CN113656842B

CN113656842B - Data verification method, device and equipment

Info

Publication number: CN113656842B
Application number: CN202110913219.0A
Authority: CN
Inventors: 余廷钊; 黄丹妮; 陈雄威; 仇恩坚; 何秋佳; 陈琦
Original assignee: Alipay Hangzhou Information Technology Co Ltd
Current assignee: Alipay Hangzhou Information Technology Co Ltd
Priority date: 2021-08-10
Filing date: 2021-08-10
Publication date: 2024-02-02
Anticipated expiration: 2041-08-10
Also published as: CN113656842A

Abstract

The embodiment of the specification discloses a data verification method, a device and equipment. The method comprises the following steps: acquiring data to be verified, which are acquired by a plurality of data acquisition devices and are aimed at a target area, and processing the data to be verified, which are provided by each data acquisition device, so as to obtain characteristic values to be verified, which correspond to each data to be verified; based on each feature value to be verified, consistency verification is carried out, and a verification result is obtained; if the verification result shows that the characteristic values of the data to be verified provided by each data acquisition device are consistent, determining that the data to be verified passes verification; uploading the verified data to be verified to a blockchain network for storage.

Description

Data verification method, device and equipment

Technical Field

The present disclosure relates to the field of blockchain technologies, and in particular, to a method, an apparatus, and a device for data verification.

Background

Blockchain (Blockchain) is a new application mode of computer technologies such as distributed data storage, point-to-point transmission, consensus mechanisms, encryption algorithms, and the like. In the block chain system, the data blocks are combined into a chain data structure in a sequential connection mode according to the time sequence, and the distributed account book which is not tamperable and counterfeit and is ensured in a cryptographic mode is formed. Because the blockchain has the characteristics of decentralization, non-tamperability of information, autonomy and the like, the blockchain is also receiving more and more attention and application.

Disclosure of Invention

The embodiment of the specification provides a data verification method, device and equipment, which are used for solving the problem that the credibility of uplink data before uplink cannot be ensured in the existing method.

In order to solve the above technical problems, the embodiments of the present specification are implemented as follows:

the data verification method provided by the embodiment of the specification comprises the following steps:

acquiring data to be verified aiming at a target area; the data to be verified are data which are acquired by a plurality of data acquisition devices and are aimed at the target area;

processing the data to be verified provided by each data acquisition device to obtain a feature value to be verified corresponding to each data to be verified;

based on each feature value to be verified, consistency verification is carried out, and a verification result is obtained;

if the verification result indicates that the characteristic values of the data to be verified provided by each data acquisition device are consistent, determining that the data to be verified passes verification;

uploading the verified data to be verified to a blockchain network for storage.

The data verification device provided in the embodiment of the present specification includes:

the data acquisition module to be verified is used for acquiring data to be verified aiming at the target area; the data to be verified are data which are acquired by a plurality of data acquisition devices and are aimed at the target area;

The to-be-verified characteristic value determining module is used for processing to-be-verified data provided by each data acquisition device to obtain to-be-verified characteristic values corresponding to each to-be-verified data;

the consistency verification module is used for carrying out consistency verification based on each characteristic value to be verified to obtain a verification result;

the verification passing determining module is used for determining that the data to be verified passes verification if the verification result indicates that the characteristic values of the data to be verified provided by each data acquisition device are consistent;

and the data to be verified uploading module is used for uploading the verified data to be verified to a blockchain network for storage.

The embodiment of the specification provides a data verification device, which comprises:

at least one processor; the method comprises the steps of,

a memory communicatively coupled to the at least one processor; wherein,

the memory stores instructions executable by the at least one processor to enable the at least one processor to:

uploading the verified data to be verified to a blockchain network for storage.

Embodiments of the present disclosure provide a computer readable medium having computer readable instructions stored thereon that are executable by a processor to implement a data verification method.

At least one embodiment of the present disclosure can achieve the following beneficial effects: processing the data to be verified provided by each data acquisition device by acquiring the data to be verified aiming at the target area, which are acquired by a plurality of data acquisition devices, so as to obtain characteristic values to be verified, which correspond to each data to be verified; based on each feature value to be verified, consistency verification is carried out, and a verification result is obtained; if the verification result indicates that the characteristic values of the data to be verified provided by each data acquisition device are consistent, determining that the data to be verified passes verification; uploading the verified data to be verified to a blockchain network for storage. By the method, before the data is uplinked, whether the data needing to be uplinked is credible or not is verified, the data can be uploaded to a blockchain network for storage after the verification is passed, the source credibility of the data stored by the data uplinking is ensured, and the data credibility before the data uplinking is ensured, so that the safety of the data is further ensured.

Drawings

In order to more clearly illustrate the embodiments of the present description or the technical solutions in the prior art, the drawings that are required to be used in the embodiments or the description of the prior art will be briefly described below, and it is obvious that the drawings in the following description are only some embodiments described in the present application, and that other drawings may be obtained according to these drawings without inventive effort to a person skilled in the art.

FIG. 1 is a schematic flow chart of an overall scheme of a data verification method in an embodiment of the present disclosure;

fig. 2 is a flow chart of a data verification method according to an embodiment of the present disclosure;

fig. 3 is a schematic structural diagram of a data verification device according to an embodiment of the present disclosure;

fig. 4 is a schematic structural diagram of a data verification device according to an embodiment of the present disclosure.

