CN112351026B - Block chain network node authority distribution method and device, computer equipment and medium - Google Patents
Block chain network node authority distribution method and device, computer equipment and medium Download PDFInfo
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Abstract
The invention relates to a block chain technology, and provides a block chain network node authority distribution method and device, computer equipment and media. The method can comprise the following steps: scoring the current node based on the transaction characteristics between the current node and other nodes in the block chain network to obtain scoring results of all nodes including the current node, constructing a scoring matrix by using the scoring results, setting the weight to enable the numerical range of each element in the scoring matrix to be in a preset range, performing column operation on the current scoring matrix to convert the current scoring matrix into a one-dimensional scoring array for representing a behavior attribute value, and distributing authority to the nodes in the block chain network according to the behavior attribute value. Data such as permission record tables, scoring matrices, etc. may be stored in the block chain. The invention can reasonably distribute the authority of each node in the block chain network on the premise of avoiding human intervention, realizes the equitable management of the block chain network and has very good node user experience.
Description
Technical Field
The invention relates to the technical field of blockchain, in particular to a method and a device for distributing access rights of blockchain network nodes, computer equipment and a medium.
Background
Currently, the authority assignment of the nodes of the blockchain network is often completed manually by an administrator, and the administrator performs operations such as rating, adding or deleting on each node. Obviously, the traditional block chain network node authority allocation strategy is contrary to the 'decentralized' block chain design concept, and the node user is hard to completely trust the manual management mode. The existing block chain network node authority allocation scheme is difficult to completely realize objective and fair management of each node, and particularly in the aspect of node authority allocation, once the condition of unreasonable authority allocation occurs, the whole block chain network environment is often affected badly, and the node user experience is poor.
Therefore, how to effectively optimize the node authority assignment to the blockchain network, improve the blockchain network environment, and improve the node user satisfaction degree becomes a key point for the technical problems to be solved and the research of the technical staff in the field.
Disclosure of Invention
In order to solve the problems of strong subjectivity, poor node user experience and the like in the conventional block chain network node permission allocation scheme, the invention can innovatively provide a block chain network node permission allocation method and device, computer equipment and a medium.
To achieve the above technical objective, the present invention discloses a method for assigning permissions to nodes in a blockchain network, where the method for assigning permissions to nodes in a blockchain network may include, but is not limited to, the following steps.
And scoring the current node based on the transaction characteristics between the current node and other nodes in the block chain network, and obtaining scoring results of all nodes including the current node.
And constructing a scoring matrix by using the scoring results of all the nodes, wherein row elements in the scoring matrix are used for representing the scoring result of one node corresponding to other nodes.
And respectively setting weights for each element of each row in the scoring matrix so as to enable the numerical range of each element in the scoring matrix to be within a preset range.
Performing column operation on a current scoring matrix to convert the current scoring matrix into a one-dimensional scoring array; wherein, the elements in the one-dimensional scoring array are used for representing the behavior attribute values of the nodes.
And distributing authority to the nodes in the block chain network according to the behavior attribute value.
Further, after assigning the authority to the node in the block chain network according to the behavior attribute value, the method further includes:
and reading the authority record table, and updating the authority record table based on the node distribution authority.
Further, the step of updating the permission record table further includes:
determining a node with the authority change reaching a set value, and monitoring the node with the authority change reaching the set value; wherein the permission change comprises a permission increase and a permission decrease.
Further, before scoring the current node by the transaction characteristics between the current node and other nodes in the blockchain-based network, the method further comprises:
and reading the authority record table, and sequencing the nodes according to the sequence of the node authorities from high to low so as to take the sequence of the node authorities from high to low as the sequence for node scoring.
Further, before the performing the column operation on the current scoring matrix, the method further includes:
and calculating the similarity between different elements in the same row in the current scoring matrix.
And screening and removing at least one element with the minimum similarity with other elements for each row in the current scoring matrix.
Further, the process of calculating the similarity between different elements in the same row in the current scoring matrix includes:
and taking the two elements as exponents of powers respectively to obtain a first exponential power and a second exponential power.
And taking the inverse of the absolute value of the difference between the first exponential power and the second exponential power as the similarity between the two elements.
Further, the transaction characteristics between the current node and other nodes comprise at least one of transaction times, transaction amount and accounting times.
To achieve the above technical objectives, the present invention provides a device for assigning permissions to nodes in a blockchain network, which may include, but is not limited to, a node scoring module, a matrix constructing module, a weight setting module, a matrix operating module, and a permission assigning module.
And the node scoring module is used for scoring the current node based on the transaction characteristics between the current node and other nodes in the block chain network and obtaining scoring results of all nodes including the current node.
And the matrix construction module is used for constructing a scoring matrix by using the scoring results of all the nodes, and row elements in the scoring matrix are used for expressing the scoring result of one node corresponding to other nodes.
