Industrial data acquisition and management method based on vehicle control digitization

Abstract

The invention relates to the technical field of industrial data acquisition and management based on vehicle control digitization, and discloses an industrial data acquisition and management method based on vehicle control digitization. The sensors are arranged at key parts of the vehicle, so that the running state of the vehicle can be monitored in real time, and comprehensive collection of vehicle data is ensured. The data acquisition frequency is dynamically adjusted according to the vehicle speed or the acceleration, and storage and computing resource use are optimized. When the collected data is encrypted through a time domain scrambling strategy, the data security is effectively improved. And integrity verification is performed on the encrypted data through a time correlation scrambling method, so that whether the data is tampered or not can be effectively detected, and the authenticity and integrity of the data are ensured. Finally, in combination with a timestamp matching key and a decryption strategy, encrypted data can be recovered to original data during legal access, efficient utilization and protection of system data are ensured, and the security and reliability of a vehicle management system are improved.

Description

Technical Field

[0001] The present invention relates to the technical field of industrial data acquisition and management based on vehicle control digitization, and specifically to an industrial data acquisition and management method based on vehicle control digitization. Background Art

[0002] With the continuous improvement of the intelligence level of modern vehicles, the data acquisition and management of vehicles have become an important part of the vehicle control system. The vehicle control system monitors and collects various operating data of the vehicle in real time through a large number of sensors. These data include not only traditional information such as vehicle speed, acceleration, fuel quantity, and engine temperature, but also involve the monitoring of more complex driving behaviors and vehicle states. Therefore, how to effectively collect, store, encrypt, and securely access this data has become a core issue in modern vehicle intelligent systems.

[0003] Existing vehicle control data acquisition technologies usually adopt the method of installing multiple sensors on the vehicle. These sensors include vehicle speed sensors, temperature sensors, fuel quantity sensors, acceleration sensors, etc. These sensors are directly connected to the in-vehicle computing system and are responsible for real-time collection of the vehicle's operating data. However, the existing technology usually adopts a fixed time interval for adjusting the data acquisition frequency, which means that even when the data changes little in some cases, it is still collected at a fixed frequency, resulting in unnecessary data storage and processing burdens. Therefore, how to intelligently adjust the data acquisition frequency according to the actual situation has become a bottleneck in current technology. With the popularization of intelligent vehicle control systems, the data collected by vehicles involves a large amount of personal privacy information and security issues. To ensure the security of vehicle data, data encryption technology is widely used. Existing vehicle control systems usually adopt traditional symmetric encryption or asymmetric encryption to ensure the security of data during storage and transmission. However, traditional encryption methods face several problems when dealing with vehicle control data. Existing key generation methods usually rely on fixed algorithms or static rules, which are easily cracked by attackers. The leakage of keys may lead to the collapse of the security of the entire data encryption system. Traditional encryption methods do not fully consider the time-domain characteristics of data and usually adopt a simple fixed-key encryption method, lacking a dynamic encryption strategy for vehicle data.

[0004] In summary, there are certain deficiencies in the existing technology in terms of data acquisition and encryption in the vehicle control digitization system. Although there has been certain technical accumulation in the acquisition and encryption of vehicle data, most methods are still limited to traditional processing methods and lack dynamic responses to factors such as data timeliness, vehicle speed changes, and driving behaviors. Therefore, this case aims to propose an industrial data acquisition and management method based on vehicle control digitization, which includes innovative data acquisition and encryption methods. Summary of the Invention

[0005] The present invention provides an industrial data acquisition and management method based on vehicle control digitization, which promotes the solution of the problems mentioned in the above background art.

[0006] The present invention provides the following technical solution: an industrial data acquisition and management method based on vehicle control digitization, including:

[0007] A vehicle speed sensor is set on the vehicle differential to obtain the vehicle speed, with the unit of km / h, and the obtained vehicle speed is denoted as v;

[0008] A temperature sensor is set on the coolant pipeline of the vehicle engine to obtain the engine temperature, with the unit of °C, and the obtained engine temperature is denoted as T;

[0009] A wheel speed sensor is set on the vehicle wheel axle to obtain the wheel speed, with the unit of rpm, and the obtained wheel speed is denoted as ω;

[0010] An oil quantity sensor is set at the bottom of the vehicle fuel tank to obtain the oil quantity in the fuel tank, with the unit of L, and the obtained oil quantity is denoted as Q;

[0011] An acceleration sensor is set on the vehicle chassis to obtain the vehicle acceleration, with the unit of m / s 2 , and the obtained vehicle acceleration is denoted as a;

[0012] Set the vehicle data group and denote it as D;

[0013] Add the obtained vehicle data to the vehicle data group to obtain D = [v, T, ω, Q, a];

[0014] Adjust the vehicle data acquisition frequency according to the vehicle speed or acceleration;

[0015] Encrypt the collected vehicle data through a time-domain scrambling strategy, and store the encrypted vehicle data group and the timestamp when the vehicle data is obtained in the database;

[0016] When it is necessary to access the stored encrypted vehicle data group, perform integrity verification on the encrypted vehicle data group to be accessed through a time-correlation scrambling method;

[0017] When the encrypted vehicle data group to be accessed passes the integrity verification, decrypt the encrypted vehicle data group to be accessed through a data decryption strategy;

[0018] When the encrypted vehicle data group to be accessed fails to pass the integrity verification, return that the integrity verification fails and reject data decryption.

[0019] Optionally, the adjusting the vehicle data acquisition frequency according to the vehicle speed or acceleration specifically includes:

[0020] Set a vehicle speed threshold, denoted as v threshold

[0021] When v ≥ v threshold Adjust the vehicle data collection frequency to once per second;

[0022] When v < v threshold Adjust the vehicle data collection frequency to once every two seconds;

[0023] Set an acceleration threshold, denoted as a threshold ;

[0024] When |a| > a threshold Adjust the vehicle data collection frequency to twice per second;

[0025] When |a| ≤ a threshold Adjust the vehicle data collection frequency to once per second.

[0026] Optionally, encrypt the collected vehicle data through a time-domain scrambling strategy, specifically including:

[0027] Design a dynamic key generation based on an oscillator function:

[0028] Generate a key through the alternating oscillation of the vehicle speed, vehicle acceleration, and the timestamp when collecting the vehicle speed, and denote the generated key as k(t);

[0029] The oscillator function is specifically:

[0030]

[0031] Among them, v is the obtained vehicle speed; a is the obtained vehicle acceleration; t is the timestamp when collecting the vehicle speed; is the exclusive OR operation;

[0032] The key k(t) = Oscillator(v, a, t);

[0033] Store the key k(t) in the key database.

