Adaptive protection method, system, device and storage medium for vehicle privacy data

Abstract

The application relates to a self-adaptive protection method, system, device and storage medium for vehicle privacy data, the method is executed on a vehicle-mounted local edge computing node, and the method comprises the following steps: acquiring vehicle information, loading a signal description file corresponding to the vehicle information from local storage; real-time receiving of an original data stream sent by a vehicle CAN bus, and stream parsing of the original data stream in chronological order to obtain CAN messages; matching the CAN messages with the signal description file to identify privacy data in the original data stream; acquiring a dynamic shielding strategy, and performing real-time shielding processing on the privacy data according to the dynamic shielding strategy to generate a compliant data stream with shielded privacy. The application realizes accurate identification of privacy data by introducing a dynamic shielding strategy; meanwhile, different vehicle models can be easily adapted through a signal description file which is configurable and can be dynamically updated, so that the deployment and maintenance costs are reduced.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of privacy data protection, in particular to a vehicle privacy data adaptive protection method, system, device and storage medium. BACKGROUND

[0002] With the rapid development of Internet of Vehicles technology, modern vehicles have become highly interconnected mobile data centers, continuously generating massive amounts of data through a large number of sensors, which have great value for optimizing traffic flow, realizing advanced driving assistance (ADAS) and automatic driving, and warning vehicle faults. However, a large amount of personal sensitive information (PII) is inevitably contained in vehicle data, such as precise positioning, driving behavior, in-vehicle audio and video, etc. The leakage of these information will bring serious user privacy risk and property safety risk, therefore, personal data needs to be strictly protected and the principle of "Privacy by Design" should be followed.

[0003] Currently, there are many challenges in vehicle data privacy protection, such as complex CAN bus data processing, Controller Area Network (CAN) is the main communication protocol of vehicle network, its data is broadcasted in binary frame format, privacy data and operation data are mixed together, it is extremely difficult to separate and identify privacy data in real time and efficiently; lack of adaptability and compatibility, existing desensitization schemes are mostly static or predefined strategies, it is difficult to flexibly adjust according to the real-time preferences of users and the dynamic state of vehicles (such as location, driving mode), at the same time, the definition of CAN data of different manufacturers and different vehicle models is greatly different, leading to the difficulty of widely deploying and maintaining a single solution. SUMMARY

[0004] The present application provides a vehicle privacy data adaptive protection method, system, device and storage medium to at least solve the problems of difficult identification of vehicle privacy data and poor desensitization flexibility in related technologies.

[0005] In a first aspect, the present application provides a vehicle privacy data adaptive protection method, which is executed on a vehicle local edge computing node, the method comprising:

[0006] obtaining vehicle information, dynamically loading a signal description file and a dynamic shielding strategy corresponding to the vehicle information from a local storage;

[0007] real-time receiving of original data stream sent by vehicle CAN bus to obtain CAN message;

[0008] matching the CAN message with the signal description file to identify the privacy data in the original data stream;

[0009] According to the dynamic shielding strategy, the privacy data is shielded in real time to generate a compliant data stream with shielded privacy.

[0010] Specifically, the signal description file pre-defines a shielding signal ID and a switch signal ID.

[0011] The matching of the CAN message with the signal description file to identify the privacy data in the original data stream includes:

[0012] The CAN ID is read from the CAN message and compared with an ID list in the signal description file to determine the ID type of the CAN ID.

[0013] If the CAN ID is a shielding signal ID, the CAN message is a privacy data item that needs to be protected; if the CAN ID is a switch signal ID, the CAN message is used to control the start and stop of the privacy shielding function; and if the CAN ID is another signal ID, the CAN message is non-privacy data.

[0014] Specifically, the dynamic shielding strategy includes:

[0015] The dynamic signal includes user configuration, vehicle state signal, environment signal, and compliance rule.

[0016] A preset strategy rule library is obtained, and a dynamic shielding strategy or a dynamically adjusted shielding strategy is generated according to the dynamic signal and the strategy rule library.

[0017] According to the order from high to low of the priority, the strategy rule library includes:

[0018] The mandatory rule shields according to the requirements of laws and regulations.

[0019] The user-defined rule shields according to user preferences.

[0020] The dynamic scene rule triggers the corresponding shielding strategy when entering a preset geographic area, or shields the driving data according to the driving mode to avoid behavior analysis.

[0021] Specifically, after identifying the privacy data in the original data stream, the method further includes:

[0022] When the CAN ID belongs to the shielding signal ID, the current state of the switch signal associated with the CAN ID is queried, and if the current state is "open shielding", the shielding operation is performed; and if the current state is "close shielding", the CAN message is not shielded.

[0023] When the CAN ID belongs to a switch signal ID, the value of the CAN message is parsed, and the corresponding global switch variable in the memory is updated;

[0024] When the CAN ID belongs to other signal IDs, the CAN message is not processed.

[0025] Specifically, the execution of the masking operation includes:

[0026] The CAN message is parsed, and a reverse mask is generated according to the start bit, length, and endianness in the CAN message;

[0027] According to the mask and the data payload of the CAN message, all bit positions of the target signal are cleared to zero, and other bit positions remain unchanged.