And the weight setting module is used for respectively setting weights for each element of each row in the scoring matrix so as to enable the numerical value range of each element in the scoring matrix to be in a preset range.
The matrix operation module is used for carrying out column operation on the current scoring matrix so as to convert the current scoring matrix into a one-dimensional scoring array; wherein, the elements in the one-dimensional scoring array are used for representing the behavior attribute values of the nodes.
And the authority distribution module is used for distributing the authority to the nodes in the block chain network according to the behavior attribute value.
To achieve the above technical object, the present invention can also provide a computer device, which includes a memory and a processor, where the memory stores computer readable instructions, and the computer readable instructions, when executed by the processor, cause the processor to execute the steps of the block chain network node permission allocation method in any embodiment of the present invention.
To achieve the above technical objects, the present invention can provide a storage medium storing computer readable instructions, which when executed by one or more processors, cause the one or more processors to execute the steps of the block chain network node authority allocation method in any embodiment of the present invention.
The invention has the beneficial effects that: the invention reasonably distributes the node authority in the blockchain network on the premise of avoiding human intervention, realizes fair management of the blockchain network, is beneficial to enhancing the enthusiasm of node users for participating in transactions, improves the activity of the blockchain network, and realizes autonomous management of the node authority in the blockchain network, thereby constructing a fairly competitive blockchain network environment, promoting the development of the blockchain network and having very good node user experience.
In addition, the invention can also contribute to obviously enhancing the safety, reliability and practicability of the block chain network, and improves the trust of the vast node users on the block chain network.
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Fig. 1 illustrates a flow diagram of a method for assigning permissions to nodes of a blockchain network in some embodiments of the invention.
Fig. 2 is a flowchart illustrating a method for assigning permissions to nodes of a blockchain network according to another embodiment of the present invention.
FIG. 3 shows a block diagram of the internal structure of a computer device in one or more embodiments of the invention.
Detailed Description
The following explains and explains a method and an apparatus for assigning a node authority of a blockchain network, a computer device, and a medium provided by the present invention in detail with reference to the drawings of the specification.
As shown in fig. 1 and fig. 2, one or more embodiments of the present invention can provide a method for assigning permissions to network nodes in a blockchain, so as to solve the problems of being not objective in the conventional way for assigning and managing permissions to blockchain. More specifically, the node authority assignment may include, but is not limited to, the following steps.
And S100, reading the authority record table, and sequencing the nodes according to the sequence of the node authorities from high to low so as to take the sequence of the node authorities from high to low as the sequence for node scoring.
In the step, the current authority of each node is determined according to the content in the authority record table, and then all the nodes are sequenced from high to low based on the node authority; of course, all nodes may also be sorted based on their low-to-high order of authority.
The authority record table may be an authority record table formed after assigning authorities to each node in the block chain network after executing the present invention at least once, or a record table formed by other existing methods for recording authorities possessed by each node in the current block chain network.
According to the method, the node scoring sequence is set based on the sequence from high to low of the current authority, so that the mode is beneficial to promoting the nodes only with low authority to actively carry out more transaction activities, and the nodes still have the opportunity to participate in the transaction activities before being scored, so that a blockchain network applying the technical scheme of the invention is more active, and a continuously competitive and continuously developed blockchain network environment is created.
It should be understood that, if the current blockchain network has no permission record table, the present invention may perform the operation of step S200 on the nodes in the blockchain network one by one in a random order or a preset order. The preset sequence may be, for example, a joining sequence of each node of the current block chain network, that is, a sequence of node scores according to a sequence of joining time of the current block chain network from long to short. The blockchain to which the present invention relates includes, but is not limited to, one of a federation chain, a public chain, or a private chain.
And S200, scoring the current node based on the transaction characteristics between the current node and other nodes in the block chain network, and obtaining scoring results of all nodes including the current node.
The transaction characteristics between the current node and other nodes represent the transaction characteristics between any two nodes in the invention. Transaction characteristics between two nodes in one or more embodiments of the invention include, but are not limited to, at least one of historical transaction characteristics of transaction times, transaction amount, billing times, communication times, number of memory blocks, and the like. For any node, the node can obtain scores of other nodes except the node itself, and the scores are used as the scoring result of the node. Assuming that the number of nodes in the blockchain network is n, the number of scores available for any node is n-1, i.e. the scoring result of the node contains n-1 scores.
For example, for node T1, the historical billing number between nodes T2 and T1 is 12, and the node T1 score corresponding to node T2 may be 12. For example, for any node Tx, the transaction amount between another node Ty and Tx is 30000, then the node Tx score for the corresponding node Ty may be 30000. The above examples, in addition to being used to explain scoring schemes, can also be seen: the transaction characteristics selected for different nodes in the implementation process may be the same or different, and the determination of the transaction characteristics is generally based on whether the data used for scoring by the current node is complete.
