A Secure and Trusted Message Sharing Method for Vehicle Networks Based on Blockchain and Trust Management

Abstract

This invention belongs to the field of blockchain and vehicle-to-everything (V2X) security management technology, and relates to a secure and trusted message sharing method for V2X based on blockchain and trust management. The method includes: a message-providing vehicle recording and broadcasting the message; a message-receiving vehicle receiving the message, scoring the authenticity of the message, and broadcasting it to a consensus vehicle; and the consensus vehicle assigning an authentic score s to each message. 1,i Usefulness scoring is performed. When the number of high-usefulness scores exceeds a threshold Q, the data (m, s) is... 1,i ,s 2,i,c ,t) Uploaded to the accounting node, s 2,i,c For consensus vehicle c to s 1,i High usefulness score; ledger nodes receive and verify data (m, s) 1,i ,s 2,i,c The verified data is packaged into blocks and stored in the blockchain; the RSU calculates the trust value of vehicles in the area and shares it in the RSU cluster; the RSU cluster makes trust decisions for vehicles based on the trust value of the vehicles; this invention improves the credibility of shared messages in the Internet of Vehicles by scoring the authenticity and usefulness of messages, and combines blockchain technology to ensure the authenticity and integrity of messages.

Description

Technical Field

[0001] This invention belongs to the field of blockchain and vehicle-to-everything (V2X) security management technology, specifically relating to a reliable message sharing method for V2X security based on blockchain and trust management. Background Technology

[0002] With the continuous development of communication technology, artificial intelligence, big data, and other fields, the Internet of Vehicles (IoV) has emerged, becoming an important platform for communication, interaction, and collaboration among intelligent vehicles. IoV devices connect via base stations, enabling more efficient vehicle-to-vehicle (V2V) communication. This not only helps vehicles obtain real-time traffic information but also enhances their environmental perception and computational decision-making capabilities. However, the distributed network architecture, high dynamism, and high openness of IoV present significant challenges to message sharing and security among vehicles.

[0003] Current research primarily focuses on establishing secure communication channels and preventing external attacks to ensure communication reliability. However, within the Internet of Vehicles (IoV), frequent interactions and collaborations between vehicles, mostly between unfamiliar vehicles, raise questions about the authenticity and reliability of message sharing. Furthermore, misleading messages spread by malicious vehicles may cause receiving vehicles to make incorrect decisions, disrupting normal driving and even leading to accidents, threatening personal safety.

[0004] Therefore, in V2V scenarios, improving the authenticity, reliability, and security of message sharing between vehicles has become an urgent problem to be solved. Summary of the Invention

[0005] To address the aforementioned technical problems, this invention employs a secure and reliable message sharing method for the Internet of Vehicles (IoV) based on blockchain and trust management. The method includes an IoV message sharing network comprising: a vehicle message broadcasting layer, a vehicle consensus layer, an accounting layer, and a trust decision layer. The vehicle message broadcasting layer includes ordinary vehicles, which in turn include message-providing vehicles and message-receiving vehicles. The consensus layer includes consensus vehicles. The accounting layer includes accounting nodes. The trust decision layer includes an RSU cluster composed of Roadside Units (RSUs).

[0006] The secure and trusted message sharing methods for connected vehicles include:

[0007] S1. The message providing vehicle records and broadcasts message m during its journey. The message receiving vehicle i receives message m, scores the authenticity of message m, and assigns the authenticity score s. 1,i The broadcast was given to the vehicles that reached a consensus;

[0008] S2, consensus vehicle received message m and authenticity score s 1,iAnd assign each authenticity score 1,i Perform a usefulness rating, when all authenticity ratings are s 1,i When the number of high-usefulness ratings exceeds the threshold Q, the authenticity rating s 1,i The consensus vehicle c, which receives a high usefulness score, will use the data (m, s) 1,i ,s 2,i,c ,t) is uploaded to the ledger node; where m is the message, s 2,i,c For consensus vehicle c, the authenticity score s 1,i The high usefulness rating, where t is the current timestamp;

[0009] S3. The accounting node receives and verifies the data uploaded by the consensus vehicle. If the verification is successful, the data uploaded by the consensus vehicle is packaged into a block and stored in the blockchain; otherwise, the data uploaded by the consensus vehicle is discarded.

