CN111885053B - Data processing method and device based on block chain and computer equipment - Google Patents

Data processing method and device based on block chain and computer equipment Download PDF

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CN111885053B
CN111885053B CN202010710856.3A CN202010710856A CN111885053B CN 111885053 B CN111885053 B CN 111885053B CN 202010710856 A CN202010710856 A CN 202010710856A CN 111885053 B CN111885053 B CN 111885053B
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data
analysis result
service
private key
block
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CN111885053A (en
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章志容
吴联波
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Dongguan Mengda Group Co ltd
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Dongguan Mengda Group Co ltd
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    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L63/00—Network architectures or network communication protocols for network security
    • H04L63/04—Network architectures or network communication protocols for network security for providing a confidential data exchange among entities communicating through data packet networks
    • H04L63/0428—Network architectures or network communication protocols for network security for providing a confidential data exchange among entities communicating through data packet networks wherein the data content is protected, e.g. by encrypting or encapsulating the payload
    • H04L63/0442—Network architectures or network communication protocols for network security for providing a confidential data exchange among entities communicating through data packet networks wherein the data content is protected, e.g. by encrypting or encapsulating the payload wherein the sending and receiving network entities apply asymmetric encryption, i.e. different keys for encryption and decryption
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L41/00—Arrangements for maintenance, administration or management of data switching networks, e.g. of packet switching networks
    • H04L41/14—Network analysis or design
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L41/00—Arrangements for maintenance, administration or management of data switching networks, e.g. of packet switching networks
    • H04L41/14—Network analysis or design
    • H04L41/145—Network analysis or design involving simulating, designing, planning or modelling of a network
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L67/00—Network arrangements or protocols for supporting network services or applications
    • H04L67/01—Protocols
    • H04L67/06—Protocols specially adapted for file transfer, e.g. file transfer protocol [FTP]
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L67/00—Network arrangements or protocols for supporting network services or applications
    • H04L67/01—Protocols
    • H04L67/10—Protocols in which an application is distributed across nodes in the network
    • H04L67/1097—Protocols in which an application is distributed across nodes in the network for distributed storage of data in networks, e.g. transport arrangements for network file system [NFS], storage area networks [SAN] or network attached storage [NAS]
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L67/00—Network arrangements or protocols for supporting network services or applications
    • H04L67/50—Network services
    • H04L67/535—Tracking the activity of the user
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L9/00—Cryptographic mechanisms or cryptographic arrangements for secret or secure communications; Network security protocols
    • H04L9/08—Key distribution or management, e.g. generation, sharing or updating, of cryptographic keys or passwords
    • H04L9/0816—Key establishment, i.e. cryptographic processes or cryptographic protocols whereby a shared secret becomes available to two or more parties, for subsequent use
    • H04L9/0819—Key transport or distribution, i.e. key establishment techniques where one party creates or otherwise obtains a secret value, and securely transfers it to the other(s)
    • H04L9/0825—Key transport or distribution, i.e. key establishment techniques where one party creates or otherwise obtains a secret value, and securely transfers it to the other(s) using asymmetric-key encryption or public key infrastructure [PKI], e.g. key signature or public key certificates
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L9/00—Cryptographic mechanisms or cryptographic arrangements for secret or secure communications; Network security protocols
    • H04L9/50—Cryptographic mechanisms or cryptographic arrangements for secret or secure communications; Network security protocols using hash chains, e.g. blockchains or hash trees

Abstract

The application relates to a data processing method and device based on a block chain and computer equipment. The method comprises the following steps: acquiring service data in a user node and determining the type of the service data; encrypting the service data through a first private key; uploading the encrypted data and the first public key to a service data block corresponding to the type of the service data, and broadcasting to each node in a block chain system, so that a data server in the block chain system decrypts the encrypted data through the first public key, calls a big data analysis model associated with the service data block, and performs data analysis on the service data to obtain a service analysis result; downloading an analysis result message and a second public key which are uploaded by the data server and generated after the business analysis result is encrypted through a second private key from the analysis result block; and decrypting the analysis result message through the second public key to obtain a service analysis result. By adopting the method, the safety of data processing can be improved.

Description

Data processing method and device based on block chain and computer equipment
Technical Field
The present application relates to the field of computer technologies and blockchain technologies, and in particular, to a data processing method and apparatus based on a blockchain, and a computer device.
