Privacy-preserving dynamic vehicle platooning management methods and systems

Abstract

This invention discloses a privacy-preserving dynamic vehicle platooning management method and system, comprising: a lead vehicle broadcasting a vehicle platooning recruitment message and transmitting the message to cloud server A; simultaneously, member vehicles generating request messages containing location information and digital signatures, which are forwarded to cloud server A via roadside units (RSUs); cloud server A, with the assistance of cloud server B, calculating the encrypted spatial distance between the lead vehicle and the requesting vehicle using the encrypted Manhattan distance calculation method, and finally outputting a trusted vehicle platooning decision; after the platooning trip is completed, member vehicles generating feedback scores and digital signatures, which are sent to cloud server A via roadside units (RSUs); cloud server A sending aggregated reputation encrypted messages to a trusted authority; and calculating the new reputation value of the lead vehicle from the aggregated reputation encrypted messages received from cloud server A. Using the technical solution of this invention, dynamic platoon disbanding in platooning management is achieved, while effectively protecting privacy and resisting various attacks.

Description

Technical Field

[0001] This invention belongs to the field of vehicle network security technology, and in particular relates to a method and system for dynamic vehicle platooning management with privacy protection. Background Technology

[0002] Today, the Internet of Vehicles (IoV) has become an integral part of intelligent transportation systems, enabling real-time communication between vehicles, infrastructure, and other road users. Among the various applications of IoV, vehicle platooning stands out as a particularly promising solution. A platoon is a group of vehicles consisting of a lead vehicle and multiple member vehicles, referring to the technology of multiple vehicles traveling in a dense, coordinated formation. Vehicle platooning not only reduces air resistance, improves fuel efficiency, and reduces emissions, but also enhances road safety by minimizing human error and optimizing braking.

[0003] In modern fleet management systems, especially in dynamic traffic scenarios, the ability to flexibly split fleets has become a critical function. However, existing research still has significant shortcomings in supporting dynamic vehicle platooning. Most existing solutions limit fleet splitting operations to scenarios where the entire fleet has already reached its destination, meaning that the lead vehicle and its members have similar origins, destinations, and routes. For example, Hu et al. (H Hu, R Lu, Z Zhang. Tpsq: Trust-based platoon service query via vehicular communications, Peer-to-peer Networking and Applications, vol. 10, pp. 262–277, 2017.) proposed a trust-based platoon service query scheme that helps users select reliable lead vehicles by considering unique vehicle location information such as current location, destination, and estimated arrival time. While this scheme can effectively construct initial platoons, it neglects the flexibility of fleet splitting during the journey. In practical applications, flexible fleet splitting management mechanisms should be implemented to improve road utilization, reduce resource waste, and enhance operational efficiency.

[0004] To address this issue, reasonable location matching and robust reputation management mechanisms are crucial. Vehicles need to provide location information to the cloud server to find platoons that match their journeys and make informed decisions. However, this process involves privacy risks. Leakage of vehicle location information could lead to malicious tracking and security vulnerabilities. Reputation values, as a tool for evaluating vehicle trustworthiness, are essential for ensuring platoon reliability. The reputation of the lead vehicle and member vehicles should be evaluated by other vehicles to avoid forming malicious platoons. However, most current vehicle platooning management schemes lack effective privacy protection. For example, Li et al. (Q Li, X Li. Trajectory planning for autonomous modular vehicle docking and autonomous vehicle platooning operations, Transportation Research Part E: Logistics and Transportation Review, vol. 166, p. 102886, 2022.) solved the trajectory planning problem for autonomous modular vehicle docking and platooning by proposing a two-stage optimization framework; however, this scheme cannot guarantee the privacy protection of location and reputation during the calculation process. Summary of the Invention

[0005] The technical problem to be solved by the present invention is to provide a privacy-protected dynamic vehicle platooning management method and system, which can query vehicles to obtain the location information and reputation value of vehicle platoons in real time in a dynamic environment, thereby making a decision on whether to join the platoon, while ensuring that the vehicle's location information and reputation are not leaked; it can also ensure that no external malicious attackers can obtain privacy information by eavesdropping in an open communication environment.