Therefore, the node scoring result of the invention completely takes the node behavior as the only basis for scoring, and the scoring result comes from all other nodes except the current node, and the evaluation data is comprehensive and reasonable, so the invention has the outstanding advantages of real and reliable data, direct reflection of the historical behavior of the node by the evaluation result, and the like.
And S300, constructing a scoring matrix by using the scoring results of all the nodes, wherein row elements in the scoring matrix are used for expressing the scoring result of one node corresponding to other nodes.
The invention can realize the storage and the display of the scoring results of all nodes in the block chain network by constructing the scoring matrix, and the scoring result of one node in some embodiments of the invention is a row of elements in the scoring matrix.
The scoring matrix obtained in step S300 is shown below, and is an n × n-1 matrix.
Wherein, S of the 1 st line1,1，S1,2…S1,n-1Can be used to represent the node scoring result for the 1 st node, S for line nn,1，Sn,2…Sn,n-1Can be used to represent the node scoring result of the nth node, Si,jWhich is used to indicate a score of the ith node corresponding to some other node on the jth column.
It should be understood that the matrix has the property of being transposable, so that alternate embodiments of the present invention can represent the scoring result of one node corresponding to another node using the column elements in the scoring matrix. For example, the scoring matrix is an n-1 × n matrix, i.e., a transposed matrix from the schematic matrix described above.
The invention can realize the comprehensive and clear record of the scoring condition of the nodes and facilitate the subsequent data processing by taking the scoring matrix as the statistical mode of the scoring results of all the nodes in the block chain network, thereby leading the invention to be easier to implement and having very low possibility of error results.
And S400, respectively setting weights for each element of each row in the scoring matrix so as to enable the numerical range of each element in the scoring matrix to be within a preset range.
In specific implementation, the method sets the same weight for n-1 elements in the same row of the matrix, and makes the actual value of each element after the weight is set in a preset range.
Some embodiments of the present invention may adopt a normalization calculation mode to select appropriate weights for each row element of the matrix respectively, and set each row element in the matrix, so that each element within a preset range can be calculated and compared on the same order of magnitude.
Therefore, even if different nodes adopt different transaction characteristics for scoring, the invention can still make each element be in a preset range by setting the weight mode, wherein the preset range can be as follows: 0 or more and 1 or less (i.e., [0, 1 ]).
The present embodiment utilizes w1…wnRespectively used for representing the weight set by the elements in the 1 st row to the n th row.
S500, performing column operation on the current scoring matrix to convert the current scoring matrix into a one-dimensional scoring array; wherein, the elements in the one-dimensional score array are used for representing the behavior attribute values of the nodes.
The column operation process in some embodiments of the invention is: performing accumulation calculation or mean calculation on elements in the same row by taking the column as a unit; of course, the present invention is not limited to this, and for example, a square sum operation or a cubic sum operation may be performed on the elements in the same row. The invention improves the operation efficiency by a matrix calculation mode and reduces the occupation of computer resources, so the invention can be suitable for occasions with higher requirements on the resource usage amount.
The operation is performed with the columns in the current scoring matrix as units, and the obtained one-dimensional scoring array is shown as Q1、Q2…QnCan be used to represent the behavior attribute values, Q, of the 1 st node to the nth node, respectivelynFor representing the behavior attribute value of the nth node.
In some improved schemes of the present invention, before performing the column operation on the current scoring matrix, the method further includes: and calculating the similarity between different elements in the same row in the current scoring matrix, and screening and removing at least one element with the minimum similarity with other elements in each row in the current scoring matrix.
More specifically, the process of calculating the similarity between two elements includes: by respectively exponentiating two elements (taking the 1 st element and the (n-1) th element of the first node as examples) as exponentiations of powers, a first exponential power (e.g., a first exponential power) is obtained
) And a second exponential power (e.g. of
) The inverse of the absolute value of the difference between the first exponential power and the second exponential power (e.g. by exponentiation of the first exponent
) As the similarity between two elements. The base numbers of the first exponential power and the second exponential power can be e or 10, and can be set reasonably according to actual conditions.
It should be understood that the number of elements in each row of the scoring matrix that are removed is the same to maintain the integrity of the scoring matrix data; for example, each row in the scoring matrix has two elements removed that have the least similarity to other elements in the row. Assuming that the similarity between the removed element and an element in the same row reserved in the matrix is C1, and the similarity between any two elements in the row reserved in the matrix is C2, C1 < C2. This approach enables efficient cleansing of unreasonable data, such as removing maxima and/or minima from the scoring matrix, thereby further improving the rationality and reliability of the implementation of the present invention.
By performing similarity calculation based on the above manner, the difference between two elements in the same row of the scoring matrix can be enlarged, so that at least one element with the smallest similarity with other elements can be screened and removed more quickly and accurately.
