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CN-122019668-A - Data sharing method based on block chain double-chain architecture

CN122019668ACN 122019668 ACN122019668 ACN 122019668ACN-122019668-A

Abstract

The invention discloses a data sharing method based on a blockchain double-chain architecture, which comprises the steps of building a double-chain blockchain network architecture comprising an emergency transaction chain and a common transaction chain based on a vehicle-mounted unit OBU and a road side unit RSU, dividing corresponding account books, collecting vehicle networking service data by the OBU and shunting the vehicle to the corresponding transaction pool according to types, calculating an emergency index for each transaction entering the emergency transaction chain, calculating a global reputation value of a node by adopting a multi-source multi-weight subjective logic reputation model, building a high reputation consensus committee and executing emergency data optimization PBFT consensus, synchronously executing common data standard PBFT consensus by legal nodes, and realizing data classification efficient sharing by parallel cooperation of the emergency transaction chain and the common transaction chain. The data sharing method based on the block chain double-chain architecture solves the problems of high emergency data transmission delay and lack of effective prevention of malicious interference of internal nodes in the existing internet of vehicles data sharing technology.

Inventors

  • FAN XIUMEI
  • GU CHAOYU

Assignees

  • 西安智行畅嘉网络科技有限公司

Dates

Publication Date
20260512
Application Date
20260130

Claims (10)

