Identity authentication method based on Internet of Vehicles technology

Abstract

The invention relates to the technical field of Internet of Vehicles, in particular to an identity authentication method based on the Internet of Vehicles technology, and aims to solve the problem of low identity authentication safety. According to the method, analysis is performed preliminarily from the perspective of the driving request of the target vehicle to improve the driving safety of the target vehicle, driving safety preliminary authentication of the target user is facilitated, and the timeliness of the authentication request of the Internet of Vehicles service of the target vehicle is analyzed to ensure whether the real-time performance of the authentication request is qualified or not, so that the user experience is improved. On the basis of qualification, analysis is carried out from the angle of combination of target user starting operation feature analysis and biological feature verification, so that the safety and reliability of the authentication system are effectively improved, and continuous authentication and driving anomaly detection operation are carried out in the driving process of the target vehicle; according to the method, identity authentication is converted from a static single process to dynamic continuous monitoring, a brand new protection dimension is provided for the security of the Internet of Vehicles, and the security of vehicle identity authentication is remarkably improved.

Description

Technical Field

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

[0002] With the rapid development of vehicle networking technology, the communication between vehicles and the outside world has become increasingly frequent, and the security issues of vehicles have become increasingly prominent. In the vehicle networking environment, vehicles need to communicate with cloud servers, other vehicles, roadside infrastructure, etc. to implement functions such as navigation, autonomous driving, and traffic information sharing. However, in these communication processes, how to ensure the identity legality of both communication parties and the security of communication data has become one of the key issues in the development of vehicle networking technology;

[0003] In the prior art, some vehicle networking systems adopt digital certificate authentication, but the certificate management is complex and there is a risk of being stolen. At the same time, some systems introduce biometric recognition, but a single biometric feature (such as fingerprint) is easy to be copied, and it is difficult to supervise the timeliness of information synchronization. Furthermore, there are problems of time synchronization and being easily intercepted, and it is difficult to authenticate users during driving. As a result, it is difficult to timely supervise and warn against the formation of substitute driving, leading to a reduction in vehicle driving safety;

[0004] In view of the above technical defects, a solution is proposed herein. Summary of the Invention

[0005] The purpose of the present invention is to provide an identity authentication method based on vehicle networking technology to solve the above-mentioned technical defects. The present invention initially analyzes from the perspective of the driving request of the target vehicle to improve the driving safety of the target vehicle, and at the same time helps to conduct a preliminary driving safety authentication for the target user. At the same time, the timeliness of the authentication request for the vehicle networking service of the target vehicle is analyzed to ensure whether the real-time performance of the authentication request is qualified. Based on the qualification, it is analyzed from the perspective of combining the analysis of the target user's startup operation characteristics and biometric verification, effectively improving the security and reliability of the authentication system. During the driving process of the target vehicle, continuous authentication and driving anomaly detection operations are carried out, that is, by changing the identity verification from a static single process to a dynamic continuous monitoring, a new protection dimension is provided for vehicle networking security, significantly enhancing the security of vehicle identity authentication, and also ensuring the user experience through intelligent analysis and adaptive mechanisms.

[0006] The purpose of the present invention can be achieved by the following technical solutions: 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, discriminate and process the request information. If a consistent instruction is obtained, proceed to Step 2; if an inconsistent instruction is obtained, output feedback;

[0008] Step 2: The biometric registration process when the target user first uses the target vehicle to obtain a multi-modal biometric template;

[0009] Step 3: The information timeliness analysis process when the target vehicle starts and accesses the vehicle networking service, that is, the time difference obtained is judged and processed. If a valid instruction is obtained, go to Step 4; if an invalid instruction is obtained, output feedback;

[0010] Step 4: The vehicle networking service security supervision process based on the combination of the target user's start operation feature analysis and biometric verification;

[0011] Step 5: The continuous authentication and driving anomaly detection operation based on the continuous driving process of the target vehicle, that is, the biometric ratio obtained is judged and processed, and the obtained driving change instruction or normal driving instruction is output for feedback.

[0012] Preferably, the driving request process for initializing the target vehicle 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, and the authentication center stores the vehicle ID and the user ID;

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

[0015] The target user inputs the user ID through the in-vehicle terminal, and the in-vehicle terminal encrypts the request information and sends it to the authentication center. After receiving the request information, the authentication center decrypts the request information, extracts the request information therein, and judges and processes the request information to obtain the evaluation output result of the request information. The evaluation output result includes consistent and inconsistent. 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 and processed to obtain a consistent instruction or an inconsistent instruction.

