Reputation-based Distributed Blockchain BPFT Consensus Method and Internet Access Method for Intelligent Vehicle Networking

Abstract

The present invention relates to the field of blockchain technology, and discloses a reputation-based distributed blockchain BPFT consensus method and an access method for an intelligent vehicle networking system. A node is randomly selected from the consensus node set as the leader node. After the leader node receives a request from the client node, it broadcasts the message to all replica nodes in the consensus node set. When all replica nodes receive the message, they verify the message. If the verification passes, the consensus node broadcasts a prepare message to other consensus nodes; the prepare message is verified. If the verification passes, the node verifies the message and returns the result to the leader node. When the leader node receives more than 2f + 1 identical confirmation messages, it is considered that consensus is reached. The leader node provides the confirmation result to all nodes and simultaneously updates the reputation scores of all nodes. Finally, the consensus nodes and candidate nodes are adjusted according to the reputation values. Compared with the prior art, the present invention greatly improves the efficiency of consensus and consistency, and effectively prevents single-node attacks.

Description

Technical Field

[0001] The present invention relates to the technical field of blockchain, and particularly to a reputation-based distributed blockchain BPFT consensus method and an access method for an intelligent vehicle networking system. Background Art

[0002] Vehicle networking has become a new technology that supports autonomous driving and intelligent driving and improves traffic service and operation efficiency. It is a large-scale system network that realizes wireless communication and information exchange among vehicles, between vehicles and people, between vehicles and roads, and between vehicles and the Internet. Vehicle networking is usually applied to an open wireless network environment with rapidly changing topologies. Traditional vehicle networking is connected by a central server and is usually used in an open wireless network environment with rapidly changing topologies. Although this structure is simple and easy to control terminals, once the central server is attacked, the entire system may be paralyzed. In addition, as the network scale continues to expand, the burden on the central server is also increasing. This easily leads to an increase in network latency and even network crashes.

[0003] Communication between vehicles in vehicle networking is used to achieve information exchange and sharing among vehicles. This information includes vehicle status information, such as the position and speed of the vehicle, which can be used to determine the road traffic conditions. Therefore, identity authentication is an important process for vehicle communication. Since communication between vehicles is transmitted through wireless communication technology, malicious vehicles can easily attack vehicles and base stations within the wireless communication range. In addition, malicious vehicles may also send false information, such as sending a false signal indicating that the road is clear on a congested road ahead, resulting in a waste of travel time. If the base station is attacked, the attacker can tamper with, add, and delete some data in the base station. This situation may disclose some private information of users. Therefore, vehicle reliability detection is the key to ensuring the security of the vehicle networking system.

[0004] As an application of the Internet of Things (IoT) technology, the Internet of Vehicles (IoV) faces two main security problems: (1) The central server of the vehicle networking may not be powerful enough to support the centralized authentication of rapidly growing connected vehicles; (2) The vehicle networking itself may not be sufficient to resist single-node attacks. Summary of the Invention

[0005] Object of the Invention: Aiming at the problems existing in the prior art, the present invention provides a reputation-based distributed blockchain BPFT consensus method and an access method for an intelligent vehicle networking system, which greatly improves the efficiency of consensus and consistency and effectively prevents single-node attacks.

[0006] Technical Solution: The present invention provides a reputation-based distributed blockchain BPFT consensus method, including the following steps:

[0007] Step 1: Initialize all nodes. The reputation score of each node is 100, and they are divided into a consensus node set and a candidate node set. There are N nodes in the system. The maximum number of Byzantine nodes is allowed to be f. There are N / 2 candidate nodes, and the number of consensus nodes must satisfy CN≥3f + 1 to ensure that the system can reach a consensus in any case. CN is the number of consensus nodes. At initialization, the number of consensus nodes is set to N / 2;

[0008] Step 2: Randomly select one node from the consensus node set each time and name it the leader node. The client node sends a request message to the leader node;

[0009] Step 3: After the leader node receives the request from the client node, it enters the preprocessing stage. The leader node broadcasts the message to all replica nodes in the consensus node set. When all replica nodes receive the message, they verify the message. If the verification passes, they enter the preparation stage; if the verification fails, no operation will be performed;

[0010] Step 4: If a consensus node passes the preprocessed message, the consensus node enters the preparation stage and broadcasts a prepare message to other consensus nodes; when the consensus node sends a prepare message, it also receives the prepare messages broadcast by other consensus nodes and verifies them; if the verification passes, it enters the response stage;

[0011] Step 5: Response stage: The node verifies the message and returns the result to the leader node;

[0012] Step 6: When the leader node receives more than 2f + 1 identical confirmation messages, it is considered that a consensus has been reached. The leader node will provide the confirmation result to all nodes, including candidate nodes, and at the same time update the reputation scores of all nodes;

[0013] Step 7: The nodes in the candidate node set and the consensus node set are updated every 50 requests according to the number of requests sent by the client. The m nodes with the lowest reputation will be removed from the consensus node set and added to the end of the candidate list; the m nodes with the highest reputation in the candidate node set will be added to the consensus node set, and these nodes will be renumbered.

