Data transmission method, apparatus, device, storage medium, and product

Abstract

The application provides a data transmission method, device, equipment, storage medium and product. The method is applied to a vehicle, and the method comprises the following steps: determining a sensitive level corresponding to target data according to a data security feature of the target data; in the case that a cross-domain transmission request for the target data occurs, evaluating a transmission risk of the cross-domain transmission request, and determining a risk level corresponding to the cross-domain transmission request; obtaining a privacy budget allocation amount based on the sensitive level and the risk level; processing the target data according to a protection strategy corresponding to the privacy budget allocation amount to obtain safe data; and sending the safe data according to the cross-domain transmission request.

Description

Technical Field

[0001] This application relates to the field of data security technology, and in particular to a data transmission method, apparatus, device, storage medium and product. Background Technology

[0002] With the rapid development of the intelligent connected vehicle industry, massive amounts of multi-dimensional data are continuously generated during vehicle operation. Under the current integrated vehicle-road-cloud collaborative operation system, cross-domain data sharing among multiple entities such as automakers, traffic management departments, road network operation platforms, and third-party service providers has become a crucial foundation for optimizing intelligent driving algorithms and making vehicle-road collaborative scheduling decisions. However, vehicle-side data contains a large amount of user privacy information, such as owner identity, precise location, and driving habits, posing security risks such as privacy leaks during cross-domain data flow.

[0003] In existing technologies, privacy protection for cross-domain sharing of vehicle-side data typically employs a uniformly strong differential privacy strategy, applying the same level of perturbation to all types of data. This leads to a disconnect between the allocation of protection resources and the actual level of risk. Perturbations exceeding actual needs are applied to low-sensitivity data, increasing computational overhead and reducing data availability, while the perturbation strength for highly sensitive data is insufficient to provide adequate privacy protection. Furthermore, risk identification is pre-configured as static rules, causing the protection strategy to lag behind scenarios with frequent and dynamic changes in vehicle-side data, resulting in inadequate data security during cross-domain sharing. Summary of the Invention

[0004] This application provides a data transmission method, apparatus, device, storage medium, and product that can solve the technical problem of insufficient data security protection in the process of cross-domain data sharing at the vehicle end.

[0005] In a first aspect, this application provides a data transmission method applied to a vehicle, the method comprising: Based on the data security characteristics of the target data, determine the sensitivity level corresponding to the target data; In the event of a cross-domain transmission request for the target data, the transmission risk of the cross-domain transmission request is assessed, and the risk level corresponding to the cross-domain transmission request is determined. Based on the sensitivity level and the risk level, the privacy budget allocation is obtained; The target data is processed according to the protection strategy corresponding to the privacy budget allocation to obtain secure data; Send the security data according to the cross-domain transfer request.

[0006] In some possible implementations, the step of assessing the transmission risk of a cross-domain transmission request and determining the risk level corresponding to the cross-domain transmission request when such a request for the target data occurs includes: In the event of a cross-domain transmission request for the target data, the data sensitivity characteristics corresponding to the target data are determined based on the sensitivity level of the target data. Obtain the identity information of the requesting subject, the transmission link type, and the shared usage scenario of the cross-domain transmission request; Based on the data sensitivity characteristics, the subject identity information, the transmission link type, and the shared usage scenario, the transmission risk of the cross-domain transmission request is comprehensively assessed to obtain a transmission risk score; Based on the transmission risk score, the risk level corresponding to the cross-domain transmission request is determined.

[0007] In some possible implementations, the comprehensive assessment of the transmission risk of the cross-domain transmission request based on the data sensitivity characteristics, the subject identity information, the transmission link type, and the shared usage scenario to obtain a transmission risk score includes: Based on the identity information of the requesting subject, the access permissions of the requesting subject are verified to obtain the permission verification result; Based on the transmission link type, the security strength of the transmission link is evaluated to obtain the link security evaluation result; Based on the permission verification results, the link security assessment results, the data sensitivity characteristics, and the shared usage scenario, the transmission risk of the cross-domain transmission request is comprehensively assessed to obtain a transmission risk score.

[0008] In some possible implementations, the comprehensive assessment of the transmission risk of the cross-domain transmission request based on the permission verification result, the link security assessment result, the data sensitivity characteristics, and the shared usage scenario, to obtain a transmission risk score, includes: Feature extraction is performed on the permission verification result, the link security assessment result, the data sensitivity feature, and the shared usage scenario to obtain the corresponding risk feature quantification value; Based on the preset risk weight configuration rules, the risk weight coefficients corresponding to the permission verification result, the link security assessment result, the data sensitivity feature, and the shared usage scenario are determined respectively. The transmission risk score is obtained by weighting and summing the quantified values ​​of each risk feature with the corresponding risk weight coefficients.

[0009] In some possible implementations, after determining the risk level corresponding to the cross-domain transmission request based on the transmission risk score, the method further includes: If the cross-domain transmission request is found to involve unauthorized access, high-risk link transmission, or batch export of privacy data, a corresponding risk warning message will be generated. Based on the type and number of abnormal behaviors corresponding to the risk warning information, the risk level of the cross-domain transmission request is increased.

[0010] In some possible implementations, processing the target data according to the protection policy corresponding to the privacy budget allocation to obtain secure data includes: Based on the privacy budget allocation, determine the protection strategy type and protection strength corresponding to the target data; Based on the protection strength, the running parameters of the privacy protection algorithm corresponding to the protection strategy type are configured to obtain the target privacy protection algorithm; The target data is processed according to the target privacy protection algorithm to obtain secure data.

[0011] In some possible implementations, the privacy protection algorithm is a differential privacy algorithm, and the step of processing the target data according to the target privacy protection algorithm to obtain secure data includes: Based on the noise addition amount corresponding to the protection strength, generate a noise vector that is consistent with the dimensions of each sensitive field in the target data; Based on each of the noise vectors, noise is injected into each of the corresponding sensitive fields in the target data to obtain secure data.

[0012] In some possible implementations, sending the security data according to the cross-domain transfer request includes: Based on the cross-domain transmission request, determine the transmission level and receiving end information corresponding to the security data; Based on the cross-domain receiver information, a transmission link is established with the receiver through the edge proximity forwarding mode; Based on the transmission level, determine the transmission strategy corresponding to the secure data; According to the transmission strategy, the security data is sent to the receiving end through the transmission link.

[0013] In some possible implementations, after sending the secure data to the receiving end via the transmission link according to the transmission strategy, the method further includes: According to the transmission strategy, obtain the hash verification result of the sent security data; If an abnormal hash verification result is detected, a link switch is performed and the transmission link is updated. The security data is sent to the receiving end via the updated transmission link.

[0014] Secondly, this application provides a data transmission apparatus, the apparatus comprising: The determination module is used to determine the sensitivity level of the target data based on its data security characteristics. The assessment module is used to assess the transmission risk of a cross-domain transmission request in the event of a cross-domain transmission request for the target data, and to determine the risk level corresponding to the cross-domain transmission request. The allocation module is used to obtain the privacy budget allocation amount based on the sensitivity level and the risk level; The processing module is used to process the target data according to the protection policy corresponding to the privacy budget allocation to obtain secure data; The sending module is used to send the security data according to the cross-domain transmission request.

[0015] Thirdly, this application provides a data transmission device, the device comprising: a processor, and a memory storing computer program instructions; the processor reads and executes the computer program instructions to implement the data transmission method described above.

[0016] Fourthly, this application provides a computer-readable storage medium storing computer program instructions, which, when executed by a processor, implement the data transmission method described above.

[0017] Fifthly, this application provides a computer program product in which instructions, when executed by a processor of an electronic device, cause the electronic device to perform the data transmission method described above.