Background
With the development of computer technology, more and more data are generated in daily life and work, the data are automatically analyzed and processed through a computer, more information is obtained from the data, and great convenience is brought to the life and work of people.
In the conventional technology, data is generally obtained directly from a user side, and then some aspect of analysis is performed on the obtained data. However, directly acquiring data in this way is prone to cause leakage of user data due to network security problems during data transmission, such as: some private information of the user is revealed, thereby reducing the security of data processing.
Disclosure of Invention
In view of the above, it is necessary to provide a block chain based data processing method, apparatus, computer device and storage medium capable of improving security.
A data processing method based on block chain is applied to user nodes in a block chain system; the method comprises the following steps:
collecting service data in the user node and determining the type of the service data;
encrypting the service data through a first private key; the first private key is a private key of the user node;
uploading the encrypted data and a first public key corresponding to the first private key to a service data block corresponding to the type of the service data, and broadcasting the encrypted data and the first public key to each node in the block chain system, so that a data server in the block chain system decrypts the encrypted data through the first public key, calls a big data analysis model associated with the service data block, and performs data analysis on the decrypted service data to obtain a service analysis result;
downloading an analysis result message which is uploaded by the data server and generated after the business analysis result is encrypted through a second private key and a second public key corresponding to the second private key from an analysis result block; the second private key is a private key of the data server;
and decrypting the analysis result message through the second public key to obtain the service analysis result.
In one embodiment, the encrypting the service data by the first private key includes:
encrypting the service data and the account of the user node through a first private key;
the decrypting the analysis result message by the second public key to obtain the service analysis result includes:
decrypting the analysis result message through the second public key to obtain the service analysis result and the account;
after the analyzing result message is decrypted by the second public key to obtain the service analyzing result, the method further includes:
comparing the account obtained by decryption with the account of the user node;
and after the account comparison is passed, performing corresponding application processing on the service analysis result according to the type of the analysis result block.
In one embodiment, the traffic data includes user behavior data; the service analysis result comprises information to be recommended; the information to be recommended is obtained by performing data analysis on the user behavior data by the data server;
the performing, according to the type of the analysis result block, corresponding application processing on the service analysis result includes:
and when the type of the analysis result block is an information recommendation type, pushing the information to be recommended to a front end.
A data processing method is applied to a data server in a block chain system; the method comprises the following steps:
downloading data which is uploaded by a user node in the block chain system and encrypted by a first private key and a first public key corresponding to the first private key from a service data block; the data encrypted by the first private key is obtained by encrypting the acquired service data by the user node through the first private key; the first private key is a private key of the user node;
decrypting the data encrypted by the first private key through the first public key to obtain the service data;
when a big data analysis model associated with the business data block exists, inputting the business data obtained by decryption into the big data analysis model, and outputting a business analysis result;
encrypting the service analysis result through a second private key to generate an analysis result message; the second private key is a private key of the data server;
and uploading the analysis result message and a second public key corresponding to the second private key to an analysis result block, and broadcasting the analysis result message and the second public key to each node in the block chain system, so that the user node decrypts the analysis result message through the second public key after downloading the analysis result message and the second public key from the analysis result block, and obtains a service analysis result.
In one embodiment, after the decrypting, by the first public key, the data encrypted by the first private key to obtain the service data, the method further includes:
storing the service data to a big data middle platform system; the big data middlebox system is a system arranged in the data server;
and respectively optimizing the model parameters of the big data analysis model associated with the business data block from which each business data is downloaded according to the business data historically stored to the big data middling station system.
In one embodiment, the service data comprises user behavior data; the big data analysis model comprises an information recommendation model; the service analysis result comprises information to be recommended;
the step of inputting the service data obtained by decryption into the big data analysis model, and outputting a service analysis result comprises:
and inputting the user behavior data obtained by decryption into the information recommendation model, and outputting the information to be recommended.