[0034] Optionally, encrypt the collected vehicle data through a time-domain scrambling strategy, specifically including:

[0035] Use the key k(t) to scramble each data in the vehicle data group D;

[0036] The scrambling process is as follows:

[0037]

[0038] Among them, D i is the i-th data in the vehicle data group D; The data after scrambling the i-th item of data in the vehicle data group D; P is a large prime number used to increase the scrambling intensity;

[0039] Set the encrypted vehicle data group, denoted as D 加扰 ;

[0040] Add the scrambled data of each item in the calculated vehicle data group D to D 加扰 to obtain D 加扰 = [v 加扰 , T 加扰 , ω 加扰 , Q 加扰 , a 加扰 .

[0041] Optionally, the integrity check of the encrypted vehicle data group that needs to be accessed after encryption by the time-correlation scrambling method specifically includes:

[0042] Generate a check value CAC(t) by combining each item of data in the encrypted vehicle data group with a scrambling factor based on the time stamp. Specifically:

[0043]

[0044] where m is the total number of elements in the encrypted vehicle data group; Hash is the hash calculation; ⊙ is the product of bitwise AND with the time offset function Shift(t); Shift(t) is the time offset function;

[0045] The time offset function Shift(t) is specifically:

[0046] Set a constant as indicating the periodic adjustment of time;

[0047]

[0048] Store the generated check value CAC(t) together with the encrypted vehicle data group in the database.

[0049] Optionally, the integrity check of the encrypted vehicle data group that needs to be accessed after encryption by the time-correlation scrambling method specifically includes:

[0050] Obtain the time stamp corresponding to the encrypted vehicle data group that needs to be accessed;

[0051] Match the corresponding key from the key database according to the obtained time stamp;

[0052] Obtain the encrypted vehicle data group that needs to be accessed stored in the database, denoted as Data;

[0053] Obtain the check value corresponding to the vehicle data to be accessed in the database;

[0054] Calculate the check value of the Data and compare it with the check value corresponding to the encrypted vehicle data group to be accessed in the database;

[0055] If the check values are equal, the encrypted vehicle data group to be accessed passes the data integrity check;

[0056] If the check values are not equal, the encrypted vehicle data group to be accessed fails the data integrity check.

[0057] Optionally, decrypting the encrypted vehicle data group to be accessed through the data decryption strategy specifically includes:

[0058] Obtain the timestamp t corresponding to the encrypted vehicle data group to be accessed from the database;

[0059] Match the corresponding key k(t) from the key database according to the timestamp t;

[0060] Decrypt each piece of data in the encrypted vehicle data group:

[0061]

[0062] The present invention has the following beneficial effects:

[0063] 1. By setting speed, temperature, wheel speed, fuel level, and acceleration sensors at key parts of the vehicle, such as the differential, engine coolant pipeline, wheel axle, bottom of the fuel tank, and chassis, various key data of the vehicle can be monitored in real time. The real-time acquisition of this data ensures comprehensive monitoring of the vehicle's operating status, including information such as the vehicle's driving speed, engine temperature, and fuel consumption. This approach provides basic data for subsequent data analysis and intelligent decision-making, effectively avoiding decision-making errors caused by data absence and improving the accuracy of vehicle management and maintenance. When collecting vehicle data, the data collection frequency can be dynamically adjusted according to changes in vehicle speed or acceleration, which can effectively reduce the collection of irrelevant data and avoid excessive unnecessary data storage and processing. For example, when the vehicle is traveling at high speed, the collection frequency can be increased, while when it is traveling at low speed or stopped, the frequency can be decreased. This mechanism not only reduces the storage pressure of the system but also optimizes the use of computing resources, improving the system's response speed and processing efficiency. The time-domain scrambling strategy is used to encrypt the collected vehicle data, effectively enhancing data security. This encryption method takes into account the time attribute of the data and adopts a dynamic encryption mechanism, making it difficult to crack even if the data is stolen during storage or transmission. Through the time-domain scrambling strategy, the encrypted data can effectively prevent malicious attacks and data leakage, ensuring the privacy and security of sensitive vehicle information. When storing and accessing encrypted data, integrity verification is performed on the encrypted data through the time-correlation scrambling method, which can effectively prevent data tampering during transmission or storage. During the verification process, a dynamic verification mechanism combining timestamps and scrambling factors ensures the authenticity and integrity of the data at any time. Even if the data is tampered with during transmission, the system can detect abnormalities through verification, preventing the use of incorrect data and thus ensuring the reliability and accuracy of the system. When accessing encrypted vehicle data, the encrypted data is effectively decrypted by matching the key with the timestamp and the decryption strategy, ensuring the availability of the encrypted data. This process ensures that while the data is protected during storage, it can still be restored to the original data during legitimate access, meeting the requirements of the vehicle management system for real-time data access and ensuring the efficient utilization of data.

[0064] 2. By setting a vehicle speed threshold and adjusting the acquisition frequency, the problems of data redundancy and low storage efficiency are solved. When the vehicle speed exceeds the preset vehicle speed threshold, the data acquisition frequency is adjusted to once per second, while when the vehicle speed is lower than the threshold, the acquisition frequency is reduced to once every two seconds. This adjustment can reasonably reduce or increase the data acquisition frequency according to the change of vehicle speed. Specifically, when the vehicle is driving at high speed, the vehicle speed changes rapidly and the demand for real-time data is high. Therefore, acquiring data at a higher frequency ensures the timeliness and accuracy of the data. When the vehicle is driving at a low speed or stopped, the vehicle speed changes slowly and the requirement for data real-time is relatively low. Reducing the acquisition frequency reduces the storage and calculation pressure and avoids the generation of unnecessary redundant data, significantly improving the resource utilization efficiency of the system and the utilization rate of the storage space. By setting an acceleration threshold and adjusting the acquisition frequency, the problem of insufficient response to vehicle dynamic changes is solved. When the absolute value of the acceleration is greater than or equal to the acceleration threshold, the acquisition frequency of vehicle data is adjusted to twice per second; when the acceleration is less than the threshold, the frequency is reduced to once per second. This mechanism can ensure that when the vehicle undergoes large dynamic changes such as acceleration or deceleration, the data acquisition is more frequent, capable of recording the acceleration fluctuations of the vehicle in real time and ensuring higher-precision data at these critical moments. In the case of small acceleration changes, the acquisition frequency is reduced to avoid wasting system resources due to excessive acquisition of unnecessary data. This method of adjusting the acquisition frequency based on acceleration changes improves the flexibility and responsiveness of data acquisition, effectively meeting the requirements for data accuracy in different driving states. Dynamically adjusting the vehicle data acquisition frequency makes the acquisition process more in line with the actual driving situation. For example, when the vehicle is in complex road conditions such as emergency braking or rapid acceleration, the increased acquisition frequency can ensure that more key data is recorded and analyzed, providing more effective data for subsequent fault diagnosis, driving behavior analysis, and driving assistance systems. During normal driving, reducing the frequency avoids unnecessary resource waste, enabling the system to efficiently use the storage space and computing resources while ensuring the acquisition of necessary data. This not only reduces the data storage and processing costs but also enhances the response ability and decision-making accuracy of the real-time analysis system. The mechanism of dynamically adjusting the acquisition frequency helps save computing resources and bandwidth. When driving at high speed, the dynamic information of the vehicle changes greatly, and frequent data acquisition can more accurately capture these changes. In the case of low speed or small acceleration, reducing the acquisition frequency not only reduces the data storage burden but also avoids wasting bandwidth and computing power due to excessive acquisition of unnecessary duplicate data. This resource optimization scheme plays a positive role in the performance and improvement of in-vehicle systems in different driving environments, further optimizing the energy efficiency and stability of the vehicle control system.

