A data encryption communication method and system for a vehicle-mounted Android terminal

Abstract

The application discloses a data encryption communication method and system for a vehicle-mounted Android terminal, and relates to the technical field of digital information transmission.The method comprises the following steps: receiving multiple communication data of the vehicle-mounted Android terminal, and performing data feature analysis and encryption resource monitoring; performing encryption load adaptation analysis on multiple data feature parameters and multiple encryption resource state parameters to obtain a load resource matching coefficient; performing encryption scheme optimization based on the data feature parameters and the multiple encryption resource state parameters to obtain an encryption scheme set; and determining an optimal encryption scheme to implement differentiated adaptive encryption processing on the multiple communication data.The technical problem that the existing vehicle-mounted encryption scheme cannot be intelligently adjusted according to a communication environment and a system resource state, which leads to the influence of communication efficiency and the inability to fully guarantee security when resources are in short supply, is solved.

Description

Technical Field

[0001] This application relates to the field of digital information transmission technology, specifically to a data encryption communication method and system for vehicle-mounted Android terminals. Background Technology

[0002] With the development of vehicle networking technology, the in-vehicle Android terminal serves as the core hub for information interaction between the vehicle and the outside world, carrying multiple functions such as navigation, entertainment, vehicle control, remote diagnostics, and data transmission of user privacy.

[0003] However, traditional in-vehicle encryption solutions typically employ fixed encryption strategies, which cannot be intelligently adjusted according to the actual communication environment and system resource status. This results in communication efficiency being affected when resources are scarce, while security cannot be fully guaranteed when resources are abundant. Summary of the Invention

[0004] This application provides a data encryption communication method and system for in-vehicle Android terminals, which solves the technical problem that existing in-vehicle encryption schemes cannot intelligently adjust according to the communication environment and system resource status, resulting in communication efficiency being affected and security not being fully guaranteed when resources are scarce.

[0005] The technical solution to the above-mentioned technical problems in this application is as follows:

[0006] Firstly, this application provides a data encryption communication method for in-vehicle Android terminals, the method comprising:

[0007] Receive multi-channel communication data from an in-vehicle Android terminal, perform data feature analysis on the multi-channel communication data to obtain multiple data feature parameters, and monitor encrypted resources of the in-vehicle Android terminal to obtain multiple encrypted resource status parameters;

[0008] Encryption load adaptation analysis is performed on the multiple data feature parameters and multiple encrypted resource status parameters to obtain load resource matching coefficients;

[0009] Based on the load resource matching coefficient, and based on the multiple data feature parameters and multiple encryption resource status parameters, the encryption scheme of the multi-channel communication data is optimized to obtain an encryption scheme set;

[0010] Based on the set of encryption schemes, the optimal encryption scheme is determined, and differentiated adaptive encryption processing is applied to the multi-channel communication data.

[0011] Secondly, this application provides a data encryption communication system for in-vehicle Android terminals, comprising:

[0012] The communication data analysis module is used to receive multi-channel communication data from the vehicle-mounted Android terminal, perform data feature analysis on the multi-channel communication data to obtain multiple data feature parameters, and monitor the encrypted resources of the vehicle-mounted Android terminal to obtain multiple encrypted resource status parameters.

[0013] The load adaptation analysis module is used to perform encrypted load adaptation analysis on the multiple data feature parameters and multiple encrypted resource status parameters to obtain the load resource matching coefficient.

[0014] The encryption scheme optimization module is used to optimize the encryption scheme of the multi-channel communication data based on the load resource matching coefficient, the multiple data feature parameters, and the multiple encryption resource status parameters, to obtain an encryption scheme set.

[0015] The optimal solution acquisition module determines the optimal encryption solution based on the set of encryption solutions and performs differentiated adaptive encryption processing on the multi-channel communication data.

[0016] This application provides one or more technical solutions, which have at least the following technical effects or advantages:

[0017] This application provides a data encryption communication method and system for vehicle-mounted Android terminals. First, it receives multiple communication data streams from the vehicle-mounted Android terminal, obtaining multiple data characteristic parameters. It also monitors the encryption resources of the vehicle-mounted Android terminal, obtaining multiple encryption resource status parameters. Through dual analysis of data characteristics and encryption resource status, it achieves a comprehensive understanding of the communication data and terminal resources. Second, it performs encryption load adaptation analysis on the multiple data characteristic parameters and multiple encryption resource status parameters to obtain a load-resource matching coefficient, which measures the degree of matching between current encryption requirements and terminal resource supply. Third, based on the load-resource matching coefficient and the multiple data characteristic parameters and multiple encryption resource status parameters, it optimizes the encryption scheme for the multiple communication data streams, obtaining a set of encryption schemes. By considering data characteristics and resource conditions, it generates multiple possible combinations of encryption strategies, avoiding the limitations of a single scheme. Finally, based on the set of encryption schemes, the optimal encryption scheme is determined, and the most suitable encryption method is dynamically selected according to the actual situation. Different encryption strategies are adopted for different types of communication data, thereby ensuring communication security while effectively improving encryption efficiency and avoiding resource waste or security risks caused by fixed encryption strategies. This achieves intelligent and refined management of communication data encryption for vehicle-mounted Android terminals.

[0018] Through the above technical solution, this application effectively solves the technical challenge of fixing encryption strategies in vehicle environments, achieving a dynamic balance between security and efficiency. It is suitable for applications with limited resources and diverse security requirements in vehicle communication scenarios. Through intelligent environmental perception and strategy optimization, the encryption strength can be automatically adjusted according to actual operating conditions, ensuring the secure transmission of critical data while avoiding unnecessary waste of computing resources. Attached Figure Description

[0019] To more clearly illustrate the technical solutions in the embodiments of this application, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0020] Figure 1 This is a flowchart illustrating a data encryption communication method for an in-vehicle Android terminal provided in an embodiment of this application;

[0021] Figure 2 This is a schematic diagram of a data encryption communication system for an in-vehicle Android terminal provided in an embodiment of this application.

[0022] The components represented by each number in the attached diagram are explained below:

[0023] The module includes a communication data analysis module 11, a load adaptation analysis module 12, an encryption scheme optimization module 13, and an optimal scheme acquisition module 14. Detailed Implementation

[0024] This application provides a data encryption communication method and system for in-vehicle Android terminals, which addresses the technical problem that existing in-vehicle encryption schemes cannot intelligently adjust according to the communication environment and system resource status, resulting in communication efficiency being affected and security not being fully guaranteed when resources are scarce.

[0025] The technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, and not all embodiments. Based on the embodiments of this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.

[0026] In the description of this application, the terms "first" and "second" are used for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the number of indicated technical features. Thus, a feature defined as "first" or "second" may explicitly or implicitly include one or more of the stated features. In the description of this application, "multiple" means two or more, unless otherwise explicitly specified.

