CN116016544A - PBFT consensus method and system for Internet of things equipment - Google Patents
PBFT consensus method and system for Internet of things equipment Download PDFInfo
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Abstract
The invention provides a PBFT consensus method and a system for Internet of things equipment, wherein the method comprises the following steps: acquiring behavior characteristics of nodes in a network, and grading the reputation of the nodes according to the behavior characteristics; dividing the nodes into a main node candidate set and a consensus node set according to the reputation scoring result, wherein the reputation scores of the nodes in the main node candidate set are higher than or equal to the reputation scores of the nodes in the consensus node set; selecting a master node from the master node candidate set, and verifying the identity of the master node; and the main node passing the identity verification achieves consensus among consensus nodes in the consensus node set through RV-PBFT algorithm. According to the PBFT consensus method for the Internet of things equipment, the nodes are subjected to reputation scoring through the behavior characteristics of the nodes, and the nodes with the front reputation scores are selected to form the master node candidate set, so that the probability that malicious nodes and fault nodes are selected as master nodes to participate in consensus is reduced, the probability of failure of the consensus caused by attack is reduced, and the success rate of the consensus is improved.
Description
Technical Field
The application relates to the field of block chain consensus, in particular to a PBFT consensus method and system for Internet of things equipment.
Background
The consensus algorithm is the soul of the blockchain. The system mainly plays a role in coordinating the accounts of all nodes in the blockchain network to keep consistent so as to ensure the consistency of the distributed system. The consensus mechanism is an algorithm for realizing distributed consensus of the block chain transaction, and is a rule which each node must adhere to, so that the consistency and stability of the whole system are ensured.
Currently, the conventional main consensus algorithms include a PoW (workload proof) algorithm, a PoS (rights and interests proof) algorithm and a PBFT (practical Bayesian fault tolerance) algorithm. The PoW obtains billing rights for a block by requiring participants to "mine. By this, poW maintains the correctness of the blockchain, but this requires a huge computing power. The token rewarding mechanism is introduced into the rights and interests proving (PoS), so that the consumption of computational resources is greatly reduced, the defect that a large amount of resources in the PoW are wasted is solved, but the problems of centralization and poor consensus efficiency exist. The PBFT consensus algorithm solves the problem of Bayesian general in the traditional distributed system, so that the network has high fault tolerance, and has the advantages that the algorithm not only supports fault-tolerant fault nodes, but also supports fault-tolerant malicious nodes. Accounting is completed by cooperation of multiple people, so that each block has finalizability, and if more than one third of nodes fail, the system cannot work normally.
However, the PBFT consensus algorithm still has the problems of random selection of the master node, overlarge consensus communication overhead and the like. The master node is acted by the nodes in the network according to the sequence number, the probability that the fault node or the malicious node is elected as the master node is high, no punishment measures are taken for the malicious node, the problem is solved only by using the view change protocol to rotate the nodes, the common recognition efficiency of the system is reduced due to frequent change of the view, and the safety of the system is also influenced.
Disclosure of Invention
In order to solve one of the technical problems, the invention provides a PBFT consensus method and a PBFT consensus system for Internet of things equipment.
The embodiment of the invention provides a PBFT consensus method for equipment of the Internet of things, which comprises the following steps:
acquiring behavior characteristics of nodes in a network, and grading reputation of the nodes according to the behavior characteristics;
dividing the nodes into a main node candidate set and a consensus node set according to the reputation scoring result, wherein the reputation scores of the nodes in the main node candidate set are higher than or equal to the reputation scores of the nodes in the consensus node set;
selecting a master node from the master node candidate set, and verifying the identity of the master node;
and the main node passing the identity verification achieves consensus among consensus nodes in the consensus node set through RV-PBFT algorithm.
Preferably, the process of obtaining the behavior characteristics of the nodes in the network and scoring the reputation of the nodes according to the behavior characteristics includes:
acquiring the times of fault behaviors, the times of active and wrought behaviors and the times of participation effective consensus completion behaviors of nodes in a network, and setting the scores of the fault behaviors, the active and wrought behaviors and the participation effective consensus completion behaviors, wherein the times of participation effective consensus completion are added items, and the times of fault and active and wrought behaviors are subtracted items;
obtaining a fault behavior value, an active and a passive values and a participation effective consensus completion value according to the fault behavior times, the active and passive behavior times and the participation effective consensus completion behavior times and the corresponding scores;
setting a basic reputation value of the node, and summing the basic reputation value, the fault behavior value, the initiative and aversion value and the participation effective consensus completion value to obtain the reputation score of the node.