[0018] The data transmission method, apparatus, device, storage medium, and product provided in this application determine the sensitivity level of the target data based on its data security characteristics, assess the transmission risk when a cross-domain transmission request occurs to determine the risk level, and then combine the sensitivity level and risk level to obtain a privacy budget allocation. The target data is then processed according to the protection strategy corresponding to the privacy budget allocation to obtain secure data before transmission. This allows the privacy protection level to simultaneously adapt to the sensitivity of the data itself and the risk level of the specific transmission scenario, achieving differentiated privacy protection for different data and different transmission requests. This avoids over-protection of low-sensitivity, low-risk data while ensuring sufficient protection for high-sensitivity, high-risk data, thus balancing data security during cross-domain data transmission. Attached Figure Description

[0019] This application can be better understood from the following description of specific embodiments in conjunction with the accompanying drawings, wherein: Other features, objects, and advantages of this application will become more apparent from the following detailed description of non-limiting embodiments with reference to the accompanying drawings, wherein the same or similar reference numerals denote the same or similar features.

[0020] Figure 1 This is a flowchart of a data transmission method provided in one embodiment of this application; Figure 2 This is a flowchart of a data transmission method provided in another embodiment of this application; Figure 3 This is a flowchart of a data transmission method provided in another embodiment of this application; Figure 4 This is a schematic diagram of the logical flow of data classification, grading, and risk identification provided in one embodiment of this application; Figure 5 This is a flowchart of a differential privacy adaptive protection algorithm provided in one embodiment of this application; Figure 6 This is a schematic diagram of the structure of a data transmission device provided in one embodiment of this application; Figure 7 This is a schematic diagram of the hardware structure of the data transmission device provided in the embodiments of this application. Detailed Implementation

[0021] The features and exemplary embodiments of various aspects of this application will be described in detail below. To make the objectives, technical solutions, and advantages of this application clearer, the application will be further described in detail below with reference to the accompanying drawings and specific embodiments. It should be understood that the specific embodiments described herein are only intended to explain this application and not to limit it. For those skilled in the art, this application can be implemented without some of these specific details. The following description of the embodiments is merely to provide a better understanding of this application by illustrating examples.

[0022] It should be noted that, in this document, relational terms such as "first" and "second" are used merely to distinguish one entity or operation from another, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Furthermore, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Without further limitations, an element defined by the phrase "comprising..." does not exclude the presence of additional identical elements in the process, method, article, or apparatus that includes said element.

[0023] With the rapid development of the intelligent connected vehicle industry, massive amounts of multi-dimensional data, including vehicle perception data, vehicle driving data, driving behavior data, and vehicle-road interaction data, are continuously being generated. Cross-domain data sharing among automakers, traffic management departments, road network operation platforms, and third-party service providers is the core foundation for achieving intelligent driving optimization, traffic situation analysis, and vehicle-road cooperative scheduling. However, the current cross-domain data sharing system for vehicle terminals faces technical bottlenecks that make it difficult to balance security and performance.

[0024] First, existing vehicle-side data lacks a standardized classification and grading mechanism, with sensitive privacy data being mixed with ordinary business data, and a uniform privacy protection strategy is generally adopted. Over-protection of low-sensitivity data increases computational overhead and reduces data availability; while insufficient protection of high-sensitivity data easily leads to user privacy leaks, resulting in extremely poor protection accuracy. Meanwhile, traditional data security risk identification methods mostly rely on static rule screening, which cannot adapt to the characteristics of real-time data collection, dynamic updates, and high-frequency interactions in vehicles, making it difficult to accurately identify risks of dynamic leakage, unauthorized access, and data tampering during cross-domain transmission.

[0025] Secondly, traditional differential privacy protection algorithms are mostly geared towards offline batch data processing scenarios in the cloud, and suffer from problems such as high algorithm redundancy, fixed privacy budget, large computation latency, and high computing power consumption. Vehicle-side devices have limited computing power and stringent real-time requirements, and traditional differential privacy computing models cannot meet the needs of millisecond-level data processing and cross-domain transmission on the vehicle side, resulting in a pain point where privacy protection and transmission performance are mutually constrained.

[0026] Finally, existing cross-domain data sharing technologies primarily focus on transmission link optimization, failing to differentiate protection based on data security levels and risk status. This makes it impossible to simultaneously meet the triple requirements of privacy security, low latency, and high reliability, significantly limiting the secure and efficient cross-domain flow and value realization of vehicle-to-everything (V2X) data. In summary, existing technologies suffer from core shortcomings such as a lack of hierarchical mechanisms, delayed risk identification, poor adaptability to differential privacy, and high latency and low reliability in cross-domain sharing, necessitating a novel integrated technical solution.

[0027] To address the problems of the prior art, embodiments of this application provide a data transmission method, apparatus, device, storage medium, and product. The data transmission method provided in this application embodiment will be described first below.

[0028] Figure 1 A schematic flowchart of a data transmission method provided in one embodiment of this application is shown. Figure 1 As shown, the method is applied to a vehicle and includes the following steps: S101 to S105.

[0029] S101: Determine the sensitivity level of the target data based on its data security characteristics.

[0030] S102: In the event of a cross-domain transmission request for target data, assess the transmission risk of the cross-domain transmission request and determine the risk level corresponding to the cross-domain transmission request.

[0031] S103: Based on the sensitivity level and risk level, obtain the privacy budget allocation.

[0032] S104: Process the target data according to the protection strategy corresponding to the privacy budget allocation to obtain secure data.

[0033] S105: Send secure data in accordance with the cross-domain transfer request.

[0034] In the specific implementation of S101, the target data is parsed, and data security feature values ​​of preset types are collected from the data's metadata, content fields, and associated attributes. For example, the type of information described by the target data is identified, distinguishing whether it belongs to vehicle driving status data, driver biometric data, in-vehicle occupant behavior data, vehicle location trajectory data, or in-vehicle entertainment preference data; it is determined whether the data contains identifiers that can uniquely identify the vehicle or occupants, such as vehicle identification numbers, driver facial feature templates, or account identity tokens; the severity of harm to vehicle safe driving, occupant personal safety, and personal privacy if the data is leaked or accessed without authorization is assessed, and a damage quantification scale is assigned. The above-mentioned types, identifier existence, and damage scale, etc., are organized into a feature description set, and this set is matched one by one with a set of judgment conditions corresponding to multiple predefined sensitivity levels. Each sensitivity level's condition set sets specific standards for each feature value. For example, the "high sensitivity" condition set requires the data type to belong to the biometric or precise location trajectory category, contain direct identifiers, and have a damage scale higher than the severity threshold. By examining which level of conditions the feature description set satisfies or has the highest degree of satisfaction, that level is assigned to the target data, thus determining its sensitivity level as high sensitivity, medium sensitivity, or low sensitivity.

[0035] In the specific implementation of S102, the security isolation level of the vehicular domain initiating the transmission is read from the source information of the request, such as whether it is a secure gateway domain or a non-secure infotainment domain; the type and trusted status of the external network domain of the receiving end are obtained from the target address information, whether it is the vehicle manufacturer's private cloud with security authentication or a third-party public service platform; the type and encryption protection status of the communication channel to be used for the transmission are obtained, whether it is a secure link established through a dedicated vehicular encrypted communication module or a general connection relying on a public cellular network; and the data purpose label is identified from the description carried in the request, whether it is for vehicle safety diagnostics or commercial data analysis. Then, based on the pre-set risk quantification mapping logic, the specific status of each risk factor is converted into a risk quantification value, thereby obtaining a comprehensive risk score. This comprehensive risk score is compared with multiple preset risk threshold ranges, and the risk level corresponding to the cross-domain transmission request is determined as low risk, medium risk, or high risk based on the range it falls into.

[0036] In the specific implementation of S103, the sensitivity level obtained in S101 and the risk level obtained in S102 are used as common input conditions. By querying a pre-established privacy budget allocation mapping structure, the privacy budget allocation corresponding to the combination of conditions is obtained. This mapping structure uses the sensitivity level identifier and the risk level identifier as joint lookup keys, and internally stores the privacy budget values ​​pre-calculated according to the differential privacy protection strength requirements.