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

[0017] Based on the in-vehicle terminal, the biometric data of the driver is synchronously collected through the built-in camera and microphone, and at the same time, the operation feature data of the target user is collected. The operation feature data includes the door opening force, the ignition start duration, and the ignition operation force;

[0018] The collected biometric data and operation feature data are preprocessed and feature extracted to generate a multi-modal biometric template, and at the same time, the multi-modal biometric template is stored.

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

[0020] When the target vehicle starts and needs to access the vehicle networking service, the in-vehicle terminal sends a vehicle networking authentication request to the authentication center. The vehicle networking authentication request includes the identification information and timestamp of the vehicle.

[0021] After receiving the vehicle networking authentication request, the authentication center obtains the time difference between the timestamp of the sent vehicle networking authentication request and the moment when the vehicle networking authentication request is synchronized by the authentication center, and performs discriminant processing on the time difference to obtain a valid instruction or an invalid instruction.

[0022] Preferably, the vehicle networking 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 in-vehicle terminal, after receiving the dynamic verification code, the in-vehicle terminal prompts the target user to perform multimodal biometric verification to obtain an authorization instruction, an auxiliary defect instruction, or an abnormal instruction.

[0023] Preferably, the multimodal biometric verification process is as follows: The parameters in the biometric data of the target user are respectively assigned corresponding preset weights, the matching scores corresponding to the parameters in the biometric data are obtained, the sum value after multiplying the matching scores corresponding to the parameters by the corresponding preset weights is set as the biometric comprehensive score, and discriminant processing is performed on the biometric comprehensive score to obtain an unqualified instruction or a qualified instruction.

[0024] Preferably, while performing biometric verification, the operation feature data of the target user is simultaneously subjected to auxiliary verification and evaluation analysis. The specific auxiliary verification and evaluation analysis process is as follows:

[0025] Collect the operation sequence when the user starts the vehicle. The operation sequence includes the change in touch screen pressure and the steering wheel grip strength. Convert the operation sequence into a feature vector, calculate the similarity between the operation sequence and the preset operation sequence, and perform discriminant processing on the similarity to obtain a fitting instruction or a deviation instruction.

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

[0027] Obtain the driving period of the target vehicle and the driving information of the target user during the driving period.

[0028] Process the driving information based on the machine learning algorithm to establish a driver driving baseline model. Based on the driver driving baseline model, obtain the output driving deviation in real time, and perform discriminant processing on the driving deviation. If the driving deviation is less than the preset driving deviation threshold, it is determined to be in a maintained state. If the driving deviation is greater than or equal to the preset driving deviation threshold, it is determined to be in a changed state.

[0029] Obtain the continuous duration of the changed state, set the continuous duration of the changed state as the driving change risk value, and perform discriminant processing on the driving change risk value to obtain a normal instruction or a change instruction.

[0030] Preferably, when generating a change instruction, obtain the set of the target user's own feature images during the driving period, where the set of the target user's own feature images includes facial feature images and left-side head feature images in the driving direction.

[0031] Then, perform corresponding comparison and analysis on the set of the target user's own feature images and the pre-set set of the target user's own feature images, obtain the proportion of the corresponding images in the set of the target user's own feature images whose similarity exceeds the pre-set similarity threshold, and set it as the biometric ratio. Then, perform discrimination processing on the biometric ratio. If the biometric ratio is less than the pre-set biometric ratio threshold, generate a driving change instruction; if the biometric ratio is greater than or equal to the pre-set biometric ratio threshold, generate a normal driving instruction.

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

[0033] (1) The present invention initially analyzes from the perspective of the driving request of the target vehicle to improve the driving safety of the target vehicle, and at the same time helps to conduct a preliminary driving safety authentication for the target user. When the target user uses the target vehicle for the first time, a multi-modal biometric template is established to provide data support for subsequent authentication. At the same time, analyze the timeliness of the authentication request for the vehicle networking service of the target vehicle to ensure whether the real-time nature of the authentication request is qualified.