Preferably, the process of dividing the nodes into a main node candidate set and a consensus node set according to the reputation scoring result comprises:
and dividing the nodes into a main node candidate set and a consensus node set according to the credit scoring result and a preset proportion.
Preferably, the process of selecting a master node from the master node candidate set and verifying the identity of the master node includes:
selecting a master node from the master node candidate set through a verifiable random function, wherein nodes except the master node in the master node candidate set are all copy nodes;
the master node broadcasts seed, PK and proof to a copy node, wherein PK is a public key of the master node, the seed is a seed of the master node randomly selected from a master node candidate set, the seed is a hash value of a current consensus Round number, and proof is a proof of a random number;
the duplicate node verifies whether the proof is generated by the master node according to the seed of the master node, and if the proof is generated by the master node according to the seed of the master node, the master node passes the identity verification.
Preferably, the process of enabling the authenticated master node to achieve consensus among consensus nodes in the consensus node set through RV-PBFT algorithm comprises the following steps:
the method comprises the steps that a master node obtains a request message initialized by a client;
the master node generates a pre-preparation message according to the request message and sends the pre-preparation message to a copy node;
the copy node verifies the pre-preparation message, generates a preparation message after the verification is successful, and sends the preparation message to other copy nodes;
the other copy nodes verify the preparation message and send a commit message to nodes in the consensus node set after verification is successful;
and acquiring a request, executing the request by a node in the consensus node when the request is in a state corresponding to the commit message, and transmitting an execution result to the client, so that the consensus is completed when the client acquires the same preset number of execution results.
Preferably, after the authenticated master node reaches consensus among consensus nodes in the consensus node set through RV-PBFT algorithm, the method further comprises:
and re-scoring the node for reputation.
Preferably, after the re-scoring the node for reputation, the method further comprises:
and when the lowest reputation score of the nodes in the main node candidate set is lower than the highest reputation score of the nodes in the consensus node set, exchanging the node with the lowest reputation score in the main node candidate set with the node with the highest reputation score in the consensus node set.
The second aspect of the embodiment of the invention provides a PBFT consensus system for equipment of the Internet of things, which comprises the following components:
the reputation score calculating unit is used for obtaining the behavior characteristics of the nodes in the network and performing reputation scoring on the nodes according to the behavior characteristics;
the node dividing unit is used for dividing the nodes into a main node candidate set and a consensus node set according to the reputation scoring result, wherein the reputation scores of the nodes in the main node candidate set are higher than or equal to the reputation scores of the nodes in the consensus node set;
a master node selecting unit, configured to select a master node from the master node candidate set, and verify the identity of the master node;
and the consensus unit is used for enabling the main node passing the identity verification to achieve consensus among consensus nodes in the consensus node set through an RV-PBFT algorithm.
A third aspect of an embodiment of the present invention provides an electronic device, including:
a memory for storing a computer program;
and the processor is used for realizing the PBFT consensus method facing the equipment of the Internet of things when executing the computer program.
The fourth aspect of the embodiment of the present invention provides a computer readable storage medium, where computer executable instructions are stored, where the computer executable instructions implement the PBFT consensus method for an internet of things device as described above when loaded and executed by a processor.
The beneficial effects of the invention are as follows: according to the PBFT consensus method for the Internet of things equipment, the nodes are subjected to reputation scoring through the behavior characteristics of the nodes, and the nodes with the front reputation scores are selected to form the master node candidate set, so that the probability that malicious nodes and fault nodes are selected as master nodes to participate in consensus is reduced, the probability of failure of the consensus caused by attack is reduced, and the success rate of the consensus is improved.
Drawings
The accompanying drawings, which are included to provide a further understanding of the application and are incorporated in and constitute a part of this application, illustrate embodiments of the application and together with the description serve to explain the application and do not constitute an undue limitation to the application. In the drawings:
fig. 1 is a flowchart of a PBFT consensus method for an internet of things device according to embodiment 1 of the present invention;
FIG. 2 is a schematic diagram illustrating the implementation of consensus among consensus nodes in a consensus node set by RV-PBFT algorithm according to embodiment 1 of the present invention;
fig. 3 is a schematic diagram of a PBFT consensus method for an internet of things device according to embodiment 1 of the present invention compared with an existing consensus method;
fig. 4 is a schematic diagram of a PBFT consensus system for an internet of things device according to embodiment 2 of the present invention.
