Block chain-based traffic data secure transmission method and system

Abstract

The invention discloses a traffic data secure transmission method and system based on a block chain, and relates to the technical field of block chain application, and the method comprises the steps: connecting a traffic data monitoring network to obtain a data set, and building an association relationship between the data set and a traffic event; according to the configuration rule partition, obtaining a block chain processing area and a mapping area; positioning data in the processing area, extracting target data, performing hash processing and signing; the abstract, the signature and the like are subjected to up-chain recording, and down-chain mapping is established; and transmitting the data set based on the block chain network and the mapping relationship. The technical problem that a traditional traffic data transmission method is insufficient in the aspects of data encryption, authority management, tampering prevention, traceability and the like is solved, and the technical effect of improving the safety, integrity and traceability of data transmission is achieved.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of blockchain application, and particularly relates to a traffic data secure transmission method and system based on a blockchain. BACKGROUND

[0002] In an intelligent transportation system, secure transmission of traffic data is crucial for traffic safety, management and related application development. In the prior art, traditional traffic data transmission methods have deficiencies in data encryption, permission management, tamper prevention and traceability.

[0003] With the development of intelligent transportation, traffic data presents the characteristics of large data volume, complex types (including vehicle position, speed, road signs, etc.), strong real-time and privacy security. Traditional methods use centralized storage, which is vulnerable to attack and has high risk of single point failure. The encryption and verification process is fragmented, which cannot guarantee data integrity. Permission management is scattered and lacks dynamic verification and traceability mechanisms. SUMMARY

[0004] The present application provides a traffic data secure transmission method and system based on a blockchain, which solves the technical problem of deficiencies in data encryption, permission management, tamper prevention and traceability of traditional traffic data transmission methods.

[0005] In a first aspect of the present application, a traffic data secure transmission method based on a blockchain is provided, the method comprising: connecting a traffic data monitoring network, obtaining a traffic collection data set, and establishing an association relationship between the traffic collection data set and a traffic event; configuring an encrypted data partition rule according to the association relationship, identifying and partitioning the traffic collection data set to obtain a blockchain processing area and a blockchain mapping area; based on the blockchain processing area, performing data positioning on the traffic collection data set, extracting target collection data for hash processing, generating a data digest, and digitally signing the data digest using a private key of a data source node; submitting the data digest, digital signature, data index and access permission information to a blockchain network for on-chain recording, and establishing an off-chain mapping relationship with the blockchain mapping area; and transmitting the traffic collection data set based on the blockchain network and the off-chain mapping relationship.

[0006] In a second aspect of the present application, a blockchain-based traffic data secure transmission system is provided, which comprises: a traffic collection dataset acquisition module configured to connect a traffic data monitoring network, acquire a traffic collection dataset, and establish an association between the traffic collection dataset and a traffic event; a traffic collection dataset partitioning module configured to configure an encrypted data partitioning rule according to the association, identify and partition the traffic collection dataset, and obtain a blockchain processing zone and a blockchain mapping zone; a traffic collection dataset positioning module configured to perform data positioning on the traffic collection dataset based on the blockchain processing zone, extract target collection data for hash processing, generate a data digest, and perform digital signature using a private key of a data source node; a blockchain network recording module configured to submit the data digest, digital signature, data index, and access permission information to a blockchain network for on-chain recording, and establish an off-chain mapping relationship with the blockchain mapping zone; and a traffic collection dataset transmission module configured to perform traffic collection dataset transmission based on the blockchain network and the off-chain mapping relationship.

[0007] The one or more technical solutions provided in the present application have at least the following technical effects or advantages:

[0008] In the present application, a traffic collection dataset is acquired by connecting a traffic data monitoring network, and an association between the traffic collection dataset and a traffic event is established. An encrypted data partitioning rule is configured according to the association, and the data is divided into a blockchain processing zone and a blockchain mapping zone. Target data in the blockchain processing zone is submitted to a blockchain network for recording after hash processing and digital signature, and an off-chain mapping relationship is established. Data is transmitted based on the blockchain network and the off-chain mapping relationship. Permission management verification is performed by a smart contract, and data consistency verification is completed by on-chain hash, thereby realizing secure and efficient transmission of traffic data, solving the deficiencies of traditional methods in terms of data encryption, permission management, tamper resistance, and traceability, improving the security and reliability of traffic data transmission, and achieving the technical effects of improving the security, integrity, and traceability of data transmission. BRIEF DESCRIPTION OF DRAWINGS

[0009] In order to more clearly illustrate the technical solutions in the embodiments of the present application, the drawings needed in the embodiment description will be briefly introduced. Obviously, the drawings in the following description are only some embodiments of the present application, and other drawings can be obtained by those skilled in the art without creative labor.

[0010] Figure 1 is a flowchart of a blockchain-based traffic data secure transmission method provided by an embodiment of the present application.

[0011] Figure 2This is a schematic diagram of a blockchain-based secure transmission system for traffic data, provided in an embodiment of this application.

