CN112685769A - Data processing method and device of block chain and electronic equipment - Google Patents
Data processing method and device of block chain and electronic equipment Download PDFInfo
- Publication number
- CN112685769A CN112685769A CN202011565155.1A CN202011565155A CN112685769A CN 112685769 A CN112685769 A CN 112685769A CN 202011565155 A CN202011565155 A CN 202011565155A CN 112685769 A CN112685769 A CN 112685769A
- Authority
- CN
- China
- Prior art keywords
- node
- nodes
- target
- data
- calculation
- 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
- 238000003672 processing method Methods 0.000 title claims description 14
- 238000004364 calculation method Methods 0.000 claims abstract description 92
- 238000013500 data storage Methods 0.000 claims abstract description 38
- 238000000034 method Methods 0.000 claims abstract description 34
- 238000012216 screening Methods 0.000 claims abstract description 26
- 239000012634 fragment Substances 0.000 claims abstract description 18
- 230000004044 response Effects 0.000 claims abstract description 15
- 238000012545 processing Methods 0.000 claims description 40
- 238000012544 monitoring process Methods 0.000 claims description 6
- 230000008569 process Effects 0.000 description 14
- 238000010586 diagram Methods 0.000 description 5
- 238000005516 engineering process Methods 0.000 description 4
- 230000006870 function Effects 0.000 description 4
- 230000002159 abnormal effect Effects 0.000 description 2
- 238000001914 filtration Methods 0.000 description 2
- 238000013461 design Methods 0.000 description 1
- 239000004744 fabric Substances 0.000 description 1
- 238000012986 modification Methods 0.000 description 1
- 230000004048 modification Effects 0.000 description 1
- 230000008520 organization Effects 0.000 description 1
- 230000000750 progressive effect Effects 0.000 description 1
- 238000012795 verification Methods 0.000 description 1
Images
Landscapes
- Information Retrieval, Db Structures And Fs Structures Therefor (AREA)
Abstract
The method is applied to scheduling nodes generated by selection of a block chain, and comprises the steps of determining nodes with data storage attributes meeting screening conditions as initial nodes in the nodes on the block chain, determining at least two target computing nodes in the initial nodes in response to receiving a computing request for private data, and sending computing instructions to the target computing nodes so that the target computing nodes compute fragments of the received private data. And finally, according to the calculation feedback information of the target calculation node, obtaining target information, and establishing a block corresponding to the target information on the block chain.
Description
Technical Field
The present application relates to the field of block chain technologies, and in particular, to a data processing method and apparatus for a block chain, and an electronic device.
Background
The block chain technology is also called as distributed book technology, is a decentralized distributed database technology and is characterized by decentralized, public transparency, no tampering and trusty.
In the block chain, a plurality of nodes are required to participate in the storage and verification of the account book, so that the private data or account information of the user is public and transparent to the outside, and effective privacy protection is not performed. Thus making the problem of protecting private data one of the major challenges facing blockchains.
Disclosure of Invention
In view of the above, the present application provides a data processing method, an apparatus and an electronic device for a block chain, which includes:
a data processing method of a block chain is applied to a scheduling node, wherein the scheduling node is a node generated by electing block chain link points, and the method comprises the following steps:
determining a node with a data storage attribute meeting a screening condition as an initial node in the nodes on the block chain;
in response to receiving a computing request for private data, determining at least two target computing nodes in the initial node;
sending a calculation instruction to the target calculation node to enable the target calculation node to calculate the received privacy data segment;
obtaining target information according to the calculation feedback information of the target extreme node, wherein the target information is result information which is obtained according to the privacy data and corresponds to the calculation request;
and establishing a block corresponding to the target information on the block chain.
Optionally, among the nodes in the block chain, determining a node whose data storage attribute meets the screening condition as an initial node includes:
in response to sending a data segment to a node on the blockchain, determining the node as an initial node if the node of the blockchain can store the data segment in a private data storage area of the node.
Optionally, among the nodes in the block chain, determining a node whose data storage attribute meets the screening condition as an initial node includes:
acquiring authentication information of nodes on the block chain;
forming a first node group by nodes of which the authentication information meets authentication conditions;
and determining the nodes with the data storage attributes meeting the screening conditions as initial nodes in the nodes of the first node group.