[0010] S4. RSU calculates the trust value of vehicles within the area and shares the vehicle trust value with the RSU cluster; the RSU cluster makes trust decisions for vehicles based on the vehicle trust value.

[0011] S5. Ordinary vehicles or consensus vehicles that need to request a message send a message request to the blockchain and receive the required message.

[0012] The authenticity scoring of message m includes: the message receiving vehicle calculating the distance between itself and the location where message m occurred and predicting the path it will take. If the distance between the message receiving vehicle and the location where message m occurred is greater than a distance threshold, or if the location where message m occurred is on the path that the message receiving vehicle predicts it will take, then the authenticity score of message m is performed; otherwise, no authenticity score is performed.

[0013] The consensus vehicle performs a usefulness score on the authenticity score by predicting the path it will take. If the message corresponding to the authenticity score is located on the path the consensus vehicle will take, then the authenticity score is evaluated for usefulness; otherwise, no usefulness score is evaluated.

[0014] In step S2, the threshold Q is When all authenticity scores s 1,i The number of high-usefulness scores H satisfies At that time, all truthfulness scores s for message m 1,i Re-evaluate the usefulness score; when all truth scores are... 1,i The number of high-usefulness scores H satisfies When the message m is invalid, it is discarded; where V is the number of consensus vehicles and L is the number of authenticity scores for message m.

[0015] The ledger layer also includes a reward and punishment mechanism, which includes a trust threshold. Ledger nodes use the reward and punishment mechanism to adjust the trust value of consensus vehicles and automatically replace consensus vehicles with trust values ​​less than the trust threshold with the vehicles with the highest trust values ​​among ordinary vehicles.

[0016] The ledger nodes adjust the trust value of the consensus vehicle using reward and punishment mechanisms, including in step S2, when all authenticity scores s 1,i When the number of high usefulness scores exceeds the threshold Q, the accounting node increases the trust value of consensus vehicles with high usefulness scores and decreases the trust value of consensus vehicles with low usefulness scores through smart contracts.

[0017] The trust value of a vehicle within the RSU calculation area includes: trust evidence of the vehicle within the RSU calculation area, and the trust value of the vehicle is calculated based on the trust evidence; the calculation of the trust value of the vehicle based on the trust evidence includes:

[0018]

[0019] Among them, T j (k) represents the trust value of vehicle j at time k. For cooperation level C j The weights of (k), For familiarity F oj The weights of (k), The weights for the authenticity score s1(k) The weights of the usefulness score s2(k) C j (k) represents the cooperation degree of vehicle j at time k, F oj (k) represents the familiarity of vehicle j at time k, s1(k) represents the authenticity rating of the received message by vehicle j at time k, s2(k) represents the usefulness rating of the received authenticity rating by vehicle j at time k, and o represents the evaluation vehicle of vehicle j, which can be any vehicle in the vehicle-to-everything (V2X) message sharing network.

[0020] The RSU cluster includes a weighted adjustment mechanism; sharing the vehicle's trust value with the RSU cluster includes: when a vehicle moves from one RSU area to another new RSU area in the RSU cluster, the new RSU inherits the vehicle's trust value and uses the weighted adjustment mechanism to adjust the vehicle's trust value to obtain the adjusted trust value.

[0021] The weighted adjustment mechanism for vehicle trust values ​​includes:

[0022] ω=α×ω net +β×ω v +γ×ω trust

[0023]

[0024] Where ω represents the weighting factor, α, β, and γ are the weight coefficients of different factors, and α + β + γ = 1, ω net ω v ω trust These are the status factors of the vehicle-to-everything (V2X) message sharing network, the dynamic factors of vehicle behavior, and the stability factors of vehicle trust values. T represents the vehicle's adjusted trust value. historical This indicates the trust value of the vehicle before adjustments.

[0025] The RSU cluster makes trust decisions about vehicles based on their trust values, including: allowing vehicles with high trust values ​​to communicate normally in the vehicle-to-everything (V2X) messaging network; restricting vehicles with low trust values ​​from communicating in the V2X messaging network and monitoring vehicles with low trust values.

