Vehicle-mounted crowd sensing data encryption transmission method and system

Abstract

The invention belongs to the technical field of data transmission of a vehicle-mounted crowd sensing system, and discloses a vehicle-mounted crowd sensing data encryption transmission method and system. A secret key exchange protocol based on an SM2 digital signature is adopted to ensure the security of data transmission, including correctness of a signature and a session secret key; and a pseudonym is generated in a data processing process to realize anonymity and traceability of the user. According to the invention, the problems of user identity privacy and user data security in the vehicle-mounted crowd sensing system are solved. User privacy protection is enhanced: by generating a pseudonym for each vehicle user, the privacy of the user is protected, and meanwhile, the capability of tracing the real identity of the user when necessary is reserved. Due to the design of the edge nodes, the system can flexibly process tasks of different scales, screening can be carried out according to the credits of the vehicle users, and the task execution efficiency and quality are improved.

Description

Technical Field

[0001] The present invention belongs to the technical field of data transmission, and in particular, relates to a data transmission method and system for a vehicle-mounted group intelligence perception system. Background Art

[0002] The remarkable progress of the Internet of Things (IoT) and vehicle technology have jointly promoted the vigorous development of intelligent connected vehicles (ICVs). With their rich sensors and advanced wireless communication equipment, ICVs not only support mobile crowdsourced sensing (MCS) applications, but also give rise to an innovative perception model, vehicle crowdsourced sensing (VCS). By entrusting perception tasks to ICVs with high mobility and powerful perception capabilities, VCS significantly reduces the cost of data collection, including financial and time costs, while providing a better quality of service than traditional MCS. This progress has led to the emergence of a series of VCS applications, such as smart parking, traffic monitoring, accident information collection, map updates, smart navigation and road monitoring, which are accelerating the construction of smart cities.

[0003] The typical in-vehicle crowd perception system architecture consists of three core components: participants (i.e., vehicles that provide perception data), perception platforms (composed of multiple servers located in data centers), and requesters (entities that send requests to the perception platform to obtain the required perception data). These three work together to support the core operating framework of the in-vehicle crowd perception system.

[0004] With the close collaboration between entities, the perception task can be completed efficiently through a series of operations such as the collection, uploading, processing and storage of perception data. However, in this process, user privacy and data transmission security have become key issues that need urgent attention. On the one hand, improper data processing or transmission methods may leak the user's identity and privacy information, causing user concerns, which in turn affects their enthusiasm for participating in perception tasks, and ultimately may lead to a decrease in data quality and quantity. On the other hand, security vulnerabilities in the data transmission process may also be exploited by malicious users to upload false data or tamper with real data, which will seriously affect the accuracy and reliability of the perception task.

[0005] In recent years, some solutions have been proposed to address the issues of user privacy and data transmission security. For example, although the GoSense system proposed by TY et al. focuses on the optimization of vehicle recruitment and task allocation, in practical applications, it is still necessary to consider how to strengthen the security protection of user privacy and data transmission while ensuring task efficiency. F. Li et al. tried to motivate users to improve data accuracy by linking task rewards with data quality, but this solution also needs to be built on a solid foundation of privacy protection and data transmission security to ensure user participation and data authenticity. In addition, although the malicious user detection solution designed by Wang et al. introduced blockchain technology to enhance privacy protection, how to balance data transparency and user privacy protection needs in the process of ensuring data quality is still a major challenge currently faced.

[0006] Through the above analysis, the problems and defects of the prior art are as follows:

[0007] (1) Inadequate protection of user privacy and security: In the process of collecting, uploading, processing and storing perception data, improper data processing or transmission methods may leak the user's identity and privacy information. This not only causes users' concerns, but also may reduce their enthusiasm for participating in perception tasks, thus affecting the quality and quantity of data.

[0008] (2) Data transmission security loopholes: Security loopholes in the data transmission process may be exploited by malicious users, resulting in the uploading of false data or the tampering of real data. This not only seriously affects the accuracy and reliability of the perception task, but may also have a negative impact on the construction and operation of smart cities. The existing data transmission security mechanism is unable to cope with complex and changing network attacks, and more advanced and effective technical means are needed to ensure the security of data transmission. Summary of the invention

[0009] In view of the problems existing in the prior art, the present invention provides a data transmission method and system for a vehicle-mounted crowd intelligence perception system to solve the data transmission problem of the vehicle-mounted crowd intelligence perception system.

[0010] The present invention is implemented as follows: a data transmission method for a vehicle-mounted crowd intelligence perception system, wherein a key exchange protocol based on SM2 digital signature is adopted to ensure the security of data transmission, including the correctness of signatures and session keys; a pseudonym is generated during data processing to achieve user anonymity and traceability. The system includes: a perception platform, an edge node, and a vehicle user.

[0011] The sensing platform (SP) has sufficient storage and computing resources to support crowdsourcing services. It is mainly responsible for receiving tasks from data demanders and distributing them to edge nodes located in the sensing area. After collecting the task reports of vehicle users, the vehicle users who complete the tasks will be rewarded and their credit will be improved. At the same time, it is also responsible for the registration and management of vehicles. In order to protect the privacy of vehicle users, SP will generate a pseudo identity for each vehicle user. When it is necessary to track illegal vehicles, SP can reveal or disclose the real identity of the vehicle.

[0012] After receiving the task assigned by the perception platform, the edge node (EN) distributes the task to nearby vehicle users. At the same time, it predicts the credit of the vehicle users and selects the vehicle users who meet the requirements of the perception task.

[0013] The vehicle user (Smart Vehicular User, V), modern vehicles are equipped with powerful computing, communication and storage capabilities, and are highly mobile. Vehicle users need to ensure that their devices have sufficient performance to support various functions. They participate in perception tasks to collect data, sign it, and finally share the data through edge nodes to obtain credit or rewards.

[0014] Furthermore, the implementation steps of the method are:

[0015] Step 1: System settings, used to disclose the system parameter list;

[0016] Step 2: User registration, which is used for the in-vehicle user to register their identity. The sensing platform generates a pseudonym for them to protect the user's identity privacy and to trace the real identity of the illegal vehicle.

[0017] Step 3: Task distribution, where the sensing platform sends the sensing task to the edge node. Once the task instruction is received, the edge node forwards it to the neighboring vehicle user group.