The invention can describe the node activity condition, the node transaction condition, the relation with other nodes and the like through the behavior attribute value, and the invention realizes the quantitative representation of the historical behavior of the node by utilizing the behavior attribute value. The behavior attribute value is obtained by scoring the current node by a plurality of other nodes, so that the node is evaluated by the behavior attribute value to have stronger objectivity and rationality, and a node user can trust thoroughly.
S600, distributing authority to the nodes in the block chain network according to the behavior attribute values.
The behavior attribute values in different ranges in the embodiment of the invention correspond to different authorities, higher authorities are distributed to nodes with higher behavior attribute values, and lower authorities are distributed to nodes with lower behavior attribute values.
For example, for nodes whose behavior attribute value is within the range of [9, + ∞), class A authority is assigned, for nodes whose behavior attribute value is within the range of [8, 9], class B authority is assigned, for nodes whose behavior attribute value is within the range of [7, 8], class C authority is assigned, for nodes whose behavior attribute value is within the range of [6, 7], class D authority is assigned, for nodes whose behavior attribute value is within the range of [5, 6], class E authority is assigned, for nodes whose behavior attribute value is within the range of [4, 5], class F authority is assigned, for nodes whose behavior attribute value is within the range of [3, 4], class G authority is assigned, for nodes whose behavior attribute value is within the range of [2, 3], class H authority is assigned, for nodes whose behavior attribute value is within the range of [1, 2], class I authority is assigned, for nodes whose behavior attribute value is within the range of (∞), 1, distributing J-gear authority to nodes in the range; wherein, the A-gear authority, the B-gear authority, the C-gear authority, the D-gear authority, the E-gear authority, the F-gear authority, the G-gear authority, the H-gear authority, the I-gear authority and the J-gear authority can be gradually reduced.
Based on a means of quantitatively evaluating node permissions, the method can repeatedly and continuously implement the scheme according to a certain period (for example, one month or half month), so that the aim of dynamically adjusting each node permission in the block chain network is fulfilled, the activity of the block chain network is improved, and the rapid development of the block chain network is promoted.
And S700, reading the authority record table, and updating the authority record table based on the node distribution authority.
If there is no authority record table, some embodiments of the present invention may further include a step of creating an authority record table, and then filling the created authority record table based on the authority assigned to the node. It should be understood that, in other embodiments of the present invention, a new permission record table may be used each time the present invention is executed, and a permission change trend graph of each node in the blockchain network may be drawn according to multiple permission record tables, so as to enable a node permission dynamics in the blockchain network to be understood more intuitively and deeply.
The step of updating the permission record table in some embodiments of the present invention may further include: determining a node of which the authority change reaches a set value in the process of updating the authority record table, and monitoring the node of which the authority change reaches the set value; the permission change includes permission increase (or increase) and permission decrease (or decrease), and the setting value may be, for example, third gear. Namely, the invention can also pay attention to the nodes with suddenly rising or suddenly falling authority.
For example, if the authority of a certain node is changed from J file to B file, the node has the possibility of threatening the network security of the block chain, and the invention can perform key monitoring on the real-time transaction behavior, the data flow direction and the like of the node; for example, if the authority of a node is changed from the A file to the G file, the node is judged to possibly exit the current blockchain network.
In particular, some embodiments of the present invention may further control a node whose authority suddenly increases, where the control manner includes locking resources and data flow used by the node in the blockchain network, calculating a risk value by performing a feature comparison between the node and a historical node that has been in danger, and giving an alarm or warning when the risk value exceeds a threshold value, so as to achieve the purpose of warning.
Still other embodiments of the present invention can provide a node authority distribution device for a blockchain network, which may include, but is not limited to, a node scoring module, a matrix construction module, a weight setting module, a matrix operation module, and an authority distribution module.
And the node scoring module is used for scoring the current node based on the transaction characteristics between the current node and other nodes in the block chain network and obtaining scoring results of all nodes including the current node.
The transaction characteristics between the current node and other nodes represent the transaction characteristics between any two nodes in the invention. Transaction characteristics between two nodes in one or more embodiments of the invention include, but are not limited to, at least one of historical transaction characteristics of transaction times, transaction amount, billing times, communication times, number of memory blocks, and the like. For any node, the node can obtain scores of other nodes except the node itself, and the scores are used as the scoring result of the node. Assuming that the number of nodes in the blockchain network is n, the number of scores available for any node is n-1, i.e. the scoring result of the node contains n-1 scores.
And the matrix construction module is used for constructing a scoring matrix by using the scoring results of all the nodes, and row elements in the scoring matrix are used for expressing the scoring result of one node corresponding to other nodes.
Some embodiments of the invention may be described as a scoring matrix, which is an n-1 matrix.
