CN114143017A - Block chain data providing method, device, system and storage medium - Google Patents
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Abstract
The disclosure provides a block chain data providing method, a block chain data providing device, a network system and a storage medium, and relates to the technical field of block chains. The block chain data providing method of the present disclosure includes: under the condition that data need to be uploaded to a block chain, randomly selecting a predetermined number of evaluation nodes, and respectively acquiring the data to be uploaded from respective predetermined sources by the selected evaluation nodes; acquiring the output value of each evaluation node; determining a credibility value according to the output value of each evaluation node, and determining the credibility of the credibility value according to the weight of the evaluation node of which the output value accords with the credibility value; and providing the credibility value and the credibility for the block link point to be uploaded. By the method, before data uplink is stored, data generation and credibility evaluation can be performed by randomly selecting multiple nodes, the reliability of uplink data is improved, the probability of irreversible pollution of error data to block chain data is reduced, and the reliability of the block chain data is improved from the perspective of a data source.
Description
Technical Field
The present disclosure relates to the field of block chain technologies, and in particular, to a method, an apparatus, a network system, and a storage medium for providing block chain data.
Background
The block chain technology is increasingly widely applied based on the characteristics of 'unforgeable', 'full-course trace', 'traceable', 'public transparency', 'collective maintenance' and the like of data. Based on the characteristics, the block chain technology lays a solid 'trust' foundation, creates a reliable 'cooperation' mechanism and has wide application prospect.
Disclosure of Invention
One object of the present disclosure is to improve reliability of block chain data.
According to an aspect of some embodiments of the present disclosure, there is provided a method for providing block chain data, including: under the condition that data need to be uploaded to a block chain, randomly selecting a predetermined number of evaluation nodes, and respectively acquiring the data to be uploaded from respective predetermined sources by the selected evaluation nodes; acquiring the output value of each evaluation node; determining a credibility value according to the output value of each evaluation node, and determining the credibility of the credibility value according to the weight of the evaluation node of which the output value accords with the credibility value; and providing the credibility value and the credibility for the block link point to be uploaded.
In some embodiments, the block chain data providing method further comprises: and adjusting the weight of the evaluation node according to the output value of each evaluation node and the determined credibility value.
In some embodiments, determining the trustworthy value from the output values of the respective evaluation nodes comprises: and under the condition that the credible value to be generated is a fixed value, determining the data with the largest occurrence frequency in the output values of the evaluation nodes as the credible value.
In some embodiments, determining the trustworthy value from the output values of the respective evaluation nodes comprises: and under the condition that the credible value to be generated is the fluctuation value, removing the minimum value and the maximum value from the output values, and determining the average value of the remaining output values as the credible value.
In some embodiments, determining the trustworthiness of the trustworthy value from the weights of the evaluation nodes whose output values meet the trustworthy value comprises: and determining the sum of the weights of the evaluation nodes of which the output values accord with the credibility values, wherein the ratio of the sum of the weights of the selected evaluation nodes is the credibility of the credibility values.
In some embodiments, adjusting the weight of the evaluation node comprises: and under the condition that the credible value to be generated is a fixed value, increasing the weight of the evaluation node with the output value equal to the credible value by a preset first value, and updating the weight of the evaluation node with the output value not equal to the credible value to a preset minimum value, wherein the preset first value and the preset minimum value are more than 0.
In some embodiments, adjusting the weight of the evaluation node comprises: under the condition that the credible value to be generated is a fluctuation value, determining the error ratio of the output value of each evaluation node and the credible value; increasing the weight of the evaluation node of which the error proportion of the output value is smaller than the predetermined first proportion by a predetermined second value; maintaining the weight of the evaluation node with the error proportion of the output value being greater than or equal to a preset first proportion and smaller than a second preset proportion unchanged; reducing the weight of the evaluation node of which the error proportion of the output value is greater than or equal to a predetermined second proportion and less than a predetermined third proportion by a predetermined third value; updating the weight of the evaluation node of which the error proportion of the output value is greater than or equal to a preset fourth proportion to a preset minimum value; wherein the predetermined first ratio < second predetermined ratio < predetermined third ratio < predetermined fourth ratio, the predetermined second value, the predetermined third value and the predetermined minimum value are greater than 0.
