Vehicle formation privacy protection location query method and system supporting dynamic joining

Abstract

The present invention relates to the field of vehicle network security technology, and more specifically to a privacy-preserving location query method and system for vehicle platoons supporting dynamic joining. The method comprises the following steps: S1, system initialization: publishing public parameters; S2, entity registration: the entity (TA) generates a pseudonym and public and private keys for each vehicle; S3, request initiation: sending the query request to the control system (CS); S4, query verification: the CS verifies the legitimacy and frequency limit of the query request; S5, response: generating a privacy-preserving response and sending it to the control system; S6, matching calculation: generating a matching certificate and forwarding the response of the pilot vehicle to the querying vehicle; S7, information acquisition: encoding the matching location and time information; and S8, joining decision: using the matching certificate to join the vehicle platoon. The present invention utilizes a pseudonym mechanism, Bloom filter encryption, and Hilbert curve encoding to effectively prevent privacy leakage, improve matching calculation efficiency, and ensure the security of vehicle platoon management.

Description

Technical Field

[0001] The present invention relates to the field of vehicle network security technology, and in particular to a privacy-preserving location query method and system for a vehicle formation supporting dynamic joining. Background Art

[0002] With the continuous development of vehicle networking technology, autonomous driving technology and related communication protocols, vehicle platooning technology has received widespread attention. Vehicle platooning is a traffic mode that uses advanced communication and control strategies to enable multiple vehicles to maintain formation and spacing while driving, achieving collaborative control. In the platoon, the lead vehicle is responsible for managing the team members and making driving decisions, while the following vehicles drive according to the instructions of the lead vehicle. Platooning can effectively alleviate traffic congestion, reduce air resistance, thereby reducing vehicle energy consumption and pollutant emissions, and improving road traffic efficiency and safety.

[0003] Although vehicle platooning technology has significant advantages, existing research has mainly focused on the construction of static formations and neglected the support of dynamic vehicle formations. Most existing solutions form formations based on fixed parameters such as location, destination, and estimated arrival time, and cannot meet the needs of vehicles joining the formation at any time during driving. The core issue in dynamic formation management is how to determine the location of newly added vehicles and match them with the existing formation. In addition, most current vehicle platooning systems lack effective privacy protection mechanisms. Once the vehicle's location information is leaked, it may lead to malicious tracking and security risks. Some existing solutions fail to use encryption to protect the vehicle's location privacy, posing a large privacy risk. Summary of the Invention

[0004] The present invention provides a privacy-preserving position query method and system for vehicle formations that support dynamic joining, enabling effective position query and information exchange between the querying vehicle and the pilot vehicle. The querying vehicle can obtain the position information of the vehicle formation in real time in a dynamic environment, thereby making a decision on whether to join the formation. At the same time, the privacy of the vehicle's complete route is protected from being leaked, and it can also ensure that no external malicious attackers can obtain private information through eavesdropping in an open communication environment.

[0005] A privacy-preserving location query method for a vehicle formation supporting dynamic joining includes the following steps:

[0006] S1, system initialization: The trusted authority TA initializes the elliptic curve cryptosystem, generates public and private keys for the cloud server CS, and publishes public parameters;

[0007] S2, Entity Registration: Vehicles apply for registration with the TA, which generates a pseudonym and public and private keys for each vehicle. The TA and CS store vehicle formation information, including the lead vehicle and follower vehicles;

[0008] S3, initiates the request: The query vehicle plans its route and encodes and encrypts the location using the Hilbert curve. After calculating the index, the query request is sent to the CS to protect privacy and obtain trip-related information;

[0009] S4, query verification: CS verifies the legitimacy and frequency limit of the query request and helps the query vehicle generate a query credential to pass to the pilot vehicle, and saves the query vehicle's index in the local database;

[0010] S5, respond: After receiving the query credential, the pilot vehicle calculates the trapdoor and generates a privacy-preserving response and sends it to the CS;

[0011] S6, Matching Calculation: After receiving the response from the pilot vehicle, the CS performs a matching calculation on the pilot vehicle trap door and the query vehicle index, generates a matching certificate, and forwards the pilot vehicle's response to the query vehicle;

[0012] S7, information acquisition: After receiving the response from the pilot vehicle returned by the CS, the query vehicle recovers the location and time information that matches the query location code through calculation;

[0013] S8, joining decision: The query vehicle adjusts its driving strategy according to the information of the vehicle formation and joins the vehicle formation using the matching certificate.

[0014] Optionally, the system initialization in S1 includes:

[0015] S11, Elliptic Curve Cryptography System Initialization: Given Security Parameters ,TA initializes the elliptic curve cryptography (ECC), given by the prime number Finite field defined , generating an elliptic curve ,in, and , all points on the elliptic curve and the point at infinity form a prime order q The additive cyclic group of , the generator is 𝑃, TA selects a random number As the system's master private key, and calculate the corresponding system public key ;

[0016] S12, generate system keys and parameters: given security parameters , TA outputs the secret key ,in, is a reversible matrix, is a vector, TA chooses Independent hash functions ;

[0017] S13, select a secure one-way hash function: TA selects a one-way hash function, including 、 、 、 ,in Represents a fixed-length string;

[0018] S14, set query request frequency limit: TA sets the maximum number of requests , represents the number of query requests submitted by any query vehicle within the scheduled time (within 10 minutes) (maximum 10 times);

[0019] S15, cloud server distributes keys and stores them: TA distributes private keys to CS , and calculate the corresponding public key , TA sends the key pair to Send it to CS, which stores the key pair securely.