[0014] Further, in step 6, the leader node will provide the confirmation result to all nodes and update the reputation scores of all nodes specifically as follows:

[0015] 1) For the nodes whose confirmation results are consistent with the final consensus result, the reputation change of the nodes is as follows:

[0016]

[0017] Among them, R CN represents the reputation value of the consensus node, and represents the increased reputation, which is specifically as follows:

[0018]

[0019] Among them, is the overall consensus success rate, is the time elapsed since the last decrease of R CN , and α, β, π are parameters;

[0020] 2) If the confirmation result is inconsistent with the final consensus result, the node reputation changes as follows:

[0021]

[0022] Among them, represents the decreased reputation, which is specifically as follows:

[0023]

[0024] Among them, is the overall consensus failure rate, and ρ is a parameter.

[0025] Furthermore, when initializing the nodes in step 1, the order of all nodes is random. The consensus node set will execute the consensus process, and the candidate nodes will only update their local states when reaching a consensus and will not participate in the consensus process temporarily.

[0026] The present invention also discloses a management method for an intelligent vehicle networking, including the following steps:

[0027] S1: Vehicle initialization. The on-vehicle unit obtains system parameters through the network. The service provider SP selects a large prime number q and two q-order groups G and G T , the generator in G is G0, and the cyclic group satisfies the bilinear mapping e: G×G T →G T ; SP selects a random number P as the private key of the system and calculates its corresponding public key as P pub ; SP selects two hash functions and The public parameters Params of SP = {q, G, G T , G0, P pub , H1, H2};

[0028] S2: Vehicle registration. The vehicle encrypts all information and sends it to SP, and SP generates a virtual identity C i for protecting its identity privacy;

[0029] S3: Vehicle identity verification. The roadside unit RSU receives the vehicle registration message from the SP and verifies it. The RSU verifies through the above reputation-based distributed blockchain BPFT consensus method to determine whether consensus can be reached. If the RSU chooses to trust the vehicle, the vehicle will be granted a digital signature; otherwise, writing the vehicle information into the blockchain will be rejected.

[0030] Preferably, the specific steps in S2 are as follows:

[0031] 1) The SP selects a hash function to calculate C i as the virtual identity of the vehicle user;

[0032] 2) The SP calculates P i based on the virtual identity C pri as the private key of the vehicle user;

[0033] 3) The SP sends the vehicle virtual identity and the user private key to the user through a secure channel.

[0034] Beneficial effects:

[0035] A reputation-based consensus algorithm proposed by the present invention is more efficient, has less communication overhead, and higher throughput than the original PBFT algorithm. Therefore, this algorithm is more suitable for the vehicle networking system. And it is recommended to adopt the vehicle-service provider-roadside unit architecture to ensure the order and safety of vehicles. Moreover, an identity authentication scheme based on blockchain proposed by the present invention uses blockchain technology and cryptography to ensure the security of the system. The present invention analogizes the universality of trust in the real world because it is used in blockchain consensus. On the one hand, reputation improves the efficiency of the blockchain through the implementation of delegated consensus, and at the same time improves the authentication efficiency by introducing reputation scores when the RUS verifies the vehicle identity. On the other hand, the behavior of the vehicle in blockchain consensus will be reflected in its future reputation score. Description of the Drawings

[0036] Figure 1 is the vehicle network access flow chart of the present invention;

[0037] Figure 2 is the algorithm process of the present invention;

[0038] Figure 3 is the network model structure diagram of the present invention. Detailed Embodiments

[0039] The present invention will be further described below with reference to the drawings. The following embodiments are only used to more clearly illustrate the technical solution of the present invention and cannot be used to limit the protection scope of the present invention.

[0040] Refer to Figures 1 to 3, the present invention discloses a consensus method for distributed blockchain BPFT based on fame and an access method for intelligent vehicle networking. The access method for intelligent vehicle networking includes three main entities: vehicles, roadside units (RSUs), and service providers (SPs). The SP is mainly responsible for system parameter initialization and vehicle registration. The vehicle submits its information to the SP. At this time, the vehicle information is stored on the blockchain. Then the SP verifies its authenticity and completes the registration. The RSU fixed by the roadside uses blockchain technology to verify the identity of the vehicle. Finally, the RSU broadcasts the result to complete the verification of the vehicle.