Detailed Description

For the purposes of making the objects, technical solutions and advantages of one or more embodiments of the present specification more clear, the technical solutions of one or more embodiments of the present specification will be clearly and completely described below in connection with specific embodiments of the present specification and corresponding drawings. It will be apparent that the described embodiments are only some, but not all, of the embodiments of the present specification. All other embodiments, which can be made by one of ordinary skill in the art based on the embodiments herein without undue burden, are intended to be within the scope of one or more embodiments herein.

The following describes in detail the technical solutions provided by the embodiments of the present specification with reference to the accompanying drawings.

With the development of society, the information age has become popular, and the demand for information services is increasing, so that it is important to grasp trusted service data. The Blockchain (Blockchain) technology is used as a core information technology in a bitcoin transaction system, and solves the problems of double consumption and Bayesian general due to the characteristics of the openness of the transaction system, the non-tamper property ensured by not depending on any trust mechanism, the time stamp and the digital signature, the permanence of legal transactions stored in the Blockchain and the like, and realizes an untrustworthy consensus network system. Then more and more blockchain projects have been developed, ethernet (ethernet) is a representative one of them, which is a complete information system of the turing and supports a custom smart contract, which is a piece of executable code on the blockchain, and when the triggering condition is met, the transparent smart contract is disclosed to be automatically executed off-center. The blockchain is a novel application mode of computer technologies such as distributed data storage, point-to-point transmission, a consensus mechanism, an encryption algorithm and the like, and can accelerate the transmission of information.

Blockchains solve the problem of data tampering, but the collection of data may still be at risk of tampering. How to ensure that reliable data can be collected and that uplink data is reliable is a problem to be solved.

In order to solve the drawbacks of the prior art, the present solution provides the following embodiments:

a data verification scheme is provided so that data can be verified by means of blockchain intelligent contract verification, whether the data is trusted or not is verified before being uplink, and trusted data acquisition is guaranteed.

Fig. 1 is a schematic flow chart of an overall scheme of a data verification method in an embodiment of the present disclosure. As shown in fig. 1, the following description will take the example of capturing video data: assuming that a camera a, a camera B and a camera C exist in the area 1, the three cameras collect video data from different angles for the area 1, the collected video data can be subjected to credibility verification through an intelligent contract in the first blockchain network 101, and after the verification is passed, the video data passing the verification can be uploaded to the second blockchain network 103 for storage. In particular, the verified video data may be uploaded to each node in the second blockchain network 103 for storage. It should be noted that, in practical application, the first blockchain network 101 and the second blockchain network 103 may be the same blockchain network, that is, before video data is uplink, the video data is verified by using an intelligent contract in the blockchain network storing the video data, and after the verification is passed, the video data is uploaded to the blockchain network where the intelligent contract is located for storage. Of course, the first blockchain network 101 and the second blockchain network 103 may be different blockchain networks, that is, the blockchain networks where the intelligent contracts for video data verification are located and the blockchain networks where video data are stored may be different blockchain networks.

Next, a data verification method provided for the embodiments of the specification will be specifically described with reference to the accompanying drawings:

fig. 2 is a flow chart of a data verification method according to an embodiment of the present disclosure. From the program perspective, the execution subject of the flow may be a program or an application client that is installed on an application server. In this embodiment, the execution subject of the flow may be an intelligent contract running in a blockchain network, which may be a blockchain network for storing authenticated data, or another blockchain network having a transmission protocol with the blockchain network storing authenticated data.

The intelligent contract may be one special agreement, and is used in making contract in block chain, and has program code Function, and may be used in interacting with other contracts, making decision, storing data, transmitting Ethernet, etc. The intelligent contract master provides conditions for verifying and executing contracts. The smart contract allows trusted transactions to be conducted without a third party.

As shown in fig. 2, the process may include the steps of:

step 210: acquiring data to be verified aiming at a target area; the data to be verified are data aiming at the target area, which are collected by a plurality of data collection devices.

The target region may represent a region where the data acquisition device acquires data, for example: in the warehouse, a plurality of areas exist, each area is provided with one or more cameras for shooting, and video data shot by the cameras can be uploaded to a blockchain network for storage after verification is passed. The target area may be an area where one or more cameras together capture video data that needs to be verified. For example: the camera a, the camera B, and the camera C are used to capture the area 1, and the area 1 may be a target area at this time. The data to be verified may be data collected by a plurality of cameras for photographing the area 1.

The data acquisition device may represent a device for acquiring data, such as: an image pickup apparatus for capturing video data, an audio capturing apparatus for capturing audio data, and an apparatus for capturing other data (temperature, humidity, illumination, electrical signals, etc.).

Step 220: and processing the data to be verified provided by each data acquisition device to obtain the characteristic value to be verified corresponding to each data to be verified.

Taking the data acquisition equipment as the image pickup equipment as an example, the computer cannot directly identify the video data acquired by the image pickup equipment, and the video data acquired by the camera needs to be converted into the data which can be identified by the computer.