Detailed Description
In order to make the technical solutions and advantages of the embodiments of the present application more apparent, the following detailed description of exemplary embodiments of the present application is given with reference to the accompanying drawings, and it is apparent that the described embodiments are only some of the embodiments of the present application and not exhaustive of all the embodiments. It should be noted that, in the case of no conflict, the embodiments and features in the embodiments may be combined with each other.
Example 1
As shown in fig. 1, this embodiment proposes a PBFT consensus method for an internet of things device, where the method includes:
s101, obtaining behavior characteristics of nodes in a network, and grading reputation of the nodes according to the behavior characteristics.
In the embodiment, all behavior characteristics of nodes in a network are collected first, so that reputation scoring is carried out on the nodes according to all behavior characteristics. The embodiment selects fault behaviors, initiative and aversion behaviors and participation in effective consensus completion behaviors as behavior characteristics.
Specifically, the times of failure behaviors, the times of active and bad behaviors and the times of participation in effective consensus completion behaviors of nodes in the network are obtained, and scores of the failure behaviors, the active and bad behaviors and the participation in the effective consensus completion behaviors are set. The number of times of completion of the effective consensus is an additive term, and the number of times of faults and the number of times of active aversion are subtractive terms. And obtaining a fault behavior value, a initiative and aversion value and a participation effective consensus completion value according to the fault behavior times, the initiative and aversion behavior times and the participation effective consensus completion behavior times and the corresponding scores. Setting a basic credit value of the node, and summing the basic credit value, the fault action value, the initiative and the aversion value and the participation effective consensus completion value to obtain the credit score of the node. The reputation score calculation process is as follows:
D Credit (i)＝D Init (i)+k succ (i)-5*k Fault (i)-10*k Mal (i)
wherein k is Fault (i) For the times of node failure, k Mal (i) For node active times, k Succ (i) The number of completions is effectively agreed for the node participation. Reputation score D Credit (i) The maximum value of (2) is 100 and the minimum value is 0. The basic reputation value of the just added node is D Init (i) =60. And evaluating the reputation score of the node according to the behavior characteristics of the node in the system, wherein the reputation score of the node is increased by 1 when the node successfully participates in one consensus in the system. And if the node fails once in the system, subtracting 5 from the node reputation score. If the node actively acts once in the system, the reputation score is reduced by 10 points. Of course, the setting of the score may be adjusted according to the actual situation, and the present embodiment is merely illustrative and not particularly limited.
S102, dividing the nodes into a main node candidate set and a consensus node set according to the reputation scoring result.
Specifically, according to the reputation scoring result, the nodes are divided into a main node candidate set and a consensus node set according to a preset proportion, and the reputation scores of the nodes in the main node candidate set are higher than or equal to the reputation scores of the nodes in the consensus node set. Wherein, nodes with reputation scores at the first 1/3 can be formed into a master node candidate set, and the rest nodes are formed into a consensus node set. By forming the nodes with the forefront reputation scores into the master node candidate set, the probability that malicious nodes and fault nodes are selected as master nodes to participate in consensus is reduced, so that the probability of failure of the consensus caused by attack is improved, and the success rate of the consensus is improved.
The node reputation score of the main node candidate set is highest, the node in the main node candidate set is selected to serve as the main node, and the node reputation score in the consensus node set is lower and is not suitable for serving as the main node, so that the nodes only participate in consensus.
S103, selecting a master node from the master node candidate set, and verifying the identity of the master node.
Specifically, the master node is selected from the master node candidate set through the verifiable random function, and nodes except the master node in the master node candidate set are all copy nodes. The master node broadcasts the seed, PK and proof to the duplicate nodes. The duplicate node verifies the master node identity by means of Verify (PK, proof). If the verification is passed, a subsequent consensus process is performed. Wherein PK is the public key of the master node, seed is the candidate set of the master node to randomly select the seed of the master node, the seed is the hash value of the current consensus Round number Round, and proof is the proof of the random number. The duplicate node verifies whether proof is generated by the master node according to the seed of the master node, and if proof is generated by the master node according to the seed of the master node, the identity verification of the master node is passed.
S104, the main node passing the identity verification achieves consensus among consensus nodes in the consensus node set through RV-PBFT algorithm.
