Data security and encryption method suitable for intelligent network connection practical training platform

Abstract

The invention discloses a data security and encryption method suitable for an intelligent network connection practical training platform. The method comprises the following steps: constructing the intelligent network connection practical training platform comprising an intelligent cockpit and an intelligent trolley; training communication between a cockpit and remote control vehicle equipment based on a key generation technology; a private key and a public key are calculated for the generated secret key according to bits through combination of a preset numerical value and modulo calculation, and transmission of the private keys is completed through exchange of the public keys; data compression processing is added in a key exchange mechanism of the intelligent cockpit and the intelligent trolley; and a block chain technology is introduced to carry out data transmission on the intelligent cockpit and the intelligent trolley. According to the invention, on the premise of ensuring the availability and security of teaching data, the transmission data volume is obviously reduced; through algorithm-level and system-level collaborative optimization, the calculation energy consumption in the encryption and compression process is reduced.

Description

Technical Field

[0001] This invention belongs to the field of vehicle data transmission and encryption, and particularly relates to a data security and encryption method suitable for intelligent connected vehicle training platforms. Background Technology

[0002] With the continuous advancement of the "new four modernizations" (electrification, intelligentization, connectivity, and sharing) in the automotive industry, automobiles have evolved from traditional mechanical transportation tools into intelligent mobile terminals integrating perception, decision-making, control, and communication. Among these advancements, the mature application of drive-by-wire chassis technology has made it possible to achieve electronic control and remote intervention in key systems such as steering, braking, and throttle; the low latency and high bandwidth characteristics of 5G / V2X wireless communication technology provide reliable guarantees for real-time information interaction between vehicles, vehicles-road systems, and vehicles-cloud systems; these technologies have significantly improved the intelligence level of advanced driver assistance systems. Against this backdrop, the demand for training talent in intelligent connected vehicle technology is becoming increasingly urgent. Traditional automotive engineering education is insufficient to cover emerging fields such as intelligent driving, vehicle-road cooperation, and data security, necessitating the construction of an interdisciplinary, practical teaching system oriented towards high-level autonomous driving technologies.

[0003] To address the aforementioned talent development needs, the development of an intelligent connected vehicle training platform has emerged. This platform requires an intelligent cockpit as its core teaching platform, utilizing remote multi-vehicle collaborative control technology to achieve a distributed teaching scenario of "one cockpit controlling multiple vehicles." Specifically, the intelligent cockpit can remotely connect to multiple training vehicles, acquire their sensor data in real time, and issue control commands to achieve closed-loop teaching and training with vehicles in the loop. However, in actual operation, the system faces a conflict between the richness of its teaching functions and the limited energy resources of the vehicles.

[0004] In summary, current intelligent connected vehicle training platforms face a conflict between the dual objectives of "security enhancement" and "energy efficiency optimization." The traditional approach of "encryption equals increased power consumption" is no longer sufficient to meet the demands of long-duration, multi-tasking, and high-concurrency teaching and training. Therefore, there is an urgent need to develop a lightweight, highly secure, and low-energy-consumption collaborative optimization method for data encryption and compression tailored to intelligent connected vehicle teaching scenarios. Summary of the Invention

[0005] Purpose of the Invention: The purpose of this invention is to provide a data security and encryption method suitable for intelligent connected training platforms. While ensuring the availability and security of teaching data, it significantly reduces the amount of data transmitted; through algorithm-level and system-level collaborative optimization, it reduces the computational energy consumption of the encryption and compression processes.

[0006] Technical solution: The present invention provides a data security and encryption method applicable to an intelligent connected training platform, comprising the following steps:

[0007] Step 1: Construct an intelligent connected training platform that includes an intelligent cockpit and intelligent vehicles;

[0008] Step 2: Practice communication between the cockpit and remote vehicle equipment based on key generation technology; calculate the intersection point of the function curve in the two-dimensional graphic space using mathematical methods based on several given parameters, and use the intersection point of the two graphics as the security key.