Wherein, S of the 1 st line1,1，S1,2…S1,n-1Can be used to represent the node scoring result for the 1 st node, S for line nn,1，Sn,2…Sn,n-1Node scoring result, S, which can be used to represent the nth nodei,jWhich is used to represent a scoring result of the ith node corresponding to some other node on the jth column.
It should be understood that the matrix has the property of being transposable, so that alternate embodiments of the present invention can represent the scoring result of one node corresponding to another node using the column elements in the scoring matrix. For example, the scoring matrix is an n-1 × n matrix, i.e., a transposed matrix from the schematic matrix described above.
The invention can realize the comprehensive and clear record of the scoring condition of the nodes and facilitate the subsequent data processing by taking the scoring matrix as the statistical mode of the scoring results of all the nodes in the block chain network, thereby leading the invention to be easier to implement and having very low possibility of error results.
And the weight setting module is used for respectively setting weights for each element of each row in the scoring matrix so as to enable the numerical value range of each element in the scoring matrix to be in a preset range.
Some embodiments of the present invention may adopt a normalization calculation mode to select appropriate weights for each row element of the matrix respectively, and set each row element in the matrix, so that each element within a preset range can be calculated and compared on the same order of magnitude. Therefore, even if different nodes adopt different transaction characteristics for scoring, the invention can still make each element be in a preset range by setting a weight mode, wherein the preset range can be as follows: 0 or more and 1 or less (i.e., [0, 1 ]).
The present embodiment utilizes w1…WnRespectively used for representing the weight set by the elements in the 1 st row to the n th row.
The matrix operation module is used for performing column operation on the current scoring matrix so as to convert the current scoring matrix into a one-dimensional scoring array; wherein, the elements in the one-dimensional score array are used for representing the behavior attribute values of the nodes.
The column operation process in some embodiments of the invention is: the row-by-row elements are subjected to the accumulation calculation or the average calculation by column units, but the present invention is not limited thereto, and for example, the row-by-row elements may be subjected to the square sum operation or the cubic sum operation, etc. The invention can improve the operation efficiency by a matrix calculation mode and reduce the occupation of computer resources, so the invention can be suitable for occasions with higher requirements on the resource usage amount.
The operation is performed with the columns in the current scoring matrix as units, and the obtained one-dimensional scoring array is shown as Q1、Q2…QnCan be used to represent the behavior attribute values, Q, of the 1 st node to the nth node, respectivelynFor representing the behavior attribute value of the nth node.
In some embodiments of the present invention, the matrix operation module is configured to calculate similarities between different elements in a same row in the current scoring matrix before performing row-column operation on the current scoring matrix, and for each row in the current scoring matrix, the matrix operation module is configured to screen and remove one or more elements with the smallest similarity with other elements.
More specifically, the matrix operation module is configured to use two elements (for example, the 1 st element and the n-1 st element of the first node) as exponents of powers respectively, so as to obtain a first exponential power (for example, a first exponential power
) And a second exponential power (e.g. of
) The inverse of the absolute value of the difference between the first exponential power and the second exponential power (e.g. by exponentiation of the first exponent
) As the similarity between two elements. It is composed ofIn the above description, the base numbers of the first exponential power and the second exponential power may be e or 10, and may be set appropriately according to actual conditions.
It should be understood that the number of elements in each row of the scoring matrix that are removed is the same to maintain the integrity of the scoring matrix data; for example, each row in the scoring matrix has two elements removed that have the least similarity to other elements in the row. Assuming that the similarity between the removed element and an element in the same row reserved in the matrix is C1, and the similarity between any two elements in the row reserved in the matrix is C2, C1 < C2. This approach enables efficient cleansing of unreasonable data, such as removing maxima and/or minima from the scoring matrix, thereby further improving the rationality and reliability of the implementation of the present invention.
By performing similarity calculation based on the above manner, the difference between two elements in the same row of the scoring matrix can be enlarged, so that at least one element with the smallest similarity with other elements can be screened and removed more quickly and accurately.
The invention can describe the node activity condition, the node transaction condition, the relation with other nodes and the like through the behavior attribute value, and the invention realizes the quantitative representation of the historical behavior of the node by utilizing the behavior attribute value. The behavior attribute value is obtained by scoring the current node by a plurality of other nodes, so that the node is evaluated by the behavior attribute value to have stronger objectivity and rationality, and a node user can trust thoroughly.
And the authority distribution module is used for distributing the authority to the nodes in the block chain network according to the behavior attribute value.
The behavior attribute values in different ranges in the embodiment of the invention correspond to different authorities, higher authorities are distributed to nodes with higher behavior attribute values, and lower authorities are distributed to nodes with lower behavior attribute values.