[0026] Beneficial effects:

[0027] 1. This invention uses a multi-layered trust management mechanism to score the authenticity and usefulness of messages, and combines blockchain technology to improve the credibility of shared messages in the Internet of Vehicles (IoV), ensuring the authenticity and integrity of messages. 2. This invention incentivizes the provision of high-quality messages and penalizes the spread of low-quality messages through trust value calculation and a trust value reward and penalty mechanism, optimizing the utilization efficiency of system resources. 3. This invention uses blockchain to store valid messages and scores, preventing data tampering and unauthorized access, while improving the efficiency of cross-regional message interaction, shortening message response time, and enhancing the collaborative working capability of the IoV system. 4. This invention improves the efficiency of cross-regional vehicle trust assessment by sharing the trust values ​​of vehicles in each RSU region through RSU clusters, and uses a weighted adjustment mechanism to adjust the trust values ​​of cross-regional vehicles, enabling RSUs to more reasonably assess the trust status of cross-regional vehicles and avoiding misjudgments that may be caused by the transmission of a single trust value. Attached Figure Description

[0028] Figure 1 This is a flowchart illustrating the secure and trusted message sharing method for vehicle networking based on blockchain and trust management according to the present invention.

[0029] Figure 2 This is a schematic diagram illustrating a scenario of the secure and trusted message sharing method for vehicle networking based on blockchain and trust management according to the present invention. Detailed Implementation

[0030] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0031] like Figure 1 , Figure 2 As shown, this invention employs a secure and trusted message sharing method for the Internet of Vehicles (IoV) based on blockchain and trust management, comprising: an IoV message sharing network, which includes: a vehicle message broadcasting layer, a vehicle consensus layer, an accounting layer, and a trust decision layer; the vehicle message broadcasting layer includes ordinary vehicles, which include message providing vehicles (MPVs) and message receiving vehicles (MRVs); the consensus layer includes consensus vehicles (CVs); the accounting layer includes accounting nodes; and the trust decision layer includes an RSU cluster composed of RSUs.

[0032] The secure and trusted message sharing methods for connected vehicles include:

[0033] S1. The message providing vehicle records and broadcasts valuable event messages m encountered on the road during its journey. The message receiving vehicle receives message m, scores the authenticity of the broadcast message m based on its own observations, and broadcasts the authenticity score to the consensus vehicle.

[0034] The message delivery vehicle (MPV) actively selects and broadcasts messages, which can cover various categories such as traffic conditions, road information, infrastructure information, services and facilities, and emergencies. Specific message categories are shown in Table 1. The MPV's broadcasting behavior enables the timely delivery of important information to surrounding vehicles, improving the efficiency of information sharing.

[0035] Table 1 Message Classification

[0036]

[0037]

[0038] The authenticity score for the Message Receiving Vehicle (MRV) is rated on a scale of 1 to 5, where 1-2 indicates the message is unreliable and false; 3 indicates the message's authenticity needs further verification; and 4-5 indicates the message is authentic and reliable. The scoring assumes the message originated near the MRV or is on its upcoming path, allowing the MRV to assess authenticity based on actual observation. The MRV broadcasts these scores to the consensus vehicle nodes, providing foundational data for subsequent trust assessments.

[0039] MRV (Morse Vehicle Detection and Reliability) accuracy scoring primarily addresses the "accuracy" of a message, i.e., whether the message matches the actual situation. Because the MRV is located near the area where the message occurred, it can provide the most direct observations based on the current environment, road conditions, or events, thereby assessing the message's accuracy. In other words, accuracy scoring relies on the MRV's direct observation of the current environment to ensure the message matches reality.

[0040] Methods for determining if a message originates near an MRV: In vehicle-to-everything (V2X) systems, vehicles are typically equipped with GPS or other positioning systems. When an MPV broadcasts a message, it includes the latitude and longitude information of the originating location. The MRV can calculate the distance to the originating location based on its own GPS location. If the distance is within the default matrix threshold range (e.g., within 300 meters), the message is considered to originate near the MRV.

[0041] The method for determining if a message originates on the MRV's upcoming path: The MRV can predict its likely future path based on its current speed and direction, combined with the navigation system's route. If the message originates on the MRV's predicted path, the MRV can consider the message relevant to its journey and conduct further authenticity assessment.