[0028] For big-endian format data, the mask is calculated and cleared in byte order; for little-endian format data, the mask is calculated and cleared from the end of the data array to the front.

[0029] Specifically, the preset process of the signal description file includes:

[0030] According to the vehicle model, the corresponding DBC file is obtained and parsed to obtain the CAN ID, signal name, start bit, length, and end sequence;

[0031] An initial signal description file is generated according to the CAN ID, signal name, start bit, length, and end sequence;

[0032] According to the preset rule, the sensitive signal is marked in the initial signal description file, the associated switch signal is set, the signal description file is generated, and the signal description file is output in JSON or XML format.

[0033] Specifically, the dynamic loading process of the signal description file includes:

[0034] When the vehicle starts or a specific event is triggered, the corresponding signal description file is automatically loaded according to the current vehicle model;

[0035] The latest signal description file or privacy policy is dynamically issued through the OTA remote update mechanism, and the latest signal description file or privacy policy is pushed to the vehicle end through the API interface;

[0036] When a new vehicle model is launched or the data definition of an existing vehicle model changes, the signal description file is updated;

[0037] Obtain the user privacy preference, and dynamically adjust the signal description file and the masking strategy in real time according to the user privacy preference.

[0038] In a second aspect, the present application provides a vehicle privacy data adaptive protection system, comprising:

[0039] a data receiving module, configured to acquire vehicle information, dynamically load a signal description file and a dynamic shielding strategy corresponding to the vehicle information from a local storage, and receive a raw data stream sent by a vehicle CAN bus in real time to obtain a CAN message;

[0040] a signal analysis module, configured to match the CAN message with the signal description file, and identify privacy data in the raw data stream;

[0041] a data shielding module, configured to shield the privacy data in real time according to the dynamic shielding strategy, and generate a desensitized data stream with shielded privacy.

[0042] In a third aspect, the present application provides a computer device, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor implements the vehicle privacy data adaptive protection method according to the first aspect.

[0043] In a fourth aspect, the present application provides a computer readable storage medium, having a computer program stored thereon, wherein the program is executable on a processor to implement the vehicle privacy data adaptive protection method according to the first aspect.

[0044] The vehicle privacy data adaptive protection method, system, device and storage medium provided by the embodiments of the present application have at least the following technical effects:

[0045] The present application can adjust the shielding strategy in real time according to user configuration and vehicle dynamic signals by introducing a dynamic shielding strategy, accurately identify privacy data, flexibly protect individual privacy, and balance privacy protection and data utilization; meanwhile, through the signal description file (such as DBC file conversion) and modular design which can be configured and dynamically updated, the present application can easily adapt to different vehicle models, and greatly reduce deployment and maintenance costs.

[0046] The details of one or more embodiments of the present application are presented in the following drawings and description to make other features, objects and advantages of the present application more apparent. BRIEF DESCRIPTION OF DRAWINGS

[0047] The drawings described herein are used to provide further understanding of the present application, and form a part of the present application. The illustrative embodiments of the present application and their descriptions are used to explain the present application, and do not constitute an improper limitation on the present application. In the drawings:

[0048] Figure 1 is a flowchart of a vehicle privacy data adaptive protection method in an embodiment of the present application;

[0049] Figure 2 is a flow chart of a method for adaptive protection of vehicle privacy data in another embodiment of the present application;

[0050] Figure 3 is a structural block diagram of an electronic device in an embodiment of the present application. DETAILED DESCRIPTION

[0051] In order to make the objects, technical solutions and advantages of the present application clearer, the present application will be described and illustrated in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present application and should not be used to limit the present application. Based on the embodiments provided by the present application, all other embodiments obtained by those of ordinary skill in the art without creative work fall within the scope of the present application.

[0052] Obviously, the accompanying drawings in the following description are only some examples or embodiments of the present application, and for those of ordinary skill in the art, the present application can be applied to other similar scenarios without creative work on the basis of these drawings. In addition, it can be understood that although the efforts made in this development process can be complex and lengthy, for those of ordinary skill in the art related to the content disclosed in the present application, some design, manufacture or production changes on the basis of the technical content disclosed in the present application are only routine technical means and should not be understood as insufficient disclosure of the present application.

[0053] In the present application, "embodiment" means that the specific features, structures or characteristics described in conjunction with the embodiment can be included in at least one embodiment of the present application. The phrase appears at various places in the specification does not necessarily refer to the same embodiment, nor is it independent or alternative to other embodiments. It is explicitly and implicitly understood by those of ordinary skill in the art that the embodiments described in the present application can be combined with other embodiments without conflict.

