Blockchain-based Reputation Consensus Methods, Devices, and Media for Vehicle Networks

Abstract

This application provides a blockchain-based method, device, and medium for vehicle network reputation consensus. The method includes: obtaining vehicle reputation values ​​based on the objective behavior of vehicles in the vehicle network; roadside units collecting vehicle reputation values ​​and temporary reputation values ​​from the vehicle network, calculating a cumulative reputation value based on the vehicle reputation values ​​and temporary reputation values ​​of vehicles participating in message interaction in the current consensus round, and temporarily storing the cumulative reputation value in the roadside units until consensus is reached and block confirmation is performed, then returning the cumulative reputation value to the vehicle nodes; obtaining a list of roadside units and filtering it using a preset filtering mechanism to obtain a leader list; selecting the roadside unit with the largest cumulative reputation value as the leader based on the feedback cumulative reputation value, performing distributed consensus, and broadcasting the message. This application improves the credibility of vehicle network information, uses roadside units as consensus nodes to ensure fairness and efficiency, and reduces computer resources and consensus centralization.

Description

Technical Field

[0001] This document relates to the field of vehicle network reputation consensus technology, and in particular to a blockchain-based vehicle network reputation consensus method, device and medium. Background Technology

[0002] Vehicle-to-everything (V2X) technology, as a crucial component of intelligent transportation, handles vehicle information exchange and sharing, providing comprehensive information support for intelligent transportation. Blockchain, a distributed ledger based on cryptocurrency and tamper-proof technology, is widely used in IoT technologies, including cloud storage, healthcare management, and key exchange. Blockchain technology encompasses smart contracts, consensus mechanisms, and cryptography, effectively enhancing its functionality. However, existing blockchain-based V2X technologies, with their massive numbers of highly mobile and random nodes, suffer from the following problems:

[0003] 1) The authenticity of message transmission cannot be guaranteed, and malicious nodes cannot be effectively monitored;

[0004] 2) The consensus mechanism is inefficient and cannot guarantee the real-time performance of the Internet of Vehicles;

[0005] 3) Lack of consensus resources leads to a significant waste of computing resources in the Internet of Vehicles (IoV) and potential centralization issues.

[0006] Therefore, this invention provides a vehicle network reputation consensus scheme based on blockchain technology to solve the above-mentioned problems. Summary of the Invention

[0007] This invention provides a method, device, and medium for consensus on vehicle network reputation based on blockchain technology, to solve the above-mentioned problems.

[0008] This invention provides a vehicle network reputation consensus method based on blockchain technology, including:

[0009] S1. Obtain historical reputation, direct reputation, indirect reputation, and equipment reputation based on the objective behavior of vehicles in the vehicle network, and obtain vehicle reputation value based on the above four reputation factors;

[0010] S2. The roadside unit collects the vehicle reputation value of the vehicle network within a preset unit time, and obtains the temporary reputation value of the current consensus round. Based on the vehicle reputation value and temporary reputation value of the vehicles participating in the message interaction in the current consensus round, the cumulative reputation value is calculated and temporarily stored in the roadside unit. After the roadside units reach a consensus and perform block confirmation, the cumulative reputation value is returned to the vehicle node.

[0011] S3. Obtain the list of roadside units and filter them using a preset filtering mechanism to obtain the leader list;

[0012] S4. The leader list selects the roadside unit with the largest cumulative reputation value as the leader based on the feedback cumulative reputation value, performs distributed consensus, and broadcasts the message.

[0013] This invention provides an electronic device, comprising:

[0014] Processor; and,

[0015] A memory is configured to store computer-executable instructions, which, when executed, cause the processor to perform the steps of the blockchain-based vehicle network reputation consensus method described above.

[0016] This invention provides a storage medium for storing computer-executable instructions, which, when executed, implement the steps of the blockchain-based vehicle network reputation consensus method described above.

[0017] This invention provides reputation feedback based on the objective behavior of vehicle nodes, effectively ensuring the credibility of vehicle-to-everything (V2X) messages. It proposes a multi-factor, high-efficiency reputation consensus mechanism, using roadside units as consensus nodes and designing a lightweight consensus process to guarantee fairness and efficiency.

[0018] This invention effectively prevents malicious node attacks through a three-round consensus filtering mechanism, reducing computing resources and consensus centralization. Attached Figure Description

[0019] To more clearly illustrate the technical solutions in one or more embodiments of this specification or in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments recorded in this specification. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0020] Figure 1 This is a flowchart of a vehicle network reputation consensus method based on blockchain technology, according to an embodiment of the present invention.