[0006] To achieve the above objectives, the present invention adopts the following technical solution:

[0007] A privacy-preserving dynamic vehicle platooning management method, comprising:

[0008] The lead vehicle broadcasts a vehicle platoon recruitment message and transmits the message to cloud server A; member vehicles generate request messages containing location information and their digital signatures, which are then forwarded to cloud server A via RSU.

[0009] Cloud server A verifies the timeliness, integrity, and authentication validity of the request message and its digital signature;

[0010] With the assistance of cloud server B, cloud server A uses the encrypted Manhattan distance calculation method to calculate the encrypted spatial distance between the lead vehicle and the requesting vehicle, and outputs a reliable vehicle formation decision.

[0011] After the convoy trip is completed, the member vehicles generate a feedback message containing feedback scores and a digital signature, which is then sent to the cloud server A via the roadside unit (RSU).

[0012] Cloud server A verifies the timeliness, integrity, and identity authentication validity of the feedback message and its digital signature, and sends the aggregated reputation ciphertext to the trusted authority TA.

[0013] The trusted authority (TA) uses Paillier's private key to decrypt the aggregated reputation ciphertext received from cloud server A, calculates the new reputation value for the lead vehicle, and stores the updated reputation value in the database.

[0014] This invention also provides a privacy-preserving dynamic vehicle platooning management system, comprising:

[0015] The first processing unit is used to enable the lead vehicle to broadcast a vehicle platoon recruitment message and transmit the message to the cloud server A; the member vehicles generate a request message containing location information and its digital signature, and forward it to the cloud server A via the RSU;

[0016] The second processing unit is used to enable cloud server A to verify the timeliness, integrity, and identity authentication validity of the request message and its digital signature;

[0017] The third processing unit is used to enable cloud server A, with the assistance of cloud server B, to calculate the encrypted spatial distance between the lead vehicle and the requesting vehicle using the encrypted Manhattan distance calculation method, and output a reliable vehicle formation decision.

[0018] The fourth processing unit is used to generate a feedback message containing a feedback score and a digital signature for the member vehicles after the platoon trip is completed, and send it to the cloud server A via the roadside unit (RSU).

[0019] The fifth processing unit is used to enable cloud server A to verify the timeliness, integrity, and identity authentication validity of the feedback message and its digital signature, and to send the aggregated reputation ciphertext to the trusted authority TA.

[0020] The sixth processing unit is used to enable the trusted authority TA to decrypt the aggregated reputation ciphertext received from cloud server A using the Paillier private key, calculate the new reputation value of the lead vehicle, and store the updated reputation value in the database.

[0021] Compared with the prior art, the present invention has the following technical effects:

[0022] 1. This invention introduces a cloud-assisted mechanism to migrate complex operations such as reputation management and location matching, which are traditionally performed by the TA alone, to the cloud for processing, significantly reducing the computational burden on the TA. At the same time, the security protocol design ensures the integrity and reliability of the cloud-assisted process, achieving efficient distributed vehicle platooning management.

[0023] 2. This invention constructs an encrypted trapdoor for the lead vehicle and an encrypted index for the query vehicle using a Bloom filter. This not only efficiently calculates the position matching value between the query vehicle and the lead vehicle, but also effectively protects user privacy and data security in the face of potential threats, providing a solid guarantee for vehicle platoon management.

[0024] 3. This invention employs Schnorr signatures to provide security, effectively protecting sensitive information in request and response messages. Furthermore, Schnorr signatures support batch verification, significantly improving the verification efficiency of CSS. Attached Figure Description

[0025] To more clearly illustrate the technical solutions in the embodiments of the present invention or 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 embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on the provided drawings without creative effort.

[0026] Figure 1 This is a schematic diagram of the physical structure of the privacy-preserving dynamic vehicle platooning management method according to an embodiment of the present invention;

[0027] Figure 2 This is a flowchart of a dynamic vehicle platooning management method for privacy protection, as described in an embodiment of the present invention. Detailed Implementation

[0028] 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.

[0029] To make the above-mentioned objects, features and advantages of the present invention more apparent and understandable, the present invention will be further described in detail below with reference to the accompanying drawings and specific embodiments.

[0030] Example 1:

[0031] like Figure 1 As shown, this embodiment of the invention provides a privacy-preserving vehicle platooning management method, such as... Figure 1 As shown, the entities involved in the embodiments of the present invention include: Trust Authority (TA), Cloud Servers (CSs), Roadside Units (RSUs), and vehicles.