For example, for nodes whose behavior attribute value is within the range of [9, + ∞), class A authority is assigned, for nodes whose behavior attribute value is within the range of [8, 9], class B authority is assigned, for nodes whose behavior attribute value is within the range of [7, 8], class C authority is assigned, for nodes whose behavior attribute value is within the range of [6, 7], class D authority is assigned, for nodes whose behavior attribute value is within the range of [5, 6], class E authority is assigned, for nodes whose behavior attribute value is within the range of [4, 5], class F authority is assigned, for nodes whose behavior attribute value is within the range of [3, 4], class G authority is assigned, for nodes whose behavior attribute value is within the range of [2, 3], class H authority is assigned, for nodes whose behavior attribute value is within the range of [1, 2], class I authority is assigned, for nodes whose behavior attribute value is within the range of (∞), 1, distributing J-gear authority to nodes in the range; wherein, the A-gear authority, the B-gear authority, the C-gear authority, the D-gear authority, the E-gear authority, the F-gear authority, the G-gear authority, the H-gear authority, the I-gear authority and the J-gear authority can be gradually reduced.
Based on a means of quantitatively evaluating node permissions, the method can repeatedly and continuously implement the scheme according to a certain period (for example, one month or half month), so that the aim of dynamically adjusting each node permission in the block chain network is fulfilled, the activity of the block chain network is improved, and the rapid development of the block chain network is promoted.
The node authority distributing device can also comprise an authority updating module and a node monitoring module. The authority updating module can be used for reading the authority record table and updating the authority record table based on the node distribution authority. If there is no authority record table, the authority updating module in some embodiments of the present invention may be configured to create a new authority record table, and then fill the created authority record table based on the authority assigned to the node. It should be understood that, in other embodiments of the present invention, a new permission record table may be used each time the present invention is executed, and a permission change trend graph of each node in the blockchain network may be drawn according to multiple permission record tables, so as to enable a node permission dynamics in the blockchain network to be understood more intuitively and deeply.
The authority updating module is used for determining a node of which the authority change reaches a set value in the process of updating the authority record table, and the node monitoring module is used for monitoring the node of which the authority change reaches the set value, wherein the authority change can include but is not limited to authority increase and authority reduction. The set value may be, for example, third gear. Namely, the invention can also pay attention to the nodes with suddenly rising or suddenly falling authority. For example, if the authority of a certain node is changed from J file to B file, the node has the possibility of threatening the network security of the block chain, and the invention can perform key monitoring on the real-time transaction behavior, the data flow direction and the like of the node; for example, if the authority of a node is changed from the A file to the G file, the node is judged to possibly exit the current blockchain network. In particular, some embodiments of the present invention may further control a node whose authority suddenly increases, where the control manner includes locking resources and data flow used by the node in the blockchain network, calculating a risk value by performing a feature comparison between the node and a historical node that has been in danger, and giving an alarm or warning when the risk value exceeds a threshold value, so as to achieve the purpose of warning.
In addition, the node scoring module in some embodiments of the present invention is also configured to read the authority record table, and rank the nodes in order of the node authorities from high to low, so that the order of the node authorities from high to low is used as the order of node scoring.
As shown in fig. 3, further embodiments of the present invention can provide a computer device, including a memory and a processor, where the memory stores computer readable instructions, and the computer readable instructions, when executed by the processor, cause the processor to execute the steps of the method for assigning permissions of nodes in a blockchain network according to any of the embodiments of the present invention. The steps of the block chain network node authority assignment method may include, but are not limited to: and S100, reading the authority record table, and sequencing the nodes according to the sequence of the node authorities from high to low so as to take the sequence of the node authorities from high to low as the sequence for node scoring. The transaction characteristics between the current node and other nodes comprise at least one of transaction times, transaction amount and accounting times. And S200, scoring the current node based on the transaction characteristics between the current node and other nodes in the block chain network, and obtaining scoring results of all nodes including the current node. And S300, constructing a scoring matrix by using the scoring results of all the nodes, wherein row elements in the scoring matrix are used for expressing the scoring result of one node corresponding to other nodes. And S400, respectively setting weights for each element of each row in the scoring matrix so as to enable the numerical range of each element in the scoring matrix to be within a preset range. S500, performing column operation on the current scoring matrix to convert the current scoring matrix into a one-dimensional scoring array; wherein, the elements in the one-dimensional score array are used for representing the behavior attribute values of the nodes. In some improved schemes of the present invention, before performing column operation on the current scoring matrix, the method further includes: and calculating the similarity between different elements in the same row in the current scoring matrix, and screening and removing at least one element with the minimum similarity with other elements in each row in the current scoring matrix. More specifically, the process of calculating the similarity between different elements in the same row in the current scoring matrix includes: and taking the two elements as exponents of powers respectively to obtain a first exponential power and a second exponential power, and taking the opposite number of the absolute value of the difference between the first exponential power and the second exponential power as the similarity between the two elements. S600, distributing authority to the nodes in the block chain network according to the behavior attribute values. And S700, reading the authority record table, and updating the authority record table based on the node distribution authority. The step of updating the permission record table in some embodiments of the present invention further includes: and determining the node with the authority change reaching the set value in the process of updating the authority record table, and monitoring the node with the authority change reaching the set value. Wherein the permission change comprises a permission increase and a permission decrease.