[0065] 3. By generating dynamic keys through the oscillator function, the problem of easy cracking of static keys is solved. A dynamic key generation mechanism based on the oscillator function is adopted, and the vehicle speed, vehicle acceleration, and timestamp at the time of vehicle speed are combined through alternating oscillation to generate keys. This key generation method based on real-time dynamic data avoids the inherent risks of traditional static key schemes. That is, once the key is stolen by an attacker, all subsequent data will face security threats. By introducing the real-time dynamic characteristics of the vehicle, the key will change with the vehicle's driving state, such as vehicle speed, acceleration, etc., and the change of time, making the key for each encryption operation different, thus greatly increasing the difficulty of cracking the key and improving the security of data encryption. By combining vehicle speed, acceleration, and timestamp to generate keys, the problems of key reuse and time dependence in the encryption process are solved. By generating keys through the alternating oscillation of vehicle speed, acceleration, and timestamp, the timeliness and variability of the keys are ensured. Dynamic data such as vehicle speed and acceleration constantly change during vehicle driving, making each generated key unique and time-sensitive, avoiding the repeated use of static keys over a long period. Especially the introduction of the timestamp makes each key generation bound to time, preventing the risk of using the same key for the same data multiple times, and enhancing the confidentiality and encryption strength of the data. This dynamic key generation method based on time-varying data solves the deficiencies of traditional static keys in terms of security and improves the security protection ability of the data encryption system. By combining time-domain scrambling strategy with dynamic key encryption, the problem that traditional encryption methods cannot adapt to complex dynamic environments is solved. Encryption is carried out by combining the time-domain scrambling strategy with dynamically generated keys, solving the limitations of traditional encryption methods in the face of vehicle real-time data and dynamic changes. The time-domain scrambling strategy takes into account the timing characteristics of the data, ensures the encryption effect of the data through the real-time change of the key, and improves the encryption strength. As the vehicle speed, acceleration, and timestamp continuously change, the key also changes accordingly, ensuring the uniqueness and unpredictability of each encryption, which enables the system to effectively guarantee the security and integrity of the data in a complex dynamic environment and avoid security vulnerabilities caused by environmental changes.

[0066] 4. By using a key to scramble each piece of vehicle data, the problem of data leakage risk during the encryption process is solved. In this solution, by using a dynamically generated key to scramble each piece of vehicle data, it can be ensured that each data item is encrypted independently, thus greatly improving the security of data encryption. Even if an attacker obtains a part of the encrypted data, since each data item is scrambled with a different key, the attacker cannot directly crack the entire data set. This per-item scrambling encryption method makes the cracking of a single data item not affect other data, avoiding potential security risks caused by the leakage of the entire data. Through this decentralized encryption method, the system can effectively prevent the risks of data leakage, tampering, or theft, and protect the privacy of vehicle data. By introducing large prime numbers to increase the scrambling intensity, the problem of insufficient encryption strength in traditional encryption methods is solved. During the scrambling process, using large prime numbers as scrambling factors can significantly enhance the scrambling intensity. Large prime numbers as scrambling factors can effectively increase the computational complexity required to crack the scrambled data and significantly improve the anti-cracking ability of the encryption process. Through this design, even if an attacker has certain computing resources, it is difficult to obtain the original content of the data through brute force cracking or other conventional encryption cracking methods. This method of using large prime numbers to increase the scrambling intensity strengthens the data encryption protection mechanism and effectively prevents the threat of cracking algorithms to data security. By generating and storing the encrypted vehicle data set, the security problem of storing encrypted data is solved. The scrambled data generates a new vehicle data set, which is stored in the system as the encrypted data. The scrambling process converts the original data into scrambled data, which means that even if the data is illegally obtained during storage and transmission, external personnel cannot directly read its original content. Through this method, the encrypted data set provides strong protection for the system and ensures the security of the data during storage. The encrypted data set can not only effectively prevent data leakage but also effectively prevent data from being tampered with and forged after being stolen. By generating the scrambled vehicle data set, the security and reliability of the data recovery process are improved. In the process of generating the scrambled data set in this solution, it is ensured that each data item requires the correct key for decryption during recovery, thus ensuring the security and reliability of data recovery. During data transmission or storage, the scrambled vehicle data set exists as ciphertext and can only be restored to the original data during the decryption process. This allows only authorized users and devices to access the encrypted data, thus avoiding unauthorized access. Through this encryption mechanism, while ensuring the security of data storage, the system also guarantees the confidentiality of data during access.

[0067] 5. By generating a check value based on a timestamp-dependent scrambling factor, the problem of data tampering during transmission is solved. During data transmission, the encrypted vehicle data group may face the risks of tampering and forgery. By combining each piece of data with a timestamp-dependent scrambling factor to generate a check value, it can effectively prevent data from being tampered with during transmission or storage. The introduction of the timestamp ensures that the check value is closely related to the time sequence of the data. Any tampering or modification of the data during transmission will result in a mismatch of the check value, thus detecting anomalies in a timely manner. This check method combined with the timestamp effectively increases the intensity of data integrity verification and improves the security of the system during data transmission and storage. By introducing a time offset function, the problem of check consistency for data in different time periods is solved. The introduction of the time offset function makes the relationship between the check value and the timestamp closer, and by periodically adjusting the constant of the time offset function, the check value can be dynamically adjusted. In this way, even if the access time of the data changes, the check value will be adjusted according to the time offset, ensuring the integrity check consistency when the data is accessed at different times. The setting of the time offset function can avoid check errors caused by time differences or time synchronization problems, thereby improving the system's adaptability to time changes and the accuracy of the check, ensuring that the correct integrity check result can be obtained every time encrypted data is accessed. By combining hash calculation with the product of bitwise multiplication by the time offset function, the problem of inadaptability of traditional check methods in complex data structures is solved. Traditional data integrity check methods often tend to have inaccurate checks when faced with large-scale complex data. By combining hash calculation with the product of bitwise multiplication by the time offset function, the generation of the check value can take into account each element of the data, and according to the dynamic adjustment of the time offset function, a strongly correlated check value is generated. This method can provide more efficient and accurate integrity verification when dealing with large-scale and complex vehicle data, avoiding errors and inconsistencies that may occur in simple check methods in complex data structures. By storing the generated check value together with the encrypted vehicle data group, the security of the stored data is enhanced. During data storage, storing only the encrypted vehicle data group alone may not fully guarantee the security and integrity of the data during subsequent access. By storing the generated check value together with the encrypted vehicle data group, it can be ensured that the system can perform effective integrity verification whenever data needs to be accessed. This approach enhances the security of the storage system, enabling the system to quickly identify anomalies through the check mechanism even if the data is damaged during storage, thus ensuring the integrity and accuracy of the data. By combining the check mechanism with the scrambling method, the problem of separation between data verification and the encryption / decryption process is solved. Traditional encryption schemes often have a certain isolation between the encrypted data and the data verification process, resulting in the inability to synchronize the check mechanism during data decryption.The verification method that combines scrambling with a time offset function is implemented synchronously with the encrypted data storage, enabling the combination of verification information and encryption information during the data storage phase to ensure that the verification mechanism can be executed promptly while decrypting. This combination method improves the smoothness of the data access process and guarantees the integrity verification of data during decryption, reducing the potential risks brought by the asynchronous encryption and decryption processes.