[0042] S2, consensus vehicle received message m and authenticity score s 1,i And assign each authenticity score 1,i Perform a usefulness rating, when all authenticity ratings are s 1,i When the number of high-usefulness ratings exceeds the threshold Q, the authenticity rating s 1,i The consensus vehicle c, which receives a high usefulness score, will use the data (m, s) 1,i ,s 2,i,c ,t) is uploaded to the ledger node; where m is the message, s 2,i,c For consensus vehicle c, the authenticity score s 1,i The high usefulness score, where t is the current timestamp; preferably, the threshold Q is... V represents the number of consensus vehicles, and L represents the number of authenticity scores for message m.

[0043] The main tasks of consensus vehicle CV are as follows:

[0044] Message reception: CV is responsible for receiving event messages sent from MPV and authenticity scores sent from MRV.

[0045] Usefulness Scoring: The CV assigns a usefulness score to the authenticity scores sent by the MRV to ensure the authenticity of the message transmission and reduce the possibility of message tampering during transmission. If an authenticity score can effectively help other vehicles, the CV will give it a high usefulness score (4-5 points); if an authenticity score is inconsistent with the actual situation and has a negative impact on other vehicles, the CV will give it a low usefulness score (1-3 points). To ensure the relevance of the usefulness scores, the CV only evaluates the authenticity scores of messages occurring on its upcoming route.

[0046] The CV's usefulness score focuses on the "usefulness" of the message, that is, whether the message can effectively assist vehicles about to enter the area. The CV is not always located at the site of the message's occurrence, but rather assesses its future value based on the message's content and the driving route. This stage of evaluation ensures the message's practicality and importance for vehicle decision-making and prevents the message from interfering with other vehicles. In other words, the usefulness score aims to assess whether the message is helpful to vehicles on their future driving routes; therefore, the CV evaluates messages along its upcoming route to ensure the message's practicality.

[0047] In one embodiment, the usefulness scoring method includes: the CV can combine the authenticity scores of all MRVs to make a summation judgment: if all other MRVs report congestion on a certain road segment, but a certain MRV gives an inconsistent authenticity score, the CV will consider the score to be inaccurate and thus give it a low usefulness score.

[0048] In one embodiment, the usefulness scoring method includes: the CV determining whether the MRV is within the area where the message occurred based on the latitude and longitude of the message and the location of the MRV; the CV matching the time of the message occurrence with the time when the MRV sends the authenticity score to determine whether the message and its authenticity score were received within a reasonable time range; if the MRV is not within the area where the message occurred, or if the consensus vehicle CV does not receive the message and its authenticity score within a reasonable time range, the CV can consider that the authenticity score of the MRV is inconsistent with the actual situation, and thus give a low usefulness score; otherwise, a high usefulness score is given.

[0049] Consensus reached: When all authenticity ratings s 1,i The number of high-usefulness ratings is greater than the threshold. If the message is valid, its authenticity is rated as s. 1,i The consensus vehicle c, which receives a high usefulness score, will use the data (m, s) 1,i ,s2,i,c If the consensus vehicles fail to reach a consensus on the message, the message will not be considered valid, and subsequent processing will include the following points:

[0050] When all authenticity scores s 1,i The number of high-usefulness scores H satisfies At that time, all truthfulness scores s for message m 1,i Reassess the usefulness score.

[0051] The same message will be evaluated only 3 times. If the high usefulness score is still in the range of 1 / 2 to 2 / 3 in the third evaluation, the message will no longer be evaluated, will be considered invalid, and will be discarded.

[0052] When all authenticity scores s 1,i The number of high-usefulness scores H satisfies If the message is invalid, it will be discarded.

[0053] For messages deemed invalid, consensus vehicles will broadcast a notification that the message is invalid. When other vehicles receive this notification, they will also discard the message, thus further preventing the spread of unreliable messages.

[0054] S3. The accounting node receives and verifies the data uploaded by the consensus vehicle. If the verification is successful, the data uploaded by the consensus vehicle is packaged into a block and stored in the blockchain; otherwise, the data uploaded by the consensus vehicle is discarded.

[0055] At the ledger layer, the ledger nodes are handled by RSUs, which are responsible for selecting consensus vehicles, replacing consensus vehicles, verifying and packaging data, and implementing reward and punishment mechanisms.

