Self-adaptive protection method, system and device for vehicle privacy data and storage medium

Abstract

The invention relates to a self-adaptive protection method, system and device for vehicle privacy data and a storage medium, the method is executed on a vehicle-mounted local edge computing node, and the method comprises the steps that vehicle information is acquired, and a signal description file corresponding to the vehicle information is loaded from a local storage; receiving an original data stream sent by a vehicle CAN bus in real time, and analyzing the original data stream according to a time sequence stream form to obtain a CAN message; matching the CAN message with the signal description file, and identifying private data in the original data stream; and obtaining a dynamic shielding strategy, performing real-time shielding processing on the privacy data according to the dynamic shielding strategy, and generating compliance data flow of which privacy is shielded. By introducing the dynamic shielding strategy, the privacy data can be accurately identified; and meanwhile, different vehicle types can be easily adapted through a configurable and dynamically-updated signal description file, so that the deployment and maintenance cost is reduced.

Description

Technical Field

[0001] This application relates to the field of privacy data protection technology, and in particular to adaptive protection methods, systems, devices and storage media for vehicle privacy data. Background Technology

[0002] With the rapid development of vehicle-to-everything (V2X) technology, modern vehicles have become highly interconnected mobile data centers, continuously generating massive amounts of data through numerous sensors. This data is of immense value in optimizing traffic flow, enabling advanced driver assistance systems (ADAS) and autonomous driving, and providing early warnings of vehicle malfunctions. However, vehicle data inevitably contains a large amount of personally identifiable information (PII), such as precise location data, driving behavior data, and in-vehicle audio and video data. The leakage of this information poses serious risks to user privacy and property security. Therefore, it is necessary to strictly protect personal data and adhere to the principle of "Privacy by Design."

[0003] Currently, in-vehicle data privacy protection faces numerous challenges. For example, CAN bus data processing is complex. Controller Area Network (CAN) is the main communication protocol for in-vehicle networks, and its data is broadcast in binary frame format. Privacy data is mixed with operational data, making it extremely difficult to separate and identify privacy data in real time and efficiently. Furthermore, there is a lack of adaptability and compatibility. Existing desensitization solutions are mostly static or predefined strategies, making it difficult to flexibly adjust according to users' real-time preferences and the dynamic status of the vehicle (such as location and driving mode). At the same time, the CAN data definitions of different manufacturers and different models vary greatly, making it difficult to widely deploy and maintain a single solution. Summary of the Invention

[0004] This application provides an adaptive protection method, system, device, and storage medium for vehicle privacy data, to at least solve the problems of difficulty in identifying vehicle privacy data and poor desensitization flexibility in related technologies.

[0005] In a first aspect, this application provides an adaptive protection method for vehicle privacy data, the method being executed on an in-vehicle local edge computing node, the method comprising: 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.

[0006] Specifically, the signal description file predefines the shielding signal ID and the switching 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.

[0007] Specifically, the dynamic shielding strategy includes: Acquire dynamic signals, including user configuration, vehicle status signals, environmental signals, and compliance rules; Obtain a preset policy rule base, and generate a dynamic blocking policy or dynamically adjust the blocking policy based on the dynamic signal and the policy rule base; 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.

[0008] Specifically, 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.

[0009] Specifically, 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.

[0010] Specifically, the preset process of 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.

[0011] Specifically, 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.

[0012] Secondly, this application provides an adaptive protection system for vehicle privacy data, 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.

[0013] Thirdly, this application provides a computer device including 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 the adaptive protection method for vehicle privacy data as described in the first aspect above.

[0014] Fourthly, this application provides a computer-readable storage medium having a computer program stored thereon that, when executed by a processor, implements the adaptive protection method for vehicle privacy data as described in the first aspect above.

[0015] The adaptive protection method, system, device, and storage medium for vehicle privacy data provided in this application have at least the following technical effects: This application introduces a dynamic shielding strategy, which can adjust the shielding strategy in real time according to user configuration and vehicle dynamic signals, achieving accurate identification of privacy data and flexible personalized privacy protection, balancing privacy protection and data utilization. At the same time, through configurable and dynamically updatable signal description files (such as DBC file conversion) and modular design, it can be easily adapted to different vehicle models, greatly reducing deployment and maintenance costs.