[0020] S16, publish public parameters: TA publishes public parameters , expressed as:

[0021] .

[0022] Optionally, the entity registration in S2 includes:

[0023] S21, Vehicle pseudonym generation and key generation: When a vehicle is registered, the TA generates a unique pseudonym and public and private keys for each vehicle and sends them to the vehicle via a secure channel. Specifically, the following steps are performed:

[0024] S211, Vehicle Registration Application: When the vehicle With real identity When applying for registration with TA, TA selects a random number , and calculate

[0025] S212, Pseudonym Generation: TA uses a hash function Calculate the pseudonym of the vehicle, expressed as:

[0026] ;

[0027] in, It means concatenating two strings. is the pseudonym generation time;

[0028] S213, key pair generation: TA is the vehicle Generate a pair of public and private keys, where the private key is , the public key is ;

[0029] S214, Bloom filter generation: TA generates it Bloom filter ;

[0030] S215, key and pseudonym are sent: TA sends Send to vehicle ;

[0031] S22, vehicle formation setting: TA and CS store vehicle formation information based on the formation's unique identifier and formation formation time, specifically including:

[0032] S221, formation scene setting: Assume there is a A platoon of vehicles, consisting of Following vehicles;

[0033] S221, formation information storage: TA and CS store formation information in their respective databases, expressed as:

[0034] ;

[0035] in, is the unique identifier of the formation, is the formation time, Indicates the pilot vehicle. Represents each following vehicle.

[0036] Optionally, the initiating request in S3 includes:

[0037] S31, planning the driving route and identifying key locations: when querying the vehicle to obtain the vehicle formation information, a query request is generated, and the query vehicle Plan its driving route and identify key locations it will pass through, including intersections, gas stations, and toll booths;

[0038] S32, using Hilbert curve encoding location: the query vehicle uses the Hilbert curve encoding method to encode key locations to form a Hilbert curve encoding set of the query location ;

[0039] S33, encrypted query position code: Encrypt each query position code and calculate the encrypted value , Select random number , and calculate , and finally generate the encrypted query location set ;

[0040] S34, request frequency limitation and privacy protection: Select the current timestamp , and set the request counter Add 1 and calculate , Using a hash function Encode each query position Insert Bloom filter , generate index ;

[0041] S35, encrypted query location index: Index Decompose into vectors and , and use the matrix and For vector and Encrypt and get the encrypted index ;

[0042] S36, Asymmetric Encryption and Signature Generation: Querying Vehicles Encrypt the query location collection , hash value and encrypted indexes Use CS's public key Perform asymmetric encryption to obtain encrypted content ,in, Represents ElGamal asymmetric encryption and uses the signature generation algorithm implemented by the elliptic curve digital signature algorithm ECDSA to generate a signature ;

[0043] S37, send query request: query vehicle The signed query request is sent to CS via RSU. The request content is .

[0044] Optionally, the query verification in S4 includes:

[0045] S41, signature verification: When CS receives the query vehicle Query request sent Finally, verify the legitimacy and frequency limit of the query request;

[0046] S42, ElGamal decryption: CS passed Verify the signature in the query request ,in, Indicates the signature verification algorithm implemented using the ECDSA algorithm, and passes Decryption ,in, Indicates ElGamal asymmetric decryption;

[0047] S43, query request validity check: CS check The validity of the query and check whether the number of queries in the current time window exceeds the threshold set by the system ,If the number of queries exceeds the limit, the query request will be rejected;

[0048] S44, Data storage: If the query request passes the validity check, CS will 、 、 and Temporarily save to the database;

[0049] S45, query certificate signature generation: CS uses private key Sign the query credential. The generated signature is expressed as:

[0050] ;

[0051] in, is the timestamp;

[0052] S46, query credential sent: the query credential generated by CS is CS will generate the query certificate Sent to the pilot vehicle via RSU .

[0053] Optionally, the responding in S5 includes:

[0054] S51, Signature Verification: Pilot Vehicle Receive query voucher Afterwards, through Verify CS's signature ,If the verification fails, the pilot vehicle rejects the message;

[0055] S52, generate a privacy protection response: pilot vehicle Generate a privacy-preserving response and send it to the CS, including information about the vehicle formation;

[0056] S53, encrypted query location set processing: Get the query vehicle Provided encrypted query location collection , Select random number , and calculate ;

[0057] S54, Hilbert curve coding set generation: Forming a Hilbert curve encoding set , each code Uniquely corresponds to a place and time information pair, expressed as:

[0058] ;

[0059] S55, Information Encryption: Pilot Vehicle calculate and ,in, ;

[0060] S56, Bloom filter and trapdoor generation: Using a hash function Encode each route location Insert Bloom filter , generating a trapdoor , The trap door Decompose into vectors and , and use the matrix and For vector and Encrypt and get the encrypted index ;

[0061] S57, Asymmetric Encryption and Signature Generation: Pilot Vehicle Use CS's public key Perform asymmetric encryption to obtain encrypted content , and generate a signature ,in, is the timestamp;

[0062] S58, response sent: pilot vehicle The signed response content is sent to CS via RSU. The response content sent is .