[0012] Figure labeling: Traffic data acquisition module 1, Traffic data partitioning module 2, Traffic data location module 3, Blockchain network recording module 4, Traffic data transmission module 5. Detailed Implementation

[0013] This application provides a blockchain-based method and system for secure transmission of traffic data, which addresses the technical shortcomings of traditional traffic data transmission methods in terms of data encryption, access control, tamper prevention, and traceability.

[0014] The technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only a part of the embodiments of this application, and not all of them. All other embodiments obtained by those skilled in the art based on the embodiments of this application without creative effort are within the scope of protection of this application.

[0015] It should be noted that the terms "first," "second," etc., in the specification and accompanying drawings of this application are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate so that the embodiments of this application described herein can be implemented in orders other than those illustrated or described herein. Furthermore, the terms "comprising" and "having," and any variations thereof, are intended to cover non-exclusive inclusion; for example, a process, method, system, product, or server that includes a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or modules not explicitly listed or inherent to such processes, methods, products, or devices.

[0016] Example 1, as Figure 1 As shown, a blockchain-based method for secure transmission of traffic data includes:

[0017] Step A100: Connect to the traffic data monitoring network, obtain the traffic data collection dataset, and establish the correlation between the traffic data collection dataset and traffic events.

[0018] In this embodiment, the traffic data monitoring network is a distributed data acquisition system composed of various sensors, intelligent devices and communication modules deployed in traffic scenarios, used to acquire multi-dimensional data information in the traffic field in real time.

[0019] Specifically, first, a collection system covering multi-dimensional data is constructed. By using the sensor network deployed in the road infrastructure (such as traffic lights, cameras, radars) and the vehicle-mounted terminal, real-time collection of vehicle position, speed, direction, road identification information, traffic light state, surrounding vehicle identification information and other data is carried out, forming a traffic collection data set containing a large amount of real-time information, and the specific steps are described in detail in A110. These data cover key elements such as vehicle dynamics and road environment in the traffic scene, providing a rich data source for subsequent analysis.

[0020] After collecting the data, the association between the traffic collection data set and the traffic event is established. The separation of data and events makes it impossible to differentiate processing according to event characteristics, so a traffic event library needs to be introduced as an association bridge. First, the events in the traffic event library are classified according to the influence range, timeliness and involved subject level. Then, for each level of event, the core influence data and auxiliary influence data are analyzed. By establishing the mapping relationship between events and data sets, the key data fields corresponding to different event types are determined, forming a bidirectional indexing mechanism for events and data, so that each collection data can be traced back to a specific traffic event scene, providing a logical basis for subsequent data partitioning and safety processing. The specific steps are described in detail in A210-A220.

[0021] Through the multi-source sensor network, comprehensive collection of traffic data is realized, and based on the event level system, deep association between data and events is established, laying a foundation for subsequent data classification processing according to event characteristics, so that traffic data can more accurately serve the safety transmission and management needs.

[0022] Step A200: According to the association relationship, configure the encryption data partitioning rule, identify the partitioning of the traffic collection data set, and obtain the blockchain processing area and the blockchain mapping area.

[0023] Optionally, according to the association between the traffic collection data set and the traffic event, configure the encryption data partitioning rule, identify the partitioning according to the division of core data and auxiliary data, and divide the core data into the blockchain processing area and the auxiliary data into the blockchain mapping area. The specific steps are described in detail in A230.

[0024] Step A300: Based on the blockchain processing area, data positioning is performed on the traffic collection data set, target collection data is extracted for hash processing, a data digest is generated, and a private key used by a data source node is used for digital signature.

[0025] In an embodiment of the present application, first, the partitioned core traffic data (such as vehicle location, speed, and other sensitive information) is precisely positioned using the blockchain processing area. The target data is quickly retrieved from the blockchain processing area using the data tag or index mechanism. For example, when processing traffic accident-related data, the key information to be chained is located through the mapping relationship between the event level and the data field (such as the vehicle collision location, driver identity, and other core data corresponding to high-level accidents).

[0026] After locating the target data, the system performs a hash processing. During the hash processing, the system calls the SHA-256 encryption hash algorithm to perform layer-by-layer operations on the target data: first, the original data (such as vehicle speed values) is divided into fixed-length data blocks, each data block is padded to meet the algorithm input requirements, and then through complex mathematical transformations (including bit operations, cyclic redundancy check, etc.), the information of each data block is gradually compressed and integrated, and finally a 256-bit hash value (i.e. data digest) is generated. The digest corresponds to the original data one-to-one, and has irreversibility (the original data cannot be inferred from the digest) and high sensitivity (any slight change in the original data will result in a completely different digest). For example, the vehicle speed of 60 km / h generates a unique 64-bit hexadecimal string after SHA-256 processing. If the data is tampered with to 65 km / h during transmission, the newly calculated hash value will be completely different from the digest stored on the chain, thereby effectively verifying the integrity of the data.