Further embodiments of the invention may provide a storage medium having stored thereon computer-readable instructions which, when executed by one or more processors, cause the one or more processors to perform the steps of the method for partition chain network node permission assignment in any of the embodiments of the invention. The steps of the block chain network node authority assignment method may include, but are not limited to: and S100, reading the authority record table, and sequencing the nodes according to the sequence of the node authorities from high to low so as to take the sequence of the node authorities from high to low as the sequence for node scoring. The transaction characteristics between the current node and other nodes comprise at least one of transaction times, transaction amount and accounting times. And S200, scoring the current node based on the transaction characteristics between the current node and other nodes in the block chain network, and obtaining scoring results of all nodes including the current node. And S300, constructing a scoring matrix by using the scoring results of all the nodes, wherein row elements in the scoring matrix are used for expressing the scoring result of one node corresponding to other nodes. And S400, respectively setting weights for each element of each row in the scoring matrix so as to enable the numerical range of each element in the scoring matrix to be within a preset range. S500, performing column operation on the current scoring matrix to convert the current scoring matrix into a one-dimensional scoring array; wherein, the elements in the one-dimensional score array are used for representing the behavior attribute values of the nodes. In some improved schemes of the present invention, before performing column operation on the current scoring matrix, the method further includes: and calculating the similarity between different elements in the same row in the current scoring matrix, and screening and removing at least one element with the minimum similarity with other elements in each row in the current scoring matrix. More specifically, the process of calculating the similarity between different elements in the same row in the current scoring matrix includes: and taking the two elements as exponents of powers respectively to obtain a first exponential power and a second exponential power, and taking the opposite number of the absolute value of the difference between the first exponential power and the second exponential power as the similarity between the two elements. S600, distributing authority to the nodes in the block chain network according to the behavior attribute values. And S700, reading the authority record table, and updating the authority record table based on the node distribution authority. The step of updating the permission record table in some embodiments of the present invention further includes: determining a node of which the authority change reaches a set value in the process of updating the authority record table, and monitoring the node of which the authority change reaches the set value; the rights changes include rights addition and rights subtraction.
It is emphasized that, in order to further ensure the privacy and security of the data in the embodiments of the present invention, the data such as the authority record table and the scoring matrix in some embodiments of the present invention may also be stored in the nodes of a block chain.
The block chain is a novel application mode of computer technologies such as distributed data storage, point-to-point transmission, a consensus mechanism, an encryption algorithm and the like. A block chain (Blockchain), which is essentially a decentralized database, is a series of data blocks associated by using a cryptographic method, and each data block contains information of a batch of network transactions, so as to verify the validity (anti-counterfeiting) of the information and generate a next block. The blockchain may include a blockchain underlying platform, a platform product service layer, an application service layer, and the like.
The logic and/or steps represented in the flowcharts or otherwise described herein, such as an ordered listing of executable instructions that can be considered to implement logical functions, can be embodied in any computer-readable storage medium for use by or in connection with an instruction execution system, apparatus, or device, such as a computer-based system, processor-containing system, or other system that can fetch the instructions from the instruction execution system, apparatus, or device and execute the instructions. For the purposes of this description, a "computer-readable storage medium" can be any means that can contain, store, communicate, propagate, or transport the program for use by or in connection with the instruction execution system, apparatus, or device. The computer readable storage medium may be non-volatile or volatile. More specific examples (a non-exhaustive list) of the computer readable storage medium would include the following: an electrical connection (electronic device) having one or more wires, a portable computer cartridge (magnetic device), a Random Access Memory (RAM), a Read-Only Memory (ROM), an Erasable Programmable Read-Only Memory (EPROM-Only Memory, or flash Memory), an optical fiber device, and a portable Compact Disc Read-Only Memory (CDROM). Additionally, the computer-readable storage medium may even be paper or another suitable medium upon which the program is printed, as the program can be electronically captured, via for instance optical scanning of the paper or other medium, then compiled, interpreted or otherwise processed in a suitable manner if necessary, and then stored in a computer memory.
It should be understood that portions of the present invention may be implemented in hardware, software, firmware, or a combination thereof. In the above embodiments, the various steps or methods may be implemented in software or firmware stored in memory and executed by a suitable instruction execution system. For example, if implemented in hardware, as in another embodiment, any one or combination of the following techniques, which are known in the art, may be used: a discrete logic circuit having a logic Gate circuit for implementing a logic function on a data signal, an application specific integrated circuit having an appropriate combinational logic Gate circuit, a Programmable Gate Array (PGA), a Field Programmable Gate Array (FPGA), or the like.