[0063] Optionally, the matching calculation in S6 includes:

[0064] S61, Signature Verification: When CS receives the pilot vehicle Response sent After that, CS passed Verify the signature in the response ;

[0065] S62, Decryption and Calculation: CS passed Decryption , CS uses and calculate , and based on As a pilot vehicle and query vehicle Route matching value, calculation ;

[0066] S63, matching certificate generation: CS uses pilot vehicle Public key Matching value for matching results Encrypt and use the private key Sign and generate a matching certificate , expressed as:

[0067] ;

[0068] S64, Generate Signature and Forward Response: Generate Signature ,in, It is the timestamp, CS sends it to RSU through Send a message with the content .

[0069] Optionally, the information acquisition in S7 includes:

[0070] S71, Signature Verification: Query Vehicle Received message Afterwards, through Verify CS's signature ,If the verification fails, the query vehicle rejects the response message;

[0071] S72, information recovery: after verification, query the vehicle use and Recover information, including:

[0072] S721, calculate the query position code: Calculate the query position encoding, expressed as:

[0073] ;

[0074] in, It is a pilot vehicle Encrypted information sent, Is the vehicle query The random number selected, Is the vehicle query The encrypted position code sent;

[0075] S722, restore location and time information: When the pilot vehicle Query position encoding and query vehicle Query position encoding When matching, by calculating , query vehicle Recover the location and time information that matches the query location code ;

[0076] S73, Adjust driving strategy: Query vehicle According to the restored location and time information Adjust your driving strategy to plan your route.

[0077] Optionally, the joining decision in S8 includes:

[0078] S81, send a join request: query vehicle Use matching certificate As proof, the pilot vehicle Send a join message. The join message is ,in, is the timestamp of the request to join, Is to query the vehicle using your own private key Signature of the request content;

[0079] S82, Verify signature: Pilot vehicle Received joining message Afterwards, through Verify the signature ;

[0080] S83, Verify matching certificate: Pilot vehicle pass Verify matching certificates The signature in Get the matching value ;

[0081] S84, Matching Degree Judgment: Pilot Vehicle Based on the matching value in the matching certificate , determine the vehicle Determine the matching degree with the vehicle formation;

[0082] S85, accept to join: if the verification is passed, the pilot vehicle Will accept vehicle inquiries and incorporate it into the vehicle formation.

[0083] The privacy-preserving location query system for vehicle formations supporting dynamic joining is used to implement the privacy-preserving location query method for vehicle formations supporting dynamic joining, and includes the following modules:

[0084] System initialization module: The trusted authority TA initializes the elliptic curve cryptography system, generates public and private keys for the cloud server CS, and publishes public parameters;

[0085] Entity registration module: Vehicles apply for registration with the TA, which generates a pseudonym and public and private keys for each vehicle. The TA and CS store vehicle formation information, including the lead vehicle and follower vehicles.

[0086] Query request initiation module: The query vehicle plans its route and encodes and encrypts the location using the Hilbert curve. After calculating the index, the query request is sent to the CS to protect privacy and obtain trip-related information;

[0087] Query Verification Module: The CS verifies the legitimacy and frequency limit of the query request, helps the querying vehicle generate a query credential and passes it to the pilot vehicle, and saves the index of the querying vehicle;

[0088] Response generation module: After receiving the query credential, the pilot vehicle calculates the trapdoor and generates a privacy-preserving response, which is then sent to the CS.

[0089] Matching calculation module: After receiving the response from the pilot vehicle, the CS performs a matching calculation on the pilot vehicle's trap door and the query vehicle's index, generates a matching certificate, and forwards the response to the query vehicle;

[0090] Information recovery module: After receiving the response from the pilot vehicle returned by the CS, the query vehicle recovers the location and time information that matches the query location code through calculation;

[0091] Joining decision module: The query vehicle adjusts its driving strategy according to the information of the vehicle formation and joins the vehicle formation using the matching certificate.

[0092] Beneficial effects of the present invention:

[0093] The present invention realizes the location query of dynamic platoons while protecting the privacy of vehicles through the application of pseudonym mechanism and oblivious transfer protocol. Through encryption technology and privacy protection means, it can effectively prevent malicious attackers from obtaining the complete route information of vehicles, ensure the privacy security of vehicles, improve the security and privacy protection capabilities of the vehicle platooning system, and avoid the privacy leakage risks caused by the plaintext transmission of location data in traditional methods.

[0094] The present invention combines a Bloom filter with an encrypted trapdoor to construct an encrypted trapdoor for the pilot vehicle and an encrypted index for the query vehicle. This allows for efficient calculation of the route matching value between the query vehicle and the pilot vehicle. At the same time, the solution can effectively address potential security threats and safeguard user privacy and data security, ensuring not only privacy protection but also improved management efficiency of vehicle formations and possessing strong anti-attack capabilities.

[0095] The present invention encodes two-dimensional space through the Hilbert curve, constructing a simple and efficient spatial location query structure. It provides an effective encoding technology for privacy-preserving location queries that support dynamically joined vehicle formations. This scheme transforms complex queries in two-dimensional space into one-dimensional space encoding, improving query efficiency and optimizing the query process through spatial partitioning, further enhancing the real-time and scalability of the system. BRIEF DESCRIPTION OF THE DRAWINGS

[0096] In order to more clearly illustrate the technical solutions in the present invention or the prior art, the following briefly introduces the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings described below are only for ordinary technicians in this field of the present invention, and other drawings can be obtained based on these drawings without paying any creative work.