[0018] Step 4: Task reception, in which vehicle users who are interested in participating in the task will actively respond to the call of the edge node and upload their user data to the edge node. These users then start the crowd sensing activity and transmit the collected data results back to the edge node;

[0019] Step 5: Data transmission, which is used by the edge node to further aggregate the digital signatures of the users who have completed the task, generate an aggregate signature, and interact securely with the perception platform to negotiate and establish a session key. With this session key, the edge node encrypts the perception data and securely transmits it to the perception platform;

[0020] Step six, task review, is used to verify the user's signature after the perception platform task receives the result information, and give corresponding rewards to the vehicle user who successfully submits valid data.

[0021] Further, the step 1 comprises:

[0022] Input security parameter λ, randomly select a large prime number q, and determine the non-singular elliptic curve E:y 2 =x 3 +ax+b(mod q)(where, ), select a prime n-order cyclic group from all points of E (including the point at infinity) And the generator Choosing a secure hash function Key derivation function KDF and decompression function uncompress. Public system parameter list

[0023] Further, the step 2 includes:

[0024] During the user registration phase, the specific process between user V and the perception platform SP is as follows:

[0025]

[0026] The user first randomly selects Then calculate P = d·G. Let the user's private key be sk v =d, the user's public key is pk v =P. Use the public key pk of the perception platform SP Encrypt the information M, H(M), and pk submitted during registration v and random number a, and send the encrypted result to SP, where M = (ID v ||m * ), ID v is the real identity of the user, m * For the user's personal information data, H(M) ensures the integrity of the user's registration information.

[0027] SP → V: E a [ID v ']

[0028] After receiving the encrypted information, SP uses its private key sk SP Decrypt and get M, H(M), pk v and random number a, and verify the integrity of M through H(M). After verification, SP generates a pseudonymous ID for the user v ', calculate ID v '=H(ID v), and encrypt it with a and send it to the user. After receiving it, the user decrypts it with a to get the ID v ', and subsequently use the pseudonym for communication. When tracing the user of the responsibility issue, the SP presents or exposes the user's real identity.

[0029] Further, the step three includes:

[0030] The task distribution link is a key step in the interaction between the perception platform SP, the edge node EN and the user V. The specific process is as follows:

[0031] σ Task =Sign(sk SP ,Task)

[0032] SP first creates task information Task = (work||re||cr th ||T1), where work is the task details, re is the reward for completing the task, cr is the reward for completing the task, th is the credit threshold required by the task for the user's credit, and T1 is the current timestamp. Then, SP calculates H(Task) and uses its private key sk SP Sign the task and generate σ Task .

[0033] Verify(pk SP ,σ Task )

[0034] SP distributes the task information with signature to nearby ENs. After receiving the information, EN calculates H(Task) to verify the integrity of the task information and uses pk SP Verify the signature to ensure the authenticity of the task information. If the verification is successful, EN will forward the task information to the surrounding users; otherwise, EN will discard the task information to prevent the spread of errors. After receiving the task information, the user will also verify the integrity and authenticity. After the verification is passed, the user decides whether to participate in the task based on the requirements of the task and his own conditions.

[0035] Further, the step 4 includes:

[0036] Task reception is the initial stage of user participation in the perception task. The specific process is as follows:

[0037]

[0038] According to the task requirements, it is assumed that a user who is willing to participate is the γth user (1≤γ≤n), and the task information is verified as EN to ensure the integrity and authenticity of the task information. If the verification is passed, the user randomly selects a random number. And calculate K γ=k γ G=(x γ ,y γ ), e γ =H(w γ ),r γ =(e γ +x γ )(mod n).w γ is the request information of the γth user participating in the perception task, that is, in is the pseudonym of the γth user, is the personal information data of the γth user, T2 is the current timestamp, and b is a random number. γ =0 or r γ +k γ =0, then reselect k γ Calculate again; otherwise calculate s γ =(1+d γ ) -1 (k γ -r γ d γ )(mod n). If s γ = 0, then return to reselect the random number, otherwise generate the signature σ γ =(r γ ,s γ )=Sign(d γ ,w γ ). The user then uses pk EN Encryption γ and w γ , and send the encrypted result to EN.

[0039] After receiving the encrypted information, EN uses its private key to decrypt it and obtains σ γ and w γ First, determine whether the time interval ΔT = T2-T1 is within the threshold range. If it exceeds the threshold, the data is discarded. If it is within the threshold, EN check Is it true? If not, the verification fails; otherwise, calculate e' γ =H(w' γ ) to test w' γ The integrity of γ ≠0, then further calculate t γ =(r′ γ +s' γ )(mod n), K′ γ =s' γ G+t γ P γ =(x' γ ,y' γ), r′ γ =(e' γ +x' γ )(mod n). Finally, check r′ γ =r γ Is it true? If true, then confirm the signature σ γ efficient.

[0040] Further, the step five includes:

[0041] T E Stores EN's transaction perception data, T s The task reward re of SP is stored. EN uses the private key to calculate the random number k in the signature E =(s E (1+d E )+r E d E )(mod n), calculate x s =(r s -H(T s ))(mod n), transaction public key Shared Secrets Calculate and output the session key SK E =KDF(x ES ).

[0042] SP uses the private key to calculate the random number k in the signature S =(s S (1+d S )+r S d S )(mod n), calculate x E =(r E -H(T E ))(mod n), transaction public key Calculate the common secret Calculate and output the session key SK S =KDF(x ES ). EN sends the sensing task data, user pseudonym group and signature group collected from the user to SP through the session key.

[0043] Further, the step six includes:

[0044] SP uses the session key to decrypt and obtain the task result information. First, it determines whether the time interval ΔT = T3-T1 is within the threshold range. If it is not within the threshold range, the data is discarded. Otherwise, If the information is verified to be true, batch verification of n user signatures (σ1,σ2,...,σ η ) validity. SP test Is it true? If not, the verification fails. Otherwise, for i=1,2,...,η, calculate in sequence: Test t γ ≠0 if not true, if true, calculate e' γ =H(w γ ) γ The completeness of the calculation test Is it true? If so, sign it. is a valid signature. SP gives a certain amount of reward re to all users in the group and increases their credibility.