A blockchain system, the system comprising at least one user node and at least one data server;
the user node is used for collecting service data in the user node and determining the type of the service data; encrypting the service data through a first private key; uploading the encrypted data and a first public key corresponding to the first private key to a service data block corresponding to the type of the service data, and broadcasting the service data block to each node in the block chain system; the first private key is a private key of the user node;
the data server is used for downloading the encrypted data and the first public key from the service data block; decrypting the encrypted data through the first public key to obtain the service data;
the data server is further used for inputting the service data obtained by decryption into the big data analysis model and outputting a service analysis result when the big data analysis model associated with the service data block exists;
the data server is further used for encrypting the service analysis result through a second private key to generate an analysis result message; uploading the analysis result message and a second public key corresponding to the second private key to an analysis result block, and broadcasting the analysis result message and the second public key to each node in the block chain system; the second private key is a private key of the data server;
the user node is further configured to download the analysis result packet and the second public key from the analysis result block; and decrypting the analysis result message through the second public key to obtain the service analysis result.
A data processing device based on a block chain is arranged in a user node in a block chain system; the device comprises:
the service data acquisition module is used for acquiring service data in the user node and determining the type of the service data;
the first encryption module is used for encrypting the service data through a first private key; the first private key is a private key of the user node;
the first uploading module is used for uploading the encrypted data and a first public key corresponding to the first private key to a service data block corresponding to the type of the service data and broadcasting the first public key to each node in the block chain system, so that a data server in the block chain system decrypts the encrypted data through the first public key, calls a big data analysis model associated with the service data block, and performs data analysis on the service data obtained through decryption to obtain a service analysis result;
the first downloading module is used for downloading an analysis result message which is uploaded by the data server and generated after the business analysis result is encrypted through a second private key and a second public key corresponding to the second private key from the analysis result block; the second private key is a private key of the data server;
and the first decryption module is used for decrypting the analysis result message through the second public key to obtain the service analysis result.
A data processing device based on a block chain is arranged in a data server in a block chain system; the device comprises:
the second downloading module is used for downloading the data which is uploaded by the user node in the block chain system and encrypted by the first private key and the first public key corresponding to the first private key from the service data block; the data encrypted by the first private key is obtained by encrypting the acquired service data by the user node through the first private key; the first private key is a private key of the user node;
the second decryption module is used for decrypting the data encrypted by the first private key through the first public key to obtain the service data;
the data analysis module is used for inputting the service data obtained by decryption into the big data analysis model and outputting a service analysis result when the big data analysis model associated with the service data block exists;
the second encryption module is used for encrypting the service analysis result through a second private key to generate an analysis result message; the second private key is a private key of the data server;
and the second uploading module is used for uploading the analysis result message and a second public key corresponding to the second private key to an analysis result block and broadcasting the analysis result message and the second public key to each node in the block chain system, so that the user node decrypts the analysis result message through the second public key after downloading the analysis result message and the second public key from the analysis result block to obtain a service analysis result.
A computer device comprising a memory and a processor, the memory having stored therein a computer program that, when executed by the processor, causes the processor to perform the steps of the method for blockchain-based data processing according to the embodiments of the present application.
A computer-readable storage medium, on which a computer program is stored, which, when executed by a processor, causes the processor to perform the steps in the method for blockchain-based data processing according to embodiments of the present application.
According to the data processing method, device, computer equipment and storage medium based on the block chain, the user node encrypts and uploads the service data of the user node to the service data block, then the data server downloads and decrypts the data from the service data block, and calls the big data analysis model associated with the service data block to perform data analysis on the service data to obtain a service analysis result, and uploads the service analysis result to the analysis result block after encryption, and the user node downloads and decrypts the data from the analysis result block to obtain the service analysis result. Therefore, data are transmitted in an encryption and decryption mode through a public key and a private key based on the block chain system to process data, the problem of data leakage in the data transmission process can be avoided, and the safety of data processing is improved.
Drawings
FIG. 1 is a diagram of an application environment of a data processing method based on a blockchain in one embodiment;
FIG. 2 is a flow diagram illustrating a method for blockchain-based data processing in one embodiment;
FIG. 3 is a flow chart illustrating a data processing method based on block chains according to another embodiment;
FIG. 4 is a timing diagram of a data processing method based on blockchains in one embodiment;
FIG. 5 is a block diagram of a data processing apparatus based on a blockchain in one embodiment;
FIG. 6 is a block diagram of a data processing apparatus based on a blockchain in another embodiment;
FIG. 7 is a block diagram showing a block chain-based data processing apparatus according to another embodiment;
FIG. 8 is a block diagram showing a block chain-based data processing apparatus according to another embodiment;
FIG. 9 is a diagram showing an internal structure of a computer device in one embodiment;
fig. 10 is an internal structural view of a computer device in another embodiment.