[0041] The access method for intelligent vehicle networking includes the following steps:

[0042] S1: Vehicle initialization. The on-vehicle unit obtains system parameters through the network. The service provider SP selects a large prime number q and two q-order groups G and G T , the generator in G is G0, and the cyclic group satisfies the bilinear mapping e: G×G T →G T ; The SP selects a random number P as the private key of the system and calculates its corresponding public key as P pub ; The SP selects two hash functions and The public parameters Params of the SP = {q, G, G T , G0, P pub , H1, H2};

[0043] S2: Vehicle registration. The vehicle encrypts all its information and sends it to the SP. The SP generates a virtual identity C for it i to protect its identity privacy.

[0044] 1) The SP selects a hash function to calculate C i as the virtual identity of the vehicle user;

[0045] 2) The SP calculates P i according to the virtual identity C pri as the private key of the vehicle user;

[0046] 3) The SP sends the vehicle virtual identity and user private key to the user through a secure channel.

[0047] S3: Vehicle identity verification. The roadside unit RSU receives the vehicle registration message from the SP and verifies it. The RSU verifies through the following fame-based distributed blockchain BPFT consensus method to determine whether consensus can be reached; if the RSU chooses to trust the vehicle, the vehicle will be granted a digital signature; otherwise, the vehicle information will be rejected from being written into the blockchain.

[0048] The reputation-based distributed blockchain BPFT consensus method includes the following steps:

[0049] Step 1: Initialize all nodes, with the reputation score of each node being 100, and divide them into a consensus node set and a candidate node set; there are N nodes in the system, the maximum number of Byzantine nodes is allowed to be f, there are N / 2 candidate nodes, and the number of consensus nodes must satisfy CN≥3f + 1 to ensure that the system can reach a consensus in any case, where CN is the number of consensus nodes. At initialization, the number of consensus nodes is set to N / 2. When initializing the nodes, the order of all nodes is random. The consensus node set will execute the consensus process, and the candidate nodes will only update their local states when a consensus is reached and will not participate in the consensus process temporarily.

[0050] Step 2: Randomly select a node in the consensus node set each time and name it the leader node. The client node sends a request message to the leader node.

[0051] Step 3: After receiving the request from the client node, the leader node enters the preprocessing stage. The leader node broadcasts the message to all other replica nodes in the consensus node set. When all other replica nodes receive the message, they verify the message. If the verification passes, they will enter the preparation stage; if the verification fails, they will not perform any operation.

[0052] Step 4: If a consensus node passes the preprocessed message, the consensus node enters the preparation stage and broadcasts the preparation message to other consensus nodes; when the consensus node sends a preparation message, it will also receive the preparation messages broadcast by other consensus nodes and verify them; if the verification passes, it will enter the response stage.

[0053] Step 5: Response stage: The node verifies the message and returns the result to the leader node.

[0054] Step 6: When the leader node receives more than 2f + 1 identical confirmation messages, it is considered that a consensus has been reached. The leader node will provide the confirmation result to all nodes, including candidate nodes, and at the same time update the reputation scores of all nodes.

[0055] The leader node will provide the confirmation result to all nodes and at the same time update the reputation scores of all nodes specifically as follows:

[0056] 1) For the nodes whose confirmation results are consistent with the final consensus result, the reputation change of the node is as follows:

[0057]

[0058] Among them, R CNRepresents the reputation value of the consensus node, Indicates the increased reputation, which is as follows:

[0059]

[0060] Among them, Is the overall consensus success rate, Is R CN The time elapsed since the last decrease, α, β, π are parameters;

[0061] 2) If the confirmation result is inconsistent with the final consensus result, the node reputation changes as follows:

[0062]

[0063] Among them, Indicates the decreased reputation, which is as follows:

[0064]

[0065] Among them, Is the overall consensus failure rate, ρ is a parameter.

[0066] Step 7: The nodes in the candidate node set and the consensus node set are updated every 50 requests according to the number of requests sent by the client. The m nodes with the lowest reputation will be deleted from the consensus node set and added to the end of the candidate list; The m nodes with the highest reputation in the candidate node set will be added to the consensus node set and these nodes will be renumbered.

[0067] See Appendix Figure 2 , assuming that nodes 0, 1, 2, and 3 are consensus nodes, and nodes 4 and 5 are candidate nodes. Randomly select node 0 as the leader node. The client node C sends a request message to node 0. After receiving the request, node 0 broadcasts the message to nodes 1, 2, and 3. Assume that node 3 is a Byzantine node. When nodes 1, 2, and 3 receive the message, they verify the message and enter the preparation stage. Nodes 1 and 2 send preparation messages, and nodes 1 and 2 also receive the preparation messages sent by nodes 2 and 1 respectively. Nodes 1 and 2 enter the response stage, verify the message and send the result to node 0. Node 0 provides the confirmation result to all nodes (including candidate nodes).

