CN117715036A

CN117715036A - Block chain-based Internet of vehicles identity registration method, device, equipment and medium

Info

Publication number: CN117715036A
Application number: CN202311429180.0A
Authority: CN
Inventors: 王绍刚
Original assignee: Industrial and Commercial Bank of China Ltd ICBC; ICBC Technology Co Ltd
Current assignee: Industrial and Commercial Bank of China Ltd ICBC; ICBC Technology Co Ltd
Priority date: 2023-10-31
Filing date: 2023-10-31
Publication date: 2024-03-15

Abstract

The application relates to a blockchain-based Internet of vehicles identity registration method, a blockchain-based Internet of vehicles identity registration device, computer equipment and a storage medium. The method comprises the steps of determining a plurality of third party data sources corresponding to user identifications, determining a plurality of trusted third party data sources according to the consensus result of a vehicle networking block chain on the plurality of third party data sources, inputting user data to be identified in the trusted third party data sources into a trained prediction model to obtain a trusted identification result of the prediction model based on the user data to be identified, and registering a user to the vehicle networking block chain according to identity information of the user when the trusted identification result is trusted. Compared with the traditional mode of directly registering the Internet of vehicles by the user, the method and the system have the advantages that the trusted data source is determined from the plurality of third-party data sources, the data is obtained from the trusted data source, the credibility of the user is predicted by combining the prediction model and the data of the trusted data source, and the user is allowed to register and be linked when the user is credible, so that the safety of the Internet of vehicles identity registration is improved.

Description

Block chain-based Internet of vehicles identity registration method, device, equipment and medium

Technical Field

The present disclosure relates to the field of blockchain technologies, and in particular, to a blockchain-based internet of vehicles identity registration method, apparatus, computer device, storage medium, and computer program product.

Background

The internet of vehicles has been rapidly developed in recent years as an important component of intelligent traffic and has gradually become the focus of "new infrastructure". With the rapid development of the internet of vehicles technology, road vehicles, road side equipment, cloud control platforms, people and other traffic participants form a complex communication network with multiple main bodies, high frequency and wide connection. The participants of the Internet of vehicles are unfamiliar with each other, so that the assurance of the credibility of the participants of the Internet of vehicles is an important measure for ensuring the normal operation of the Internet of vehicles. However, an illegal user exists in the internet of vehicles, and the illegal user attacks other users or transmits malicious information and other behaviors.

Therefore, the existing internet of vehicles has the defect of lower safety.

Disclosure of Invention

In view of the foregoing, it is desirable to provide a blockchain-based internet of vehicles identity registration method, apparatus, computer device, computer readable storage medium, and computer program product that can improve internet of vehicles security.

In a first aspect, the present application provides a blockchain-based internet of vehicles identity registration method, the method comprising:

acquiring a registration request of a user to be registered for a block chain of the Internet of vehicles; the registration request carries the user identification and the identity information of the user to be registered;

determining a plurality of corresponding third party data sources according to the user identification, and determining a plurality of trusted third party data sources according to the consensus result of the Internet of vehicles block chain on the plurality of third party data sources;

obtaining user data to be identified corresponding to the user identification according to the plurality of trusted third party data sources, inputting the user data to be identified into a trained prediction model, and obtaining a trusted identification result output by the prediction model based on the user data to be identified;

and if the trusted identification result is trusted, registering the user to be registered to the Internet of vehicles blockchain according to the identity information.

In one embodiment, the determining a corresponding plurality of third party data sources according to the user identification includes:

determining the user type corresponding to the user to be registered according to the user identification;

and acquiring a plurality of third party data sources corresponding to the user type.

In one embodiment, the determining a plurality of trusted third party data sources according to the consensus result of the internet of vehicles blockchain on the plurality of third party data sources includes:

performing consensus voting on the plurality of third party data sources through a plurality of distributed predictors in the Internet of vehicles block chain to obtain a plurality of credible grade evaluation values corresponding to the plurality of third party data sources;

and determining a plurality of trusted third party data sources from the plurality of third party data sources according to comparison results of the plurality of trusted grade evaluation values corresponding to the plurality of third party data sources and a preset trusted grade evaluation value threshold.

In one embodiment, the method further comprises:

acquiring user sample data and a trusted identification sample result corresponding to the user identifier;

aiming at a user type corresponding to each user identifier, acquiring a plurality of candidate prediction models to be trained corresponding to the user type; wherein, the prediction algorithm corresponding to each candidate prediction model is different;

inputting the user sample data into each candidate prediction model to obtain a candidate credible identification prediction result output by the candidate prediction model through a corresponding prediction algorithm and the user sample data; according to the similarity comparison result of the candidate credible recognition result and the credible recognition sample result, adjusting model parameters of the candidate prediction model until a preset training ending condition is met, and obtaining a trained candidate prediction model;

Respectively inputting user sample data corresponding to the user type into a plurality of trained candidate prediction models, and obtaining a plurality of candidate credible recognition results which are respectively output by the plurality of candidate prediction models based on the user sample data;

and obtaining a target candidate trusted identification result with highest similarity with the trusted identification sample result, and obtaining a trained prediction model corresponding to the user type according to a candidate prediction model corresponding to the target candidate trusted identification result.