[0056] Selecting consensus vehicles: Ledger nodes select vehicles with high reliability, abundant resources, and slow state changes as consensus vehicles through trust value evaluation.

[0057] The specific selection process is as follows:

[0058] First, in the early stages of the network, before any attacks have occurred, all vehicle nodes are in a trusted state. Therefore, the ledger node selects consensus vehicles based on the vehicle's operating status (computing resources, network connection stability, travel route, frequency of vehicle status changes, etc.).

[0059] Secondly, during network operation, the accounting nodes calculate the trust value of vehicles based on their behavior (see step S4 for details) and determine their driving status based on the collected vehicle status information.

[0060] Consensus Vehicle Replacement: When a consensus vehicle's trust value falls below the trust threshold, the accounting node automatically cancels its consensus qualification, downgrades it to a regular vehicle, and replaces it with the regular vehicle that has the highest trust value. The trust value ranges from 0 to 1, where 0 represents malicious intent and 1 represents trustworthiness. Because the trust value of consensus vehicles needs to be maintained at a high level, the trust threshold is set to 0.6. When a consensus vehicle's trust value falls below 0.6, it will be replaced.

[0061] Verify and package data: Ledger nodes receive and verify messages and scores submitted by consensus vehicles; verified data is packaged into blocks and uploaded to the blockchain, thereby ensuring data integrity and traceability.

[0062] The specific verification process is as follows:

[0063] Step 1, Format Validation: The accounting node checks whether the uploaded data conforms to the predetermined format specifications (such as data type, field integrity, etc.) to ensure that the data has not been tampered with during transmission.

[0064] Step 2, Timestamp Verification: Confirm the timestamp of the uploaded data to ensure that the data is submitted within a reasonable timeframe and to avoid the impact of outdated information. A reasonable timeframe is when the difference between the message upload timestamp and the current time should be between 5 and 30 seconds to ensure the timeliness of the information.

[0065] Step 3, Consensus Vehicle Rating Consistency Check: Check if more than 2 / 3 of the received data are uploaded by consensus vehicles. If so, determine if the uploaded usefulness scores are similar. If so, the data can be considered reliable and the check passes.

[0066] When verification is successful, the average of the authenticity score and the average of the usefulness score of the uploaded content are calculated. The message, the average of the authenticity score, the average of the usefulness score, and the current timestamp are then stored as a record in the blockchain.

[0067] Implementation of reward and penalty mechanisms: To ensure the fairness and transparency of the system, the ledger nodes implement reward and penalty measures through smart contracts. When all authenticity scores are... 1,i When the number of high usefulness scores exceeds the threshold Q, the accounting node increases the trust value of consensus vehicles with high usefulness scores and decreases the trust value of consensus vehicles with low usefulness scores through smart contracts.

[0068] S4. In the trust decision layer, RSU calculates the trust value of vehicles within the region and shares the vehicle trust value with the RSU cluster to achieve cross-regional vehicle trust assessment. Finally, the RSU cluster makes trust decisions for vehicles based on the trust value. Vehicles within the RSU region include ordinary vehicles and consensus vehicles.

[0069] Specifically, it is implemented in four steps: vehicle trust evidence calculation, vehicle trust value calculation within the region, RSU cluster sharing of trust information, and trust decision-making.

[0070] Step 1: Collect vehicle data and calculate relevant trust evidence. There are four types of trust evidence: the degree of cooperation and familiarity between vehicle nodes, and the vehicle's rating of the message's authenticity and usefulness. These four types of trust evidence are explained below.

[0071] Cooperation level: This measures the frequency and intensity of interactions between the evaluated vehicle and other vehicles in the network. Specifically, cooperation level reflects the degree to which the evaluated vehicle cooperates with other vehicles in the network over a period of time, i.e., assessing the cooperative activity of a vehicle throughout the network. The formula is shown below.

[0072]

[0073] Among them, C j (k) represents the degree of cooperation of vehicle j being evaluated at time k; N j (k) represents the set of neighboring vehicles that interact with the evaluated vehicle j at time k, and N represents the total number of vehicles in the network.