[0068] 6. By matching the timestamp with the key, the problem of key loss or incorrect matching is solved, improving the security of data access. When storing and transmitting encrypted data, the correctness and matching of the key are crucial for ensuring data security. By matching the corresponding key from the key database according to the timestamp, it is ensured that the correct and time-related key is used each time the encrypted vehicle data group is accessed. This not only effectively solves the problem of incorrect decryption of data caused by key loss, incorrect matching or synchronization issues in traditional systems, but also improves the efficiency of key management, reducing the risk of human errors and security vulnerabilities. Through the precise matching of the timestamp and the key, the security and accuracy of data access are ensured. By obtaining the check value corresponding to the vehicle data, the problems of data tampering and forgery are solved, ensuring the integrity of data transmission. During the process of data storage and transmission, the encrypted vehicle data may face the risk of being tampered with or forged. By obtaining the check value corresponding to the vehicle data in the database and comparing it with the calculated check value, it is possible to effectively detect whether the data has been tampered with during transmission or storage. If the check values are not equal, the system will promptly identify the situation where the data has been tampered with and reject the decryption of the data. This method ensures that only the untampered data can successfully pass the integrity check and be decrypted smoothly in any data that needs to be accessed, greatly enhancing the data integrity guarantee. Through the data integrity check mechanism, the effectiveness of the encrypted data is solved, ensuring the credibility of the data. Even after the data is encrypted, it is still necessary to ensure the authenticity and effectiveness of the data during transmission. Through the calculation and comparison of the check values, it can effectively ensure that the encrypted data has not been damaged during transmission and storage. Only when the data has not been tampered with will the check values match, thus realizing the data integrity check. The check mechanism can judge the effectiveness of the data, avoiding the incorrect decryption and use of incomplete or damaged data, and ensuring that the data is always in a trustworthy state. Through the real-time check mechanism, the problem that the system fails to detect data tampering in a timely manner is solved, improving the system response ability. The check mechanism is not only executed in real time during the data transmission process, but also can verify the integrity of the data at any time. This solves the problem that it is difficult to detect data tampering in a timely manner in traditional methods. By continuously checking the transmitted data, the system can quickly respond and reject the data requests with tampered data. This mechanism enhances the real-time response ability of the system and prevents the long-term risks that may be brought by tampered data. Through the matching of the check values, the sequentiality and consistency of vehicle data access are ensured. In a complex system, the vehicle data accessed at different times may face problems such as different versions or inconsistent checks. Through the design of associating the check value with the timestamp, it is ensured that the data accessed at different times can successfully pass the check and maintain consistency during the access process. Even if the data is accessed at different times, the system can ensure that it is still complete and reliable during decryption, thus avoiding data inconsistency problems caused by data version or time confusion.

[0069] 7. By matching the timestamp with the key, the security and accuracy of the decryption operation are ensured, and the key synchronization problem is solved. In the process of data encryption and decryption, the management and synchronization of keys are the key to ensuring security. By obtaining the timestamp corresponding to the encrypted vehicle data group and matching the corresponding key from the key database, it can be ensured that the key used for each decryption operation is the latest and matches the key at the time of storage, thus solving the problems of key obsolescence or incorrect matching in the traditional decryption process. This step ensures that accurate and secure data can be obtained for each decryption, avoiding decryption failures or data errors caused by key out-of-sync. Through the precise matching of timestamps, incorrect data decryption is prevented, and the risk of data leakage is avoided. If an incorrect key is used during decryption, it may lead to data errors or leakage. Therefore, by precisely matching the corresponding key according to the timestamp, the risk of decrypting with an incorrect key is avoided. This method effectively prevents problems such as leakage, tampering, or damage caused by decrypting with an expired or incorrect key, ensuring the accuracy and confidentiality of the data after decryption, thereby enhancing the overall security of the system. By ensuring the consistency of the decryption operation, the reliability and consistency of data access are ensured. Each time the encrypted vehicle data group is accessed, the consistency of the decryption operation is ensured through the matching of the timestamp and the key. After the vehicle data is stored and encrypted, the original data can only be restored after being decrypted with the correct key. This decryption mechanism ensures the consistency of data access and is not affected by time delays or network fluctuations, guaranteeing that the vehicle data can be accurately decrypted and restored under any circumstances, ensuring the reliability of the data during multiple accesses. By decrypting each piece of data, the accuracy and fine-grainedness of data decryption are solved. By decrypting each piece of data in the vehicle data group item by item, it is ensured that each piece of data undergoes separate and precise decryption processing. This fine-grained decryption operation avoids omissions or errors during overall decryption, ensuring the complete restoration and accuracy of each piece of data. Compared with the traditional method of decrypting all data at once, item-by-item decryption can improve the accuracy of the decryption process and avoid systematic errors or security risks during data decryption. BRIEF DESCRIPTION OF THE DRAWINGS

[0070] Figure 1 It is a schematic diagram of the process of the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0071] Next, the technical solutions in the embodiments of the present invention will be clearly and completely described in conjunction with the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative efforts shall fall within the protection scope of the present invention.

[0072] Embodiment, refer toFigure 1 , an industrial data acquisition and management method based on vehicle control digitization, including:

[0073] Set a vehicle speed sensor on the vehicle differential to obtain the vehicle speed, with the unit of km / h, and record the obtained vehicle speed as v;

[0074] Set a temperature sensor on the coolant pipeline of the vehicle engine to obtain the engine temperature, with the unit of °C, and record the obtained engine temperature as T;

[0075] Set a wheel speed sensor on the vehicle wheel axle to obtain the wheel speed, with the unit of rpm, and record the obtained wheel speed as ω;

[0076] Set an oil quantity sensor at the bottom of the vehicle fuel tank to obtain the oil quantity in the fuel tank, with the unit of L, and record the obtained oil quantity as Q;

[0077] Set an acceleration sensor on the vehicle chassis to obtain the vehicle acceleration, with the unit of m / s 2 , and record the obtained vehicle acceleration as a;

[0078] Set a vehicle data group and record it as D;

[0079] Add the obtained vehicle data to the vehicle data group to get D = [v, T, ω, Q, a];

[0080] Adjust the vehicle data acquisition frequency according to the vehicle speed or acceleration;

[0081] Encrypt the collected vehicle data through a time domain scrambling strategy, and store the encrypted vehicle data group and the time stamp when the vehicle data is obtained in the database;

[0082] When it is necessary to access the stored encrypted vehicle data group, perform integrity verification on the encrypted vehicle data group to be accessed through the time correlation scrambling method;

[0083] When the encrypted vehicle data group to be accessed passes the integrity verification, decrypt the encrypted vehicle data group to be accessed through the data decryption strategy;

[0084] When the encrypted vehicle data group to be accessed fails the integrity verification, return that the integrity verification fails and reject data decryption.