[0027] In the description of this application, the term "for example" is used to mean "used as an example, illustration, or description." Any embodiment described as "for example" in this application is not necessarily to be construed as being more preferred or advantageous than other embodiments. The following description is provided to enable any person skilled in the art to make and use this application. Details are set forth in the following description for purposes of explanation. It should be understood that those skilled in the art will recognize that this application can be made without using these specific details. In other instances, well-known structures and processes will not be described in detail to avoid unnecessarily obscuring the description of this application. Therefore, this application is not intended to be limited to the embodiments shown, but is consistent with the broadest scope of the principles and features disclosed in this application.

[0028] Example 1, as Figure 1 As shown in the figure, this application provides a data encryption communication method for vehicle-mounted Android terminals, including:

[0029] S10: Receive multi-channel communication data from the vehicle-mounted Android terminal, perform data feature analysis on the multi-channel communication data to obtain multiple data feature parameters, and monitor the encrypted resources of the vehicle-mounted Android terminal to obtain multiple encrypted resource status parameters.

[0030] In this embodiment, firstly, multiple communication data from the vehicle-mounted Android terminal are received, including various information interactions generated during vehicle operation, such as navigation map data, vehicle status diagnostic data, user privacy data, and remote control command data.

[0031] Secondly, data feature analysis is performed on the multi-channel communication data, extracting data feature parameters for each channel. These parameters include data transmission rate, data sensitivity level, data integrity verification requirements, and data transmission cycle. Simultaneously, encrypted resources are monitored on the in-vehicle Android terminal. Encrypted resources refer to the hardware and software resources used by the terminal to perform encryption operations; multiple encrypted resource status parameters are obtained through monitoring.

[0032] Specifically, step S10 in the method includes:

[0033] Extract the first communication data from the multi-channel communication data, input the first communication data into a pre-built data feature recognizer, perform data feature analysis, and obtain the first data feature parameter;

[0034] Following the method of obtaining the first data feature parameter, data feature analysis is performed on the remaining communication data to obtain multiple data feature parameters;

[0035] The encrypted resources of the vehicle-mounted Android terminal are monitored to obtain multiple encrypted resource status parameters, including CPU processing load, memory usage, encryption module load status, and terminal temperature status.

[0036] In this embodiment, firstly, any one of the multiple communication data streams is selected as the first communication data stream, for example, navigation map data is selected as the first communication data stream. This first communication data stream is then input into a pre-built data feature recognizer, which is trained using a deep learning model and can automatically identify and extract data features. After analyzing the first communication data stream through the data feature recognizer, first data feature parameters are obtained, including information such as the transmission rate, sensitivity level, integrity verification requirements, and transmission cycle of the data stream.

[0037] Secondly, following the same approach, data feature analysis is performed on the remaining communication data, such as vehicle status diagnostic data, user privacy data, and remote control command data, to obtain multiple data feature parameters corresponding to the multiple communication data.

[0038] Furthermore, during the data feature analysis process, encrypted resource monitoring is simultaneously performed on the in-vehicle Android terminal. By calling the API interface provided by the terminal system, information such as CPU processing load, memory usage, encryption module load status, and terminal temperature status is collected in real time and combined into multiple encrypted resource status parameters.

[0039] The construction process of the data feature recognizer includes:

[0040] Collect historical vehicle communication data, construct a sample communication dataset based on the historical vehicle communication data, and perform data feature annotation on each sample communication data in the sample communication dataset to obtain a sample data feature parameter set;

[0041] A data feature recognizer is built based on deep learning;

[0042] Using the sample communication dataset as input and the sample data feature parameter set as labels, the data feature recognizer is trained until convergence, thus completing the construction.

[0043] In this embodiment, historical vehicle communication data is first collected, including communication records of in-vehicle Android terminals under different vehicle models and usage scenarios, including navigation data, diagnostic data, and user data generated under various operating conditions such as normal driving, remote control, and entertainment interaction. A sample communication dataset is then constructed based on the historical data to ensure the diversity and representativeness of the dataset, covering various data characteristics of vehicle communication.

[0044] Subsequently, each sample communication data in the sample communication dataset is manually or semi-automatically labeled with data features. The labeling content includes the data transmission rate range, such as low speed <1Mbps, medium speed 1-10Mbps, and high speed >10Mbps. At the same time, the data sensitivity level, data integrity verification requirements, and data transmission cycle are also labeled, such as real-time transmission, minute-level cycle transmission, and hour-level cycle transmission, forming a sample data feature parameter set.

[0045] Secondly, a data feature recognizer is constructed based on deep learning technology. A hybrid model architecture combining convolutional neural network (CNN) and long short-term memory network (LSTM) is adopted. CNN is used to extract local features of data, such as protocol identifiers in data packet headers and specific field structures of data segments. LSTM is used to capture temporal features of data, such as dynamic changes in transmission rate and time patterns of periodic transmission.

[0046] Finally, using the sample communication dataset as input, and the parameters in the sample data feature parameter set as labels, a data feature recognizer is trained using the backpropagation algorithm. One to three hidden layers are set, with the number of nodes in each layer adjusted experimentally (e.g., 64, 32). The ReLU activation function is chosen. The output layer generally does not use an activation function; if the output takes two nodes, continuous values ​​are directly output. During training, the model's weights and biases are continuously adjusted, and the cross-entropy loss function is used to calculate the error between the predicted and labeled values. Training stops when the error converges to a preset threshold (e.g., 0.001) and the model's accuracy on the validation set reaches 95% or higher, completing the construction of the data feature recognizer.

[0047] S20: Perform encryption load adaptation analysis on the multiple data feature parameters and multiple encryption resource status parameters to obtain the load resource matching coefficient;

[0048] In this embodiment, after acquiring multiple data feature parameters and multiple encryption resource status parameters, an encryption load adaptation analysis is performed on both to quantify the degree of adaptation between the current encryption demand and the terminal resource supply, thereby obtaining the load resource matching coefficient. The load resource matching coefficient is a key indicator for measuring the balance between the encryption task's demand for terminal resources and the actual encryption resources that the terminal can provide. Its value range can be set to [0,1]. The closer it is to 1, the higher the matching degree between the current encryption load and the resource status; the closer it is to 0, the lower the matching degree, which may indicate insufficient resources or wasted resources.

[0049] Specifically, step S20 in the method includes:

[0050] The encrypted resource evaluator is invoked to predict the encrypted resource demand based on the multiple data feature parameters, thereby obtaining multiple ideal encrypted resource state parameters. The encrypted resource evaluator is trained based on historical data feature parameters and corresponding ideal resource state parameters.

[0051] Extract a first ideal encrypted resource state parameter from the plurality of ideal encrypted resource state parameters, and extract the corresponding first encrypted resource state parameter from the plurality of encrypted resource state parameters;

[0052] Calculate the parameter ratio between the first encrypted resource state parameter and the first ideal encrypted resource state parameter to obtain the first parameter matching degree, wherein when the parameter ratio is greater than 1, the first parameter matching degree is set to 1;

[0053] Calculate the ratio of the remaining encrypted resource state parameters to the corresponding ideal encrypted resource state parameters in turn to obtain multiple parameter matching degrees;

[0054] The weights of each encrypted resource status parameter are set, and the matching degrees of the multiple parameters are weighted and summed based on the weights of each encrypted resource status parameter to obtain the load resource matching coefficient. The load resource matching coefficient is obtained by multiplying the matching degree of each encrypted resource status parameter by its weight and then summing the results.

