An identity authentication method based on vehicle networking technology

Abstract

This invention relates to the field of vehicle networking technology, specifically addressing the problem of low security in identity authentication, and particularly to an identity authentication method based on vehicle networking technology. The invention initially analyzes the driving requests of the target vehicle to improve driving safety, while also facilitating preliminary authentication of the target user's driving safety. It further analyzes the timeliness of the vehicle networking service authentication requests to ensure the real-time validity of the authentication requests. Based on this validity, it combines the analysis of the target user's initiation operation characteristics with biometric verification, effectively improving the security and reliability of the authentication system. Furthermore, it performs continuous authentication and driving anomaly detection during the vehicle's operation, transforming identity verification from a static, one-time process into dynamic, continuous monitoring, providing a new dimension of protection for vehicle networking security and significantly enhancing the security of vehicle identity authentication.

Description

Technical Field

[0001] This invention relates to the field of vehicle networking technology, and in particular to an identity authentication method based on vehicle networking technology. Background Technology

[0002] With the rapid development of vehicle-to-everything (V2X) technology, vehicles are communicating with the outside world more and more frequently, and vehicle security issues are becoming increasingly prominent. In the V2X environment, vehicles need to communicate with cloud servers, other vehicles, roadside infrastructure, etc., to achieve functions such as navigation, autonomous driving, and traffic information sharing. However, in these communication processes, how to ensure the legality of the identities of the communicating parties and the security of the communication data has become one of the key issues in the development of V2X technology.

[0003] In existing technologies, some vehicle networking systems use digital certificate authentication, but certificate management is complex and there is a risk of theft. At the same time, some systems introduce biometric recognition, but single biometric features (such as fingerprints) are easy to copy, and it is difficult to monitor the timeliness of information synchronization, resulting in time synchronization and interception problems. In addition, it is difficult to authenticate users while driving, making it difficult to monitor and warn of driver substitution in a timely manner, thus reducing vehicle driving safety.

[0004] To address the aforementioned technical shortcomings, a solution is proposed. Summary of the Invention

[0005] The purpose of this invention is to provide an identity authentication method based on vehicle-to-everything (V2X) technology to address the aforementioned technical deficiencies. This invention initially analyzes the target vehicle's driving requests to improve driving safety and facilitates preliminary authentication of the target user's driving safety. It also analyzes the timeliness of the target vehicle's V2X service authentication requests to ensure the real-time validity of the authentication requests. Based on this validity, it analyzes the target user's initiation operation characteristics combined with biometric verification, effectively improving the security and reliability of the authentication system. Furthermore, it performs continuous authentication and driving anomaly detection during the target vehicle's operation, transforming identity verification from a static, one-time process into dynamic, continuous monitoring. This provides a new dimension of protection for V2X security, significantly enhancing the security of vehicle identity authentication. Additionally, it ensures a better user experience through intelligent analysis and adaptive mechanisms.

[0006] The objective of this invention can be achieved through the following technical solution: an identity authentication method based on vehicle networking technology, comprising the following steps:

[0007] Step 1: Initialize the driving request process of the target vehicle, that is, process the request information. If a consistent instruction is received, proceed to Step 2; if an inconsistent instruction is received, output feedback.

[0008] Step 2: Biometric registration process when the target user uses the target vehicle for the first time, obtaining a multimodal biometric template;

[0009] Step 3: The timeliness analysis process of information when the target vehicle starts up and connects to the vehicle network service, that is, to judge and process the obtained time difference. If a valid instruction is obtained, proceed to step 4; if an invalid instruction is obtained, output feedback.

[0010] Step 4: A vehicle-to-everything (V2X) service security supervision process that combines target user startup operation feature analysis with biometric verification;

[0011] Step 5: Based on the continuous authentication and driving anomaly detection operation during the continuous driving process of the target vehicle, the obtained biometric ratio is processed and the obtained driving change command or regular driving command is output and fed back.

[0012] Preferably, the process of initializing the target vehicle's driving request is as follows:

[0013] The authentication center assigns a unique vehicle ID to the target vehicle and a unique user ID to the target user. The authentication center stores the vehicle ID and user ID.

[0014] When a target user initiates an authentication request, the authentication process is as follows:

[0015] The target user enters their user ID through the vehicle terminal. The vehicle terminal encrypts the request information and sends it to the authentication center. After receiving the request information, the authentication center decrypts it, extracts the request information, and performs discrimination processing to obtain the evaluation output results of the request information. The evaluation output results include consistency and inconsistency. The center obtains the number of consistent evaluation output results of the request information and performs discrimination processing on the number of consistent evaluation output results of the request information to obtain a consistent instruction or an inconsistent instruction.