[0045] Another object of the present invention is to provide a vehicle-mounted crowd intelligence perception data encryption transmission system, comprising:

[0046] System settings module: used to disclose the system parameter list;

[0047] User registration module: used for in-vehicle users to register their identities. The sensing platform generates pseudonyms for them to protect user privacy and to track down the real identities of illegal vehicles.

[0048] Task distribution module: used by the perception platform to send perception tasks to edge nodes. Once the task instruction is received, the edge node will forward it to the neighboring vehicle user group;

[0049] Task receiving module: Vehicle users who are interested in participating in the task will actively respond to the call of the edge node and upload their user data to the edge node. These users then start the crowd sensing activity and transmit the collected data results back to the edge node;

[0050] Data transmission module: used by edge nodes to further aggregate the digital signatures of users who have completed the task, generate aggregate signatures, and interact securely with the perception platform to negotiate and establish session keys. With this session key, the edge node encrypts the perception data and securely transmits it to the perception platform;

[0051] The task review module is used to verify the user's signature after receiving the result information of the sensing platform task, and give corresponding rewards to the vehicle user who successfully submits valid data.

[0052] The problems existing in the prior art solved by the present invention are:

[0053] Insufficient user privacy and security protection: In the process of collecting, uploading, processing and storing perception data, improper data processing or transmission methods may leak the user's identity and privacy information. This not only causes users' concerns, but also may reduce their enthusiasm for participating in perception tasks, thus affecting the quality and quantity of data.

[0054] There are loopholes in data transmission security: Security loopholes in the data transmission process may be exploited by malicious users, resulting in the uploading of false data or the tampering of real data. This not only seriously affects the accuracy and reliability of perception tasks, but may also have a negative impact on the construction and operation of smart cities. The existing data transmission security mechanism is unable to cope with complex and changing network attacks, and more advanced and effective technical means are needed to ensure the security of data transmission.

[0055] In combination with the above technical solutions and the technical problems solved, the advantages and positive effects of the technical solutions to be protected by the present invention are as follows:

[0056] First, the present invention addresses the problems existing in the prior art, such as insufficient protection of user privacy and security, and loopholes in data transmission security, and proposes a method and system for encrypted transmission of in-vehicle crowd-sensing data. The significant technical advancement of the present invention is that by adopting a key exchange protocol based on SM2 digital signatures, the security of data transmission is enhanced, ensuring the confidentiality and integrity of data during transmission. At the same time, by generating pseudonyms to achieve user anonymity, the user's privacy is protected, and the user's true identity can be traced back when necessary, effectively balancing privacy protection and regulatory requirements.

[0057] Second, from the product perspective, the technical solution to be protected by the present invention has the following technical effects and advantages:

[0058] (1) Improved data transmission security: By using SM2 digital signatures, the security of data during transmission is ensured, preventing data from being tampered with or stolen.

[0059] (2) Enhanced user privacy protection: By generating a pseudonym for each vehicle user, the user's privacy is protected while retaining the ability to trace the user's true identity when necessary.

[0060] (3) Improved scalability and flexibility of the system: The design of edge nodes enables the system to flexibly handle tasks of different sizes and can screen vehicle users based on their creditworthiness, thereby improving the efficiency and quality of task execution.

[0061] (4) Promoted the participation of vehicle users: Through the reward mechanism, vehicle users are encouraged to actively participate in data collection and sharing, which improves the activity of the crowd sensing system and the richness of data.

[0062] Third, (1) Expected benefits and commercial value: The implementation of the present invention can provide a more secure and reliable data transmission platform for the vehicle-mounted crowd intelligence perception system, attract more vehicle users to participate, and thus provide data demanders with richer and higher-quality data services, thereby creating commercial value.

[0063] (2) Filling the technical gap: The present invention fills the gap in the existing technology in terms of data transmission security and user privacy protection of the vehicle-mounted crowd intelligence perception system through innovative data transmission methods and system designs.

[0064] (3) Overcoming technical bias: The present invention overcomes the bias of traditional technologies in dealing with user privacy and data security by adopting advanced encryption technology and user identity management mechanism, and provides a more fair and just data transmission environment.

[0065] Fourth, in the field of data transmission technology, traditional methods often cannot effectively balance data security and user privacy protection needs. The present invention not only improves the security of data transmission through innovative technical solutions, but also effectively protects user privacy, providing new possibilities for the development of vehicle-mounted crowd intelligence perception systems. In addition, the present invention also improves the participation of vehicle users and the overall efficiency of the system through reward mechanisms and credit management, providing strong technical support for the application and development of vehicle-mounted crowd intelligence perception systems.

[0066] In order to solve the above problems, the present invention proposes a method for encrypted transmission of vehicle-mounted crowd intelligence perception data. The method adopts a key exchange protocol based on SM2 digital signature to ensure the security of data transmission, including the correctness of signatures and session keys; pseudonyms are generated during data processing to achieve user anonymity and traceability. The present invention solves the problems of user identity privacy and user data security in the vehicle-mounted crowd intelligence perception system.

[0067] The implementation of the method includes steps such as system setting, user registration, key generation, task distribution and credit prediction. First, a parameter list for the public system is used. Then, the on-board user registers his identity, and the perception platform generates a pseudonym for him to protect the user's identity privacy and trace the real identity of the illegal vehicle. The perception platform sends the perception task to the edge node. Once the task instruction is received, the edge node forwards it to the neighboring vehicle user group. Vehicle users who are interested in participating in the task will actively respond to the call of the edge node and upload their user data to the edge node. These users then start the crowd sensing activity and transmit the collected data results back to the edge node. The edge node further aggregates the digital signatures of the users who complete the task, generates an aggregate signature, and interacts securely with the perception platform to negotiate and establish a session key. With this session key, the edge node encrypts the perception data and transmits it securely to the perception platform. Finally, after receiving the result information, the perception platform task verifies the user signature and gives corresponding rewards to the vehicle users who successfully submit valid data. BRIEF DESCRIPTION OF THE DRAWINGS

[0068] Figure 1 This is a flow chart of a method for encrypting and transmitting vehicle-mounted crowd intelligence perception data provided by an embodiment of the present invention;

[0069] Figure 2 is a schematic diagram of a typical vehicle-mounted group intelligence perception system provided by an embodiment of the present invention;

[0070] Figure 3 This is a running time comparison diagram provided by an embodiment of the present invention.