[0034] (2) Based on the qualified situation, the present invention analyzes from the perspective of combining the analysis of the target user's startup operation characteristics and biometric verification, effectively improving the security and reliability of the authentication system. During the driving process of the target vehicle, continuous authentication and driving anomaly detection operations are performed, that is, by changing the identity authentication from a static single process to a dynamic continuous monitoring, a new protection dimension is provided for vehicle networking security, significantly improving the security of vehicle identity authentication, and also ensuring the user experience through intelligent analysis and adaptive mechanisms. Description of the Drawings

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

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

[0037] Figure 2 is the reference diagram of the framework of the present invention. Detailed Embodiments

[0038] The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all the embodiments. All other embodiments obtained by those of ordinary skill in the art based on the embodiments of the present invention without creative efforts shall fall within the protection scope of the present invention.

[0039] As used herein, the mention of "embodiment" means that the specific features, structures, or characteristics described in connection with the embodiment may be included in at least one embodiment of the present invention. The appearance of this phrase at various positions in the specification does not necessarily refer to the same embodiment, nor is it an independent or alternative embodiment that is mutually exclusive with other embodiments. Those skilled in the art will explicitly and implicitly understand that the embodiments described herein may be combined with other embodiments;

[0040] Embodiment 1:

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

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

[0043] Step 2: The biometric registration process when the target user first uses the target vehicle to obtain a multi-modal biometric template;

[0044] Step 3: The information timeliness analysis process when the target vehicle starts and accesses the vehicle networking service, that is, perform discrimination processing on 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 networking service security supervision process based on the combination of the analysis of the target user's start operation characteristics and biometric verification, that is, perform discrimination processing on the comprehensive biometric score to obtain unqualified instructions and qualified instructions, perform discrimination processing on the obtained similarity to obtain fitting instructions and deviation instructions, and obtain authorization instructions, auxiliary defect instructions, or abnormal instructions based on the instruction interaction analysis;

[0046] Step 5: The continuous authentication and driving anomaly detection operation during the continuous driving process of the target vehicle, that is, perform discrimination processing on the obtained biometric ratio and output feedback of the obtained driving change instruction or normal driving instruction;

[0047] The specific initialization of the driving request process of the target vehicle 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 the vehicle ID and user ID;

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

[0050] The target user inputs the user ID through the in-vehicle terminal. The in-vehicle terminal encrypts the request information such as the user ID, vehicle ID, and vehicle location information and sends it to the authentication center. After receiving the request information, the authentication center decrypts the request information, extracts the request information such as the user ID, vehicle ID, and vehicle location information, and performs discrimination processing on the request information to obtain the evaluation output result of the request information. The evaluation output result includes consistent and inconsistent. The number of evaluation output results of the request information that are consistent is obtained, and discrimination processing is performed on the number of evaluation output results of the request information that are consistent. If the number of evaluation output results of the request information that are consistent is equal to the preset threshold, a consistent instruction is generated. If the number of evaluation output results of the request information that are consistent is not equal to the preset threshold, an inconsistent instruction is generated. When the inconsistent instruction is generated, the preset result corresponding to the inconsistent instruction is output;

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

[0052] For example: if the user ID is consistent with the pre-set user ID, it is determined to be consistent; if the user ID is inconsistent with the pre-set user ID, it is determined to be inconsistent; if the vehicle ID is consistent with the pre-set vehicle ID, it is determined to be consistent; if the vehicle ID is inconsistent with the pre-set vehicle ID, it is determined to be inconsistent; if the vehicle location information belongs to the preset area, it is determined to be consistent; if the vehicle location information does not belong to the preset area, it is determined to be inconsistent.

[0053] Embodiment 2:

[0054] Step 2: The biometric registration process when the target user first uses the target vehicle to obtain a multi-modal biometric template;

[0055] The biometric registration process is as follows:

[0056] Based on the in-vehicle terminal, biometric data such as the driver's facial image and voice sample are synchronously collected through devices such as built-in cameras and microphones;

[0057] At the same time, the operation feature data of the target user is collected. The operation feature data includes operation features such as the door opening force, ignition start duration, and ignition operation force;

[0058] The collected biometric data and operation feature data are pre-processed and feature extracted to generate a multi-modal biometric template, and at the same time, the multi-modal biometric template is stored;

[0059] Step 3: Information timeliness analysis process when the target vehicle starts and accesses the vehicle networking service, that is, discriminant processing is performed on the obtained time difference. If a valid instruction is obtained, go to Step 4; if an invalid instruction is obtained, output feedback.

[0060] The specific information timeliness analysis process is as follows:

[0061] When the target vehicle starts and needs to access the vehicle networking service, the in-vehicle terminal sends a vehicle networking authentication request to the authentication center. The vehicle networking authentication request includes vehicle identification information, timestamp, etc.