In addition, each video corresponds to a continuous multi-frame image, and when verification is performed, characteristic values in the video need to be extracted. The feature value may be used to represent an important feature in each frame of image. Feature extraction is a concept in computer vision and image processing. It may be expressed that the computer is used to extract image information and determine whether the point of each image belongs to an image feature. The result of feature extraction is to divide the points on the image into different subsets, which often belong to isolated points, continuous curves or continuous areas, feature extraction is a primary operation in image processing, from each pixel in the image it can be determined whether that pixel represents a feature. Common image features may include color features, texture features, shape features, spatial relationship features. And the method for extracting the features from the image may include Fourier transform, window Fourier transform (Gabor), wavelet transform, least square method, boundary direction histogram method, texture feature extraction based on Tamura texture features, and the like.

Step 230: and carrying out consistency verification based on each characteristic value to be verified to obtain a verification result.

The consistency check may represent a determination of consistency for data acquired by the data acquisition devices for the same area. For example: the camera A, the camera B and the camera C are used for shooting the area 1, and when data consistency verification is carried out, whether the characteristic value 1 corresponding to the video data collected by the camera A, the characteristic value 2 corresponding to the video data collected by the camera B and the characteristic value 3 corresponding to the video data collected by the camera C are the same or not or whether the similarity is larger than a preset threshold value or not can be indicated.

Step 240: and if the verification result indicates that the characteristic values of the data to be verified provided by the data acquisition equipment are consistent, determining that the data to be verified passes verification.

The "coincidence" may indicate that the data collected by the plurality of data collection devices for the same region are the same, or may indicate that the similarity of the data collected by the plurality of data collection devices for the same region is greater than a preset threshold. "consistent" may then determine that the data is verified.

Step 250: uploading the verified data to be verified to a blockchain network for storage.

The blockchain network can be a shared database, and data or information stored in the shared database has the characteristics of 'non-falsifiability', 'whole-course trace', 'traceability', 'disclosure transparency', 'collective maintenance', and the like. The verified data can be uploaded to the blockchain network for storage so as to ensure the security and privacy of the data.

The method steps are applied to intelligent contracts in the block chain network, whether the data are trusted before being uploaded is verified by the intelligent contracts, and the data are uploaded to the block chain network for storage after verification is passed.

Blockchain technology starts with ethernet, which is one of the biggest advances in ethernet over bitcoin technology to support users to create and invoke some complex logic in the blockchain network. At the heart of the ethernet as a programmable blockchain is an Ethernet Virtual Machine (EVM), which can be run by each ethernet node. The EVM is a graphics-complete virtual machine, meaning that various complex logic can be implemented by it. Deployment and invocation of the smart contract by the user in the ethernet house may be performed by the EVM. In the deployment phase, the user may send a transaction to the ethernet network containing the creation of the smart contract, the data field of which may contain the code (e.g., bytecode) of the smart contract, and the to field of which is empty. After the diffusion and consensus of the transaction, each node in the ethernet network can execute the transaction through the EVM and generate a corresponding contract instance, thereby completing the intelligent contract deployment. At this point, the blockchain may have a contract account corresponding to the smart contract that has a specific contract address. In the calling phase, the user (which may be the same as or different from the user deploying the smart contract) sends a transaction for calling the smart contract to the ethernet network, the from field of the transaction is the address of the external account corresponding to the user, the to field is the contract address of the smart contract to be called, and the data field contains the method and parameters for calling the smart contract. After the nodes agree with each other through a consensus mechanism, the intelligent contract called by the transaction statement is independently executed on each node of the Ethernet network in a specified mode, and all execution records and data are stored on the blockchain, so that after the transaction is completed, transaction certificates which cannot be tampered and lost are stored on the blockchain. With the development of blockchain technology, many other types of virtual machines, such as WASM (WebAssembly) virtual machines, have been produced in addition to EVM.

Each blockchain network node may perform creation and invocation of intelligent contracts through a virtual machine. Both transactions involving smart contracts and the results of execution of the transactions are stored on the blockchain ledger or in such a way that each full node in the blockchain stores the full ledger, a challenge for privacy protection. Privacy protection may be achieved through a variety of techniques, such as cryptography (e.g., homomorphic encryption Homomorphic encryption, or Zero-knowledge proof Zero-knowledgeproof proof), hardware privacy techniques, network quarantine techniques, and the like.

Nodes in the blockchain may provide calls to deployed smart contracts. When a specific intelligent contract is called, the byte code of the deployed contract can be loaded and executed in a trusted execution environment, and an execution result can be fed back to a caller of the contract, or fed back to a designated receiver in the contract or a designated receiver in a transaction for calling the contract, or fed back to the blockchain network node through the predictor mechanism. And feeding back to the block chain network node through the predictor mechanism.

It should be understood that the method according to one or more embodiments of the present disclosure may include the steps in which some of the steps are interchanged as needed, or some of the steps may be omitted or deleted.

In the method in fig. 2, data to be verified, which are provided by each data acquisition device, are processed by acquiring the data to be verified, which are acquired by a plurality of data acquisition devices and are aimed at a target area, so as to obtain feature values to be verified, which correspond to the data to be verified; based on each feature value to be verified, consistency verification is carried out, and a verification result is obtained; if the verification result indicates that the characteristic values of the data to be verified provided by each data acquisition device are consistent, determining that the data to be verified passes verification; uploading the verified data to be verified to a blockchain network for storage. By the method, before the data is uplinked, whether the data needing to be uplinked is credible or not is verified, the data can be uploaded to a blockchain network for storage after the verification is passed, the source credibility of the data stored by the data uplinking is ensured, and the data credibility before the data uplinking is ensured, so that the safety of the data is further ensured.

