CN115134161A - Defense method for resisting tenure forgery based on Raft consensus algorithm - Google Patents
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Abstract
The invention discloses a defense method for resisting tenure forgery based on a Raft consensus algorithm, which is implemented according to the following steps: step 1, constructing a Raft cluster, and creating a Raft node to add into the constructed Raft cluster; step 2, initializing the Raft cluster obtained in the step 1, and creating initial data; step 3, setting an interval range of any period increase in the election time; step 4, starting the Raft cluster, wherein all the Raft nodes in the Raft cluster are follower states; and 5, judging whether the node is a malicious node or not according to the step 4, and if the node is the malicious node, forcibly returning the state to the follower state. By setting the increment range of the random value, the fake random attack of a malicious node on the Raft cluster in the election process is effectively prevented, the fake random defense is achieved in the Raft consensus algorithm election process, and the election process and the result of the Raft consensus algorithm are fairer, safe and reliable.
Description
Technical Field
The invention relates to the technical field of block chain consensus mechanisms, in particular to a defense method for resisting tenure forgery based on a Raft consensus algorithm.
Background
The consensus algorithm, as a key element and a core component of the blockchain technology, is a leading hotspot in the development of distributed system technology in recent years. With the rapid development of the blockchain technology, new consensus algorithms are continuously proposed, and improved algorithms are continuously verified. From the beginning of intelligently issuing the white paper of the bitcoin, the internet is at a new revolution starting point, the block chain technology has wide application prospect and various ramifications, and experts and scholars in the field of block chains pay attention to the performance and the safety of the technology and realize application landing on the basis of the performance and the safety. One of the core values of the blockchain is consensus and is also one of the properties of the blockchain. The consensus algorithm refers to a distributed algorithm in which multiple Raft nodes operate to achieve the same data state in a distributed scenario. The existing Raft consensus algorithm is a research direction which needs to be continuously researched in terms of safety, particularly aiming at the problem that the fairness is disturbed in the algorithm election process is optimized because the malicious nodes are not processed completely.
The Raft consensus algorithm mainly depends on a voting mechanism and a log replication mechanism to realize consensus among nodes. In the Raft algorithm, each Raft node is identified by three identities: a leader, a follower, and a candidate. The leader is responsible for interaction with the client and log replication, and only one leader node is allowed to be owned in the system Raft cluster at any certain time. The time instants referred to herein specify time as arbitrary values of indefinite length in the Raft algorithm, with one and only one leader node in each arbitrary period. The follower node passively responds in the request RPC in the system interaction process, and does not actively initiate the request RPC. The candidates are the follower transition leader's transition state. In a distributed scenario of the Raft algorithm, fault conditions such as network packet loss, node downtime, node cheating and the like may occur, and the consensus algorithm needs to be capable of tolerating the faults, so that a plurality of Raft nodes can obtain the same data state. Consensus algorithms can be divided into two categories, depending on the type of fault that can be tolerated: (1) the delay tolerant error algorithm can tolerate the benign errors of the nodes such as network packet loss, clock drift and partial node delay. Common algorithms are Paxos, Raft. (2) The Byzantine error tolerant algorithm can tolerate any type of errors of partial nodes, including the condition that the nodes are bad. Common algorithms are PBFT, PoW, PoS, etc.
The Raft consensus algorithm can only tolerate a downtime error algorithm, and as malicious nodes cannot be identified, the algorithm has many fairness and safety problems in the processes of leader node election, log replication and the like. An exception problem needs to be considered in the flow of leader election: in a distributed Raft cluster, if the problem that a certain Raft node intentionally badly acts exists, so that other follower nodes in the Raft cluster cannot fairly compete for the identity state of a leader, the method can disturb fair competition of the nodes in the Raft cluster by means of tampering voting and logs or maliciously increasing the deadline value of the follower nodes in the Raft cluster in the leader election process. The invention mainly provides a solution for the problem that nodes maliciously increase own random value, under the condition that logs are the same, the nodes maliciously increase own random value to enable the own random value to be larger than those of other nodes, and the malicious nodes change the own identity state into a leader state according to an election mechanism of a Raft consensus algorithm, so that the fairness of the whole Raft cluster is seriously disturbed.
Disclosure of Invention
The invention aims to provide a defense method for resisting tenure forgery based on a Raft consensus algorithm, which solves the problems that the fairness of a Raft cluster is maliciously disturbed in the election process and the algorithm safety is not high enough in the existing algorithm.