[0062] After receiving the vehicle networking authentication request, the authentication center obtains the time difference between the timestamp when the vehicle networking authentication request is sent and the moment when the authentication center synchronizes the vehicle networking authentication request, and performs discriminant processing on the time difference. If the time difference is less than or equal to the preset time difference threshold, it is determined as a valid instruction; if the time difference is greater than the preset time difference threshold, it is determined as an invalid instruction, and then the invalid instruction is responded to, and a preset feedback operation for the invalid instruction is performed to ensure the real-time nature of the authentication request.

[0063] Embodiment 3:

[0064] Step 4: Vehicle networking service security supervision process based on the combination of target user start operation feature analysis and biometric verification, that is, discriminant processing is performed on the comprehensive biometric score to obtain unqualified instructions and qualified instructions, discriminant processing is performed on the obtained similarity to obtain fitting instructions and deviation instructions, and authorization instructions or auxiliary defect instructions or abnormal instructions are obtained based on instruction interaction analysis.

[0065] The specific vehicle networking service security supervision process 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 in-vehicle terminal, after receiving the dynamic verification code, the in-vehicle terminal prompts the target user to perform multimodal biometric verification.

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

[0068] Parameters in the biometric data of the target user are respectively assigned corresponding preset weights, the matching scores corresponding to the parameters in the biometric data are obtained, the sum value after multiplying the matching scores corresponding to the parameters by the corresponding preset weights is set as the comprehensive biometric score, and discriminant processing is performed on the comprehensive biometric score: 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, and the similarity between the facial image of the target user and the preset facial image is 70 points out of 100, etc.;

[0070] While performing biometric verification, the operation feature data of the target user is simultaneously subjected to auxiliary verification and evaluation analysis. The specific process of auxiliary verification and evaluation analysis is as follows:

[0071] Collect the operation sequence when the user starts the vehicle. The operation sequence includes touch screen pressure changes, steering wheel grip strength, etc. Convert the operation sequence into a feature vector (such as One-Hot encoding), calculate the similarity between the operation sequence and the preset operation sequence, and perform discrimination processing on the similarity: If the similarity is greater than or equal to the preset similarity threshold, generate a fitting instruction; if the similarity is less than the preset similarity threshold, generate a deviation instruction;

[0072] Perform interactive analysis on the qualified instruction, unqualified instruction, fitting instruction, and deviation instruction:

[0073] If a qualified instruction and a fitting instruction are generated, an authorization instruction is obtained, that is, the authorization instruction is output to normally authorize 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 to prompt the target user that the operation habit has changed and suggest updating the multi-modal biometric template;

[0075] If an unqualified instruction and a fitting instruction or an unqualified instruction and a deviation instruction are generated, an abnormal instruction is obtained, that is, the abnormal instruction is output to trigger secondary verification of multi-modal biometric verification and auxiliary verification and evaluation analysis, and record the event to perform safety supervision and certification on the security of the vehicle networking service of the target vehicle, so as to improve the use safety of the vehicle networking service of the target vehicle;

[0076] At the same time, by combining the analysis of the target user's start-up operation behavior with biometric verification, this method provides an additional dimension of identity verification, effectively improving the security and reliability of the authentication system. The operation behavior features are difficult to imitate and change slowly dynamically, and can serve as a powerful supplement to biometric verification, especially providing key decision-making support in cases where the biometric part fails or there are disputes;

[0077] Step Five: Based on the continuous authentication and driving anomaly detection operation during the continuous driving process of the target vehicle, that is, perform discrimination processing on the obtained biometric ratio, and output and feedback the obtained driving change instruction or normal driving instruction;

[0078] The specific process of continuous authentication and driving anomaly detection operation is as follows:

[0079] When generating an authorization instruction, obtain the driving period of the target vehicle and the driving information of the target user during the driving period. The driving information includes steering angle, acceleration change, lane keeping duration, etc.;

[0080] Based on machine learning algorithms (such as LSTM), process the driving information to establish a driver driving baseline model. Based on the driver driving baseline model, obtain the output driving deviation in real time and perform discriminant processing on the driving deviation. If the driving deviation is less than the preset driving deviation threshold, it is determined to be in a maintenance state. If the driving deviation is greater than or equal to the preset driving deviation threshold, it is determined to be in a change state;