[0027] Finally, the data source node (such as a vehicle terminal or a traffic sensor) uses its private key to digitally sign the data digest. The private key signing process is implemented through asymmetric encryption technology, and the signature result is bound to the data digest, ensuring the non-repudiation of the data source. For example, a traffic camera as a data source node signs the digest of the collected road identification information with a private key, and the receiver verifies the validity of the signature through a public key to confirm that the data was indeed sent by the node.

[0028] Through the above steps, the encryption preprocessing of core traffic data is realized. The hash processing ensures data integrity, and the private key signature ensures the credibility of the data source. The combination of the two solves the problem of data tampering and difficulty in tracing responsibility in the prior art, and ultimately achieves the effect of verifying the integrity and tracing the source of core traffic data based on blockchain technology, improving the security and credibility of data transmission.

[0029] Step A400: submit the data digest, digital signature, data index, and access permission information to the blockchain network for on-chain recording, and establish a chain-off mapping relationship with the blockchain mapping area.

[0030] In the embodiments of the present application, the data index is a unique identifier for locating the traffic collection data (including on-chain core data and off-chain auxiliary data). The access permission information refers to the permission rules set for different data access parties, including access identity, data access permission, and access history behavior, and other information related to multi-factor strategy matching mechanism.

[0031] Specifically, after completing the hash processing and digital signature of the core traffic data, the key information needs to be stored on the chain and the off-chain mapping needs to be established. First, the system encapsulates the data digest (a unique identifier generated by a hash algorithm), the digital signature (the private key signature result of the data source node), the data index (a unique identifier for locating the data), and the access permission information (such as the role permission of the data access party) in a structured manner to form a transaction data unit that conforms to the storage format of the blockchain. For example, the digest of the vehicle location data, the signature of the corresponding node, the storage index of the data off-chain, and the permission information of the authorized traffic police department for access are integrated into a transaction package.

[0032] Subsequently, the transaction package is submitted to the blockchain network for verification and recording through the consensus mechanism of the blockchain network, such as Proof of Work (PoW) or Proof of Stake (PoS). The consensus nodes verify the validity of the transaction, such as checking whether the digital signature matches and whether the access permission is compliant, and after verification, the transaction is written to the new block of the blockchain, realizing the non-tamperable storage of the data. For example, in the traffic data scenario, multiple intersection sensor nodes act as consensus nodes to jointly verify the transaction package of certain accident-related data, and after ensuring its legality, it is permanently recorded on the chain.

[0033] At the same time, the system establishes the off-chain mapping relationship between the blockchain processing area and the blockchain mapping area. For auxiliary data in the blockchain mapping area, such as surrounding vehicle trajectories, it is stored in an off-chain distributed database such as IPFS through an encryption algorithm (such as AES), and the index information such as the database address, file hash, etc. is recorded on the chain, and the specific steps are described in detail in A410. For example, after the auxiliary data is encrypted and stored off-chain, only the index value of the data is saved on the chain, forming a mapping pair of on-chain index-off-chain data, ensuring that the data can be quickly located off-chain resources when accessed.

[0034] Through the process of data encapsulation, consensus verification, on-chain recording, and off-chain mapping, the on-chain evidence of core data and the efficient management of auxiliary data off-chain are realized, ensuring data security while avoiding the performance bottleneck caused by the on-chain storage of full data. Ultimately, it achieves the effect of trusted storage of core data based on blockchain and efficient collaboration of off-chain data, realizing the safe transmission and flexible access of traffic data.

[0035] Step A500: Perform traffic collection data set transmission based on the blockchain network and the off-chain mapping relationship.

[0036] In an embodiment of the present application, first, data preprocessing is completed based on a blockchain processing area and a blockchain mapping area. The system generates a unique data digest by hashing the core data through the blockchain processing area, and signs it with a private key by the data source node, ensuring the integrity and source credibility of the core data; at the same time, the auxiliary data is stored in an off-chain distributed database after encryption, and a unique mapping relationship is established between the on-chain data index and the off-chain data path, forming a hierarchical storage structure of core data on-chain and auxiliary data off-chain. For example, vehicle location, speed and other core data are stored on-chain, and surrounding vehicle trajectory and other auxiliary data are stored off-chain, and fast association is achieved through indexing.

[0037] In the data transmission phase, the system utilizes the distributed characteristics of the blockchain network to write data digest, digital signature, data index and access permission information into the blockchain through the consensus mechanism, realizing the tamper-proof transmission of core data. At the same time, the off-chain auxiliary data is transmitted synchronously with the on-chain data through an encrypted channel, ensuring the confidentiality of the data during transmission. For example, in the transmission of traffic event data, the hash value and signature of the core data are broadcast to each node through the blockchain network, and the auxiliary data is transmitted to the target node through the Secure Sockets Layer (SSL) protocol, and the two are synchronously associated through the data index.

[0038] After transmission is completed, the system performs permission management and data verification through the smart contract deployed in the blockchain network. When the data access party initiates a request, the smart contract first verifies its identity and access permission, calls the off-chain auxiliary data, and performs consistency verification based on the on-chain hash value, ensuring that the data has not been tampered with during transmission. For example, when the traffic police department applies to access certain accident data, the smart contract first checks its permission level, calls the off-chain auxiliary data, and compares it with the hash value of the core data stored on-chain, and allows access if they are consistent.