[0055] In this embodiment of the application, firstly, a pre-trained encrypted resource evaluator is retrieved. This evaluator is trained based on multiple historical data feature parameters and corresponding ideal resource state parameters, and can predict the ideal resource configuration that meets the encryption requirements based on the input data feature parameters.

[0056] For example, the multiple data feature parameters obtained in the above steps are input into the encryption resource evaluator. For example, the transmission rate of navigation map data is 5Mbps, the sensitivity level is medium, the integrity verification requirement is low, and the transmission cycle is 5 minutes / time. The corresponding ideal CPU processing load required for data encryption is 30%, the ideal memory utilization rate is 25%, the ideal encryption module load state is 40%, and the ideal terminal temperature state is 45℃, which are combined into multiple ideal encryption resource state parameters.

[0057] Secondly, select any one of the multiple ideal encrypted resource status parameters as the first ideal encrypted resource status parameter, for example, select an ideal CPU processing load of 30%. Simultaneously, extract the first encrypted resource status parameter corresponding to the first ideal encrypted resource status parameter from the multiple encrypted resource status parameters monitored in step S10, i.e., the current actual CPU processing load, such as 25%. Calculate the parameter ratio between the first encrypted resource status parameter and the first ideal encrypted resource status parameter, i.e., 25% / 30%≈0.83, which is the first parameter matching degree.

[0058] If the actual monitored encrypted resource status parameters are greater than the ideal value, for example, the current CPU processing load is 40%, while the ideal value is 30%, the parameter ratio is 40% / 30%≈1.33, which is greater than 1. In order to avoid excessive resource consumption from negatively impacting terminal performance, the first parameter matching degree in this case is set to 1, indicating that the current resources can fully meet the encryption requirements of this dimension.

[0059] Following the method described above, the parameter ratios of the remaining encrypted resource status parameters to the corresponding ideal encrypted resource status parameters are calculated sequentially. For example, the memory occupancy rate, encryption module load status, and terminal temperature status yield corresponding parameter matching degrees of 0.8, 0.875, and 0.933, respectively.

[0060] Finally, weights are assigned to each encrypted resource status parameter, and the resulting matching degrees of multiple parameters are weighted and summed based on these weights. Considering the varying degrees of impact of different encrypted resource status parameters on the encryption task, and the higher the weight of important parameters, different weights are assigned to each parameter matching degree. The specific weights for each parameter matching degree are determined by the expert group. The load resource matching coefficient is obtained by multiplying the matching degree of each encrypted resource status parameter by its corresponding weight and then summing the results. For example, CPU processing load and encryption module load status have a significant impact on encryption efficiency, and their weights can be set to 0.3 and 0.3 respectively; memory occupancy and terminal temperature status have relatively less impact, and their weights can be set to 0.2 and 0.2 respectively.

[0061] For example, the load resource matching coefficient = (0.83×0.3) + (0.8×0.2) + (0.875×0.3) + (0.933×0.2) ≈ 0.8581, which indicates that the current encryption resource status of the vehicle Android terminal has a high degree of matching with the encryption requirements of multi-channel communication data.

[0062] S30: Based on the load resource matching coefficient, and based on the multiple data feature parameters and multiple encryption resource status parameters, optimize the encryption scheme of the multi-channel communication data to obtain an encryption scheme set;

[0063] In this embodiment, after obtaining the load resource matching coefficient, the encryption scheme for multi-channel communication data is optimized by combining multiple data feature parameters and multiple encryption resource status parameters, generating an encryption scheme set containing multiple candidate encryption strategies. Specifically, the encryption scheme optimization process needs to comprehensively consider the security requirements of the data itself and the actual carrying capacity of the terminal resources to avoid the problem of "over-encryption" leading to low efficiency or "under-encryption" causing security risks when a single encryption scheme fluctuates during resource periods.

[0064] Specifically, step S30 in the method includes:

[0065] With communication efficiency and communication security as the guiding principles respectively, the multi-channel communication data is randomly encrypted twice to obtain a first efficiency-oriented encryption scheme and a first security-oriented encryption scheme. Each encryption scheme includes multiple encryption strategy configurations corresponding to the multi-channel communication data.

[0066] Obtain the efficiency benchmark parameters and security benchmark parameters of the preset encryption strategy set, and calculate the encryption fitness of the first efficiency-oriented encryption scheme and the first security-oriented encryption scheme respectively;

[0067] Based on the load resource matching coefficient, the first efficiency-oriented encryption scheme and the first security-oriented encryption scheme are simultaneously optimized to generate an encryption scheme set.

[0068] In this embodiment, firstly, encryption strategies are initially allocated for multi-channel communication data from two different dimensions: communication efficiency and communication security. When communication efficiency is the primary consideration, encryption strategies with low computational complexity and short encryption time are prioritized. For example, a lightweight AES-128 encryption algorithm can be allocated to navigation map data with high transmission rates but low sensitivity levels. When communication security is the primary consideration, encryption strategies with high encryption strength and strong resistance to attacks are prioritized. For example, a combination strategy of RSA-2048 asymmetric encryption algorithm and SHA-256 hash verification is allocated to user privacy data with high sensitivity levels. Through the above methods, a first efficiency-oriented encryption scheme and a first security-oriented encryption scheme are generated, each containing configuration information such as the encryption algorithm, key length, and encryption mode for the multi-channel communication data.

[0069] Secondly, obtain the security and efficiency benchmark parameters of each basic encryption strategy in the preset encryption strategy set, such as encryption time and throughput under standard conditions. Using these benchmark parameters as a reference, calculate the encryption fitness of the first efficiency-oriented encryption scheme. This fitness is obtained by comprehensively evaluating indicators such as the average encryption time and overall data throughput improvement rate of all encryption strategies in the scheme. Similarly, calculate the encryption fitness of the first security-oriented encryption scheme by evaluating indicators such as the average anti-attack strength of the encryption strategies in the scheme and the rationality of the key update cycle.

[0070] Finally, the load resource matching coefficient is used as a key adjustment factor to simultaneously optimize the first efficiency-oriented encryption scheme and the first security-oriented encryption scheme. If the load resource matching coefficient is high, such as greater than 0.8, it indicates that the terminal resources are sufficient, and the weight of the security-oriented scheme can be appropriately increased, adding encryption layers for some highly sensitive data. If the load resource matching coefficient is low, such as less than 0.5, the weight of the efficiency-oriented scheme needs to be increased, and the encryption strategy for some non-critical data needs to be downgraded, for example, switching the encryption algorithm of some data from RSA to ECC to reduce resource consumption.

[0071] After multiple rounds of iterative adjustments, a set of encryption schemes was finally generated, which included 2-3 candidate encryption schemes with the best overall performance. Each scheme was labeled with its expected encryption efficiency, security level, and estimated resource consumption under the current resource conditions.