[0097] Figure 1 A schematic diagram of the entity structure of a privacy-preserving location query method for a vehicle formation supporting dynamic joining according to an embodiment of the present invention;

[0098] Figure 2 A flowchart of a privacy-preserving location query method for a vehicle formation supporting dynamic joining according to an embodiment of the present invention is provided;

[0099] Figure 3 Schematic diagram of system function modules according to an embodiment of the present invention. DETAILED DESCRIPTION

[0100] The present invention is described in detail below with reference to the accompanying drawings and specific embodiments. It is also noted that, to provide a more detailed description, the following embodiments are best and preferred embodiments, and those skilled in the art may employ alternative methods for implementing certain known technologies. Furthermore, the accompanying drawings are intended only to provide a more detailed description of the embodiments and are not intended to limit the present invention.

[0101] It should be noted that references in the specification to "one embodiment," "an embodiment," "exemplary embodiments," "some embodiments," etc. indicate that the described embodiments may include specific features, structures, or characteristics, but not necessarily every embodiment will include such specific features, structures, or characteristics. Furthermore, when specific features, structures, or characteristics are described in conjunction with an embodiment, it is within the knowledge of persons skilled in the relevant art to implement such features, structures, or characteristics in conjunction with other embodiments (whether or not explicitly described).

[0102] In general, terms can be understood, at least in part, from their use in context. For example, depending at least in part on the context, the term "one or more" as used herein can be used to describe any feature, structure, or characteristic in the singular sense, or can be used to describe a combination of features, structures, or characteristics in the plural sense. Additionally, the term "based on" can be understood as not necessarily intended to convey an exclusive set of factors, but can instead, depending at least in part on the context, allow for the presence of other factors that are not necessarily explicitly described.

[0103] like Figure 1 As shown, the entities involved in this embodiment include: a trusted authority (TA), a cloud server (CS), a road-side unit (RSU) and a vehicle.

[0104] The trusted authority TA is used to generate system parameters and maintain vehicle information.

[0105] The cloud server CS has powerful computing and storage capabilities. CS is responsible for calculating the matching value and generating the matching certificate.

[0106] The roadside unit (RSU) is installed on the roadside with a wide coverage area and is only the communication interface between the vehicle and the upper-layer entity (i.e., TA and CS).

[0107] Vehicles have three roles: ① Leading vehicle: As the initiator of a platoon, the leading vehicle is responsible for managing the entire platoon through the Internet of Vehicles, from its formation to its disbanding. ② Following vehicle: In a platoon, vehicles other than the leading vehicle are led by the leading vehicle. When a following vehicle leaves the platoon, it becomes a regular vehicle. ③ Querying vehicle: Vehicles outside the platoon that wish to join the platoon and submit a query request are called querying vehicles.

[0108] The TA is fully trustworthy. The RSU, CS, pilot vehicle, and follower vehicles are honest but curious, meaning they strictly follow the protocol but may be curious about certain private information. We assume that most querying vehicles are honest, while a minority are malicious and can launch multiple request attacks.

[0109] like Figure 2 As shown, the privacy-preserving location query method for a vehicle formation supporting dynamic joining includes the following steps:

[0110] Step S1: System initialization:

[0111] The TA initializes the elliptic curve cryptography system and generates public and private keys for the CS. The TA then generates the system key and other system parameters and publishes the public parameters.

[0112] Step S2: Entity registration:

[0113] Vehicles apply for registration with the TA. The TA generates a pseudonym and public and private keys for each vehicle. The TA and CS store vehicle formation information, including the pilot vehicle and the following vehicles.

[0114] Step S3: Initiate a request:

[0115] The query vehicle plans its route and encodes and encrypts its location using the Hilbert curve. After calculating the index, the query request is sent to the CS to protect privacy and obtain trip-related information.

[0116] Step S4: Query and Verification:

[0117] CS needs to verify the legitimacy and frequency limit of the query request and help the query vehicle generate query credentials to pass to the pilot vehicle, and save the index of the query vehicle in the local database.

[0118] Step S5: respond:

[0119] After receiving the query credential, the pilot vehicle calculates the trapdoor and generates a privacy-preserving response and sends it to the CS.

[0120] Step S6: Matching calculation:

[0121] After receiving the response from the pilot vehicle, the CS performs a matching calculation on the pilot vehicle trap door and the query vehicle index, generates a matching certificate, and forwards the pilot vehicle's response to the query vehicle.

[0122] Step S7: Information acquisition:

[0123] After receiving the response from the pilot vehicle returned by the CS, the query vehicle recovers the place and time information that matches the query location code through calculation.

[0124] Step S8: Join decision:

[0125] The query vehicle adjusts its driving strategy according to the information of the vehicle formation and joins the vehicle formation using the matching certificate.

[0126] Step S1 includes:

[0127] Given a security parameter ,TA initializes the elliptic curve cryptography system (ECC): given a prime number Finite field defined , generating an elliptic curve ,in, and , all points on the elliptic curve and the point at infinity form a prime order q The additive cyclic group of , the generator is 𝑃. Next, TA chooses a random number As the system's master private key, then calculate the corresponding system public key .

[0128] Then, given the security parameters , TA outputs the secret key ,in is a reversible matrix, is a vector, and in addition, TA chooses Independent hash functions .

[0129] Next, TA selects several secure one-way hash functions: , , , ,in Represents a fixed-length string.