In some embodiments, the error ratio is a ratio of an absolute value of a difference of the output value and the confidence value to the confidence value.
By the method, before data uplink is stored, data generation and credibility evaluation can be performed by randomly selecting multiple nodes, the reliability of uplink data is improved, the probability of irreversible pollution of error data to block chain data is reduced, and the reliability of the block chain data is improved from the perspective of a data source.
According to an aspect of some embodiments of the present disclosure, there is provided a block chain data providing apparatus, including: the evaluation node selection unit is configured to randomly select a predetermined number of evaluation nodes under the condition that data needs to be uploaded to the block chain; the plurality of evaluation nodes are configured to acquire data to be uploaded from a predetermined source under the selected condition; an evaluation node output value acquisition unit configured to acquire an output value of each evaluation node; the credibility value and credibility determining unit is configured to determine a credibility value according to the output value of each evaluation node and determine the credibility of the credibility value according to the weight of the evaluation node of which the output value accords with the credibility value; and the data uploading unit is configured to provide the credibility value and the credibility for block link point uploading.
In some embodiments, the block chain data providing apparatus further comprises: and the weight updating unit is configured to adjust the weight of the evaluation node according to the output value of each evaluation node and the determined credibility value.
According to an aspect of some embodiments of the present disclosure, there is provided a block chain data providing apparatus, including: a memory; and a processor coupled to the memory, the processor configured to perform any one of the above-mentioned block chain data providing methods based on instructions stored in the memory.
The device can randomly select multiple nodes to perform data generation and credibility evaluation before data uplink is stored, reliability of uplink data is improved, probability of irreversible pollution of error data to block chain data is reduced, and reliability of the block chain data is improved from the perspective of a data source.
According to an aspect of some embodiments of the present disclosure, a computer-readable storage medium is proposed, on which computer program instructions are stored, which instructions, when executed by a processor, implement the steps of any one of the above-mentioned blockchain data providing methods.
By executing the instructions on the storage medium, before data uplink is stored, multiple nodes are randomly selected to perform data generation and credibility evaluation, the reliability of uplink data is improved, the probability of irreversible pollution of error data to block chain data is reduced, and the reliability of the block chain data is improved from the perspective of a data source.
According to an aspect of some embodiments of the present disclosure, there is provided a blockchain system, including: any one of the above block chain data providing devices; and a blockchain configured to activate the blockchain data providing device to generate a confidence value and a confidence level in case of data needing to be uploaded; and acquiring a credibility value and credibility and uplink storing.
The block chain system can randomly select multiple nodes to perform data generation and credibility evaluation before data uplink is stored, reliability of uplink data is improved, probability of irreversible pollution of error data to the block chain data is reduced, and reliability of the block chain data is improved from the perspective of a data source.
Drawings
The accompanying drawings, which are included to provide a further understanding of the disclosure and are incorporated in and constitute a part of this disclosure, illustrate embodiments of the disclosure and together with the description serve to explain the disclosure and not to limit the disclosure. In the drawings:
fig. 1 is a flow chart of some embodiments of a blockchain data providing method of the present disclosure.
Fig. 2 is a flowchart of another embodiment of a method for providing blockchain data according to the present disclosure.
Fig. 3 is a schematic diagram of some embodiments of a blockchain data providing apparatus according to the present disclosure.
Fig. 4 is a schematic diagram of another embodiment of a device for providing block chain data according to the present disclosure.
Fig. 5 is a schematic diagram of a block chain data providing apparatus according to still other embodiments of the disclosure.
Fig. 6 is a schematic diagram of some embodiments of a blockchain system of the present disclosure.
Detailed Description
The technical solution of the present disclosure is further described in detail by the accompanying drawings and examples.
The inventor finds that the block chain is a closed system, external data cannot be actively acquired on the chain, and an intermediary system is needed to write external information into the block chain to complete the intercommunication between the block chain and the external world. In the block chain technique, the credibility of the external information is not guaranteed compared to the credible environment on the chain, and the uplink of the external error data pollutes the data on the chain.