  1. 1. The data sharing method based on the block chain double-chain architecture is characterized by comprising the following steps of: step 1, building a double-chain block chain network architecture containing an emergency transaction chain and a common transaction chain based on an on-board unit (OBU) and a Road Side Unit (RSU) of a vehicle, and dividing a corresponding account book; step 2, the vehicle collects the service data of the internet of vehicles through the OBU and shunts the service data to the corresponding transaction pool according to the type; Step3, calculating an emergency index for each transaction entering an emergency transaction chain; calculating the global reputation value of the node by adopting a multi-source multi-weight subjective logic reputation model; And 5, constructing a high credit consensus committee, executing emergency data optimization PBFT consensus, executing common data standard PBFT consensus by legal nodes synchronously, and realizing data classification and high-efficiency sharing through parallel cooperation of an emergency transaction chain and a common transaction chain.
  2. 2. The method for data sharing based on a blockchain double-chain architecture as in claim 1, wherein the urgency index in step 3 is calculated by the following formula: (1) In the formula, Representing an emergency degree index and measuring the final emergency degree of the transaction; indicating that the vehicle has accumulated the number of emergency transactions applied during the present consensus period, An impact weight representing the number of applied urgent transactions; Representing the vehicle expectation of the transaction urgency, and calculating by the formula (2) to reflect the transaction delay sensitivity degree: (2) In the formula, Indicating the average delay of the emergency transaction chain for confirming a block; The expected time delay of the transaction, namely the maximum tolerable time delay for the transaction to complete consensus, is preset by the transaction type; representing the time of generation of the transaction, i.e., the timestamp at which the vehicle generated the transaction; the time stamp representing the transmission of the transaction from the vehicle to receipt by the roadside unit reflects the transaction transmission delay.
  3. 3. The method for sharing data based on the blockchain double-chain architecture as in claim 1, wherein step 4 specifically comprises the steps of: setting different priority coefficients for different transaction types, and calculating basic parameters including familiarity, direct opinion timeliness and track similarity, and providing input basis for reputation evaluation; Step 4.2, generating and combining direct opinions based on direct interaction behaviors among nodes; step 4.3, deriving and combining indirect opinions based on indirect interaction paths among nodes; And 4.4, merging the direct opinion with the indirect opinion and outputting a global reputation value.
  4. 4. The method for data sharing based on blockchain double-chain architecture as in claim 3, wherein step 4.1 specifically comprises: firstly, setting different priority coefficients for different transaction types for weighting processing in subsequent credit value calculation, and calculating according to the following formula: (3) In the formula, Representing a different type of transaction, An emergency transaction is indicated and a transaction is made, Representing a non-urgent transaction, Representing a priority coefficient associated with the transaction type; secondly, the familiarity, the direct opinion timeliness and the track similarity are calculated respectively, and specifically: Familiarity is recorded as Calculated by the following formula (4): (4) In the formula, Indicating that the vehicle is within a set time window And a vehicle Total number of actual interactions between occurrences, vehicle Vehicle as data user As a data provider; Representing a vehicle Average interaction count with other vehicle nodes; Representation and vehicle All vehicle sets that interact; Representing a collection The number of vehicles in the middle; the timeliness of the direct opinion is recorded as Calculated by the following formula (5): (5) In the formula, Representing a vehicle Time to complete the transaction; representing a vehicle The point in time at which the data to be evaluated is uploaded, Representing the time-dependent amplification factor; Representing an attenuation index; And Is the time-dependent amplification factor and decay index for the emergency data, And Is directed at the time-efficiency amplification coefficient and the attenuation index of common data, meets the following requirements , ; The track similarity is recorded as Calculated by the following formula (6): (6) In the formula, Weights representing speed and direction similarity; Representing the speed similarity; The similarity of the directions is expressed and calculated by the following formula (7): (7) In the formula, Representing the number of trace points involved in the comparison, 、 Respectively represent vehicles And a vehicle Characteristic values at the kth trace point.
  5. 5. The method for data sharing based on a blockchain double-chain architecture of claim 4, the method is characterized in that the step 4.2 specifically comprises the following steps: firstly, the familiarity, the timeliness of direct opinion and the track similarity are accumulated according to weights, and the urgent interaction duty ratio is combined And emergency transaction weighting coefficients to obtain the vehicle And a vehicle Is the direct opinion weight of (2) The expression is as follows: (8) (9) In the formula, 、 、 Representing familiarity Timeliness of direct opinion Similarity to track Corresponding weight satisfies ; Indicating the immediate opinion weight of emergency or non-emergency, Representing a vehicle And a vehicle The emergency interaction duty cycle between them, Representing the weighting coefficients of the emergency transactions, Representing an emergency duty cycle weighting parameter; Secondly, calculating the effectiveness of abnormal data by combining the growth curve function of the Pearl model The normal data validity is expressed as The calculation is performed according to the following formula: (10) In the formula, Representing an adjustment factor, the urgent data and the non-urgent data being different, X representing a set of all vehicles that interacted with vehicle j, Any vehicle in the representation set For vehicles Is a direct weight of (2); Representing the amount of abnormal data observed by vehicle x in the interaction with vehicle j; Representing the weighted abnormal data average value; The number of times of normal data and the number of times of abnormal data are taken as input, and the effectiveness weighting of the normal data and the abnormal data is completed by combining positive/negative evidence amplification coefficients, wherein the effectiveness weighting is represented as follows: (11) In the formula, Representing a vehicle And a vehicle The number of times that normal data occurs in between, Representing the amount of urgent and non-urgent data between vehicles, respectively; Representing a vehicle And a vehicle The number of times of occurrence of the abnormal data therebetween, And the same is done; Representing positive evidence magnification factor, emergency generally , Representing negative evidence magnification factor, emergency generally ; Subsequently, based on the evidence mapping operator in the subjective logic SL trust model, the direct opinion of vehicle i on vehicle j is calculated by the following formula (12): (12) In the formula, Representing the trust degree of the vehicle i on the vehicle j; representing the degree of distrust of the vehicle i on the vehicle j; representing uncertainty of vehicle i to vehicle j; the fruit breaking property of the emergency transaction opinion is enhanced; representing the urgent evidence duty cycle of statistics in the window; Finally, the opinions of the set X of all vehicles interacted with the vehicle j in the period are weighted and integrated to obtain a direct opinion combination, which is expressed as follows: (13) In the formula, 、 、 The trust, the distrust and the uncertainty of the direct opinion of the system on the vehicle j are indicated.