[0016] Details of one or more embodiments of this application are set forth in the following drawings and description to make other features, objects and advantages of this application more readily apparent. Attached Figure Description

[0017] The accompanying drawings, which are included to provide a further understanding of this application and form part of this application, illustrate exemplary embodiments and are used to explain this application, but do not constitute an undue limitation of this application. In the drawings: Figure 1 This is a flowchart of an adaptive protection method for vehicle privacy data in one embodiment of this application; Figure 2 This is a flowchart of an adaptive protection method for vehicle privacy data in another embodiment of this application; Figure 3 This is a structural block diagram of an electronic device according to an embodiment of this application. Detailed Implementation

[0018] To make the objectives, technical solutions, and advantages of this application clearer, the application is described and illustrated below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative and not intended to limit the scope of this application. All other embodiments obtained by those skilled in the art based on the embodiments provided in this application without inventive effort are within the scope of protection of this application.

[0019] Obviously, the accompanying drawings described below are merely some examples or embodiments of this application. Those skilled in the art can apply this application to other similar scenarios based on these drawings without any inventive effort. Furthermore, it is understood that although the efforts made in this development process may be complex and lengthy, for those skilled in the art related to the content disclosed in this application, any changes to design, manufacturing, or production based on the technical content disclosed in this application are merely conventional technical means and should not be construed as insufficient disclosure of the content of this application.

[0020] In this application, the reference to "embodiment" means that a specific feature, structure, or characteristic described in connection with an embodiment may be included in at least one embodiment of this application. The appearance of this phrase in various places in the specification does not necessarily refer to the same embodiment, nor is it a separate or alternative embodiment that is mutually exclusive with other embodiments. It will be explicitly and implicitly understood by those skilled in the art that the embodiments described in this application may be combined with other embodiments without conflict.

[0021] Unless otherwise defined, the technical or scientific terms used in this application shall have the ordinary meaning understood by one of ordinary skill in the art to which this application pertains. The terms “a,” “an,” “an,” “the,” and similar words used in this application do not indicate quantity limitation and may indicate singular or plural. The terms “comprising,” “including,” “having,” and any variations thereof used in this application are intended to cover non-exclusive inclusion; for example, a process, method, system, product, or device that includes a series of steps or modules (units) is not limited to the listed steps or units, but may also include steps or units not listed, or may include other steps or units inherent to these processes, methods, products, or devices. The terms “connected,” “linked,” “coupled,” and similar words used in this application are not limited to physical or mechanical connections, but may include electrical connections, whether direct or indirect. “Multiple” used in this application refers to two or more. “And / or” describes the relationship between related objects, indicating that three relationships may exist; for example, “A and / or B” can represent: A alone, A and B simultaneously, and B alone. The character " / " generally indicates that the preceding and following objects are in an "or" relationship. The terms "first," "second," and "third" used in this application are merely to distinguish similar objects and do not represent a specific ordering of the objects.

[0022] Example 1

[0023] This application provides an adaptive method for protecting vehicle privacy data, which is executed on an on-board local edge computing node. Figure 1This is a flowchart of the method, such as... Figure 1 As shown, the adaptive protection method of this application embodiment is implemented by the following steps.

[0024] Step S1: Obtain vehicle information and dynamically load the signal description file and dynamic masking strategy corresponding to the vehicle information from local storage. Specifically, the preset process for the signal description file includes: obtaining and parsing the corresponding DBC file according to the vehicle model to obtain the CAN ID, signal name, start bit, length, and terminal sequence; generating an initial signal description file based on the CAN ID, signal name, start bit, length, and terminal sequence; marking sensitive signals and setting associated switch signals in the initial signal description file according to preset rules, generating the signal description file and outputting it in JSON or XML format. The signal description file predefines the masking signal ID and the switch signal ID.

[0025] 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 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.

[0026] The specific dynamic masking strategy includes: 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.

[0027] 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.

[0028] Specifically, the raw binary data stream is captured through the CAN controller hardware interface of the vehicle edge node (such as ECU, 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. The CAN ID is extracted from the arbitration segment (e.g., 0x123) to identify the signal type (e.g., vehicle speed, GPS coordinates, etc.); the data length (DLC) is obtained from the control segment (e.g., 8 indicates that the data segment has 8 bytes); the data payload is extracted as 8 bytes of data (e.g., 01 02 03 04 05 06 07 08). Subsequent matching with the signal description file is then performed. A preset signal description file (e.g., JSON / DBC format) needs to be loaded, defining how to parse the data payload. The data segment is parsed according to rules, and the target signal (big-endian or little-endian) is extracted from the data payload according to the definition in the signal description file. Finally, process the cross-byte signals. If the signal spans multiple bytes (e.g., start bit = 12, length = 20), locate the start byte and offset (e.g., bits 12-15 of the first byte + bits 0-3 of the second byte + bits 0-3 of the third byte); concatenate the cross-byte data, adjust the order according to the end order; and apply the scaling factor and offset.