[0016] Preferably, the biometric registration process is as follows:

[0017] Based on the vehicle terminal, the driver's biometric data is collected simultaneously through the built-in camera and microphone, as well as the target user's operation characteristic data, including the door opening force, ignition start time, and ignition operation force.

[0018] The collected biometric and operational data are preprocessed and feature extracted to generate multimodal biometric templates, which are then stored.

[0019] Preferably, the information timeliness analysis process is as follows:

[0020] When the target vehicle starts up and needs to access the vehicle network service, the vehicle terminal sends a vehicle network authentication request to the authentication center. The vehicle network authentication request includes the vehicle's identification information and timestamp.

[0021] After receiving the vehicle network authentication request, the authentication center obtains the time difference between the timestamp of sending the vehicle network authentication request and the time when the authentication center synchronizes the vehicle network authentication request, and performs discrimination processing on the time difference to obtain a valid instruction or an invalid instruction.

[0022] Preferably, the vehicle network service security supervision process is as follows: when a dynamic verification code is randomly generated based on the identification information of the target vehicle and sent to the vehicle terminal, after receiving the dynamic verification code, the vehicle terminal prompts the target user to perform multimodal biometric verification and obtains authorization instructions, auxiliary defect instructions, or abnormal instructions.

[0023] Preferably, the multimodal biometric verification process is as follows: assign corresponding preset weights to the parameters in the biometric data of the target user, obtain the matching score corresponding to each parameter in the biometric data, set the sum of the matching score corresponding to each parameter and the corresponding preset weight as the comprehensive biometric score, and perform discrimination processing on the comprehensive biometric score to obtain an unqualified instruction or a qualified instruction.

[0024] Preferably, while performing biometric verification, the target user's operational characteristic data is simultaneously analyzed for auxiliary verification. The specific auxiliary verification and analysis process is as follows:

[0025] The system collects the user's operation sequence when starting the vehicle, including changes in touchscreen pressure and steering wheel grip strength. The operation sequence is converted into a feature vector, and the similarity between the operation sequence and the preset operation sequence is calculated. The similarity is then processed to obtain the alignment command or deviation command.

[0026] Preferably, the continuous authentication and driving anomaly detection process is as follows:

[0027] Obtain the driving time period of the target vehicle, and obtain the driving information of the target user during the driving time period;

[0028] The driving information is processed based on machine learning algorithms to establish a driver driving baseline model. The driving deviation is obtained in real time based on the driver driving baseline model and the driving deviation is judged. If the driving deviation is less than the preset driving deviation threshold, it is judged to be in the maintenance state. If the driving deviation is greater than or equal to the preset driving deviation threshold, it is judged to be in the change state.

[0029] The duration of the changed status is obtained, and the duration of the changed status is set as the driving change risk value. The driving change risk value is then processed to obtain a regular instruction or a change instruction.

[0030] Preferably, when a change instruction is generated, the target user's own feature image set during the driving period is obtained, and the own feature image set includes facial feature images and head feature images on the left side of the driving direction;

[0031] It compares and analyzes its own feature image set with a pre-set own feature image set, obtains the proportion of images in its own feature image set whose similarity exceeds a preset similarity threshold, and sets this as the biometric ratio. It then performs discrimination processing on the biometric ratio. If the biometric ratio is less than the preset biometric ratio threshold, a driving change command is generated. If the biometric ratio is greater than or equal to the preset biometric ratio threshold, a regular driving command is generated.

[0032] The beneficial effects of this invention are as follows:

[0033] (1) This invention initially analyzes the driving request of the target vehicle to improve the driving safety of the target vehicle and helps to conduct preliminary driving safety authentication of the target user. When the target user uses the target vehicle for the first time, a multimodal biometric template is established to provide data support for subsequent authentication. At the same time, the timeliness of the authentication request of the vehicle network service of the target vehicle is analyzed to ensure that the real-time performance of the authentication request is qualified.