[0072] This includes obtaining the efficiency benchmark parameters and security benchmark parameters of the preset encryption strategy set, and calculating the encryption fitness of the first efficiency-oriented encryption scheme and the first security-oriented encryption scheme, respectively, including:

[0073] Based on the encryption strategy configuration corresponding to each communication data in the first efficiency-oriented encryption scheme, the efficiency benchmark parameters and security benchmark parameters corresponding to the encryption strategy used by each communication data are extracted from the efficiency benchmark parameters and security benchmark parameters of the preset encryption strategy set.

[0074] Calculate the average efficiency benchmark parameter of all encryption strategies in the first efficiency-oriented encryption scheme to obtain the efficiency evaluation value, and calculate the average security benchmark parameter of all encryption strategies as the security evaluation value;

[0075] Obtain the security weight coefficient and the efficiency weight coefficient, and perform a weighted summation calculation on the efficiency evaluation value and the security evaluation value based on the security weight coefficient and the efficiency weight coefficient to obtain the encryption fitness of the first efficiency-oriented encryption scheme, wherein the encryption fitness is equal to the product of the security evaluation value and the security weight coefficient plus the product of the efficiency evaluation value and the efficiency weight coefficient.

[0076] The encryption fitness of the first security-oriented encryption scheme is calculated in accordance with the method used to obtain the encryption fitness of the first efficiency-oriented encryption scheme.

[0077] In this embodiment, firstly, efficiency and security baseline parameters corresponding to the encryption strategies used by each communication data path in the first efficiency-oriented encryption scheme are extracted from a preset encryption strategy set. For example, if a navigation data path uses the AES-128 encryption algorithm, the efficiency baseline parameters of the algorithm, such as standard encryption time of 0.5ms / KB and standard throughput of 80MB / s, are obtained from the preset strategy set, along with its security baseline parameters, such as resistance to brute-force attacks of 10^18 years and a key space of 128 bits. This process is performed on all encryption strategies in the first efficiency-oriented encryption scheme to obtain a list of efficiency and security baseline parameters corresponding to each data path.

[0078] Secondly, the efficiency and security evaluation values ​​of the first efficiency-oriented encryption scheme are calculated. The efficiency evaluation value is obtained by averaging the efficiency benchmark parameters of all encryption strategies. For example, if the scheme contains 3 data streams with encryption times of 0.5ms / KB, 0.6ms / KB, and 0.4ms / KB respectively, the average encryption time is (0.5 + 0.6 + 0.4) / 3 = 0.5ms / KB. The overall efficiency evaluation value is calculated by combining this with the average throughput improvement rate, etc. The security evaluation value is obtained by averaging the security benchmark parameters of all encryption strategies, such as average attack resistance and average key length, and is then used to calculate the overall security evaluation value.

[0079] Then, the security weight coefficient and efficiency weight coefficient are obtained. Based on these coefficients, the efficiency evaluation value and the security evaluation value are weighted and summed to obtain the encryption fitness of the first efficiency-oriented encryption scheme. Since this scheme is efficiency-oriented, the efficiency evaluation value has a higher weight than the security evaluation value. For example, if the efficiency evaluation value has a weight of 0.7 and the security evaluation value has a weight of 0.3, the standardized score of the efficiency evaluation value is 0.85, and the standardized score of the security evaluation value is 0.70, then the encryption fitness = 0.85 × 0.7 + 0.70 × 0.3 = 0.805.

[0080] Furthermore, the same process is used to calculate the encryption fitness of the first security-oriented encryption scheme. First, the efficiency and security benchmark parameters corresponding to each data encryption strategy in the scheme are extracted, the average efficiency benchmark parameter and the average security benchmark parameter are calculated, and then a weighted summation is performed.

[0081] For example, the weight of the security assessment value is 0.7, which is higher than the weight of the efficiency assessment value of 0.3. The standardized score of the security assessment value is 0.90, and the standardized score of the efficiency assessment value is 0.65. Then the encryption fitness = 0.90 × 0.7 + 0.65 × 0.3 = 0.825.

[0082] Through the above calculation process, the overall performance of the two preliminary schemes under their respective guidance is quantified.

[0083] Further, security weight coefficients and efficiency weight coefficients are obtained. Based on the security weight coefficients and efficiency weight coefficients, the efficiency evaluation value and the security evaluation value are weighted and summed to obtain the encryption fitness of the first efficiency-oriented encryption scheme, including:

[0084] Obtain the preset security threat level threshold and the current communication environment threat level monitored by the vehicle-mounted Android terminal;

[0085] Calculate the ratio of the current communication environment threat level to the security threat level threshold to obtain the security weight coefficient, and obtain the efficiency weight coefficient based on the security weight coefficient;

[0086] Using the security weight coefficient and efficiency weight coefficient, the security evaluation value and efficiency evaluation value are weighted and summed to obtain the encryption fitness of the first efficiency-oriented encryption scheme, wherein the encryption fitness is equal to the product of the security evaluation value and the security weight coefficient plus the product of the efficiency evaluation value and the efficiency weight coefficient.

[0087] In this embodiment, threat level data of the current communication environment is first obtained from the communication environment monitoring module of the vehicle-mounted Android terminal. This data can be obtained comprehensively through multiple methods. The vehicle-mounted Android terminal first detects the type and status of the current network connection. For example, public WiFi networks have a higher threat level than dedicated mobile networks. At the same time, it monitors the number of abnormal traffic and suspicious connection requests in the network.

[0088] Simultaneously, the system retrieves a preset security threat threshold, which is pre-configured by the system based on the security requirements of the vehicle communication scenario. For example, the security threat threshold is set to 0.6 in a typical urban road scenario. The ratio of the current communication environment threat level to the security threat threshold is calculated to obtain the threat ratio.

[0089] For example, if the current communication environment threat level is 0.75 and the security threat threshold is 0.6, then the threat ratio = 0.75 / 0.6 = 1.25. A threat ratio greater than 1 indicates that the current environment threat level is higher than the baseline, requiring greater attention to security. The threat ratio is normalized to the [0,1] interval to obtain a security weighting coefficient. For instance, a threat ratio of 1.25 can be mapped to a security weighting coefficient of 0.8 using a function.

[0090] Furthermore, the efficiency weighting coefficient is obtained by subtracting the safety weighting coefficient from 1, i.e., efficiency weighting coefficient = 1 - safety weighting coefficient. When the safety weighting coefficient is 0.8, the efficiency weighting coefficient = 1 - 0.8 = 0.2.

[0091] Subsequently, the security and efficiency evaluation values ​​of the first efficiency-oriented encryption scheme are weighted and summed using the adjusted security and efficiency weight coefficients. For example, if the standardized score of the security evaluation value is 0.70, the standardized score of the efficiency evaluation value is 0.85, the security weight coefficient is 0.8 (truncated to 1.25), and the efficiency weight coefficient is 0.2, then the encryption fitness = 0.70 × 0.8 + 0.85 × 0.2 = 0.73, thus obtaining the actual encryption fitness of the scheme under the current environmental threats.