In one embodiment, the inputting the user data to be identified into a trained predictive model includes:

inputting the user data to be identified into a prediction model corresponding to the user type of the user identification, obtaining a corresponding trusted identification value by the prediction model based on the user data to be identified, and outputting a trusted identification result according to the trusted identification value.

In one embodiment, the registering the user to be registered to the internet of vehicles blockchain according to the identity information includes:

obtaining a public key corresponding to the user identifier;

generating a blockchain certificate according to the identity information and the public key, and carrying out hash operation on the blockchain certificate to obtain a corresponding hash value;

And generating a block corresponding to the blockchain certificate in the Internet of vehicles blockchain, and storing the blockchain certificate and the hash value into the block to obtain the registered user.

In one embodiment, after the registering the user to be registered with the internet of vehicles blockchain according to the identity information, the method further includes:

and generating a registration result corresponding to the registered user according to the block corresponding to the blockchain certificate in the Internet of vehicles blockchain, and returning the registration result to the registered user.

In a second aspect, the present application provides a blockchain-based internet of vehicles identity registration device, the device comprising:

the acquisition module is used for acquiring a registration request of a user to be registered for the block chain of the Internet of vehicles; the registration request carries the user identification and the identity information of the user to be registered;

the determining module is used for determining a plurality of corresponding third party data sources according to the user identification, and determining a plurality of trusted third party data sources according to the consensus result of the Internet of vehicles block chain on the plurality of third party data sources;

the identification module is used for obtaining user data to be identified corresponding to the user identification according to the plurality of trusted third party data sources, inputting the user data to be identified into a trained prediction model, and obtaining a trusted identification result output by the prediction model based on the user data to be identified;

And the registration module is used for registering the user to be registered to the Internet of vehicles blockchain according to the identity information if the trusted identification result is trusted.

In a third aspect, the present application provides a computer device comprising a memory storing a computer program and a processor implementing the steps of the method described above when the processor executes the computer program.

In a fourth aspect, the present application provides a computer readable storage medium having stored thereon a computer program which when executed by a processor performs the steps of the method described above.

In a fifth aspect, the present application provides a computer program product comprising a computer program which, when executed by a processor, implements the steps of the method described above.

According to the blockchain-based Internet of vehicles identity registration method, device, computer equipment, storage medium and computer program product, the corresponding multiple third party data sources are determined according to the user identification, the multiple trusted third party data sources are determined according to the consensus result of the Internet of vehicles blockchain on the multiple third party data sources, user data to be identified in the trusted third party data sources are input into the trained prediction model, the trusted identification result of the prediction model based on the input of the user data to be identified is obtained, and when the trusted identification result is trusted, the user is registered to the Internet of vehicles blockchain according to the identity information of the user. Compared with the traditional mode of directly registering the Internet of vehicles by the user, the method and the system have the advantages that the trusted data source is determined from the plurality of third-party data sources, the data is obtained from the trusted data source, the credibility of the user is predicted by combining the prediction model and the data of the trusted data source, and the user is allowed to register and be linked when the user is credible, so that the safety of the Internet of vehicles identity registration is improved.

Drawings

FIG. 1 is an application environment diagram of a blockchain-based Internet of vehicles identity registration method in one embodiment;

FIG. 2 is a flow diagram of a blockchain-based Internet of vehicles identity registration method in one embodiment;

FIG. 3 is a flow chart of a third party data source determination step in one embodiment;

FIG. 4 is a flowchart of a blockchain-based Internet of vehicles identity registration method in another embodiment;

FIG. 5 is a schematic diagram of a block chain architecture of a blockchain-based Internet of vehicles in one embodiment;

FIG. 6 is a block diagram of an architecture of a blockchain-based Internet of vehicles identity registration device in one embodiment;

fig. 7 is an internal structural diagram of a computer device in one embodiment.

Detailed Description

In order to make the objects, technical solutions and advantages of the present application more apparent, the present application will be further described in detail with reference to the accompanying drawings and examples. It should be understood that the specific embodiments described herein are for purposes of illustration only and are not intended to limit the present application.

The blockchain-based Internet of vehicles identity registration method provided by the embodiment of the application can be applied to an application environment shown in fig. 1. The terminal communicates with a management end in the block chain of the Internet of vehicles through a network. The data storage system can store data which the management end needs to process. The terminal held by the user to be registered can send a registration request by the management end, so that the management end calls a corresponding node in the Internet of vehicles blockchain to process the registration request according to the registration request, and allows the user to register in the Internet of vehicles blockchain when the user to be registered is identified to be credible. The terminal can be, but not limited to, various personal computers, notebook computers, smart phones, tablet computers and internet of things equipment, and the internet of things equipment can be intelligent vehicle-mounted equipment and the like. The management end can be implemented by a stand-alone server or a server cluster formed by a plurality of servers.