[0021] Figure 2 This is a framework diagram of the vehicle network reputation consensus method based on blockchain technology according to an embodiment of the present invention;

[0022] Figure 3 This is a flowchart illustrating the distributed consensus process in an embodiment of the present invention. Detailed Implementation

[0023] To enable those skilled in the art to better understand the technical solutions in one or more embodiments of this specification, the technical solutions in one or more embodiments of this specification will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only a part of the embodiments of this specification, and not all of the embodiments. Based on one or more embodiments of this specification, all other embodiments obtained by those skilled in the art without creative effort should fall within the protection scope of this document.

[0024] Method Implementation Examples

[0025] According to embodiments of the present invention, a vehicle network reputation consensus method based on blockchain technology is provided. Figure 1 This is a flowchart of a vehicle network reputation consensus method based on blockchain technology, according to an embodiment of the present invention. Figure 2 This is a framework diagram of a vehicle network reputation consensus method based on blockchain technology according to an embodiment of the present invention. Figure 1 and Figure 2 As shown, the vehicle network reputation consensus method based on blockchain technology in this embodiment of the invention specifically includes:

[0026] S1. Obtain historical reputation, direct reputation, indirect reputation, and equipment reputation based on the objective behavior of vehicles in the vehicle network, and obtain vehicle reputation value based on the above four reputation factors;

[0027] In S1, vehicle behavior in the Internet of Vehicles (IoV) is converted into a reputation value. Four IoV factors are weighted and assigned to obtain the total reputation score for that time period. The model framework based on this is [see...]. Figure 1 The reputation of vehicle nodes is obtained according to the following calculation rule.

[0028] Re car =ηRe history +αRe direct +βRe indirect +γRe falicities ;

[0029] η+α+β+γ=1;

[0030] Re history Represents historical credibility, Re direct Represents direct reputation, Re indirect Indicates indirect reputation, Re falicities The device reputation is represented by η, α, β, and γ, which represent the weights of the four reputation values ​​and are used to control the proportion of vehicle node behavior.

[0031] Furthermore, historical reputation in S1 is obtained based on the time difference between entering and exiting roadside units;

[0032]

[0033] Among them, Re history Re represents historical reputation, Re represents the total reputation value of the current consensus round, and t represents historical reputation. enter The time t represents the time of entry into the roadside unit. exit This indicates the time it takes to leave the roadside unit, where "time" represents the rated time for vehicle-to-everything (V2X) connectivity.

[0034] Direct reputation is transformed through vehicle node message interactions, and it is closely related to four physical factors: latency factor, location factor, security factor, and interaction frequency factor, which are μ. time ,μ localtion ,μ safety ,μ frequency The direct credit calculation method is as follows:

[0035] Re direct =μ time ×μ localtion ×μ safety ×μ frequency ;

[0036] μ time =e -t ;

[0037]

[0038] other;

[0039] Based on the above, parameter t represents the time consumed by message propagation, parameter R represents the maximum range of the current roadside unit, parameter D represents the distance of the vehicle node from the roadside unit when the message is sent, and parameter S... car This is the vehicle's current safety factor score. The constant S is the rated vehicle safety score. Safety factor values ​​are only acquired when the rated safety score is exceeded. This is to prevent unsafe factors from occurring in the vehicle network. pre This represents the number of successful interactions at the current vehicle node, failure. pre This represents the number of times the vehicle node has failed to interact, and parameter n represents the total number of vehicles in the vehicle network during the current time period.

[0040] In the Internet of Vehicles (IoV), vehicle nodes primarily engage in message exchange, and their evaluation of these messages is equally crucial. For various message exchanges, the truthfulness or falsity of the messages is used to reward participating vehicles with a reputation value. This is similar to a voting process; participating nodes gain reputation feedback value if they make a positive choice, and deduct value if they make a negative choice. Below is the calculation method for indirect reputation, where p is the fixed message truthfulness / falsity ratio, and N... carThe number of vehicles involved in this judgment is num, which is the number of votes that were true in this event.

[0041]

[0042] For each information exchange performed on vehicle node i, other nodes will judge this message, and the group of vehicles participating in the indirect reputation value calculation will be denoted as [i]. and their reputation value groups Let parameter 'a' represent the number of true votes and parameter 'b' represent the number of false votes. Generally, a + b = N. car The reputation scores of Re1 and Re2, assuming the message is true or false, are shown in Table 1.

[0043] Table 1. Reputation scores for Re1 and Re2

[0044]

[0045] Secondly, for the interaction behavior of vehicle nodes with other devices in the vehicle network, such as parking behavior, road speed limits, driving conditions, etc., the device reputation is updated by recording round by round. The device reputation is updated using a binomial distribution of (0,1). The device reputation is calculated as follows:

[0046]

[0047] Among them, Re falicities Re represents the device reputation, g represents the number of times a vehicle node has performed well, m represents the number of times a vehicle has performed maliciously, and Re represents the reputation value of the vehicle in the current consensus round.