The examples of the present specification also provide some specific embodiments of the method based on the method of fig. 2, which is described below.

The technical scheme provided by the embodiment of the specification can be applied to various application scenes, for example: the warehouse scene, the logistics scene, the car navigation scene and the like are applicable to the scheme provided by the embodiment of the specification as long as the scene needs a plurality of data acquisition devices to acquire data for the same area and needs to verify the acquired data.

Taking the example that a plurality of cameras acquire video data of the same area, the data to be verified in the steps can be video data, and the data acquisition equipment can be camera shooting equipment; the acquiring the data to be verified for the target area may specifically include:

determining device identifications of a plurality of image capturing devices in the target area; each camera device is used for collecting video data of the target area from different angles;

and acquiring video data corresponding to the equipment identifiers of the plurality of camera equipment.

The device identification may be a device ID, a device model number or a device name, etc. Identification information that uniquely indicates a device can be used as the device identification. The video data collected by each camera device is cached, and when the data to be verified is obtained, the video data to be verified aiming at the target area can be obtained based on the device identification of the camera device. In practical applications, when a plurality of image capturing devices are used for capturing images in the same area, the plurality of image capturing devices typically capture images of a target area from different angles, so as to ensure that events occurring in the target area can be completely recorded. The action behavior of any object in a target area can be recorded by one or more of a plurality of image capturing apparatuses provided in the target area.

Optionally, the processing the to-be-verified data provided by each data acquisition device to obtain to-be-verified feature values corresponding to each to-be-verified data may specifically include:

for the corresponding first video data of the device identification of one image capturing device,

selecting a video frame for feature extraction from the first video data;

extracting characteristic points of the image in the target area from the video frame;

and determining the position information of the characteristic points and the characteristic values of the characteristic points.

For each video frame in the video data collected by each camera, the video frame for feature extraction may be determined first, then feature extraction may be performed, and not all video data required for image feature extraction may include key information in each video frame, that is, not each video frame includes an object for feature extraction, so that it is not necessary to use each video frame for feature extraction.

For example, when the video data to be subjected to feature extraction is a road monitoring video, and feature extraction is performed on vehicles in the road monitoring video, there may be cases where there is no vehicle in the video frame, and where there is a vehicle in the video frame, but the vehicle area is too small to have feature extraction conditions, and there may also be cases where there is a vehicle in the video frame, but the vehicle area is not complete enough due to the angular relationship of the vehicle and the image capturing apparatus, but does not have feature extraction conditions.

Therefore, in the processing procedure, taking video data collected by a certain image capturing device as an example, a video frame for feature extraction can be selected from the collected video data, and the selected condition can be defined according to the actual situation. After selecting the video frame for feature extraction, feature points of the target area image are extracted from the video frame. Specifically, the position information and the feature value where each feature point is located may be determined.

In practical application, because the shooting angles of the image capturing devices are different, in order to facilitate comparison of video data shot by each image capturing device, position information of each feature point in the video data acquired by each image capturing device can be determined first, matrix transformation is performed based on the position information, the data acquired by each image capturing device is converted into the same direction, and then consistency of the data is compared. The method can be realized on the basis of the following steps:

determining a characteristic value set in first video data corresponding to equipment identifiers of a plurality of camera equipment;

selecting a reference feature value from the feature value set;

and according to the position information of the feature points and the reference feature values, performing matrix transformation on the rest feature values in the feature value set to obtain transformed feature values to be verified.

Based on the method for determining the position information and the characteristic value of the characteristic points, the video data of each image capturing device are subjected to the operation, so that second video data corresponding to device identifiers of a plurality of image capturing devices are obtained, and the respective characteristic values are determined, so that a characteristic value set is obtained.

In the feature value set, a reference feature value is selected, the positions of feature points corresponding to the reference feature value are determined, matrix transformation is performed on the rest feature values according to the positions, and the fact that other feature points are subjected to position transformation according to the positions of the feature points corresponding to the reference feature value can be understood as that the directions of the positions of the feature points corresponding to the reference feature value are the same. And then checking.

Optionally, the performing consistency verification based on each feature value to be verified to obtain a verification result may specifically include:

calculating the similarity between the transformed feature values to be verified;

and comparing the similarity with a preset threshold value to obtain a comparison result.

When consistency verification is performed, the similarity between the eigenvalues after matrix transformation can be calculated, in practical application, one image pickup device can correspond to a group of eigenvalues, when consistency of the eigenvalues of a plurality of devices is compared, the similarity between the eigenvalues of the plurality of devices can be calculated, the similarity is larger than a preset threshold value, and then the eigenvalues can be determined to pass the comparison.

After the consistency check is passed, the checked data can be uploaded to a blockchain network for storage. However, in practical applications, the capacity of the blockchain network is limited, because each complete node in the network requiring a bit coin in the blockchain network holds complete blockchain information, with the popularity of blockchain applications, the storage space in the blockchain network is already nearly saturated, and the capacity of the bit coin and the number of participating nodes are rapidly increased over time, so that the blockchain technology occupies a large amount of storage space in massive nodes. Based on this, in the scheme of the embodiment of the present specification, after the data to be verified passes the verification, the data to be verified may be stored after being compressed and combined, and therefore, after the data to be verified passes the verification, the data to be verified may be stored based on the following method:

the first method is that all the data to be verified passing verification are compressed and combined and then uploaded to a blockchain network for storage.