Optionally, the method further comprises:
sending a data fragment generation instruction to a node on the blockchain;
and if the node can generate the data segment based on the data segment generation instruction, determining the node as an initial node.
Optionally, the method further comprises:
monitoring the state of the target computing node;
and if the target computing node is in an offline state, re-determining the target computing node in the initial node.
Optionally, the method further comprises:
generating a node queue of an initial node;
determining a number of compute nodes based on the compute request;
and selecting the initial nodes with the matched number from the node queue as target computing nodes.
Optionally, the number of the target computing nodes is greater than or equal to the required number of the computing nodes corresponding to the computing request.
Optionally, the target information is calculation feedback information of each target calculation node, and interpolation processing is performed to obtain calculation result information corresponding to the private data.
A data processing device of a block chain is applied to a scheduling node, wherein the scheduling node is a node generated by selecting block chain link points, and the device comprises:
the first determining unit is used for determining a node of which the data storage attribute meets the screening condition as an initial node in the nodes of the block chain;
a second determining unit, configured to determine, in response to receiving a computation request for private data, at least two target computing nodes in the initial node;
a sending unit, configured to send a calculation instruction to the target computing node, so that the target computing node calculates a segment of the received private data;
the acquisition unit is used for acquiring target information according to the calculation feedback information of the target calculation node, wherein the target information is result information which is obtained according to the privacy data and corresponds to the calculation request;
and the establishing unit is used for establishing the block corresponding to the target information on the block chain.
An electronic device, comprising:
a memory for storing a program;
a processor configured to execute the program, where the program is specifically configured to implement the data processing method of the blockchain as described in any one of the above.
According to the technical scheme, the method, the device and the electronic equipment for processing the data of the block chain are applied to the scheduling node, wherein the scheduling node is a node generated by electing the block chain link points. In the nodes on the block chain, the nodes with the data storage attributes meeting the screening conditions are determined as initial nodes, at least two target computing nodes are determined in the initial nodes in response to the received privacy data computing request, and computing instructions are sent to the target computing nodes so that the target computing nodes compute the received privacy data fragments. And finally, according to the calculation feedback information of the target calculation node, obtaining target information, and establishing a block corresponding to the target information on the block chain. Therefore, in the application, at least two target computing nodes are determined in the nodes of the block chain, and the target computing nodes compute the segments of the private data, so that the private data are processed by the multiple target computing nodes to obtain the target information corresponding to the private data, the private data can be processed only by the target computing nodes on the block chain without introducing third-party nodes in the processing process of the private data in the block chain, and the security of the private data on the block chain is improved.
Drawings
In order to more clearly illustrate the technical solutions of the embodiments of the present application, the drawings needed to be used in the description of the embodiments are briefly introduced below, and it is obvious that the drawings in the following description are only some embodiments of the present application, and it is obvious for those skilled in the art to obtain other drawings without creative efforts.
Fig. 1 is a schematic flowchart illustrating a data processing method for a block chain according to an embodiment of the present disclosure;
FIG. 2 is a schematic diagram illustrating a target computing node determination disclosed in an embodiment of the present application;
fig. 3 is a schematic structural diagram of a data processing apparatus of a block chain according to an embodiment of the present disclosure;
fig. 4 is a schematic structural diagram of an electronic device disclosed in an embodiment of the present application.
Detailed Description
The technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the drawings in the embodiments of the present application, and it is obvious that the described embodiments are only a part of the embodiments of the present application, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present application.
Blockchains are generally divided into three types: public chain (Public Blockchain), Private chain (Private Blockchain) and alliance chain (consortium Blockchain). In addition, there are various types of combinations, such as private chain + federation chain, federation chain + public chain, and other different combinations.
The Hyperledger Fabric is an enterprise-level client oriented alliance chaining source project, and can be conveniently used for building an alliance chain which is participated in by each enterprise and social organization and is used for data sharing. However, many enterprises will have some data with higher security requirements, and it is not desirable to open the data to other enterprises on the same blockchain network. The application provides a data processing method of a block chain, which solves the problem of original privacy data protection and expands the application scene of the block chain.