In one embodiment, as shown in fig. 2, a blockchain-based internet of vehicles identity registration method is provided, and the method is applied to the management end in fig. 1 for illustration, and includes the following steps:

step S202, acquiring a registration request of a user to be registered for a block chain of the Internet of vehicles; the registration request carries a user identification and identity information of the user to be registered.

The internet of vehicles refers to a communication network including multiple types of participants as a main body, for example, a communication network including traffic participants such as road vehicles, road side equipment, cloud control platforms, people and the like. The functions of mass data interaction, inter-vehicle communication, user identity registration and the like can be provided for the Internet of vehicles environment through the Internet of vehicles blockchain. The Internet of vehicles blockchain can adopt a distributed system, so that a reliable information transmission environment is provided for vehicles. The user may submit a registration request through the terminal. The registration request may include the user identifier of the user to be registered, and may further include identity information of the user to be registered. Therefore, the management end of the block chain of the Internet of vehicles can acquire a registration request sent by a user to be registered. And performing trusted identification and registration uplink on the user to be registered according to the registration request.

The users in the Internet of vehicles are not in mutual trust relationship, so that the users cannot trust the authenticity of information sent by other users on the premise of no safety protection measures, and the data sharing in the Internet of vehicles is not facilitated, and the development of the Internet of vehicles is hindered. In order to ensure that users in the Internet of vehicles are trusted, the management end needs to carry out strict examination on registered users, so that the joining of malicious users and the damage of safety communication among the users of the Internet of vehicles are avoided. When the user registers in the system with the trusted identity, the user is allowed to carry out the next operations such as communication, data sharing and the like, thereby being beneficial to establishing a safe and trusted communication environment in the Internet of vehicles system and improving the safe and trusted sharing of information.

Step S204, determining a plurality of corresponding third party data sources according to the user identification, and determining a plurality of trusted third party data sources according to the consensus result of the block chain of the Internet of vehicles on the plurality of third party data sources.

In order to perform trusted verification on a user to be registered, a management end needs to acquire trusted data of the user from a trusted third party data source. The trusted third party data source can be determined from a plurality of third party data sources by the management end. For example, the management end determines a plurality of corresponding third party data sources according to the user identification. The third party data source may be an external data source outside the internet of vehicles blockchain, and the user identifier may be used to identify a type of the user. User identities of different registration types may correspond to different third party data sources.

That is, the user types of the users to be registered can be various, and the management end can determine the third party data source based on the user types. For example, in one embodiment, the management end may determine, according to the user identifier, a user type corresponding to the user to be registered, and obtain a plurality of third party data sources corresponding to the user type. Specifically, as shown in fig. 3, fig. 3 is a schematic flow chart of a third party data source determining step in one embodiment. Participants in the above-described internet of vehicles include, but are not limited to, people, vehicles, roadside units, traffic authorities, and the like. In this embodiment, the driver, the vehicle and the road side unit are mainly used, and the management end includes a plurality of distributed predictor nodes. Taking the user to be registered as a driver as an example, the management end can acquire driving habit, driving behavior, credit reputation and other influencing factors corresponding to the user of the driver type from the external third-party data sources as a plurality of third-party data sources. Wherein the influence factors corresponding to different registration types are also different.

After the management end determines a plurality of third party data sources corresponding to the user types, the third party data sources can be subjected to consensus voting through the Internet of vehicles block chain, so that a consensus result of the Internet of vehicles block chain on the third party data sources is obtained. Therefore, the management end can determine a plurality of trusted third party data sources from a plurality of third party data sources based on the consensus result.

Step S206, obtaining user data to be identified corresponding to the user identification according to the plurality of trusted third party data sources, inputting the user data to be identified into a trained prediction model, and obtaining a trusted identification result output by the prediction model based on the user data to be identified.

After determining the plurality of trusted third party data sources corresponding to the user to be registered, the management end can acquire user data to be identified corresponding to the user identifier from the determined plurality of trusted third party data sources based on the identifier of the user. The management end can input the user data to be identified into the trained prediction model, so that the prediction model can output a corresponding trusted identification result based on the user data to be identified. The above-mentioned trusted identification result may include an evaluation of the credibility of the user to be registered by the prediction model, for example, a credibility evaluation value of the user to be registered by the prediction model. The prediction model may be a prediction model corresponding to a user type of the user to be registered. For example, the management end may train a plurality of candidate prediction models by using a plurality of algorithms, and select a candidate prediction model with the best reliable recognition result for each user type from the candidate prediction models as a trained prediction model corresponding to each user type.

And step S208, if the trusted identification result is trusted, registering the user to be registered to the Internet of vehicles blockchain according to the identity information.