Detailed Description
In order to make the objects, technical solutions and advantages of the present application more apparent, the present application is described in further detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative of the present application and are not intended to limit the present application.
The data processing method based on the block chain can be applied to the application environment shown in fig. 1. The blockchain system in the figure includes at least one user node 102, at least one data server 104, and at least one business system administrator node 106, forming a federation chain. That is, the user node 102, the data server 104, and the service system administrator node 106 are all nodes in the same blockchain system, and the same blockchain system is installed, and after the blockchain system is installed at each node, the blockchain system automatically generates a key pair of the private key and the public key for each node. The user node 102 is a device operated by a user, and a user corresponding to the user node does not define a user role, for example, in an e-commerce scenario, the user corresponding to the user node may include at least one of a seller and a buyer. The data server 104 is a server that performs data analysis on the service data collected by the user node. The service system administrator node 106 is configured to manage the blockchain system, for example, in an e-commerce service scenario, the service system administrator node 106 may be configured to perform shelving of commodity information or maintenance of commodity page information. Specifically, the user node 102 encrypts and uploads collected service data of the user node to a service data block, the data server 104 downloads and decrypts the data from the service data block to obtain service data, the data server 104 inputs the service data into a big data analysis model associated with the service data block to output a service analysis result, and then encrypts and uploads the service analysis result to an analysis result block, and the user node 102 downloads and decrypts the data from the analysis result block to obtain a service analysis result. The business system administrator node 106 is used to manage the blockchain system. The user node 102 may be, but is not limited to, various personal computers, laptops, smartphones, tablets, and portable wearable devices, among others. The data server 104 may be implemented as a stand-alone server or a server cluster composed of a plurality of servers. The business system administrator node 106 can be, but is not limited to, various personal computers, laptops, smartphones, tablets, and portable wearable devices.
In one embodiment, as shown in fig. 2, a data processing method based on a block chain is provided, which is described by taking the method as an example applied to the user node in fig. 1, and includes the following steps:
s202, collecting service data in the user node and determining the type of the service data.
The service data is data generated by various operations performed by the user in the user node. Such as: in the e-commerce scenario, the business data may include at least one of order data generated by a user purchasing goods in the user node, browsing record data generated by browsing the goods, and the like. Such as: and when the service data is order data, the type of the service data is an order. And when the service data is browsing record data, the type of the service data is browsing record.
Specifically, the user node may collect service data generated by various operations performed by the user in the user node, and then determine the type of the service data corresponding to the service data. Such as: the service data collected by the user node is that the user A browses the commodity A and the commodity B, and then the type of the service data corresponding to the service data is a browsing record.
S204, encrypting the service data through a first private key; the first private key is a private key of the user node.
In one embodiment, the user node may encrypt the service data and the account of the user node together through the first private key, so as to be able to clarify the service data as the data collected by the user node.
And S206, uploading the encrypted data and a first public key corresponding to the first private key to a service data block corresponding to the type of the service data, and broadcasting to each node in the block chain system, so that a data server in the block chain system decrypts the encrypted data through the first public key, calls a big data analysis model associated with the service data block, and performs data analysis on the decrypted service data to obtain a service analysis result.
The service data block is a block for storing encrypted service data in the block chain system. The big data analysis model is a machine learning model used for big data analysis of business data. The service analysis result is an analysis result obtained by performing data analysis on the service data.
In one embodiment, the machine learning model employed by the big data analysis model may include at least one of a decision tree model, a cluster analysis model, a neural network model, a timing model, and the like.
In one embodiment, the big data analysis model may be composed of a single model or a plurality of models associated through a data interface.
It can be understood that different types of service data correspond to different service data blocks. Such as: and if the browsing record and the order are different types of business data, the browsing record and the order respectively correspond to different business data blocks. The user node can encrypt and upload the order data and the browsing record data to different service data blocks respectively, that is, encrypt and upload the order data to the service data block corresponding to the order, and encrypt and upload the browsing record data to the service data block corresponding to the browsing record.
Specifically, the user node may upload the encrypted data and the first public key corresponding to the first private key to a service data block corresponding to the type of the service data, and broadcast a new message on the service data block to each node in the block chain system. The data server may download the encrypted data and the first public key from the service data block after receiving a new message on the service data block, and decrypt the encrypted data and the first public key to obtain the service data. The data server can call a big data analysis model associated with the business data block, and perform data analysis on the business data obtained through decryption to obtain a business analysis result.