In the description herein, references to the description of the term "the present embodiment," "one embodiment," "some embodiments," "an example," "a specific example," or "some examples," etc., mean that a particular feature, structure, material, or characteristic described in connection with the embodiment or example is included in at least one embodiment or example of the present invention. In this specification, the schematic representations of the terms used above are not necessarily intended to refer to the same embodiment or example. Furthermore, the particular features, structures, materials, or characteristics described may be combined in any suitable manner in any one or more embodiments or examples. Furthermore, various embodiments or examples and features of different embodiments or examples described in this specification can be combined and combined by one skilled in the art without contradiction.
Furthermore, the terms "first", "second" and "first" are used for descriptive purposes only and are not to be construed as indicating or implying relative importance or implicitly indicating the number of technical features indicated. Thus, a feature defined as "first" or "second" may explicitly or implicitly include at least one such feature. In the description of the present invention, "a plurality" means at least two, e.g., two, three, etc., unless specifically limited otherwise.
The above description is only for the purpose of illustrating the preferred embodiments of the present invention and is not to be construed as limiting the invention, and any modifications, equivalents and simplifications made in the spirit of the present invention are intended to be included in the scope of the present invention.
Claims (10)
1. A method for assigning block chain network node permissions, comprising:
scoring the current node based on the transaction characteristics between the current node and other nodes in the block chain network, and obtaining scoring results of all nodes including the current node;
constructing a scoring matrix by using the scoring results of all the nodes, wherein row elements in the scoring matrix are used for expressing the scoring result of one node corresponding to other nodes;
setting weights for each element of each row in the scoring matrix respectively so as to enable the numerical value range of each element in the scoring matrix to be within a preset range;
performing column operation on a current scoring matrix to convert the current scoring matrix into a one-dimensional scoring array; wherein, the elements in the one-dimensional scoring array are used for representing the behavior attribute values of the nodes;
and distributing authority to the nodes in the block chain network according to the behavior attribute value.
2. The method of claim 1, wherein the assigning the permission to the node in the blockchain network according to the behavior attribute value further comprises:
and reading an authority record table, and updating the authority record table based on the node distribution authority.
3. A method for assigning permissions to network nodes of a block chain as claimed in claim 2 wherein said step of updating said permission record table further comprises:
determining a node with the authority change reaching a set value, and monitoring the node with the authority change reaching the set value; wherein the permission change comprises a permission increase and a permission decrease.
4. The method of claim 1, wherein before scoring the current node based on transaction characteristics between the current node and other nodes in the blockchain network, further comprising:
and reading the authority record table, and sequencing the nodes according to the sequence of the node authorities from high to low so as to take the sequence of the node authorities from high to low as the sequence for node scoring.
5. A method as claimed in claim 1, further comprising, prior to said performing column operations on the current scoring matrix:
calculating the similarity between different elements in the same row in the current scoring matrix;
and screening and removing at least one element with the minimum similarity with other elements for each row in the current scoring matrix.
6. The method of claim 5, wherein calculating the similarity between different elements in the same row in the current scoring matrix comprises:
taking the two elements as exponents of powers respectively to obtain a first exponential power and a second exponential power;
and taking the inverse of the absolute value of the difference between the first exponential power and the second exponential power as the similarity between the two elements.
7. A method for assigning block chain network node permissions according to claim 1,
the transaction characteristics between the current node and other nodes comprise at least one of transaction times, transaction amount and accounting times.
8. A device for assigning block chain network node permissions, comprising:
the node scoring module is used for scoring the current node based on the transaction characteristics between the current node and other nodes in the block chain network and obtaining scoring results of all nodes including the current node;
the matrix construction module is used for constructing a scoring matrix by using the scoring results of all the nodes, and row elements in the scoring matrix are used for expressing the scoring result of one node corresponding to other nodes;
the weight setting module is used for respectively setting weights for each element of each row in the scoring matrix so as to enable the numerical value range of each element in the scoring matrix to be within a preset range;
the matrix operation module is used for carrying out column operation on the current scoring matrix so as to convert the current scoring matrix into a one-dimensional scoring array; wherein, the elements in the one-dimensional scoring array are used for representing the behavior attribute values of the nodes;
and the authority distribution module is used for distributing the authority to the nodes in the block chain network according to the behavior attribute value.
9. A computer device comprising a memory and a processor, the memory having stored therein computer readable instructions which, when executed by the processor, cause the processor to perform the steps of the blockchain network node permission assignment method of any one of claims 1 to 7.
10. A storage medium having stored thereon computer readable instructions which, when executed by one or more processors, cause the one or more processors to perform the steps of the blockchain network node permission assignment method of any one of claims 1 to 7.
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| PCT/CN2021/096756 WO2022095422A1 (en) | 2020-11-03 | 2021-05-28 | Method and apparatus for assigning permissions for nodes in blockchain network, computer device, and medium |
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