[0037] In the specific implementation of S104, based on the specific value of the privacy budget allocated in S103, a differential privacy perturbation mechanism adapted to that value is selected to perform a protective transformation on the target data. First, the noise generation distribution type is determined according to the numerical range of the privacy budget value; for example, a Laplace distribution is used when the value is small, and a Gaussian distribution is used when the value is large. Next, for the query or analysis function in the target data that is intended to be provided externally, the precise value is replaced with a generalized category or range, thereby generating secure data that retains its utility in a statistical sense but cannot reconstruct the original individual's precise information.

[0038] In the specific implementation of S105, after the target data is processed and transformed into secure data, the transmission operation is performed according to the transmission protocol declared in the original cross-domain transmission request. The secure data is serialized according to the format specified in the request and encapsulated into a message payload defined by the transmission protocol. The message header field is filled with the session identifier associated with the original request, the target domain network address, the payload data format indicator, and the integrity checksum calculated by secure hashing, for verification by the receiver. Subsequently, based on the secure transmission requirements specified in the request and the previously assessed risk level, the corresponding transport layer protection mechanism is activated, such as negotiating and establishing a mutually authenticated encrypted transmission tunnel with the target domain, or enabling data encryption based on a pre-shared key. Afterwards, the encapsulated message is delivered to the target domain address specified in the request via the protected communication channel. During the transmission process, the system listens for successful reception confirmation messages from the target domain. If no confirmation is received within a set time, a retransmission process is automatically initiated for a limited number of retries. Once a successful confirmation is received, the cross-domain transmission task is marked as complete.

[0039] The data transmission method provided in this application determines the sensitivity level of the target data based on its data security characteristics, assesses the transmission risk when a cross-domain transmission request occurs to determine the risk level, and then combines the sensitivity level and risk level to obtain a privacy budget allocation. The target data is then processed according to the protection strategy corresponding to the privacy budget allocation to obtain secure data before transmission. This allows the privacy protection level to simultaneously adapt to the sensitivity of the data itself and the risk level of the specific transmission scenario, achieving differentiated privacy protection for different data and different transmission requests. This avoids over-protection of low-sensitivity, low-risk data while ensuring sufficient protection for high-sensitivity, high-risk data, thus balancing data security during cross-domain data transmission.

[0040] In order to obtain an accurate risk level, in some implementations, S102 may include the following steps: S1021 to S1024.

[0041] S1021: In the event of a cross-domain transmission request for target data, determine the data sensitivity characteristics corresponding to the target data based on the sensitivity level of the target data.

[0042] S1022: Obtain the identity information of the requesting subject, the type of the transmission link, and the shared usage scenario of the cross-domain transmission request.

[0043] S1023: Based on data sensitivity characteristics, subject identity information, transmission link type, and shared usage scenario, a comprehensive assessment of the transmission risk of cross-domain transmission requests is conducted to obtain a transmission risk score.

[0044] S1024: Determine the risk level corresponding to the cross-domain transmission request based on the transmission risk score.

[0045] In the specific implementation of S1021, when a cross-domain transmission request pointing to target data is detected, the sensitivity level label assigned to the target data in the previous step is read, and the corresponding data sensitivity feature is extracted from the preset sensitivity feature mapping relationship based on the sensitivity level. Specifically, a correspondence between sensitivity levels and data sensitivity features is pre-constructed. This correspondence can be represented as a mapping table or a transformation function, where data sensitivity features are defined as a set of feature quantities that can numerically describe the data sensitivity attribute, such as sensitivity score, data impact range coefficient, and leakage hazard index.

[0046] In the specific implementation of S1022, the intercepted cross-domain transmission requests are deeply analyzed to extract key information for risk assessment. First, the identity information of the requesting entity is parsed from the source declaration, digital signature, or security token of the request message. This identity information includes the entity identifier, the entity's organizational domain, and the entity's authenticated security level or role attributes, such as distinguishing whether it is a vehicle manufacturer's cloud diagnostic platform, an authorized repair service provider, a third-party insurance analysis service, or an in-vehicle occupant's personal device. Second, the transmission link type is identified from the negotiation parameters and channel description of the transmission session, specifically including the network standard and security protocol used by the link. For example, is it a point-to-point encrypted link established via dedicated in-vehicle short-range communication, a transport layer secure tunnel established via a public cellular network, or an unencrypted local wireless connection? The encryption algorithm suite and authentication method used by the link are also extracted. Finally, the sharing usage scenario is obtained from the request's semantic tags or data usage declaration field. This scenario describes the purpose for which the data will be used, such as remote vehicle fault diagnosis, driving behavior analysis and optimization, ride-sharing matching, or third-party commercial advertising. The parsed request subject identity information, transmission link type, and shared usage scenario are stored separately.

[0047] In the specific implementation of S1023, a pre-built risk assessment model is invoked, and the data sensitivity characteristics determined in step S1021, as well as the request subject identity information, transmission link type and shared usage scenario obtained in step S1022, are used as input variables to perform multi-dimensional risk quantification calculations and obtain a transmission risk score.

[0048] In the specific implementation of S1024, the transmission risk score obtained from the comprehensive evaluation in step S1023 is compared with several pre-set risk level threshold intervals. Based on the comparison results, the final risk level of the cross-domain transmission request is determined. The pre-set risk level threshold intervals define the mapping relationship between the score range and the risk level. The calculated transmission risk score is read, and it is determined which threshold interval it falls into. Then, the risk level label corresponding to that interval is extracted as the risk level of the cross-domain transmission request.

[0049] The above-described implementation method of this application, when a cross-domain transmission request for target data occurs, determines the data sensitivity characteristics corresponding to the target data based on the sensitivity level of the target data, then obtains the identity information of the requesting subject, transmission link type, and shared usage scenario of the cross-domain transmission request, and then comprehensively assesses the transmission risk of the cross-domain transmission request based on the data sensitivity characteristics, subject identity information, transmission link type, and shared usage scenario to obtain a transmission risk score, and then determines the risk level corresponding to the cross-domain transmission request based on the transmission risk score, thereby obtaining an accurate risk level.

[0050] In order to determine a reasonable transmission risk score, in some implementations, S1023 may include the following steps: S10231 to S10233.

[0051] S10231: Based on the identity information of the requesting subject, verify the access permissions of the requesting subject and obtain the permission verification result.

[0052] S10232: Based on the transmission link type, assess the security strength of the transmission link to obtain the link security assessment result.

[0053] S10233: Based on the permission verification results, link security assessment results, data sensitivity characteristics, and shared usage scenarios, a comprehensive assessment of the transmission risk of cross-domain transmission requests is conducted to obtain a transmission risk score.

[0054] In the specific implementation of S10231, after parsing the request subject's identity information from the cross-domain transmission request, this identity information is used as a query credential to verify whether the request subject has the permission to access the target data. Specifically, the parsed subject identifier, affiliated organizational domain, and security role attributes are compared item by item with the data access control policy library stored in the data security management module to obtain the permission verification result. This data access control policy library maintains a list of authorized subjects and corresponding permission levels for each data resource.

[0055] In the specific implementation of S10232, after obtaining the transmission link type used for the cross-domain transmission request, the security protection strength that the link type can provide is quantitatively evaluated based on its specific attributes. During the evaluation, characteristic elements related to the transmission link type, such as link encryption protocols, authentication mechanisms, and the link physical environment, are extracted. These characteristic elements are then matched with a pre-built set of link security strength evaluation rules to obtain the link security evaluation result. This rule set defines the mapping relationship between various link characteristics and security strength scores.