A flow diagram of some embodiments of a blockchain data providing method of the present disclosure is shown in fig. 1.
In step 101, in a case that data needs to be uploaded to the block chain, a predetermined number of evaluation nodes are randomly selected, and the selected evaluation nodes respectively obtain data to be uploaded from respective predetermined sources. In some embodiments, the operation of selecting a predetermined number of evaluation nodes may be triggered in case of data request issued by the blockchain or external uplink request received by the blockchain. In some embodiments, the selected evaluation nodes form a working group of the data uploading operation.
In some embodiments, the evaluation nodes are independent and independent from each other, and the evaluation nodes may have different data sources, so as to respectively obtain data of the same event from the respective data sources, and the obtained data may be the same or different.
In step 102, the output values of the respective evaluation nodes are acquired. In some embodiments, the evaluation node is pre-stored with processing algorithms for the data, and generates output values based on the predetermined algorithms from the data to be uploaded obtained from the external data source.
In step 103, a confidence value is determined according to the output value of each evaluation node, and the confidence level of the confidence value is determined according to the weight of the evaluation node whose output value meets the confidence value. In some embodiments, an initial weight may be set for each evaluation node, and the weight of each evaluation node is modified during operation according to its performance, where the weight represents how well each node is in data acquisition, and the higher the weight is, the better the historical performance is. In some embodiments, the initial weight of all nodes may be set to W-5, and the maximum and minimum weights are W respectivelymax＝10，Wmin＝1。
In step 104, the confidence value and confidence level are provided to the block link point for uploading.
By the method, the reliability of the external information can be evaluated before data uplink, a plurality of external information copies are obtained by using a depocenter intermediary system, evaluation and comparison are carried out, the reliability and the reliability value are finally given after algorithm processing, so that the reliability of uplink data is improved, the probability of irreversible pollution of error data to block chain data is reduced, and the reliability of the block chain data is improved from the perspective of a data source.
In some embodiments, as shown in fig. 1, the method for providing block chain data may further include step 105: and adjusting the weight of the evaluation node according to the output value of each evaluation node and the determined credibility value.
By the method, the weight of the output value of the evaluation node can be adjusted based on the reliability of the output value of the evaluation node, the evaluation accuracy is improved, the change of the state of the evaluation node can be tracked in time, the evaluation on the evaluation node is updated in time, and the timeliness is improved.
A flow chart of further embodiments of the blockchain data providing method of the present disclosure is shown in fig. 2.
In step 201, in a case that data needs to be uploaded to the block chain, a predetermined number of evaluation nodes are randomly selected, and the selected evaluation nodes respectively obtain data to be uploaded from respective predetermined sources. In some embodiments, the predetermined number is not less than 10, and the node selection may be performed by a predetermined random algorithm.
In step 202, the output values of the respective evaluation nodes are acquired. In some embodiments, the evaluation node is pre-stored with processing algorithms for the data, and generates output values based on the predetermined algorithms from the data to be uploaded obtained from the external data source.
In step 203, it is determined whether the confidence value that needs to be generated is a fixed value. If the value is a fixed value, go to step 204; otherwise, the confidence value to be generated is a fluctuating value, such as data fluctuating over time, and step 205 is executed. In some embodiments, it may also be determined whether the trusted value that needs to be generated is a fluctuating value, and similarly, step 205 is performed if it is, and step 204 is performed otherwise.
In some embodiments, a fixed value is an invariant value, such as the value of a certain equation, the time at which a certain event occurs, etc.; the value of the fluctuation value along with the time is different at different time, such as stock price and the like. The type of the trusted value to be generated can be determined according to the application scenario of the blockchain, the application scenario and the attribute of the data to be uploaded currently, and the like.
In step 204, the data that appears most frequently in the output values of the evaluation nodes is determined as the trusted value. Step 206 is then performed.
For example, for a workgroup of n evaluation nodes, each evaluation node outputs an output value Ri(i is an evaluation node identification), thereby obtaining a sequence of output values R1，R2...Rn. From R1～RnAnd screening out the value with the most occurrence times, namely the determined credible value R.