[0085] By installing sensors for vehicle speed, temperature, wheel speed, fuel level, and acceleration at key components such as the differential, engine coolant pipeline, wheel axles, bottom of the fuel tank, and chassis of the vehicle, various key data of the vehicle can be monitored in real time. The real-time acquisition of this data ensures comprehensive monitoring of the vehicle's operating status, including information such as the driving speed, engine temperature, and fuel consumption. This approach provides the basic data for subsequent data analysis and intelligent decision-making, effectively avoiding decision-making errors caused by data absence and improving the accuracy of vehicle management and maintenance. When collecting vehicle data, the data collection frequency can be dynamically adjusted according to changes in vehicle speed or acceleration, which can effectively reduce the collection of irrelevant data and avoid excessive unnecessary data storage and processing. For example, when the vehicle is traveling at high speed, the collection frequency can be increased, while when it is traveling at low speed or stationary, the frequency can be decreased. This mechanism not only reduces the storage pressure on the system but also optimizes the use of computing resources, improving the system's response speed and processing efficiency. The time-domain scrambling strategy is used to encrypt the collected vehicle data, effectively enhancing data security. This encryption method takes into account the time attribute of the data and adopts a dynamic encryption mechanism, making it difficult to crack even if the data is stolen during storage or transmission. Through the time-domain scrambling strategy, the encrypted data can effectively prevent malicious attacks and data leakage, ensuring the privacy and security of sensitive vehicle information. When storing and accessing encrypted data, integrity verification is performed on the encrypted data using the time-correlation scrambling method, which can effectively prevent data tampering during transmission or storage. During the verification process, a dynamic verification mechanism that combines timestamps and scrambling factors ensures the authenticity and integrity of the data at any time. Even if the data is tampered with during transmission, the system can detect anomalies through verification, preventing the use of incorrect data and thus ensuring the reliability and accuracy of the system. When accessing encrypted vehicle data, the encrypted data is effectively decrypted by matching the key with the timestamp and the decryption strategy, ensuring the availability of the encrypted data. This process ensures that while the data is protected during storage, it can still be restored to the original data during legitimate access, meeting the real-time data access requirements of the vehicle management system and ensuring the efficient utilization of the data.

[0086] The adjustment of the vehicle data collection frequency according to vehicle speed or acceleration specifically includes:

[0087] Set a vehicle speed threshold, denoted as v threshold

[0088] When v ≥ v threshold Adjust the vehicle data collection frequency to once per second;

[0089] When v < v threshold Adjust the vehicle data collection frequency to once every two seconds;

[0090] Set an acceleration threshold, denoted as athreshold ;

[0091] When |a| > a threshold Adjust the vehicle data acquisition frequency to twice per second;

[0092] When |a| ≤ a threshold Adjust the vehicle data acquisition frequency to once per second.

[0093] By setting a vehicle speed threshold and adjusting the acquisition frequency, the problems of data redundancy and low storage efficiency are solved. When the vehicle speed exceeds the preset vehicle speed threshold, the data acquisition frequency is adjusted to once per second, while when the vehicle speed is lower than the threshold, the acquisition frequency is reduced to once every two seconds. This adjustment can reasonably reduce or increase the data acquisition frequency according to the change of vehicle speed. Specifically, when the vehicle is traveling at a high speed, the vehicle speed changes rapidly and the demand for real-time data is high. Therefore, acquiring data at a high frequency ensures the timeliness and accuracy of the data. When the vehicle is traveling at a low speed or in a stopped state, the vehicle speed changes slowly and the requirement for data real-time is relatively low. Reducing the acquisition frequency reduces the storage and calculation pressure and avoids the generation of unnecessary redundant data, significantly improving the resource utilization efficiency of the system and the utilization rate of the storage space. By setting an acceleration threshold and adjusting the acquisition frequency, the problem of insufficient response to vehicle dynamic changes is solved. When the absolute value of the acceleration is greater than or equal to the acceleration threshold, the acquisition frequency of vehicle data is adjusted to twice per second; when the acceleration is less than the threshold, the frequency is reduced to once per second. This mechanism can ensure that when the vehicle undergoes large dynamic changes such as acceleration or deceleration, the data acquisition is more frequent, and the acceleration fluctuations of the vehicle can be recorded in real time to ensure higher-precision data at these critical moments. When the acceleration change is small, the acquisition frequency is reduced to avoid wasting system resources due to excessive acquisition of unnecessary data. This method of adjusting the acquisition frequency based on acceleration changes improves the flexibility and responsiveness of data acquisition and effectively meets the requirements for data accuracy in different driving states. Dynamically adjusting the vehicle data acquisition frequency makes the acquisition process more in line with the actual driving situation. For example, when the vehicle is in complex road conditions such as emergency braking or rapid acceleration, the increase in the acquisition frequency can ensure that more key data is recorded and analyzed, thus providing more effective data for subsequent fault diagnosis, driving behavior analysis, and driving assistance systems. During normal driving, reducing the frequency avoids unnecessary resource waste, enabling the system to efficiently use the storage space and computing resources while ensuring the acquisition of necessary data. This not only reduces the data storage and processing costs but also enhances the response ability and decision-making accuracy of the real-time analysis system. The mechanism of dynamically adjusting the acquisition frequency helps to save computing resources and bandwidth. When the vehicle is traveling at a high speed, the dynamic information of the vehicle changes greatly, and frequent data acquisition can more accurately capture these changes. When the vehicle is traveling at a low speed or with a small acceleration, reducing the acquisition frequency not only reduces the data storage burden but also avoids wasting bandwidth and computing power due to excessive acquisition of unnecessary duplicate data. This resource optimization scheme plays a positive role in improving the performance and performance of the in-vehicle system in different driving environments, further optimizing the energy efficiency and stability of the vehicle control system.

[0094] The encrypted vehicle data collected is encrypted through a time-domain scrambling strategy, which specifically includes:

[0095] Design of dynamic key generation based on oscillator function:

[0096] Generate a key through the alternating oscillation of vehicle speed, vehicle acceleration, and the timestamp when the vehicle speed is collected, and denote the generated key as k(t);

[0097] The oscillator function is specifically:

[0098]

[0099] where v is the obtained vehicle speed; a is the obtained vehicle acceleration; t is the timestamp when the vehicle speed is obtained; is the exclusive OR operation;

[0100] The key k(t) = Oscillator(v, a, t);

[0101] Store the key k(t) in the key database.