The data processing method of the block chain provided by the embodiment of the application is applied to the scheduling node, the scheduling node is a node generated by electing the block chain link points, the scheduling node is generated by electing the block chain link points instead of fixedly appointing a certain node as the scheduling node, so that when the current scheduling node is abnormal, the block chain link points are reselected to generate a new scheduling node to replace the original scheduling node, and the availability of the scheduling node is ensured. A blockchain is a distributed decentralized system with many nodes in each system. Each node corresponds to each computer or server terminal that stores all block data. The nodes on the block chain can start an election intelligent contract to elect the nodes, and the selected nodes are determined as scheduling nodes, wherein the election intelligent contract realizes the automatic processing of the election contract in a computer instruction mode. The scheduling node has the functions of scheduling and instruction control of the nodes on the blockchain.
Referring to fig. 1, a data processing method for a blockchain provided by an embodiment of the present application is shown, where the method may include the following steps:
s101, determining a node with a data storage attribute meeting the screening condition as an initial node in the nodes on the block chain.
Firstly, an initial node is determined in nodes of a block chain, wherein the initial node refers to a node of which the data storage attribute meets screening conditions, the screening conditions refer to determination conditions corresponding to the nodes capable of processing the private data, and the initial node screened by the screening conditions can process the private data. The data storage attribute refers to a characteristic of data that a node of the block chain can store, or an application state of a storage region corresponding thereto. Data stored on a node of a blockchain is typically represented as a shared, public and private portion of data storage, with corresponding data storage attributes referring to the storage state for the data.
In one implementation, among the nodes in the blockchain, determining a node whose data storage attribute meets the filtering condition as an initial node includes: in response to sending the data segment to a node on the blockchain, determining the node as an initial node if the node on the blockchain is capable of storing the data segment in a private data storage area of the node.
In this embodiment, the data fragment is used for calculating the private data, and since the blockchain has the characteristic of being public and transparent, if the data fragment is directly stored in a block of the blockchain, the data fragment is easily stolen, so that the protection of the private data cannot be really completed. Thus, there is a need to store data segments in a private data storage area of a node that stores data that is accessible and retrievable only by the node. If a node can store a data segment in a private data storage area, the node can be used in a subsequent process of protecting private data, and therefore the node is determined as an initial node.
In another embodiment, the nodes on the blockchain need to be authenticated and then qualified to participate in subsequent processing of private data. Correspondingly, the determining, among the nodes in the blockchain, a node whose data storage attribute meets the screening condition as an initial node includes: acquiring authentication information of nodes on a block chain; forming a first node group by nodes of which the authentication information meets authentication conditions; and determining the nodes with the data storage attributes meeting the screening conditions as initial nodes in the nodes of the first node group.
The authentication information of the node on the blockchain may refer to information obtained by authenticating the acquired information of the node, such as identity authentication information obtained by performing identity authentication on identity information of the node, or state authentication information obtained by authenticating a state of the node, or attribute authentication information obtained by authenticating an attribute of the node.
The authentication condition is determined according to an application scenario of the private data processing, and if it is a real-time requirement to ensure security of the private data, the node that needs to participate in the private data processing is in an online state. And then, acquiring data storage attributes corresponding to the nodes in the first node group, and determining the nodes with idle private data storage areas in the first node group as initial nodes if detecting whether the private data storage areas of the nodes in the first node group are idle.
In yet another possible implementation manner, a node capable of generating a data fragment for private data processing may also be determined as an initial node, that is, the scheduling node may send a data fragment generation instruction to a node on the blockchain, and if the node on the blockchain is capable of generating the data fragment based on the data fragment generation instruction, the node is determined as the initial node. If the data fragment processed by the private data can be generated, the node can store the data fragment in a private data storage area which is not easy to be stolen by other nodes, so that the node can participate in the subsequent private data processing process.
The foregoing embodiments are merely examples in the embodiments of the present application, and correspondingly, the embodiments of determining an initial node in the embodiments of the present application are not limited to this, and all nodes that can ensure private storage of data segments of private data and are not stolen by other nodes may be used as the initial node.
And S102, responding to the received computing request for the private data, and determining at least two target computing nodes in the initial node.
S103, sending a calculation instruction to a target calculation node to enable the target calculation node to calculate the received privacy data segment.
And S104, obtaining target information according to the calculation feedback information of the target calculation node.
The computation request of the private data can be sent by a client, and the client can communicate with the scheduling node, so that the scheduling node can receive the computation request of the private data sent by the client. The private data may be data in a private transaction, or may be data that a user corresponding to the client desires not to be known by other users in the process of performing other computations. For example, two users both desire to obtain more products produced by whom, but do not desire the other side to know the number of products actually generated by the other side, so the two users desire to protect the privacy of the actual number of the respective products, and the actual number of the corresponding products is privacy data.