[0130] TA sets a maximum number of requests , refers to the number of query requests (e.g., a maximum of 10) that any query vehicle can submit within a certain period of time (e.g., within 10 minutes).

[0131] TA assigns a private key to CS , and calculate the corresponding public key Finally, TA sends the key pair to The key pair is sent to CS, which stores it securely.

[0132] Finally, TA publishes public parameters .

[0133] Step S2 includes:

[0134] (1) Vehicle pseudonym generation and key generation:

[0135] When the vehicle In real identity (i.e. ) When applying for registration with TA, TA selects a random number , and calculate Then, TA uses the hash function Calculate the pseudonym of the vehicle: ,in, It means concatenating two strings. is the pseudonym generation time. In this way, the pseudonym generation depends on the random number of the vehicle. , also combined with the vehicle's real identity At the same time, TA is the vehicle Generate a pair of public and private keys, where the private key is , the public key is Next, TA generates Bloom filter Finally, TA sends Send to vehicle . The vehicle uses a pseudonym Used to protect the vehicle's true identity in subsequent communications while ensuring the anonymity of the communication.

[0136] (2) Vehicle formation setting:

[0137] Since the formation process of vehicle formation and the selection of leading and following vehicles have been fully discussed in previous studies, these contents are not the focus of this paper. In this paper, we consider a typical vehicle formation scenario. Specifically, assume that there is a vehicle formation containing A platoon of vehicles, Indicates the pilot vehicle. represents each following vehicle. Therefore, the formation contains TA and CS store formation information in their respective databases. ,in is the unique identifier of the formation, It is the formation time of the formation.

[0138] Step S3 includes:

[0139] When querying a vehicle and wanting to obtain vehicle formation information, a query request needs to be generated. First, the vehicle plans its route and identifies key locations it will pass through (such as intersections, gas stations, toll booths, etc.). To protect privacy, the querying vehicle encodes these locations using the Hilbert curve encoding method. The Hilbert curve encodes locations by mapping two-dimensional space to one-dimensional space. Form a Hilbert curve encoding set of query positions , where each Represents an encoded query position.

[0140] Encode each query position Encryption, calculation .then, Select random number , and calculate Finally, the encrypted query location set is generated .

[0141] Then, To ensure the frequency limit and privacy protection of query requests, select the current timestamp , and set the request counter Increase by 1. calculate .

[0142] Next, Using a hash function Encode each query position Insert Bloom filter , used to generate the index To encrypt the index , Index Decompose into two vectors and The splitting rule is: for each element in the index ,if , then and All set to Otherwise, Set to , Set to ,in is a random number. Then, using the matrix and Encrypt these two vectors separately to obtain the encrypted index .

[0143] Query vehicle Encrypt the query location collection , hash value and encrypted indexes Use CS's public key Perform asymmetric encryption to obtain encrypted content ,in, represents ElGamal asymmetric encryption. Subsequently, Generate a signature using the signature generation algorithm implemented by the Elliptic Curve Digital Signature Algorithm (ECDSA) .

[0144] Query vehicle The signed query request is sent to CS via RSU. The request content is .

[0145] Step S4 includes:

[0146] When CS receives the query vehicle Query request sent After that, it is necessary to verify the legitimacy and frequency limit of the query request. CS first passes Verify the signature in the query request To ensure that the query request comes from a legitimate query vehicle, Indicates the signature verification algorithm implemented using the ECDSA algorithm. Decryption , Indicates ElGamal asymmetric decryption.

[0147] Then, CS checks The validity of the query and check whether the number of queries in the current time window exceeds the threshold set by the system If the query request exceeds the limit, the query request will be rejected. If the query request passes the above verification, CS will 、 、 and Temporarily stored in the database.

[0148] Next, CS generates a query credential for the query vehicle , for this purpose, CS uses its own private key Sign the key information of the query credential to ensure the integrity and non-forgeability of the query credential. The generated signature is ,in, It is a timestamp.

[0149] Finally, the query credential generated by CS is CS will generate the query certificate Sent to the pilot vehicle via RSU .

[0150] Step S5 includes:

[0151] pilot vehicle Receive query voucher After that, first pass Verify CS's signature If the verification fails, the pilot vehicle rejects the message.

[0152] Next step, pilot vehicle Generate a privacy-preserving response and send it to the CS. The response includes information about the vehicle formation and helps query the vehicle Get the required data.

[0153] first, Get the query vehicle Provided encrypted query location collection , for the sake of privacy protection, Pick a random number , and calculate .

[0154] Then, Form a Hilbert curve encoding set specific to its own route position , where each encoding Uniquely corresponds to a place and time information pair To encrypt this information, calculate and ,in, .

[0155] Next, Using a hash function Encode each route location Insert Bloom filter , used to generate a trapdoor To encrypt the trapdoor The trap door Decompose into two vectors and The splitting rule is: for each element in the trapdoor ,if , then and All set to Otherwise, Set to , Set to ,in is a random number. Then, using the matrix and Encrypt these two vectors separately to obtain the encrypted index .

[0156] pilot vehicle Use CS's public key Perform asymmetric encryption to obtain encrypted content . Then, Generate signature ,in, It is a timestamp.

[0157] pilot vehicle The signed response content is sent to CS via RSU. The response content sent is .