[0056] In the specific implementation of S10233, a pre-built multi-factor risk assessment model is invoked. The permission verification results output from step S10231 and the link security assessment results output from step S10232, along with the data sensitivity characteristics and quantitative representations of shared usage scenarios determined in previous steps, are used as input variables for a weighted comprehensive calculation. First, each input variable is normalized or standardized to convert it into a calculable risk contribution value. For the permission verification results, a lower risk contribution value is assigned if the verification passes and the permission level is high; a very high risk contribution value is assigned if the verification fails or the permission is insufficient. For the link security assessment results, the intensity value is inverted or converted into a risk exposure. For the data sensitivity characteristics, the sensitivity score is directly used as a risk contribution factor. For the shared usage scenario, the scenario risk value is pre-defined based on its relevance to the data subject's interests and compliance risks. Then, the risk assessment model applies preset weight coefficients according to the impact of each factor on the overall transmission risk, and performs a weighted summation of the above risk contribution values ​​to obtain the transmission risk score.

[0057] The above-described implementation method of this application verifies the access rights of the requesting subject based on the requesting subject's identity information to obtain the access rights verification result. Then, it assesses the security strength of the transmission link based on the transmission link type to obtain the link security assessment result. Finally, based on the access rights verification result, the link security assessment result, data sensitivity characteristics, and shared usage scenarios, it comprehensively assesses the transmission risk of cross-domain transmission requests to obtain a transmission risk score, thereby determining a reasonable transmission risk score.

[0058] To accurately calculate the transmission risk score, in some implementations, reference is made to... Figure 2 S10233 may include the following steps: S201 to S203.

[0059] S201: Extract features from the permission verification results, link security assessment results, data sensitivity characteristics, and shared usage scenarios to obtain the corresponding risk feature quantification values.

[0060] S202: Based on the preset risk weight configuration rules, determine the risk weight coefficients corresponding to the permission verification results, link security assessment results, data sensitivity characteristics, and shared usage scenarios.

[0061] S203: The transmission risk score is obtained by weighted summation of the quantitative values ​​of each risk characteristic and the corresponding risk weight coefficients.

[0062] In the specific implementation of S201, for the permission verification result, the verification status identifier and permission level information contained therein are parsed. The combination of verification status and permission level is used as the query key to retrieve the corresponding risk quantification value from a preset mapping table. If the verification status is failed, a preset maximum risk exposure fixed value is directly assigned. For the link security assessment result, its output format is determined. If it is a numerical security strength score, it is processed by the risk exposure conversion function, i.e., the maximum security score is subtracted from the current security strength score to obtain the risk quantification value reflecting the link vulnerability. If it is a discrete level label, the corresponding quantification value is read from the level-risk mapping table. For data sensitivity features, the value of the preset sensitivity score field is extracted from its structured feature quantity and directly used as the risk feature quantification value for that dimension. For shared use scenarios, the scenario description label is matched with a pre-built scenario risk dictionary to obtain the transmission risk score corresponding to that scenario.

[0063] In the specific implementation of S202, a preset risk weight configuration rule is read. This rule uses contextual attributes such as data service classification, security policy level, or transmission task criticality as index conditions to maintain the weight allocation relationship of each risk dimension under different evaluation schemes. During execution, the service classification label of the target data to be transmitted and the policy level of the current security domain are obtained. These attributes are compared one by one with the conditions in the configuration rule. If a match is found, the weight coefficients set for data sensitivity features, permission verification results, link security assessment results, and shared usage scenarios under that scheme are extracted. If no specific condition scheme is matched, the default static weight configuration is directly called to obtain a set of fixed weight coefficients.

[0064] In the specific implementation of S203, the quantified values ​​of data sensitivity risk features, permission verification risk features, link security risk features, and shared usage scenario risk features extracted in step S201 are weighted and summed with the corresponding weight coefficients determined in step S202. Specifically, the quantified value of the risk feature in each dimension is multiplied by its weight coefficient to generate the risk-weighted component for that dimension; then, the risk-weighted components of all dimensions are summed, and the resulting sum is the transmission risk score.

[0065] The above-described implementation method of this application extracts features from the permission verification result, link security assessment result, data sensitivity feature, and shared usage scenario to obtain the corresponding risk feature quantification value. Then, according to the preset risk weight configuration rule, the risk weight coefficients corresponding to the permission verification result, link security assessment result, data sensitivity feature, and shared usage scenario are determined respectively. Finally, the transmission risk score is obtained by weighted summation based on each risk feature quantification value and the corresponding risk weight coefficient, thereby accurately calculating the transmission risk score.

[0066] In order to address specific risky behaviors, some implementations refer to Figure 3 After S1024, the method may further include the following steps: S301 to S302.

[0067] S301: When cross-domain transmission requests are found to involve unauthorized access, high-risk link transmissions, or batch export of private data, corresponding risk warning information is generated.

[0068] S302: Based on the type and number of abnormal behaviors corresponding to the risk warning information, the risk level of cross-domain transmission requests is increased.

[0069] In the specific implementation of S301, the permission verification result is obtained from the request processing flow. If the verification result is marked as "failed" or the permission level is insufficient to cover the operation type declared in the request, the request is marked as having an unauthorized access anomaly. Simultaneously, the transmission link type and the corresponding link security assessment result are read. If the link type is plaintext transmission, a weak encryption suite, or an unauthenticated public network, and its security strength score is lower than a preset high-risk threshold, a high-risk link transmission anomaly is determined. Furthermore, the target data range and data volume specified in the request are parsed, and the number of records, fields, or total data capacity to be transmitted are counted and compared with a preset batch export threshold. If the amount of data to be transmitted exceeds the threshold, or the frequency of data export requests initiated by the same subject within a preset time window exceeds the limit, a batch privacy data export anomaly is determined. Upon identifying any one or more of the above abnormal behaviors, corresponding risk warning information is generated.

[0070] In the specific implementation of S302, the risk level determined for this cross-domain transmission request in step S1024 is obtained, and this level serves as the baseline level before adjustment. The magnitude of this adjustment is determined according to preset abnormal behavior adjustment rules. These adjustment rules define the corresponding adjustment amount or adjustment level for different abnormal behavior types, as well as the strategy for accumulating adjustment amounts when multiple abnormal behaviors occur concurrently.

[0071] The above-described implementation of this application's embodiments generates corresponding risk warning information when cross-domain transmission requests are found to involve unauthorized access, high-risk link transmission, or batch export of private data. Then, based on the type and quantity of abnormal behavior corresponding to the risk warning information, the risk level of the cross-domain transmission request is increased, thereby handling specific risky behaviors.

[0072] In order to perform reasonable data processing, in some embodiments, S104 may include the following steps: S1041 to S1043.

[0073] S1041: Determine the type and strength of protection strategy corresponding to the target data based on the privacy budget allocation.

[0074] S1042: Based on the protection strength, configure the running parameters of the privacy protection algorithm corresponding to the protection strategy type to obtain the target privacy protection algorithm.

[0075] S1043: Process the target data according to the target privacy protection algorithm to obtain secure data.

[0076] In the specific implementation of S1041, a matching query is performed in the preset protection policy configuration library to determine the type of protection policy to be adopted and the corresponding protection strength level. This protection policy configuration library maintains a mapping relationship between privacy budget value ranges and protection policy schemes.

[0077] In the specific implementation of S1042, after determining the protection strategy type and protection strength level, the required operating parameters for the privacy protection algorithm of that type are specifically assigned and configured according to the strength level. First, based on the query operation or statistical function to be protected in the target data, its global sensitivity is calculated, which is the maximum difference between query results on any two adjacent datasets. Then, according to the parameter calculation rules corresponding to the protection strength level, the core control parameters of the algorithm are calculated using the privacy budget allocation and global sensitivity. For the differential privacy Laplace mechanism, the higher the protection strength level, the larger the corresponding noise scale. The selected algorithm type, the calculated noise scale or standard deviation parameter, and the global sensitivity information are combined to complete the instantiation configuration of the privacy protection algorithm and generate an executable target privacy protection algorithm.