In order to achieve the purpose, the invention provides the following technical scheme: a defense method for resisting tenure forgery based on a Raft consensus algorithm is implemented according to the following steps:
step 1, constructing a Raft cluster, and creating a Raft node to add into the constructed Raft cluster;
step 2, initializing the Raft cluster obtained in the step 1, and creating initial data;
step 4, starting the Raft cluster, wherein all the Raft nodes in the Raft cluster are follower states;
step 5, judging whether the node is a malicious node or not according to the step 4, and if the node is the malicious node, forcibly returning the state to the follower state;
and 6, storing the times of taking each Raft node as a malicious node into a third-party block chain distributed account book, and if the times of taking a certain Raft node as a malicious node are more than three times, moving the malicious node out of the Raft cluster.
The invention is also characterized in that:
the step 1 specifically comprises the following steps: creating three Raft nodes so as to form a Raft cluster; in the interface provided by the Raft consensus algorithm, a NewRaft method is provided to newly build a Raft structure.
The step 2 specifically comprises the following steps: creating a Raft cluster through the step 1, and initializing the Raft cluster; and calling an initialization function, and creating an expiration date and node information as initial data.
The step 3 specifically comprises the following steps: and setting an interval range a-b of the optional period increase in the election time through the optional period increase interval of the normal election time when the test node is positioned under the non-malicious node.
The step 4 specifically comprises the following steps: starting a Raft cluster, wherein all Raft node states in the Raft cluster are follower states, and the method is implemented according to the following steps:
step 4.1, starting a first Raft node in a Bootstrap mode, and adding the other Raft nodes into the Raft cluster when starting the other Raft nodes;
step 4.2, after the first-started Raft node receives the request, the address of the other side is obtained;
and 4.3, the Raft nodes applying for adding the Raft cluster automatically enter a follower state, and then the Raft nodes of the Raft cluster can normally communicate with each other.
The step 5 specifically comprises the following steps: according to the random growth interval range set in the step 2, the method is implemented according to the following steps:
step 5.1, if the tenure increment value delta Term of a certain Raft node in an election time is more than a < delta Term < b, judging that the Raft node is not a malicious node, and turning to step 5.4;
step 5.2, if the increment value delta Term of a certain Raft node in the free period of an election time is larger than b, judging that the Raft node is possibly a malicious node, and turning to step 5.3;
step 5.3, the Raft node is a malicious node, the identity state of the malicious node is forcibly returned to a follower state from a candidate state or a leader state, and the tenure value of the malicious node is forcibly converted to be the same as the tenure values of other nodes;
and 5.4, according to the rule of the Raft consensus algorithm, electing the leader of the Raft cluster with the largest period value and the newest log, and copying the request to other Raft nodes in a log mode.
The step 6 specifically comprises the following steps: and (5) judging whether the Raft node is a malicious node or not according to the step (5), if the node is the malicious node, linking the number num of times of the malicious node to a distributed account book of a third-party block chain in a transaction mode, and if the number num is more than 3, punishing to move the malicious node out of the Raft cluster.
Compared with the prior art, the invention has the following beneficial effects:
the invention discloses a defense method for resisting tenure forgery based on a Raft consensus algorithm, which solves the problem that in the technology, in the process of the Raft consensus algorithm, an arbitrary value of a node is intentionally increased by a malicious node to obtain the identity of a leader, so that the election fairness in a Raft cluster of the algorithm is ensured. By setting the range of increasing the random value, the attack of malicious nodes on the random cluster is effectively prevented, the defense against counterfeiting the random in the election process of the random consensus algorithm is realized, and the election process and the result of the random consensus algorithm are safer and more reliable.
Drawings
FIG. 1 is a system flow chart of the forgery prevention grace period defense method based on the Raft consensus algorithm;
fig. 2 is an experimental flow chart of malicious node counterfeiting tenure attack based on a Raft consensus algorithm.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only some embodiments of the present invention, and not all 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 invention.
As shown in fig. 1 and fig. 2, the invention relates to a defense method against tenuous forging based on a Raft consensus algorithm, which is implemented according to the following steps:
step 1, constructing a Raft cluster, and creating a Raft node to be added into the constructed Raft cluster. The method is implemented according to the following steps: three Raft nodes are created, in an interface provided by a Raft consensus algorithm, NewRaft is provided to newly create a Raft structure, the structure represents one Raft node, and three Raft nodes are repeatedly created to form a Raft cluster.
Step 2, initializing the Raft cluster obtained in the step 1, and creating initial data; and calling an initialization function, initializing information such as a Raft node address (raftAddr), a Raft node ID (raftId) and the like of the myRaft function, and initializing an expiration value Term of the added Raft node to be 1.
ΔTerm＝currentTerm-lastTerm
step 4, starting the Raft cluster, wherein all the states of the Raft nodes are follower states; starting a Raft cluster through Bootstrap, monitoring the change of a leader, observing the change process of the leader node, and starting an http server. The method is implemented according to the following steps:
and 4.1, starting the first node in a Bootstrap mode. When other Raft nodes are started, the Raft cluster needs to be added, when the Raft nodes are started, the address of the first node is appointed, and a request is sent to be added into the Raft cluster, wherein the request is defined as a direct request through HTTP;
step 4.2, after receiving the request, the first started node acquires the address of the opposite side, wherein the pointed address is the tcp address of the interior communication of the Raft cluster;
and 4.3, the Raft nodes applying for adding the Raft cluster automatically enter a follower state, and then the nodes of the Raft cluster can normally communicate.