[0039] Through the complete process of data preprocessing, blockchain network transmission and smart contract verification, the core data is secured by the tamper-proof nature of the blockchain, and the auxiliary data transmission efficiency is improved by the off-chain mapping mechanism, achieving efficient collaborative transmission of core data and auxiliary data while ensuring the integrity and credibility of traffic data, meeting the dual requirements of data security and real-time performance of the intelligent transportation system.

[0040] Further, step A500 in the method provided in the embodiments of the present application comprises:

[0041] A510: permission management and verification of access, authorization and calling behavior of traffic collection data through the smart contract deployed in the blockchain network.

[0042] A520: When the data access party is verified by the permission management, the off-chain data is called through the data index and consistency verification is performed based on the on-chain hash, and the traffic transmission data is obtained after the consistency verification.

[0043] In the embodiments of the present application, the smart contract is deployed in the blockchain network, which is an automatic program for permission management verification of access, authorization and calling behavior of traffic collection data. It contains a multi-factor access strategy matching mechanism of access identity, data access permission and access history behavior.

[0044] Specifically, after completing the transmission of the traffic collection data set based on the blockchain network and the off-chain mapping relationship, the access and use of the data need to be safely controlled. When the data access party initiates a data acquisition request, the smart contract deployed in the blockchain network is first triggered to trigger the permission management verification process, and the specific steps are described in detail in A511-A512.

[0045] When the access party passes the permission verification, the auxiliary data (such as the trajectories of surrounding vehicles and the status of traffic lights) stored in the off-chain distributed database is called according to the data index (such as the off-chain data path corresponding to the event ID) stored on the chain, and the corresponding core data hash value (such as the hash digest of the vehicle speed and position) is obtained from the blockchain. At this time, the system will perform consistency verification: comparing the off-chain auxiliary data with the hash value of the on-chain core data, by recalculating the hash value of the off-chain data and matching it with the on-chain record, to ensure that the data has not been tampered with during transmission. For example, when calling the congestion auxiliary data (off-chain) of a road section, the data integrity is verified by comparing it with the hash value of the vehicle speed data stored on the chain for that road section. If the comparison is consistent, the access party is allowed to obtain the complete traffic transmission data; if it is not consistent, the access is denied and an exception log is recorded.

[0046] During the entire permission verification and data calling process, the smart contract will automatically write the access behavior (such as access time, data type, and operation subject) into the blockchain in the form of a transaction, forming an unalterable audit log. These logs can be used for subsequent data usage traceability, permission compliance review and security incident investigation, ensuring the transparency and traceability of data access.

[0047] Through the processes of permission verification, off-chain data calling, on-chain hash comparison and operation audit, the safe access and trusted use of traffic collection data are realized, achieving the effect of ensuring the compliance of traffic data access, protecting the integrity of data through on-chain and off-chain collaborative verification mechanism, and improving the data security management level of intelligent transportation system through the whole process audit of access behavior through blockchain storage.

[0048] Further, the step A100 in the method provided by the embodiments of the present application comprises:

[0049] A110: the traffic collection dataset comprises one or more of vehicle position, vehicle speed, vehicle direction, road identification information, traffic light state, and surrounding vehicle identification information.

[0050] Optionally, first, sensor devices deployed at key nodes of the road, such as global positioning system (GPS) receivers, traffic signals, laser radars, cameras, and wireless communication modules, capture vehicle dynamic data and road environment information in real time. For example, the vehicle position coordinates and driving direction are continuously obtained by using the vehicle-mounted GPS module, the vehicle speed is monitored by the radar devices installed on both sides of the road, the road identification and traffic light state are identified by the cameras at the traffic intersection, and the identification information of the surrounding vehicles, such as license plates and vehicle models, is obtained by the vehicle-mounted cameras or sensor network. These devices transmit the collected data to the data aggregation center in real time through 5G, Wi-Fi Internet of Things communication protocols, forming a traffic collection dataset containing multiple types of data.

[0051] Taking vehicle speed monitoring as an example, the traditional single-point speed measurement device is easily disturbed by the environment and has a limited coverage, while the collaborative work of the distributed radar network and the vehicle-mounted sensor can realize dynamic tracking and multi-source verification of the vehicle speed, ensuring the reliability of the data. In terms of road identification information collection, the built-in image recognition algorithm of the camera can analyze the images captured by the camera in real time, extract key information such as speed limit signs and no-passing signs, and avoid the lag and errors of manual input. By integrating these different dimensions of data, a three-dimensional traffic scene model can be constructed, providing rich information support for subsequent analysis of traffic events and data security transmission.

[0052] Through the collaborative deployment of multiple types of sensor devices and data fusion technology, multi-dimensional traffic collection datasets can be obtained, ensuring the integrity of the dataset and the scene restoration ability, laying a foundation for establishing the correlation between traffic data and events and implementing differentiated data security processing strategies.