[0078] In the specific implementation of S1043, the completed target privacy protection algorithm is invoked to perform perturbation processing on each field or statistical value in the target data that requires privacy protection. Specifically, depending on the algorithm type and parameters, a random number generator is driven to generate a random noise sequence that follows the corresponding distribution; for the Laplace mechanism, random noise values ​​following a Laplace distribution with a scale of b are generated; for the Gaussian mechanism, random noise values ​​following a Gaussian distribution with a mean of zero are generated. Then, the generated noise values ​​are added to the original values ​​or query result values ​​of the numerical fields to be output in the target data one by one, changing their precise values ​​through additive perturbation. For categorical or label fields, the precise values ​​are replaced with generalized category labels according to the built-in generalization replacement rules in the algorithm, ultimately generating secure data that retains the overall statistical distribution trend but cannot infer precise individual information.

[0079] The above-described implementation method of this application determines the protection strategy type and protection strength corresponding to the target data based on the privacy budget allocation. Then, based on the protection strength, the running parameters of the privacy protection algorithm corresponding to the protection strategy type are configured to obtain the target privacy protection algorithm. The target data is then processed according to the target privacy protection algorithm to obtain secure data, thereby performing reasonable data processing.

[0080] In order to perform noise injection processing quickly, in some embodiments, S1043 may include the following steps: S10431 to S10432.

[0081] S10431: Generate a noise vector that is consistent with the dimensions of each sensitive field in the target data according to the noise addition amount corresponding to the protection strength.

[0082] S10432: Based on each noise vector, noise is injected into each corresponding sensitive field in the target data to obtain secure data.

[0083] In the specific implementation of S10431, the noise addition parameter determined according to the protection strength level is read. For each sensitive field to be protected that has been marked in the target data, a noise vector matching its dimension is generated individually. During the generation process, the data dimension occupied by the sensitive field in the target data is first obtained. For example, if the field is a single-column numerical value, the dimension is one-dimensional; if it is a multi-dimensional vector, the dimension is the same as the vector length. Then, a random number generator is called, using the noise addition parameter as the distribution control parameter, to generate independent and identically distributed random noise values ​​dimension by dimension of the field. The noise values ​​of each dimension together form a noise vector of the same dimension as the field.

[0084] In the specific implementation of S10432, after generating noise vectors corresponding to each sensitive field, these noise vectors are injected one by one into the corresponding sensitive fields in the target data to perturb their original precise values. For each sensitive field, the original numerical vector of that field in the target data is obtained, and the corresponding noise vector generated in step S10431 is added to the original numerical vector element-wise. That is, the original value and the noise value of the corresponding dimension are added to obtain the noisy numerical vector. After the addition is completed, the original numerical vector of the sensitive field in the target data is replaced by the noisy numerical vector. If the sensitive field is categorical data, the replacement category is first determined in the predefined generalization hierarchy tree or replacement candidate set according to the numerical pointer in the noise vector, and then the replacement operation is performed. After performing the above noise injection operation on all labeled sensitive fields one by one, the precise values ​​of each sensitive field in the target data have been perturbed, and the overall dataset is transformed into safe data that retains statistical usability but whose individual information cannot be restored.

[0085] The above-described implementation method of this application generates a noise vector consistent with the dimensions of each sensitive field in the target data according to the noise addition amount corresponding to the protection strength. Then, based on each noise vector, noise is injected into each corresponding sensitive field in the target data to obtain secure data, thereby quickly performing noise injection processing.

[0086] In order to securely transmit data, in some implementations, S105 may include the following steps: S1051 to S1054.

[0087] S1051: Based on the cross-domain transmission request, determine the transmission level and receiving end information corresponding to the security data.

[0088] S1052: Based on cross-domain receiver information, establish a transmission link with the receiver through the edge-nearest forwarding mode.

[0089] S1053: Determine the transmission strategy corresponding to secure data based on the transmission level.

[0090] S1054: According to the transmission strategy, send secure data to the receiving end through the transmission link.

[0091] In the specific implementation of S1051, the cross-domain transmission request message is parsed to extract transmission level indicators and receiver information to guide subsequent transmission operations. Specifically, the transmission priority identifier field is read from the request header or payload. This field can be pre-set by the request initiator according to the urgency or reliability requirements of the transmission task. If the request does not explicitly carry this identifier, it is converted according to the risk level through a preset mapping relationship, for example, high risk is mapped to high reliability transmission level, and low risk is mapped to normal transmission level. At the same time, the receiver's network identity identifier, including the receiver's domain name or network address, port number, and supported communication protocol type, is parsed from the request's destination address field. This information is then combined into structured receiver information.

[0092] In the specific implementation of S1052, an edge-nearest forwarding mode is adopted to select the optimal network transmission path and establish an end-to-end transmission link with the receiving end. First, based on the network address of the receiving end, the list of available edge access nodes in the current network environment of the vehicle is queried. These edge access nodes include roadside communication units, mobile edge computing platforms, or the currently attached basic network access point. Then, through measurement methods such as signal strength, link delay, and bandwidth, the node with the closest distance and appropriate load is selected from the available nodes as a forwarding relay. Next, a transport layer connection establishment request is initiated to the receiving end through this edge node, and two-way authentication and session key negotiation are performed to build a secure and encrypted channel between the vehicle and the receiving end through edge node-optimized forwarding, thus completing the establishment of the transmission link.

[0093] In the specific implementation of S1053, the transmission level label determined in step S1051 is read, and a transmission strategy suitable for the current secure data is matched from a preset transmission strategy configuration set based on this level. This transmission strategy configuration set stores the correspondence between different transmission levels and a set of transmission control parameters. During matching, if the transmission level is high-reliability transmission, the corresponding high-reliability strategy is extracted. This strategy may include enabling application-layer acknowledgment and retransmission mechanisms, setting the maximum number of retransmissions to a preset value, selecting a high-strength algorithm for the data encryption suite, and enabling data compression. If the transmission level is normal transmission, the matched strategy may only include basic encryption and single-transmission without acknowledgment.

[0094] In the specific implementation of S1054, according to the data format and encryption requirements in the transmission strategy, secure data is serialized and encrypted, and a sequence number, timestamp, and message integrity check code are appended. If the transmission strategy requires the use of an acknowledgment and retransmission mechanism, a corresponding timeout retransmission timer is started after each frame or data block is sent, and a copy of the sent data is temporarily stored in the transmission buffer. Subsequently, the system continuously listens for acknowledgment responses from the receiving end. If an acknowledgment is received before the timer expires, the corresponding data in the buffer is cleared and the next part is sent. If no acknowledgment is received before the timer expires, a copy of the data is retrieved from the buffer for retransmission, and the retransmission counter is updated. If the retransmission attempt still fails after reaching the maximum number of retransmissions specified by the strategy, an exception alarm is triggered and transmission is terminated.

[0095] The above-described implementation of this application involves determining the transmission level and receiver information corresponding to the secure data based on the cross-domain transmission request. Then, based on the cross-domain receiver information, a transmission link is established with the receiver through an edge-nearest forwarding mode. Next, the transmission strategy corresponding to the secure data is determined according to the transmission level. In accordance with the transmission strategy, secure data is sent to the receiver through the transmission link, thereby enabling secure data transmission.

[0096] To ensure the reliability of the transmission of the secure data, in some embodiments, after S1054, the method may further include the following steps: S1055 to S1057.

[0097] S1055: According to the transmission strategy, obtain the hash verification result of the sent security data.

[0098] S1056: If an abnormal hash check result is detected, perform a link switch and update the transmission link.

[0099] S1057: Send secure data to the receiving end through the updated transmission link.

[0100] In the specific implementation of S1055, based on the convention regarding verification methods in the transmission strategy, an end-to-end hash verification mode is adopted, triggering the verification result retrieval action. The sending end sends a verification request message to the receiving end. This message carries the original hash value calculated and stored by the sending end for the sent secure data before transmission, and instructs the receiving end to return its equivalent hash value. Upon receiving the request, the receiving end performs the same hash algorithm on the received and assembled secure data, and sends the calculation result back in a verification response message. The sending end receives the verification response message, extracts the hash value calculated by the receiving end, and compares this value bit by bit with the original hash value stored locally to obtain the hash verification result.