The credible recognition result represents the credibility of the user to be registered, which is output by the prediction model based on the user data to be recognized. The management end can judge whether the user to be registered is credible or not based on the credible identification result. For example, the trusted identification result may be in the form of a numerical value, and the management end determines whether the user to be registered is trusted by detecting a specific numerical value of the trusted identification result. If the management end determines that the user to be registered is trusted based on the trusted identification result, the management end can determine that the user to be registered allows the login uplink. When the management end determines that the user to be registered allows the login uplink, the user to be registered can be registered to the Internet of vehicles blockchain according to the identity information of the user to be registered, and the registered user is obtained. The registered user can correspond to a corresponding block in the Internet of vehicles block chain, and the block stores information such as user data of the user. After the user is registered in the Internet of vehicles blockchain, information interaction can be performed between the Internet of vehicles blockchain and other registered users.

In the blockchain-based internet of vehicles identity registration method, a plurality of corresponding third party data sources are determined according to the user identification, a plurality of reliable third party data sources are determined according to the consensus result of the internet of vehicles blockchain on the plurality of third party data sources, user data to be identified in the reliable third party data sources are input into a trained prediction model, a reliable identification result of the prediction model based on the user data to be identified is obtained, and when the reliable identification result is reliable, the user is registered to the internet of vehicles blockchain according to the identity information of the user. Compared with the traditional mode of directly registering the Internet of vehicles by the user, the method and the system have the advantages that the trusted data source is determined from the plurality of third-party data sources, the data is obtained from the trusted data source, the credibility of the user is predicted by combining the prediction model and the data of the trusted data source, and the user is allowed to register and be linked when the user is credible, so that the safety of the Internet of vehicles identity registration is improved.

In one embodiment, determining a plurality of trusted third party data sources based on a consensus of the Internet of vehicles blockchain to the plurality of third party data sources includes: performing consensus voting on a plurality of third party data sources through a plurality of distributed predictors in the block chain of the Internet of vehicles to obtain a plurality of credible grade evaluation values corresponding to the plurality of third party data sources; and determining a plurality of trusted third-party data sources from the plurality of third-party data sources according to comparison results of the plurality of trusted grade evaluation values corresponding to the plurality of third-party data sources and a preset trusted grade evaluation value threshold.

In this embodiment, the trusted data source may be obtained by consensus voting. The management end management framework can be composed of components such as registration category, identity registration intelligent contract, prophetic machine intelligent contract, distributed prophetic machine node, third party data source, trusted identity chain, trusted prediction of registered users and the like. That is, the above-described internet of vehicles blockchain may include a plurality of distributed predictors therein. In some embodiments, the distributed predictors may be configured to determine a plurality of third party data sources corresponding to the user to be registered, and perform consensus voting on the third party data sources. The management end can perform consensus voting on a plurality of third-party data sources through a plurality of distributed predictors in the block chain of the Internet of vehicles. The management end can obtain a plurality of credible grade evaluation values obtained after the distributed predictors perform consensus voting on a plurality of third-party data sources. Wherein the plurality of confidence level evaluation values may be numerical information. The management terminal can obtain comparison results of the multiple credible grade evaluation values corresponding to the multiple third-party data sources and a preset credible grade evaluation threshold. For example, the management end compares each credible grade evaluation value with the credible grade evaluation threshold value, so that the management end can determine a plurality of credible third-party data sources from a plurality of third-party data sources according to the comparison result.

In particular, the third party data source may be a third party database external to the blockchain of the internet of vehicles, such as an external third party database for traffic authorities, social media, other vehicles, and roadside units. Wherein different user types may correspond to different third party databases. The third party database stores a large amount of influence factor data for evaluating whether the user is credible or not. When the trusted prediction is carried out on the registered user, the dependence on the data on the chain is insufficient, a large amount of relevant influence factor data is required to be acquired from an external third party data source by means of the distributed predictors, a large amount of trusted data is used for modeling and predicting whether the registered user is trusted, and the authenticity and reliability of identity information can be increased. Therefore, a plurality of distributed predictors can be set in the block chain of the internet of vehicles, and the distributed predictors are commonly provided with services by a plurality of predictors nodes. The management end can send a data request to the distributed predictor node through the predictor intelligent contract so as to acquire a corresponding third-party data source. When each distributed predictor node receives a data request of a predictor intelligent contract, the external data source is actively called and related data information is acquired, as shown in fig. 3. The predictor node can simultaneously perform consensus voting aiming at the credibility on the acquired multiple third-party data sources, obtain credibility level evaluation values of the multiple third-party data sources and record the credibility level evaluation values. For the determined trusted third party data sources, the distributed predictors can preferentially select the trusted third party data sources when the data sources are acquired later.

Through the embodiment, the management end can perform consensus voting on the credibility of a plurality of third-party data sources through the distributed predictive engine, so that the credible third-party data sources are determined according to the result of the consensus voting, and the credible verification is performed on the users to be registered based on the credible third-party data sources, thereby improving the safety of the registered users of the Internet of vehicles.