[0053] Further, the method provided in the embodiments of the present application comprises the following steps:

[0054] A210: obtaining a traffic event library, and classifying traffic events according to the influence range, timeliness, and involved subject level of the traffic event library.

[0055] A220: analyzing event core influence data and auxiliary influence data for each classified traffic event, establishing a mapping relationship between the traffic event and the traffic collection dataset, and identifying the classification features of the core data and auxiliary data of each traffic event.

[0056] A230: Set the encrypted data partition rule according to the division of the core data and auxiliary data, wherein the core data corresponds to the blockchain processing area, and the auxiliary data corresponds to the blockchain mapping area.

[0057] In the embodiments of the present application, the traffic event library is a collection for storing traffic event data.

[0058] Specifically, first, a traffic event library is constructed, which integrates historical traffic event data (such as accidents, congestion, construction, etc.) and is classified into three levels according to the influence range (such as regional level, city level), timeliness (such as real-time event, historical event), and involved subject level (such as ordinary vehicles, emergency vehicles). For example, a city-level real-time traffic accident is divided into a high level because of its wide influence range and involvement of emergency vehicles; and a local road section temporary congestion is classified as a low level event.

[0059] After classification, the core influence data and auxiliary influence data need to be analyzed for each level of event, the cross relationship dimension of the core and auxiliary influence data is set according to the level (the higher the level, the higher the dimension), and the extraction rule of the two types of data is determined according to the analysis of the relationship, which is specifically described in A221-A222.

[0060] Then, the mapping relationship between the event and the data set is established, the key attributes (such as influence range, timeliness, and involved subject level) of each level of event are extracted from the traffic event library, and then these attributes are associated and matched with specific fields in the traffic collection data set. Taking the accident level as an example, a low level accident is only associated with basic data fields such as vehicle speed and position, a medium level accident is further associated with fields such as involved vehicle type and collision angle, and a high level accident needs to be associated with more fields such as driver identity and vehicle trajectory within 500 meters. By gradually expanding the corresponding relationship between event attributes and data fields, sensitive features (such as geographic location and identity) contained in the core data and extended features (such as environmental state and non-sensitive trajectory) of the auxiliary data are identified, and finally clear standards for dividing core data and auxiliary data according to event level are formed, providing a basis for setting the encrypted data partition rule later.

[0061] Based on the above association relationship and features, the system configures the encrypted data partition rule: the core data is divided into the blockchain processing area, the data digest is generated by using the hash algorithm and is signed by the private key, to ensure the integrity and traceability of the data on the chain; the auxiliary data is divided into the blockchain mapping area and is stored in the off-chain distributed database, and the quick call is realized through the on-chain index. For example, the real-time position of the emergency vehicle is stored on the chain as the core data, and the model information of the surrounding ordinary vehicles is stored off-chain as the auxiliary data, which is accessed through the index after permission verification.

[0062] Through the process of event library construction, level classification, data analysis and partition configuration, precise mapping from traffic event characteristics to data security strategy is realized. With the help of event level driven data grading mechanism, the core data security is ensured through the blockchain, and the auxiliary data processing efficiency is improved through off-chain storage, so as to achieve the effect of differentiated data security management and efficient transmission based on event characteristics.

[0063] Further, the step A220 in the method provided by the embodiment of the application comprises:

[0064] A221: According to the cross relationship dimension of the core influence data and the auxiliary influence data, the higher the traffic event level, the higher the cross relationship dimension.

[0065] A222: According to the cross relationship dimension, the core influence data and the auxiliary influence data of the traffic event are analyzed, and the extraction rule of the core influence data and the auxiliary influence data is determined.

[0066] In the embodiment of the application, the cross relationship dimension refers to the number of associated levels between the core influence data and the auxiliary influence data according to the traffic event level, which is used to reflect the analysis complexity of the two types of data.

[0067] Specifically, first, the cross relationship dimension of the core influence data and the auxiliary influence data is preset according to the level of the traffic event (such as low, medium and high). For example, a low-level event (such as a temporary congestion of a local road section) is set to have 1-2 cross dimensions, only the vehicle speed and the congestion position are taken as the core data, and the surrounding road signs are taken as auxiliary data. A medium-level event (such as a traffic accident on a city trunk road) is improved to have 2-3 cross dimensions, in addition to the position and speed of the accident vehicle, the type of the involved vehicle and the driving direction of the surrounding vehicles need to be associated and analyzed. A high-level event (such as a city-level traffic control involving emergency vehicles) is set to have 3-5 cross dimensions, and the cross relationship of multiple source data such as the route of the emergency vehicle, the real-time traffic light state and the trajectory of the surrounding vehicles within 500 meters needs to be integrated.

[0068] In the analysis process, the data is processed hierarchically using the cross relationship dimension. Taking a high-level event as an example, first, the position of the emergency vehicle is extracted as the core data, then based on the vehicle type-direction dimension, the avoidance trajectory of the surrounding ordinary vehicles is taken as auxiliary data and cross-verified with the core data; and through the traffic light state-event timeliness dimension, the expansion effect of the intersection signal timing adjustment on the event influence range is analyzed to form the second layer of auxiliary data. Through multi-dimensional cross analysis, the core data and the auxiliary data are no longer simply divided into two categories, but form a network association structure, ensuring the data integrity and scene restoration of high-level events. Low-level events are quickly divided using simple dimensions.