The calculation request for the private data is a request for a protection process for the private data. For example, in the case where the private data is not output, a request for the comparison result can be obtained. In the embodiment of the application, in order to realize protection processing on the private data, corresponding parts of the private data can be processed through different computing nodes, so that even if the processing result of the computing node is obtained, the real private data cannot be recovered because the processing result is different for different sections of the private data and different data sections are used for processing. Therefore, at least two determined computing nodes participating in the final private data can be determined, and the number of the computing nodes can be determined according to the processing attributes of the data fragments and the processing results corresponding to the computing requests, so that the target computing node is obtained.
Since the determined initial node can store the sub-data segments for private data processing, a corresponding number of target computing nodes can be determined in the initial node. The compute instruction is then sent by the scheduling node to the target compute node. And after receiving the calculation instruction, the target calculation node performs related calculation on the private data. However, when each target calculation node calculates the private data, the private data is not calculated for all but for a segment of the corresponding private data. And then processing is carried out according to the calculation feedback information of each target calculation node, namely the calculation result aiming at the segment of the private data, so as to obtain the target information. Each target computing node may send the corresponding computing feedback information to the scheduling node, and the scheduling node processes the computing feedback information to obtain the target information. Or the calculation feedback information of each target calculation node is sent to one of the target nodes and processed by the target node to obtain the target information. The target information is result information which is obtained according to privacy data and corresponds to the calculation request. For example, in the application example of comparing the number of generated products by the two users, the private data is the number of products actually produced by the two users, the calculation request is to obtain the user with the larger number of products produced by the two users, and the target information is that the number of products produced by the user a is higher than that of products produced by the user b.
And S105, establishing a block corresponding to the target information on the block chain.
The target information is result information of the corresponding calculation request obtained according to the privacy data. And establishing a block corresponding to the target information on the block chain, namely, uplink storage of the target information, so that a node on the block chain can access the block to obtain the corresponding target information, and the result is ensured to be public and transparent. Or hash calculation of the target information is carried out, and the hash value of the target information is stored in the corresponding block on the block chain, so that when the target information is long in length, the target information is stored on the block chain without any stress on the block chain.
The method is applied to a scheduling node, wherein the scheduling node is a node generated by electing a block chain link point. In the nodes on the block chain, the nodes with the data storage attributes meeting the screening conditions are determined as initial nodes, at least two target computing nodes are determined in the initial nodes in response to the received privacy data computing request, and computing instructions are sent to the target computing nodes so that the target computing nodes compute the received privacy data fragments. And finally, according to the calculation feedback information of the target calculation node, obtaining target information, and establishing a block corresponding to the target information on the block chain. Therefore, in the application, at least two target computing nodes are determined in the nodes of the block chain, and the target computing nodes compute the segments of the private data, so that the private data are processed by the multiple target computing nodes to obtain the target information corresponding to the private data, the private data can be processed only by the target computing nodes on the block chain without introducing third-party nodes in the processing process of the private data in the block chain, and the security of the private data on the block chain is improved.
In an implementation manner, the data processing method for a block chain provided in the embodiment of the present application may further include:
monitoring the state of a target computing node;
and if the target computing node is in an offline state, re-determining the target computing node in the initial node.
The scheduling node has a function of selecting and monitoring target computing nodes in a computing process, when the target computing nodes are determined, computing instructions need to be sent to the corresponding target computing nodes, and since the number of the target computing nodes is multiple, after feedback information of each target computing node is received, fragments of private data are sent to the corresponding target computing nodes, in the process, due to network reasons or the load problem of node processing information, the target computing nodes or abnormal computing nodes existing in the current target computing nodes need to be determined again in the initial nodes, so that normal operation of private data computing is guaranteed.
Optionally, the number of target computing nodes is equal to the required number of computing nodes corresponding to the computing request, and the specific required number needs to be determined according to the application scenario for performing the private data processing and the selected computing mode. Correspondingly, in order to avoid the target computing node from being suddenly offline, the number of the selected target computing nodes can be larger than the required number of the computing nodes corresponding to the computing request.