In one embodiment, further comprising: acquiring user sample data and a trusted identification sample result corresponding to a user identifier; aiming at a user type corresponding to each user identifier, acquiring a plurality of candidate prediction models to be trained corresponding to the user type; wherein, the prediction algorithm corresponding to each candidate prediction model is different; inputting user sample data into each candidate prediction model aiming at each candidate prediction model, and obtaining a candidate credible identification prediction result output by the candidate prediction model through a corresponding prediction algorithm and the user sample data; according to the similarity comparison result of the candidate credible recognition result and the credible recognition sample result, adjusting the model parameters of the candidate prediction model until the preset training ending condition is met, and obtaining a trained candidate prediction model; respectively inputting user sample data corresponding to the user type into a plurality of trained candidate prediction models to obtain a plurality of candidate credible recognition results which are respectively output by the plurality of candidate prediction models based on the user sample data; and obtaining a target candidate reliable recognition result with highest similarity with the reliable recognition sample result, and obtaining a trained prediction model corresponding to the user type according to a candidate prediction model corresponding to the target candidate reliable recognition result.

In this embodiment, the prediction models may correspond to the user types one by one. The management end can train the prediction model to be trained through various algorithms, so that the prediction model with the best prediction effect for each user type is determined from the models trained by the various algorithms. For example, the management end may obtain the user sample data and the trusted identification sample result corresponding to the user identifier. The user sample data and the trusted identification sample result can be obtained from a correct historical prediction result or can be obtained by manual labeling. The above user types may include a plurality of types. For each user type corresponding to the user identifier, the management end can acquire a plurality of candidate prediction models to be trained corresponding to the user type. Wherein, the prediction algorithm corresponding to each candidate prediction model is different.

And for each candidate prediction model, the management end inputs the user sample data into the candidate prediction model, acquires the candidate prediction model, pre-stores the user sample data through a corresponding prediction algorithm, and outputs a candidate credible identification prediction result. And the management end compares the candidate credible identification prediction result with the credible identification sample result in similarity, so as to obtain a corresponding similarity comparison result. The management end can adjust the model parameters of the candidate prediction model according to the similarity comparison result, and returns to the step of inputting the user sample data into the candidate prediction model, and performs the next iterative training until the preset training ending condition is met, so that the trained candidate prediction model can be obtained. The preset training ending condition may be that the similarity of the confidence identification prediction result and the confidence identification sample result is greater than or equal to a preset similarity threshold value, or the training frequency reaches a preset frequency within a preset training frequency.

The management end can train the candidate prediction models of different prediction algorithms, so that a plurality of trained candidate prediction models can be obtained. The management end can respectively input the user sample data corresponding to the user type into the plurality of trained candidate prediction models, and the plurality of candidate prediction models respectively output corresponding candidate trusted identification results based on the user sample data to obtain a plurality of candidate trusted identification results. The management end can acquire a target candidate trusted identification result with highest similarity with the trusted identification sample result in the plurality of candidate trusted identification results, so that the management end can acquire a trained prediction model corresponding to the user type according to the candidate prediction model corresponding to the target candidate trusted identification result. The management end can perform the training determination of the optimal prediction model for each user type, so that the management end can obtain a trained prediction model corresponding to each user type.

Specifically, the management end can determine an optimal prediction model based on the accuracy of predicting the credibility of the registration category identity. For example, the management end firstly cleans a large amount of registration category information data sets acquired by the predictor, discards some unavailable data, and then performs corresponding operations such as data complement, feature mining and screening, feature digital processing and the like on the cleaned data through an artificial intelligent algorithm, so that models of various user categories are trained based on the processed information data sets of various user types. The prediction algorithm may be various. For example, the management end compares the prediction accuracy trained by the three algorithms, so as to select the optimal prediction model corresponding to the registration category of each user type.

According to the method and the device for the vehicle networking registration, the management end determines the prediction model with the highest prediction accuracy corresponding to each user type from multiple candidate prediction models, predicts the credibility of the user to be registered based on the prediction model, and improves the safety of the vehicle networking registration.

In one embodiment, inputting user data to be identified into a trained predictive model includes: inputting the user data to be identified into a prediction model corresponding to the user type of the user identification, obtaining a corresponding trusted identification value based on the user data to be identified by the prediction model, and outputting a trusted identification result according to the trusted identification value.

In this embodiment, the trained prediction model may be a prediction model corresponding to a user type represented by the user identifier. The management end can input the user data to be identified into a prediction model corresponding to the user type of the user identification, and the prediction model obtains a corresponding trusted identification value through a corresponding prediction algorithm based on the user data to be identified, so that the prediction model outputs a trusted identification result according to the trusted identification value. Therefore, the management end can determine whether the user to be registered is trusted or not based on the trusted identification result. It is determined whether the user to be registered is authentic, for example, based on the size of the authentic identification value.

Specifically, after the distributed predictor node determines the trusted data source, the distributed predictor node may acquire corresponding data from the trusted third party data source for processing. The management end can consider whether the registered user is trusted as a classification problem in the registered identity trusted prediction module, namely, whether the user is trusted can be determined through the trusted identification value. For example, the number 0 indicates unreliable and the number 1 indicates reliable. The management end can utilize the optimal prediction model in the registration category to which the registered user belongs to predict after the management end invokes the corresponding credible influence factor distinguishing data of the registered user through the distributed prediction machine. For example, after the management end inputs the user data into the prediction model, if the prediction model outputs the number 1, the management end indicates that the user is trusted; if the predictive model outputs a digital 0, it indicates that the user is not trusted.