[0032] The trusted authority (TA) is responsible for initializing the cryptographic system, vehicle registration, and storing vehicle user information.

[0033] The cloud server CSS possesses powerful computing and storage capabilities. Among them, CSS... A CS is responsible for location matching and fleet generation decisions. B CS is assisted by querying the Bloom filter module. A Generate fleet decisions.

[0034] The Roadside Unit (RSU) is installed on the roadside, covering a wide area. It mainly undertakes message forwarding and serves as the communication interface between vehicles and upper-level entities (i.e., TA and CSs).

[0035] The vehicles have two roles: ① Lead vehicle: As the initiator and manager of the vehicle platoon, the lead vehicle is responsible for route planning and decision-making, and guides member vehicles through the communication system. ② Member vehicles: Under the guidance of the lead vehicle, they adjust their speed, maintain platoon formation and safe distance, and achieve coordinated and efficient driving.

[0036] The TA is completely trustworthy. CSs and RSUs are honest but curious, meaning they will strictly adhere to the protocol but may exhibit curiosity about certain private information. We assume that most of the lead vehicle and crew vehicles are honest, while a minority are malicious and can launch various attack methods, including Sybil attacks, tampering attacks, spoofing attacks, and replay attacks, to attempt to disrupt the vehicle-to-everything (V2X) system.

[0037] like Figure 2 As shown, this embodiment of the invention provides a privacy-preserving vehicle platooning management method, including:

[0038] Step S1, System Initialization:

[0039] TA initializes the elliptic curve cryptosystem and Paillier cryptosystem parameters, publishes public parameters, and transmits them to CS via a secure channel. B Send to the Bloom filter module.

[0040] Step S2, Entity Registration:

[0041] Vehicles register by submitting their real identity and location vector to the TA via a secure channel. The TA generates a privacy-protected pseudonym for each vehicle and distributes encrypted location vectors and reputation values, ensuring identity privacy, reputation privacy, and location privacy.

[0042] Step S3: Initiate a request:

[0043] The lead vehicle broadcasts a platoon recruitment message and sends it to the cloud server CS via RSU. AMessage transmission. The member vehicle generates a request message containing location information and a digital signature, which is forwarded to the CS via the RSU. A .

[0044] Step S4: Request verification:

[0045] CS A Verify the timeliness, integrity, and authentication validity of the request message to ensure that the request has not been tampered with and that its origin is legitimate.

[0046] Step S5, Formation Decision:

[0047] CS A In CS B With assistance, the encrypted Manhattan distance calculation method is used to calculate the encrypted spatial distance between the lead vehicle and the requesting vehicle, and finally output a reliable vehicle formation decision.

[0048] Step S6, Feedback Generation:

[0049] After the convoy trip is completed, the member vehicles generate feedback scores and digital signatures, which are then sent to the CS via the RSU. A .

[0050] Step S7, Feedback Verification:

[0051] CS A Verify the timeliness, completeness, and authentication validity of the feedback message, ensure that the request has not been tampered with and is of legitimate origin, and send the aggregated reputation encrypted message to TA.

[0052] Step S8, Reputation Update:

[0053] TA uses Paillier's private key to decrypt from CS A Receive the aggregated reputation ciphertext, calculate the new reputation value for the lead vehicle, and store the updated reputation value in the database.

[0054] As one embodiment of the present invention, step S1 includes:

[0055] TA Initialize Elliptic Curve Cryptosystem (ECC): Choosing a Prime Order Elliptic curve group The generator is TA randomly selects As the master private key of the ECC system, calculate the public key. Simultaneously, TA initializes the Paillier encryption system and generates Paillier key pairs. .

[0056] TA selects secret parameters and Each independent hash function and initialize Bit-Bloom filter array: All elements are initially set to 0.

[0057] TA divides the regional map into Blocks, vehicle locations are represented as integer coordinates Subsequently, TA used Paillier's public key. For all in the map Encryption, .

[0058] TA defines the upper and lower bounds of the reputation value for integers. and And set a Manhattan distance threshold Navigator vehicle reputation threshold Member vehicle reputation threshold , which serves as the core constraint parameter for formation decision-making.