[0158] Step S6 includes:

[0159] When CS receives the pilot vehicle Response sent After that, the legitimacy of the response needs to be verified. CS first passes Verify the signature in the response to ensure the response comes from a legitimate pilot vehicle.

[0160] Subsequently, CS passed Decryption . Then, CS uses and calculate The result of the calculation As a pilot vehicle and query vehicle The route matching value of .

[0161] Next, CS generates a matching certificate for the matching result To do this, CS first uses a pilot vehicle Public key Matching value for matching results CS then uses its own private key to encrypt the Sign and generate a matching certificate ,in, .

[0162] Next, CS forwards the pilot vehicle Response information, generate signature ,in, Is the timestamp. Finally, CS sends Send a message with the content .

[0163] Step S7 includes:

[0164] Query vehicle Received message Afterwards, through Verify CS's signature If the verification fails, the inquiring vehicle rejects the response message.

[0165] After verification, query the vehicle use and To recover the information, first, Calculate query position code ,in, It is a pilot vehicle Encrypted information sent; Is the vehicle query The random number chosen previously; and Is the vehicle query The encrypted position code sent previously. When the pilot vehicle Query position encoding and query vehicle Query position encoding When matching, by calculating , query vehicle You can recover the place and time information that matches the query location code .

[0166] During subsequent driving, query the vehicle You can restore the location and time information Adjust its own driving strategy to plan the subsequent driving route.

[0167] Step S8 includes:

[0168] Query vehicle After completing the information recovery and verifying the legitimacy of the response message, the recovered location and time information will be and matching certificates to join the vehicle formation and adjust its own driving strategy.

[0169] Query vehicle Use matching certificate As proof, the pilot vehicle Send a join message. The join message is ,in, is the timestamp of the request to join, and Is to query the vehicle using your own private key Signing the request content ensures the integrity and non-forgeability of the request.

[0170] pilot vehicle Received joining message After that, first pass Verify the signature , ensuring that the request comes from a legitimate querying vehicle.

[0171] Next, the pilot vehicle pass Verify matching certificates The signature in the certificate ensures that the matching certificate is generated by CS and has not been tampered with. Get the matching value . Pilot vehicle Based on the matching value in the matching certificate , determine the vehicle Whether the matching degree with the vehicle formation meets the joining conditions. If the verification is passed, the pilot vehicle Will accept vehicle inquiries and incorporate it into the vehicle formation.

[0172] like Figure 3 As shown, the privacy-preserving location query system for vehicle formations supporting dynamic joining is used to implement the privacy-preserving location query method for vehicle formations supporting dynamic joining, and includes the following modules:

[0173] System initialization module: The trusted authority TA initializes the elliptic curve cryptography system, generates public and private keys for the cloud server CS, and publishes public parameters;

[0174] Entity registration module: Vehicles apply for registration with the TA, which generates a pseudonym and public and private keys for each vehicle. The TA and CS store vehicle formation information, including the lead vehicle and follower vehicles.

[0175] Query request initiation module: The query vehicle plans its route and encodes and encrypts the location using the Hilbert curve. After calculating the index, the query request is sent to the CS to protect privacy and obtain trip-related information;

[0176] Query Verification Module: The CS verifies the legitimacy and frequency limit of the query request, helps the querying vehicle generate a query credential and passes it to the pilot vehicle, and saves the index of the querying vehicle;

[0177] Response generation module: After receiving the query credential, the pilot vehicle calculates the trapdoor and generates a privacy-preserving response, which is then sent to the CS.

[0178] Matching calculation module: After receiving the response from the pilot vehicle, the CS performs a matching calculation on the pilot vehicle's trap door and the query vehicle's index, generates a matching certificate, and forwards the response to the query vehicle;

[0179] Information recovery module: After receiving the response from the pilot vehicle returned by the CS, the query vehicle recovers the location and time information that matches the query location code through calculation;

[0180] Joining decision module: The query vehicle adjusts its driving strategy according to the information of the vehicle formation and joins the vehicle formation using the matching certificate.

[0181] The present invention encompasses any alternatives, modifications, equivalents, and solutions that fall within the spirit and scope of the present invention. To provide a thorough understanding of the present invention, specific details are described in detail below in connection with the preferred embodiments of the present invention, but those skilled in the art will be able to fully understand the present invention without these detailed descriptions. Furthermore, to avoid unnecessary confusion regarding the essence of the present invention, well-known methods, processes, procedures, components, and circuits have not been described in detail.

[0182] The above is only a preferred embodiment of the present invention. It should be pointed out that for ordinary technicians in this technical field, several improvements and modifications can be made without departing from the principles of the present invention. These improvements and modifications should also be regarded as within the scope of protection of the present invention.

Claims

1. A privacy-preserving location query method for vehicle formations supporting dynamic joining, characterized in that: The following steps are involved: S1, system initialization: The trusted authority TA initializes the elliptic curve cryptosystem, generates public and private keys for the cloud server CS, and publishes public parameters; S2, Entity Registration: Vehicles apply for registration with the TA, which generates a pseudonym and public and private keys for each vehicle. The TA and CS store vehicle formation information, including the lead vehicle and follower vehicles; S3, initiates the request: plans the vehicle's route and uses the Hilbert curve to encode and encrypt the location. After calculating the index, the query request is sent to the CS to protect privacy and obtain trip-related information; S4, query verification: CS verifies the legitimacy and frequency limit of the query request and helps the query vehicle generate a query credential to pass to the pilot vehicle, and saves the query vehicle's index in the local database; S5, respond: After receiving the query credential, the pilot vehicle calculates the trapdoor and generates a privacy-preserving response and sends it to the CS; S6, Matching Calculation: After receiving the response from the pilot vehicle, the CS performs a matching calculation on the pilot vehicle trap door and the query vehicle index, generates a matching certificate, and forwards the pilot vehicle's response to the query vehicle; S7, information acquisition: After receiving the response from the pilot vehicle returned by the CS, the query vehicle recovers the location and time information that matches the query location code through calculation; S8, joining decision: The query vehicle adjusts its driving strategy according to the information of the vehicle formation and joins the vehicle formation using the matching certificate.