  6. 6. The method for data sharing based on a blockchain double-chain architecture of claim 5, the method is characterized in that the step 4.3 specifically comprises the following steps: Firstly, searching all indirect paths from a source node A to a target node C in a vehicle interaction graph by adopting a depth-first search algorithm, and calculating indirect opinion of a single indirect path based on a paste operator of a subjective logic SL trust model, wherein the indirect opinion is expressed as follows: (14) wherein B represents an intermediate node and is obtained by a depth-first search algorithm; 、 、 The trust degree, the untrustworthiness and the uncertainty of the direct opinion of the node A to the intermediate node B are represented; 、 、 representing the trust, the uncertainty and the uncertainty of the direct opinion of the intermediate node B to the node C; 、 、 the trust degree, the untrustworthiness and the uncertainty of the indirect opinion of the node A and the intermediate node B to the node C are represented; Secondly, for the path with urgent transaction, the weight of the path is amplified according to the path priority coefficient, and the weight is expressed as follows: (15) (16) In the formula, Represents a path priority coefficient, m represents a middle node satisfying a sequence relationship, Representing the weight coefficient of the emergency data, Indicating whether there is an urgent transaction on the path; path weights are calculated, expressed as follows: (17) In the formula, When the node A evaluates the target node C through the intermediate node m, the weight of the indirect path decays along with the increase of the path transfer times; representing a vehicle node set meeting the sequence relation obtained by an indirect opinion path search algorithm; Representing the direct opinion weight of node m to node C; Finally, a weighted average method is adopted to integrate indirect opinions with more indirect paths, and the indirect opinion combination of the system to the target node C is obtained and expressed as follows: (18) In the formula, 、 、 Respectively representing the trust degree, the distrust degree and the uncertainty of the indirect opinion of the system comprehensive to the target vehicle node C.
  7. 7. The method for data sharing based on a blockchain double-chain architecture of claim 6, the method is characterized in that the step 4.4 is specifically as follows: firstly, merging direct opinion combination and indirect opinion combination to obtain final system opinion, which is expressed as follows: (19) In the formula, The final degree of trust is indicated as such, Indicating the final degree of distrust, K represents a normalization coefficient; Based on the fused final trust degree and final untrustworthiness, calculating a global reputation value The expression is as follows: (20) In the formula, A conversion coefficient representing the uncertainty.
  8. 8. The method for data sharing based on the blockchain double-chain architecture of claim 1, wherein the constructing the high reputation consensus committee in step 5 specifically comprises: the global reputation values of all nodes are ordered in a descending order, and p nodes before the ordering are selected to form a high reputation consensus committee to replace all nodes to participate in optimization PBFT consensus; The emergency data optimization PBFT is executed in step 5, and specifically includes the following sub-steps: Step 5.2.1, selecting a master node and packaging blocks, wherein the node with the highest reputation value in the high reputation consensus committee serves as the master node, and the master node selects the emergency block with the highest urgency according to the urgency index sequencing result of the packaged emergency transaction block and broadcasts the block to other verification nodes in the high reputation consensus committee; step 5.2.2, node local verification and voting feedback, wherein after each verification node receives the candidate emergency block, the block structural integrity and the transaction validity are locally verified, and voting information agreed by the signature is fed back to the main node after verification; Step 5.2.3, judging the consensus result, namely when the master node cumulatively receives not less than f+1 identical consent tickets, wherein f is a Bayesian fault-tolerant parameter, f is less than p/3, judging that the consensus is successful, and recording the block into an emergency data block chain account book; And 5.2.4, broadcasting and uplink the consensus result, namely broadcasting a successful consensus result to the whole network by the master node, and completing an emergency data uplink flow.
  9. 9. The data sharing method based on the blockchain double-chain architecture of claim 8, wherein the high reputation consensus committee is dynamically optimized, specifically: The round limit of the master node is that the same node continuously acts as the round of the master node and does not exceed a preset value H, and after the role of the master node is completed, the same node is not acted as the master node in the subsequent H rounds of emergency consensus; And updating the committee members, namely reevaluating based on the global reputation value of the latest node after processing T urgent blocks, selecting a new palace reputation node to replace the member with the lowered global reputation value, and maintaining the reliability of the high reputation consensus committee.
  10. 10. The method for data sharing based on the blockchain double-chain architecture as in claim 1, wherein in step 5, the common data standard PBFT consensus is executed by the legal node, specifically: The method comprises the steps of screening nodes with the global reputation value reaching a basic threshold value of the whole network as legal nodes, taking the nodes as common data consensus participation nodes, taking all legal nodes as common data consensus participation standard PBFT, verifying, voting and accounting common data transaction according to the conventional block size and the block outlet speed, and recording common data blocks into a common data block chain account book after the whole network consensus is achieved, so that the consistency and the reliability of common data sharing are ensured.