[0069] By dynamically adjusting the cross relationship dimension, fine analysis of different level event data is realized. For low level events, concise dimension setting avoids waste of data processing resources; for high level events, multi-dimensional cross analysis ensures the comprehensiveness of core data and the relevance of auxiliary data, so as to dynamically adjust the data analysis depth based on the event level, and improve the correlation degree of high level event data and the processing efficiency of low level event.

[0070] Further, the step A400 in the method provided by the embodiment of the application comprises:

[0071] A410: The auxiliary data is stored in the off-chain distributed database in an encrypted manner, and an on-chain data index is used to establish a unique mapping relationship with the auxiliary data path, which is used to call the off-chain data after the smart contract verification.

[0072] Specifically, in order to optimize the management of auxiliary data, first, the auxiliary data (such as surrounding vehicle trajectory, road environment information, etc.) in the blockchain mapping area is encrypted, and high-strength encryption algorithms such as AES-256 are used to encrypt the data field by field or file by file, to ensure the confidentiality of off-chain storage. For example, the surrounding vehicle identification information in the traffic event is encrypted by the AES algorithm, and stored in the off-chain distributed database such as IPFS or CouchDB in the form of ciphertext, to prevent the data from being illegally read during storage.

[0073] Then, a unique mapping relationship between the on-chain data index and the off-chain auxiliary data path is established in the blockchain network. Specifically, each auxiliary data file generates a unique path identifier when stored off-chain, such as a file hash value or a database address, and the mapping relationship between the path identifier and the data index (such as a unique key value composed of event ID and data type) is recorded on the chain.

[0074] When the smart contract verification is passed, such as the successful permission verification of the data access party, the off-chain auxiliary data path is quickly located by using the on-chain data index, the encrypted auxiliary data is called and decrypted, to ensure the compliance and real-time of data use. For example, when the traffic management department initiates a data access request, the smart contract first verifies its permission, finds the off-chain data path according to the on-chain index after passing, calls the encrypted surrounding vehicle trajectory data, and performs correlation analysis with the on-chain core data after decryption.

[0075] Through the above process, the secure storage and efficient calling of auxiliary data are realized, so as to improve the data access efficiency and system scalability under the premise of ensuring the security of auxiliary data, and support real-time collaborative processing of multi-dimensional data in the intelligent transportation scenario.

[0076] Further, the step A510 in the method provided by the embodiment of the application comprises:

[0077] A511: After the access request is initiated, the current access identity and data access permission are compared by the smart contract, and the calling behavior authorization matching determination is performed in combination with the access behavior, wherein the smart contract includes a multi-factor access strategy matching mechanism of access identity, data access permission, and access historical behavior.

[0078] A512: When the matching is successful, the off-chain auxiliary data is allowed to be consistent with the on-chain core data, and the access behavior is written into the blockchain network to form an audit log for subsequent data tracking and backtracking analysis.

[0079] In one embodiment, to realize fine-grained permission management, a multi-factor access strategy mechanism is constructed by deploying a smart contract in a blockchain network. When a data access party (such as a traffic police department or a scientific research institution) initiates a request, the smart contract first extracts the access identity information (such as an institution code or a user ID) and compares it with a predefined permission list (such as the traffic police department having access to real-time accident data), and retrieves the historical behavior record (such as the data calling frequency and operation type in the past 30 days) of the access person, forming multi-dimensional verification parameters. For example, when a traffic police department applies to call congestion data of a certain road section, the smart contract will check whether it has the access permission of real-time traffic data, and analyze whether its historical access record has abnormal calling behavior.

[0080] In the matching determination stage, the smart contract uses a rule engine to weight match the access identity, permission, and historical behavior. If the access identity meets the permission requirements and the historical behavior is normal (such as no unauthorized record), it is determined that the matching is successful, and the off-chain auxiliary data and the on-chain core data are allowed to be called. For example, after the matching is successful, the surrounding vehicle trajectory data (auxiliary data) stored in the off-chain encryption is retrieved through data indexing, and consistency verification is performed with the core data hash value stored on the chain to ensure that the data has not been tampered with. After the verification is passed, the access party obtains the complete traffic data, and the smart contract writes this access behavior (such as access time, data type, and operation subject) into the blockchain in the form of a transaction to form an unalterable audit log.

[0081] Through this process, the smart contract realizes the full-process automatic management from permission verification, data verification to operation audit, achieves fine-grained control of traffic data access and credible traceability of operation behavior through multi-factor verification of the smart contract and storage on the blockchain, and improves the standardization and auditability of data security management.