Through the embodiment, the management end can determine whether the user is credible or not based on the prediction model corresponding to the user type and the user data of the user to be registered and a two-classification method, so that the security of Internet of vehicles registration is improved.

In one embodiment, registering a user to be registered with the internet of vehicles blockchain based on identity information includes: obtaining a public key corresponding to the user identifier; generating a block chain certificate according to the identity information and the public key, and carrying out hash operation on the block chain certificate to obtain a corresponding hash value; and generating a block corresponding to the blockchain certificate in the blockchain of the Internet of vehicles, and storing the blockchain certificate and the hash value into the block to obtain the registered user.

In this embodiment, after determining that the user to be registered is a trusted user, the management end may determine that the user to be registered allows registration, and perform registration and uplink on the user to be registered. During registration, the management end can generate a corresponding public key based on the user identifier, generate a corresponding blockchain certificate according to the identity information and the public key of the user, and perform hash operation on the blockchain certificate to obtain a corresponding hash value. The management end can generate a block corresponding to the blockchain certificate in the blockchain of the Internet of vehicles, and store the blockchain certificate and the hash value into the block, so that the registered user is obtained.

After the user to be registered is successfully registered, the management end can also return the information of successful registration to the user. For example, in one embodiment, after the management end registers the user to be registered to the internet of vehicles blockchain according to the identity information, the management end may also generate a registration result corresponding to the registered user according to a block corresponding to the blockchain certificate in the internet of vehicles blockchain, and return the registration result to the registered user.

The management end can request and feed back corresponding data through the identity registration intelligent contract and the predictor intelligent contract, the predictor node is responsible for acquiring data in a third-party data source, and the third-party data source comprises a vehicle management station, other vehicles, traffic departments, road side units and the like. For example, after receiving the result of whether the user to be registered output by the prediction model is trusted or not through the identity registration intelligent contract, the management end can register the uplink if the result is trusted. For a user capable of registering a uplink, if the user to be registered is verified to be legal through the agreement, the management end generates a public key and a private key for the user through a trusted authentication center, generates a blockchain certificate comprising identity information of the user to be registered and the public key of the user to be registered, and carries out hash operation on the blockchain certificate by the management end to obtain a hash value. The user private key and the hash are encrypted through the trusted authentication center and then sent to the user, and the trusted identity chain in the blockchain stores the blockchain certificate of the registered user and the corresponding hash value. The blockchain node takes the blockchain certificate which is not currently included in the block as a transaction to generate a new block, thereby realizing registration and uplink of the user. After the user registration is completed, the management end may broadcast the information of the registration completion to other accounting nodes. And finally, the registered user receives a message of successful completion of registration fed back by the management end through the trusted authentication center.

Through the embodiment, the management terminal generates the corresponding blockchain certificate and the public key based on the identity information of the user, registers and links the trusted user, improves the security of Internet of vehicles registration, feeds back the information of successful registration to the user, and improves the timeliness of registration information feedback.

In one embodiment, as shown in fig. 4, fig. 4 is a flow chart of a blockchain-based internet of vehicles identity registration method in another embodiment. It can be applied to the architecture shown in fig. 5, and fig. 5 is a schematic diagram of the architecture of the block chain based on the internet of vehicles in one embodiment. The architecture of the block chain of the Internet of vehicles mainly comprises intelligent contracts, distributed predictor nodes, registered user identity trusted prediction, a trusted identity chain and the like. The management end realizes trusted data acquisition and registration uplink for the user through the parts. The management end requests and feeds back corresponding user data through the identity registration intelligent contract and the predictor intelligent contract, and obtains data in a third-party data source through a predictor node, wherein the third-party data source comprises a vehicle management station, other vehicles, traffic departments, road side units and the like.

In this embodiment, the method includes the following steps: the user initiates a registration request, and the management terminal calls an identity registration intelligent contract to carry out relevant registration authentication based on the registration request. The management system initiates a request for judging whether the user to be registered is credible to the distributed prophetic intelligent contract through the identity registration intelligent contract. The management node can be mobilized to acquire all third-party data sources when receiving the request through the distributed propulsor intelligent contract. The management end performs consensus voting on the third-party data sources through each distributed predictor node to obtain the trusted third-party data sources, so that the reliability of the data sources is ensured, and the reliability of the data is increased. After the management end obtains the user data from the trusted third party data source through the distributed predictor node, the management end can predict whether the registered user is trusted by performing corresponding processing on the user data in the trusted prediction of the registered user identity. The management system returns the result of predicting whether the intelligent contract is trusted to the identity registration intelligent contract through the distributed predictor intelligent contract. For the user with the credible predicted result, the management end can perform credible identity uplink operation on the user, and the user with the credible predicted result is not allowed to be uplink, and finally the registration result is returned to the registration user.