[0081] Obtain the duration of the change state, set the duration of the change state as the driving change risk value, and perform discriminant processing on the driving change risk value. If the driving change risk value is less than the preset driving change risk value threshold, generate a normal instruction. If the driving change risk value is greater than or equal to the preset driving change risk value threshold, generate a change instruction;

[0082] When generating a change instruction, obtain the set of self - feature images of the target user during the driving period. The set of self - feature images includes facial feature images, left - side head feature images in the driving direction, etc.;

[0083] And perform corresponding comparison and analysis on the set of self - feature images and the pre - set set of self - feature images, obtain the proportion of corresponding images in the set of self - feature images whose similarity exceeds the preset similarity threshold, and set it as the biometric ratio. Perform discriminant processing on the biometric ratio. If the biometric ratio is less than the preset biometric ratio threshold, generate a driving change instruction. If the biometric ratio is greater than or equal to the preset biometric ratio threshold, generate a normal driving instruction. When generating a driving change instruction, automatically trigger the identity re - authentication process, requiring the driver to re - perform biometric verification. When generating a normal driving instruction, continuously monitor the driving safety of the target user, changing the identity verification from a static single - time process to a dynamic continuous monitoring, providing a new protection dimension for vehicle - to - everything (V2X) security, significantly improving the security of vehicle identity authentication, and also ensuring the user experience through intelligent analysis and adaptive mechanisms;

[0084] In summary, the present invention initially analyzes from the perspective of the driving request of the target vehicle to improve the driving safety of the target vehicle, and at the same time helps to conduct a preliminary driving safety authentication for the target user. When the target user first uses the target vehicle, a multi-modal biometric template is established to provide data support for subsequent authentication. At the same time, the timeliness of the authentication request for the vehicle networking service of the target vehicle is analyzed to ensure whether the real-time nature of the authentication request is qualified. Based on the qualified situation, analysis is carried out from the perspective of combining the analysis of the target user's startup operation characteristics and biometric verification, effectively improving the security and reliability of the authentication system. During the driving process of the target vehicle, continuous authentication and driving anomaly detection operations are carried out, that is, by changing the identity authentication from a static single process to a dynamic continuous monitoring, a new protection dimension is provided for vehicle networking security, significantly enhancing the security of vehicle identity authentication, and also ensuring the user experience through intelligent analysis and adaptive mechanisms.

[0085] The setting of the threshold is for result comparison and analysis to determine whether it is good or bad. Regarding the value of the threshold, it is set and stored by combining the large model analysis of sample data and manual experience, and can also be appropriately adjusted according to seasonal or regular influencing conditions;

[0086] The magnitude of the coefficient is a specific value obtained by quantifying each parameter for subsequent comparison. Regarding the magnitude of the coefficient, it depends on the amount of sample data and the corresponding operating coefficients initially set by those skilled in the art for each group of sample data; as long as the proportional relationship between the parameter and the quantified value is not affected.

[0087] The above is only a preferred specific embodiment of the present invention, but the protection scope of the present invention is not limited thereto. Any person skilled in the art within the technical scope disclosed by the present invention, according to the technical solution and inventive concept of the present invention, making equivalent substitutions or changes, should be covered by the protection scope of the present invention.

Claims

1. An identity authentication method based on vehicle networking technology, characterized in that, It includes the following steps: Step 1: Initialize the driving request process of the target vehicle, that is, discriminate and process the request information. If a consistent instruction is obtained, go to Step 2; if an inconsistent instruction is obtained, output feedback. Step 2: The biometric registration process when the target user first uses the target vehicle to obtain a multi-modal biometric template. Step 3: The information timeliness analysis process when the target vehicle starts and accesses the vehicle networking service, that is, discriminate and process the obtained time difference. If a valid instruction is obtained, go to Step 4; if an invalid instruction is obtained, output feedback. Step 4: The vehicle networking service security supervision process based on the combination of the target user's start operation feature analysis and biometric verification. Step 5: The continuous authentication and driving anomaly detection operation based on the continuous driving process of the target vehicle, that is, discriminate and process the obtained biometric ratio, and output feedback of the obtained driving change instruction or normal driving instruction.

2. The identity authentication method based on vehicle networking technology according to claim 1, characterized in that, The initialization of the driving request process of the target vehicle is as follows: The authentication center assigns a unique vehicle ID to the target vehicle and a unique user ID to the target user, and the authentication center stores the vehicle ID and user ID. When the target user initiates an identity authentication request, the identity authentication request process is as follows: The target user inputs the user ID through the in-vehicle terminal. The in-vehicle terminal encrypts the request information and sends it to the authentication center. After receiving the request information, the authentication center decrypts the request information, extracts the request information therein, and discriminates and processes the request information to obtain the evaluation output result of the request information. The evaluation output result includes consistent and inconsistent. Obtain the number of consistent evaluation output results of the request information, and discriminate and process the number of consistent evaluation output results of the request information to obtain a consistent instruction or an inconsistent instruction.