[0074] Familiarity: Any vehicle is selected as the evaluation vehicle. The evaluation vehicle refers to the vehicle responsible for performing trust assessments on other vehicles (the vehicles being evaluated) in the vehicle-to-everything (V2X) network. It can be any vehicle in the network with evaluation capabilities. It measures the proportion of common neighbors between the evaluation vehicle and the vehicle being evaluated. Specifically, familiarity reflects the strength of the relationship and the frequency of common contact between the evaluation vehicle and the vehicle being evaluated; that is, it assesses the level of familiarity and trust between the two specific vehicles. High familiarity indicates that the two vehicles have more common neighbors and may know and trust each other more. The formula is shown below.

[0075]

[0076] Among them, F oj (k) represents the familiarity between the evaluating vehicle o and the evaluated vehicle j at time k, N o (k) represents the set of neighboring vehicles of vehicle o at time k. The neighboring vehicles of vehicle o typically refer to other vehicles in the vehicle network that are close to the vehicle being evaluated and can communicate directly with it. N j (k) represents the set of neighboring vehicles of vehicle j being evaluated at time k; N o (k)∩N j (k) represents the set of common neighbors of the evaluating car o and the evaluated car j at time k.

[0077] Authenticity score: This refers to the authenticity score given to received messages by MRV, as shown in the formula below.

[0078]

[0079] The purpose of authenticity scoring is to quickly filter out fake news and increase the initial credibility of the information.

[0080] Usefulness score: refers to the usefulness score given by consensus vehicles to the authenticity score issued by MRV.

[0081]

[0082] The purpose of usefulness scoring is to ensure the authenticity and reliability of messages during the dissemination process through secondary verification.

[0083] Based on the above evidence of trust, the trust score for each vehicle is calculated using the following formula:

[0084]

[0085] Among them, T j (k) represents the trust value of vehicle j at time k. For cooperation level C j The weights of (k), For familiarity F oj The weights of (k), The weights for the authenticity score s1(k) The weights of the usefulness score s2(k)

[0086] To address the issue of trust value update delays caused by the dynamic movement of vehicles across different areas—specifically, the Reliable State Unit (RSU) in a new area needs to re-collect evidence and calculate the vehicle's trust value, potentially posing a cybersecurity risk—this invention employs a method of sharing vehicle trust information within the RSU cluster. When a vehicle moves to a new RSU coverage area, the new RSU can immediately access the vehicle's trust data in other areas, avoiding the need to re-evaluate trust from scratch, effectively shortening the response time for trust classification, and improving the system's real-time performance and reliability. However, considering the significant differences in network environment, vehicle behavior patterns, and malicious node distribution across different RSU areas, simply transferring trust values ​​when a vehicle crosses areas may lead to biased evaluation results. Therefore, a weighted adjustment mechanism can be adopted. When a vehicle enters a new RSU area, the new RSU not only inherits the trust value but also performs appropriate weighted adjustments. The weighting factor of the weighted adjustment mechanism is calculated by the new RSU based on factors such as the current network conditions, vehicle behavior, and the stability of the trust value. Through this mechanism, the RSU can more reasonably assess the trust status of vehicles crossing domains, avoiding misjudgments that may result from the transfer of a single trust value.

[0087] Specifically, the process of using a weighted adjustment mechanism to adjust the vehicle's trust value is as follows:

[0088] Network Condition Assessment: The new RSU assesses the current network condition, including network latency, bandwidth, signal strength, etc. For example, in poor network conditions, the trust value may be weighted lower because an unstable network may lead to unreliable information transmission; in one embodiment, network latency, network bandwidth, and signal strength are weighted, combined, and normalized to obtain a network condition factor.

[0089] Vehicle Behavior Dynamics Analysis: The RSU monitors vehicle behavior patterns in new areas, including its speed and interactions with other vehicles. If a vehicle exhibits abnormal behavior in a new area (such as sudden stops or lane changes), its trust value may be lowered. In one embodiment, the vehicle's speed and the number of interactions with other vehicles are weighted, combined, and normalized to obtain a behavioral dynamics factor.

[0090] Trust value stability assessment: RSU analysis assesses the stability of the trust value to determine whether it has remained consistent over a past period or has fluctuated drastically. If the trust value does not change much and remains at a high level, the vehicle is considered relatively reliable; otherwise, its trust value needs to be lowered. In one embodiment, the variance or standard deviation of the trust value over a past period is calculated and normalized to obtain the stability factor.