[0009] Step 3: Using preset values ​​and modulo calculation, calculate the private key and public key bit by bit for the generated key, and complete the transfer of the private key by exchanging the public key.

[0010] Step 4: Add data compression processing to the key exchange mechanism of the intelligent cockpit and intelligent vehicle;

[0011] Step 5: Introduce blockchain technology to transmit data between the smart cockpit and the smart car.

[0012] Furthermore, step 1 specifically involves: setting up a network with multiple nodes in the intelligent connected training platform. Each node and The link is used to select nodes with hardware and network resources as aggregators. Let the number of aggregators be . one, and Model the network as a connected graph .

[0013] Furthermore, step 2 specifically involves the following: In the intelligent connected training platform, the key is generated through a structure formed by the intersection of a sine curve and a horizontal line. The key can only be restored and extracted after all the parameters of the unit in the structure work together; the spacing between each horizontal line and the sine line in the structure is not completely equal.

[0014] In constructing the network structure, one required parameter is the height h of the horizontal line; after the horizontal line is completed, the sine curve is drawn, using the origin of the coordinate axis as the reference point; first, the maximum value of the sine curve is set. Then set the period T and phase of the sine curve. As the sine curve extends to both sides, the interval T reaches its maximum or minimum value at each interval; therefore, the construction of the sine curve is based on the maximum value. Period T and phase The formula for the intersection point of a sine curve and a horizontal line is jointly determined:

[0015]

[0016]

[0017] in, y represents the position of the point in the horizontal direction, and y represents the position of the point in the vertical direction;

[0018] All intersections of the horizontal line and the sine curve are extracted to generate a security key; this key is then constructed by filling in the numerical coordinates of these intersections and concatenating them. After the security key is generated, it is appended to the data and sent together.

[0019] Further, step 3 specifically involves the following steps: At the beginning of the key exchange, the communicating smart cockpit and smart car agree on a common super-large prime number P beforehand. Then, the smart cockpit and smart car each generate their private keys according to the key generation method, denoted as a and b respectively. Next, both parties perform bitwise modulo operations on P to obtain their respective public keys Pa and Pb, and then perform binary conversion and Gray code encoding on the public keys to enhance the accuracy during transmission. After exchanging the encoded public keys, both parties restore them to their original binary form. Finally, A uses the received public key Pb from B and its own private key Pa to calculate the shared key Sa = (Pb × a) mod P; similarly, it calculates the shared key Sb = (Pa × b) mod P. Due to the nature of modulo operations, Sa and Sb are equal, thus the smart cockpit and smart car securely obtain the same session key.

[0020] Furthermore, step 4 specifically includes the following steps:

[0021] Step 4.1: In the platform consisting of the intelligent cockpit and the training vehicle, the training vehicle transmits video stream signals and information from various sensor units to the cockpit, and receives command signals from the intelligent cockpit; in this system, the data and commands transmitted by node n are denoted as... Subsequently, data and instructions With a security key Perform a bitwise XOR operation to generate a ciphertext message. ; Ciphertext data Compressed as The compressed ciphertext data is received by the aggregation node from all connected devices; the security key generation process is carried out simultaneously at both the node and the aggregation node; as long as the variable values ​​input into the key generation units of the node and the aggregation node are the same, the security keys generated at both ends are consistent.

[0022]

[0023] Step 4.2: A key exchange mechanism is established between the aggregation node and the sensor nodes;

[0024] Step 4.3: Decompress the data on both the intelligent cockpit and the intelligent vehicle.

[0025] Step 4.4: If several devices send data to the aggregation node, the message of each device is recorded as follows: , , ... The corresponding compressed ciphertext messages are generated sequentially and denoted as follows: , , ... The aggregation node also receives encrypted messages from other aggregation nodes, which are denoted as... The encrypted message received by the aggregation node contains the original message perceived by device n and its corresponding security key. Subsequently, the aggregation node receives the data. Calculate the corresponding key The aggregation node compares the key with the key carried in the message; if they match, the aggregation node accepts the message; after verifying all messages from each node, the aggregation node summarizes all accepted messages and represents them uniformly as follows: ... .