[0029] Step S3: Match the CAN message with the signal description file to identify privacy data in the original data stream. Specifically, read the CAN ID from the CAN message and compare it 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, the CAN message is used to define privacy data items that need to be protected; if the CAN ID is a switch signal ID, the CAN message is used to control the activation or deactivation of the privacy masking function; if the CAN ID is any other signal ID, the CAN message contains non-privacy data.

[0030] When the CAN ID belongs to a masking signal ID, query the current state of the switch signal associated with the CAN ID. If the current state is "masking on", perform a masking operation; if the current state is "masking off", do not mask the CAN message. When the CAN ID belongs to a switch signal ID, parse the value of the CAN message and update the corresponding global switch variable in memory. When the CAN ID belongs to another signal ID, do not process the CAN message.

[0031] Step S4: Perform real-time blocking processing on the privacy data according to the dynamic blocking strategy to generate a compliant data stream with blocked privacy.

[0032] During the masking operation, the CAN message is parsed, and an inverse mask is generated based on the start bit, length, and endianness of the CAN message. The target signal's bits are cleared to zero according to the mask and the data payload of the CAN message, while other bits remain unchanged. Specifically, for big-endian data, the mask is calculated and cleared byte-by-byte; for little-endian data, the mask is calculated and cleared from the end of the data array backwards.

[0033] This application addresses the challenges of existing technologies, such as complex separation of CAN bus privacy data, low processing efficiency due to limited onboard computing power, and static masking strategies that cannot be adapted across vehicle models. It achieves efficient and real-time privacy data protection under limited onboard computing power, dynamically adjusts the masking strategy based on user configuration and vehicle status, and performs real-time masking of the identified privacy data to generate a masked data stream. This solution resolves these issues by using an onboard local edge computing node to receive and parse raw data frames from the CAN bus in real time. It also addresses the limitations of existing technologies, including complex privacy data separation on the CAN bus, low processing efficiency due to limited onboard computing power, and static masking strategies that cannot be adapted across vehicle models. This application enables efficient and real-time protection of privacy data under limited onboard computing power, achieving adaptability based on user and environment dynamic adjustments and flexible adaptation to multiple vehicle models, thus achieving an effective balance between protecting user privacy and the value of data utilization.

[0034] Example 2

[0035] The adaptive protection method for vehicle privacy data in this embodiment is executed on the vehicle-mounted local edge computing node, and the implementation process includes the following steps.

[0036] Step 1: Receive raw data frames from the vehicle's CAN bus in real time, and perform real-time parsing and masking processing on the data frames. Specifically, acquire vehicle information, load the signal description file corresponding to the vehicle information from local storage, 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.

[0037] The signal description file, which is either preset or dynamically loaded, is used to identify whether and what privacy data is contained in the data frame. Therefore, the signal description file is the key to this application. It defines the signals that need to be processed, including switch signals used to control the start and stop of the shielding function and the specific shielding signals that need to be protected.

[0038] Specifically, the signal description file is a key component of this invention, defining how raw CAN message data (typically in binary format) is parsed into meaningful vehicle signals. Each signal contains the following key information in the file: CAN ID is used to uniquely identify CAN messages. The system uses this ID to quickly locate the message containing the target signal. Start bit: The starting bit position of the signal in the CAN message data payload; Length (Len), the bit length of the signal; Endianness (IsBigEndian) indicates the byte order of a signal, meaning the starting address in memory where the most significant or least significant byte of a multi-byte data set is stored. This is crucial for correctly parsing multi-byte signals.

[0039] Together, this information precisely describes the position and format of the signal within the CAN message data payload. The signal description file can be divided into two categories: switch signals and shield signals. Switch signals are used to control the activation or deactivation of specific privacy shielding functions (e.g., whether the user agrees to share location information), while shield signals specify the specific data items that need privacy protection (e.g., GPS coordinates, driver biometric data).