[0092] Furthermore, based on the load resource matching coefficient, the first efficiency-oriented encryption scheme and the first security-oriented encryption scheme are simultaneously optimized to generate an encryption scheme set, including:

[0093] The total amount of communication data is obtained by counting the number of multiple communication data streams, and the number of iterations for optimization is determined based on the load resource matching coefficient and the total amount of communication data.

[0094] Within the first efficiency-oriented encryption scheme, communication data of the number of iterations is randomly selected as the first selected optimization dataset. The encryption strategy of the first selected optimization dataset is configured according to the encryption strategy of the first security-oriented encryption scheme. The strategy is adjusted within the first efficiency-oriented encryption scheme to obtain the first adjusted efficiency-oriented encryption scheme.

[0095] Within the first security-oriented encryption scheme, communication data of the number of iterations is randomly selected as the second selected optimization dataset. The encryption strategy of the second selected optimization dataset within the first efficiency-oriented encryption scheme is configured, and the strategy is adjusted within the first security-oriented encryption scheme to obtain the first adjusted security-oriented encryption scheme.

[0096] Repeat the strategy adjustment, fitness calculation and synchronization optimization until the convergence optimization number is reached. Then, summarize all the efficiency-oriented encryption schemes and security-oriented encryption schemes generated during the optimization process to obtain the encryption scheme set.

[0097] In this embodiment of the application, firstly, the number of multiple communication data is counted to determine the total amount of communication data N. For example, when the system processes 5 communication data such as navigation data, user account data, and in-vehicle entertainment data at the same time, the total amount of communication data N=5.

[0098] Subsequently, the number of iterations for optimization is determined based on the load resource matching coefficient F and the total amount of communication data N. The formula for calculating K can be set as K=round(N×(1-F)), where round is the rounding function.

[0099] For example, if the load resource matching coefficient F = 0.8581 and the total amount of communication data N = 5, then K = round(5 × (1 - 0.8581)) = round(5 × 0.1419) = round(0.7095) = 1, meaning that one communication data path is selected for strategy adjustment in each iteration of optimization. If the load resource matching coefficient F is low, such as F = 0.4 and the total amount of communication data N = 5, then K = round(5 × (1 - 0.4)) = round(3) = 3, indicating that the encryption strategy of three communication data paths needs to be adjusted simultaneously to quickly adapt to the resource status.

[0100] Secondly, in the first efficiency-oriented encryption scheme, a random number generator is used to randomly select K channels from N communication data as the first selected optimization dataset. Assuming the encryption strategies for the 5 data channels in the first efficiency-oriented encryption scheme are [AES-128, AES-128, ChaCha20, AES-256, AES-128], the 4th data channel is randomly selected, with the original strategy being AES-256, as the first selected optimization dataset. Then, the encryption strategy configuration for this data channel in the first security-oriented encryption scheme is queried. If the first security-oriented encryption scheme uses the RSA-2048 encryption strategy for this data channel, the encryption strategy for the 4th data channel in the first efficiency-oriented encryption scheme is adjusted from AES-256 to RSA-2048, resulting in the first adjusted efficiency-oriented encryption scheme.

[0101] Similarly, in the first security-oriented encryption scheme, K communication data channels are randomly selected as the second selected optimization dataset. Assuming that the second data channel is randomly selected from the encryption strategies of the five data channels in the first security-oriented encryption scheme as the second selected optimization dataset, its strategy in the first efficiency-oriented encryption scheme is queried. Then, the encryption strategy of the second data channel in the first security-oriented encryption scheme is adjusted to obtain the first adjusted security-oriented encryption scheme.

[0102] After the initial policy adjustment, the encryption fitness of the first adjusted efficiency-oriented encryption scheme and the first adjusted security-oriented encryption scheme are calculated according to the aforementioned encryption fitness calculation method, and compared with the fitness of the scheme before adjustment. If the fitness of the adjusted scheme improves, the adjustment result is retained; if the fitness decreases, the adjustment is abandoned, and a new optimization dataset is selected for iteration.

[0103] Repeat the above process of strategy adjustment, fitness calculation and comparison until the preset number of convergence optimizations is reached, such as 10 iterations or 3 consecutive iterations where the fitness change rate is less than 0.05.

[0104] Finally, all the efficiency-oriented and security-oriented encryption schemes generated during the optimization process are summarized, duplicate schemes are removed, and the 2-3 schemes with the highest fitness are selected to form the final encryption scheme set.

[0105] S40: Based on the set of encryption schemes, determine the optimal encryption scheme and perform differentiated adaptive encryption processing on the multi-channel communication data.

[0106] In this embodiment of the application, based on the above-screened set of encryption schemes, the encryption scheme with the highest encryption adaptability is selected as the optimal encryption scheme, and differentiated adaptive encryption processing is implemented on the multi-channel communication data.

[0107] Furthermore, adaptive encryption processing refers to the process of dynamically adjusting the encryption strategy based on the real-time operating status and communication environment of the in-vehicle Android terminal. After the optimal encryption scheme is determined, the corresponding encryption strategy in the scheme is first assigned to each communication data channel, including specific configurations such as encryption algorithm type, key length, and encryption mode.

[0108] Specifically, step S40 in the method includes:

[0109] Within the set of encryption schemes, the encryption fitness of each encryption scheme is extracted, and the encryption fitness of each encryption scheme is compared.

[0110] Select the encryption scheme with the highest encryption adaptability as the optimal encryption scheme;

[0111] Based on the multiple encryption strategy configurations corresponding to the multi-channel communication data in the optimal encryption scheme, the corresponding encryption strategy is applied to the multi-channel communication data to complete the differentiated adaptive encryption processing.

[0112] In this embodiment, firstly, the encryption fitness value of each candidate encryption scheme is read from the encryption scheme set. For example, the fitness of scheme A is 0.85, scheme B is 0.82, and scheme C is 0.79. By comparing the values, scheme A is determined to be the scheme with the highest encryption fitness and is selected as the optimal encryption scheme in the current environment.

[0113] Secondly, we analyze the specific encryption strategy configuration for each communication data path in the optimal encryption scheme. Assume the scheme includes five communication data paths: navigation data, user identity data, vehicle status data, entertainment streaming data, and OTA upgrade data. The corresponding encryption strategy configurations are as follows: navigation data uses AES-128, user identity data uses RSA-2048, vehicle status data uses ECC, entertainment streaming data uses ChaCha20, and OTA upgrade data uses AES-256.

[0114] Subsequently, the encryption processing module of the in-vehicle Android terminal, based on the above configuration, calls the corresponding encryption algorithm interface for each communication data, loads the corresponding key material, and performs data encryption operations according to the specified encryption mode and parameters. For example, when processing user identity data, the terminal retrieves the RSA private key from the secure key storage area, uses the OAEP padding mode to encrypt the data, and records the resource consumption and time consumption during the encryption process; for entertainment streaming media data, the ChaCha20 stream encryption algorithm is enabled, combined with Poly1305 for integrity verification, to balance encryption efficiency and data security.