S208, downloading an analysis result message which is uploaded by the data server and generated after the business analysis result is encrypted through a second private key and a second public key corresponding to the second private key from the analysis result block; the second private key is a private key of the data server.
The analysis result block is a block for storing an analysis result message in the block chain system. The analysis result message is data generated by encrypting the service analysis result through the second private key.
Specifically, the data server may encrypt the service analysis result through the second private key to generate an analysis result message, upload a second public key corresponding to the second private key and the analysis result message to the analysis result block, and broadcast a new message on the analysis result block to each node in the block chain. After receiving the new message on the analysis result block, the user node may download the second public key and the analysis result message from the analysis result block.
S210, the analysis result message is decrypted through the second public key, and a service analysis result is obtained.
Specifically, the user node may decrypt the analysis result packet through the second public key to obtain the service analysis result
In the data processing method based on the block chain, the user node encrypts and uploads the service data of the user node to the service data block, then the data server downloads and decrypts the data from the service data block, and calls a big data analysis model associated with the service data block to perform data analysis on the service data to obtain a service analysis result, and uploads the service analysis result to the analysis result block after being encrypted, and the user node downloads and decrypts the data from the analysis result block to obtain the service analysis result. Therefore, data are transmitted in an encryption and decryption mode through a public key and a private key based on the block chain system to process data, the problem of data leakage in the data transmission process can be avoided, and the safety of data processing is improved. In addition, different types of service data are uploaded to different service data blocks, and different service data can be subjected to different data analysis by performing data analysis on the service data through a big data analysis model associated with the service data blocks, so that the intelligence of data processing is improved, and the information amount in a service analysis result obtained by data processing is increased. Because the blockchain system integrates various big data analysis models, the method can be applied to various scenes needing big data mining and analysis, such as: intelligent marketing or enterprise wind control, and the like.
In an embodiment, the step of encrypting the service data by using the first private key specifically includes the following steps: and encrypting the service data and the account of the user node by the first private key. The step of decrypting the analysis result message through the second public key to obtain the service analysis result specifically comprises the following steps: and decrypting the analysis result message through the second public key to obtain a service analysis result and an account. After the step of decrypting the analysis result message by the second public key to obtain the service analysis result, the method further comprises the following steps: comparing the account obtained by decryption with the account of the user node; and after the account comparison is passed, performing corresponding application processing on the service analysis result according to the type of the analysis result block.
Specifically, the user node encrypts the service data and the account of the user node through a first private key, uploads the encrypted data and the first public key to a service data block corresponding to the type of the service data, and broadcasts a new message on the service data block to each node in the block chain system. The data server may download the encrypted data and the first public key from the service data block after receiving a new message on the service data block, and decrypt the encrypted data and the first public key through the first public key to obtain the service data and the account. The data server can call a big data analysis model associated with the business data block, and perform data analysis on the business data obtained through decryption to obtain a business analysis result. The data server can encrypt the service analysis result and the account through the second private key to generate an analysis result message, upload the analysis result message and the second public key to the analysis result block, and broadcast a new message on the analysis result block to each node in the block chain system. After receiving the new message on the analysis result block, the user node may download the analysis result message and the second public key from the analysis result block, and then decrypt the analysis result message through the second public key to obtain the service analysis result and the account. The user node may compare the account obtained by decryption with the account of the node itself, and perform corresponding application processing on the service analysis result according to the type of the analysis result block after the account comparison passes (that is, the account obtained by decryption is consistent with the account of the node itself).
It can be understood that each user node in the blockchain system downloads the analysis result message and the second public key from the analysis result block, and decrypts the analysis result message and the second public key to obtain the service analysis result and the account. The user node needs to determine whether the service analysis result obtained by decryption after downloading is a service analysis result obtained by performing data analysis on the service data uploaded by the user node through account comparison. And when the account comparison is passed, if the service analysis result is the service analysis result obtained by performing data analysis on the service data uploaded by the user node, performing corresponding application processing on the service analysis result. When the account comparison does not pass (that is, the account obtained by decryption is inconsistent with the account of the node), it is indicated that the service analysis result is a service analysis result obtained by performing data analysis on service data uploaded by other user nodes except the user node in the blockchain system, and therefore, the user node does not perform application processing on the service analysis result.