[0071] Figure 4 It is a structural block diagram of the vehicle-mounted crowd intelligence perception data encryption transmission system provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0072] In order to make the purpose, technical solution and advantages of the present invention more clearly understood, the present invention is further described in detail below in conjunction with the embodiments. It should be understood that the specific embodiments described herein are only used to explain the present invention and are not used to limit the present invention.

[0073] like Figure 1 As shown, a method for encrypting and transmitting vehicle-mounted crowd intelligence perception data provided by an embodiment of the present invention includes the following steps:

[0074] S101, system settings, for publishing the parameter list of the system;

[0075] S102, user registration, is used for the in-vehicle user to register his / her identity. The sensing platform generates a pseudonym for the user to protect the user's identity privacy and to trace the real identity of the illegal vehicle;

[0076] S103, task distribution, is used for the perception platform to send a perception task to the edge node. Once the task instruction is received, the edge node immediately forwards it to the neighboring vehicle user group;

[0077] S104, task reception, vehicle users who are interested in participating in the task will actively respond to the call of the edge node and upload their user data to the edge node. These users then start the crowd sensing activity and transmit the collected data results back to the edge node;

[0078] S105, data transmission, is used for the edge node to further aggregate the digital signatures of the users who have completed the task, generate an aggregate signature, and interact securely with the perception platform to negotiate and establish a session key. With this session key, the edge node encrypts the perception data and securely transmits it to the perception platform;

[0079] S106, task review, is used to verify the user's signature after the sensing platform task receives the result information, and give corresponding rewards to the vehicle user who successfully submits valid data.

[0080] like Figure 2 As shown, a method for encrypting and transmitting vehicle-mounted crowd intelligence perception data provided by an embodiment of the present invention includes the following steps:

[0081] (1) In the perception platform (SP), the session key is generated and distributed based on the key exchange protocol of SM2 digital signature to ensure the security of data during transmission. The session key contains signature and encryption verification functions to ensure the integrity and correctness of the data.

[0082] (2) In the perception platform, a pseudo identity is generated for each vehicle user to achieve user anonymity, while retaining the real identity information to achieve traceability, and revealing or disclosing the real identity of the vehicle when necessary to track the illegal vehicle;

[0083] (3) The edge node (EN) receives the sensing tasks from the sensing platform, screens them based on the credit prediction of the vehicle users, and distributes the tasks to the vehicle users who meet the requirements;

[0084] (4) The vehicle user (V) receives the task request from the edge node, collects and processes the data, encrypts the data by generating a digital signature, and transmits the encrypted data to the edge node. The vehicle user obtains corresponding credits and rewards by completing the sensing task;

[0085] (5) After collecting the task data uploaded by the vehicle user, the perception platform decrypts and verifies the integrity and authenticity of the data, rewards the vehicle user who completes the task and improves his credit.

[0086] S101 provided in the embodiment of the present invention includes:

[0087] Input security parameter λ, randomly select a large prime number q, and determine the non-singular elliptic curve E:y 2 =x 3 +ax+b(mod q)(where, ), select a prime n-order cyclic group from all points of E (including the point at infinity) And generators Choosing a secure hash function Key derivation function KDF and decompression function uncompress. Public system parameter list

[0088] S102 provided in the embodiment of the present invention includes:

[0089] During the user registration phase, the specific process between user V and the perception platform SP is as follows:

[0090]

[0091] The user first randomly selects Then calculate P = d·G. Let the user's private key be sk v =d, the user's public key is pk v=P. Use the public key pk of the perception platform SP Encrypt the information M, H(M), and pk submitted during registration v and random number a, and send the encrypted result to SP, where M = (ID v ||m * ), ID v is the real identity of the user, m * For the user's personal information data, H(M) ensures the integrity of the user's registration information.

[0092] SP → V: E a [ID v ']

[0093] After receiving the encrypted information, SP uses its private key sk SP Decrypt and get M, H(M), pk v and random number a, and verify the integrity of M through H(M). After verification, SP generates a pseudonymous ID for the user v ', calculate ID v '=H(ID v ), and encrypt it with a and send it to the user. After receiving it, the user decrypts it with a to get the ID v ', and subsequently use the pseudonym for communication. When tracing the user of the responsibility issue, the SP presents or exposes the user's real identity.

[0094] S103 provided in the embodiment of the present invention includes:

[0095] The task distribution link is a key step in the interaction between the perception platform SP, the edge node EN and the user V. The specific process is as follows:

[0096] σ Task =Sign(sk SP ,Task)

[0097] SP first creates task information Task = (work||re||cr th ||T1), where work is the task details, re is the reward for completing the task, cr is the reward for completing the task, th is the credit threshold required by the task for the user's credit, and T1 is the current timestamp. Then, SP calculates H(Task) and uses its private key sk SP Sign the task and generate σ Task .

[0098] Verify(pk SP ,σ Task )

[0099] SP distributes the task information with signature to nearby ENs. After receiving the information, EN calculates H(Task) to verify the integrity of the task information and uses pk SP Verify the signature to ensure the authenticity of the task information. If the verification is successful, EN will forward the task information to the surrounding users; otherwise, EN will discard the task information to prevent the spread of errors. After receiving the task information, the user will also verify the integrity and authenticity. After the verification is passed, the user decides whether to participate in the task based on the requirements of the task and his own conditions.

[0100] S104 provided in the embodiment of the present invention includes:

[0101] Task reception is the initial stage of user participation in the perception task. The specific process is as follows:

[0102]

[0103] According to the task requirements, it is assumed that a user who is willing to participate is the γth user (1≤γ≤n), and the task information is verified as EN to ensure the integrity and authenticity of the task information. If the verification is passed, the user randomly selects a random number. And calculate K γ =k γ G=(x γ ,y γ ), e γ =H(w γ ),r γ =(e γ +x γ )(mod n).w γ is the request information of the γth user participating in the perception task, that is, in is the pseudonym of the γth user, is the personal information data of the γth user, T2 is the current timestamp, and b is a random number. γ =0 or r γ +k γ =0, then reselect k γ Calculate again; otherwise calculate s γ =(1+d γ ) -1 (k γ -r γ d γ )(mod n). If s γ = 0, then return to reselect the random number, otherwise generate the signature σ γ =(r γ ,s γ )=Sign(d γ ,w γ). The user then uses pk EN Encryption γ and w γ , and send the encrypted result to EN.