[0034] (2) This invention analyzes the target user's startup operation characteristics and biometric verification from the perspective of qualified users, which effectively improves the security and reliability of the authentication system. In the process of the target vehicle driving, continuous authentication and driving anomaly detection are performed. That is, by changing the identity verification from a static single process to dynamic continuous monitoring, a new protection dimension is provided for the security of the Internet of Vehicles, which significantly improves the security of vehicle identity authentication. In addition, the user experience is guaranteed through intelligent analysis and adaptive mechanism. Attached Figure Description

[0035] The invention will now be further described with reference to the accompanying drawings;

[0036] Figure 1 This is a reference diagram of the method of the present invention;

[0037] Figure 2 This is a reference diagram of the framework of the present invention. Detailed Implementation

[0038] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0039] In this document, the term "embodiment" means that a particular feature, structure, or characteristic described in connection with an embodiment may be included in at least one embodiment of the invention. The appearance of this phrase in various places throughout the specification does not necessarily refer to the same embodiment, nor is it a separate or alternative embodiment mutually exclusive with other embodiments. It will be explicitly and implicitly understood by those skilled in the art that the embodiments described herein can be combined with other embodiments;

[0040] Example 1:

[0041] Please see Figures 1 to 2 As shown, this invention is an identity authentication method based on vehicle networking technology, comprising the following steps:

[0042] Step 1: Initialize the driving request process of the target vehicle, that is, process the request information. If a consistent instruction is received, proceed to Step 2; if an inconsistent instruction is received, output feedback.

[0043] Step 2: Biometric registration process when the target user uses the target vehicle for the first time, obtaining a multimodal biometric template;

[0044] Step 3: The timeliness analysis process of information when the target vehicle starts up and connects to the vehicle network service, that is, to judge and process the obtained time difference. If a valid instruction is obtained, proceed to step 4; if an invalid instruction is obtained, output feedback.

[0045] Step 4: The vehicle network service safety supervision process combines target user startup operation feature analysis and biometric verification. This involves processing the comprehensive biometric score to obtain unqualified and qualified instructions, processing the similarity to obtain conforming and deviating instructions, and obtaining authorized instructions, auxiliary defect instructions, or abnormal instructions based on instruction interaction analysis.

[0046] Step 5: Based on the continuous authentication and driving anomaly detection operation during the continuous driving process of the target vehicle, the obtained biometric ratio is processed and the obtained driving change command or regular driving command is output and fed back.

[0047] The specific process for initializing the target vehicle's driving request is as follows:

[0048] The authentication center assigns a unique vehicle ID to the target vehicle and a unique user ID to the target user. The authentication center stores information such as vehicle ID and user ID.

[0049] When a target user initiates an authentication request, the authentication process is as follows:

[0050] The target user inputs their user ID through the vehicle terminal. The vehicle terminal encrypts the request information, including the user ID, vehicle ID, and vehicle location information, and sends it to the authentication center. Upon receiving the request information, the authentication center decrypts it, extracts the user ID, vehicle ID, and vehicle location information, and performs a judgment process to obtain the evaluation output results. The evaluation output results include consistency and inconsistency. The center obtains the number of consistent evaluation output results and performs a judgment process on the number of consistent evaluation output results. If the number of consistent evaluation output results is equal to a preset threshold, a consistency instruction is generated. If the number of consistent evaluation output results is not equal to the preset threshold, an inconsistency instruction is generated. When an inconsistency instruction is generated, the preset result corresponding to the inconsistency instruction is output.

[0051] When a consistent instruction is generated, the authentication center determines that the authentication is successful, generates a successful authentication result, and encrypts the result using the communication key between the target vehicle and the authentication center, and sends it to the target vehicle; after receiving the successful authentication result, the target vehicle unlocks the door, and the target user can drive the target vehicle.

[0052] For example: if the user ID is the same as the preset user ID, it is determined to be consistent; if the user ID is different from the preset user ID, it is determined to be inconsistent. If the vehicle ID is the same as the preset vehicle ID, it is determined to be consistent; if the vehicle ID is different from the preset vehicle ID, it is determined to be inconsistent. If the vehicle location information is within the preset area, it is determined to be consistent; if the vehicle location information is not within the preset area, it is determined to be inconsistent.

[0053] Example 2:

[0054] Step 2: Biometric registration process when the target user uses the target vehicle for the first time, obtaining a multimodal biometric template;

[0055] The biometric registration process is as follows:

[0056] Based on the vehicle terminal, the driver's facial images, voice samples and other biometric data are collected simultaneously through built-in cameras, microphones and other devices.

[0057] Simultaneously, the operation characteristic data of the target user is collected, including operation characteristics such as door opening force, ignition start time, and ignition operation force.