It is understood that different types of traffic data generate different types of traffic analysis results. Different types of service analysis results are respectively uploaded to different types of analysis result blocks. The different types of analysis result blocks correspond to different types of application processing. Such as: in an e-commerce scene, when the type of the service data is a browsing record, the generated service analysis result can be to-be-recommended commodity information, the to-be-recommended commodity information is uploaded to an analysis result block for storing the to-be-recommended commodity information, application processing corresponding to the analysis result block for storing the to-be-recommended commodity information can be commodity recommendation, and the user node can push the to-be-recommended commodity information to the front end so as to realize commodity recommendation to a user.
In this embodiment, on one hand, the user node may avoid performing application processing on the service analysis result of the non-user node by mistake through account comparison, and on the other hand, the user node may perform corresponding application processing on the service analysis result according to the type of the analysis result block, thereby implementing different application processing on the service analysis result in various aspects.
In one embodiment, the traffic data includes user behavior data. The service analysis result comprises information to be recommended. And the information to be recommended is obtained by carrying out data analysis on the user behavior data by the data server. According to the type of the analysis result block, the step of performing corresponding application processing on the service analysis result specifically comprises the following steps: and when the type of the analysis result block is an information recommendation type, pushing the information to be recommended to the front end.
The user behavior data is data of operation behaviors performed by the user in the user node. Such as: the user behavior data may include data for at least one of browsing, favorites, and likes. The information to be recommended is information which is obtained by the data server performing data analysis on the user behavior data of the user node and needs to be recommended to the user node. The type of the analysis result block is information recommendation type, which means that the analysis result block is a block for storing information to be recommended in a block chain system.
Specifically, when the type of the analysis result block is an information recommendation type, that is, when the service analysis result stored in the analysis result block is to-be-recommended information, the user node downloads data from the analysis result block and decrypts the data to obtain to-be-recommended information and an account, and pushes the to-be-recommended information to the front end after the account comparison is passed.
In one embodiment, in an e-commerce scenario, the user behavior data may include merchandise information corresponding to at least one of browsing, collecting, and joining a shopping cart by the user in the user node. The information to be recommended may include at least one of commodity information or merchant information and the like that needs to be recommended to the user node.
In this embodiment, when the service data includes user behavior data, the generated service analysis result may include information to be recommended, and the user node may push the information to be recommended to the front end, so that personalized information may be intelligently recommended to the user according to the user behavior data, thereby satisfying different requirements of different users.
In one embodiment, as shown in fig. 3, a block chain-based data processing method is provided, which is described by taking the data server in fig. 1 as an example, and includes the following steps:
s302, downloading data which are uploaded by user nodes in a block chain system and encrypted through a first private key and a first public key corresponding to the first private key from a service data block; the data encrypted by the first private key is data obtained by encrypting the collected service data by the user node through the first private key; the first private key is a private key of the user node.
Specifically, the user node may encrypt the service data through the first private key, upload the first public key and the encrypted data to the service data block, and broadcast a new message on the service data block to each node in the blockchain system. The data server may download the encrypted data and the first public key from the service data chunk after receiving a new message on the service data chunk.
In one embodiment, the user node may encrypt the service data together with an account of the user node through the first private key, and upload the first public key and the encrypted data to the service data block.
S304, decrypting the data encrypted by the first private key through the first public key to obtain the service data.
Specifically, the data server decrypts the data encrypted by the first private key through the first public key to obtain the service data.
In one embodiment, the data server decrypts, by using the first public key, the data encrypted by using the first private key, and obtains the service data and an account of the user node corresponding to the service data.
S306, when a big data analysis model associated with the business data block exists, inputting the business data obtained through decryption into the big data analysis model, and outputting a business analysis result.
Specifically, the data server may determine whether there is an associated big data analysis model associated with the service data chunk from which the service data is downloaded. When the big data analysis model associated with the service data block exists, the data server may input the decrypted service data into the big data analysis model, perform data analysis on the service data, and output a service analysis result. When the big data analysis model associated with the service data block does not exist, the data server may not perform the step of inputting the decrypted service data into the big data analysis model, and outputting the service analysis result and the subsequent steps.