[0082] In summary, the traffic data security transmission method based on the blockchain provided by the embodiments of the present application has the following technical effects:

[0083] This application collects traffic datasets by connecting to a traffic data monitoring network, establishes a correlation between the datasets and traffic events, and processes the data through event level classification, core and auxiliary data parsing, and encrypted partitioning. The core data is hash-signed and recorded on the blockchain, while the auxiliary data is encrypted and stored off-chain with a mapping relationship established. Data transmission is achieved based on the blockchain network and off-chain mapping. Access verification and data consistency verification are performed through smart contracts, thereby completing the transmission and management of traffic data securely and efficiently. This makes the secure transmission method of traffic data more reliable and achieves the technical effect of improving the security, integrity, and traceability of data transmission.

[0084] Example 2, as Figure 2 As shown, based on the same inventive concept as in Embodiment 1 above, this application provides a blockchain-based secure transmission system for traffic data, the system comprising:

[0085] Traffic data acquisition module 1 is used to connect to the traffic data monitoring network, obtain traffic data sets, and establish the correlation between the traffic data sets and traffic events.

[0086] Traffic data collection dataset partitioning module 2 is used to configure encrypted data partitioning rules according to the association relationship, identify and partition the traffic data collection dataset, and obtain the blockchain processing area and the blockchain mapping area.

[0087] The traffic data collection dataset positioning module 3 locates the traffic data collection dataset based on the blockchain processing area, extracts the target data collection data, performs hash processing, generates a data digest, and digitally signs it using the private key used by the data source node.

[0088] The blockchain network recording module 4 is used to submit the data digest, digital signature and data index, and access permission information to the blockchain network for on-chain recording, and to establish an off-chain mapping relationship with the blockchain mapping area.

[0089] Traffic data collection and transmission module 5 transmits traffic data based on the blockchain network and off-chain mapping relationship.

[0090] Furthermore, the traffic data collection transmission module 5 is used to perform the following steps:

[0091] The access, authorization, and calling behavior of the traffic collection data are verified by a smart contract deployed in a blockchain network; when the data access party passes the permission management verification, the off-chain data is called through data indexing and consistency verification is performed based on on-chain hashing, and the traffic transmission data is obtained after passing the consistency verification.

[0092] Further, the traffic collection dataset obtaining module 1 is configured to perform the following steps:

[0093] The traffic collection dataset includes one or more of vehicle position, vehicle speed, vehicle direction, road identification information, traffic light status, and surrounding vehicle identification information.

[0094] Further, the traffic collection dataset partitioning module 2 is configured to perform the following steps:

[0095] A traffic event library is obtained, and traffic events are classified by level according to the influence range, timeliness, and involved subject level of the traffic event library; event core influence data and auxiliary influence data are analyzed for traffic events classified by level, a mapping relationship between the traffic events and the traffic collection dataset is established, and division and identification features of the core data and the auxiliary data of each traffic event are established; the encryption data partitioning rules are set according to the division and identification features of the core data and the auxiliary data, wherein the core data corresponds to a blockchain processing area and the auxiliary data corresponds to a blockchain mapping area.

[0096] Further, the traffic collection dataset partitioning module 2 is configured to perform the following steps:

[0097] The cross relationship dimension of the core influence data and the auxiliary influence data is set according to the level, wherein the higher the level of the traffic event, the higher the cross relationship dimension; the core influence data and the auxiliary influence data relationship of the traffic event is analyzed according to the cross relationship dimension, and the extraction rules of the core influence data and the auxiliary influence data are determined.

[0098] Further, the blockchain network recording module 4 is configured to perform the following steps:

[0099] The auxiliary data is stored in an off-chain distributed database through encryption, and a unique mapping relationship between the on-chain data indexing and the auxiliary data path is established, which is used to call the off-chain data after the smart contract verification.

[0100] Further, the traffic collection dataset transmission module 5 is configured to perform the following steps:

[0101] When the access request is initiated, the current visitor identity and data access permission are compared through the smart contract, and the calling behavior authorization matching judgment is performed in combination with the access behavior, wherein the smart contract includes a multi-factor access strategy matching mechanism of access identity, data access permission and access history behavior; when the matching is successful, the off-chain auxiliary data and the on-chain core data are allowed to be verified for consistency, and the access behavior is called to be written into the blockchain network to form an audit log for subsequent data tracking and backtracking analysis.

[0102] The traffic data security transmission system based on the blockchain provided by the embodiment of the application can execute the traffic data security transmission method based on the blockchain provided by any embodiment of the application, and has the corresponding function modules and beneficial effects of the execution method.

[0103] Although the present application makes various references to certain modules in the system according to the embodiments of the present application, however, any number of different modules can be used and run on the user terminal and / or server, and each unit and module included is only divided according to the functional logic, but is not limited to the above division, as long as the corresponding functions can be realized; in addition, the specific names of each functional unit are only for easy mutual distinction, and do not limit the protection scope of the present application.