[0054] Unless otherwise defined, technical terms and scientific terms used in the present application shall have the same meaning as commonly understood by one of ordinary skill in the art to which this application pertains. The terms "a", "an", "one", "this", and the like, as used in the present application, do not denote a limitation of quantity and can mean one or more. The terms "comprising", "containing", "having", and the like, as used in the present application, are intended to cover the process, method, system, product, or apparatus that comprises, contains, or has the specified steps or units, without limiting to the listed steps or units. The terms "connected", "coupled", and the like, as used in the present application, are not limited to direct connections or physical connections, but can include electrical connections, whether direct or indirect. The term "multiple" refers to two or more. The term "and / or" describes the associated relationship of associated objects, which means that there can be three relationships, for example, "A and / or B" can mean that A exists alone, A and B exist together, and B exists alone. The character " / " generally represents an "or" relationship between the front and rear associated objects. The terms "first", "second", "third", and the like, as used in the present application, are merely to distinguish similar objects, and do not represent a specific order of the objects.

[0055] Embodiment 1

[0056] The embodiment of the present application provides a self-adaptive protection method for vehicle privacy data, which is executed on a vehicle-mounted local edge computing node, Figure 1 is a flowchart of the method, as Figure 1 shown, the self-adaptive protection method of the embodiment of the present application is realized by the following steps.

[0057] Step S1, acquiring vehicle information, dynamically loading a signal description file and a dynamic shielding strategy corresponding to the vehicle information from a local storage. Specifically, the preset process of the signal description file includes: obtaining the corresponding DBC file according to the vehicle type and parsing to obtain CAN ID, signal name, start bit, length and end sequence; generating an initial signal description file according to the CAN ID, signal name, start bit, length and end sequence; marking sensitive signals and setting associated switch signals in the initial signal description file according to a preset rule, generating the signal description file and outputting in JSON or XML format. Wherein, the signal description file predefines shielding signal ID and switch signal ID.

[0058] The dynamic loading process of the signal description file includes:

[0059] When the vehicle starts or a specific event is triggered, the corresponding signal description file is automatically loaded according to the current vehicle model; the latest signal description file or privacy policy is dynamically distributed through the OTA remote update mechanism, and the latest signal description file or privacy policy is pushed to the vehicle through the API interface; when a new model is launched or the data definition of an existing model changes, the signal description file is updated; user privacy preferences are obtained, and the signal description file and blocking policy are dynamically adjusted in real time according to the user privacy preferences.

[0060] The specific dynamic masking strategy includes:

[0061] The system acquires dynamic signals, including user configuration, vehicle status signals, environmental signals, and compliance rules; it also acquires a preset policy rule base and generates or dynamically adjusts a blocking strategy based on the dynamic signals and the policy rule base. The policy rule base, in descending order of priority, includes: mandatory rules for blocking according to regulatory requirements; user-defined rules for blocking based on user preferences; and dynamic scenario rules that trigger corresponding blocking strategies when entering a preset geographical area, or block driving data based on driving mode to avoid behavioral analysis. The dynamic blocking strategy of this application adjusts the blocking strategy based on the following dynamic signals: user privacy preferences set through the in-vehicle interface or mobile application; real-time vehicle location, driving mode, or geofence trigger conditions; and automated matching of built-in compliance rules.

[0062] Step S2: Receive the raw data stream sent by the vehicle's CAN bus in real time, and parse the raw data stream in chronological order to obtain CAN messages. Specifically, capture the raw binary data stream through the CAN controller hardware interface of the on-board local edge computing node; extract key fields from the binary data stream, including CAN ID, data length, and data payload.

[0063] Specifically, the original binary data stream is captured through the CAN controller hardware interface of the vehicle-mounted edge node (such as an ECU or a gateway). For example, a frame of CAN data (hexadecimal: 0x123 8 01 02 03 04 05 06 07 08) is received. Then, key fields are extracted, wherein the CAN ID is extracted from the arbitration segment (such as 0x123) for identifying the signal type (such as vehicle speed, GPS coordinates, etc.); the data length (DLC) is obtained from the control segment (such as 8 indicating that the data segment has 8 bytes); and the data payload is extracted as 8 bytes of data (such as 01 02 03 04 05 06 07 08). Subsequent matching of the signal description file is performed, and a preset signal description file (such as in JSON / DBC format) needs to be loaded to define how to parse the data payload. The data segment is parsed according to the rules, and the target signal is extracted from the data payload according to the definition of the signal description file: big-endian and little-endian. Finally, cross-byte signals are processed. If the signal crosses multiple bytes (such as start bit = 12 and length = 20), the starting byte and offset are located (such as bits 12-15 of the first byte + the second byte + bits 0-3 of the third byte); the cross-byte data is spliced, and the order is adjusted according to the endianness; and a scaling factor and an offset are applied.

[0064] Step S3, the CAN message is matched with the signal description file to identify the privacy data in the original data stream. Specifically, the CAN ID is read from the CAN message, and the CAN ID is compared with the ID list in the signal description file to determine the ID type of the CAN ID. If the CAN ID is a shield signal ID, the CAN message is used to define the privacy data item to be protected; if the CAN ID is a switch signal ID, the CAN message is used to control the start and stop of the privacy shielding function; and if the CAN ID is another signal ID, the CAN message is non-privacy data.