[0101] In the specific implementation of S1056, if an abnormal hash check result is detected, it is determined that the current transmission link has a problem of data tampering, transmission error, or link unreliability, triggering a link switching operation. The sending end sends a disconnect request to the current transmission link, terminating all session states on the link and releasing link resources. Then, the edge node screening process is re-executed, excluding the edge nodes traversed by the link that just experienced the anomaly, and selecting another node from the list of available edge access nodes with the best comprehensive evaluation of signal quality, latency, and load as a new forwarding relay. Next, through the newly selected edge node, a new transport layer connection establishment request is initiated to the receiving end, performing bidirectional authentication and session key negotiation to establish a new transmission link that is distinct from the original link's physical or network path. Finally, the currently valid transmission link identifier is replaced with the newly established transmission link identifier, completing the transmission link update.

[0102] In the specific implementation of S1057, the secure data transmission operation is re-executed using the newly established transmission link. The sending end retrieves a previously processed copy of the secure data from local storage; this copy is the original secure data saved before transmission in step S1054. According to the parameters regarding encapsulation format, encryption algorithm, and reliability guarantees in the transmission strategy, the secure data copy is re-serialized, encrypted, and encapsulated with message integrity protection. Subsequently, through the updated transmission link, the encapsulated data is sent to the receiving end frame by frame or block by block, and the corresponding acknowledgment and retransmission guarantee mechanisms are executed according to the transmission strategy until all secure data is successfully transmitted and completely received by the receiving end.

[0103] The above-described implementation of this application's embodiments obtains the hash verification result of the sent security data according to the transmission strategy, and then performs link switching and updates the transmission link when an abnormal hash verification result is detected. The security data is then sent to the receiving end through the updated transmission link, thereby ensuring the reliability of the security data transmission.

[0104] As another embodiment, refer to Figure 4For all in-vehicle data from intelligent connected vehicles, a four-level standardized classification and grading system is constructed based on data sensitivity, information attributes, the degree of leakage risk, and business application scenarios to achieve accurate classification of all data: Level 1 is publicly available operation and maintenance data, including fixed road network information, publicly available traffic control data, and other data with no privacy risks; Level 2 is low-sensitivity driving data, including non-precise personal data such as regular vehicle speed, travel routes, and vehicle operating condition statistics; Level 3 is moderately sensitive perception data, including in-vehicle image perception, short-term driving trajectory, and driving behavior habit data; Level 4 is highly sensitive privacy data, including vehicle owner identity information, precise location data, in-vehicle voice interaction data, and vehicle unique identifier data. Real-time data collected from the vehicle is automatically labeled and classified, generating data level identifiers to provide a basis for subsequent differentiated privacy protection, risk assessment, and cross-domain access control.

[0105] A multi-dimensional dynamic risk identification model is constructed, based on data classification results, to extract risk characteristic parameters in real time from four dimensions: data sensitivity, cross-domain access subjects, data transmission links, and shared usage scenarios. A risk weighting algorithm is used to calculate the risk score for cross-domain data sharing in real time, dynamically classifying it into low, medium, and high risk levels.

[0106] The model monitors abnormal behaviors in real time during cross-domain sharing, including unauthorized sharing of highly sensitive data, access by untrusted entities, batch export of high-frequency data, and transmission link anomalies, enabling real-time risk identification, early warning, and tracing. Simultaneously, a risk strategy linkage mechanism is established, synchronizing real-time risk levels to the differential privacy protection module to achieve dynamic adaptive adjustment of protection strategies.

[0107] Based on data classification results and dynamic risk levels, a lightweight differential privacy and security protection framework adapted to vehicle-side scenarios is built, breaking through the limitations of traditional differential privacy with fixed noise and fixed privacy budget. This framework adopts an adaptive privacy budget allocation mechanism: for Level 1 public data, no privacy perturbation is performed, and sharing is directly allowed to ensure ultimate transmission performance; for Level 2 low-sensitivity, low-risk data, a small privacy budget is allocated, and lightweight Gaussian noise is added to achieve basic privacy protection; for Level 3 medium-sensitivity, medium-risk data, the noise intensity is dynamically adjusted to balance privacy security and data accuracy; for Level 4 high-sensitivity, high-risk data, the privacy budget is maximized, and dual protection of differential privacy perturbation and data anonymization is combined to prevent privacy leakage.

[0108] Meanwhile, the differential privacy algorithm is lightweighted on the vehicle side, eliminating redundant iterative calculation steps in the cloud algorithm, simplifying the noise generation formula, and sinking the core computing tasks to the edge nodes of the vehicle. This eliminates the need for cloud interaction, significantly reducing privacy computing latency and computing power consumption, and adapting to the limited computing power resources on the vehicle side.

[0109] Based on data protected by lightweight differential privacy, a vehicle-specific cross-domain sharing transmission mechanism is designed. An edge-nearest forwarding architecture is adopted, abandoning the traditional cloud-based relay transmission mode and shortening the data transmission link. Differentiated transmission strategies are set for different data levels: low-level data uses high-speed direct transmission, while high-level data uses encrypted fragmented verification transmission.

[0110] Simultaneously, a transmission reliability guarantee mechanism is configured. Through data hash verification, packet loss retransmission, and dynamic link optimization technology, the problems of packet loss, delay, and data distortion caused by fluctuations in the vehicle-side wireless network are solved. Under the premise of ensuring differential privacy protection and security, low-latency and high-reliability transmission of vehicle-side data across domains is achieved.

[0111] In the specific implementation process, refer to Figure 5 It collects all vehicle data in real time through onboard sensors, onboard terminals, and vehicle infotainment systems, including driving data, perception data, user privacy data, and operation and maintenance data. It then invokes a pre-defined data classification and grading rule engine to automatically classify the real-time data stream based on data field attributes, sensitive tags, and the level of leakage hazard, labeling it as level one to four data level tags. These level tags are then synchronized to the risk identification module and the privacy protection module.

[0112] For data to be shared across domains, four parameters are retrieved: data classification results, access subject identity, transmission link type, and sharing scenario. These parameters are then input into a multi-dimensional risk identification model. The model calculates a real-time risk score through weighted summaries, determining whether the current sharing scenario is low, medium, or high risk. If unauthorized access, high-risk link transmission, or batch export of private data is detected, a risk warning is immediately triggered, and the protection level of the corresponding data is upgraded.

[0113] Based on data classification labels and real-time risk levels, a differentiated privacy protection strategy is initiated: Level 1 public data, with no privacy disturbance, is directly transmitted; Level 2 low-sensitivity, low-risk data is allocated a basic privacy budget of 0.5, with lightweight Gaussian noise added for simple privacy desensitization; Level 3 medium-sensitivity, medium-risk data has its privacy budget dynamically adjusted between 1.0 and 2.0 based on the risk score, adaptively adjusting noise intensity to balance data accuracy and privacy security; Level 4 high-sensitivity, high-risk data is configured with the highest privacy budget of 3.0, superimposed with differential privacy disturbance and field desensitization for dual protection, completely shielding user privacy features. This solution deploys differential privacy computation at the vehicle's edge nodes, eliminating the round-trip latency of cloud data upload, computation, and distribution, with algorithm computation latency controlled within 10ms, meeting the real-time business needs of the vehicle.

[0114] After differential privacy and security processing is completed, the vehicle-side cross-domain transmission mechanism is activated: an edge-nearest forwarding mode is adopted to establish a high-speed transmission link with the cross-domain receiver; a hierarchical transmission strategy is adopted for different levels of data, with low-level data transmitted directly and high-level data transmitted in fragments with encryption. During transmission, data hash verification is performed in real time, and packet loss retransmission and optimal link switching are automatically triggered to address packet loss and latency issues caused by wireless network fluctuations, ensuring data transmission reliability.