3. An identity authentication method based on vehicle networking technology according to claim 1, characterized in that, The biometric registration process is as follows: Based on the in-vehicle terminal, synchronously collect the driver's biometric data through the built-in camera and microphone, and at the same time collect the target user's operation feature data. The operation feature data includes the door opening force, ignition start duration, and ignition operation force. Preprocess and extract the collected biometric data and operation feature data to generate a multi-modal biometric template, and at the same time store the multi-modal biometric template.

4. The identity authentication method based on vehicle networking technology according to claim 1, wherein The information timeliness analysis process is as follows: When the target vehicle starts and needs to access the vehicle networking service, the in-vehicle terminal sends a vehicle networking authentication request to the authentication center. The vehicle networking authentication request includes the identification information and timestamp of the vehicle. After receiving the vehicle networking authentication request, the authentication center obtains the time difference between the timestamp of sending the vehicle networking authentication request and the time when the authentication center synchronizes the vehicle networking authentication request, and discriminates and processes the time difference to obtain a valid instruction or an invalid instruction.

5. The identity authentication method based on vehicle networking technology according to claim 1, characterized in that, The vehicle networking service security supervision process is as follows: Randomly generate a dynamic verification code based on the identification information of the target vehicle and send the dynamic verification code to the in-vehicle terminal. After receiving the dynamic verification code, the in-vehicle terminal prompts the target user to perform multi-modal biometric verification to obtain an authorization instruction, an auxiliary defect instruction, or an abnormal instruction.

6. The identity authentication method based on vehicle networking technology according to claim 5, characterized in that, The multi-modal biometric verification process is as follows: The parameters in the biometric data of the target user are respectively assigned corresponding preset weights, the matching scores corresponding to the parameters in the biometric data are obtained, the sum value after multiplying the matching scores corresponding to the parameters by the corresponding preset weights is set as the comprehensive biometric score, and the comprehensive biometric score is subjected to discrimination processing to obtain a non-conforming instruction or a conforming instruction.

7. An identity authentication method based on vehicle networking technology according to claim 6, characterized in that, During biometric verification, the operation feature data of the target user is simultaneously subjected to auxiliary verification and evaluation analysis. The specific auxiliary verification and evaluation analysis process is as follows: Collect the operation sequence when the user starts the vehicle. The operation sequence includes the change in touch screen pressure and the grip strength of the steering wheel. Convert the operation sequence into a feature vector, calculate the similarity between the operation sequence and the preset operation sequence, and perform discrimination processing on the similarity to obtain a fitting instruction or a deviation instruction.

8. An identity authentication method based on vehicle networking technology according to claim 1, characterized in that, The continuous authentication and driving anomaly detection operation process is as follows: Obtain the driving time period of the target vehicle and the driving information of the target user during the driving time period; Based on the machine learning algorithm, process the driving information to establish a driver driving baseline model. Based on the driver driving baseline model, obtain the output driving deviation in real time, and perform discrimination processing on the driving deviation. If the driving deviation is less than the preset driving deviation threshold, it is determined to be in a maintained state. If the driving deviation is greater than or equal to the preset driving deviation threshold, it is determined to be in a changed state; Obtain the continuous duration of the changed state, set the continuous duration of the changed state as the driving change risk value, and perform discrimination processing on the driving change risk value to obtain a normal instruction or a change instruction.

9. The identity authentication method based on vehicle networking technology according to claim 8, characterized in that, When a change instruction is generated, obtain the set of self-feature images of the target user during the driving time period. The set of self-feature images includes facial feature images and head feature images on the left side of the driving direction; And perform corresponding comparison and analysis on the set of self-feature images and the pre-set set of self-feature images, obtain the proportion of the images in the set of self-feature images whose similarity exceeds the preset similarity threshold, and set it as the biometric ratio. Perform discrimination processing on the biometric ratio. If the biometric ratio is less than the preset biometric ratio threshold, generate a driving change instruction. If the biometric ratio is greater than or equal to the preset biometric ratio threshold, generate a normal driving instruction.

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