[0115] During the encryption process, the encryption progress, resource usage, and encryption anomalies of each data stream are monitored in real time to ensure that the differentiated encryption strategy is applied accurately and efficiently to each communication data stream, thereby achieving adaptive security protection for the entire communication link.

[0116] In summary, compared to existing technologies, this application constructs an encryption scheme generation mechanism that combines efficiency and security by dynamically integrating the load resource status of the in-vehicle Android terminal with the threat level of the communication environment. By introducing a load resource matching coefficient, it achieves precise adaptation to the terminal's computing power, avoiding system lag or response delays caused by excessive resource consumption of the encryption algorithm.

[0117] In summary, the embodiments of this application have at least the following technical effects:

[0118] This application provides a data encryption communication method for vehicle-mounted Android terminals. First, it receives multiple communication data streams from the vehicle-mounted Android terminal, obtaining multiple data feature parameters. It also monitors the encryption resources of the vehicle-mounted Android terminal, obtaining multiple encryption resource status parameters. Through dual analysis of data features and encryption resource status, it achieves a comprehensive understanding of communication data and terminal resources. Second, it performs encryption load adaptation analysis on the multiple data feature parameters and encryption resource status parameters to obtain a load-resource matching coefficient, which measures the degree of matching between current encryption requirements and terminal resource supply. Third, based on the load-resource matching coefficient, and using the multiple data feature parameters and encryption resource status parameters, it optimizes the encryption scheme for the multiple communication data streams, obtaining a set of encryption schemes. By considering data characteristics and resource conditions, it generates multiple possible combinations of encryption strategies, avoiding the limitations of a single scheme. Finally, based on the encryption scheme set, it determines the optimal encryption scheme and dynamically selects the most suitable encryption method according to the actual situation. Different encryption strategies are used for different types of communication data, thereby effectively improving encryption efficiency while ensuring communication security. This avoids resource waste or security risks caused by fixed encryption strategies, achieving intelligent and refined management of communication data encryption for vehicle-mounted Android terminals.

[0119] Through the above technical solution, this application effectively solves the technical challenge of fixing encryption strategies in vehicle environments, achieving a dynamic balance between security and efficiency. It is suitable for applications with limited resources and diverse security requirements in vehicle communication scenarios. Through intelligent environmental perception and strategy optimization, the encryption strength can be automatically adjusted according to actual operating conditions, ensuring the secure transmission of critical data while avoiding unnecessary waste of computing resources.

[0120] Example 2, as Figure 2As shown, based on the same inventive concept as the data encryption communication method for vehicle-mounted Android terminals provided in Embodiment 1, this application also provides a data encryption communication system for vehicle-mounted Android terminals, including:

[0121] The communication data analysis module 11 is used to receive multi-channel communication data from the vehicle-mounted Android terminal, perform data feature analysis on the multi-channel communication data to obtain multiple data feature parameters, and monitor the encrypted resources of the vehicle-mounted Android terminal to obtain multiple encrypted resource status parameters.

[0122] The load adaptation analysis module 12 is used to perform encrypted load adaptation analysis on the multiple data feature parameters and multiple encrypted resource status parameters to obtain the load resource matching coefficient.

[0123] The encryption scheme optimization module 13 is used to optimize the encryption scheme of the multi-channel communication data based on the load resource matching coefficient, the multiple data feature parameters and the multiple encryption resource status parameters, and obtain an encryption scheme set.

[0124] The optimal solution acquisition module 14 determines the optimal encryption scheme based on the encryption scheme set and performs differentiated adaptive encryption processing on the multi-channel communication data.

[0125] In one embodiment, the communication data analysis module 11 is specifically used for:

[0126] Extract the first communication data from the multi-channel communication data, input the first communication data into a pre-built data feature recognizer, perform data feature analysis, and obtain the first data feature parameter;

[0127] Following the method of obtaining the first data feature parameter, data feature analysis is performed on the remaining communication data to obtain multiple data feature parameters;

[0128] The encrypted resources of the vehicle-mounted Android terminal are monitored to obtain multiple encrypted resource status parameters, including CPU processing load, memory usage, encryption module load status, and terminal temperature status.

[0129] Furthermore, in one embodiment of the application, the construction process of the data feature recognizer includes:

[0130] Collect historical vehicle communication data, construct a sample communication dataset based on the historical vehicle communication data, and perform data feature annotation on each sample communication data in the sample communication dataset to obtain a sample data feature parameter set;

[0131] A data feature recognizer is built based on deep learning;

[0132] Using the sample communication dataset as input and the sample data feature parameter set as labels, the data feature recognizer is trained until convergence, thus completing the construction.

[0133] In one embodiment, the load adaptation analysis module 12 is specifically used for:

[0134] The encrypted resource evaluator is invoked to predict the encrypted resource demand based on the multiple data feature parameters, thereby obtaining multiple ideal encrypted resource state parameters. The encrypted resource evaluator is trained based on historical data feature parameters and corresponding ideal resource state parameters.

[0135] Extract a first ideal encrypted resource state parameter from the plurality of ideal encrypted resource state parameters, and extract the corresponding first encrypted resource state parameter from the plurality of encrypted resource state parameters;

[0136] Calculate the parameter ratio between the first encrypted resource state parameter and the first ideal encrypted resource state parameter to obtain the first parameter matching degree, wherein when the parameter ratio is greater than 1, the first parameter matching degree is set to 1;

[0137] Calculate the ratio of the remaining encrypted resource state parameters to the corresponding ideal encrypted resource state parameters in turn to obtain multiple parameter matching degrees;

[0138] The weights of each encrypted resource status parameter are set, and the matching degrees of the multiple parameters are weighted and summed based on the weights of each encrypted resource status parameter to obtain the load resource matching coefficient. The load resource matching coefficient is obtained by multiplying the matching degree of each encrypted resource status parameter by its weight and then summing the results.

[0139] In one embodiment, the encryption scheme optimization module 13 is specifically used for:

[0140] With communication efficiency and communication security as the guiding principles respectively, the multi-channel communication data is randomly encrypted twice to obtain a first efficiency-oriented encryption scheme and a first security-oriented encryption scheme. Each encryption scheme includes multiple encryption strategy configurations corresponding to the multi-channel communication data.

[0141] Obtain the efficiency benchmark parameters and security benchmark parameters of the preset encryption strategy set, and calculate the encryption fitness of the first efficiency-oriented encryption scheme and the first security-oriented encryption scheme respectively;

[0142] Based on the load resource matching coefficient, the first efficiency-oriented encryption scheme and the first security-oriented encryption scheme are simultaneously optimized to generate an encryption scheme set.

[0143] Further, the efficiency benchmark parameters and security benchmark parameters of the preset encryption strategy set are obtained, and the encryption fitness of the first efficiency-oriented encryption scheme and the first security-oriented encryption scheme are calculated respectively, including:

[0144] Based on the encryption strategy configuration corresponding to each communication data in the first efficiency-oriented encryption scheme, the efficiency benchmark parameters and security benchmark parameters corresponding to the encryption strategy used by each communication data are extracted from the efficiency benchmark parameters and security benchmark parameters of the preset encryption strategy set.