2. The privacy-preserving location query method for vehicle formations supporting dynamic joining according to claim 1 is characterized in that: The system initialization in S1 includes: S11, Elliptic Curve Cryptography System Initialization: Given Security Parameters , TA initializes the elliptic curve cryptosystem, given by prime numbers Finite field defined , generating an elliptic curve ,in, and , all points on the elliptic curve and the point at infinity form a prime order q The additive cyclic group of , the generator is 𝑃, TA selects a random number As the system's master private key, and calculate the corresponding system public key ; S12, generate system keys and parameters: given security parameters , TA outputs the secret key ,in, is a reversible matrix, is a vector, TA chooses Independent hash functions ; S13, select a secure one-way hash function: TA selects a one-way hash function, including 、 、 、 ,in Represents a fixed-length string; S14, set query request frequency limit: TA sets the maximum number of requests , represents the number of query requests submitted by any query vehicle within the predetermined time; S15, cloud server distributes keys and storage: TA distributes private keys to CS ,and , and calculate the corresponding public key , TA sends the key pair to Send it to CS, which stores the key pair securely. S16, publish public parameters: TA publishes public parameters , expressed as: 。 3. The privacy-preserving location query method for vehicle formations supporting dynamic joining according to claim 2 is characterized in that: The entity registration in S2 includes: S21, Vehicle pseudonym generation and key generation: When a vehicle is registered, the TA generates a unique pseudonym and public and private keys for each vehicle and sends them to the vehicle via a secure channel. Specifically, the following steps are performed: S211, Vehicle Registration Application: When the vehicle With real identity When applying for registration with TA, TA selects a random number , and calculate ; S212, Pseudonym Generation: TA uses a hash function Calculate the pseudonym of the vehicle, expressed as: ； in, represents exclusive OR, It means concatenating two strings. is the pseudonym generation time; S213, key pair generation: TA is the vehicle Generate a pair of public and private keys, where the private key is , the public key is ; S214, Bloom filter generation: TA is the vehicle generate Bloom filter ; S215, key and pseudonym are sent: TA sends Send to vehicle ; S22, vehicle formation setting: TA and CS store vehicle formation information based on the formation's unique identifier and formation formation time, specifically including: S221, formation scene setting: Assume there is a A platoon of vehicles, consisting of Following vehicles; S221, formation information storage: TA and CS store formation information in their respective databases, expressed as: ； in, is the unique identifier of the formation, is the formation time, Indicates the pilot vehicle. Represents each following vehicle.

4. The privacy-preserving location query method for vehicle formations supporting dynamic joining according to claim 3 is characterized in that: The initiation request in S3 includes: S31, planning driving routes and identifying key locations: when querying a vehicle to obtain vehicle formation information, a query request is generated. Query vehicle The driving route and identification of the query vehicle Key locations you will pass through, including intersections, gas stations, and toll booths; S32, using Hilbert curve encoding location: the query vehicle uses the Hilbert curve encoding method to encode key locations to form a Hilbert curve encoding set of the query location ; S33, encrypted query position code: Encrypt each query position code and calculate the encrypted value , Select random number , and calculate , and finally generate the encrypted query location set ; S34, request frequency limitation and privacy protection: Select the current timestamp , and set the request counter Add 1 and calculate , Using a hash function Encode each query position Insert Bloom filter , generate index ; S35, encrypted query location index: Index Decompose into vectors and , and use the matrix and For vector and Encrypt and get the encrypted index ; S36, Asymmetric Encryption and Signature Generation: Querying Vehicles Encrypt the query location collection , hash value and encrypted indexes Use CS's public key Perform asymmetric encryption to obtain encrypted content ,in, Represents ElGamal asymmetric encryption and uses the signature generation algorithm implemented by the elliptic curve digital signature algorithm ECDSA to generate a signature ; S37, send query request: query vehicle The signed query request is sent to CS via RSU. The request content is .

5. The privacy-preserving location query method for vehicle formations supporting dynamic joining according to claim 4 is characterized in that: The query verification in S4 includes: S41, signature verification: When CS receives the query vehicle Query request sent Finally, verify the legitimacy and frequency limit of the query request; S42, ElGamal decryption: CS passed Verify the signature in the query request ,in, Indicates the signature verification algorithm implemented using the ECDSA algorithm, and passes Decryption ,in, Indicates ElGamal asymmetric decryption; S43, query request validity check: CS check The validity of the query and check whether the number of queries in the current time window exceeds the threshold set by the system ,If the number of queries exceeds the limit, the query request will be rejected; S44, Data storage: If the query request passes the validity check, CS will 、 、 and Temporarily save to the database; S45, query certificate signature generation: CS uses private key Sign the query credential. The generated signature is expressed as: ； in, is the timestamp; S46, query credential sent: the query credential generated by CS is CS will generate the query certificate Sent to the pilot vehicle via RSU .