[0026] Furthermore, step 4.2 specifically involves:

[0027] The aggregation node first generates a key. It is then sent to a non-convergence node, even if that node is attacked or the key is intercepted; the encrypted message is compressed using a linear compression function.

[0028]

[0029] Encrypted data It is mapped from a high-dimensional space to a low-dimensional space, thus obtaining a compressed form. Here, The compression factor is calculated as equal to the compressed length. Length before compression The ratio of .

[0030] Furthermore, step 4.3 specifically includes:

[0031] Restored data This is accomplished through a decompression function;

[0032]

[0033] The decompression process is completed on both the intelligent cockpit and the intelligent vehicle end according to the above formula.

[0034] Furthermore, step 5 specifically involves: a data point from the smart car's terminal. It is divided into several blocks; the data in these blocks is represented as , … ,in This indicates the total number of blocks; data blocks are categorized by type and identified by the type. , … Subsequently, the corresponding security key is selected according to the category and added to the block; at this point, the data block is denoted as... , … Ultimately, in the blockchain, a complete block containing a pointer to the previous block and its hash code is represented as: , … Final data Depend on , , , Composition, in which , , These represent the security key, pointer, and hash code, respectively; the data is stored within a block, and the base station receives this block containing... , … The blockchain;

[0035] Smart car The data is recorded as It is transmitted to the next-hop aggregation node. ;data and The number of data packets in the process is denoted as m and n, respectively. In the initial stage, only m data packets are sent to the next-hop aggregation node. After sending m data packets, the transmission message is submitted to the tag contract. The transmission message includes: the number of data packets sent, the next-hop aggregation node, the device ID, the routing address, and the timestamp. Subsequently, the tag contract verifies the message and sends the remaining n data packets to the next-hop aggregation node. When the confirmation message arrives, the system checks the number of data packets.

[0036] The present invention also discloses a computer device, including a memory, a processor, and a computer program stored in the memory, wherein the processor executes the computer program to implement the steps of the method of the present invention.

[0037] The present invention also discloses a computer-readable storage medium having a computer program / instructions stored thereon, which, when executed by a processor, implements the steps of the method of the present invention.

[0038] Beneficial effects: Compared with the prior art, the present invention has the following significant advantages:

[0039] In this invention, addressing the scenario of information and command transmission under general-purpose networks, a low-latency, high-reliability encryption and encoding algorithm method is proposed, capable of handling adverse factors such as network fluctuations. The method utilizes the training equipment's own resources to generate a hash key before compressing and aggregating the data, achieving efficient use of limited computing resources. The compressed data is then transmitted via blockchain routing. In the accompanying key distribution scenario, considering resource constraints, a key exchange method is adopted. After pre-agreeing on a large integer, a random number is generated, and then each party's private key is generated bit-by-bit. The corresponding public key is then calculated based on the private key and Gray code, and finally, a shared key is generated. Through this combined method, data security and encryption are achieved in the intelligent connected vehicle training platform, and this module can help facilitate teaching students about vehicle network data security.

[0040] This invention encrypts command or sensor signal stream data at the device level with the participation of a key, and then compresses it through the transmission node, reducing signal transmission burden and device power consumption. The data is organized into data blocks, and blockchain technology is used to maintain the fidelity of signal transmission, avoiding the impact of deception and interference on control security. Ultimately, while ensuring the availability and security of teaching data, the amount of transmitted data is significantly reduced; through algorithm-level and system-level collaborative optimization, the computational energy consumption of the encryption and compression processes is reduced. Attached Figure Description

[0041] Figure 1 This is a system model diagram of the present invention.

[0042] Figure 2 This is a schematic diagram of the network model for the training platform.

[0043] Figure 3 Schematic diagram of the structure generated for the key

[0044] Figure 4 Blockchain structure diagram Detailed Implementation

[0045] The technical solution of the present invention will be further described below with reference to the accompanying drawings.