[0091] Weighting factor calculation: Based on the above assessment, a weighting factor is calculated for the RSU trust value, using the following formula:

[0092] ω=α×ω net +β×ω v +γ×ω trust

[0093] Where ω represents the weighting factor, α, β, and γ are the weight coefficients of different factors, and α + β + γ = 1, ω net ω v ω trust These are the network status factor, vehicle behavior dynamic factor, and vehicle trust value stability factor, respectively. The range of the network status factor, behavior dynamic factor, and stability factor is between 0 and 1.

[0094] Trust value adjustment: The trust value is adjusted using a weighting factor ω, as follows:

[0095]

[0096] in, T represents the adjusted trust value. historical This indicates the trust value before adjustment.

[0097] The RSU makes trust decisions for all vehicles in the area based on their trust values. For vehicles with high trust values, the RSU allows them to continue communicating and interacting normally in the network; for vehicles with low trust values ​​or suspected of being malicious, the RSU may take security measures such as restricting communication and monitoring their behavior to ensure that messages in the network can be reliably propagated and to effectively maintain the overall security and stability of the vehicle network. Among these, a trust value greater than the trust threshold is considered a high trust value, and a trust value less than the trust threshold is considered a low trust value.

[0098] S5. Ordinary vehicles or consensus vehicles that need to request a message send a message request to the blockchain and receive the required message.

[0099] If the event message has already been recorded in the blockchain, the requesting vehicle can retrieve the reliable message through the blockchain. Furthermore, to improve retrieval efficiency, the requesting vehicle can narrow its search based on timestamps, message categories, etc., thereby locating the relevant message in the blockchain. After successfully obtaining the required message, the requesting vehicle can apply it to its own decision-making and real-world scenarios, further improving its driving safety, decision-making accuracy, and user experience.

[0100] The above-described embodiments further illustrate the purpose, technical solution, and advantages of the present invention. It should be understood that the above-described embodiments are merely preferred embodiments of the present invention and are not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc., made to the present invention within the spirit and principles of the present invention should be included within the protection scope of the present invention.

Claims

1. A secure and trusted message sharing method for vehicle-to-everything (V2X) networks based on blockchain and trust management, characterized in that: include: The vehicle-to-everything (V2X) message sharing network comprises: a vehicle message broadcast layer, a vehicle consensus layer, an accounting layer, and a trust decision layer. The vehicle message broadcast layer includes ordinary vehicles, which include message-providing vehicles and message-receiving vehicles. The consensus layer includes consensus vehicles. The accounting layer includes accounting nodes. The trust decision layer includes an RSU cluster composed of Roadside Units (RSUs). The secure and trusted message sharing methods for connected vehicles include: S1. The message providing vehicle records and broadcasts message m during its journey. The message receiving vehicle i receives message m, scores the authenticity of message m, and assigns the authenticity score s. 1,i The broadcast was given to the vehicles that reached a consensus; S2, consensus vehicle received message m and authenticity score s 1,i And assign each authenticity score 1,i Perform a usefulness rating, when all authenticity ratings are s 1,i When the number of high-usefulness ratings exceeds the threshold Q, the authenticity rating s 1,i The consensus vehicle c, which receives a high usefulness score, will use the data (m, s) 1,i ,s 2,i,c ,t) is uploaded to the ledger node; where m is the message, s 2,i,c For consensus vehicle c, the authenticity score s 1,i The high usefulness rating, where t is the current timestamp; S3. The accounting node receives and verifies the data uploaded by the consensus vehicle. If the verification is successful, the data uploaded by the consensus vehicle is packaged into a block and stored in the blockchain; otherwise, the data uploaded by the consensus vehicle is discarded. S4. RSU calculates the trust value of vehicles within the area and shares the vehicle trust value with the RSU cluster; the RSU cluster makes trust decisions for vehicles based on the vehicle trust value. S5. Ordinary vehicles or consensus vehicles that need to request a message send a message request to the blockchain and receive the required message. The trust value of a vehicle within the RSU calculation area includes: trust evidence of the vehicle within the RSU calculation area, and the trust value of the vehicle is calculated based on the trust evidence; the calculation of the trust value of the vehicle based on the trust evidence includes: Among them, T j (k) represents the trust value of vehicle j at time k. For cooperation level C j The weights of (k), For familiarity F oj The weights of (k), The weights for the authenticity score s1(k) The weights of the usefulness score s2(k) C j (k) represents the cooperation degree of vehicle j at time k, F oj (k) represents the familiarity of vehicle j at time k, s1(k) represents the authenticity rating of the received message by vehicle j at time k, s2(k) represents the usefulness rating of the received authenticity rating by vehicle j at time k, and o represents the evaluation vehicle of vehicle j, which can be any vehicle in the vehicle network message sharing network. The RSU cluster includes a weighted adjustment mechanism; sharing the vehicle's trust value with the RSU cluster includes: when a vehicle moves from one RSU area to another new RSU area in the RSU cluster, the new RSU inherits the vehicle's trust value and uses the weighted adjustment mechanism to adjust the vehicle's trust value to obtain the adjusted trust value. The weighted adjustment mechanism for vehicle trust values ​​includes: ω=α×ω net +β×ω v +γ×ω trust T new =ωT historical Where ω represents the weighting factor, α, β, and γ are the weight coefficients of different factors, and α + β + γ = 1, ω net ω v ω trust These are the status factors of the vehicle-to-everything (V2X) message sharing network, the dynamic factors of vehicle behavior, and the stability factors of vehicle trust values, respectively. new T represents the vehicle's adjusted trust value. historical This indicates the trust value of the vehicle before adjustments.