And 5, judging whether the node is a malicious node or not according to the extended interval range delta Term of the deadline value set in the step 3, and if the node is the malicious node, forcibly returning the identity state of the node to the follower state. The step 5 specifically comprises the following steps: according to the random growth interval range set in the step 2, the method is implemented according to the following steps:
step 5.1, if the tenure increment value a of a certain node in an election time is more than delta Term and less than b, judging that the node is not a malicious node, and turning to step 5.4;
step 5.2, if the tenure increment value delta Term of a certain node in an election time is more than b, judging that the node is possibly a malicious node, and turning to step 5.3;
step 5.3, the node is a malicious node, the identity state of the node is forcibly returned to a follower state from a candidate state or a leader state, and the tenure value of the malicious node is forcibly converted to be the same as the tenure values of other nodes;
and 5.4, according to the rule of the Raft consensus algorithm, electing the leader of the Raft cluster with the largest period value and the newest log, and copying the request to other nodes in a log mode.
And 6, storing the times of each node as a malicious node into a third-party block chain distributed account book, and if the times of a certain node as a malicious node are more, moving the node out of the Raft cluster. The step 6 specifically comprises the following steps: and (5) judging whether the node is a malicious node or not according to the step (5), if the node is the malicious node, linking the times num which is taken as the malicious node to a distributed account book of the third-party block chain in a transaction mode, and if the times num is more than 3, punishing to move the node out of the Raft cluster.
Example (b):
following the research method of the patent, a defense method against tenuous forgery based on a Raft consensus algorithm is described, as shown in fig. 1 and fig. 2. The experiment takes the Raft consensus algorithm process of three Raft nodes as an example, the malicious nodes are restored and attack the Raft cluster by using a fake tenure method, and therefore the purpose of obtaining the identity of the leader is achieved. The printed log content comprises id of the Raft node, address of the Raft node and identity state of the current node, and also comprises total vote tally, current optional value Term and currently selected leader node. In this experiment, there are three Raft nodes, where one malicious node interferes with the fairness of the election process of the Raft cluster, as shown in fig. 2, in the case of the same log content, a node with Raft _ id ═ 2 will increase its expiration value by 10000 within an election time (5000 ms in this experiment), and then this Raft node will send its expiration value Term to other nodes, since the expiration value of this Raft node is the largest in the Raft cluster, it has the right to initiate a new round of election, and the node entering the candidate identity at the same time with this Raft node will print the information of finding the newer expiration value because finding the expiration value of other nodes is larger than itself, return to the state of the follower, and vote to the node with Raft _ id ═ 2. In a Raft cluster with three Raft nodes, if the total number of votes is greater than half the total number of nodes plus one, i.e., tally ≧ votes/2 +1, the state transitions to the leader state. The method ensures that when the candidate identity and other nodes are used for election of the leader at the same time, more votes can be obtained certainly, and therefore the attack effect is achieved.
As shown in fig. 1, corresponding to step 3, step 4, and step 5, the Raft cluster is started first, and all Raft node states are follower states at this time; by launching a Raft cluster through Bootstrap and listening for changes in the leader, the process that the leader has become can be observed and the http server is launched. The first time in the Raft cluster is only one Raft node, and the first Raft node is started in a Bootstrap mode. When other Raft nodes are started, a Raft cluster needs to be added, and when the other Raft nodes are started, the address of the first Raft node is appointed, and in the experiment, the address of the first Raft node is as follows: raft _ addr 127.0.0.1: 7000. And sends a request to join the Raft cluster, defined here as a direct request over HTTP. After the started nodes receive the request, the addresses of the nodes of the opposite side are obtained, the nodes applying for joining enter a follower state, then normal communication can be carried out among the nodes of the Raft cluster, and normal processes of leader election and log replication are carried out.
And secondly, setting a normal and free period increasing interval in the election time, and judging whether the Raft node is a malicious node. In the voting channel in the runCandidate function, an arbitrary period growth interval range is set, the arbitrary period growth interval a < delta Term < b, and in the experiment, the obtained valid data a is 1, and b is 3. When the above-mentioned any-period forgery attack occurs, whether the Raft node is a malicious node is judged by judging whether the delta Term is in the set interval. In this experiment, the tenure increase value Δ Term of 2 nodes in an election time is 10000, and exceeds the set range of the normal tenure increase, it can be determined that the Raft node is a malicious node, the log of the Raft node will print the Raft node as a malicious node, the identity of the Raft node is returned to the identity state of a follower, and the tenure value Term is forcibly reset to 1.