[0065] When the CAN ID belongs to the shield signal ID, the current state of the switch signal associated with the CAN ID is queried. If the current state is “open shielding”, the shielding operation is performed; and if the current state is “close shielding”, the CAN message is not shielded. When the CAN ID belongs to the switch signal ID, the value of the CAN message is parsed, and the corresponding global switch variable in the memory is updated. When the CAN ID belongs to another signal ID, the CAN message is not processed.

[0066] Step S4, the privacy data is shielded in real time according to the dynamic shielding strategy to generate a compliant data stream with shielded privacy.

[0067] In the process of performing the shielding operation, the CAN message is parsed, and a reverse mask is generated according to the start bit, length and size end format in the CAN message; according to the mask and the data payload of the CAN message, the bit positions of the target signal are all cleared to zero, and the other bit positions remain unchanged. For big-endian format data, the mask is calculated and cleared in byte order; for little-endian format data, the mask is calculated and cleared from the end of the data array to the front.

[0068] The application receives and parses the original data frame of the CAN bus in real time through the vehicle local edge computing node; identifies the privacy data in the data frame according to the pre-set or dynamically loaded signal description file; obtains dynamic signals such as user configuration and vehicle state, and dynamically adjusts the shielding strategy through the intelligent strategy engine; and generates a data stream with shielded privacy by shielding the identified privacy data in real time according to the strategy, which can solve the problems of complex CAN bus privacy data separation, low processing efficiency caused by limited vehicle local computing power, static shielding strategy and cross-model adaptation in the prior art. The application can efficiently and timely protect privacy data under limited vehicle computing power, realize self-adaptability according to user and environment dynamic adjustment, and flexibly adapt to multiple vehicle models, achieving an effective balance between protecting user privacy and data utilization value.

[0069] Embodiment 2

[0070] The adaptive protection method for vehicle privacy data of the embodiment is executed on a vehicle local edge computing node, and the implementation process includes the following steps.

[0071] Step one, real-time receive original data frame from vehicle CAN bus, real-time analyze and shield the data frame. Specifically, obtain vehicle information, load the signal description file corresponding to the vehicle information from the local storage, real-time receive the original data stream sent by the vehicle CAN bus, and streamingly analyze the original data stream in time sequence to obtain CAN message.

[0072] Among them, according to the pre-set or dynamically loaded signal description file, it is identified whether the data frame contains privacy data and which privacy data it contains, therefore, the signal description file is the key of the application, which defines the signals that need to be processed, including the switch signal for controlling the start and stop of shielding function and the shielding signal that needs to be protected.

[0073] Specifically, the signal description file is a key component of the application, which defines how to parse the original CAN message data (usually in binary format) into vehicle signals with actual meaning. Each signal in the file contains the following key information:

[0074] CAN ID, used to uniquely identify the CAN message, the system quickly locates the message containing the target signal through this ID;

[0075] Start, the starting bit position of the signal in the CAN message data payload;

[0076] Len, the bit length of the signal;

[0077] IsBigEndian, indicating the byte order of the signal, i.e., whether the high-order byte or the low-order byte of multi-byte data is stored at the starting address of the memory. This is crucial for correctly parsing signals that span bytes.

[0078] These pieces of information collectively and accurately describe the location and format of the signal in the CAN message data payload. Signal description files can be divided into two categories: switch signals and shield signals. Switch signals are used to control the opening or closing of specific privacy shielding functions (e.g., whether the user agrees to share location information), while shield signals indicate specific data items that need privacy protection (e.g., GPS coordinates, driver biometric data).

[0079] These signal description files can be pre-configured and generated by engineers or privacy compliance teams of automobile manufacturers. They can be converted and extended based on industry-standard DBC (Database CAN) files, which are commonly used formats for describing signal definitions in CAN networks. This invention supports automatic conversion of user-readable signal names into the precise bit-level shielding signal files required by this method by configuring them, which greatly simplifies the configuration process, improves compatibility, and enhances ease of use. In addition, to address the differences in CAN bus data definitions for different vehicle models, each vehicle model can be individually configured with its own shielding description file, ensuring accurate adaptation to the data definitions of specific vehicle models.

[0080] In a preferred embodiment, signal description files can be dynamically loaded and updated, achieving high flexibility and scalability, including the following cases:

[0081] 1. Runtime loading: the on-board local edge computing node (such as ECU or dedicated gateway) can automatically load the corresponding signal description file according to the current vehicle model (e.g., identified by the vehicle identification number VIN) at system startup or upon triggering of a specific event. This means that different software versions do not need to be compiled for each vehicle model, and a general software framework can adapt to various vehicle models by loading different configuration files.

[0082] 2. Remote update and delivery: signal description files and related privacy policy configurations can be dynamically delivered and updated through OTA (Over-The-Air) remote update mechanisms. Automobile manufacturers can push the latest configurations to the vehicle end through API interfaces, thereby adapting without physical intervention:

[0083] 3. New vehicle models or data definitions: When a new vehicle model is launched or the data definition of an existing vehicle model changes, only the corresponding DBC file or signal description file needs to be updated.