[0059] TA traverses block coordinates and Calculate the hash difference For each ,pass Each hash function is mapped to Set the corresponding position to 1 to complete the setting of the positional relationship check bit. Through the above operations, TA completes the Bloom filter module. The settings.

[0060] TA defines the Manhattan distance threshold traversal ,calculate ,pass Hash function updates The corresponding bit is 1. Traverse ,calculate ,pass hash functions Will Corresponding bit Set to 1; iterate through ,calculate ,pass Hash function updates Corresponding to position 1. Through the above operations, TA completes the Bloom filter module. The settings.

[0061] Finally, TA publishes public parameters. ,Will Transmitted to CS via secure channel A and will Transmitted to CS via secure channel B.

[0062] As one embodiment of the present invention, step S2 includes:

[0063] Since the formation process of vehicle platooning and the selection of lead and crew vehicles have been thoroughly discussed in previous studies, these are not the focus of this invention. When non-lead vehicles... With real identity When you apply for registration with TA, TA will do the following:

[0064] TA randomly selects a random number Calculate the points of the elliptic curve Generate kana components , where the position vector Each element represents the starting coordinate of the vehicle's journey. The final synthesized vehicle pseudonym TA generates a private key for the vehicle. ( (For timestamps), and query the coordinates of the encrypted blocks stored during the initialization phase to generate the location vector ciphertext. Each coordinate component The inverse operation is represented in detail as follows: as well as Simultaneously, TA calculates the hash position vector. ,in, .

[0065] Trusted Authority (TA) sets initial reputation values ​​based on vehicle type: (1) Law enforcement vehicles: (2) Public service vehicles: (3) Private vehicles: . in, For the floor function, To control the scaling factor of the reputation value range, TA uses the Paillier encryption algorithm to generate reputation ciphertext. and distribute the encrypted message to the vehicle. .

[0066] Finally, TA will Transmitted through a secure channel and will Stored in a database.

[0067] In this step, for the lead vehicle The special treatment is as follows:

[0068] TA is Planning between start and end coordinates Each anchor point generates a set of encrypted anchor point coordinates. Each element in the set of encrypted anchor point coordinates is represented as Simultaneously, TA calculates the hash position vector. and hash anchor set Finally, TA will provide the complete parameter set. Send via secure channel .

[0069] As one embodiment of the present invention, step S3 includes: Generate recruitment message ,in For the set of encrypted anchor point coordinates, For the set of hash anchors, Generate a timestamp for the private key. This is the timestamp of the current request. Randomly select a temporary private key Calculate the temporary public key and generate broadcast signature. .

[0070] Complete request data packet The request is broadcast to nearby vehicles via the RSU, and the RSU simultaneously forwards the request to the cloud server CS. A .

[0071] As one embodiment of the present invention, step S4 includes:

[0072] Verifying the lead vehicle After the broadcast signature is obtained, a request message is generated. (in (For the requested timestamp), randomly selected. Calculate the temporary public key and generate a request signature. The vehicle will send a request message via the RSU. Send to cloud server CS A .

[0073] CS A Execute verification operation after receiving the request:

[0074] Single verification: Verification via elliptic curve operations Ensure the signature is valid;

[0075] Batch verification: For applications to join a vehicle platoon vehicle collection ,verify This enables efficient batch verification.

[0076] As one embodiment of the present invention, step S5 includes:

[0077] CS A Calculate vehicles With lead vehicle hash position difference ,in Simultaneously calculate the path anchor point difference. Corresponding to After completing the above calculations, CS A Will Send to CS via secure channel B .

[0078] CS B Perform position vector comparison: initialize flag bits , and . use Each independent hash function is used for each Calculate hash value and query Bloom filter module Are the corresponding bits 1? If all are 1, then keep them. Otherwise, set it to 0. Process similarly. CS B Will and Return to CS via secure channel A .

[0079] CS A Based on CS B Calculate the ciphertext Manhattan distance of the received message:

[0080] when At that time, calculate the distance between the starting points of the two vehicles in the ciphertext Manhattan. Otherwise calculate Similarly, according to and Calculate the encrypted distance of the endpoint and anchor point x-coordinates respectively. Ciphertext distance from the endpoint / anchor point's ordinate .

[0081] CS A Generate Manhattan distance ciphertext set as well as .