[0046] 1. Overall System Model:

[0047] In the intelligent connected vehicle training platform, vehicles and roadside sensing devices are interconnected via wireless links and connected to a base station (BS). The base station uploads data to a local area network, and then the uploaded data can be accessed and control commands issued via the network. The system model is as follows: Figure 1 As shown. It is possible to configure a network with [a certain number of nodes]. Each node and One link. Select nodes with relatively abundant hardware and network resources as aggregators (assuming the number of aggregators is [number]). one, and Model the network as a connected graph. The network model diagram of the training platform is shown below. Figure 2 As shown.

[0048] 2. Performance-friendly key generation technology:

[0049] In the intelligent connected vehicle training platform, the vehicle-mounted terminal is powered by a battery, and its own chip computing power is relatively weak. To meet the training requirements, a long battery life is needed. Under this requirement, a balance between performance and power consumption needs to be achieved. In this intelligent connected vehicle training platform, encryption technology can enable communication between the training cockpit and remotely controlled vehicles, and can also serve as an introductory teaching method to help students understand the functions and applications of encryption and decryption modules. In this training platform, the key is generated through a structure formed by the intersection of a sine curve and a horizontal line. The key can only be restored and extracted after all the parameters of the units in the structure work together. The spacing between the horizontal lines and the sine lines in the structure is not exactly equal, and the specific values ​​of these spacings are set by parameters derived from the horizontal lines and the sine curve.

[0050] In constructing the network structure, one required parameter is the height h of the horizontal line. After the horizontal line is drawn, the sine curve is plotted, using the origin of the coordinate axes as a reference point. First, the maximum value of the sine curve is set. Then set the period T and phase of the sine curve. As the sine curve extends to both sides, the interval T reaches its maximum or minimum value at each interval. Therefore, the construction of the sine curve is based on the maximum value. Period T and phase The decision is made jointly. The formula for the intersection point of a sine curve and a horizontal line is:

[0051]

[0052]

[0053] All intersections of the horizontal line and the sine curve are extracted to generate a security key. This key is then constructed by filling in the numerical coordinates of these intersections and concatenating them. After the security key is generated, it is appended to the data and sent together. Because the key generation process does not involve the generation of random numbers, it cannot be easily deciphered or stolen.

[0054] 3. Key exchange implementation:

[0055] At the start of the key exchange, the communicating smart cockpit and smart car pre-agree on a common, very large prime number P. Then, each generates its private key (denoted as a and b) according to the key generation method from the previous step. Next, both parties perform a bitwise modulo operation on P to obtain their respective public keys Pa and Pb. These public keys are then converted to binary and encoded in Gray code to enhance the accuracy during transmission. After exchanging the encoded public keys, they are restored to their original binary form. Finally, A uses the received public key Pb from B and its own private key Pa to calculate the shared key Sa = (Pb × a) mod P; similarly, it calculates the shared key Sb = (Pa × b) mod P. Due to the nature of modulo operations, Sa and Sb are necessarily equal, thus ensuring that the cockpit and car can securely obtain the same session key.

[0056] 4. Secure compression methods after data aggregation:

[0057] In the platform comprised of an intelligent cockpit and a training vehicle, the training vehicle transmits video stream signals and information from various sensor units to the cockpit, and receives command signals from the intelligent cockpit. In this system, the data and commands transmitted by node n are denoted as... Subsequently, data and instructions. With a security key Perform a bitwise XOR operation to generate a ciphertext message. The security key is generated in the previous step. Next, the encrypted data... Compressed (denoted as) The compressed ciphertext data is received by the aggregation node from all connected devices. The security key generation process occurs simultaneously at both the node and aggregation nodes. This is achieved by inputting variable values ​​(such as...) into the key generation units of both the node and aggregation nodes. , , , If the keys (etc.) are the same, then the security keys generated at both ends will be completely identical.

[0058]

[0059] The key exchange mechanism between the aggregation node and the sensor nodes is as follows: The aggregation node first generates a key. It is then sent to a non-convergence node. Even if the node is attacked and the key is intercepted, the key cannot be truly recovered because the relevant parameters in the structural unit are unknown.