[0084] 4. Evolving privacy regulations: As global data privacy regulations are updated, blocking strategies can be quickly adjusted to ensure compliance.

[0085] 5. Changes in user privacy preferences allow users to adjust their privacy settings in real time through the in-vehicle system or mobile application. These settings will be dynamically reflected in the loading and blocking strategies of the signal description file.

[0086] This dynamic loading and updating capability enables the system to flexibly respond to data differences in multi-vehicle environments and ensures that privacy protection strategies are always in sync with the latest business needs, regulatory requirements, and user preferences.

[0087] Step 2: Signal masking process. The CAN message is matched with the signal description file to identify privacy data in the original data stream; a dynamic masking strategy is obtained, and the privacy data is masked in real time according to the dynamic masking strategy to generate a de-identified data stream with masked privacy. The specific implementation process is described below.

[0088] When the vehicle system is running, it acquires dynamic signals based on configuration files, such as user-defined privacy preferences via the in-vehicle screen, the vehicle's current GPS location, and the current driving mode (e.g., private mode). Then, an intelligent policy engine dynamically generates or adjusts privacy data masking strategies based on these dynamic signals. For example, when the vehicle enters a user-defined home area, the masking level for location information is automatically increased. Finally, based on this dynamic policy, real-time masking is performed on identified privacy data. Specifically, when a CAN message ID is determined to be a signal that needs to be masked, and its corresponding switch signal is in the "on" state, the system precisely calculates a bitmask and clears the corresponding bit in the CAN message data payload to zero, thus completing the masking without affecting other data. After processing, a compliant, privacy-masked data stream is generated for subsequent local analysis or limited cloud transmission.

[0089] When the switch signal is set to open shielding, the system will perform a signal clearing operation. This operation aims to clear the bits of specific signals in the CAN message data payload, thereby achieving the purpose of shielding private data. The algorithm will perform precise calculations and operations based on the signal's start bit, length, and endianness (Big-Endian or Little-Endian) format.

[0090] For Big-Endian format data, the algorithm starts from the start bit of the signal, and operates byte by byte or cross-byte. First, the starting byte where the signal is located is calculated, and if the signal spans multiple bytes, the part of the signal in the starting byte is processed first and cleared by a bitmask. Then, the complete byte occupied by the signal in the middle is cleared. Finally, the byte where the signal ends is processed, and the remaining part is cleared by a bitmask. If the signal is only in one byte, the range of bits that need to be cleared in the byte is calculated directly, and the corresponding bitmask is applied to clear them.

[0091] For Little-Endian format data, the algorithm starts from the characteristics of Little-Endian format, i.e., the low byte is in front. First, the starting byte where the signal is located is determined (calculated from the end of the data array). If the signal spans multiple bytes, the part of the signal in the starting byte is processed first and cleared by a bitmask. Then, the complete byte occupied by the signal in the middle is cleared. Finally, the byte where the signal ends is processed, and the remaining part is cleared by a bitmask. If the signal is only in one byte, the range of bits that need to be cleared in the byte is calculated directly, and the corresponding bitmask is applied to clear them.

[0092] This algorithm ensures that the specified privacy signal is cleared efficiently and accurately without affecting other non-privacy data in the CAN message. This underlying and fine-grained processing capability is the key to realizing real-time privacy protection in the limited computing power environment of the vehicle.

[0093] The shielding mechanism of the embodiments of the present application can use a variety of efficient data desensitization algorithms, including but not limited to Dynamic Data Masking (DDM), Tokenization, Format Preserving Encryption (FPE), Data Obfuscation, and Data Scrambling. The choice of specific algorithm depends on the type of privacy data, the degree of sensitivity, and the subsequent data utilization requirements. For example, for scenarios that require to preserve data format but hide the real content, FPE can be used; for scenarios that require to completely replace sensitive data, Tokenization can be used. These algorithms are optimized to adapt to the limited computing resources of the vehicle ECU, ensuring extremely low latency when processing high-throughput CAN data. For example, GPU or AI accelerators integrated in the ECU can be used for parallel computing to speed up data processing and shielding.

[0094] In addition, the mechanism also includes an efficient data flow management module responsible for guiding the compliant and desensitized data flow to different destinations after the shielding operation is completed: part of the data may be analyzed locally for vehicle control or driving assistance functions; another part of the data that has been strictly desensitized may be allowed to be transmitted to the cloud for macro data analysis, product improvement or remote diagnosis. This combination of local processing and selective cloud transmission maximizes the balance between data utilization value and privacy protection needs, while reducing data transmission and storage costs. By processing in real time at the data source (CAN bus) and edge node, the invention effectively reduces the risk of data leakage in an un-desensitized state and ensures immediate protection of private data.