[0102] Generate a dynamic key through the oscillator function, which solves the problem that static keys are easily cracked. Adopt a dynamic key generation mechanism based on the oscillator function, and combine the vehicle speed, vehicle acceleration, and timestamp at the time of vehicle speed through an alternating oscillation effect to generate a key. This key generation method based on real-time dynamic data avoids the inherent risks of traditional static key schemes. That is, once the key is stolen by an attacker, all subsequent data will face security threats. By introducing the real-time dynamic characteristics of the vehicle, the key will change with the vehicle's driving state, such as vehicle speed, acceleration, etc., and the change of time, making the key for each encryption operation different, thus greatly increasing the difficulty of cracking the key and improving the security of data encryption. By combining vehicle speed, acceleration, and timestamp to generate a key, the problems of key reuse and time dependence in the encryption process are solved. By generating a key through the alternating oscillation effect of vehicle speed, acceleration, and timestamp, the timeliness and variability of the key are ensured. Dynamic data such as vehicle speed and acceleration continuously change during vehicle driving, making each generated key unique and timely, avoiding the repeated use of static keys over a long period of time. Especially the introduction of the timestamp makes each key generation bound to time, preventing the risk of using the same key for the same data multiple times, and enhancing the confidentiality and encryption strength of the data. This dynamic key generation method based on time-varying data solves the deficiencies of traditional static keys in terms of security and improves the security protection ability of the data encryption system. By combining the time-domain scrambling strategy with dynamic key encryption, the problem that traditional encryption methods cannot adapt to complex dynamic environments is solved. Encryption is carried out by combining the time-domain scrambling strategy with a dynamically generated key, solving the limitations of traditional encryption methods in the face of vehicle real-time data and dynamic changes. The time-domain scrambling strategy takes into account the timing characteristics of the data, ensures the encryption effect of the data through the real-time change of the key, and improves the encryption strength. As the vehicle speed, acceleration, and timestamp continuously change, the key also changes accordingly, ensuring the uniqueness and unpredictability of each encryption, which enables the system to effectively guarantee the security and integrity of the data in a complex dynamic environment and avoid security vulnerabilities caused by environmental changes.

[0103] The encrypted vehicle data collected through the time-domain scrambling strategy specifically includes:

[0104] Scramble each data in the vehicle data group D using the key k(t);

[0105] The scrambling process is as follows:

[0106]

[0107] where D i is the i-th data in the vehicle data group D; is the data after scrambling the i-th data in the vehicle data group D; P is a large prime number used to increase the scrambling intensity;

[0108] Set the encrypted vehicle data group, denoted as D 加扰 ;

[0109] Add the scrambled data of each item in the calculated vehicle data group D to D 加扰 to obtain D 加扰 = [v 加扰 , T 加扰 , ω 加扰 , Q 加扰 , a 加扰 .

[0110] By using a key to scramble each piece of vehicle data in a data group, the problem of data leakage risk during the encryption process is solved. In this solution, by using a dynamically generated key to scramble each piece of vehicle data, it can be ensured that each data item is encrypted independently, thus greatly improving the security of data encryption. Even if an attacker obtains a part of the encrypted data, since each data item is scrambled with a different key, the attacker cannot directly crack the entire data group. This per-item scrambling encryption method makes the cracking of a single data item not affect other data, avoiding potential security risks caused by overall data leakage. Through this decentralized encryption method, the system can effectively prevent the risks of data leakage, tampering, or theft, and safeguard the privacy of vehicle data. By introducing large prime numbers to increase the scrambling intensity, the problem of insufficient encryption intensity in traditional encryption methods is solved. During the scrambling process, using large prime numbers as scrambling factors can significantly enhance the scrambling intensity. Large prime numbers as scrambling factors can effectively increase the computational complexity required to crack the scrambled data and significantly improve the anti-cracking ability of the encryption process. Through this design, even if an attacker has certain computing resources, it is difficult to obtain the original content of the data through brute force cracking or other conventional encryption cracking methods. This way of using large prime numbers to increase the scrambling intensity strengthens the protection mechanism of data encryption and effectively prevents the threat of cracking algorithms to data security. By generating and storing the encrypted vehicle data group, the security problem of storing encrypted data is solved. The scrambled data generates a new vehicle data group, which is stored in the system as the encrypted data. The scrambling process converts the original data into scrambled data, which means that even if the data is illegally obtained during storage and transmission, external personnel cannot directly read its original content. Through this method, the encrypted data group provides strong protection for the system and ensures the security of data during storage. The encrypted data group can not only effectively prevent data leakage but also effectively prevent the data from being tampered with and forged after being stolen. By generating the scrambled vehicle data group, the security and reliability of the data recovery process are improved. In the process of generating the scrambled data group in this solution, it is ensured that each piece of data requires the correct key for decryption during recovery, thus ensuring the security and reliability of data recovery. During data transmission or storage, the scrambled vehicle data group exists as ciphertext and can only be restored to the original data during the decryption process. This allows only authorized users and devices to access the encrypted data, thus avoiding unauthorized access. Through this encryption mechanism, while ensuring the security of data storage, the system also guarantees the confidentiality of data during access.

[0111] The integrity verification of the encrypted vehicle data group that needs to be accessed is performed on the encrypted vehicle data group through the time correlation scrambling method, which specifically includes:

[0112] The check value CAC(t) is generated by combining each piece of data in the encrypted vehicle data group with a scrambling factor based on a timestamp, specifically as follows:

[0113]

[0114] where m is the total number of elements in the encrypted vehicle data group; Hash is the hash calculation; ⊙ is the product of bitwise AND with the time offset function Shift(t); Shift(t) is the time offset function;

[0115] The time offset function Shift(t) is specifically as follows:

[0116] Set a constant as indicating the periodic adjustment of time;

[0117]

[0118] The generated check value CAC(t) is stored in the database together with the encrypted vehicle data group.