[0040] These signal description files can be pre-configured and generated by engineers or privacy compliance teams at automakers. They can be converted and extended based on industry-standard DBC (Database CAN) files, a common format for describing signal definitions in CAN networks. This invention supports the automatic conversion of user-readable signal names into the precise bit-level masked signal files required by this method, greatly simplifying the configuration process and improving compatibility and ease of use. Furthermore, to address the differences in CAN bus data definitions across different vehicle models, each model can be individually configured with its own masked description file, ensuring precise adaptation to specific vehicle model data definitions.

[0041] In a preferred embodiment, the signal description file can be dynamically loaded and updated, thereby achieving high flexibility and scalability, specifically including the following situations: 1. Runtime loading: When the system starts or a specific event is triggered, the onboard local edge computing node (such as an ECU or dedicated gateway) can automatically load the corresponding signal description file based on the current vehicle model (e.g., identified by the Vehicle Identification Number, VIN). This means that there is no need to compile different software versions for each vehicle model; a universal software framework can adapt to diverse vehicle models by loading different configuration files.

[0042] 2. Remote updates and distribution: Signal description files and related privacy policy configurations can be dynamically distributed and updated via OTA (Over-The-Air) remote update mechanism. Automakers can push the latest configurations to the vehicle via API, thus adapting without physical intervention. 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.

[0043] 4. Evolving privacy regulations: As global data privacy regulations are updated, blocking strategies can be quickly adjusted to ensure compliance.

[0044] 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.

[0045] 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.

[0046] 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.

[0047] 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.

[0048] 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.

[0049] For big-endian data, the algorithm operates byte-by-byte or across bytes, starting from the beginning of the signal. First, it calculates the starting byte of the signal. If the signal spans multiple bytes, it processes the portion of the starting byte occupied by the signal, clearing it to zero using a bitmask. Then, it clears all the complete bytes occupied by the signal in the middle. Finally, it processes the byte where the signal ends, clearing the remaining portion to zero using a bitmask. If the signal is within a single byte, it directly calculates the range of bits within that byte that need to be cleared and applies the corresponding bitmask.

[0050] For little-endian data, the algorithm operates on the characteristics of little-endian, where the least significant byte comes first. First, the starting byte of the signal is determined (counting backwards from the end of the data array). If the signal spans multiple bytes, the portion of the starting byte occupied by the signal is processed first, clearing it to zero using a bitmask. Then, all complete bytes occupied by the signal in the middle are cleared to zero. Finally, the byte where the signal ends is processed, clearing the remaining portion to zero using a bitmask. If the signal is within a single byte, the range of bits within that byte that need to be cleared is directly calculated, and the corresponding bitmask is applied for clearing.

[0051] This algorithm, through precise bit manipulation, ensures that specified privacy signals are cleared efficiently and accurately without affecting other non-privacy data in the CAN message. This low-level, refined processing capability is key to achieving real-time privacy protection in the limited computing power environment of an in-vehicle system.

[0052] The masking mechanism in this application can employ various efficient data anonymization algorithms, including but not limited to Dynamic Data Masking (DDM), tokenization, format-preserving encryption (FPE), data obfuscation, and data scrambling. The specific algorithm chosen depends on the type and sensitivity of the privacy data, as well as the needs for subsequent data utilization. For example, format-preserving encryption can be used in scenarios where the data format needs to be preserved while hiding the true content; tokenization can be used in scenarios where sensitive data needs to be completely replaced. These algorithms are optimized to adapt to the limited computing resources of the vehicle ECU, ensuring extremely low latency even when processing high-throughput CAN data. For example, parallel computing can be performed using GPUs or AI accelerators integrated in the ECU to accelerate data processing and masking.

[0053] Furthermore, this mechanism includes a highly efficient data flow management module responsible for directing compliant, anonymized data flows to different destinations after the masking process is complete: some data may be analyzed locally for vehicle control or driver assistance functions; other rigorously anonymized data may be allowed to be transmitted to the cloud for macro-data analysis, product improvement, or remote diagnostics. 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 performing real-time processing at the data source (CAN bus) and edge nodes, this invention effectively reduces the risk of data leakage in its unanonymized state and ensures immediate protection of privacy data.

[0054] In summary, compared with the prior art, the adaptive protection method for vehicle privacy data in this application has the following advantages: 1. High efficiency: By performing 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 in the vehicle is solved, reducing latency and data transmission costs. 2. Adaptability: The introduction of an intelligent strategy engine enables real-time adjustment of the shielding strategy based on user configuration and vehicle dynamic signals, achieving precise and flexible personalized privacy protection and balancing privacy protection with data utilization. 3. Compatibility and scalability: Through configurable and dynamically updatable signal description files (such as DBC file conversion) and modular design, it can easily adapt to different vehicle models, greatly reducing deployment and maintenance costs; 4. Compliance and security: Real-time processing from the source of data collection fundamentally prevents the risk of leakage of sensitive data in the un-anonymized state, effectively meets the requirements of global data privacy regulations, and enhances user trust.