[0048] S2. The roadside unit collects the vehicle reputation value of the vehicle network within a preset unit time, and obtains the temporary reputation value of the current consensus round. Based on the vehicle reputation value and temporary reputation value of the vehicles participating in the message interaction in the current consensus round, the cumulative reputation value is calculated and temporarily stored in the roadside unit. After the roadside units reach a consensus and perform block confirmation, the cumulative reputation value is returned to the vehicle node.

[0049] The system collects the reputation values ​​of vehicle nodes within roadside units as temporary reputation values. Roadside units collect reputation values ​​among vehicles within each unit, temporarily storing the accumulated reputation values ​​of vehicles participating in message interactions within the roadside unit. These values ​​are not immediately returned to the vehicle users. Only after a consensus is reached among roadside units and block confirmation is performed will the relevant reputation values ​​be returned to the vehicle nodes. The calculation rule is as follows:

[0050]

[0051] Among them, Re RSURe represents the reputation value of a road test unit. car N represents the vehicle's credit rating. car This refers to the number of vehicles.

[0052] S3. Obtain the list of roadside units and filter them using a preset filtering mechanism to obtain the leader list;

[0053] S3 employs a three-stage filtering mechanism on the roadside unit list: random hash filtering, periodic filtering, and leader optimization. a) Random hash filtering sets the target value as the average reputation of the leader list divided by the hash of the public key, filtering out leaders that do not meet the target value. b) Periodic filtering ensures that each roadside unit can participate equally in the consensus process and become a leader. This means that roadside units that have recently become leaders will undergo a temporary periodic decay mechanism. This effectively prevents the centralization of the consensus mechanism, and since those with higher reputation values ​​are more likely to become leaders, a proportional reputation decay rule is adopted. c) Leader optimization prevents vehicles from maliciously accumulating reputation values ​​within roadside units, thus avoiding an imbalance in reputation scores. A normal distribution is used to select leaders within the expected and variance range. The specific algorithm is as follows:

[0054] Algorithm 1: Leader Election

[0055] Input:RSUs,RSUlist(),PKlist(),Round R;

[0056] Output:Optimized leader list RSUList();

[0057] noteStep 1

[0058] 1) for all RSUs do

[0059] 2) TargetHash → Hash(E(Re) RSUlist() )||Hash(PKlist()));

[0060] 3) end for

[0061] 4) for {i=0,i <N,i++}do

[0062] 5) if Hash(RSU) i ||PK i )>TargetHash then

[0063] 6) Add to RSUlist();

[0064] 7) end if

[0065] 8) end for

[0066] noteStep2

[0067] 9) for all RSUs do

[0068] 10) Get r value;

[0069] 11)Re RSU =(r / R) 2 ×Re RSU ;

[0070] 12)end for

[0071] noteStep3

[0072] 13) Calculate E(Re) RSU );

[0073] 14) Calculate D(Re) RSU );

[0074] 15) for all RSUs do

[0075] 16)RSUlist()∈[E(Re RSU )-R×D(Re RSU ),

[0076] E(Re RSU )+R×D(Re RSU )];

[0077] 17) end for

[0078] 18) return RSUlist();

[0079] S4. The leader list selects the roadside unit with the largest cumulative reputation value as the leader based on the feedback cumulative reputation value, performs distributed consensus, and broadcasts the message.

[0080] S4 performs distributed consensus and broadcasts it to every roadside unit. See the detailed flowchart below. Figure 3 An optimized leader list elects the roadside unit with the highest reputation value as the leader, conducts distributed consensus, and broadcasts the message. Other nodes can verify the leader's credentials, and the reputation value is only reflected after the blockchain system confirms the generation of a confirmation block for half a cycle. Due to the large number of nodes and randomness in the vehicle network, the network complexity will gradually increase. Therefore, considering consensus boundary groups is one of the research areas to be explored in the future.

[0081] By employing the embodiments of the present invention, the following beneficial effects are achieved:

[0082] This invention provides reputation feedback based on the objective behavior of vehicle nodes, effectively ensuring the credibility of vehicle network messages.

[0083] This invention proposes a multi-factor, high-efficiency reputation consensus mechanism, using RSUs as consensus nodes and designing a lightweight consensus process to ensure fairness and efficiency.

[0084] This invention effectively prevents malicious node attacks through a three-round consensus filtering mechanism, reducing computing resources and consensus centralization.

[0085] Device Example 1

[0086] According to an embodiment of the present invention, an electronic device is provided, comprising:

[0087] Processor; and,

[0088] A memory is configured to store computer-executable instructions, which, when executed, cause the processor to perform the steps of the method embodiments described above.