Combining the verified data to be verified to generate target data to be stored; the data size of the target data is smaller than the sum of the data sizes of the data to be verified, which pass through verification.

The memory occupied by the target data to be uploaded after merging and compression should be smaller than the sum of the memories occupied by the to-be-checked data to be stored before merging, for example: the data to be verified which needs to be stored is 1GB video data corresponding to the camera 1, 1.2GB video data corresponding to the camera 2 and 0.8GB video data corresponding to the camera 3, and the data volume of target data obtained after the video data of the camera 1, the camera 3 and the camera 3 are combined and compressed is 1.1GB which is smaller than the sum (2 GB) of the memory occupied by the video data of the three cameras before combination.

And selecting part of the data passing the verification to upload to the blockchain network for storage.

Selecting data to be uploaded in the verified data according to a preset selection rule; the data to be uploaded meets the most preset conditions or the number of the preset conditions met by the data to be uploaded is larger than a preset threshold;

and uploading the data to be uploaded to a block chain for storage.

When the data to be uploaded and saved is selected, the video data of one of the image capturing devices may be selected, or the video data of a plurality of image capturing devices may be selected.

The preset selection rule may be that the data that satisfies the most preset conditions is the data to be uploaded, and the preset conditions may include: the number of feature points involved, the image sharpness of the video frame, the number of objects involved, the object behavior feature information involved, etc.

And thirdly, randomly selecting video data of one of the camera devices, and uploading the video data to a blockchain network for storage.

The data after passing the verification has higher similarity, so that the video data of one of the image pickup devices can be randomly selected as the data to be uploaded.

By the method, the video data shot by the camera can be uploaded to the blockchain for storage, and meanwhile, the storage space occupied by the video data is reduced as much as possible, so that the waste of the storage space in the blockchain network is avoided.

Optionally, the performing consistency verification based on each feature value to be verified, after obtaining a verification result, may further include:

and if the verification result indicates that the characteristic values of the data to be verified acquired by each data acquisition device are inconsistent, stopping uploading the data to be verified to the blockchain network.

and if the verification result indicates that the characteristic values of the data to be verified acquired by each data acquisition device are inconsistent, determining that abnormal data acquisition devices exist.

When the data verification is not passed, the abnormal data acquisition equipment can be stored in the data acquisition equipment to be verified. Wherein, the data acquisition device with abnormality may include: device hardware damage, device system damage, device uploaded false video, device system attack, etc.

If the verification is not passed, it can be determined that there is unreliable data in the batch of data, and in practical application, all the data can be refused to be uploaded. In addition, the data acquisition equipment with problems can be further determined, the data acquired by other data acquisition equipment without abnormality is subjected to consistency verification again, and after the verification is passed, the data acquired by the other data acquisition equipment without abnormality can be uploaded to a blockchain system for storage.

And the data acquisition equipment with abnormality can be overhauled by background personnel.

After the data to be verified passes verification, the credibility of the data can be further determined, and in particular, a proof carried in the data to be verified can be determined, wherein the proof can comprise a Verifiable Claim (VC). VC is also an important application in DID. The VCs may be stored in a blockchain platform.

In this embodiment, each enterprise, as well as some regulatory authorities, etc., may each create a pair of public and private keys in the blockchain, the private keys being stored securely, and may create a distributed digital identity (also referred to as a decentralised identifier, decentralized Identitfiers, DID). The DID may be created by the user himself or a distributed identity service (Decentralized Identity Service, DIS) system may be requested to create the DID. DIS is an identity management scheme based on block chains, and can provide functions of digital identity creation, verification, management and the like, so that standardized management and protection of entity data are realized, the authenticity and efficiency of information circulation are ensured, and the difficulties of identity authentication, data cooperation and the like across institutions can be solved. The DIS system may be coupled to a blockchain platform. A DID can be created for a user through the DIS system, the DID and the public key are sent to the blockchain platform for storage, and the created DID is returned to the user. The public key may be included in DIDdoc, which may be stored in a blockchain platform. DIS creates DID for the user, and can be created based on the public key sent by the user, for example, after calculating the public key of the user by using a Hash function, or can be created according to other information (which may or may not include the public key) of the user. The latter may require the user to provide information beyond some public key.

In the present description embodiment, the corresponding VC may be verified through the blockchain. Specifically, the system may obtain the public key in the DIDdoc from the blockchain, and verify the signature of the VC, thereby confirming that the VC is issued by the data acquisition device and is complete, i.e., has not been tampered with.

By the method, the data to be verified and the verifiable statement carried by the data to be verified which can be verified are stored in the blockchain, and the credibility of the acquired data can be ensured.

When the data to be verified passing verification is stored, the data to be verified can be stored after being encrypted.

The core of the scheme in the embodiment of the present specification may be to implement verification of input data by directly inputting video data of different angles for the same region into an intelligent contract running on a blockchain network, and key core technology points may include:

1) The same area provides at least two data acquisition devices at different angles.