Specifically, as shown in fig. 2, the master node obtains a request message initialized by the client. The master node generates a pre-preparation message according to the request message and sends the pre-preparation message to the replica node. And the copy node verifies the pre-preparation message, generates the preparation message after the verification is successful, and sends the preparation message to other copy nodes. The other copy nodes verify the preparation message and send a commit message to the nodes in the consensus node set after the verification is successful.
And acquiring a request, executing the request by a node in the consensus node when the request is in a state corresponding to the commit message, and transmitting an execution result to the client, so that the consensus is completed when the client acquires the same preset number of execution results. The preset number can be set to be f+1, the total number of nodes is n, n is not less than 3f+1, and in order to ensure that the consensus can be correctly achieved, the agreement of 2f+1 nodes is ensured, and the number of error nodes is less than f.
Further, after the authenticated master node reaches consensus among consensus nodes in the consensus node set through RV-PBFT algorithm, the method provided by this embodiment further includes:
and re-scoring the node for reputation.
After re-scoring the nodes, the present embodiment also adjusts the nodes in the master node candidate set and the consensus node set. Specifically, when the lowest reputation score of the nodes in the main node candidate set is lower than the highest reputation score of the nodes in the consensus node set, the nodes with the lowest reputation score in the main node candidate set are exchanged with the nodes with the highest reputation score in the consensus node set.
Fig. 3 is a schematic diagram illustrating a comparison between the consensus method and the prior art method according to the present embodiment. It can be seen that the RV-PBFT fault tolerant consensus algorithm has lower transaction delay than the other two schemes with the same number of nodes. As the number of nodes increases, the consensus delay of the RV-PBFT algorithm increases more slowly, and experiments show that the RV-PBFT fault-tolerant consensus algorithm has lower transaction delay and is more stable.
According to the embodiment, the nodes are subjected to reputation scoring through the behavior characteristics of the nodes, the nodes with the front reputation scoring are selected to form the master node candidate set, the probability that malicious nodes and fault nodes are selected as master nodes to participate in consensus is reduced, so that the probability of failure of the consensus caused by attack is improved, and the success rate of the consensus is improved.
Example 2
As shown in fig. 4, this embodiment proposes a PBFT consensus system for an internet of things device, where the system includes:
the reputation score calculating unit is used for obtaining the behavior characteristics of the nodes in the network and performing reputation scoring on the nodes according to the behavior characteristics;
the node dividing unit is used for dividing the nodes into a main node candidate set and a consensus node set according to the reputation scoring result, wherein the reputation scores of the nodes in the main node candidate set are higher than or equal to the reputation scores of the nodes in the consensus node set;
a master node selecting unit, configured to select a master node from the master node candidate set, and verify the identity of the master node;
and the consensus unit is used for enabling the main node passing the identity verification to achieve consensus among consensus nodes in the consensus node set through an RV-PBFT algorithm.
Because the embodiment of the PBFT consensus system facing the internet of things device corresponds to the embodiment of the PBFT consensus method part facing the internet of things device, the embodiment of the PBFT consensus system facing the internet of things device is described with reference to the embodiment of the PBFT consensus method part facing the internet of things device, and will not be repeated herein.
Example 3
The present embodiment proposes an electronic device including:
a memory for storing a computer program;
and the processor is used for realizing the PBFT consensus method facing the equipment of the Internet of things when executing the computer program.
Because the embodiment of the electronic device portion corresponds to the embodiment of the PBFT consensus method portion facing the internet of things device, the embodiment of the electronic device portion refers to the description of the embodiment of the PBFT consensus method portion facing the internet of things device, and will not be repeated herein.
Example 4
The embodiment provides a computer readable storage medium, in which computer executable instructions are stored, and when the computer executable instructions are loaded and executed by a processor, the PBFT consensus method for the internet of things device is implemented.
Because the embodiment of the computer readable storage medium portion corresponds to the embodiment of the PBFT consensus method portion facing the internet of things device, the embodiment of the storage medium portion is described with reference to the embodiment of the PBFT consensus method facing the internet of things device, and will not be repeated here.
It will be apparent to those skilled in the art that various modifications and variations can be made in the present application without departing from the spirit or scope of the application. Thus, if such modifications and variations of the present application fall within the scope of the claims and the equivalents thereof, the present application is intended to cover such modifications and variations.