[0060] The encrypted message is compressed using a linear compression function:

[0061]

[0062] Encrypted data It is mapped from a high-dimensional space to a low-dimensional space, thus obtaining a compressed form. Here, The compression factor is calculated as equal to the compressed length. Length before compression The ratio. Restored data. This can be accomplished using a decompression function.

[0063]

[0064] The decompression process can be completed on both the smart cockpit and the smart car end according to the above formula.

[0065] If several devices send data to the aggregation node, the messages from each device are denoted as follows: , , ... The corresponding compressed ciphertext messages are generated sequentially and denoted as follows: , , ... In addition, the aggregation node will also receive encrypted messages from other aggregation nodes, denoted as... The encrypted message received by the aggregation node contains the original message perceived by device n and its corresponding security key. Subsequently, the aggregation node receives the data. Calculate the corresponding key The aggregation node compares the key carried in the message with the data. If they match, the aggregation node accepts the message. After verifying all messages from each node, the aggregation node summarizes all accepted messages, which can be uniformly represented as follows: ... .

[0066] 5. Data transmission methods in smart cockpits and small workshops powered by blockchain technology:

[0067] Data from various sensors on the vehicle is compressed into data blocks, encrypted using a blockchain, and then transmitted to the smart cockpit. In the blockchain, data, along with its corresponding hash value, is stored within a block. During this process, any change to a block requires authorization from other ports on the chain. The aggregated data at the vehicle is divided into several blocks, and the system selects a corresponding security key based on the type of data block. This key is then encrypted along with the block's data. Each block containing data uploaded by the vehicle consists of three parts: the data, the security key, and a pointer to the previous block. Subsequent blocks carrying the data and security key are then added to the chain, and these blocks are assigned a signature established by the receiving node. Therefore, each block in the entire data blockchain contains a pointer to the previous block. When the smart vehicle is operating, the surrounding environmental data is processed and formed into an encrypted data block, which is appended to the preceding block containing the data record, thus creating a blockchain and enabling data sharing between different vehicles and the smart cockpit.

[0068] Before being sent to the smart cockpit, data received by the vehicle is first stored in the vehicle's blockchain database. To store the data on the blockchain, it is first split into several blocks, and a security key is attached to each block to encrypt it. Different security keys are selected from a previously generated key list based on the data type. Here, an attacker cannot recover the original data without knowing the key. This "data-aware encryption" can use different types of keys based on the data type, thus providing a higher level of key protection for more important data; for example, the cockpit's control commands to the vehicle are protected with a more complex key. In this system, the key length can dynamically change based on factors such as data importance, the degree of exposure to attacks, and the likelihood of being compromised, aiding in cognitive learning.

[0069] In the specific implementation, a single piece of data from the vehicle's end... It is divided into several blocks. The data in these blocks can be represented as... , … ,in This indicates the total number of blocks. Data blocks are categorized and identified by their respective categories. , … Then, the corresponding security key is selected according to the category and added to the block; at this point, the data block is denoted as... , … Ultimately, in the blockchain, a complete block, containing a pointer to the previous block and its hash code, is represented as... , … Final data Depend on , , , Composition, in which , , These represent the security key, pointer, and hash code, respectively. The data is stored within a block, and the base station receives this block containing... , … . The blockchain.

[0070] small car The data is recorded as It is transmitted to the next-hop aggregation node. .data and The number of data packets in the process is denoted as m and n, respectively. Initially, only m data packets are sent to the next-hop aggregation node. After sending m data packets, a transmission message is submitted to the tagging contract. This transmission message includes: the number of data packets transmitted, the next-hop aggregation node, the device ID, the routing address, and a timestamp. Subsequently, the tagging contract verifies the message and then sends the remaining n data packets to the next-hop aggregation node. When the confirmation message arrives, the system checks the number of data packets. This blockchain-based data transmission scheme can provide a secure transmission mechanism for data transmission between devices on the training platform.