In one embodiment, the data server may store the decrypted service data to the big data console system. The big data middle station system is arranged in the data server. The big data middle platform system is provided with a plurality of big data analysis models and is provided with incidence relations between different business data blocks and different big data analysis models. The data server can judge whether a big data analysis model related to a business data block from which the business data is downloaded exists in the big data middlebox system. When a big data analysis model associated with the business data block exists, the data server can input the business data obtained through decryption into the big data analysis model through a big data middling platform system, performs data analysis on the business data, and outputs a business analysis result. When the big data analysis model associated with the service data block does not exist, the data server may not perform the step of inputting the decrypted service data into the big data analysis model, and outputting the service analysis result and the subsequent steps.
For example: in an electric business scene, a user purchases commodities in an electric business system installed in a user node, and the electric business system in the user node automatically uploads order data (namely business data) of the commodities and an account of the user node to a business data block for storing the order data after being encrypted by a first private key and broadcasts the order data. And after receiving the new message on the service data block, the data server node downloads and decrypts the data to obtain order data and an account, and stores the decrypted data into a big data middle platform system of the data server. And the data server judges whether a big data analysis model associated with the business data block from which the order data is downloaded exists or not, and if the big data analysis model does not exist, the data server does not process the order data.
S308, encrypting the service analysis result through a second private key to generate an analysis result message; the second private key is a private key of the data server.
The analysis result message is information which is obtained by encrypting the second private key and needs to be fed back to the user node.
Specifically, the data server may encrypt the service analysis result through the second private key to generate an analysis result message.
In an embodiment, the data server may further encrypt the service analysis result and the account of the user node corresponding to the analyzed service data together by using the second private key to generate an analysis result message, so as to specify the user node corresponding to the analysis result message.
And S310, uploading the analysis result message and a second public key corresponding to the second private key to an analysis result block, and broadcasting to each node in the block chain system, so that the user node decrypts the analysis result message through the second public key after downloading the analysis result message and the second public key from the analysis result block, and obtains a service analysis result.
Specifically, the data server may upload the analysis result message and the second public key to the analysis result block together, and broadcast a new message on the analysis result block to each node in the blockchain system. After receiving the new message on the analysis result block, the user node may download the analysis result message and the second public key from the analysis result block, and then decrypt the analysis result message through the second public key to obtain the service analysis result.
In one embodiment, the user node decrypts the analysis result message through the second public key to obtain the service analysis result and an account of the user node corresponding to the service analysis result. The user node can compare the account obtained by decryption with the account of the user node, and after the account comparison is passed, corresponding application processing is carried out on the service analysis result.
In the data processing method based on the block chain, the user node encrypts and uploads the service data of the user node to the service data block, then the data server downloads and decrypts the data from the service data block, and calls a big data analysis model associated with the service data block to perform data analysis on the service data to obtain a service analysis result, and uploads the service analysis result to the analysis result block after being encrypted, and the user node downloads and decrypts the data from the analysis result block to obtain the service analysis result. Therefore, data are transmitted in an encryption and decryption mode through a public key and a private key based on the block chain system to process data, the problem of data leakage in the data transmission process can be avoided, and the safety of data processing is improved. In addition, different types of service data are uploaded to different service data blocks, and different service data can be subjected to different data analysis by performing data analysis on the service data through a big data analysis model associated with the service data blocks, so that the intelligence of data processing is improved, and the information amount in a service analysis result obtained by data processing is increased. Because the blockchain system integrates various big data analysis models, the method can be applied to various scenes needing big data mining and analysis, such as: intelligent marketing or enterprise wind control, and the like.
In one embodiment, after the step of decrypting, by the first public key, the data encrypted by the first private key to obtain the service data, the method further includes the following steps: storing the service data to a big data middle platform system; the big data middle platform system is a system arranged in the data server; and respectively optimizing the model parameters of the big data analysis model associated with the business data block from which each business data is downloaded according to the business data historically stored to the big data central station system.
The large data middle platform system collects, calculates, stores, processes and the like mass data through a data technology, and unifies a standard system and a caliber system.
Specifically, the data server stores the service data to the big data middle station system each time after downloading the data from the service data block and decrypting the data to obtain the service data. The data server respectively optimizes the model parameters of the big data analysis model associated with the business data block from which each business data is downloaded according to the business data historically stored to the big data middle platform system, so that the business analysis result of the big data analysis model is more accurate.