[0082] CS A Calculate hash value and ,in represent Each element in CS. A calculate hash reputation value and request vehicle hash reputation value CS A Will Send to CS via secure channel B .

[0083] CS B Receive CS A Sent Then, execute the final formation decision-making process: CS B use Each independent hash function calculates... The hash value of each element is used as an index to query the formation decision Bloom filter module. The corresponding bit; if all corresponding bits of the Bloom filters are 1, then set the decision flag. and return the flag to CS A .

[0084] CS A according to Value update of the swarm member set :when At that time, the pseudonym for vehicle V_i will be used. Join vehicle formation Member set After completing all requested vehicle decisions, CS A Storing vehicle platoons in a database Core data At the same time Add vehicle pseudonyms to trip status collection To mark it as having joined the formation.

[0085] As one embodiment of the present invention, step S6 includes:

[0086] Passenger vehicles Leave the formation At that time, a feedback score is generated. And construct feedback messages ( (For feedback timestamps).

[0087] Randomly select feedback private key Calculate the temporary public key Generate feedback signature .

[0088] Data packets via RSU Send to cloud server CS A .

[0089] As one embodiment of the present invention, step S7 includes:

[0090] CS A Receiving Formation vehicle assembly of members After receiving feedback messages from all member vehicles, perform batch signature verification: through equation Verify the validity of all feedback signatures.

[0091] In formation After all member vehicles' feedback signatures pass batch verification, CS A Extract rating sets from feedback messages Then, perform encrypted aggregation calculations. First, CS... A Calculating the fundamental reputation product using Paillier's homomorphic addition property Next, the score-weighted product is calculated using scalar multiplication homomorphism. Finally, CSA will aggregate the reputation ciphertext. It is sent to the TA via a secure channel for subsequent TA calculations of the weighted average reputation value.

[0092] As one embodiment of the present invention, step S8 includes:

[0093] TA receives CS A Sent Then, use Paillier's private key. Decrypting Computational Navigation Vehicles The reputation value is assessed. TA first decrypts the base reputation product. Receive the sum of the reputation points of the members' vehicles. Then decrypt the weighted product of the scores. ,get Through the formula Calculate the weighted average evaluation value, where, This is a rounding function that ensures the result is rounded to an integer.

[0094] To ensure that there is no overflow during the calculation process, the system parameters are designed to meet the following requirements. Under this constraint, To ensure that Paillier's decryption results are in the model Valid within the domain to prevent values ​​from going out of bounds.

[0095] TA further integrates historical reputation with new evaluation values ​​to generate a new reputation value for the lead vehicle V_L. Weighting factors By function Dynamic calculation, in which Controlling the rate of change This is a reliable threshold for group size. When the number of members... hour, As it approaches 0, the system tends to retain historical reputation; when... When the threshold is exceeded, Approaching 1, the new evaluation value dominates the update, achieving a balance between noise resistance for small formations and sensitive response for large formations.

[0096] Example 2:

[0097] This invention also provides a privacy-preserving dynamic vehicle platooning management system, comprising:

[0098] The first processing unit is used to enable the lead vehicle to broadcast a vehicle platoon recruitment message and transmit the message to the cloud server A; the member vehicles generate a request message containing location information and its digital signature, and forward it to the cloud server A via the RSU;

[0099] The second processing unit is used to enable cloud server A to verify the timeliness, integrity, and identity authentication validity of the request message and its digital signature;

[0100] The third processing unit is used to enable cloud server A, with the assistance of cloud server B, to calculate the encrypted spatial distance between the lead vehicle and the requesting vehicle using the encrypted Manhattan distance calculation method, and output a reliable vehicle formation decision.

[0101] The fourth processing unit is used to generate a feedback message containing a feedback score and a digital signature for the member vehicles after the platoon trip is completed, and send it to the cloud server A via the roadside unit (RSU).

[0102] The fifth processing unit is used to enable cloud server A to verify the timeliness, integrity, and identity authentication validity of the feedback message and its digital signature, and to send the aggregated reputation ciphertext to the trusted authority TA.

[0103] The sixth processing unit is used to enable the trusted authority TA to decrypt the aggregated reputation ciphertext received from cloud server A using the Paillier private key, calculate the new reputation value of the lead vehicle, and store the updated reputation value in the database.