Calculating the ratio P of the sum of the weights of the evaluation nodes with the output value R to the total weight value of the working groupw：
Wherein G is a set of evaluation nodes with an output value of R, n (G) is the number of evaluation nodes with an output value of R, PaTo evaluate the weight of node a, the confidence level T ═ Pw。
In step 205, the minimum and maximum values are removed from the output values, and the average of the remaining output values is determined as the confidence value. Step 206 is then performed.
For example, for a workgroup of n evaluation nodes, each evaluation node outputs an output value RiThereby obtaining a sequence of output values R1，R2...Rn。
The maximum value R is removed in the sequencemaxAnd a minimum value RminObtaining the set G { R }a,Rb...}. And averaging the elements in the set G to obtain a credible value R.
Calculating the ratio P of the sum of the weights of the evaluation nodes corresponding to the output values in the set G to the total weight value of the working groupw：
Wherein n (G) is the number of output values in the set G (counting when different nodes output the same value respectively), PaTo evaluate the weight of node a, the confidence level T ═ Pw。
In step 206, the sum of the weights of the evaluation nodes whose output values meet the confidence value is determined, and the ratio of the sum of the weights of the selected evaluation nodes is the confidence level of the confidence value, and step 207 and step 208 are further performed.
In step 207, the confidence value and confidence level are provided to the block link point for uploading.
In step 208, if the credible value that needs to be generated is a fixed value, the operation in step 209 is executed; if the confidence value to be generated is a fluctuation value, step 210 is executed.
In step 209, the weight of the evaluation node whose output value is equal to the trusted value is increased by a predetermined first value, and the weight of the evaluation node whose output value is not equal to the trusted value is updated to a predetermined minimum value, in some embodiments, the predetermined first value is 1 and the predetermined minimum value is 1.
In step 210, the weight of the evaluation node is adjusted according to a weight adjustment policy for the fluctuation value, which may specifically include: an error ratio of the output value of each evaluation node to the confidence value is determined, and in some embodiments the error ratio is a ratio of an absolute value of a difference between the output value and the confidence value to the confidence value. Increasing the weight of the evaluation node of which the error proportion of the output value is smaller than the predetermined first proportion by a predetermined second value; maintaining the weight of the evaluation node with the error proportion of the output value being greater than or equal to a preset first proportion and smaller than a second preset proportion unchanged; reducing the weight of the evaluation node of which the error proportion of the output value is greater than or equal to a predetermined second proportion and less than a predetermined third proportion by a predetermined third value; updating the weight of the evaluation node of which the error proportion of the output value is greater than or equal to a preset fourth proportion to a preset minimum value; wherein the predetermined first ratio < the second predetermined ratio < the predetermined third ratio < the predetermined fourth ratio.
In some embodiments, for the evaluation node i, the error ratio E ═ R-Ri|/R。
If the error is less than 10%, adding 1 to the weight, wherein W is W + 1;
if the error is between 10% and 30%, the weight is unchanged, and W is equal to W;
if the error is between 30% and 50%, the weight is reduced by 3, and W is W-3;
if the error is more than 50%, the weight is adjusted to the minimum value of 1, and W is equal to 1.
By the method, the evaluation node can be randomly selected, the randomness and verifiability of the node are ensured, and the external attack can be resisted favorably; a group of evaluation nodes going to the center are used for acquiring data to resist the Byzantine behavior, and the method is more reliable than the traditional centralized form; the credibility is based on a weight feedback algorithm, can be updated in real time, can accurately reflect the credibility of currently uploaded data, and is convenient for credibility consideration when the block chain data is used in the later period.
In some embodiments, the above-described method for providing blockchain data can be applied to various blockchain scenarios, for example, a chinese telecom blockchain platform is a closed blockchain, and it is often necessary to access external data, such as clearing bills, charge roaming data, etc., due to business relations alone, and thus, the method can provide data credibility assessment for the telecom blockchain platform.
A schematic diagram of some embodiments of the block chain data providing apparatus of the present disclosure is shown in fig. 3.