[0071] 6. Overview of the transmission process:

[0072] The intelligent cockpit first parses the hash code and verifies it to decrypt the message, thus reconstructing the actual data from the block. Then, it compares the block number with the previous block to confirm the integrity of the entire chain. The decrypted data blocks are merged to recover the complete original message from the intelligent vehicle. The intelligent cockpit system verifies the hash code: if the received hash code matches the hash code sent with the block, the data is accepted. Next, the data is decompressed and decrypted to obtain the original signal data piece by piece. The security key shared with the base station is retrieved and added to the data... With the shared key A bitwise XOR operation is performed between them. Then, this process is repeated cyclically from 1 to... Repeat the process to restore the data corresponding to all nodes involved in the transmission.

[0073] Example

[0074] The proposed method was simulated using a Python-built environment. During the simulation, storage costs were compared using keys of different lengths: 32-bit, 48-bit, and 64-bit keys. The results showed that with a 32-bit key, the required storage cost was 19 bytes; with a 48-bit key, it was 35 bytes; and with a 64-bit key, it was 49 bytes. The experiment demonstrates that longer keys result in higher storage costs. The compression effect was then tested; a compression ratio of 50% significantly reduced storage costs.

Claims

1. A data security and encryption method suitable for intelligent connected training platforms, characterized in that, Includes the following steps: Step 1: Construct an intelligent connected training platform that includes an intelligent cockpit and intelligent vehicles; Step 2: Practice communication between the cockpit and remote vehicle equipment based on key generation technology; calculate the intersection point of the function curve in the two-dimensional graphic space using mathematical methods based on several given parameters, and use the intersection point of the two graphics as the security key. Step 3: Using preset values ​​and modulo calculation, calculate the private key and public key bit by bit for the generated key, and complete the transfer of the private key by exchanging the public key. Step 4: Add data compression processing to the key exchange mechanism of the intelligent cockpit and intelligent vehicle; Step 5: Introduce blockchain technology to transmit data between the smart cockpit and the smart car.

2. The data security and encryption method applicable to an intelligent connected training platform according to claim 1, characterized in that, Step 1 specifically involves: setting up the network of the intelligent connected training platform to include a total of Each node and The link is used to select nodes with hardware and network resources as aggregators. Let the number of aggregators be . one, and Model the network as a connected graph .

3. The data security and encryption method applicable to an intelligent connected training platform according to claim 1, characterized in that, Step 2 specifically involves the following: In the intelligent connected training platform, the key is generated through a structure formed by the intersection of a sine curve and a horizontal line. The key can only be restored and extracted after all the parameters of the unit in the structure work together. The spacing between each horizontal line and the sine line in the structure is not exactly equal. In constructing the network structure, one required parameter is the height h of the horizontal line; after the horizontal line is completed, the sine curve is drawn, using the origin of the coordinate axis as the reference point; first, the maximum value of the sine curve is set. Then set the period T and phase of the sine curve. As the sine curve extends to both sides, the interval T reaches its maximum or minimum value at each interval; therefore, the construction of the sine curve is based on the maximum value. Period T and phase The formula for the intersection point of a sine curve and a horizontal line is jointly determined: ； ； in, y represents the position of the point in the horizontal direction, and y represents the position of the point in the vertical direction; All intersections of the horizontal line and the sine curve are extracted to generate a security key; this key is then constructed by filling in the numerical coordinates of these intersections and concatenating them. After the security key is generated, it is appended to the data and sent together.

4. The data security and encryption method applicable to an intelligent connected training platform according to claim 1, characterized in that, Step 3 is as follows: At the beginning of the key exchange, the intelligent cockpit and the intelligent vehicle agree on a common super-large prime number P beforehand. Then, the intelligent cockpit and the intelligent vehicle each generate private keys according to the key generation method, denoted as a and b respectively. Next, both parties perform bitwise modulo operations on P to obtain their respective public keys Pa and Pb, and then perform binary conversion and Gray code encoding on the public keys to enhance the accuracy during transmission. After exchanging the encoded public keys, they are restored to their original binary form. Finally, A uses the received public key Pb of B and its own private key Pa to calculate the shared key Sa = (Pb × a) mod P; similarly, the shared key Sb = (Pa × b) mod P is calculated. Due to the nature of modulo operations, Sa and Sb are equal, thus the intelligent cockpit and the intelligent vehicle securely obtain the same session key.