[0115] After cross-domain data sharing is completed, information throughout the entire process, including the sharing entity, data level, protection strategy, and transmission logs, is recorded to create a security traceability ledger. Based on historical shared data, the risk identification model weights and differential privacy budget allocation rules are continuously iterated and optimized to continuously improve the system's protection accuracy and transmission performance.

[0116] Based on the data transmission method provided in the above embodiments, this application also provides specific implementations of the data transmission device. Please refer to the following embodiments.

[0117] First see Figure 6 The data transmission apparatus 600 provided in this application embodiment includes: The determination module 601 is used to determine the sensitivity level of the target data based on the data security characteristics of the target data.

[0118] The assessment module 602 is used to assess the transmission risk of a cross-domain transmission request in the event of a cross-domain transmission request for target data, and to determine the risk level corresponding to the cross-domain transmission request.

[0119] Allocation module 603 is used to obtain the privacy budget allocation based on sensitivity level and risk level.

[0120] The processing module 604 is used to process the target data according to the protection policy corresponding to the privacy budget allocation to obtain secure data.

[0121] The sending module 605 is used to send secure data in accordance with cross-domain transfer requests.

[0122] As one implementation of this application, the evaluation module 602 includes: The determination unit is used to determine the data sensitivity characteristics corresponding to the target data based on the sensitivity level of the target data when a cross-domain transmission request for the target data occurs.

[0123] The acquisition unit is used to acquire the identity information of the requesting subject, the transmission link type, and the shared usage scenario of the cross-domain transmission request.

[0124] The assessment unit is used to comprehensively assess the transmission risk of cross-domain transmission requests based on data sensitivity characteristics, subject identity information, transmission link type, and shared usage scenario, and obtain a transmission risk score.

[0125] The determination unit is also used to determine the risk level corresponding to the cross-domain transmission request based on the transmission risk score.

[0126] As one implementation of this application, the evaluation unit includes: The verification subunit is used to verify the access rights of the requesting subject based on the requesting subject's identity information and obtain the access rights verification result.

[0127] The evaluation subunit is used to evaluate the security strength of the transmission link according to the transmission link type and obtain the link security evaluation result.

[0128] The evaluation subunit is also used to comprehensively assess the transmission risk of cross-domain transmission requests based on permission verification results, link security assessment results, data sensitivity characteristics, and shared usage scenarios, and obtain a transmission risk score.

[0129] As one implementation of this application, the evaluation sub-unit includes: Extraction sub-units are used to extract features from permission verification results, link security assessment results, data sensitivity features, and shared usage scenarios to obtain corresponding risk feature quantification values.

[0130] The sub-unit is determined to determine the risk weight coefficients corresponding to the permission verification result, link security assessment result, data sensitivity characteristics, and shared usage scenario, respectively, according to the preset risk weight configuration rules.

[0131] The summation subunit is used to perform weighted summation based on the quantified values ​​of each risk feature and the corresponding risk weight coefficients to obtain the transmission risk score.

[0132] As one implementation of this application, it also includes: The generation module is used to generate corresponding risk warning information when cross-domain transmission requests are found to involve unauthorized access, high-risk link transmissions, or batch export of private data.

[0133] The risk level adjustment module is used to adjust the risk level of cross-domain transmission requests based on the type and number of abnormal behaviors corresponding to the risk warning information.

[0134] As one implementation of this application, the processing module 604 includes: The determination unit is used to determine the type and strength of protection strategy corresponding to the target data based on the privacy budget allocation.

[0135] The configuration unit is used to configure the running parameters of the privacy protection algorithm corresponding to the protection strategy type based on the protection strength, so as to obtain the target privacy protection algorithm.

[0136] The processing unit is used to process the target data according to the target privacy protection algorithm to obtain secure data.

[0137] As one implementation of this application, the processing unit includes: The generation sub-unit is used to generate a noise vector that is consistent with the dimensions of each sensitive field in the target data, according to the noise addition amount corresponding to the protection strength.

[0138] The injection subunit is used to inject noise into each corresponding sensitive field in the target data based on each noise vector to obtain safe data.

[0139] As one implementation of this application, the sending module 605 includes: The determination unit is used to determine the transmission level and receiving end information corresponding to the security data based on the cross-domain transmission request.

[0140] The establishment unit is used to establish a transmission link with the receiver based on cross-domain receiver information through the edge-nearest forwarding mode.

[0141] The determination unit is also used to determine the transmission strategy corresponding to secure data based on the transmission level.

[0142] The transmitting unit is used to send secure data to the receiving end through the transmission link in accordance with the transmission strategy.

[0143] As one implementation of this application, it also includes: The acquisition module is used to obtain the hash verification results of the sent secure data according to the transmission strategy.

[0144] The switching module is used to switch links and update transmission links when an abnormal hash check result is detected.

[0145] The sending module is used to send secure data to the receiving end through the updated transmission link.

[0146] Figure 7 A schematic diagram of the data transmission hardware provided in an embodiment of this application is shown.

[0147] The data transmission device may include a processor 701 and a memory 702 storing computer program instructions.

[0148] Specifically, the processor 701 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.

[0149] Memory 702 may include mass storage for data or instructions. For example, and not limitingly, memory 702 may include a hard disk drive (HDD), floppy disk drive, flash memory, optical disk, magneto-optical disk, magnetic tape, or Universal Serial Bus (USB) drive, or a combination of two or more of these. Where appropriate, memory 702 may include removable or non-removable (or fixed) media. Where appropriate, memory 702 may be internal or external to the integrated gateway disaster recovery device. In a particular embodiment, memory 702 is non-volatile solid-state memory.

[0150] Memory may include read-only memory (ROM), random access memory (RAM), disk storage media devices, optical storage media devices, flash memory devices, and electrical, optical, or other physical / tangible memory storage devices. Therefore, typically, memory includes one or more tangible (non-transitory) computer-readable storage media (e.g., memory devices) encoded with software including computer-executable instructions, and when the software is executed (e.g., by one or more processors), it is operable to perform the operations described with reference to the data transfer method according to any embodiment of this disclosure.

[0151] The processor 701 implements any of the data transmission methods described in the above embodiments by reading and executing computer program instructions stored in the memory 702.

[0152] In one example, the data transmission device may further include a communication interface 703 and a bus 710. For example, Figure 7 As shown, the processor 701, memory 702, and communication interface 703 are connected through bus 710 and complete communication with each other.

[0153] The communication interface 703 is mainly used to realize communication between various modules, devices, units and / or equipment in the embodiments of this application.

[0154] Bus 710 includes hardware, software, or both, that couples components of an online data traffic metering device together. For example, and not limitingly, the bus may include an Accelerated Graphics Port (AGP) or other graphics bus, an Enhanced Industry Standard Architecture (EISA) bus, a Front Side Bus (FSB), HyperTransport (HT) interconnect, an Industry Standard Architecture (ISA) bus, an Infinite Bandwidth Interconnect, a Low Pin Count (LPC) bus, a memory bus, a Microchannel 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 other suitable buses, or combinations of two or more of these. Where appropriate, bus 710 may include one or more buses. Although specific buses are described and illustrated in embodiments of this application, any suitable bus or interconnect is contemplated herein.

[0155] Furthermore, in conjunction with the data transmission methods described in the above embodiments, this application embodiment can provide a computer storage medium for implementation. This computer storage medium stores computer program instructions; when these computer program instructions are executed by a processor, they implement any of the data transmission methods described in the above embodiments.

[0156] This application also provides a computer program product, including a computer program, which, when executed, implements any of the data transmission methods described in the above embodiments.

[0157] It should be clarified that this application is not limited to the specific configurations and processes described above and shown in the figures. For the sake of brevity, detailed descriptions of known methods are omitted here. In the above embodiments, several specific steps are described and shown as examples. However, the method process of this application is not limited to the specific steps described and shown. Those skilled in the art can make various changes, modifications, and additions, or change the order of steps, after understanding the spirit of this application.