The evaluation node selection unit 301 can randomly select a predetermined number of evaluation nodes in a case where data needs to be uploaded to the blockchain. In some embodiments, the operation of selecting a predetermined number of evaluation nodes may be triggered in case of data request issued by the blockchain or external uplink request received by the blockchain. In some embodiments, the selected evaluation nodes form a working group of the data uploading operation.
Each evaluation node 3021 to 302n is capable of obtaining data to be uploaded from a predetermined source under the selected condition. In some embodiments, n is a positive integer greater than 10. The evaluation nodes are independent and do not influence each other, and the evaluation nodes can have different data sources, so that the data of the same event can be acquired from the respective data sources respectively, and the acquired data can be the same or different. In some embodiments, the evaluation node is pre-stored with processing algorithms for the data, and generates output values based on the predetermined algorithms from the data to be uploaded obtained from the external data source.
The evaluation node output value acquisition unit 303 can acquire the output value of each evaluation node.
The confidence value and confidence level determination unit 304 can determine a confidence level from the output value of each evaluation node, and determine the confidence level of the confidence value from the weight of the evaluation node whose output value matches the confidence level. In some embodiments, an initial weight may be set for each evaluation node, and the weight of each evaluation node may be modified during operation according to its performance.
The data uploading unit 305 can provide the confidence level and confidence value determined by the confidence level determination unit 304 to the block link point for uploading.
The device can randomly select multiple nodes to perform data generation and credibility evaluation before data uplink is stored, reliability of uplink data is improved, probability of irreversible pollution of error data to block chain data is reduced, and reliability of the block chain data is improved from the perspective of a data source.
In some embodiments, as shown in fig. 3, the blockchain data providing apparatus may further include a weight updating unit 306 capable of adjusting the weight of each evaluation node according to the output value of each evaluation node and the determined confidence value.
The device can adjust the weight of the output value of the evaluation node based on the reliability of the output value of the evaluation node, improve the evaluation accuracy, track the change of the self state of the evaluation node in time, update the evaluation of the evaluation node in time and improve the timeliness.
In some embodiments, the data of the upload block chain may be divided into two types, i.e., a fixed value and a fluctuating value, and the confidence value and confidence level determining unit 304 may determine the confidence value in different manners according to different data types. For example, if the credible value to be generated is a fixed value, determining the data with the largest occurrence number in the output values of the evaluation nodes as the credible value; if the credible value needing to be generated is a fluctuation value, the minimum value and the maximum value are removed from the output values, and the average value of the remaining output values is determined as the credible value.
The device can improve the rationality and reliability of data selection and evaluation according to different distinguishing and processing modes of data types.
In some embodiments, the weight updating unit 306 may also adopt different adjustment manners for the weights of the evaluation nodes according to different data types. For example, if the credible value required to be generated is a fixed value, increasing the weight of the evaluation node with the output value equal to the credible value by a predetermined first value, and updating the weight of the evaluation node with the output value not equal to the credible value to a predetermined minimum value; if the credible value to be generated is a fluctuation value, the error ratios of the output values of the evaluation nodes and the credible value may be determined, the error ratios are divided into sections, and the weights of the evaluation nodes are processed differently according to the error ratios, and the specific processing manner may be as shown in step 210.
The device can perform different processing on the weight of the evaluation node according to different data types, and the reasonability and the reliability of node evaluation are improved.
Fig. 4 is a schematic structural diagram of an embodiment of a block chain data providing apparatus according to the present disclosure. The block chain data providing apparatus includes a memory 401 and a processor 402. Wherein: the memory 401 may be a magnetic disk, flash memory, or any other non-volatile storage medium. The memory is for storing instructions in the corresponding embodiments of the blockchain data providing method above. The processor 402 is coupled to the memory 401 and may be implemented as one or more integrated circuits, such as a microprocessor or microcontroller. The processor 402 is configured to execute instructions stored in a memory, so as to improve the reliability of uplink data and improve the reliability of blockchain data.
In one embodiment, as also shown in fig. 5, the block chain data providing apparatus 500 includes a memory 501 and a processor 502. The processor 502 is coupled to the memory 501 by a BUS 503. The blockchain data providing device 500 may also be connected to an external storage device 505 through a storage interface 504 for calling external data, and may also be connected to a network or another computer system (not shown) through a network interface 506. And will not be described in detail herein.