[0068] The above embodiments are only for illustrating the technical concept and features of the present invention, and their purpose is to enable those who are familiar with this technology to understand the content of the present invention and implement it accordingly, and cannot be used to limit the protection scope of the present invention. Any equivalent transformation or modification made according to the spirit and essence of the present invention should be covered within the protection scope of the present invention.

Claims

1. A reputation-based distributed blockchain BPFT consensus method, characterized in that, It includes the following steps: Step 1: Initialize all nodes. The reputation score of each node is 100, and they are divided into a consensus node set and a candidate node set. There are N nodes in the system. The maximum number of Byzantine nodes allowed is f. There are N / 2 candidate nodes, and the number of consensus nodes must satisfy CN≥3f + 1 to ensure that the system can reach a consensus in any case. CN is the number of consensus nodes. At initialization, the number of consensus nodes is set to N / 2; Step 2: Randomly select one node from the consensus node set each time and name it the leader node. The client node sends a request message to the leader node; Step 3: After receiving the request from the client node, the leader node enters the preprocessing stage. The leader node broadcasts the message to all replica nodes in the consensus node set. When all replica nodes receive the message, they verify the message. If the verification passes, they enter the preparation stage; if the verification fails, no operation will be performed; Step 4: If a consensus node passes the preprocessed message, the consensus node enters the preparation stage and broadcasts a preparation message to other consensus nodes; when the consensus node sends a preparation message, it also receives the preparation messages broadcast by other consensus nodes and verifies them; If the verification passes, it enters the response stage; Step 5: Response stage: The node verifies the message and returns the result to the leader node; Step 6: When the leader node receives more than 2f + 1 identical confirmation messages, it is considered that a consensus has been reached. The leader node provides the confirmation result to all nodes, including candidate nodes, and simultaneously updates the reputation scores of all nodes; Step 7: The nodes in the candidate node set and the consensus node set are updated every 50 requests according to the number of requests sent by the client. The m nodes with the lowest reputation will be removed from the consensus node set and added to the end of the candidate list; The m nodes with the highest reputation in the candidate node set will be added to the consensus node set and these nodes are renumbered.

2. The reputation-based distributed blockchain BPFT consensus method according to claim 1, wherein In the above Step 6, the leader node provides the confirmation result to all nodes and simultaneously updates the reputation scores of all nodes specifically as follows: 1) For the nodes whose confirmation results are consistent with the final consensus result, the reputation change of the nodes is as follows: Among them, R CN represents the reputation value of the consensus node, represents the increased reputation, which is specifically as follows: Among them, is the overall consensus success rate, is R CN is the time elapsed since the previous decline, and α, β, and π are parameters; 2) If the confirmation result is inconsistent with the final consensus result, the reputation change of the nodes is as follows: Among them, represents the reduced prestige, which is as follows: Among them, is the overall consensus failure rate, and ρ is a parameter.

3. The reputation-based distributed blockchain BPFT consensus method according to claim 1, wherein When initializing the nodes in the above Step 1, the order of all nodes is random. The consensus node set will execute the consensus process. The candidate nodes only update their local states when a consensus is reached and do not participate in the consensus process temporarily.

4. An access method for an intelligent vehicle networking system, characterized in that, It includes the following steps: S1: Vehicle initialization. The on-vehicle unit obtains system parameters through the network. The service provider SP selects a large prime number q and two groups G and G of order q. T , the generator in G is G0, and the cyclic group satisfies the bilinear mapping e: G×G T →G T ; SP selects a random number P as the private key of the system and calculates its corresponding public key as P pub ; SP selects two hash functions and The public parameters Params of SP = {q, G, G T , G0, P pub , H1, H2}; S2: Vehicle registration. After encrypting all information, the vehicle sends it to the SP, and the SP generates a virtual identity C for it i to protect its identity privacy; S3: Vehicle authentication. The roadside unit RSU receives the vehicle registration message from the SP and verifies it. The RSU verifies it through the reputation-based distributed blockchain BPFT consensus method described in any one of Claims 1 to 3 to determine whether a consensus can be reached; If the RSU chooses to trust the vehicle, the vehicle will be granted a digital signature; otherwise, writing the vehicle information into the blockchain will be rejected.

5. The network access method of the intelligent vehicle networking according to claim 4, wherein The specific steps in the above S2 are: 1) The SP selects a hash function to calculate the virtual identity C of the vehicle user i ; 2) The SP calculates the private key P of the vehicle user according to the virtual identity C i ; pri ; 3) The SP sends the vehicle virtual identity and the user's private key to the user through a secure channel.

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