[0158] The functional blocks shown in the above-described structural diagram can be implemented as hardware, software, firmware, or a combination thereof. When implemented in hardware, they can be, for example, electronic circuits, application-specific integrated circuits (ASICs), appropriate firmware, plug-ins, function cards, etc. When implemented in software, the elements of this application are programs or code segments used to perform the required tasks. Programs or code segments can be stored on a machine-readable medium or transmitted over a transmission medium or communication link via data signals carried on a carrier wave. "Machine-readable medium" can include any medium capable of storing or transmitting information. Examples of machine-readable media include electronic circuits, semiconductor memory devices, ROM, flash memory, erasable ROM (EROM), floppy disks, CD-ROMs, optical disks, hard disks, fiber optic media, radio frequency (RF) links, etc. Code segments can be downloaded via computer networks such as the Internet, intranets, etc.

[0159] It should also be noted that the exemplary embodiments mentioned in this application describe methods or systems based on a series of steps or apparatus. However, this application is not limited to the order of the above steps; that is, the steps can be performed in the order mentioned in the embodiments, or in a different order, or several steps can be performed simultaneously.

[0160] The aspects of this disclosure have been described above with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of this disclosure. It should be understood that each block in the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, or other programmable data processing apparatus to produce a machine such that these instructions, executable via the processor of the computer or other programmable data processing apparatus, enable the implementation of the functions / actions specified in one or more blocks of the flowchart illustrations and / or block diagrams. Such a processor can be, but is not limited to, a general-purpose processor, a special-purpose processor, a special application processor, or a field-programmable logic circuit. It is also understood that each block in the block diagrams and / or flowchart illustrations, and combinations of blocks in the block diagrams and / or flowchart illustrations, can also be implemented by an FPGA performing the specified functions or actions, or can be implemented by a combination of an FPGA and computer instructions.

[0161] The above description is merely a specific implementation of this application. Those skilled in the art will clearly understand that, for the sake of convenience and brevity, the specific working processes of the systems, modules, and units described above can be referred to the corresponding processes in the foregoing method embodiments, and will not be repeated here. It should be understood that the protection scope of this application is not limited thereto. Any person skilled in the art can easily conceive of various equivalent modifications or substitutions within the technical scope disclosed in this application, and these modifications or substitutions should all be covered within the protection scope of this application.

Claims

1. A data transmission method, characterized in that, The method is applied to a vehicle, and the method includes: Based on the data security characteristics of the target data, determine the sensitivity level corresponding to the target data; In the event of a cross-domain transmission request for the target data, the transmission risk of the cross-domain transmission request is assessed, and the risk level corresponding to the cross-domain transmission request is determined. Based on the sensitivity level and the risk level, the privacy budget allocation is obtained; The target data is processed according to the protection strategy corresponding to the privacy budget allocation to obtain secure data; Send the security data according to the cross-domain transfer request.

2. The data transmission method according to claim 1, characterized in that, In the event of a cross-domain transmission request for the target data, the transmission risk of the cross-domain transmission request is assessed, and the risk level corresponding to the cross-domain transmission request is determined, including: In the event of a cross-domain transmission request for the target data, the data sensitivity characteristics corresponding to the target data are determined based on the sensitivity level of the target data. Obtain the identity information of the requesting subject, the transmission link type, and the shared usage scenario of the cross-domain transmission request; Based on the data sensitivity characteristics, the subject identity information, the transmission link type, and the shared usage scenario, the transmission risk of the cross-domain transmission request is comprehensively assessed to obtain a transmission risk score; Based on the transmission risk score, the risk level corresponding to the cross-domain transmission request is determined.

3. The data transmission method according to claim 2, characterized in that, The method of comprehensively assessing the transmission risk of the cross-domain transmission request based on the data sensitivity characteristics, the subject identity information, the transmission link type, and the shared usage scenario to obtain a transmission risk score includes: Based on the identity information of the requesting subject, the access permissions of the requesting subject are verified to obtain the permission verification result; Based on the transmission link type, the security strength of the transmission link is evaluated to obtain the link security evaluation result; Based on the permission verification results, the link security assessment results, the data sensitivity characteristics, and the shared usage scenario, the transmission risk of the cross-domain transmission request is comprehensively assessed to obtain a transmission risk score.

4. The data transmission method according to claim 3, characterized in that, Based on the permission verification result, the link security assessment result, the data sensitivity characteristics, and the shared usage scenario, a comprehensive assessment of the transmission risk of the cross-domain transmission request is performed to obtain a transmission risk score, including: Feature extraction is performed on the permission verification result, the link security assessment result, the data sensitivity feature, and the shared usage scenario to obtain the corresponding risk feature quantification value; Based on the preset risk weight configuration rules, the risk weight coefficients corresponding to the permission verification result, the link security assessment result, the data sensitivity feature, and the shared usage scenario are determined respectively. The transmission risk score is obtained by weighting and summing the quantified values ​​of each risk feature with the corresponding risk weight coefficients.

5. The data transmission method according to claim 2, characterized in that, After determining the risk level corresponding to the cross-domain transmission request based on the transmission risk score, the method further includes: If the cross-domain transmission request is found to involve unauthorized access, high-risk link transmission, or batch export of privacy data, a corresponding risk warning message will be generated. Based on the type and number of abnormal behaviors corresponding to the risk warning information, the risk level of the cross-domain transmission request is increased.

6. The data transmission method according to claim 1, characterized in that, The process of processing the target data according to the protection policy corresponding to the privacy budget allocation to obtain secure data includes: Based on the privacy budget allocation, determine the protection strategy type and protection strength corresponding to the target data; Based on the protection strength, the running parameters of the privacy protection algorithm corresponding to the protection strategy type are configured to obtain the target privacy protection algorithm; The target data is processed according to the target privacy protection algorithm to obtain secure data.

7. The data transmission method according to claim 6, characterized in that, The privacy protection algorithm is a differential privacy algorithm. The step of processing the target data according to the target privacy protection algorithm to obtain secure data includes: Based on the noise addition amount corresponding to the protection strength, generate a noise vector that is consistent with the dimensions of each sensitive field in the target data; Based on each of the noise vectors, noise is injected into each of the corresponding sensitive fields in the target data to obtain secure data.

8. The data transmission method according to claim 1, characterized in that, Sending the security data according to the cross-domain transfer request includes: Based on the cross-domain transmission request, determine the transmission level and receiving end information corresponding to the security data; Based on the cross-domain receiver information, a transmission link is established with the receiver through the edge proximity forwarding mode; Based on the transmission level, determine the transmission strategy corresponding to the secure data; According to the transmission strategy, the security data is sent to the receiving end through the transmission link.

9. The data transmission method according to claim 8, characterized in that, After transmitting the secure data to the receiving end via the transmission link according to the transmission strategy, the method further includes: According to the transmission strategy, obtain the hash verification result of the sent security data; If an abnormal hash verification result is detected, a link switch is performed and the transmission link is updated. The security data is sent to the receiving end via the updated transmission link.

10. A data transmission device, characterized in that, The device includes: The determination module is used to determine the sensitivity level of the target data based on its data security characteristics. The assessment module is used to assess the transmission risk of a cross-domain transmission request in the event of a cross-domain transmission request for the target data, and to determine the risk level corresponding to the cross-domain transmission request. The allocation module is used to obtain the privacy budget allocation amount based on the sensitivity level and the risk level; The processing module is used to process the target data according to the protection policy corresponding to the privacy budget allocation to obtain secure data; The sending module is used to send the security data according to the cross-domain transmission request.

11. A data transmission device, characterized in that, The device includes: a processor and a memory storing computer program instructions; the processor reads and executes the computer program instructions to implement the data transmission method as described in any one of claims 1-9.

12. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores computer program instructions, which, when executed by a processor, implement the data transmission method as described in any one of claims 1-9.

13. A computer program product, characterized in that, When the instructions in the computer program product are executed by the processor of the electronic device, the electronic device performs the data transmission method as described in any one of claims 1-9.

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