And finally, counting the times of taking a certain node as a malicious node in the step 6, and uploading the node to a distributed book of a third party of the block chain. If the number of times that a certain node is found to be a malicious node exceeds three times, punishment is made, and the malicious node is forced to be moved out of the Raft cluster.
The invention discloses a defense method for resisting tenure forgery based on a Raft consensus algorithm, which solves the problem that a leader identity is obtained due to the fact that a malicious node intentionally increases a tenure value in the process of the Raft consensus algorithm in the technology, and ensures the election fairness in a Raft cluster of the algorithm. By setting the increment range of the random value, the fake random attack of a malicious node on the Raft cluster in the election process is effectively prevented, the fake random defense is achieved in the Raft consensus algorithm election process, and the election process and the result of the Raft consensus algorithm are fairer, safe and reliable.
Although embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that various changes, modifications, substitutions and alterations can be made in these embodiments without departing from the principles and spirit of the invention, the scope of which is defined in the appended claims and their equivalents.
Claims (7)
1. A defense method for resisting tenuous forgery based on a Raft consensus algorithm is characterized by comprising the following steps:
step 1, constructing a Raft cluster, and creating a Raft node to add into the constructed Raft cluster;
step 2, initializing the Raft cluster obtained in the step 1, and creating initial data;
step 3, setting an interval range a-b which is increased at any time within the election time;
step 4, starting the Raft cluster, wherein all the Raft nodes in the Raft cluster are follower states;
step 5, judging whether the node is a malicious node or not according to the step 4, and if the node is the malicious node, forcibly returning the state to the follower state;
and 6, storing the times of taking each Raft node as a malicious node into a third-party block chain distributed account book, and if the times of taking a certain Raft node as a malicious node are more than three times, moving the malicious node out of the Raft cluster.
2. The method as claimed in claim 1, wherein the step 1 is specifically: creating three Raft nodes so as to form a Raft cluster; in the interface provided by the Raft consensus algorithm, a NewRaft method is provided to newly build a Raft structure.
3. The method for defending against tenuous forgery based on the Raft consensus algorithm as claimed in claim 1, wherein the step 2 is specifically: creating a Raft cluster through the step 1, and initializing the Raft cluster; and calling an initialization function, and creating an expiration date and node information as initial data.
4. The method as claimed in claim 1, wherein the step 3 is specifically: and setting an interval range a-b of the random increase in the election time through the random increase interval of the normal election time of the test node under the non-malicious node.
5. The method for defending against tenuous forgery based on the Raft consensus algorithm as claimed in claim 1, wherein the step 4 is specifically: starting a Raft cluster, wherein all Raft node states in the Raft cluster are follower states, and the method is implemented according to the following steps:
step 4.1, starting a first Raft node in a Bootstrap mode, and adding the other Raft nodes into the Raft cluster when starting the other Raft nodes;
step 4.2, after the first-started Raft node receives the request, the address of the other side is obtained;
and 4.3, the Raft nodes applying for adding the Raft cluster automatically enter a follower state, and then the Raft nodes of the Raft cluster can normally communicate with each other.
6. The method for defending against tenuous forgery based on the Raft consensus algorithm as claimed in claim 1, wherein the step 5 is specifically: according to the random growth interval range set in the step 2, the method is implemented according to the following steps:
step 5.1, if the free period increment value delta Term of a certain Raft node in an election time is larger than a and smaller than delta Term and smaller than b, judging that the Raft node is not a malicious node, and turning to step 5.4;
step 5.2, if the increment value delta Term of a certain Raft node in the free period of an election time is larger than b, judging that the Raft node is possibly a malicious node, and turning to step 5.3;
step 5.3, the Raft node is a malicious node, the identity state of the malicious node is forcibly returned to a follower state from a candidate state or a leader state, and the tenure value of the malicious node is forcibly converted to be the same as the tenure values of other nodes;
and 5.4, according to the rule of the Raft consensus algorithm, electing the leader of the Raft cluster by the node with the largest expiration value and the newest log, and copying the request to other Raft nodes in a log mode.
7. The method for defending against tenuous forgery based on the Raft consensus algorithm as claimed in claim 1, wherein the step 6 is specifically: and (5) judging whether the Raft node is a malicious node or not according to the step (5), if the node is the malicious node, linking the number num of times of the malicious node to a third-party block chain distributed ledger in a transaction mode, and if the number num is more than 3, punishing to move the malicious node out of the Raft cluster.
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| CN116760837A (en) * | 2023-08-22 | 2023-09-15 | 苏州海加网络科技股份有限公司 | Distributed consensus method and system based on federal learning and equity election |
| CN116760837B (en) * | 2023-08-22 | 2023-11-24 | 苏州海加网络科技股份有限公司 | Distributed consensus method and system based on federal learning and equity election |
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