[0089] Device Example 2

[0090] According to an embodiment of the present invention, a storage medium is provided for storing computer-executable instructions, which, when executed, implement the steps of the method embodiments described above.

[0091] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, and not to limit them; although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some or all of the technical features; and these modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of the embodiments of the present invention.

Claims

1. A blockchain-based consensus method for vehicle-to-everything (V2X) reputation, characterized in that: include: S1. Obtain historical reputation, direct reputation, indirect reputation, and device reputation based on the objective behavior of vehicles in the Internet of Vehicles (IoV), and obtain vehicle reputation value based on the above four reputation factors; the historical reputation is obtained through the time difference of entering and exiting the roadside unit, the direct reputation is obtained through conversion by vehicle node message interaction, the indirect reputation is obtained through true / false feedback, and the device reputation is obtained through the interaction behavior of vehicle nodes with other devices in the IoV. S2. The roadside unit collects the vehicle reputation value within a preset unit time in the vehicle network, and obtains the temporary reputation value of the current consensus round. Based on the vehicle reputation value and temporary reputation value of the vehicles participating in the message interaction in the current consensus round, the cumulative reputation value is calculated and temporarily stored in the roadside unit. After the roadside units reach a consensus and perform block confirmation, the cumulative reputation value is returned to the vehicle node. S3. Obtain the list of roadside units and filter them using a preset filtering mechanism to obtain the leader list; S4. The leader list selects the roadside unit with the largest cumulative reputation value as the leader based on the feedback cumulative reputation value, performs distributed consensus, and broadcasts the message; The filtering using a preset filtering mechanism specifically includes: The roadside unit list is filtered three times, including random hash filtering, periodic filtering, and leader optimization. The random hash filtering specifically includes: setting the target value to the average reputation of the leader list and the hash of the public key, and filtering out some leaders that do not meet the target value; The periodic filtering involves randomly applying a periodic decay mechanism to the roadside unit that has recently become the leader. The optimization of the leader specifically includes: selecting leaders within the expected and variance ranges using a normal distribution.

2. The method according to claim 1, characterized in that, The historical reputation is obtained using Formula 1 based on the time difference between entering and exiting roadside units: Formula 1: in, Indicating historical credibility, This represents the total reputation value of the current consensus round. Indicates the time of entry into the roadside unit. Indicates the time of departure from the roadside unit. This indicates the rated time for vehicle-to-everything (V2X) connectivity.

3. The method according to claim 1, characterized in that, The direct reputation is converted through vehicle node message interaction, and the specific calculation method includes: Formula 2: in , , , These represent the delay factor, location factor, security factor, and interaction frequency factor, respectively.

4. The method according to claim 1, characterized in that, The indirect reputation is obtained through true / false feedback. If a participating node makes a positive choice, it receives a reputation feedback value; otherwise, it is deducted. Specifically, it is obtained through Formula 3: Formula 3: in, For indirect reputation, The ratio of true to false messages is the fixed value. The number of vehicles involved in this assessment. It refers to the number of votes that were actually counted in the incident. This indicates that the vote is true. This indicates that the vote was sham.

5. The method according to claim 1, characterized in that, The device reputation is obtained through the interaction behavior of the vehicle node with other devices in the vehicle network, specifically through Formula 4: Formula 4: in, Indicates the equipment's reputation. This indicates the number of times a vehicle node has a good record. This indicates the number of times a vehicle has been maliciously recorded. This represents the current consensus on the credibility of wheeled vehicles.

6. The method according to claim 1, characterized in that, The specific methods for obtaining the four reputation factors include: Formula 5: in, Indicating historical credibility, Indicates direct credit, Indicating indirect credibility, Indicates the equipment's reputation. These represent the weights of the four reputation values, used to control the proportion of vehicle node behavior, and Satisfy the following formula: Formula 6.

7. The method according to claim 1, characterized in that, The calculation of the cumulative reputation value based on the vehicle reputation value and temporary reputation value of the vehicles participating in the message interaction in the current consensus round specifically includes: Obtain the cumulative reputation score using Formula 7: Formula 7: in, Indicates the reputation value of the road test unit. Indicates the vehicle's credit score. This refers to the number of vehicles.

8. An electronic device, comprising: processor; as well as, A memory configured to store computer-executable instructions, which, when executed, cause the processor to perform the steps of the blockchain-based vehicle network reputation consensus method as described in any one of claims 1-7.

9. A storage medium for storing computer-executable instructions, which, when executed, implement the steps of the blockchain-based vehicle network reputation consensus method as described in any one of claims 1-7.

Images