[0058] The collected biometric data and operational feature data are preprocessed and feature extracted to generate multimodal biometric templates, which are then stored.

[0059] Step 3: The timeliness analysis process of information when the target vehicle starts up and connects to the vehicle network service, that is, to judge and process the obtained time difference. If a valid instruction is obtained, proceed to step 4; if an invalid instruction is obtained, output feedback.

[0060] The specific process for analyzing the timeliness of information is as follows:

[0061] When the target vehicle starts up and needs to access the vehicle network service, the vehicle terminal sends a vehicle network authentication request to the authentication center. The vehicle network authentication request includes the vehicle's identification information, timestamp, etc.

[0062] After receiving the vehicle network authentication request, the authentication center obtains the time difference between the timestamp of sending the vehicle network authentication request and the time when the authentication center synchronizes the vehicle network authentication request. The time difference is then processed. If the time difference is less than or equal to a preset time difference threshold, it is determined to be a valid instruction. If the time difference is greater than the preset time difference threshold, it is determined to be an invalid instruction. The center then responds to the invalid instruction and performs a preset feedback operation to ensure that the authentication request is real-time.

[0063] Example 3:

[0064] Step 4: The vehicle network service safety supervision process combines target user startup operation feature analysis and biometric verification. This involves processing the comprehensive biometric score to obtain unqualified and qualified instructions, processing the similarity to obtain conforming and deviating instructions, and obtaining authorized instructions, auxiliary defect instructions, or abnormal instructions based on instruction interaction analysis.

[0065] The specific process for supervising the safety of connected vehicle services is as follows:

[0066] When a dynamic verification code is randomly generated based on the identification information of the target vehicle and sent to the vehicle terminal, the vehicle terminal prompts the target user to perform multimodal biometric verification after receiving the dynamic verification code.

[0067] The multimodal biometric verification process is as follows:

[0068] The parameters in the biometric data of the target user are assigned corresponding preset weights, and the matching score corresponding to each parameter in the biometric data is obtained. The sum of the matching scores corresponding to each parameter and the corresponding preset weights is set as the comprehensive biometric score. The comprehensive biometric score is then judged: if the comprehensive biometric score is less than the preset comprehensive biometric score threshold, an unqualified instruction is generated; if the comprehensive biometric score is greater than or equal to the preset comprehensive biometric score threshold, a qualified instruction is generated.

[0069] For example: the similarity between the fingerprint feature image of the target user and the preset fingerprint feature image is 90 points out of 100; the similarity between the facial image of the target user and the preset facial image is 70 points out of 100.

[0070] Simultaneously with biometric verification, auxiliary verification and evaluation analysis are performed on the target user's operational characteristic data. The specific auxiliary verification and evaluation analysis process is as follows:

[0071] The system collects the user's operation sequence when starting the vehicle, including touchscreen pressure changes, steering wheel grip strength, etc. The operation sequence is converted into a feature vector (such as One-Hot encoding), and the similarity between the operation sequence and the preset operation sequence is calculated. The similarity is then processed: if the similarity is greater than or equal to the preset similarity threshold, a matching instruction is generated; if the similarity is less than the preset similarity threshold, a deviation instruction is generated.

[0072] Interactive analysis of qualified instructions, unqualified instructions, fit instructions, and deviation instructions:

[0073] If a qualified instruction and a fitting instruction are generated, an authorization instruction is obtained, which is then output to grant normal authorization to the target user.

[0074] If a qualified instruction and a deviation instruction are generated, an auxiliary defect instruction is obtained, that is, the auxiliary defect instruction is output, which prompts the target user's operating habits to change and suggests updating the multimodal biometric template;

[0075] If unqualified instructions and fitting instructions or unqualified instructions and deviation instructions are generated, an abnormal instruction is obtained, that is, an abnormal instruction is output, triggering secondary verification multimodal biometric verification and auxiliary verification evaluation analysis, and the event is recorded, so as to conduct security supervision and certification of the vehicle network service of the target vehicle, thereby improving the safety of using the vehicle network service of the target vehicle.

[0076] Meanwhile, by combining target user startup behavior analysis with biometric verification, this method provides an additional dimension of identity verification, effectively improving the security and reliability of the authentication system. The operational behavior characteristics are difficult to imitate and change slowly, which can serve as a powerful supplement to biometric verification, especially in cases where the biometric part fails or is disputed, providing key decision support.