2) And each data acquisition device directly calls an intelligent contract interface to output to the intelligent contract, and the intelligent contract is used for judging.

3) Cross-validation is performed in the intelligent contract through multiple data sources, and the validation scheme makes intelligent judgment based on imaging of different angles of the image. Wherein, the multi-data source cross-validation may represent a consistency check of data collected by the plurality of data collection devices via the smart contract.

4) The image processing and checking algorithms can be realized through intelligent contracts, and the whole process runs on a block chain to ensure the credibility of the checking process.

5) The process of determining whether the data collection is trusted is performed within an intelligent contract running on the blockchain network, and only data that passes the verification is ultimately written on the blockchain network.

6) The verifiable statement carried by the verified data is stored in the blockchain, so that the credibility of the obtained data can be ensured, and the credibility of the data storage in the blockchain network is ensured.

7) The data passing through verification is encrypted and then stored in the blockchain network, so that the safety of data storage can be ensured.

Compared with the traditional mode that data is directly uplinked through a terminal, the method has the advantages that the reliability verification of the data of the input source is verified on the chain through the fact that only a contract is executed on the data collected by a plurality of collecting devices, and the accuracy and the reliability of the uplinked data are guaranteed to a greater extent.

In the method, the video data captured by the camera is mostly taken as an example for scheme description. In addition, the scheme of the embodiment of the specification can be applied to acquisition verification of audio data. The data to be verified can be audio data, and the data acquisition device can be audio acquisition device.

Based on the same thought, the embodiment of the specification also provides a device corresponding to the method. Fig. 3 is a schematic structural diagram of a data verification device according to an embodiment of the present disclosure. As shown in fig. 3, the apparatus may include:

a data to be verified acquisition module 310, configured to acquire data to be verified for a target area; the data to be verified are data which are acquired by a plurality of data acquisition devices and are aimed at the target area;

the feature value to be verified determining module 320 is configured to process the data to be verified provided by each data acquisition device to obtain feature values to be verified corresponding to each data to be verified;

the consistency verification module 330 is configured to perform consistency verification based on each of the feature values to be verified, so as to obtain a verification result;

a verification passing determining module 340, configured to determine that the data to be verified passes verification if the verification result indicates that the feature values of the data to be verified provided by each data acquisition device are consistent;

and the data to be verified uploading module 350 is configured to upload the verified data to be verified to the blockchain network for storage.

The present description example also provides some specific embodiments of the device based on the device of fig. 3, which is described below.

Optionally, the data to be verified may be video data, and the data acquisition device may be a camera device; the data to be verified obtaining module 310 may specifically include:

an apparatus identification determination unit configured to determine apparatus identifications of a plurality of image capturing apparatuses in the target area; each camera device is used for collecting video data of the target area from different angles;

and the data acquisition unit to be verified is used for acquiring video data corresponding to the equipment identifiers of the plurality of image pickup equipment.

Optionally, the to-be-verified feature value determining module 320 may specifically include:

a video frame selection unit, configured to select, for first video data corresponding to a device identifier of an image capturing device, a video frame for feature extraction from the first video data;

a feature point extracting unit, configured to extract feature points of an image in the target area from the video frame;

and the characteristic point position information and characteristic value determining unit is used for determining the position information of the characteristic points and the characteristic values of the characteristic points.

Optionally, the apparatus may further include:

a feature value set determining module, configured to determine feature value sets in second video data corresponding to device identifiers of a plurality of image capturing devices;

The reference characteristic value selecting module is used for selecting a reference characteristic value from the characteristic value set;

and the matrix transformation module is used for carrying out matrix transformation on the rest characteristic values in the characteristic value set according to the reference characteristic values and the position information of the characteristic points to obtain transformed characteristic values to be verified.

Optionally, the consistency verification module 330 may specifically include:

a similarity calculation unit, configured to calculate a similarity between the transformed feature values to be verified;

and the comparison unit is used for comparing the similarity with a preset threshold value to obtain a comparison result.

Optionally, the apparatus may further include:

and the data to be verified stops uploading the module, and is used for stopping uploading the data to be verified to the blockchain network if the verification result indicates that the characteristic values of the data to be verified acquired by the data acquisition equipment are inconsistent.

Optionally, the apparatus may further include:

and the abnormal data acquisition equipment determining module is used for determining abnormal data acquisition equipment if the verification result indicates that the characteristic values of the data to be verified acquired by each data acquisition equipment are inconsistent.

Optionally, the apparatus may further include:

the merging module is used for merging the data to be verified which passes verification to generate target data to be stored; the data size of the target data is smaller than the sum of the data sizes of the data to be verified, which pass through verification.

Optionally, the data to be verified may be audio data, and the data acquisition device may be an audio acquisition device.

Optionally, a smart contract is deployed in the blockchain network, and the smart contract may be used to perform the step of data verification.

Optionally, the apparatus may further include:

a verifiable statement generation module for generating a verifiable statement for proving the trustworthiness of the data to be verified;

and the verifiable statement storage module is used for sending the verifiable statement to the blockchain network for storage.

Optionally, the data upload module to be verified 350 may specifically include:

and the encryption unit is used for encrypting the data to be verified which passes verification and storing the data to be verified into the blockchain network.

Based on the same thought, the embodiment of the specification also provides equipment corresponding to the method.