[0104] After receiving the encrypted information, EN uses its private key to decrypt it and obtains σ γ and w γ First, determine whether the time interval ΔT = T2-T1 is within the threshold range. If it exceeds the threshold, the data is discarded. If it is within the threshold, EN check Is it true? If not, the verification fails; otherwise, calculate e' γ =H(w' γ ) to test w' γ The integrity of γ ≠0, then further calculate t γ =(r′ γ +s' γ )(mod n), K′ γ =s' γ G+t γ P γ =(x' γ ,y' γ ), r′ γ =(e' γ +x' γ )(mod n). Finally, check r′ γ =r γ Is it true? If true, then confirm the signature σ γ efficient.

[0105] S105 provided in the embodiment of the present invention includes:

[0106] T E Stores EN's transaction perception data, T s The task reward re of SP is stored. EN uses the private key to calculate the random number k in the signature E =(s E (1+d E )+r E d E )(mod n), calculate x s =(r s -H(T s ))(mod n), transaction public key Shared Secrets Calculate and output the session key SK E =KDF(x ES ).

[0107] SP uses the private key to calculate the random number k in the signature S =(sS (1+d S )+r S d S )(mod n), calculate x E =(r E -H(T E ))(mod n), transaction public key Calculate the common secret Calculate and output the session key SK S =KDF(x ES ). EN sends the sensing task data, user pseudonym group and signature group collected from the user to SP through the session key.

[0108] S106 provided in the embodiment of the present invention includes:

[0109] SP uses the session key to decrypt and obtain the task result information. First, it determines whether the time interval ΔT = T3-T1 is within the threshold range. If it is not within the threshold range, the data is discarded. Otherwise, If the information is verified to be true, batch verification of n user signatures (σ1,σ2,...,σ η ) validity. SP test Is it true? If not, the verification fails. Otherwise, for i=1,2,...,η, calculate in sequence: Test t γ ≠0 if not true, if true, calculate e' γ =H(w γ ) γ The completeness of the calculation test Is it established? If yes, please sign is a valid signature. SP gives a certain amount of reward re to all users in the group and increases their credibility.

[0110] like Figure 4 As shown, the vehicle-mounted crowd intelligence perception data encryption transmission system provided by the embodiment of the present invention includes:

[0111] System settings module: used to disclose the system parameter list;

[0112] User registration module: used for in-vehicle users to register their identities. The sensing platform generates pseudonyms for them to protect user privacy and to track down the real identities of illegal vehicles.

[0113] Task distribution module: used by the perception platform to send perception tasks to edge nodes. Once the task instruction is received, the edge node will forward it to the neighboring vehicle user group;

[0114] Task receiving module: Vehicle users who are interested in participating in the task will actively respond to the call of the edge node and upload their user data to the edge node. These users then start the crowd sensing activity and transmit the collected data results back to the edge node;

[0115] Data transmission module: used by edge nodes to further aggregate the digital signatures of users who have completed the task, generate aggregate signatures, and interact securely with the perception platform to negotiate and establish session keys. With this session key, the edge node encrypts the perception data and securely transmits it to the perception platform;

[0116] The task review module is used to verify the user's signature after receiving the result information of the sensing platform task, and give corresponding rewards to the vehicle user who successfully submits valid data.

[0117] Embodiment 1: Data transmission method of vehicle-mounted crowd intelligence perception system

[0118] The present invention provides a data transmission method for a vehicle-mounted crowd intelligence perception system, which is special in that the method adopts a key exchange protocol based on SM2 digital signature to ensure the security of data transmission, including the correctness of signatures and session keys; and generates pseudonyms during data processing to achieve user anonymity and traceability. The system includes: a perception platform, an edge node, and a vehicle user.

[0119] The sensing platform (SP) has sufficient storage and computing resources to support crowdsourcing services. It is mainly responsible for receiving tasks from data demanders and distributing them to edge nodes located in the sensing area. After collecting the task reports of vehicle users, the vehicle users who complete the tasks will be rewarded and their credit will be improved. At the same time, it is also responsible for the registration and management of vehicles. In order to protect the privacy of vehicle users, SP will generate a pseudo identity for each vehicle user. When it is necessary to track illegal vehicles, SP can reveal or disclose the real identity of the vehicle.

[0120] After receiving the task assigned by the perception platform, the edge node (EN) distributes the task to nearby vehicle users. At the same time, it predicts the credit of the vehicle users and selects the vehicle users who meet the requirements of the perception task.

[0121] The vehicle user (Smart Vehicular User, V), modern vehicles are equipped with powerful computing, communication and storage capabilities, and are highly mobile. Vehicle users need to ensure that their devices have sufficient performance to support various functions. They participate in perception tasks to collect data, sign it, and finally share the data through edge nodes to obtain credit or rewards.

[0122] Specifically, the system is set up to publish the parameter list of the system, including: inputting the security parameter λ, randomly selecting a large prime number q, and determining the non-singular elliptic curve E:y 2 =x 3 +ax+b(mod q)(where, ), select a prime n-order cyclic group from all points of E (including the point at infinity) And generators Choosing a secure hash function Key derivation function KDF and decompression function uncompress. Public system parameter list

[0123] User registration is used for in-vehicle user identity registration. The perception platform generates a pseudonym for the user to protect the user's identity privacy and can also trace the true identity of the illegal vehicle.

[0124] Task distribution is used by the perception platform to send perception tasks to edge nodes. Once the task instruction is received, the edge node will forward it to the neighboring vehicle user group.

[0125] Task reception: Vehicle users who are interested in participating in the task will actively respond to the call of the edge node and upload their user data to the edge node. These users then start the crowd sensing activity and transmit the collected data results back to the edge node.

[0126] Data transmission is used by the edge node to further aggregate the digital signatures of the users who have completed the task, generate an aggregate signature, and interact securely with the perception platform to negotiate and establish a session key. With this session key, the edge node encrypts the perception data and securely transmits it to the perception platform.