[0095] In summary, compared with the prior art, the adaptive protection method for vehicle privacy data of the present application has the beneficial effects that:

[0096] 1. High efficiency, by highly optimized algorithm processing at the edge node of the data source (CAN bus), the problem of real-time shielding of high-throughput data under limited computing power on vehicles is solved, and the delay and data transmission cost are reduced;

[0097] 2. Adaptability, an intelligent strategy engine is introduced, which can adjust the shielding strategy in real time according to user configuration and vehicle dynamic signals, realizing accurate, flexible and personalized privacy protection, balancing privacy protection and data utilization;

[0098] 3. Compatibility and scalability, through configurable and dynamically updateable signal description files (such as DBC file conversion) and modular design, it is easy to adapt to different vehicle models, greatly reducing deployment and maintenance costs;

[0099] 4. Compliance and security, real-time processing from the data acquisition source fundamentally prevents the risk of sensitive data leakage in an un-desensitized state, effectively meets the requirements of global data privacy regulations, and improves user trust.

[0100] Embodiment 3

[0101] The adaptive protection method for vehicle privacy data of the present embodiment refers to Figure 2 , and the specific execution process is as follows:

[0102] After the software is started, the system first loads the signal shielding description file for the current vehicle model from the local storage. This file can be a JSON or XML format configuration file, which defines a series of switch signals and shielding signals.

[0103] For example, a switch signal can be defined as: { "name": "GPSEnable", "can_id": "0x100", "start": 0, "len": 1, "is_big_endian": true, "type": "switch"}; a mask signal can be defined as: { "name": "Latitude", "can_id": "0x200", "start": 8, "len": 32, "is_big_endian": true, "type": "mask"}.

[0104] To improve the ease of use, the adaptive protection of the embodiment can directly read the standard DBC file, and automatically generate the description file in the above format according to the signal name (such as "Latitude") selected by the user.

[0105] Then the system accesses the CAN bus and starts to process the received CAN messages in time sequence. For each CAN message, the CAN ID is read and compared with the ID list in the signal mask description file. If the ID of the current message is not in the list, it means that it does not contain any signal that needs to be concerned, and the system will quickly skip to ensure the processing efficiency.

[0106] If the ID matches and is defined as a switch signal ID, the system will parse the value of the signal (for example, extract the bit of the GPS switch from the CAN message to represent 0 or 1), and update the corresponding global switch variable in the memory. After processing, the next message is processed.

[0107] If the ID matches and is defined as a mask signal ID (such as 0x200), the system will check the current state of the associated switch signal (such as GPSEnable). If the switch is "on mask" (value is 1), the mask operation is performed. The mask operation is realized by precise bit operation: according to the start bit, length and big-endian format of the signal, a reverse bit mask (mask) is generated, and then the mask is "and" with the data payload of the CAN message (data &= mask), that is, the bit of the target signal is all cleared to zero, and other bits remain unchanged. If the switch is "off mask" (value is 0), the mask signal is ignored and no modification is made to the message.

[0108] Through the above process, the application can complete the adaptive masking of private data in real time and efficiently without interrupting the data stream.

[0109] The adaptive protection of vehicle privacy data provided by the embodiment can have adaptive strategies and multi-vehicle adaptation. Specifically, an intelligent strategy engine is constructed, which is the core of adaptability and can subscribe to multiple dynamic signal sources and then generate corresponding shielding strategies.

[0110] For example, a user can set a "privacy mode" through an in-vehicle interface or a mobile phone App. When the user turns on the "privacy mode", the strategy engine sends an instruction to the signal processing module to set all switch signals related to location and driving behavior to "open shielding".

[0111] The strategy engine can continuously obtain vehicle dynamic signals of the vehicle, such as GPS position. When it is detected that the vehicle enters a user-pre-set "home" or "company" or other geofence area, the shielding level of the location information can be automatically improved (for example, from precise coordinate shielding to fuzzy area, or complete shielding).

[0112] The engine has built-in key regulatory requirements. For example, for vehicles sold to Europe, the engine will automatically turn on shielding for certain sensitive data to meet the requirements of GDPR.

[0113] When the application needs to be deployed to a new vehicle model, engineers do not need to modify the core code. Only the DBC file of the vehicle model needs to be obtained, a new signal shielding description file is generated through a matching tool, and it is deployed to the vehicle. The whole system supports OTA (Over-The-Air) update, and new description files or strategy rules can be remotely issued, realizing low-cost, high-efficiency multi-vehicle compatibility and later maintenance.

[0114] In summary, the application provides an end-to-end adaptive privacy protection solution implemented on a vehicle-mounted edge node. Through innovative system architecture and algorithm design, it effectively solves many challenges faced by existing technologies, has very high practical value and broad application prospects.

[0115] In a second aspect, the embodiments of the application provide a vehicle privacy data adaptive protection system for executing the vehicle privacy data adaptive protection method as described in any of the above embodiments. The system comprises:

[0116] A data receiving module is configured to obtain vehicle information, load a signal description file corresponding to the vehicle information from a local storage, receive an original data stream sent by a CAN bus of the vehicle in real time, and streamingly analyze the original data stream in time sequence to obtain a CAN message.

[0117] A signal analysis module is configured to match the CAN message with the signal description file, and identify privacy data in the original data stream.