In this embodiment, the data instructions are stored in the memory and processed by the processor, so as to improve the reliability of the uplink data and improve the reliability of the block chain data.
In another embodiment, a computer readable storage medium has stored thereon computer program instructions which, when executed by a processor, implement the steps of the method in the corresponding embodiment of the block chain data providing method. As will be appreciated by one skilled in the art, embodiments of the present disclosure may be provided as a method, apparatus, or computer program product. Accordingly, the present disclosure may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, the present disclosure may take the form of a computer program product embodied on one or more computer-usable non-transitory storage media (including, but not limited to, disk storage, CD-ROM, optical storage, and the like) having computer-usable program code embodied therein.
A schematic diagram of some embodiments of the blockchain system of the present disclosure is shown in fig. 6.
The blockchain 61 may be any blockchain in the related art, and one or more nodes in the blockchain may be connected to the blockchain data providing device 62.
The block chain data providing means 62 may be any of those mentioned above. In some embodiments, the block chain data provider 62 may include a plurality of evaluation nodes (nodes in the figure), each of which has a respective weight (e.g., W in the figure)1～Wn). Each evaluation node is connected to one or more external data sources, which are not all the same.
The block chain system can randomly select multiple nodes to perform data generation and credibility evaluation before data uplink is stored, reliability of uplink data is improved, irreversible pollution of error data to the block chain data is reduced, and reliability of the block chain data is improved from the perspective of a data source.
In some embodiments, the blockchain system may be a decentered points redemption system. Taking an operator system as an example, the system has a large amount of points and strong public credibility in society, and in order to promote the value transfer of the points, a central transaction system is designed to exchange various points. In the point exchange system, information such as the number of various points and exchange ratio from the outside is required to be continuously obtained, and the block chain system in the above can perform credible evaluation on the latest acquired data, thereby playing a critical guiding role on the system.
In some embodiments, the blockchain system may be a decentralised financial item (DeFi). The decentralised financial project may issue stable currencies in blockchain projects for exchange or transaction with other types of currency. The price of the stable currency to other currencies needs to be obtained from the outside and converted. The blockchain system can acquire price information from external transactions, and perform feasibility evaluation, so that the blockchain system plays a key guiding role for the system.
The present disclosure is described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems) and computer program products according to embodiments of the disclosure. It will be understood that each flow and/or block of the flow diagrams and/or block diagrams, and combinations of flows and/or blocks in the flow diagrams and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instruction means which implement the function specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
Thus far, the present disclosure has been described in detail. Some details that are well known in the art have not been described in order to avoid obscuring the concepts of the present disclosure. It will be fully apparent to those skilled in the art from the foregoing description how to practice the presently disclosed embodiments.
The methods and apparatus of the present disclosure may be implemented in a number of ways. For example, the methods and apparatus of the present disclosure may be implemented by software, hardware, firmware, or any combination of software, hardware, and firmware. The above-described order for the steps of the method is for illustration only, and the steps of the method of the present disclosure are not limited to the order specifically described above unless specifically stated otherwise. Further, in some embodiments, the present disclosure may also be embodied as programs recorded in a recording medium, the programs including machine-readable instructions for implementing the methods according to the present disclosure. Thus, the present disclosure also covers a recording medium storing a program for executing the method according to the present disclosure.
Finally, it should be noted that: the above examples are intended only to illustrate the technical solutions of the present disclosure and not to limit them; although the present disclosure has been described in detail with reference to preferred embodiments, those of ordinary skill in the art will understand that: modifications to the specific embodiments of the disclosure or equivalent substitutions for parts of the technical features may still be made; all such modifications are intended to be included within the scope of the claims of this disclosure without departing from the spirit thereof.