[0055] Example 3

[0056] The adaptive protection method for vehicle privacy data in this embodiment is referenced. Figure 2 The specific execution process is as follows: After the software starts, the system first loads the signal shielding description file for the current vehicle model from local storage. This file can be a configuration file in JSON or XML format, which defines a series of switching signals and shielding signals.

[0057] 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"}.

[0058] To improve ease of use, the adaptive protection in this embodiment can directly read standard DBC files and automatically generate a description file in the above format based on the signal name selected by the user (such as "Latitude").

[0059] The system then connects to the CAN bus and begins streaming the received CAN messages in chronological order. For each CAN message, its 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 signals of interest, and the system will quickly skip it to ensure processing efficiency.

[0060] If the ID matches and is defined as a switch signal ID, the system will parse the value of the signal (e.g., extract whether the bit representing the GPS switch is 0 or 1 from the CAN message) and update the corresponding global switch variable in memory. After processing, it will continue processing the next message.

[0061] If the ID matches and is defined as a mask signal ID (e.g., 0x200), the system checks the current state of its associated switch signal (e.g., GPSEnable). If the switch is "mask on" (value 1), a masking operation is performed. The masking operation is implemented through precise bitwise operations: based on the signal's start bit, length, and endianness, an inverted bit mask is generated. This mask is then ANDed with the CAN message's data payload (data &= mask), clearing all bits of the target signal while leaving other bits unchanged. If the switch is "mask off" (value 0), the masking signal is ignored, and no changes are made to the message.

[0062] Through the above process, the present invention can adaptively shield privacy data in real time and efficiently without interrupting the data flow.

[0063] The adaptive protection of vehicle privacy data provided in this embodiment can adapt to multiple vehicle models with adaptive strategies. Specifically, an intelligent strategy engine is constructed, which is the core of achieving adaptability. This engine can subscribe to multiple dynamic signal sources and then generate corresponding blocking strategies.

[0064] For example, users can set a "privacy mode" through the vehicle's infotainment system or a mobile app. When a user activates "privacy mode," the strategy engine sends a command to the signal processing module to set all location- and driving behavior-related switch signals to "on shield."

[0065] The strategy engine continuously acquires vehicle dynamic signals, such as GPS location. When it detects that a vehicle has entered a user-preset geofenced area, such as "home" or "company," it can automatically increase the masking level of the location information (e.g., masking from precise coordinates to a blurred area, or masking completely).

[0066] The engine incorporates key regulatory requirements. For example, for vehicles sold in Europe, the engine will by default enable the blocking of certain sensitive data to comply with GDPR requirements.

[0067] When this application needs to be deployed to a new vehicle model, engineers do not need to modify the core code. They only need to obtain the DBC file for that vehicle model, generate a new signal shielding description file using the accompanying tools, and then deploy it to the vehicle. The entire system supports OTA (Over-The-Air) updates, which can remotely distribute new description files or policy rules, achieving low-cost, high-efficiency multi-vehicle compatibility and subsequent maintenance.

[0068] In summary, this invention provides an end-to-end adaptive privacy protection solution implemented at the vehicle edge node. Through innovative system architecture and algorithm design, it effectively solves many challenges faced by existing technologies and has extremely high practical value and broad application prospects.

[0069] Secondly, embodiments of this application provide an adaptive protection system for vehicle privacy data, used to execute the adaptive protection method for vehicle privacy data as described in any of the preceding embodiments, the system comprising: The data receiving module is used to acquire vehicle information, load the signal description file corresponding to the vehicle information from local storage, receive the raw data stream sent by the vehicle CAN bus in real time, and parse the raw data stream in time order 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 acquire a dynamic masking strategy, 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.

[0070] It should be noted that the system provided in this embodiment is used to implement the above-described embodiments, and details already described will not be repeated. As used above, terms such as "module," "unit," and "subunit" can refer to a combination of software and / or hardware that performs a predetermined function. Although the apparatus described in the above embodiments is preferably implemented in software, hardware implementation, or a combination of software and hardware, is also possible and contemplated.