[0127] Task review is used to verify the user's signature after the perception platform task receives the result information, and give corresponding rewards to vehicle users who successfully submit valid data.

[0128] In the embodiment of the present invention, a key exchange protocol based on SM2 digital signature ensures the security of data transmission, including the correctness of signature and session key; a pseudonym is generated during data processing to achieve user anonymity and traceability.

[0129] Application Example 1: Data Transmission of the In-Vehicle Group Intelligence Perception System

[0130] By applying the data transmission method of the vehicle-mounted crowd intelligence perception system of the present invention to the intelligent vehicle-mounted system, a safer and more reliable data transmission platform is provided for the vehicle-mounted crowd intelligence perception system, attracting more vehicle users to participate, thereby providing richer and higher-quality data services for data demanders and creating commercial value. The present invention can achieve the following functions:

[0131] By applying the data transmission method of the vehicle-mounted group intelligence perception system of the present invention to the intelligent vehicle-mounted system, the following functions can be achieved:

[0132] Enhanced data security: By adopting SM2 digital signature technology, the security and integrity of data transmitted by vehicle users during transmission in the network are ensured to prevent data from being illegally tampered with or stolen.

[0133] Protect user privacy: By generating pseudonyms for vehicle users, their real identities are protected from unauthorized third parties, while being able to trace back to the user's real identity when necessary to respond to violations.

[0134] Improve user engagement: Through reward mechanisms and credit management, vehicle users are encouraged to actively participate in data collection and sharing, thereby improving the quality and quantity of data.

[0135] Optimize task allocation: The perception platform can effectively assign data collection tasks to edge nodes, which in turn assign tasks to nearby vehicle users, improving the efficiency and accuracy of task allocation.

[0136] Improve data processing capabilities: Edge nodes pre-process and aggregate vehicle user data, reduce the computing burden of the perception platform, and improve the data processing capabilities of the entire system.

[0137] Ensure data transmission efficiency: Through secure session key negotiation between edge nodes and the perception platform, ensure that data can be transmitted to the perception platform quickly and securely.

[0138] Enhanced system scalability: The system design allows flexibility in handling tasks of different sizes and adapting to changing data requirements and the number of vehicle users.

[0139] Promote data service innovation: Provide richer and higher-quality data services, create new business opportunities for data demanders, and promote the development of intelligent transportation systems and smart cities.

[0140] Realize intelligent supervision: Through the credit management of vehicle users and the traceability mechanism of illegal behaviors, realize intelligent supervision of vehicle behavior and improve road safety.

[0141] Support decision-making: Provide real-time and accurate data support for urban traffic management, environmental monitoring, emergency response and other fields, helping decision makers make more scientific and reasonable decisions.

[0142] Promote vehicle intelligence: Through the application of on-board group intelligence perception system, promote the development of vehicle intelligence and improve vehicle autonomy and interoperability.

[0143] Enhance user experience: By providing a secure and reliable data transmission platform, the user experience of vehicle users is enhanced, and user satisfaction and loyalty to the smart vehicle system are improved.

[0144] Through the demonstration of this application embodiment, it can be seen that the present invention not only improves the performance of the vehicle-mounted group intelligence perception system, but also provides strong technical support for the construction of intelligent transportation and smart cities, while also creating significant economic and social value for participating vehicle users and data demanders.

[0145] The embodiments of the present invention have achieved some positive effects during the development or use process, and indeed have great advantages over the prior art. The following content is described in conjunction with data, charts, etc. of the test process.

[0146] To fully evaluate the prediction performance of our invention, we compare the computational cost of our invention with that of Tsai et al. [1] , Wu et al. [2] , Wang Fei et al. [3] , H. Lian et al. [4] With Wang Xiaohu et al. [5] The computational cost of the methods is compared. To clearly describe the theoretical analysis results, the article uses T em Represents the multiplication operation on the elliptic curve, T m express Multiplication operation on T H represents a secure hash operation, T E Represents modular exponentiation and T P Represents the bilinear pairing operation.

[0147] In the present invention, the required operations are T em +3T m +T H The total computational overhead is 2.378ms. In the method proposed by Tsai et al., the required computation is 15T. P +33T E, the total computational overhead is 214.215ms; in the method proposed by Wu et al., An identity-based authenticated key exchange protocol resilient to continuous key leakage, 4+27 operations are required, and the total computational overhead is 127.194ms; in the method proposed by Wang Fei et al., a perfect forward-secure identity-based key negotiation scheme, T operations are required. P +8T E , the total computational overhead is 36.611; in the method proposed by H.Lian et al. for Efficient and Strong Symmetric Password Authenticated Key Exchange With Identity Privacy for IoT, the required computation is 6T E +14T H , the total computational overhead is 23.132ms; in the method of identity authentication key exchange protocol based on SM2 proposed by Wang Xiaohu et al., the required operation is 1T E +15T em ,The total computational cost is 37.24ms. The computational cost comparison of each method is shown in Table 1. Figure 3 This is the running time comparison result of the existing method and the method in the present invention. The experimental analysis results show that the time overhead of the present invention is the smallest, so it is more suitable for resource-constrained network environments such as the Internet of Vehicles.

[0148] Table 1 Performance comparison

[0149]

[0150] The following are two specific embodiments of the method for encrypting and transmitting vehicle-mounted crowd intelligence perception data in the present invention:

[0151] Example 1: Traffic congestion information collection and transmission

[0152] 1. Task allocation and vehicle user selection: During peak traffic hours, the perception platform SP receives a request from the traffic management department to collect traffic congestion information in a specific area. SP distributes the collection task to vehicle users in the target area through the edge node EN. EN selects vehicle users V with high credit and qualified conditions based on the credit prediction and location of the vehicle users.

[0153] 2. Data collection and encrypted transmission: The selected vehicle users use on-board sensors to collect data such as speed, density, and traffic volume of the road section during driving. After collecting the data, each vehicle user uses the key exchange protocol based on SM2 digital signature to generate a session key, sign and encrypt the data to ensure data integrity and confidentiality. The encrypted data is transmitted to the SP through EN.

[0154] 3. Data verification and rewards: After receiving the encrypted traffic data, SP uses the session key to decrypt and verify it to ensure the authenticity of the data. For vehicle users who complete the task, SP gives corresponding credit and rewards, and records the pseudo-identity. If abnormal data occurs, SP can track the user's real identity through the pseudo-identity mechanism for traceability.