Through the embodiment, the management end determines the trusted data source from the plurality of third party data sources, acquires data from the trusted data source, predicts the credibility of the user by combining the prediction model and the data of the trusted data source, and allows the user to register for uplink when the user is credible, so that the safety of the identity registration of the Internet of vehicles is improved. And the management end integrates and manages the digital identity data information of the user, conveniently and rapidly completes digital identity registration on a chain, performs closed-loop management on the flow, and improves management efficiency. And the problem that single-point faults are difficult to solve in the traditional Internet of vehicles centralized system can be solved through the Internet of vehicles architecture.

It should be understood that, although the steps in the flowcharts related to the above embodiments are sequentially shown as indicated by arrows, these steps are not necessarily sequentially performed in the order indicated by the arrows. The steps are not strictly limited to the order of execution unless explicitly recited herein, and the steps may be executed in other orders. Moreover, at least some of the steps in the flowcharts described in the above embodiments may include a plurality of steps or a plurality of stages, which are not necessarily performed at the same time, but may be performed at different times, and the order of the steps or stages is not necessarily performed sequentially, but may be performed alternately or alternately with at least some of the other steps or stages.

Based on the same inventive concept, the embodiment of the application also provides a blockchain-based internet of vehicles identity registration device for realizing the blockchain-based internet of vehicles identity registration method. The implementation scheme of the solution provided by the device is similar to the implementation scheme recorded in the method, so the specific limitation in the embodiment of the one or more blockchain-based internet of vehicles identity registration devices provided below can be referred to the limitation of the blockchain-based internet of vehicles identity registration method hereinabove, and the description thereof is omitted herein.

In one embodiment, as shown in fig. 6, there is provided a blockchain-based internet of vehicles identity registration device, including: an acquisition module 500, a determination module 502, an identification module 504, and a registration module 506, wherein:

the acquisition module 500 is configured to acquire a registration request of a user to be registered for a block chain of the internet of vehicles; the registration request carries a user identification and identity information of the user to be registered.

The determining module 502 is configured to determine a plurality of corresponding third party data sources according to the user identifier, and determine a plurality of trusted third party data sources according to a consensus result of the internet of vehicles blockchain on the plurality of third party data sources.

The identifying module 504 is configured to obtain user data to be identified corresponding to the user identifier according to a plurality of trusted third party data sources, input the user data to be identified into a trained prediction model, and obtain a trusted identification result output by the prediction model based on the user data to be identified.

And the registration module 506 is configured to register the user to be registered to the internet of vehicles blockchain according to the identity information if the trusted identification result is trusted.

In one embodiment, the determining module 502 is configured to determine, according to the user identifier, a user type corresponding to the user to be registered; and acquiring a plurality of third party data sources corresponding to the user types.

In one embodiment, the determining module 502 is configured to perform consensus voting on a plurality of third party data sources through a plurality of distributed predictors in a blockchain of the internet of vehicles to obtain a plurality of trust level evaluation values corresponding to the plurality of third party data sources; and determining a plurality of trusted third-party data sources from the plurality of third-party data sources according to comparison results of the plurality of trusted grade evaluation values corresponding to the plurality of third-party data sources and a preset trusted grade evaluation value threshold.

In one embodiment, the apparatus further comprises: the training module is used for acquiring user sample data and a trusted identification sample result corresponding to the user identifier; aiming at a user type corresponding to each user identifier, acquiring a plurality of candidate prediction models to be trained corresponding to the user type; wherein, the prediction algorithm corresponding to each candidate prediction model is different; inputting user sample data into each candidate prediction model aiming at each candidate prediction model, and obtaining a candidate credible identification prediction result output by the candidate prediction model through a corresponding prediction algorithm and the user sample data; according to the similarity comparison result of the candidate credible recognition result and the credible recognition sample result, adjusting the model parameters of the candidate prediction model until the preset training ending condition is met, and obtaining a trained candidate prediction model; respectively inputting user sample data corresponding to the user type into a plurality of trained candidate prediction models to obtain a plurality of candidate credible recognition results which are respectively output by the plurality of candidate prediction models based on the user sample data; and obtaining a target candidate reliable recognition result with highest similarity with the reliable recognition sample result, and obtaining a trained prediction model corresponding to the user type according to a candidate prediction model corresponding to the target candidate reliable recognition result.

In one embodiment, the identifying module 504 is configured to input the user data to be identified into a prediction model corresponding to the user type of the user identifier, obtain, based on the user data to be identified, a corresponding trusted identification value by using the prediction model, and output a trusted identification result according to the trusted identification value.

In one embodiment, the registration module 506 is configured to obtain a public key corresponding to the user identifier; generating a block chain certificate according to the identity information and the public key, and carrying out hash operation on the block chain certificate to obtain a corresponding hash value; and generating a block corresponding to the blockchain certificate in the blockchain of the Internet of vehicles, and storing the blockchain certificate and the hash value into the block to obtain the registered user.

In one embodiment, the apparatus further comprises: and the feedback module is used for generating a registration result corresponding to the registered user according to the block corresponding to the blockchain certificate in the blockchain of the Internet of vehicles, and returning the registration result to the registered user.