Fig. 4 is a schematic structural diagram of a data verification device according to an embodiment of the present disclosure. As shown in fig. 4, the apparatus 400 may include:

at least one processor 410; the method comprises the steps of,

a memory 430 communicatively coupled to the at least one processor; wherein,

the memory 430 stores instructions 420 executable by the at least one processor 410, the instructions being executable by the at least one processor 410 to enable the at least one processor 410 to:

uploading the verified data to be verified to a blockchain network for storage.

Based on the same thought, the embodiment of the specification also provides a computer readable medium corresponding to the method. Computer readable instructions stored on a computer readable medium, the computer readable instructions being executable by a processor to perform a method of:

uploading the verified data to be verified to a blockchain network for storage.

In this specification, each embodiment is described in a progressive manner, and identical and similar parts of each embodiment are all referred to each other, and each embodiment mainly describes differences from other embodiments. In particular, for the apparatus embodiments, since they are substantially similar to the method embodiments, the description is relatively simple, and reference is made to the description of the method embodiments in part.

In the 90 s of the 20 th century, improvements to one technology could clearly be distinguished as improvements in hardware (e.g., improvements to circuit structures such as diodes, transistors, switches, etc.) or software (improvements to the process flow). However, with the development of technology, many improvements of the current method flows can be regarded as direct improvements of hardware circuit structures. Designers almost always obtain corresponding hardware circuit structures by programming improved method flows into hardware circuits. Therefore, an improvement of a method flow cannot be said to be realized by a hardware entity module. For example, a programmable logic device (Programmable Logic Device, PLD) (e.g., field programmable gate array (Field Programmable Gate Array, FPGA)) is an integrated circuit whose logic function is determined by the programming of the device by a user. The designer programs itself to "integrate" a digital system onto a single PLD without requiring the chip manufacturer to design and fabricate application specific integrated circuit chips. Moreover, nowadays, instead of manually manufacturing integrated circuit chips, such programming is mostly implemented by using "logic compiler" software, which is similar to the software compiler used in program development and writing, and the original code before the compiling is also written in a specific programming language, which is called hardware description language (Hardware Description Language, HDL), but not just one of the hdds, but a plurality of kinds, such as ABEL (Advanced Boolean Expression Language), AHDL (Altera Hardware Description Language), confluence, CUPL (Cornell University Programming Language), HDCal, JHDL (Java Hardware Description Language), lava, lola, myHDL, PALASM, RHDL (Ruby Hardware Description Language), etc., VHDL (Very-High-Speed Integrated Circuit Hardware Description Language) and Verilog are currently most commonly used. It will also be apparent to those skilled in the art that a hardware circuit implementing the logic method flow can be readily obtained by merely slightly programming the method flow into an integrated circuit using several of the hardware description languages described above.

The controller may be implemented in any suitable manner, for example, the controller may take the form of, for example, a microprocessor or processor and a computer readable medium storing computer readable program code (e.g., software or firmware) executable by the (micro) processor, logic gates, switches, application specific integrated circuits (Application Specific Integrated Circuit, ASIC), programmable logic controllers, and embedded microcontrollers, examples of which include, but are not limited to, the following microcontrollers: ARC 625D, atmel AT91SAM, microchip PIC18F26K20, and Silicone Labs C8051F320, the memory controller may also be implemented as part of the control logic of the memory. Those skilled in the art will also appreciate that, in addition to implementing the controller in a pure computer readable program code, it is well possible to implement the same functionality by logically programming the method steps such that the controller is in the form of logic gates, switches, application specific integrated circuits, programmable logic controllers, embedded microcontrollers, etc. Such a controller may thus be regarded as a kind of hardware component, and means for performing various functions included therein may also be regarded as structures within the hardware component. Or even means for achieving the various functions may be regarded as either software modules implementing the methods or structures within hardware components.

The system, apparatus, module or unit set forth in the above embodiments may be implemented in particular by a computer chip or entity, or by a product having a certain function. One typical implementation is a computer. In particular, the computer may be, for example, a personal computer, a laptop computer, a cellular telephone, a camera phone, a smart phone, a personal digital assistant, a media player, a navigation device, an email device, a game console, a tablet computer, a wearable device, or a combination of any of these devices.

For convenience of description, the above devices are described as being functionally divided into various units, respectively. Of course, the functions of each element may be implemented in one or more software and/or hardware elements when implemented in the present application.

It will be appreciated by those skilled in the art that embodiments of the present invention may be provided as a method, system, or computer program product. Accordingly, the present invention may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, the present invention may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, and the like) having computer-usable program code embodied therein.

The present invention is described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems) and computer program products according to embodiments of the invention. It will be understood that each flow and/or block of the flowchart illustrations and/or block diagrams, and combinations of flows and/or blocks in the flowchart illustrations and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.

These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instruction means which implement the function specified in the flowchart flow or flows and/or block diagram block or blocks.

These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.

In one typical configuration, a computing device includes one or more processors (CPUs), input/output interfaces, network interfaces, and memory.

The memory may include volatile memory in a computer-readable medium, random Access Memory (RAM) and/or nonvolatile memory, such as Read Only Memory (ROM) or flash memory (flash RAM). Memory is an example of computer-readable media.