[0077] Step 5: Based on the continuous authentication and driving anomaly detection operation during the continuous driving process of the target vehicle, the obtained biometric ratio is processed and the obtained driving change command or regular driving command is output and fed back.

[0078] The specific procedures for continuous certification and driving anomaly detection are as follows:

[0079] When an authorization command is generated, the driving time period of the target vehicle is obtained, and the driving information of the target user during the driving time period is obtained, including steering angle, acceleration change, lane keeping duration, etc.

[0080] The driving information is processed using machine learning algorithms (such as LSTM) to establish a driver driving baseline model. The driving deviation is obtained in real time based on the driver driving baseline model and the driving deviation is judged. If the driving deviation is less than the preset driving deviation threshold, it is judged to be in the maintenance state. If the driving deviation is greater than or equal to the preset driving deviation threshold, it is judged to be in the change state.

[0081] The duration of the changed status is obtained and set as the driving change risk value. The driving change risk value is then judged. If the driving change risk value is less than the preset driving change risk value threshold, a normal instruction is generated. If the driving change risk value is greater than or equal to the preset driving change risk value threshold, a change instruction is generated.

[0082] When a change command is generated, the target user's own feature image set during the driving period is obtained. The own feature image set includes facial feature images, head feature images on the left side of the driving direction, etc.

[0083] It compares and analyzes its own feature image set with a pre-set self-feature image set, obtains the proportion of images in the self-feature image set whose similarity exceeds a preset similarity threshold, and sets this as the biometric ratio. The biometric ratio is then processed. If the biometric ratio is less than the preset biometric ratio threshold, a driving change command is generated. If the biometric ratio is greater than or equal to the preset biometric ratio threshold, a regular driving command is generated. When a driving change command is generated, the identity re-authentication process is automatically triggered, requiring the driver to re-verify biometrics. When a regular driving command is generated, the driving safety of the target user is continuously monitored. Continuous authentication and anomaly detection transform identity verification from a static, one-time process to dynamic, continuous monitoring, providing a new dimension of protection for vehicle network security, significantly improving the security of vehicle identity authentication, and also ensuring user experience through intelligent analysis and adaptive mechanisms.

[0084] In summary, this invention initially analyzes the driving requests of the target vehicle to improve its driving safety and facilitates initial driving safety authentication for the target user. For the first use of the target vehicle by the target user, a multimodal biometric template is established to provide data support for subsequent authentication. The timeliness of the vehicle's Internet of Vehicles (V2V) service authentication requests is analyzed to ensure the real-time validity of the authentication requests. Based on this validity, the analysis combines user initiation operation feature analysis with biometric verification, effectively improving the security and reliability of the authentication system. Furthermore, continuous authentication and driving anomaly detection are performed during the vehicle's operation, transforming identity verification from a static, one-time process to dynamic, continuous monitoring. This provides a new dimension of protection for V2V security, significantly enhancing the security of vehicle identity authentication. Intelligent analysis and adaptive mechanisms also ensure a superior user experience.

[0085] The threshold is set for comparative analysis of results to determine whether they are good or bad. The value of the threshold is determined by a combination of large-scale model analysis of sample data and human experience. It can also be adjusted appropriately based on seasonal or common-sense influencing factors.

[0086] The size of the coefficient is a specific value obtained by quantifying each parameter to facilitate subsequent comparison. The size of the coefficient depends on the amount of sample data and the corresponding operating coefficient initially set by those skilled in the art for each set of sample data; as long as it does not affect the proportional relationship between the parameter and the quantified value.

[0087] The above description is only a preferred embodiment of the present invention, but the scope of protection of the present invention is not limited thereto. Any equivalent substitutions or modifications made by those skilled in the art within the scope of the technology disclosed in the present invention, based on the technical solution and inventive concept of the present invention, should be covered within the scope of protection of the present invention.