[0119] By generating a check value based on a timestamp-based scrambling factor, the problem of data tampering during transmission is solved. During data transmission, the encrypted vehicle data group may face the risks of tampering and forgery. By combining each piece of data with a timestamp-based scrambling factor to generate a check value, it can effectively prevent data from being tampered with during transmission or storage. The introduction of the timestamp ensures that the check value is closely related to the time sequence of the data. Any tampering or modification of the data during transmission will result in a mismatch of the check value, thus detecting anomalies in a timely manner. This check method combined with the timestamp effectively increases the intensity of data integrity verification and improves the security of the system during data transmission and storage. By introducing a time offset function, the problem of check consistency for data in different time periods is solved. The introduction of the time offset function makes the relationship between the check value and the timestamp closer, and by periodically adjusting the constant of the time offset function, the check value can be dynamically adjusted. In this way, even if the access time of the data changes, the check value will be adjusted according to the time offset, ensuring the integrity verification consistency when the data is accessed at different times. The setting of the time offset function can avoid check errors caused by time differences or time synchronization problems, thereby improving the system's adaptability to time changes and the accuracy of verification, ensuring that the correct integrity verification result can be obtained every time encrypted data is accessed. By combining hash calculation with the product of each bit and the time offset function, the problem of inadaptability of traditional check methods in complex data structures is solved. Traditional data integrity check methods tend to have inaccurate check problems when faced with large-scale complex data. By combining hash calculation with the product of each bit and the time offset function, the generation of the check value can take into account each element of the data, and according to the dynamic adjustment of the time offset function, a strongly correlated check value is generated. This method can provide more efficient and accurate integrity verification when dealing with large-scale and complex vehicle data, avoiding errors and inconsistencies that may occur in simple check methods in complex data structures. By storing the generated check value together with the encrypted vehicle data group, the security of the stored data is enhanced. During data storage, storing only the encrypted vehicle data group alone may not fully guarantee the security and integrity of the data during subsequent access. By storing the generated check value together with the encrypted vehicle data group, it can be ensured that the system can perform effective integrity verification whenever data needs to be accessed. This practice enhances the security of the storage system, enabling the system to quickly identify anomalies through the check mechanism even if the data is damaged during storage, thus ensuring the integrity and accuracy of the data. By combining the check mechanism with the scrambling method, the problem of separation between data verification and the encryption / decryption process is solved. Traditional encryption schemes often have a certain isolation between the encrypted data and the data verification process, resulting in the inability to synchronize the check mechanism when decrypting the data.By synchronously implementing the verification method that combines scrambling with a time offset function with encrypted data storage, it is possible to combine verification information and encryption information during the data storage phase, ensuring that the verification mechanism can be quickly executed while decrypting. This combination method improves the smoothness of the data access process and guarantees the integrity verification of data during decryption, reducing the potential risks brought by asynchronous encryption and decryption processes.

[0120] The integrity verification of the encrypted vehicle data group to be accessed after encryption by the time-correlation scrambling method specifically includes:

[0121] Obtain the time stamp corresponding to the encrypted vehicle data group to be accessed;

[0122] Match the corresponding key from the key database according to the obtained time stamp;

[0123] Obtain the encrypted vehicle data group to be accessed stored in the database, denoted as Data;

[0124] Obtain the verification value corresponding to the vehicle data to be accessed in the database;

[0125] Calculate the verification value of Data and compare it with the verification value corresponding to the encrypted vehicle data group to be accessed in the database;

[0126] If the verification values are equal, it means that when obtaining the encrypted vehicle data group to be accessed, it has not been tampered with during the transmission process, and the obtained encrypted vehicle data group to be accessed passes the data integrity verification;

[0127] If the verification values are not equal, it means that when obtaining the encrypted vehicle data group to be accessed, it has been tampered with during the transmission process, and the obtained encrypted vehicle data group to be accessed fails the data integrity verification.

[0128] By matching the timestamp with the key, the problem of key loss or incorrect matching is solved, improving the security of data access. When storing and transmitting encrypted data, the correctness and matching of the key are crucial for ensuring data security. By matching the corresponding key from the key database according to the timestamp, it is ensured that the correct and time-related key is used each time encrypted vehicle data groups are accessed. This not only effectively solves the problem of incorrect decryption of data caused by key loss, incorrect matching, or synchronization issues in traditional systems, but also improves the efficiency of key management and reduces the risk of human errors and security vulnerabilities. Through the precise matching of the timestamp and the key, the security and accuracy of data access are ensured. By obtaining the check value corresponding to the vehicle data, the problems of data tampering and forgery are solved, ensuring the integrity of data transmission. During the process of data storage and transmission, the encrypted vehicle data may face the risk of being tampered with or forged. By obtaining the check value corresponding to the vehicle data in the database and comparing it with the calculated check value, it is possible to effectively detect whether the data has been tampered with during transmission or storage. If the check values are not equal, the system will promptly identify the situation where the data has been tampered with and reject the decryption of the data. This method ensures that only untampered data can successfully pass the integrity check and be decrypted successfully in any data that needs to be accessed, greatly enhancing the data integrity guarantee. Through the data integrity check mechanism, the validity of encrypted data is solved, ensuring the credibility of the data. Even after the data is encrypted, it is still necessary to ensure the authenticity and validity of the data during transmission. Through the calculation and comparison of the check value, it can effectively ensure that the encrypted data has not been damaged during transmission and storage. Only when the data has not been tampered with will the check values match, thus achieving the data integrity check. The check mechanism can determine the validity of the data, avoiding the incorrect decryption and use of incomplete or damaged data, and ensuring that the data is always in a trustworthy state. Through the real-time check mechanism, the problem that the system fails to detect data tampering in a timely manner is solved, improving the system response ability. The check mechanism is not only executed in real-time during data transmission, but also can verify the integrity of the data at any time. This solves the problem in traditional methods that it is difficult to detect data tampering in a timely manner. By continuously checking the transmitted data, the system can quickly respond and reject the data requests for tampered data. This mechanism enhances the real-time response ability of the system and prevents the long-term risks that may be brought by tampered data. Through the matching of the check values, the sequentiality and consistency of vehicle data access are ensured. In a complex system, vehicle data accessed at different times may face problems such as different versions or inconsistent checks. Through the design of associating the check value with the timestamp, it is ensured that the data accessed at different times can successfully pass the check and maintain consistency during the access process. Even if the data is accessed at different times, the system can ensure that it is still complete and reliable during decryption, thus avoiding data inconsistency problems caused by data version or time confusion.

[0129] The decryption of the encrypted vehicle data group to be accessed through the data decryption policy specifically includes:

[0130] Obtain the timestamp t corresponding to the encrypted vehicle data group to be accessed from the database;

[0131] Match the corresponding key k(t) from the key database according to the timestamp t;

[0132] Decrypt each piece of data in the encrypted vehicle data group:

[0133]

[0134] By matching the timestamp with the key, the security and accuracy of the decryption operation are ensured, and the key synchronization problem is solved. In the process of data encryption and decryption, the management and synchronization of keys are the keys to ensuring security. By obtaining the timestamp corresponding to the encrypted vehicle data group and matching the corresponding key from the key database, it can be ensured that the key used for each decryption operation is the latest and matches the key at the time of storage, thus solving the problems of key obsolescence or incorrect matching in the traditional decryption process. This step ensures that accurate and secure data can be obtained for each decryption, avoiding decryption failures or data errors caused by key out-of-sync. Through the precise matching of timestamps, incorrect data decryption is prevented, and the risk of data leakage is avoided. If the wrong key is used for decryption, it may lead to data errors or leakage. Therefore, by precisely matching the corresponding key according to the timestamp, the risk of decrypting with the wrong key is avoided. This method effectively prevents problems such as leakage, tampering, or damage caused by decrypting with an expired or incorrect key, ensuring the accuracy and confidentiality of the data after decryption, thereby enhancing the overall security of the system. Through the consistency of the decryption operation, the reliability and consistency of data access are ensured. Each time the encrypted vehicle data group is accessed, the consistency of the decryption operation is ensured through the matching of the timestamp and the key. After the vehicle data is stored and encrypted, the original data can only be restored after being decrypted with the correct key. This decryption mechanism ensures the consistency of data access and is not affected by time delays or network fluctuations, ensuring that the vehicle data can be accurately decrypted and restored under any circumstances, and ensuring the reliability of the data during multiple accesses. By decrypting each piece of data, the accuracy and fine-grained problems of data decryption are solved. By decrypting each piece of data in the vehicle data group item by item, it is ensured that each piece of data undergoes separate and precise decryption processing. This fine-grained decryption operation avoids omissions or errors during overall decryption, ensuring the complete restoration and accuracy of each piece of data. Compared with the traditional method of decrypting all data at once, item-by-item decryption can improve the accuracy of the decryption process and avoid systematic errors or security risks during data decryption.