[0145] Calculate the average efficiency benchmark parameter of all encryption strategies in the first efficiency-oriented encryption scheme to obtain the efficiency evaluation value, and calculate the average security benchmark parameter of all encryption strategies as the security evaluation value;

[0146] Obtain the security weight coefficient and the efficiency weight coefficient, and perform a weighted summation calculation on the efficiency evaluation value and the security evaluation value based on the security weight coefficient and the efficiency weight coefficient to obtain the encryption fitness of the first efficiency-oriented encryption scheme, wherein the encryption fitness is equal to the product of the security evaluation value and the security weight coefficient plus the product of the efficiency evaluation value and the efficiency weight coefficient.

[0147] The encryption fitness of the first security-oriented encryption scheme is calculated in accordance with the method used to obtain the encryption fitness of the first efficiency-oriented encryption scheme.

[0148] Further, security weight coefficients and efficiency weight coefficients are obtained. Based on the security weight coefficients and efficiency weight coefficients, the efficiency evaluation value and the security evaluation value are weighted and summed to obtain the encryption fitness of the first efficiency-oriented encryption scheme, including:

[0149] Obtain the preset security threat level threshold and the current communication environment threat level monitored by the vehicle-mounted Android terminal;

[0150] Calculate the ratio of the current communication environment threat level to the security threat level threshold to obtain the security weight coefficient, and obtain the efficiency weight coefficient based on the security weight coefficient;

[0151] Using the security weight coefficient and efficiency weight coefficient, the security evaluation value and efficiency evaluation value are weighted and summed to obtain the encryption fitness of the first efficiency-oriented encryption scheme, wherein the encryption fitness is equal to the product of the security evaluation value and the security weight coefficient plus the product of the efficiency evaluation value and the efficiency weight coefficient.

[0152] Furthermore, following the method for obtaining the encryption fitness of the first efficiency-oriented encryption scheme, the encryption fitness of the first security-oriented encryption scheme is calculated. Based on the load-resource matching coefficient, the first efficiency-oriented encryption scheme and the first security-oriented encryption scheme are simultaneously optimized to generate an encryption scheme set, including:

[0153] The total amount of communication data is obtained by counting the number of multiple communication data streams, and the number of iterations for optimization is determined based on the load resource matching coefficient and the total amount of communication data.

[0154] Within the first efficiency-oriented encryption scheme, communication data of the number of iterations is randomly selected as the first selected optimization dataset. The encryption strategy of the first selected optimization dataset is configured according to the encryption strategy of the first security-oriented encryption scheme. The strategy is adjusted within the first efficiency-oriented encryption scheme to obtain the first adjusted efficiency-oriented encryption scheme.

[0155] Within the first security-oriented encryption scheme, communication data of the number of iterations is randomly selected as the second selected optimization dataset. The encryption strategy of the second selected optimization dataset within the first efficiency-oriented encryption scheme is configured, and the strategy is adjusted within the first security-oriented encryption scheme to obtain the first adjusted security-oriented encryption scheme.

[0156] Repeat the strategy adjustment, fitness calculation and synchronization optimization until the convergence optimization number is reached. Then, summarize all the efficiency-oriented encryption schemes and security-oriented encryption schemes generated during the optimization process to obtain the encryption scheme set.

[0157] In one embodiment, the optimal solution acquisition module 14 is specifically used for:

[0158] Within the set of encryption schemes, the encryption fitness of each encryption scheme is extracted, and the encryption fitness of each encryption scheme is compared.

[0159] Select the encryption scheme with the highest encryption adaptability as the optimal encryption scheme;

[0160] Based on the multiple encryption strategy configurations corresponding to the multi-channel communication data in the optimal encryption scheme, the corresponding encryption strategy is applied to the multi-channel communication data to complete the differentiated adaptive encryption processing.

[0161] It should be noted that the order of the embodiments described above is merely for descriptive purposes and does not represent the superiority or inferiority of the embodiments. Furthermore, the above description focuses on specific embodiments of this specification. Additionally, the processes depicted in the accompanying drawings do not necessarily require a specific or sequential order to achieve the desired results. In some implementations, multitasking and parallel processing are possible or may be advantageous.

[0162] The above description is only a preferred embodiment of this application and is not intended to limit this application. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of this application should be included within the protection scope of this application.

[0163] This specification and accompanying drawings are merely illustrative examples of this application and are intended to cover any and all modifications, variations, combinations, or equivalents within the scope of this application. Clearly, those skilled in the art can make various alterations and modifications to this application without departing from its scope. Therefore, if such modifications and modifications fall within the scope of this application and its equivalents, this application intends to include such modifications and modifications.