2. The method for secure and trusted message sharing in the Internet of Vehicles based on blockchain and trust management according to claim 1, characterized in that, The authenticity scoring of message m includes: the message receiving vehicle calculating the distance between itself and the location where message m occurred and predicting the path it will take. If the distance between the message receiving vehicle and the location where message m occurred is greater than a distance threshold or the location where message m occurred is on the path that the message receiving vehicle predicts it will take, then the authenticity score of message m is performed; otherwise, no authenticity score is performed.

3. The method for secure and trusted message sharing in the Internet of Vehicles based on blockchain and trust management according to claim 1, characterized in that, The consensus vehicle performs a usefulness score on the authenticity score by predicting the path it will take. If the message corresponding to the authenticity score is located on the path the consensus vehicle will take, then the authenticity score is evaluated for usefulness; otherwise, no usefulness score is evaluated.

4. The method for secure and trusted message sharing in the Internet of Vehicles based on blockchain and trust management according to claim 1, characterized in that, In step S2, the threshold Q is When all authenticity scores s 1,i The number of high-usefulness scores H satisfies At that time, all truthfulness scores s for message m 1,i Re-evaluate the usefulness score; when all truth scores are... 1,i The number of high-usefulness scores H satisfies When the message m is invalid, it is discarded; where V is the number of consensus vehicles and L is the number of authenticity scores for message m.

5. The method for secure and trusted message sharing in the Internet of Vehicles based on blockchain and trust management according to claim 1, characterized in that, The ledger layer also includes a reward and punishment mechanism, which includes a trust threshold. Ledger nodes use the reward and punishment mechanism to adjust the trust value of consensus vehicles and automatically replace consensus vehicles with trust values ​​less than the trust threshold with the vehicles with the highest trust values ​​among ordinary vehicles.

6. The method for secure and trusted message sharing in the Internet of Vehicles based on blockchain and trust management according to claim 5, characterized in that, The ledger nodes adjust the trust value of the consensus vehicle using reward and punishment mechanisms, including in step S2, when all authenticity scores s 1,i When the number of high usefulness scores exceeds the threshold Q, the accounting node increases the trust value of consensus vehicles with high usefulness scores and decreases the trust value of consensus vehicles with low usefulness scores through smart contracts.

7. The method for secure and trusted message sharing in the Internet of Vehicles based on blockchain and trust management according to claim 1, characterized in that, The RSU cluster makes trust decisions about vehicles based on their trust values, including: allowing vehicles with high trust values ​​to communicate normally in the vehicle-to-everything (V2X) messaging network; restricting vehicles with low trust values ​​from communicating in the V2X messaging network and monitoring vehicles with low trust values.

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