Description

Data sharing method based on block chain double-chain architecture Technical Field The invention belongs to the technical field of Internet of vehicles and block chain data sharing, and particularly relates to a data sharing method based on a block chain double-chain architecture. Background In the Internet of vehicles, massive driving data and traffic state data can be generated in real time, and sharing of the data is helpful for improving traffic efficiency and driving safety. However, the traditional centralized internet of vehicles data management mode has the problems that data is easy to tamper, user privacy is revealed, trust is lost and the like. The blockchain technology is used as a decentralized, tamper-proof and traceable distributed account book, and provides a new solution for the data sharing of the Internet of vehicles. However, due to the huge data volume and high dynamic node in the internet of vehicles, if all data are recorded on a single blockchain indiscriminately, the storage and consensus load on the chain may be too high, and the requirement of low-delay processing of urgent data is difficult to meet. In the prior art, some researches attempt to improve the efficiency and reliability of internet of vehicles data sharing by improving a blockchain consensus algorithm. For example, a scheme is adopted to reduce the node scale participating in the consensus based on PBFT committee consensus, so that the communication complexity is reduced, the confirmation speed is improved, and a scheme is also adopted to introduce a reputation evaluation mechanism to reject bad behavior nodes from the consensus process, so that the capability of the system for resisting internal attacks is enhanced. However, the existing scheme still has the defects that firstly, the existing blockchain consensus is difficult to process in time and preferentially in the face of emergency data such as traffic accident alarms, emergency information can be submerged in the consensus processing of a large amount of common information to cause too high delay, and secondly, the traditional scheme lacks fine and effective constraint on malicious nodes in the Internet of vehicles, and an attacker can participate in the consensus by frequently broadcasting false emergency messages or falsified identities to interfere the normal operation of the system. In view of the above-mentioned shortcomings, a new method for sharing internet of vehicles data is needed, which not only can ensure quick and reliable uplink of emergency data, but also can prevent misuse of malicious nodes. Disclosure of Invention The invention aims to provide a data sharing method based on a block chain double-chain architecture, which solves the problems of high emergency data transmission delay and lack of effective prevention of malicious interference of internal nodes in the existing internet of vehicles data sharing technology. The technical scheme adopted by the invention is that the data sharing method based on the block chain double-chain architecture comprises the following steps: step 1, building a double-chain block chain network architecture containing an emergency transaction chain and a common transaction chain based on an on-board unit (OBU) and a Road Side Unit (RSU) of a vehicle, and dividing a corresponding account book; step 2, the vehicle collects the service data of the internet of vehicles through the OBU and shunts the service data to the corresponding transaction pool according to the type; Step3, calculating an emergency index for each transaction entering an emergency transaction chain; calculating the global reputation value of the node by adopting a multi-source multi-weight subjective logic reputation model; And 5, constructing a high credit consensus committee, executing emergency data optimization PBFT consensus, executing common data standard PBFT consensus by legal nodes synchronously, and realizing data classification and high-efficiency sharing through parallel cooperation of an emergency transaction chain and a common transaction chain. The invention is also characterized in that: in the step 3, the emergency index is calculated by the following formula: (1) In the formula, Representing an emergency degree index and measuring the final emergency degree of the transaction; indicating that the vehicle has accumulated the number of emergency transactions applied during the present consensus period, An impact weight representing the number of applied urgent transactions; Representing the vehicle expectation of the transaction urgency, and calculating by the formula (2) to reflect the transaction delay sensitivity degree: (2) In the formula, Indicating the average delay of the emergency transaction chain for confirming a block; The expected time delay of the transaction, namely the maximum tolerable time delay for the transaction to complete consensus, is preset by the transaction type; representing the time of generation of t