[0104] The embodiments described above are merely preferred embodiments of the present invention and are not intended to limit the scope of the present invention. Various modifications and improvements made to the technical solutions of the present invention by those skilled in the art without departing from the spirit of the present invention should fall within the protection scope defined by the claims of the present invention.

Claims

1. A privacy-preserving dynamic vehicle platooning management method, characterized in that, include: The lead vehicle broadcasts a vehicle platoon recruitment message and transmits the message to cloud server A. The member vehicle generates a request message containing location information and its digital signature, which is then forwarded to cloud server A via RSU; Cloud server A verifies the timeliness, integrity, and authentication validity of the request message and its digital signature; With the assistance of cloud server B, cloud server A uses the encrypted Manhattan distance calculation method to calculate the encrypted spatial distance between the lead vehicle and the requesting vehicle, and outputs a reliable vehicle formation decision. After the convoy trip is completed, the member vehicles generate a feedback message containing feedback scores and a digital signature, which is then sent to the cloud server A via the roadside unit (RSU). Cloud server A verifies the timeliness, integrity, and identity authentication validity of the feedback message and its digital signature, and sends the aggregated reputation ciphertext to the trusted authority TA. The trusted authority TA uses Paillier's private key to decrypt the aggregated reputation ciphertext received from cloud server A, calculates the new reputation value of the lead vehicle, and stores the updated reputation value in the database; Outputting reliable vehicle platooning decisions includes: CS A Calculate vehicles With lead vehicle hash position difference ,in Simultaneously calculate the path anchor point difference. Corresponding to After completing the above calculations, Send to CS via secure channel B , CS B Perform position vector comparison: initialize flag bits and ,use Each independent hash function is used for each Calculate hash value and query Bloom filter module Are the corresponding bits 1? If all are 1, then keep them. Otherwise, set to 0, and process similarly. CS B Will and Return to CS via secure channel A , CS A Based on CS B Calculate the ciphertext Manhattan distance of the received message: when At that time, calculate the distance between the starting points of the two vehicles in the ciphertext Manhattan. Otherwise calculate Similarly, according to and Calculate the encrypted distance of the endpoint and anchor point x-coordinates respectively. Ciphertext distance from endpoint / anchor point ordinate , CS A Generate Manhattan distance ciphertext set as well as , CS A Calculate hash value ,in represent Each element in CS A calculate hash reputation value and request vehicle hash reputation value CS A Will Send to CS via secure channel B , CS B Receive CS A Sent Then, execute the final formation decision-making process: CS B use Each independent hash function calculates... The hash value of each element is used as an index to query the formation decision Bloom filter module. The corresponding bit; if all corresponding bits of the Bloom filters are 1, then set the decision flag. and return the flag to CS A , CS A according to Value update of the swarm member set :when At that time, the pseudonym for vehicle V_i will be used. Join vehicle formation Member set After completing all requested vehicle decisions, CS A Storing vehicle platoons in a database Core data At the same time Add vehicle pseudonyms to trip status collection To mark it as having joined the formation.

2. A privacy-preserving dynamic vehicle platooning management system that implements the privacy-preserving dynamic vehicle platooning management method of claim 1, characterized in that, include: The first processing unit is used to enable the lead vehicle to broadcast a vehicle formation recruitment message and transmit the message to the cloud server A. The member vehicle generates a request message containing location information and its digital signature, which is then forwarded to cloud server A via RSU; The second processing unit is used to enable cloud server A to verify the timeliness, integrity, and identity authentication validity of the request message and its digital signature; The third processing unit is used to enable cloud server A, with the assistance of cloud server B, to calculate the encrypted spatial distance between the lead vehicle and the requesting vehicle using the encrypted Manhattan distance calculation method, and output a reliable vehicle formation decision. The fourth processing unit is used to generate a feedback message containing a feedback score and a digital signature for the member vehicles after the platoon trip is completed, and send it to the cloud server A via the roadside unit (RSU). The fifth processing unit is used to enable cloud server A to verify the timeliness, integrity, and identity authentication validity of the feedback message and its digital signature, and to send the aggregated reputation ciphertext to the trusted authority TA. The sixth processing unit is used to enable the trusted authority TA to decrypt the aggregated reputation ciphertext received from cloud server A using the Paillier private key, calculate the new reputation value of the lead vehicle, and store the updated reputation value in the database.

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