Optionally, in order to facilitate real-time acquisition of the target computing node, a node queue of initial nodes may be generated, the number of computing nodes is determined based on the computing request, and the initial nodes with the matched number are selected as the target computing nodes in the node queue. In this embodiment, after the nodes on the blockchain are authenticated, the nodes whose data storage attributes meet the screening condition are initial nodes and form a node queue, so that the nodes in the node queue can wait for participating in the processing of the private data at any time, that is, after receiving the corresponding calculation request, it is only required to directly determine the target calculation node from the node queue to complete the calculation. And the nodes in the node queue can be adjusted in real time according to the states of the nodes in the node queue, so that the screening time of the nodes is saved.
Referring to fig. 2, a schematic diagram of determining a target computing node according to an embodiment of the present application is shown. The scheduling node 201 filters nodes on the blockchain, determines nodes whose data storage attributes meet the filtering conditions as initial nodes, such as Peer a, Peer B, Peer C, and Peer d, and forms a node queue 202 with the four nodes, and after receiving a computation request sent by the client 203, the scheduling node 201 responds to the computation request, and randomly filters out target computation nodes participating in the computation in the node queue 202 to form a target computation node group 204, which may include Peer a, Peer B, and Peer C. Therefore, the nodes participate in the calculation of the private data, and each target calculation node obtains a corresponding calculation result through calculation. And then, the scheduling node or any one of the target calculation nodes performs summary processing on the calculation results to obtain target information, wherein the target information is result information which is obtained according to the privacy data and corresponds to the calculation request.
In a possible implementation manner, the target information is calculation result information corresponding to the private data obtained by performing interpolation processing according to the calculation feedback information of each target calculation node. The interpolation processing may be a processing method for summarizing the calculation feedback information, and may generate a polynomial function capable of obtaining the calculation feedback information of each target calculation node by using a lagrangian interpolation method, and then determine the final target information based on the polynomial function. And processing each piece of calculation feedback information according to the calculation requirement corresponding to the calculation request, wherein if the product quantity needs to be counted, the product quantity needs to be summed, and if the wage needs to be averaged, the average processing needs to be carried out.
For example, the calculation request is to calculate the average payroll of user a, user B, and user C, while neither user a, user B, or user C expects others to know their true payroll amounts. The corresponding target compute nodes include a first target compute node and a second target compute node. The user A can divide the self true payroll amount into two payroll segments and send the two payroll segments to the first target computing node and the second target computing node, so that the first target computing node can intelligently obtain one payroll segment and cannot obtain the second payroll segment, and only one processing result can be obtained based on the self-stored data segment; similarly, the second target computing node cannot obtain other payroll segments, and only can obtain the corresponding processing result by computing. And then processing the processing results of the first target calculation node and the second target calculation node to obtain the average wages of the three users, wherein any target calculation node cannot restore the real wage amount of each user in the process.
It should be noted that in the embodiment of the present application, the scheduling node is generated by selecting a block link node, and after the scheduling node fails, a new scheduling node may be reselected for replacement. Meanwhile, the determined target computing node is a node on the blockchain, and multi-party computation of the privacy data can be realized based on the node on the blockchain, so that any one target computing node can only obtain a segment of the corresponding privacy data, the original privacy data cannot be restored, the problem of protection of the original privacy data is solved, a third node outside the blockchain is not required to be introduced, decentralized transaction computation is realized, the privacy data is not required to be provided in the transaction computation process, and a computation result corresponding to the privacy data can also be obtained.
Referring to fig. 3, the data processing apparatus for a blockchain provided in the embodiment of the present application is shown, and is applied to a scheduling node, where the scheduling node is a node generated by selecting a blockchain link point.
Specifically, the apparatus in this embodiment may include the following units:
a first determining unit 301, configured to determine, as an initial node, a node whose data storage attribute meets a screening condition, in the nodes of the block chain;
a second determining unit 302, configured to determine, in response to receiving a computation request for private data, at least two target computing nodes in the initial node;
a sending unit 303, configured to send a calculation instruction to the target computing node, so that the target computing node calculates the received segment of the private data;
an obtaining unit 304, configured to obtain target information according to computation feedback information of the target computing node, where the target information is result information corresponding to the computation request obtained according to the privacy data;
an establishing unit 305, configured to establish a block corresponding to the target information on the block chain.