[0135] It should be noted that in this text, relational terms such as first and second are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any actual relationship or order between these entities or operations. Moreover, the term "comprising", "including" or any other variant thereof is intended to cover non-exclusive inclusion, such that a process, method, article or device comprising a series of elements not only includes those elements but also includes other elements not expressly listed, or elements inherent to such process, method, article or device.

[0136] The above are only the preferred embodiments of the present invention. It should be pointed out that for those of ordinary skill in the art, without departing from the technical principle of the present invention, several improvements and refinements can be made, and these improvements and refinements should also be regarded as the protection scope of the present invention.

Claims

1. An industrial data collection and management method based on vehicle control digitization, characterized in that: include: A speed sensor is provided at the vehicle differential to obtain the vehicle speed in km / h, and the obtained speed is recorded as v; A temperature sensor is provided on the coolant pipeline of the vehicle engine to obtain the engine temperature in °C, and the obtained engine temperature is recorded as T; A wheel speed sensor is set on the wheel shaft of the vehicle to obtain the wheel speed in rpm, and the obtained wheel speed is recorded as ω; A fuel level sensor is provided at the bottom of the vehicle fuel tank to obtain the fuel level in the fuel tank in L, and the obtained fuel level is recorded as Q; An acceleration sensor is installed on the vehicle chassis to obtain the vehicle acceleration in m / s 2 , the obtained vehicle acceleration is recorded as a; Set the vehicle data group to be D; Add the acquired vehicle data to the vehicle data group to obtain D = [v, T, ω, Q, a]; Adjust vehicle data collection frequency according to vehicle speed or acceleration; Encrypting the collected vehicle data through a time domain scrambling strategy, and storing the encrypted vehicle data group and the timestamp when the vehicle data was obtained in a database; When the stored encrypted vehicle data group needs to be accessed, the encrypted vehicle data group integrity check is performed on the encrypted vehicle data group that needs to be accessed by using a time-related scrambling method; When the encrypted vehicle data group that needs to be accessed passes the integrity check, the encrypted vehicle data group that needs to be accessed is decrypted using the data decryption strategy; If the encrypted vehicle data group to be accessed fails the integrity check, the integrity check fails and the data decryption is rejected.

2. The industrial data collection and management method based on vehicle control digitization according to claim 1 is characterized in that: The adjusting the vehicle data collection frequency according to the vehicle speed or acceleration specifically includes: Set the vehicle speed threshold, denoted as v threshold When v ≥ v threshold When the vehicle data collection frequency is adjusted to once per second; When v <v threshold When adjusting the vehicle data collection frequency to once every two seconds; Set the acceleration threshold, denoted as a threshold ; when |a|>a threshold When adjusting the vehicle data collection frequency to twice per second; When |a|≤a threshold When adjusting the vehicle data collection frequency to once per second.

3. The industrial data collection and management method based on vehicle control digitization according to claim 1 is characterized in that: The collected vehicle data is encrypted by a time domain scrambling strategy, specifically including: Design of dynamic key generation based on oscillator function: The key is generated by alternating the vehicle speed, the vehicle acceleration and the timestamp when the vehicle speed is collected, and the generated key is recorded as k(t); The oscillator function is: Wherein, v is the obtained vehicle speed; a is the obtained vehicle acceleration; t is the timestamp when the vehicle speed is obtained; is an XOR operation; Key k(t) = Oscillator(v, a, t); Store the key k(t) in the key database.

4. The industrial data collection and management method based on vehicle control digitization according to claim 3 is characterized in that: The collected vehicle data is encrypted by a time domain scrambling strategy, specifically including: Use the key k(t) to scramble each data in the vehicle data set D; The scrambling process is as follows: Among them, D i is the i-th item of data in vehicle data set D; is the scrambled data of the i-th item in the vehicle data group D; P is a large prime number used to increase the scrambling strength; Set the encrypted vehicle data group, denoted as D 加扰 ; Add the scrambled data of each item in the calculated vehicle data set D to D 加扰 In the D 加扰 =[v 加扰 ,T 加扰 ,ω 加扰 ,Q 加扰 ,a 加扰 ].

5. The industrial data collection and management method based on vehicle control digitization according to claim 4 is characterized in that: The integrity check of the encrypted vehicle data group to be accessed by using a time-related scrambling method specifically includes: The check value CAC(t) is generated by combining each data item in the encrypted vehicle data group with a scrambling factor based on the timestamp, specifically: Wherein, m is the total number of elements in the encrypted vehicle data group; Hash is the hash calculation; ⊙ is the bit-by-bit product of the time shift function Shift(t); Shift(t) is the time shift function; The time shift function Shift(t) is specifically: Set a constant to Indicates the periodic adjustment of time; The generated verification value CAC(t) is stored in the database together with the encrypted vehicle data set.

6. The industrial data collection and management method based on vehicle control digitization according to claim 5 is characterized in that: The integrity check of the encrypted vehicle data group to be accessed by using a time-related scrambling method specifically includes: Obtain the timestamp corresponding to the encrypted vehicle data group that needs to be accessed; Match the corresponding key from the key database according to the obtained timestamp; Obtain the encrypted vehicle data group that needs to be accessed and stored in the database, recorded as Data; Obtain the check value corresponding to the vehicle data to be accessed in the database; Calculate the check value of Data and compare it with the check value in the database corresponding to the encrypted vehicle data group to be accessed; If the check values ​​are equal, the encrypted vehicle data group to be accessed has passed the data integrity check; If the verification values ​​are not equal, the encrypted vehicle data set to be accessed has not passed the data integrity check.

7. The industrial data collection and management method based on vehicle control digitization according to claim 4 is characterized in that: Decrypting the encrypted vehicle data group that needs to be accessed by using the data decryption strategy specifically includes: Obtain the timestamp t corresponding to the encrypted vehicle data group to be accessed from the database; Match the corresponding key k(t) from the key database according to the timestamp t; Decrypt each item of data in the encrypted vehicle data group:

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