[0104] The above specific embodiments do not constitute a limitation on the protection scope of the present application. Those skilled in the art should understand that various modifications, combinations and substitutions can be made according to design requirements and other factors. Any modification, equivalent replacement and improvement made within the spirit and principles of the present application should be included in the protection scope of the present application. In some cases, the actions or steps described in the present application can be executed in an order different from that in the embodiments and still achieve the desired results. In addition, the processes depicted in the drawings do not necessarily require the specific order or continuous order shown to achieve the desired results. In some embodiments, multi-task processing and parallel processing are possible or can be advantageous.

Claims

1.A blockchain-based method for secure transmission of traffic data, characterized in that, The method comprises the following steps: connecting a traffic data monitoring network, obtaining a traffic collection data set, and establishing an association between the traffic collection data set and a traffic event; According to the association, configure the encryption data partition rule, identify the partition of the traffic collection data set, obtain the blockchain processing area and the blockchain mapping area; Based on the blockchain processing area, the data positioning of the traffic collection data set is carried out, the target collection data is extracted for hash processing, the data digest is generated, and the private key used by the data source node is digitally signed; The data digest, digital signature, data index and access permission information are submitted to the blockchain network for on-chain recording, and the off-chain mapping relationship with the blockchain mapping area is established; Based on the blockchain network and the off-chain mapping relationship, the traffic collection data set is transmitted. 2.The blockchain-based traffic data secure transmission method of claim 1, wherein, Based on the blockchain network and the off-chain mapping relationship, the traffic collection data set is transmitted, and then comprises: Through the smart contract deployed in the blockchain network, the access, authorization and calling behavior of the traffic collection data are verified by the permission management; When the data access party passes the permission management verification, the off-chain data is called through the data index and the consistency is verified based on the on-chain hash, and the traffic transmission data is obtained after the consistency verification. 3.The blockchain-based traffic data secure transmission method of claim 1, wherein, The traffic collection data set comprises one or more of vehicle position, vehicle speed, vehicle direction, road identification information, traffic light state and surrounding vehicle identification information. 4.The blockchain-based traffic data secure transmission method of claim 1, wherein, Before the association, the encryption data partition rule is configured, and the traffic collection data set is identified and partitioned, which comprises: Obtain the traffic event library, classify the traffic events according to the influence range, timeliness and involved subject level of the traffic event library; For each level of classified traffic event, the event core influence data and auxiliary influence data are analyzed, the mapping relationship between the traffic event and the traffic collection data set is established, and the division and identification characteristics of the core data and auxiliary data of each traffic event are established; According to the division and identification characteristics of the core data and auxiliary data, the encryption data partition rule is set, wherein the core data corresponds to the blockchain processing area, and the auxiliary data corresponds to the blockchain mapping area. 5.The blockchain-based traffic data secure transmission method of claim 4, wherein, For each level of classified traffic event, the event core influence data and auxiliary influence data are analyzed, which comprises: According to the level, the cross relationship dimension of the core influence data and the auxiliary influence data is set, wherein the higher the level of the traffic event, the higher the cross relationship dimension; According to the cross relationship dimension, the relationship between the core influence data and the auxiliary influence data of the traffic event is analyzed, and the extraction rule of the core influence data and the auxiliary influence data is determined. 6.The blockchain-based traffic data secure transmission method of claim 4, wherein, The off-chain mapping relationship with the blockchain mapping area comprises: The auxiliary data is stored in the off-chain distributed database by encryption, and the unique mapping relationship between the on-chain data index and the auxiliary data path is established, which is used to call the off-chain data after the smart contract verification. 7.The blockchain-based traffic data secure transmission method of claim 2, wherein, Through the smart contract deployed in the blockchain network, the access, authorization and calling behavior of the traffic collection data are verified by the permission management, which comprises: When the access request is initiated, the current visitor identity and data access setting permissions are compared through the smart contract, and the calling behavior authorization matching judgment is performed in combination with the access behavior, wherein the smart contract includes a multi-factor access strategy matching mechanism of access identity, data access permission and access history behavior; When the matching is successful, the off-chain auxiliary data is allowed to be consistent with the on-chain core data, and the access behavior is called to be written into the blockchain network to form an audit log for subsequent data tracking and backtracking analysis. 8.A blockchain-based traffic data secure transmission system, characterized in that, A traffic data security transmission method based on a blockchain for implementing any one of claims 1-7, the system comprising: a traffic collection dataset acquisition module for connecting a traffic data monitoring network, obtaining a traffic collection dataset, and establishing an association relationship between the traffic collection dataset and a traffic event; a traffic collection dataset partitioning module for configuring an encrypted data partitioning rule according to the association relationship, identifying and partitioning the traffic collection dataset, and obtaining a blockchain processing area and a blockchain mapping area; a traffic collection dataset positioning module for performing data positioning on the traffic collection dataset based on the blockchain processing area, extracting target collection data for hash processing, generating a data digest, and digitally signing the data digest with a private key used by a data source node; a blockchain network recording module for submitting the data digest, digital signature, data index, and access permission information to the blockchain network for on-chain recording, and establishing an off-chain mapping relationship with the blockchain mapping area; a traffic collection dataset transmission module for transmitting the traffic collection dataset based on the blockchain network and the off-chain mapping relationship.

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