In the data processing apparatus of the blockchain provided by the embodiment of the present application, among nodes in the blockchain, a node whose data storage attribute meets a screening condition is determined as an initial node, in response to receiving a calculation request for private data, at least two target calculation nodes are determined in the initial node, and then a calculation instruction is sent to the target calculation nodes, so that the target calculation nodes calculate segments of the received private data. And finally, according to the calculation feedback information of the target calculation node, obtaining target information, and establishing a block corresponding to the target information on the block chain. Therefore, in the application, at least two target computing nodes are determined in the nodes of the block chain, and the target computing nodes compute the segments of the private data, so that the private data are processed by the multiple target computing nodes to obtain the target information corresponding to the private data, the private data can be processed only by the target computing nodes on the block chain without introducing third-party nodes in the processing process of the private data in the block chain, and the security of the private data on the block chain is improved.
In one implementation, the first determining unit 301 is specifically configured to:
in response to sending a data segment to a node on the blockchain, determining the node as an initial node if the node on the blockchain can store the data segment in a private data storage area of the node.
In another embodiment, the first determining unit 301 is specifically configured to:
acquiring authentication information of nodes on the block chain;
forming a first node group by nodes of which the authentication information meets authentication conditions;
and determining the nodes with the data storage attributes meeting the screening conditions as initial nodes in the nodes of the first node group.
Optionally, the apparatus further comprises:
a third determining unit, configured to send a data fragment generation instruction to a node on the blockchain; and if the node can generate the data segment based on the data segment generation instruction, determining the node as an initial node.
In one implementation, the apparatus further comprises:
the monitoring unit is used for monitoring the state of the target computing node; and if the target computing node is in an offline state, re-determining the target computing node in the initial node.
In one implementation, the apparatus further comprises:
the queue generating unit is used for generating a node queue of the initial node;
a fourth determination unit configured to determine the number of computing nodes based on the computing request; and selecting the initial nodes with the matched number from the node queue as target computing nodes.
Optionally, the number of the target computing nodes is greater than or equal to the required number of the computing nodes corresponding to the computing request.
Optionally, the target information is calculation result information corresponding to the private data, which is obtained by performing interpolation processing according to calculation feedback information of each target calculation node.
It should be noted that, for the specific implementation of each unit in the present embodiment, reference may be made to the corresponding content in the foregoing, and details are not described here.
Referring to fig. 4, a schematic structural diagram of an electronic device according to an embodiment of the present application is shown, where the electronic device may be a scheduling node on a blockchain, and the scheduling node is a node generated by electing a blockchain link point.
Specifically, the electronic device in this embodiment may include the following structure:
a memory 401 for storing a program;
a processor 402 for executing the program, the program being specifically configured to implement:
determining a node with a data storage attribute meeting a screening condition as an initial node in the nodes on the block chain;
in response to receiving a computing request for private data, determining at least two target computing nodes in the initial node;
sending a calculation instruction to the target calculation node to enable the target calculation node to calculate the received privacy data segment;
obtaining target information according to the calculation feedback information of the target calculation node, wherein the target information is result information which is obtained according to privacy data and corresponds to the calculation request;
and establishing a block corresponding to the target information on the block chain.
According to the electronic equipment, among nodes on a block chain, the nodes with the data storage attributes meeting the screening conditions are determined to be initial nodes, at least two target computing nodes are determined in the initial nodes in response to the received privacy data computing requests, and computing instructions are sent to the target computing nodes, so that the target computing nodes compute the received privacy data fragments. And finally, according to the calculation feedback information of the target calculation node, obtaining target information, and establishing a block corresponding to the target information on the block chain. Therefore, in the application, at least two target computing nodes are determined in the nodes of the block chain, and the target computing nodes compute the segments of the private data, so that the private data are processed by the multiple target computing nodes to obtain the target information corresponding to the private data, the private data can be processed only by the target computing nodes on the block chain without introducing third-party nodes in the processing process of the private data in the block chain, and the security of the private data on the block chain is improved.
It should be noted that, for the specific implementation of the processor in this embodiment, reference may be made to the corresponding contents in the foregoing, and details are not described here again.
The embodiments in the present description are described in a progressive manner, each embodiment focuses on differences from other embodiments, and the same and similar parts among the embodiments are referred to each other. The device disclosed by the embodiment corresponds to the method disclosed by the embodiment, so that the description is simple, and the relevant points can be referred to the method part for description.