[0155] Example 2: Road safety status monitoring

[0156] 1. Task assignment and pseudo identity generation: To monitor the safety of a specific road, SP receives a request from the traffic safety department. SP generates collection tasks based on the demand and generates a pseudo identity for each vehicle user before the task is released to ensure anonymity. After receiving the task, EN assigns the collection task to the qualified vehicle user V who has passed the credit screening.

[0157] 2. Data collection and processing: Vehicle users collect real-time information about the road through on-board sensors, including road conditions, obstacles, traffic sign clarity, etc. During data collection and processing, vehicle users use the SM2 digital signature encryption protocol to generate signatures and session keys, encrypt the collected data, and ensure data security and integrity.

[0158] 3. Data transmission and identity tracking: Encrypted data is uploaded to SP through EN. After decrypting and verifying the data, SP evaluates the road safety status and provides rewards and credit points to vehicle users who complete the task. If security risks are found in the data, SP can track the real identity of the corresponding vehicle user through a pseudo-identity mechanism to further obtain detailed information on the road section or confirm the authenticity of the data source.

[0159] The method for encrypted transmission of in-vehicle crowd-sensing data proposed in the present invention solves the deficiencies in the prior art in terms of data security, privacy protection, and data traceability during the transmission of in-vehicle sensing data, and achieves significant technological progress. In traditional in-vehicle crowd-sensing data transmission systems, there are problems such as weak data security, difficulty in protecting user privacy, and low data transmission efficiency, which lead to risks such as user data leakage and data untraceability. The present invention has made innovative designs in data encryption transmission and privacy protection, and adopts a key exchange protocol based on SM2 digital signatures and a pseudo-identity generation mechanism to effectively solve the above problems.

[0160] First, in terms of data security, the present invention adopts a key exchange protocol based on SM2 digital signature to ensure the encryption and integrity of data during transmission. Through the encrypted signature mechanism of the session key, not only the security and correctness of the data transmission process can be ensured, but also the reliability of the transmission can be guaranteed. This solution significantly reduces the risk of data being tampered with or stolen during transmission in the vehicle network, solves the problem of insufficient data transmission security in traditional vehicle-mounted group intelligence perception systems, and provides a guarantee for efficient and reliable data transmission.

[0161] Secondly, in terms of user privacy protection, the present invention achieves anonymity by generating a pseudo-identity for each vehicle user on the perception platform, so that vehicle users do not need to reveal their real identities when participating in perception tasks, thus avoiding the risk of privacy leakage. At the same time, the present invention allows the user's real identity to be traced through a pseudo-identity when necessary, thereby taking into account both privacy protection and traceability. Compared with the identity disclosure or completely anonymous mode in traditional methods, the pseudo-identity mechanism of the present invention improves user privacy protection while enhancing the flexibility and management capabilities of the system.

[0162] In terms of edge computing and task scheduling, the present invention uses edge nodes to intelligently allocate tasks, and selects qualified users for sensing tasks based on the credit of vehicle users, thereby improving the accuracy of tasks and the utilization of system resources. This design not only ensures data quality, but also significantly improves the reliability of data collection, reduces the system's computing overhead and transmission load, and solves the problems of low task allocation efficiency and unstable data quality in traditional systems.

[0163] Finally, in terms of data transmission and incentive mechanism, the present invention establishes a data collection and reward mechanism so that vehicle users can obtain credit points and rewards after completing the perception task, thus motivating users to actively participate in the perception task. After verifying the authenticity and integrity of the data, the perception platform rewards users who meet the requirements. This mechanism not only ensures data quality, but also improves the enthusiasm of user participation and the coverage of data collection, providing impetus for the sustainable development of the crowd-intelligence perception data system.

[0164] In general, the present invention has achieved significant progress in data security, privacy protection, task scheduling and incentive mechanisms, successfully improving the security, applicability and stability of the vehicle-mounted crowd intelligence perception system in a heterogeneous network environment, and providing innovative technical support for the development of intelligent transportation systems and the Internet of Vehicles industry.

[0165] The above description is only a specific implementation mode of the present invention, but the protection scope of the present invention is not limited thereto. Any modifications, equivalent substitutions and improvements made by any technician familiar with the technical field within the technical scope disclosed by the present invention and within the spirit and principle of the present invention should be covered by the protection scope of the present invention.

Claims

1. A method for encrypting and transmitting vehicle-mounted crowd intelligence perception data, characterized in that: The method comprises the following steps: Step 1: System settings, used to disclose the system parameter list; Step 2: User registration, which is used for the in-vehicle user to register their identity. The sensing platform generates a pseudonym for them to protect the user's identity privacy and to trace the real identity of the illegal vehicle. Step 3: Task distribution, where the sensing platform sends the sensing task to the edge node. Once the task instruction is received, the edge node forwards it to the neighboring vehicle user group. Step 4: Task reception, in which vehicle users who are interested in participating in the task will actively respond to the call of the edge node and upload their user data to the edge node. These users then start the crowd sensing activity and transmit the collected data results back to the edge node; Step 5: Data transmission, which is used by the edge node to further aggregate the digital signatures of the users who have completed the task, generate an aggregate signature, and interact securely with the perception platform to negotiate and establish a session key. With this session key, the edge node encrypts the perception data and securely transmits it to the perception platform. Step six, task review, is used to verify the user's signature after the perception platform task receives the result information, and give corresponding rewards to the vehicle user who successfully submits valid data.