Computer readable media, including both non-transitory and non-transitory, removable and non-removable media, may implement information storage by any method or technology. The information may be computer readable instructions, data structures, modules of a program, or other data. Examples of storage media for a computer include, but are not limited to, phase change memory (PRAM), static Random Access Memory (SRAM), dynamic Random Access Memory (DRAM), other types of Random Access Memory (RAM), read Only Memory (ROM), electrically Erasable Programmable Read Only Memory (EEPROM), flash memory or other memory technology, compact disc read only memory (CD-ROM), digital Versatile Discs (DVD) or other optical storage, magnetic cassettes, magnetic tape disk storage or other magnetic storage devices, or any other non-transmission medium, which can be used to store information that can be accessed by a computing device. Computer-readable media, as defined herein, does not include transitory computer-readable media (transmission media), such as modulated data signals and carrier waves.

It should also be noted that the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising one … …" does not exclude the presence of other like elements in a process, method, article or apparatus that comprises the element.

It will be appreciated by those skilled in the art that embodiments of the present application may be provided as a method, system, or computer program product. Accordingly, the present application may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, the present application may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, and the like) having computer-usable program code embodied therein.

The application may be described in the general context of computer-executable instructions, such as program modules, being executed by a computer. Generally, program modules include routines, programs, objects, components, data structures, etc. that perform particular tasks or implement particular abstract data types. The application may also be practiced in distributed computing environments where tasks are performed by remote processing devices that are linked through a communications network. In a distributed computing environment, program modules may be located in both local and remote computer storage media including memory storage devices.

The foregoing is merely exemplary of the present application and is not intended to limit the present application. Various modifications and changes may be made to the present application by those skilled in the art. Any modifications, equivalent substitutions, improvements, etc. which are within the spirit and principles of the present application are intended to be included within the scope of the claims of the present application.

Claims

1. A data verification method, comprising:

uploading the verified data to be verified to a blockchain network for storage;

the processing the data to be verified provided by each data acquisition device to obtain the feature value to be verified corresponding to each data to be verified specifically comprises the following steps:

For first video data corresponding to equipment identification of one camera equipment, selecting video frames for feature extraction from the first video data;

determining the position information of the feature points and the feature values of the feature points;

determining a characteristic value set in second video data corresponding to equipment identifiers of a plurality of camera equipment;

selecting a reference feature value from the feature value set;

and determining the position information of the feature points corresponding to the reference feature values, carrying out matrix transformation on the feature points corresponding to the rest feature values in the feature value set according to the positions of the feature points corresponding to the reference feature values, and obtaining the transformed feature values to be verified, wherein the direction of the transformed position of the feature points corresponding to the reference feature values is the same.

2. The method of claim 1, wherein the data to be verified is video data, and the data acquisition device is a camera device; the obtaining the data to be verified for the target area specifically includes:

3. The method according to claim 1, wherein the performing the consistency check based on each feature value to be verified, to obtain a check result, specifically includes:

4. The method according to claim 1, wherein the performing the consistency check based on each feature value to be verified, after obtaining the check result, further comprises:

5. The method according to claim 4, wherein the performing the consistency check based on each feature value to be verified, after obtaining the check result, further comprises:

6. The method of claim 1, the uploading the verified data to be verified to a blockchain network for storage, further comprising:

7. The method of claim 1, wherein the data to be verified is audio data and the data acquisition device is an audio acquisition device.

8. The method of claim 1, wherein a smart contract is deployed in the blockchain network, the smart contract for performing the step of data validation.

9. The method of claim 1, the uploading the verified data to be verified to a blockchain network for storage, further comprising:

generating a verifiable statement for proving the trustworthiness of the data to be verified;

and sending the verifiable statement to the blockchain network for storage.

10. The method according to claim 1, wherein the uploading the verified data to be verified into a blockchain network for storage specifically comprises:

encrypting the verified data to be verified, and storing the encrypted data to the blockchain network.

11. A data verification apparatus comprising:

the data to be verified uploading module is used for uploading the data to be verified which passes verification to a blockchain network for storage;

the to-be-verified characteristic value determining module specifically comprises:

A feature point position information and feature value determining unit for determining the position information of the feature point and the feature value of the feature point;

the matrix transformation module is used for determining the position information of the feature points corresponding to the reference feature values, carrying out matrix transformation on the feature points corresponding to the rest feature values in the feature value set according to the positions of the feature points corresponding to the reference feature values, and obtaining the transformed feature values to be verified, wherein the direction of the transformed feature points is the same as the direction of the positions of the feature points corresponding to the reference feature values.

12. The apparatus of claim 11, the data to be verified being video data, the data acquisition device being a camera device; the data acquisition module to be verified specifically comprises:

13. The apparatus of claim 11, the blockchain network having a smart contract deployed therein, the smart contract for performing the step of data validation.

14. The apparatus of claim 11, the apparatus further comprising:

15. The apparatus of claim 11, wherein the data to be verified uploading module specifically comprises:

16. A data verification apparatus comprising:

at least one processor; the method comprises the steps of,

a memory communicatively coupled to the at least one processor; wherein,

uploading the verified data to be verified to a blockchain network for storage;

Selecting a reference feature value from the feature value set;

17. A computer readable medium having stored thereon computer readable instructions executable by a processor to implement the data verification method of any one of claims 1 to 10.