Those of skill would further appreciate that the various illustrative elements and algorithm steps described in connection with the embodiments disclosed herein may be implemented as electronic hardware, computer software, or combinations of both, and that the various illustrative components and steps have been described above generally in terms of their functionality in order to clearly illustrate this interchangeability of hardware and software. Whether such functionality is implemented as hardware or software depends upon the particular application and design constraints imposed on the implementation. Skilled artisans may implement the described functionality in varying ways for each particular application, but such implementation decisions should not be interpreted as causing a departure from the scope of the present application.
The steps of a method or algorithm described in connection with the embodiments disclosed herein may be embodied directly in hardware, in a software module executed by a processor, or in a combination of the two. A software module may reside in Random Access Memory (RAM), memory, Read Only Memory (ROM), electrically programmable ROM, electrically erasable programmable ROM, registers, hard disk, a removable disk, a CD-ROM, or any other form of storage medium known in the art.
The previous description of the disclosed embodiments is provided to enable any person skilled in the art to make or use the present application. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the generic principles defined herein may be applied to other embodiments without departing from the spirit or scope of the application. Thus, the present application is not intended to be limited to the embodiments shown herein but is to be accorded the widest scope consistent with the principles and novel features disclosed herein.
Claims (10)
1. A data processing method of a block chain is applied to a scheduling node, wherein the scheduling node is a node generated by electing block chain link points, and the method comprises the following steps:
determining a node with a data storage attribute meeting a screening condition as an initial node in the nodes on the block chain;
in response to receiving a computing request for private data, determining at least two target computing nodes in the initial node;
sending a calculation instruction to the target calculation node to enable the target calculation node to calculate the received privacy data segment;
obtaining target information according to the calculation feedback information of the target calculation node, wherein the target information is result information which is obtained according to privacy data and corresponds to the calculation request;
and establishing a block corresponding to the target information on the block chain.
2. The method of claim 1, wherein among the nodes in the blockchain, determining a node with a data storage attribute meeting a screening condition as an initial node comprises:
in response to sending a data segment to a node on the blockchain, determining the node as an initial node if the node on the blockchain can store the data segment in a private data storage area of the node.
3. The method of claim 1, wherein among the nodes in the blockchain, determining a node with a data storage attribute meeting a screening condition as an initial node comprises:
acquiring authentication information of nodes on the block chain;
forming a first node group by nodes of which the authentication information meets authentication conditions;
and determining the nodes with the data storage attributes meeting the screening conditions as initial nodes in the nodes of the first node group.
4. The method of claim 1, further comprising:
sending a data fragment generation instruction to a node on the blockchain;
and if the node can generate the data segment based on the data segment generation instruction, determining the node as an initial node.
5. The method of claim 1, further comprising:
monitoring the state of the target computing node;
and if the target computing node is in an offline state, re-determining the target computing node in the initial node.
6. The method of claim 1, further comprising:
generating a node queue of an initial node;
determining a number of compute nodes based on the compute request;
and selecting the initial nodes with the matched number from the node queue as target computing nodes.
7. The method of claim 6, the number of target compute nodes being greater than or equal to a required number of compute nodes to which the compute request corresponds.
8. The method according to claim 1, wherein the target information is calculation result information corresponding to the private data obtained by performing interpolation processing according to calculation feedback information of each target calculation node.
9. A data processing device of a block chain is applied to a scheduling node, wherein the scheduling node is a node generated by selecting block chain link points, and the device comprises:
the first determining unit is used for determining a node of which the data storage attribute meets the screening condition as an initial node in the nodes of the block chain;
a second determining unit, configured to determine, in response to receiving a computation request for private data, at least two target computing nodes in the initial node;
a sending unit, configured to send a calculation instruction to the target computing node, so that the target computing node calculates a segment of the received private data;
the acquisition unit is used for acquiring target information according to the calculation feedback information of the target calculation node, wherein the target information is result information which is obtained according to the privacy data and corresponds to the calculation request;
and the establishing unit is used for establishing the block corresponding to the target information on the block chain.