Claims (10)
1. The PBFT consensus method for the equipment of the Internet of things is characterized by comprising the following steps of:
acquiring behavior characteristics of nodes in a network, and grading reputation of the nodes according to the behavior characteristics;
dividing the nodes into a main node candidate set and a consensus node set according to the reputation scoring result, wherein the reputation scores of the nodes in the main node candidate set are higher than or equal to the reputation scores of the nodes in the consensus node set;
selecting a master node from the master node candidate set, and verifying the identity of the master node;
and the main node passing the identity verification achieves consensus among consensus nodes in the consensus node set through RV-PBFT algorithm.
2. The method of claim 1, wherein the step of obtaining behavior characteristics of nodes in the network and scoring the reputation of the nodes based on the behavior characteristics comprises:
acquiring the times of fault behaviors, the times of active and wrought behaviors and the times of participation effective consensus completion behaviors of nodes in a network, and setting the scores of the fault behaviors, the active and wrought behaviors and the participation effective consensus completion behaviors, wherein the times of participation effective consensus completion are added items, and the times of fault and active and wrought behaviors are subtracted items;
obtaining a fault behavior value, an active and a passive values and a participation effective consensus completion value according to the fault behavior times, the active and passive behavior times and the participation effective consensus completion behavior times and the corresponding scores;
setting a basic reputation value of the node, and summing the basic reputation value, the fault behavior value, the initiative and aversion value and the participation effective consensus completion value to obtain the reputation score of the node.
3. The method of claim 1, wherein the step of dividing the nodes into a master node candidate set and a consensus node set based on reputation scoring results comprises:
and dividing the nodes into a main node candidate set and a consensus node set according to the credit scoring result and a preset proportion.
4. The method of claim 1, wherein the selecting a master node from the master node candidate set and verifying the identity of the master node comprises:
selecting a master node from the master node candidate set through a verifiable random function, wherein nodes except the master node in the master node candidate set are all copy nodes;
the master node broadcasts seed, PK and proof to a copy node, wherein PK is a public key of the master node, the seed is a seed of the master node randomly selected from a master node candidate set, the seed is a hash value of a current consensus Round number, and proof is a proof of a random number;
the duplicate node verifies whether the proof is generated by the master node according to the seed of the master node, and if the proof is generated by the master node according to the seed of the master node, the master node passes the identity verification.
5. The method of claim 4, wherein the process of consensus among the consensus nodes in the consensus node set by the master node passing the authentication through the RV-PBFT algorithm comprises:
the method comprises the steps that a master node obtains a request message initialized by a client;
the master node generates a pre-preparation message according to the request message and sends the pre-preparation message to a copy node;
the copy node verifies the pre-preparation message, generates a preparation message after the verification is successful, and sends the preparation message to other copy nodes;
the other copy nodes verify the preparation message and send a commit message to nodes in the consensus node set after verification is successful;
and acquiring a request, executing the request by a node in the consensus node when the request is in a state corresponding to the commit message, and transmitting an execution result to the client, so that the consensus is completed when the client acquires the same preset number of execution results.
6. The method of claim 1, wherein after the authentication-passing master node reaches a consensus among consensus nodes in a set of consensus nodes by RV-PBFT algorithm, the method further comprises:
and re-scoring the node for reputation.
7. The method of claim 6, wherein after the re-scoring the node for reputation, the method further comprises:
and when the lowest reputation score of the nodes in the main node candidate set is lower than the highest reputation score of the nodes in the consensus node set, exchanging the node with the lowest reputation score in the main node candidate set with the node with the highest reputation score in the consensus node set.
8. The utility model provides a PBFT consensus system towards thing networking device which characterized in that, the system includes:
the reputation score calculating unit is used for obtaining the behavior characteristics of the nodes in the network and performing reputation scoring on the nodes according to the behavior characteristics;
the node dividing unit is used for dividing the nodes into a main node candidate set and a consensus node set according to the reputation scoring result, wherein the reputation scores of the nodes in the main node candidate set are higher than or equal to the reputation scores of the nodes in the consensus node set;
a master node selecting unit, configured to select a master node from the master node candidate set, and verify the identity of the master node;
and the consensus unit is used for enabling the main node passing the identity verification to achieve consensus among consensus nodes in the consensus node set through an RV-PBFT algorithm.
9. An electronic device, comprising:
a memory for storing a computer program;
a processor for implementing the PBFT consensus method for an internet of things device according to any of claims 1 to 7 when executing the computer program.
10. A computer readable storage medium, wherein computer executable instructions are stored in the computer readable storage medium, and when loaded and executed by a processor, the computer executable instructions implement the PBFT consensus method for an internet of things device according to any one of claims 1 to 7.
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