The above-described modules in the blockchain-based internet of vehicles identity registration device may be implemented in whole or in part by software, hardware, and combinations thereof. The above modules may be embedded in hardware or may be independent of a processor in the computer device, or may be stored in software in a memory in the computer device, so that the processor may call and execute operations corresponding to the above modules.

In one embodiment, a computer device is provided, which may be a server, the internal structure of which may be as shown in fig. 7. The computer device includes a processor, a memory, and a network interface connected by a system bus. Wherein the processor of the computer device is configured to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system, computer programs, and a database. The internal memory provides an environment for the operation of the operating system and computer programs in the non-volatile storage media. The database of the computer device is used for storing the user registration data. The network interface of the computer device is used for communicating with an external terminal through a network connection. The computer program, when executed by a processor, implements a blockchain-based internet of vehicles identity registration method.

It will be appreciated by those skilled in the art that the structure shown in fig. 7 is merely a block diagram of some of the structures associated with the present application and is not limiting of the computer device to which the present application may be applied, and that a particular computer device may include more or fewer components than shown, or may combine certain components, or have a different arrangement of components.

In one embodiment, a computer device is provided that includes a memory and a processor, the memory storing a computer program that when executed implements the blockchain-based internet of vehicles identity registration method described above.

In one embodiment, a computer readable storage medium is provided, on which a computer program is stored, which when executed by a processor implements the blockchain-based internet of vehicles identity registration method described above.

In one embodiment, a computer program product is provided, comprising a computer program that when executed by a processor implements the blockchain-based internet of vehicles identity registration method described above.

It should be noted that, user information (including but not limited to user equipment information, user personal information, etc.) and data (including but not limited to data for analysis, stored data, presented data, etc.) referred to in the present application are information and data authorized by the user or sufficiently authorized by each party.

Those skilled in the art will appreciate that implementing all or part of the above described methods may be accomplished by way of a computer program stored on a non-transitory computer readable storage medium, which when executed, may comprise the steps of the embodiments of the methods described above. Any reference to memory, database, or other medium used in the various embodiments provided herein may include at least one of non-volatile and volatile memory. The nonvolatile Memory may include Read-Only Memory (ROM), magnetic tape, floppy disk, flash Memory, optical Memory, high density embedded nonvolatile Memory, resistive random access Memory (ReRAM), magnetic random access Memory (Magnetoresistive Random Access Memory, MRAM), ferroelectric Memory (Ferroelectric Random Access Memory, FRAM), phase change Memory (Phase Change Memory, PCM), graphene Memory, and the like. Volatile memory can include random access memory (Random Access Memory, RAM) or external cache memory, and the like. By way of illustration, and not limitation, RAM can be in the form of a variety of forms, such as static random access memory (Static Random Access Memory, SRAM) or dynamic random access memory (Dynamic Random Access Memory, DRAM), and the like. The databases referred to in the various embodiments provided herein may include at least one of relational databases and non-relational databases. The non-relational database may include, but is not limited to, a blockchain-based distributed database, and the like. The processors referred to in the embodiments provided herein may be general purpose processors, central processing units, graphics processors, digital signal processors, programmable logic units, quantum computing-based data processing logic units, etc., without being limited thereto.

The technical features of the above embodiments may be arbitrarily combined, and all possible combinations of the technical features in the above embodiments are not described for brevity of description, however, as long as there is no contradiction between the combinations of the technical features, they should be considered as the scope of the description.

The above examples only represent a few embodiments of the present application, which are described in more detail and are not to be construed as limiting the scope of the present application. It should be noted that it would be apparent to those skilled in the art that various modifications and improvements could be made without departing from the spirit of the present application, which would be within the scope of the present application. Accordingly, the scope of protection of the present application shall be subject to the appended claims.

Claims

1. A blockchain-based internet of vehicles identity registration method, the method comprising:

2. The method of claim 1, wherein said determining a corresponding plurality of third party data sources from said user identification comprises:

3. The method of claim 1, wherein the determining a plurality of trusted third party data sources based on the consensus of the internet of vehicles blockchain to the plurality of third party data sources comprises:

4. The method according to claim 1, wherein the method further comprises:

5. The method of claim 1, wherein the inputting the user data to be identified into the trained predictive model comprises:

6. The method of claim 1, wherein registering the user to be registered with the internet of vehicles blockchain according to the identity information comprises:

obtaining a public key corresponding to the user identifier;

7. The method of claim 6, wherein after registering the user to be registered with the internet of vehicles blockchain according to the identity information, further comprising:

8. A blockchain-based internet of vehicles identity registration device, the device comprising:

9. A computer device comprising a memory and a processor, the memory storing a computer program, characterized in that the processor implements the steps of the method of any of claims 1 to 7 when the computer program is executed.

10. A computer readable storage medium, on which a computer program is stored, characterized in that the computer program, when being executed by a processor, implements the steps of the method of any of claims 1 to 7.

11. A computer program product comprising a computer program, characterized in that the computer program, when being executed by a processor, implements the steps of the method of any of claims 1 to 7.