Claims

1. An identity authentication method based on vehicle networking technology, characterized in that, Includes the following steps: Step 1: Initialize the driving request process of the target vehicle, that is, process the request information. If a consistent instruction is received, proceed to Step 2; if an inconsistent instruction is received, output feedback. Step 2: Biometric registration process when the target user uses the target vehicle for the first time, obtaining a multimodal biometric template; Step 3: The timeliness analysis process of information when the target vehicle starts up and connects to the vehicle network service, that is, to judge and process the obtained time difference. If a valid instruction is obtained, proceed to step 4; if an invalid instruction is obtained, output feedback. Step 4: A vehicle-to-everything (V2X) service security supervision process that combines target user startup operation feature analysis with biometric verification; Step 5: Based on the continuous authentication and driving anomaly detection operation during the continuous driving process of the target vehicle, the obtained biometric ratio is processed and the obtained driving change command or regular driving command is output and fed back. The process of initializing the target vehicle's driving request is as follows: The authentication center assigns a unique vehicle ID to the target vehicle and a unique user ID to the target user. The authentication center stores the vehicle ID and user ID. When a target user initiates an authentication request, the authentication process is as follows: The target user enters their user ID through the vehicle terminal. The vehicle terminal encrypts the request information and sends it to the authentication center. After receiving the request information, the authentication center decrypts it, extracts the request information, and performs judgment processing on the request information to obtain the evaluation output result of the request information. The evaluation output result includes consistency and inconsistency. The number of consistent evaluation output results of the request information is obtained, and the number of consistent evaluation output results of the request information is judged to obtain a consistent instruction or an inconsistent instruction. The biometric registration process is as follows: Based on the vehicle terminal, the driver's biometric data is collected simultaneously through the built-in camera and microphone, as well as the target user's operation characteristic data, including the door opening force, ignition start time, and ignition operation force. The collected biometric data and operational feature data are preprocessed and feature extracted to generate multimodal biometric templates, which are then stored. The information timeliness analysis process is as follows: When the target vehicle starts up and needs to access the vehicle network service, the vehicle terminal sends a vehicle network authentication request to the authentication center. The vehicle network authentication request includes the vehicle's identification information and timestamp. After receiving the vehicle network authentication request, the authentication center obtains the time difference between the timestamp of sending the vehicle network authentication request and the time when the authentication center synchronizes the vehicle network authentication request, and performs discrimination processing on the time difference to obtain a valid instruction or an invalid instruction. The vehicle network service security supervision process is as follows: When a dynamic verification code is randomly generated based on the identification information of the target vehicle and sent to the vehicle terminal, the vehicle terminal prompts the target user to perform multimodal biometric verification after receiving the dynamic verification code, and obtains authorization instructions, auxiliary defect instructions, or abnormal instructions. The multimodal biometric verification process is as follows: assign corresponding preset weights to the parameters in the biometric data of the target user, obtain the matching score corresponding to each parameter in the biometric data, set the sum of the matching score corresponding to each parameter and the corresponding preset weight as the comprehensive biometric score, and perform discrimination processing on the comprehensive biometric score to obtain an unqualified instruction or a qualified instruction. Simultaneously with biometric verification, auxiliary verification and evaluation analysis are performed on the target user's operational characteristic data. The specific auxiliary verification and evaluation analysis process is as follows: The system collects the user's operation sequence when starting the vehicle, including changes in touchscreen pressure and steering wheel grip strength. The operation sequence is converted into a feature vector, and the similarity between the operation sequence and the preset operation sequence is calculated. The similarity is then processed to obtain the alignment command or deviation command.

2. The identity authentication method based on vehicle networking technology according to claim 1, characterized in that, The continuous authentication and driving anomaly detection process is as follows: Obtain the driving time period of the target vehicle, and obtain the driving information of the target user during the driving time period; The driving information is processed based on machine learning algorithms to establish a driver driving baseline model. The driving deviation is obtained in real time based on the driver driving baseline model and the driving deviation is judged. If the driving deviation is less than the preset driving deviation threshold, it is judged to be in the maintenance state. If the driving deviation is greater than or equal to the preset driving deviation threshold, it is judged to be in the change state. The duration of the changed status is obtained, and the duration of the changed status is set as the driving change risk value. The driving change risk value is then processed to obtain a regular instruction or a change instruction.

3. The identity authentication method based on vehicle networking technology according to claim 2, characterized in that, When a change command is generated, the target user's own feature image set during the driving period is obtained. The own feature image set includes facial feature images and head feature images on the left side of the driving direction. It compares and analyzes its own feature image set with a pre-set own feature image set, obtains the proportion of images in its own feature image set whose similarity exceeds a preset similarity threshold, and sets this as the biometric ratio. It then performs discrimination processing on the biometric ratio. If the biometric ratio is less than the preset biometric ratio threshold, a driving change command is generated. If the biometric ratio is greater than or equal to the preset biometric ratio threshold, a regular driving command is generated.

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