[0118] A data shielding module is configured to acquire a dynamic shielding strategy, shield the privacy data in real time according to the dynamic shielding strategy, and generate a desensitized data stream of the shielded privacy.

[0119] It should be noted that the system provided in the embodiment is used to implement the above-mentioned embodiments, and the description of which has been made and will not be repeated. As used above, the terms "module", "unit", "sub-unit", and the like can be a combination of software and / or hardware that implements a predetermined function. Although the above embodiments describe the device preferably implemented in software, the implementation of hardware, or a combination of software and hardware, is also possible and contemplated.

[0120] In a third aspect, the embodiments of the present application provide an electronic device. As shown in FIG. 3, the electronic device can include a processor 11 and a memory 12 storing computer program instructions.

[0121] Specifically, the processor 11 can include a central processing unit (CPU), or an application specific integrated circuit (ASIC), or one or more integrated circuits configured to implement the embodiments of the present application.

[0122] The memory 12 can include a mass storage for data or instructions. By way of example and not limitation, the memory 12 can include a Hard Disk Drive (HDD), floppy disk drive, a Solid State Drive (SSD), flash memory, a Compact Disc Read Only Memory (CDROM), a Digital Versatile Disk (DVD), a magnetic tape, or a Universal Serial Bus (USB) drive, or a combination of two or more of these. The memory 12 can be removable and / or non-removable (or fixed) as appropriate. The memory 12 can be internal or external as appropriate. In particular embodiments, the memory 12 is a Non-Volatile memory. In particular embodiments, the memory 12 includes a Read-Only Memory (ROM) and a Random-Access Memory (RAM). The ROM can be a mask-programmed ROM, a Programmable ROM (PROM), an Erasable PROM (EPROM), an Electrically EPROM (EEPROM), an Electrically Alterable ROM (EAROM), or a FLASH, or a combination of two or more of these, as appropriate. The RAM can be a Static Random-Access Memory (SRAM) or a Dynamic Random-Access Memory (DRAM), which can be a Fast Page Mode Dynamic Random-Access Memory (FPMDRAM), an Extended Data Out Dynamic Random-Access Memory (EDODRAM), a Synchronous Dynamic Random-Access Memory (SDRAM), or the like, as appropriate.

[0123] The memory 12 can be used to store or buffer various data files required for processing and / or communication, and possible computer program instructions executed by the processor 11.

[0124] The processor 11 realizes the adaptive protection method of vehicle privacy data in any of the above embodiments by reading and executing the computer program instructions stored in the memory 12.

[0125] In an embodiment, the electronic device can further include a communication interface 13 and a bus 10. As shown in FIG. 3, the processor 11, the memory 12, and the communication interface 13 are connected through the bus 10 and complete communication with each other.

[0126] The communication interface 13 is used to realize the communication between the modules, devices, units and / or equipment in the embodiments of the present application. The communication interface 13 can also realize data communication with other components, such as external devices, image / data acquisition devices, databases, external storage, image / data processing workstations, etc.

[0127] Bus 10 includes a hardware, software, or both that couples components of electronic device to each other. Bus 10 includes, but is not limited to, at least one of a data bus, address bus, control bus, expansion bus, local bus, etc. By way of example and not limitation, bus 10 can include an Accelerated Graphics Port (AGP) or other graphics bus, an Extended Industry Standard Architecture (EISA) bus, a Front Side Bus (FSB), a Hyper Transport (HT) interconnect, an Industry Standard Architecture (ISA) bus, an InfiniBand (IB) interconnect, a Low Pin Count (LPC) bus, a memory bus, a Micro Channel Architecture (MCA) bus, a Peripheral Component Interconnect (PCI) bus, a PCI-Express (PCI-X) bus, a Serial Advanced Technology Attachment (SATA) bus, a Video Electronics Standards Association Local (VLB) bus, or another suitable bus or a combination of two or more of these. Where appropriate, bus 10 can include one or more buses. Although the present application is described and illustrated with a particular bus, the present application contemplates any suitable bus or interconnect.

[0128] In a fourth aspect, the embodiments of the present application provide a computer readable storage medium, having a program stored thereon, where the program is executed by a processor to implement the method for adaptive protection of vehicle privacy data according to the first aspect.

[0129] More specifically, the computer readable storage medium can include, but is not limited to, a portable disc, a hard disk, a random access memory, a read-only memory, an erasable programmable read-only memory, an optical storage device, a magnetic storage device, or any suitable combination of the above.

[0130] In possible implementation manners, the present application can also be implemented in the form of a program product, which comprises program codes for causing a terminal device to perform the steps of the method for adaptively protecting vehicle privacy data according to the first aspect when the program product is run on the terminal device.

[0131] The program code for executing the present application can be written in any combination of one or more programming languages, and can be executed entirely on the user device, partly on the user device, as a stand-alone software package, partly on the user device and partly on a remote device, or entirely on a remote device.

[0132] The technical features of the above-described embodiments can be combined in any manner. For brevity, not all possible combinations of the technical features in the above-described embodiments are described, but it should be understood that any combination of the technical features is within the scope of the present disclosure as long as the combination does not result in contradictions.