6. The privacy-preserving location query method for vehicle formations supporting dynamic joining according to claim 5 is characterized in that: The response in S5 includes: S51, Signature Verification: Pilot Vehicle Receive query voucher Afterwards, through Verify CS's signature If the verification fails, the pilot vehicle will refuse to query the credentials. ; S52, generate a privacy protection response: pilot vehicle Generate a privacy-preserving response and send it to the CS, including information about the vehicle formation; S53, encrypted query location set processing: Get the query vehicle Provided encrypted query location collection , Select random number , and calculate ; S54, Hilbert curve coding set generation: Forming a Hilbert curve encoding set , each code Uniquely corresponds to a place and time information pair, expressed as: ； S55, Information Encryption: Pilot Vehicle calculate and ,in, ; S56, Bloom filter and trapdoor generation: Using a hash function Encode each route location Insert Bloom filter , generating a trapdoor , The trap door Decompose into vectors and , and use the matrix and For vector and Encrypt and get the encrypted index ; S57, Asymmetric Encryption and Signature Generation: Pilot Vehicle Use CS's public key Perform asymmetric encryption to obtain encrypted content , and generate a signature ,in, is the timestamp; S58, response sent: pilot vehicle The signed response content is sent to CS via RSU. The response content sent is .

7. The privacy-preserving location query method for vehicle formations supporting dynamic joining according to claim 6, characterized in that: The matching calculation in S6 includes: S61, Signature Verification: When CS receives the pilot vehicle Response sent After that, CS passed Verify the signature in the response ; S62, Decryption and Calculation: CS passed Decryption , CS uses and calculate , and based on As a pilot vehicle and query vehicle Route matching value, calculation ; S63, matching certificate generation: CS uses pilot vehicle Public key Matching value for matching results Encrypt and use the private key Sign and generate a matching certificate , expressed as: ； S64, Generate Signature and Forward Response: Generate Signature ,in, It is the timestamp, CS sends it to RSU through Send a message with the content .

8. The privacy-preserving location query method for vehicle formations supporting dynamic joining according to claim 7, characterized in that: The information acquisition in S7 includes: S71, Signature Verification: Query Vehicle Received message Afterwards, through Verify CS's signature If verification fails, query the vehicle rejection message ; S72, information recovery: after verification, query the vehicle use and Recover information, including: S721, calculate the query position code: Calculate the query position encoding, expressed as: ； in, It is a pilot vehicle Encrypted information sent, Is the vehicle query The random number selected, Is the vehicle query The encrypted position code sent; S722, restore location and time information: When the pilot vehicle Query position encoding and query vehicle Query position encoding When matching, by calculating , query vehicle Recover the location and time information that matches the query location code ; S73, Adjust driving strategy: Query vehicle According to the restored location and time information Adjust your driving strategy to plan your route.

9. The privacy-preserving location query method for vehicle formations supporting dynamic joining according to claim 8, characterized in that: The joining decision in S8 includes: S81, send a join request: query vehicle Use matching certificate As proof, the pilot vehicle Send a join message. The join message is ,in, is the timestamp of the request to join, Is to query the vehicle using your own private key Signature of the request content; S82, Verify signature: Pilot vehicle Received joining message Afterwards, through Verify the signature ; S83, Verify matching certificate: Pilot vehicle pass Verify matching certificates The signature in Get the matching value ; S84, Matching Degree Judgment: Pilot Vehicle Based on the matching value in the matching certificate , determine the vehicle Determine the matching degree with the vehicle formation; S85, accept to join: if the verification is passed, the pilot vehicle Will accept vehicle inquiries Join and query the vehicle Incorporate into vehicle formation.

10. A privacy-preserving location query system for a vehicle formation supporting dynamic joining, for implementing a privacy-preserving location query method for a vehicle formation supporting dynamic joining as claimed in any one of claims 1 to 9, characterized in that: Includes the following modules: System initialization module: The trusted authority TA initializes the elliptic curve cryptography system, generates public and private keys for the cloud server CS, and publishes public parameters; Entity registration module: Vehicles apply for registration with the TA, which generates a pseudonym and public and private keys for each vehicle. The TA and CS store vehicle formation information, including the lead vehicle and follower vehicles. Query request initiation module: This module plans the vehicle's route and uses the Hilbert curve to encode and encrypt the location. After calculating the index, it sends the query request to the CS to protect privacy and obtain trip-related information. Query Verification Module: The CS verifies the legitimacy and frequency limit of the query request, helps the querying vehicle generate a query credential and passes it to the pilot vehicle, and saves the index of the querying vehicle; Response generation module: After receiving the query credential, the pilot vehicle calculates the trapdoor and generates a privacy-preserving response, which is then sent to the CS. Matching calculation module: After receiving the response from the pilot vehicle, the CS performs a matching calculation on the pilot vehicle's trap door and the query vehicle's index, generates a matching certificate, and forwards the response to the query vehicle; Information recovery module: After receiving the response from the pilot vehicle returned by the CS, the query vehicle recovers the location and time information that matches the query location code through calculation; Joining decision module: The query vehicle adjusts its driving strategy according to the information of the vehicle formation and joins the vehicle formation using the matching certificate.

Images