[0071] Thirdly, embodiments of this application provide an electronic device, as shown in block diagram 3, which illustrates an exemplary embodiment of the electronic device. As shown in block diagram 3, the electronic device may include a processor 11 and a memory 12 storing computer program instructions.

[0072] Specifically, the processor 11 may include a central processing unit (CPU), an application specific integrated circuit (ASIC), or one or more integrated circuits that can be configured to implement the embodiments of this application.

[0073] The memory 12 may include a large-capacity storage device for data or instructions. For example, and not limitingly, the memory 12 may include a hard disk drive (HDD), a floppy disk drive, a solid-state drive (SSD), flash memory, an optical disk drive, a magneto-optical disk drive, magnetic tape, or a Universal Serial Bus (USB) drive, or a combination of two or more of these. Where appropriate, the memory 12 may include removable or non-removable (or fixed) media. Where appropriate, the memory 12 may be internal or external to a data processing device. In a particular embodiment, the memory 12 is non-volatile memory. In a particular embodiment, the memory 12 includes read-only memory (ROM) and random access memory (RAM). Where appropriate, the ROM may be a mask-programmed ROM, a programmable read-only memory (PROM), an erasable programmable read-only memory (EPROM), an electrically erasable programmable read-only memory (EEPROM), an electrically alterable read-only memory (EAROM), or flash memory, or a combination of two or more of these. Where appropriate, the RAM can be Static Random-Access Memory (SRAM) or Dynamic Random-Access Memory (DRAM). DRAM can be Fast Page Mode Dynamic Random-Access Memory (FPMDRAM), Extended Data Out Dynamic Random-Access Memory (EDODRAM), Synchronous Dynamic Random-Access Memory (SDRAM), etc.

[0074] The memory 12 can be used to store or cache various data files that need to be processed and / or communicated, as well as possible computer program instructions executed by the processor 11.

[0075] The processor 11 reads and executes computer program instructions stored in the memory 12 to implement any of the adaptive protection methods for vehicle privacy data in the above embodiments.

[0076] In one embodiment, the electronic device may further include a communication interface 13 and a bus 10. As shown in Figure 3, the processor 11, memory 12, and communication interface 13 are connected via the bus 10 and communicate with each other.

[0077] The communication interface 13 is used to enable communication between the various modules, devices, units, and / or equipment in the embodiments of this application. The communication port 13 can also enable data communication with other components such as external devices, image / data acquisition devices, databases, external storage, and image / data processing workstations.

[0078] Bus 10 includes hardware, software, or both, that couples components of an electronic device together. Bus 10 includes, but is not limited to, at least one of the following: data bus, address bus, control bus, expansion bus, and local bus. For example, and not as a limitation, bus 10 may 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 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 Bus (VLB) bus, or other suitable buses, or a combination of two or more of these. Where appropriate, bus 10 may include one or more buses. Although specific buses are described and illustrated in the embodiments of this application, this application considers any suitable bus or interconnection.

[0079] Fourthly, embodiments of this application provide a computer-readable storage medium having a program stored thereon, which, when executed by a processor, implements the adaptive protection method for vehicle privacy data provided in the first aspect.

[0080] The readable storage medium may be more specifically adopted, including but not limited to: portable disk, hard disk, random access memory, read-only memory, erasable programmable read-only memory, optical storage device, magnetic storage device, or any suitable combination thereof.

[0081] In a possible implementation, the present invention can also be implemented as a program product comprising program code that, when the program product is run on a terminal device, causes the terminal device to perform steps implementing the adaptive protection method for vehicle privacy data provided in the first aspect.

[0082] The program code for executing the present invention can be written in any combination of one or more programming languages. The program code can be executed entirely on the user device, partially on the user device, as a standalone software package, partially on the user device and partially on a remote device, or entirely on a remote device.

[0083] The technical features of the above embodiments can be combined in any way. For the sake of brevity, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0084] The embodiments described above are merely illustrative of several implementation methods of this application, and while the descriptions are relatively specific and detailed, they should not be construed as limiting the scope of the invention patent. It should be noted that those skilled in the art can make various modifications and improvements without departing from the concept of this application, and these all fall within the protection scope of this application. Therefore, the protection scope of this patent application should be determined by 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.

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 dynamic masking strategy includes: Acquire dynamic signals, including user configuration, vehicle status signals, environmental signals, and compliance rules; Obtain a preset policy rule base, and generate a dynamic blocking policy or dynamically adjust the blocking policy based on the dynamic signal and the policy rule base; 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 keeping 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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