[0133] The above-described embodiments only express several implementation manners of the present application, and the description is relatively specific and detailed, but it should not be understood as a limitation on the scope of the patent. It should be pointed out that, for those skilled in the art, several modifications and improvements can be made without departing from the concept of the present application, and these are within the scope of protection of the present application. Therefore, the scope of protection of the patent of the present application should be subject to the appended claims.

Claims

1. An adaptive protection method for vehicle privacy data, characterized in that, The method is executed on an on-board local edge computing node, and the method includes: Obtain vehicle information and dynamically load the signal description file and dynamic blocking strategy corresponding to the vehicle information from local storage; It receives the raw data stream sent by the vehicle's CAN bus in real time and obtains CAN messages; The CAN message is matched with the signal description file to identify the privacy data in the original data stream; The privacy data is processed in real time according to the dynamic blocking strategy to generate a compliant data stream with blocked privacy. The generation of the dynamic shielding strategy includes: Acquire dynamic signals, including user configuration, vehicle status signals, environmental signals, and compliance rules; acquire a preset policy rule base, and generate or dynamically adjust a blocking policy based on the dynamic signals and the policy rule base.

2. The adaptive protection method according to claim 1, characterized in that, The signal description file predefines the shield signal ID and the switch signal ID; The step of matching the CAN message with the signal description file to identify privacy data in the original data stream includes: Read the CAN ID from the CAN message and compare the CAN ID with the ID list in the signal description file to determine the ID type of the CAN ID; If the CAN ID is a masking signal ID, then the CAN message contains privacy data that needs to be protected; if the CAN ID is a switch signal ID, then the CAN message is used to control the start and stop of the privacy masking function; if the CAN ID is any other signal ID, then the CAN message contains non-privacy data.

3. The adaptive protection method according to claim 1, characterized in that, The policy rule base, ordered from highest to lowest priority, includes: Mandatory rules, requiring blocking according to regulations; User-defined rules allow for blocking based on user preferences; Dynamic scene rules trigger corresponding blocking strategies when entering a preset geographical area, or block driving data based on driving mode to avoid behavior analysis.

4. The adaptive protection method according to claim 2, characterized in that, After identifying the privacy data in the original data stream, the method further includes: When the CAN ID belongs to the masking signal ID, query the current status of the switch signal associated with the CAN ID. If the current status is "masking on", then perform the masking operation; if the current status is "masking off", then do not mask the CAN message. When the CAN ID belongs to a switch signal ID, the value of the CAN message is parsed and the corresponding global switch variable in memory is updated; If the CAN ID belongs to another signal ID, the CAN message will not be processed.

5. The adaptive protection method according to claim 4, characterized in that, The masking operation includes: The CAN message is parsed, and an inverse mask is generated based on the start bit, length, and endianness of the CAN message. Based on the mask and the data payload of the CAN message, clear all bits of the target signal to zero, while leaving other bits unchanged; Specifically, for big-endian data, the mask is calculated and cleared to zero in byte order; for little-endian data, the mask is calculated and cleared to zero from the end of the data array backwards.

6. The adaptive protection method according to claim 1, characterized in that, The preset process for the signal description file includes: Obtain and parse the corresponding DBC file based on the vehicle model to obtain the CAN ID, signal name, start bit, length, and terminal sequence; An initial signal description file is generated based on the CAN ID, signal name, start bit, length, and end sequence. According to preset rules, sensitive signals are marked and associated switch signals are set in the initial signal description file, the signal description file is generated and output in JSON or XML format.

7. The adaptive protection method according to claim 1, characterized in that, The dynamic loading process of the signal description file includes: When the vehicle starts or a specific event is triggered, the corresponding signal description file is automatically loaded according to the current vehicle model; The latest signal description file or privacy policy is dynamically distributed through the OTA remote update mechanism, and pushed to the vehicle through the API interface. When a new model is launched or the data definition of an existing model changes, the signal description file should be updated. Obtain user privacy preferences and dynamically adjust the signal description file and blocking strategy in real time based on these preferences.

8. An adaptive protection system for vehicle privacy data, characterized in that, The system is used to perform the adaptive protection method for vehicle privacy data as described in any one of claims 1-7, the system comprising: The data receiving module is used to acquire vehicle information, dynamically load the signal description file and dynamic masking strategy corresponding to the vehicle information from local storage, and receive the raw data stream sent by the vehicle CAN bus in real time to obtain CAN messages. The signal parsing module is used to match the CAN message with the signal description file and identify the privacy data in the original data stream; The data masking module is used to perform real-time masking processing on the privacy data according to the dynamic masking strategy, and generate a de-identified data stream with masked privacy.

9. An electronic device, characterized in that, The system includes a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor, when executing the computer program, implements an adaptive protection method for vehicle privacy data as claimed in any one of claims 1 to 7.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the program is executed by the processor, it implements the adaptive protection method for vehicle privacy data as described in any one of claims 1 to 7.

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