Claims (13)
1. A method for providing blockchain data, comprising:
under the condition that data need to be uploaded to a block chain, randomly selecting a predetermined number of evaluation nodes, and respectively acquiring the data to be uploaded from respective predetermined sources by the selected evaluation nodes;
acquiring the output value of each evaluation node;
determining a credibility value according to the output value of each evaluation node, and determining the credibility of the credibility value according to the weight of the evaluation node of which the output value accords with the credibility value;
and providing the credibility value and the credibility for the block link point to be uploaded.
2. The method of claim 1, further comprising:
and adjusting the weight of each evaluation node according to the output value of each evaluation node and the determined credibility value.
3. The method of claim 1, wherein said determining a trustworthy value from the output values of the respective evaluation nodes comprises:
and under the condition that the credible value to be generated is a fixed value, determining data with the largest occurrence frequency in the output values of the evaluation nodes as the credible value.
4. The method of claim 1, wherein said determining a trustworthy value from the output values of the respective evaluation nodes comprises:
and under the condition that the credible value to be generated is a fluctuation value, removing the minimum value and the maximum value from the output values, and determining the average value of the remaining output values as the credible value.
5. The method of claim 3 or 4, wherein said determining the trustworthiness of the trustworthy value from the weights of the evaluation nodes whose output values meet the trustworthy value comprises:
and determining the sum of the weights of the evaluation nodes of which the output values accord with the credibility values, wherein the ratio of the sum of the weights of the selected evaluation nodes is the credibility of the credibility values.
6. The method of claim 2, wherein the adjusting the weight of the evaluation node comprises:
and under the condition that the credible value to be generated is a fixed value, increasing the weight of the evaluation node with the output value equal to the credible value by a preset first value, and updating the weight of the evaluation node with the output value not equal to the credible value to a preset minimum value, wherein the preset first value and the preset minimum value are more than 0.
7. The method of claim 2, wherein the adjusting the weight of the evaluation node comprises:
under the condition that the credible value to be generated is a fluctuation value, determining the error ratio of the output value of each evaluation node and the credible value;
increasing the weight of the evaluation node of which the error proportion of the output value is smaller than the predetermined first proportion by a predetermined second value;
maintaining the weight of the evaluation node with the error proportion of the output value being greater than or equal to a preset first proportion and smaller than a second preset proportion unchanged;
reducing the weight of the evaluation node whose error proportion of the output value is greater than or equal to a predetermined second proportion and less than a predetermined third proportion by a predetermined third value;
updating the weight of the evaluation node of which the error proportion of the output value is greater than or equal to a predetermined fourth proportion to a predetermined minimum value;
wherein the predetermined first ratio < second predetermined ratio < predetermined third ratio < predetermined fourth ratio, the predetermined second value, the predetermined third value and the predetermined minimum value are greater than 0.
8. The method of claim 7, wherein the error ratio is a ratio of an absolute value of a difference of the output value and the confidence value to the confidence value.
9. A block chain data providing apparatus comprising:
the evaluation node selection unit is configured to randomly select a predetermined number of evaluation nodes under the condition that data needs to be uploaded to the block chain;
the plurality of evaluation nodes are configured to acquire data to be uploaded from a predetermined source under the selected condition;
an evaluation node output value acquisition unit configured to acquire an output value of each evaluation node;
a credibility value and credibility determination unit configured to determine a credibility value from an output value of each evaluation node, and determine the credibility of the credibility value from the weight of the evaluation node whose output value meets the credibility value;
a data uploading unit configured to provide the confidence value and the confidence level to a block link point for uploading.
10. The apparatus of claim 9, further comprising:
a weight updating unit configured to adjust the weights of the evaluation nodes according to the output values of the respective evaluation nodes and the determined credibility value.
11. A block chain data providing apparatus comprising:
a memory; and
a processor coupled to the memory, the processor configured to perform the method of any of claims 1-8 based on instructions stored in the memory.
12. A computer readable storage medium having stored thereon computer program instructions which, when executed by a processor, implement the steps of the method of any one of claims 1 to 8.
13. A blockchain network system, comprising:
the blockchain data providing apparatus according to any one of claims 9 to 11; and
the blockchain is configured to activate the blockchain data providing device to generate a credibility value and a credibility when the data needs to be uploaded; and acquiring the credibility value and the credibility and uploading for storage.
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