Claims

1. A data encryption communication method for a vehicle-mounted Android terminal, characterized in that, The method comprises: Receiving multi-channel communication data of the vehicle-mounted Android terminal, performing data feature analysis on the multi-channel communication data to obtain a plurality of data feature parameters, and performing encrypted resource monitoring on the vehicle-mounted Android terminal to obtain a plurality of encrypted resource state parameters; Performing encrypted load adaptation analysis on the plurality of data feature parameters and the plurality of encrypted resource state parameters to obtain a load resource matching coefficient; Based on the load resource matching coefficient, performing encrypted scheme optimization on the multi-channel communication data based on the plurality of data feature parameters and the plurality of encrypted resource state parameters to obtain an encrypted scheme set; Based on the encrypted scheme set, determining an optimal encrypted scheme, and performing differential adaptive encryption processing on the multi-channel communication data; Wherein, receiving multi-channel communication data of the vehicle-mounted Android terminal, performing data feature analysis on the multi-channel communication data to obtain a plurality of data feature parameters, and performing encrypted resource monitoring on the vehicle-mounted Android terminal to obtain a plurality of encrypted resource state parameters, comprising: Extracting first channel communication data from the multi-channel communication data, inputting the first channel communication data into a pre-constructed data feature recognizer, performing data feature analysis, and obtaining first data feature parameters; According to the way of obtaining the first data feature parameters, data feature analysis is performed on the remaining channel communication data to obtain a plurality of data feature parameters; Performing encrypted resource monitoring on the vehicle-mounted Android terminal to obtain a plurality of encrypted resource state parameters, wherein the encrypted resource state parameters include CPU processing load, memory occupancy rate, encrypted module load state and terminal temperature state; Wherein, based on the load resource matching coefficient, the encrypted scheme set is obtained by performing encrypted scheme optimization on the multi-channel communication data based on the plurality of data feature parameters and the plurality of encrypted resource state parameters, comprising: Respectively, according to the communication efficiency and the communication security, the multi-channel communication data is randomly encrypted twice to obtain a first efficiency-oriented encryption scheme and a first security-oriented encryption scheme, wherein each encryption scheme includes a plurality of encryption strategy configurations corresponding to the multi-channel communication data; Obtaining efficiency benchmark parameters and security benchmark parameters of a preset encryption strategy set, and calculating the encryption fitness of the first efficiency-oriented encryption scheme and the first security-oriented encryption scheme; Based on the load resource matching coefficient, the first efficiency-oriented encryption scheme and the first security-oriented encryption scheme are simultaneously optimized to generate an encrypted scheme set; Wherein, based on the load resource matching coefficient, the first efficiency-oriented encryption scheme and the first security-oriented encryption scheme are simultaneously optimized to generate an encrypted scheme set, comprising: Statistically obtaining the total amount of communication data, and determining the number of iterative optimization according to the load resource matching coefficient and the total amount of communication data; In the first efficiency-oriented encryption scheme, randomly select the number of iterative optimization communication data as the first selected optimization data set, and perform strategy adjustment in the first efficiency-oriented encryption scheme according to the encryption strategy configuration of the first selected optimization data set in the first security-oriented encryption scheme to obtain a first adjusted efficiency-oriented encryption scheme; In the first security-oriented encryption scheme, a plurality of communication data are randomly selected as a second selected optimization data set, and a policy adjustment is performed in the first security-oriented encryption scheme according to an encryption strategy configuration of the second selected optimization data set in the first efficiency-oriented encryption scheme, to obtain a first adjusted security-oriented encryption scheme; The policy adjustment, fitness calculation and synchronization optimization are repeatedly performed until a convergence optimization number is reached, and all efficiency-oriented encryption schemes and security-oriented encryption schemes generated in the optimization process are summarized to obtain an encryption scheme set; Based on the encryption scheme set, an optimal encryption scheme is determined, and a differential adaptive encryption processing is performed on the plurality of communication data, including: In the encryption scheme set, the encryption fitness of each encryption scheme is extracted, and the encryption fitness of each encryption scheme is compared; The encryption scheme with the highest encryption fitness is selected as the optimal encryption scheme; According to the plurality of encryption strategy configurations corresponding to the plurality of communication data in the optimal encryption scheme, the corresponding encryption strategy processing is performed on the plurality of communication data, to complete the differential adaptive encryption processing. 2.The data encryption communication method for the Android terminal in a vehicle according to claim 1, wherein, The construction process of the data feature identifier includes: Collecting historical vehicle-mounted communication data, constructing a sample communication data set based on the historical vehicle-mounted communication data, labeling each sample communication data in the sample communication data set with data features, and obtaining a sample data feature parameter set; Based on deep learning, a data feature identifier is constructed; The sample communication data set is input, the sample data feature parameter set is labeled, and the data feature identifier is trained until convergence is achieved, and the construction is completed. 3.The data encryption communication method for the Android terminal in a vehicle according to claim 1, wherein, The plurality of data feature parameters and the plurality of encryption resource state parameters are subjected to encryption load adaptation analysis to obtain a load resource matching coefficient, including: The encryption resource evaluator is called to predict the encryption resource demand of the plurality of data feature parameters to obtain a plurality of ideal encryption resource state parameters, wherein the encryption resource evaluator is trained based on historical data feature parameters and corresponding ideal resource state parameters; A first ideal encryption resource state parameter is extracted from the plurality of ideal encryption resource state parameters, and a corresponding first encryption resource state parameter is extracted from the plurality of encryption resource state parameters; The parameter ratio of the first encryption resource state parameter to the first ideal encryption resource state parameter is calculated to obtain a first parameter matching degree, wherein when the parameter ratio is greater than 1, the first parameter matching degree is set to 1; The parameter ratios of the remaining encryption resource state parameters to the corresponding ideal encryption resource state parameters are calculated in sequence to obtain a plurality of parameter matching degrees; The weights of the encryption resource state parameters are set, and the plurality of parameter matching degrees are weighted and summed based on the weights of the encryption resource state parameters to obtain a load resource matching coefficient, wherein the load resource matching coefficient is obtained by multiplying each encryption resource state parameter corresponding parameter matching degree and the weight of the encryption resource state parameter and then summing. 4.The data encryption communication method for a car-mounted Android terminal according to claim 1, characterized in that, Efficiency benchmark parameters and security benchmark parameters of a preset encryption strategy set are obtained, and the encryption fitness of the first efficiency-oriented encryption scheme and the first security-oriented encryption scheme is calculated, including: According to the encryption strategy configuration corresponding to each communication data in the first efficiency-oriented encryption scheme, the efficiency reference parameter and the security reference parameter corresponding to the encryption strategy used by each communication data are extracted from the efficiency reference parameter and the security reference parameter of the preset encryption strategy set; The efficiency reference parameter average of all encryption strategies in the first efficiency-oriented encryption scheme is calculated to obtain an efficiency evaluation value, and the security reference parameter average of all encryption strategies is calculated as a security evaluation value; The security weight coefficient and the efficiency weight coefficient are obtained, and the efficiency evaluation value and the security evaluation value are weighted and summed based on the security weight coefficient and the efficiency weight coefficient to obtain the encryption fitness of the first efficiency-oriented encryption scheme, wherein the encryption fitness is equal to the product of the security evaluation value and the security weight coefficient plus the product of the efficiency evaluation value and the efficiency weight coefficient; The encryption fitness of the first security-oriented encryption scheme is calculated in the same way as the encryption fitness of the first efficiency-oriented encryption scheme. 5.The data encryption communication method for the Android terminal in a vehicle according to claim 4, wherein, The security weight coefficient and the efficiency weight coefficient are obtained, and the efficiency evaluation value and the security evaluation value are weighted and summed to obtain the encryption fitness of the first efficiency-oriented encryption scheme, including: A preset security threat degree threshold is obtained, and the current communication environment threat degree monitored by the vehicle-mounted Android terminal is obtained; The ratio of the current communication environment threat degree to the security threat degree threshold is calculated to obtain the security weight coefficient, and the efficiency weight coefficient is obtained according to the security weight coefficient; The security weight coefficient and the efficiency weight coefficient are used to weighted and summed the security evaluation value and the efficiency evaluation value to obtain the encryption fitness of the first efficiency-oriented encryption scheme, wherein the encryption fitness is equal to the product of the security evaluation value and the security weight coefficient plus the product of the efficiency evaluation value and the efficiency weight coefficient.

6. A data encryption communication system for a vehicle-mounted Android terminal, characterized by, A data encryption communication method for a vehicle-mounted Android terminal is used to perform any one of claims 1-5, comprising: A communication data analysis module is used to receive multiple communication data of a vehicle-mounted Android terminal, analyze the data characteristics of the multiple communication data, obtain multiple data characteristic parameters, and monitor the encryption resources of the vehicle-mounted Android terminal to obtain multiple encryption resource state parameters; A load adaptation analysis module is used to perform encryption load adaptation analysis on the multiple data characteristic parameters and the multiple encryption resource state parameters to obtain a load resource matching coefficient; An encryption scheme optimization module is used to perform encryption scheme optimization on the multiple communication data based on the multiple data characteristic parameters and the multiple encryption resource state parameters based on the load resource matching coefficient to obtain an encryption scheme set; An optimal scheme acquisition module is used to determine an optimal encryption scheme based on the encryption scheme set and perform differential adaptive encryption processing on the multiple communication data.

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