据与所述目标字段相对应。
  10. 根据权利要求9所述的电子设备，其中，所述根据每个区块链节点的上传方的数据信用分，确定针对目标字段上传相同数据的上传方的总数据信用分包括：
    将针对目标字段上传相同数据的上传方确定为同一个类别；
    确定每个类别对应的总数据信用分；其中，所述总数据信用分为针对目标字段上传相同数据的区块链节点的上传方的数据信用分之和。
  11. 根据权利要求10所述的电子设备，其中，所述根据所述可信度权重值从所述上传方上传的数据中确定出目标数据包括：
    从所述可信度权重值中确定出高于预设权重值的目标可信度权重值；
    从所述上传方上传的数据中，确定出与所述目标可信度权重值对应的数据作为目标数据。
  12. 根据权利要求11所述的电子设备，其中，所述确定出与所述目标可信度权重值对应的数据作为目标数据之后，还包括：
    根据所述可信度权重值与所述预设权重值的比对，调整每个所述上传方对应的数据信用分。
  13. 根据权利要求12所述的电子设备，其中，还包括：
    检测是否存在高于所述预设权重值的可信度权重值；
    如果不存在，则确定所述目标字段对应的交易存在风险，并上报风险信息。
  14. 根据权利要求13所述的电子设备，其中，还包括：
    如果接收到抽查指令，读取与所述抽查指令对应的历史交易信息并输出；其中，所述历史交易信息包括历史交易中每个字段对应的上传方上传的数据。
  15. 根据权利要求9所述的电子设备，其中，所述根据每个区块链节点的上传方的数据信用分，确定针对目标字段上传相同数据的上传方的总数据信用分包括：
    根据每个区块链节点的上传方的数据信用分，确定针对目标字段上传相同数据的每个上传方对应的比例系数；
    将所有所述上传方对应的比例系数与所述上传方对应的数据信用分的相乘结果之和，作为上传相同数据的所述上传方对应的总数据信用分。
  16. 一种计算机可读介质，其上存储有计算机程序，其中，所述程序被处理器执行时实现基于区块链的数据管理方法，所述基于区块链的数据管理方法，具体包括如下步骤：根据每个区块链节点的上传方的数据信用分，确定针对目标字段上传相同数据的上传方的总数据信用分；
    确定所有所述总数据信用分的加和结果；
    将所述总数据信用分与所述加和结果的比值作为可信度权重值；
    根据所述可信度权重值从所述上传方上传的数据中确定出目标数据；其中，所述目标数据与所述目标字段相对应。
  17. 根据权利要求16所述的计算机可读介质，其中，所述根据每个区块链节点的上传方的数据信用分，确定针对目标字段上传相同数据的上传方的总数据信用分包括：
    将针对目标字段上传相同数据的上传方确定为同一个类别；
    确定每个类别对应的总数据信用分；其中，所述总数据信用分为针对目标字段上传相同数据的区块链节点的上传方的数据信用分之和。
  18. 根据权利要求16所述的计算机可读介质，其中，所述根据所述可信度权重值从所述上传方上传的数据中确定出目标数据包括：
    从所述可信度权重值中确定出高于预设权重值的目标可信度权重值；
    从所述上传方上传的数据中，确定出与所述目标可信度权重值对应的数据作为目标数据。
  19. 根据权利要求16所述的计算机可读介质，其中，所述确定出与所述目标可信度权重值对应的数据作为目标数据之后，还包括：
    根据所述可信度权重值与所述预设权重值的比对，调整每个所述上传方对应的数据信用分。
  20. 根据权利要求16所述的计算机可读介质，其中，所述根据每个区块链节点的上传方的数据信用分，确定针对目标字段上传相同数据的上传方的总数据信用分包括：
    根据每个区块链节点的上传方的数据信用分，确定针对目标字段上传相同数据的每个上传方对应的比例系数；
    将所有所述上传方对应的比例系数与所述上传方对应的数据信用分的相乘结果之和，作为上传相同数据的所述上传方对应的总数据信用分。
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