5. A data security and encryption method suitable for an intelligent connected training platform according to claim 1, characterized in that, Step 4 specifically includes the following steps: Step 4.1: In the platform consisting of the intelligent cockpit and the training vehicle, the training vehicle transmits video stream signals and information from various sensor units to the cockpit, and receives command signals from the intelligent cockpit; in this system, the data and commands transmitted by node n are denoted as... Subsequently, data and instructions With a security key Perform a bitwise XOR operation to generate a ciphertext message. ; Ciphertext data Compressed as The compressed ciphertext data is received by the aggregation node from all connected devices; the security key generation process is carried out simultaneously at both the node and the aggregation node; as long as the variable values ​​input into the key generation units of the node and the aggregation node are the same, the security keys generated at both ends are consistent. ； Step 4.2: A key exchange mechanism is established between the aggregation node and the sensor nodes; Step 4.3: Decompress the data on both the intelligent cockpit and the intelligent vehicle. Step 4.4: If several devices send data to the aggregation node, the message of each device is recorded as follows: , , ... The corresponding compressed ciphertext messages are generated sequentially and denoted as follows: , , ... The aggregation node also receives encrypted messages from other aggregation nodes, which are denoted as... The encrypted message received by the aggregation node contains the original message perceived by device n and its corresponding security key. Subsequently, the aggregation node receives the data. Calculate the corresponding key The aggregation node compares the key with the key carried in the message; if they match, the aggregation node accepts the message; after verifying all messages from each node, the aggregation node summarizes all accepted messages and represents them uniformly as follows: ... .

6. A data security and encryption method suitable for an intelligent connected training platform according to claim 5, characterized in that, Step 4.2 specifically involves: The aggregation node first generates a key. It is then sent to a non-convergence node, even if that node is attacked or the key is intercepted; the encrypted message is compressed using a linear compression function. ； Encrypted data It is mapped from a high-dimensional space to a low-dimensional space, thus obtaining a compressed form. Here, The compression factor is calculated as equal to the compressed length. Length before compression The ratio of .

7. A data security and encryption method suitable for an intelligent connected training platform according to claim 6, characterized in that, Step 4.3 specifically involves: Restored data This is accomplished through a decompression function; ； The decompression process is completed on both the intelligent cockpit and the intelligent vehicle end according to the above formula.

8. A data security and encryption method suitable for an intelligent connected training platform according to claim 1, characterized in that, Step 5 specifically involves: a data point from the smart car's terminal. It is divided into several blocks; the data in these blocks is represented as , … ,in Indicates the total number of blocks; Data blocks are categorized by type and identified by type. , … ; Then, select the corresponding security key according to the category and add it to the block. At this point, the data block is denoted as... , … Ultimately, in the blockchain, a complete block containing a pointer to the previous block and its hash code is represented as: , … Final data Depend on , , , Composition, in which , , These represent the security key, pointer, and hash code, respectively; the data is stored within a block, and the base station receives this block containing... , … The blockchain; Smart car The data is recorded as It is transmitted to the next-hop aggregation node. ;data and The number of data packets in the process is denoted as m and n, respectively. In the initial stage, only m data packets are sent to the next-hop aggregation node. After sending m data packets, the transmission message is submitted to the tag contract. The transmission message includes: the number of data packets sent, the next-hop aggregation node, the device ID, the routing address, and the timestamp. Subsequently, the tag contract verifies the message and sends the remaining n data packets to the next-hop aggregation node. When the confirmation message arrives, the system checks the number of data packets.

9. A computer device comprising a memory, a processor, and a computer program stored in the memory, characterized in that, The processor executes the computer program to implement the steps of the method of claim 1.

10. A computer-readable storage medium having a computer program / instructions stored thereon, characterized in that, When the computer program / instructions are executed by the processor, they implement the steps of the method of claim 1.

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