2. The method for encrypting and transmitting vehicle-mounted crowd intelligence perception data according to claim 1, characterized in that: The step one comprises: Input security parameter λ, randomly select a large prime number q, and determine the non-singular elliptic curve E:y 2 =x 3 +ax+b(mod q)(where, ), select a prime n-order cyclic group from all points of E (including the point at infinity) And generators Choosing a secure hash function Key derivation function KDF and decompression function uncompress. Public system parameter list 3. The method for encrypting and transmitting vehicle-mounted crowd intelligence perception data as claimed in claim 1, characterized in that: The second step comprises: During the user registration phase, the specific process between user V and the perception platform SP is as follows: The user first randomly selects Then calculate P = d·G. Let the user's private key be sk v =d, the user's public key is pk v =P. Use the public key pk of the perception platform SP Encrypt the information M, H(M), and pk submitted during registration v and random number a, and send the encrypted result to SP, where M = (ID v ||m * ), ID v is the real identity of the user, m * For the user's personal information data, H(M) ensures the integrity of the user's registration information. SP→V:E a [ID v '] After receiving the encrypted information, SP uses its private key sk SP Decrypt and get M, H(M), pk v and random number a, and verify the integrity of M through H(M). After verification, SP generates a pseudonymous ID for the user v ', calculate ID v '=H(ID v ), and encrypt it with a and send it to the user. After receiving it, the user decrypts it with a to get the ID v ', and subsequently use the pseudonym for communication. When tracing the user of the responsibility issue, the SP presents or exposes the user's real identity.

4. The method for encrypting and transmitting vehicle-mounted crowd intelligence perception data according to claim 1, characterized in that: The step three comprises: The task distribution link is a key step in the interaction between the perception platform SP, the edge node EN and the user V. The specific process is as follows: σ Task =Sign(sk SP ,Task) SP first creates task information Task = (work||re||cr th ||T1), where work is the task details, re is the reward for completing the task, cr is the reward for completing the task, th is the credit threshold required by the task for the user's credit, and T1 is the current timestamp. Then, SP calculates H(Task) and uses its private key sk SP Sign the task and generate σ Task . Verify(pk SP ,σ Task ) SP distributes the task information with signature to nearby ENs. After receiving the information, EN calculates H(Task) to verify the integrity of the task information and uses pk SP Verify the signature to ensure the authenticity of the task information. If the verification is successful, EN will forward the task information to the surrounding users; otherwise, EN will discard the task information to prevent the spread of errors. After receiving the task information, the user will also verify the integrity and authenticity. After the verification is passed, the user decides whether to participate in the task based on the requirements of the task and his own conditions.

5. The method for encrypting and transmitting vehicle-mounted crowd intelligence perception data as claimed in claim 1, characterized in that: The fourth step comprises: Task reception is the initial stage of user participation in the perception task. The specific process is as follows: According to the task requirements, it is assumed that a user who is willing to participate is the γth user (1≤γ≤n), and the task information is verified as EN to ensure the integrity and authenticity of the task information. If the verification is passed, the user randomly selects a random number. And calculate K γ =k γ G=(x γ ,y γ ), e γ =H(w γ ),r γ =(e γ +x γ )(mod n).w γ is the request information of the γth user participating in the perception task, that is, in is the pseudonym of the γth user, is the personal information data of the γth user, T2 is the current timestamp, and b is a random number. γ =0 or r γ +k γ =0, then reselect k γ Calculate again; otherwise calculate s γ =(1+d γ ) -1 (k γ -r γ d γ )(mod n). If s γ = 0, then return to reselect the random number, otherwise generate the signature σ γ =(r γ ,s γ )=Sign(d γ ,w γ ). The user then uses pk EN Encryption γ and w γ , and send the encrypted result to EN. After receiving the encrypted information, EN uses its private key to decrypt it and obtains σ γ and w γ First, determine whether the time interval ΔT = T2-T1 is within the threshold range. If it exceeds the threshold, the data is discarded. If it is within the threshold, EN check Is it true? If not, the verification fails; otherwise, calculate e' γ =H(w' γ ) to test w' γ The integrity of γ ≠0, then further calculate t γ =(r' γ +s' γ )(mod n), K' γ =s' γ G+t γ P γ =(x' γ ,y' γ ), r' γ =(e' γ +x' γ )(mod n). Finally, check r' γ =r γ Is it true? If true, then confirm the signature σ γ efficient.

6. The method for encrypting and transmitting vehicle-mounted crowd intelligence perception data as claimed in claim 1, characterized in that: The step five comprises: T E Stores EN's transaction perception data, T s The task reward re of SP is stored. EN uses the private key to calculate the random number k in the signature E =(s E (1+d E )+r E d E )(mod n), calculate x s =(r s -H(T s ))(mod n), transaction public key Shared Secrets Calculate and output the session key SK E =KDF(x ES ). SP uses the private key to calculate the random number k in the signature S =(s S (1+d S )+r S d S )(mod n), calculate x E =(r E -H(T E ))(modn), transaction public key Calculate the common secret Calculate and output the session key SK S =KDF(x ES ). EN sends the sensing task data, user pseudonym group and signature group collected from the user to SP through the session key.

7. The method for encrypting and transmitting vehicle-mounted crowd intelligence perception data as claimed in claim 1, characterized in that: The step six comprises: SP uses the session key to decrypt and obtain the task result information. First, it determines whether the time interval ΔT = T3-T1 is within the threshold range. If it is not within the threshold range, the data is discarded. Otherwise, If the information is verified to be true, batch verification of n user signatures (σ1,σ2,...,σ η ) validity. SP test Is it true? If not, the verification fails. Otherwise, for i=1,2,...,η, calculate in sequence: Test t γ ≠0 if not true, if true, calculate e' γ =H(w γ ) γ The completeness of the calculation test Is it true? If so, sign it. is a valid signature. SP gives a certain amount of reward re to all users in the group and increases their credibility.

8. A vehicle-mounted crowd intelligence perception data encryption transmission system according to the method of claim 1, characterized in that: include: System settings module: used to disclose the system parameter list; User registration module: used for in-vehicle users to register their identities. The sensing platform generates pseudonyms for them to protect user privacy and to track down the real identities of illegal vehicles. Task distribution module: used by the perception platform to send perception tasks to edge nodes. Once the task instruction is received, the edge node will forward it to the neighboring vehicle user group; Task receiving module: Vehicle users who are interested in participating in the task will actively respond to the call of the edge node and upload their user data to the edge node. These users then start the crowd sensing activity and transmit the collected data results back to the edge node; Data transmission module: used by edge nodes to further aggregate the digital signatures of users who have completed the task, generate aggregate signatures, and interact securely with the perception platform to negotiate and establish session keys. With this session key, the edge node encrypts the perception data and securely transmits it to the perception platform; The task review module is used to verify the user's signature after receiving the result information of the sensing platform task, and give corresponding rewards to the vehicle user who successfully submits valid data.

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