10. An electronic device, comprising:
a memory for storing a program;
a processor for executing the program, the program being in particular for implementing the data processing method of a blockchain according to any one of claims 1 to 8.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202011565155.1A CN112685769A (en) | 2020-12-25 | 2020-12-25 | Data processing method and device of block chain and electronic equipment |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202011565155.1A CN112685769A (en) | 2020-12-25 | 2020-12-25 | Data processing method and device of block chain and electronic equipment |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN112685769A true CN112685769A (en) | 2021-04-20 |
Family
ID=75453345
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202011565155.1A Pending CN112685769A (en) | 2020-12-25 | 2020-12-25 | Data processing method and device of block chain and electronic equipment |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN112685769A (en) |
Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN113726758A (en) * | 2021-08-25 | 2021-11-30 | 百保(上海)科技有限公司 | Data privacy calculation method and system based on block chain |
Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN111047450A (en) * | 2020-03-18 | 2020-04-21 | 支付宝(杭州)信息技术有限公司 | Method and device for calculating down-link privacy of on-link data |
| US20200169387A1 (en) * | 2019-07-31 | 2020-05-28 | Alibaba Group Holding Limited | Blockchain-based data authorization method and apparatus |
| CN111597043A (en) * | 2020-05-14 | 2020-08-28 | 行星算力(深圳)科技有限公司 | Method, device and system for calculating edge of whole scene |
| CN111885133A (en) * | 2020-07-10 | 2020-11-03 | 深圳力维智联技术有限公司 | Data processing method and device based on block chain and computer storage medium |
-
2020
- 2020-12-25 CN CN202011565155.1A patent/CN112685769A/en active Pending
Patent Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20200169387A1 (en) * | 2019-07-31 | 2020-05-28 | Alibaba Group Holding Limited | Blockchain-based data authorization method and apparatus |
| CN111047450A (en) * | 2020-03-18 | 2020-04-21 | 支付宝(杭州)信息技术有限公司 | Method and device for calculating down-link privacy of on-link data |
| CN111597043A (en) * | 2020-05-14 | 2020-08-28 | 行星算力(深圳)科技有限公司 | Method, device and system for calculating edge of whole scene |
| CN111885133A (en) * | 2020-07-10 | 2020-11-03 | 深圳力维智联技术有限公司 | Data processing method and device based on block chain and computer storage medium |
Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN113726758A (en) * | 2021-08-25 | 2021-11-30 | 百保(上海)科技有限公司 | Data privacy calculation method and system based on block chain |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| Yun et al. | DQN-based optimization framework for secure sharded blockchain systems | |
| KR102002509B1 (en) | Privite blockchain system including notarizing center and notarial method thereof | |
| CN110035059B (en) | Block chain construction method and device | |
| CN110602217B (en) | Block chain-based alliance management method, device, equipment and storage medium | |
| CN112527912B (en) | Data processing method and device based on block chain network and computer equipment | |
| EP3861494A1 (en) | A consensus method and framework for a blockchain system | |
| Huang et al. | Resource allocation and consensus of blockchains in pervasive edge computing environments | |
| KR20220091560A (en) | Blockchain-based data detection method and device, and computer-readable storage medium | |
| JP7198371B2 (en) | How to elect a leader node using a role-based consensus protocol in a blockchain network | |
| CN111556120A (en) | Data processing method and device based on block chain, storage medium and equipment | |
| WO2022217807A1 (en) | Blockchain consensus node selection method and apparatus, and computer device and storage medium | |
| CN111861477A (en) | Block chain-based post-transaction data processing method and device and computer equipment | |
| JP6904644B2 (en) | Blockchain monitoring | |
| CN110990790B (en) | Data processing method and equipment | |
| CN112487091A (en) | Method and device for determining block chain consensus node | |
| CN114500119B (en) | Method and device for calling block chain service | |
| CN110460471B (en) | Super node election method, device and storage medium | |
| CN112685769A (en) | Data processing method and device of block chain and electronic equipment | |
| CN112685750A (en) | Data processing method and device | |
| CN112862607A (en) | Method, device, equipment and storage medium for realizing block chain consensus mechanism | |
| CN116431929A (en) | Information recommendation method, device, equipment and medium based on privacy calculation | |
| Müller et al. | On fairness in voting consensus protocols | |
| KR20200117473A (en) | Apparatus and method for anomaly detection based on blockchain | |
| WO2022111109A1 (en) | Fork resistance detection method and apparatus for blockchain | |
| GB2587541A (en) | A consensus method and framework for a blockchain system |
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 |