In this embodiment, the data server may continuously optimize the model parameters of the big data analysis model according to the historical service data stored to the big data console system, thereby improving the accuracy of the service analysis result output by the big data analysis model.
In one embodiment, the traffic data includes user behavior data. The big data analysis model comprises an information recommendation model. The service analysis result comprises information to be recommended. Inputting the decrypted service data into a big data analysis model, and outputting a service analysis result, wherein the method specifically comprises the following steps: and inputting the user behavior data obtained by decryption into an information recommendation model, and outputting information to be recommended.
The information recommendation model is a big data analysis model used for analyzing user behavior data and outputting information to be recommended.
Specifically, when the service data includes user behavior data, the big data analysis model associated with the service data block for storing the user behavior data is an information recommendation model, and the data server may input the user behavior data into the information recommendation model and output information to be recommended.
In one embodiment, in an e-commerce scenario, the user behavior data may include merchandise information corresponding to at least one of browsing, collecting, and joining a shopping cart by the user in the user node. The information to be recommended may include at least one of commodity information or merchant information and the like that needs to be recommended to the user node.
For example: the method comprises the steps that a user browses commodities in an e-commerce service system installed in a user node, the e-commerce service system identifies browsing record data (namely service data) of the user in the user node, the browsing record data and an account of the user node are automatically encrypted, the browsing record data and the account of the user node are uploaded to a service data block used for storing the browsing record data, and the service data block is broadcasted. And after receiving the new message on the service data block, the data server downloads and decrypts the data from the service data block to obtain browsing record data and an account, and stores the decrypted data into a big data middle station system of the data server. The data server judges whether a big data analysis model associated with the business data block from which the browsing record data is downloaded exists or not, if the judgment result is yes, the browsing record data is input into an intelligent recommendation model (namely, a big data analysis model) associated with the business data block for storing the browsing record data, and information of the goods to be recommended (namely, a business analysis result) is output. And the data server encrypts and uploads the commodity information to be recommended and the account obtained by decryption together to an analysis result block for storing the commodity information to be recommended, and broadcasts the encrypted and uploaded commodity information. And after the user node receives the new information on the analysis result block, downloading data from the analysis result block and decrypting the data to obtain the commodity information to be recommended and the account, and after the account comparison is passed, pushing the commodity information to be recommended to the front end by the user node. Thereby realizing intelligent commodity recommendation.
In this embodiment, when the service data includes user behavior data, the service analysis result generated by the data server may include information to be recommended, so that personalized information can be intelligently recommended to the user according to the user behavior data, thereby meeting different requirements of different users.
In an embodiment, as shown in fig. 4, a timing chart of a data processing method based on a block chain is provided, where the timing chart specifically includes the following steps:
s1, the user node collects the service data in the user node and determines the type of the service data;
s2, the user node encrypts the service data through a first private key;
s3, the user node uploads the encrypted data and the first public key to a service data block corresponding to the type of the service data and broadcasts the data and the first public key;
s4, downloading the encrypted data and the first public key from the service data block by the data server;
s5, the data server decrypts the encrypted data through the first public key to obtain service data;
s6, the data server inputs the service data into a big data analysis module associated with the service data block and outputs a service analysis result;
s7, the data server encrypts the service analysis result and the account of the user node corresponding to the service data through a second private key;
s8, the data server uploads the analysis result message and the second public key generated by encryption to an analysis result block and broadcasts the analysis result block;
s9, the user node downloads the analysis result message and the second public key from the analysis result block;
s10, the user node decrypts the analysis result message through the second public key to obtain a service analysis result and an account;
and S11, comparing the accounts by the user node, and applying and processing the service analysis result after the account comparison is passed.
In one embodiment, a blockchain system is provided that includes at least one user node and at least one data server.
The user node is used for collecting service data in the user node and determining the type of the service data; encrypting the service data through a first private key; uploading the encrypted data and a first public key corresponding to the first private key to a service data block corresponding to the type of the service data, and broadcasting the service data block to each node in a block chain system; the first private key is a private key of the user node.
The data server is used for downloading the encrypted data and the first public key from the service data block; and decrypting the encrypted data through the first public key to obtain the service data.
And the data server is also used for inputting the decrypted service data into the big data analysis model and outputting a service analysis result when the big data analysis model associated with the service data block exists.
The data server is also used for encrypting the service analysis result through a second private key to generate an analysis result message; uploading the analysis result message and a second public key corresponding to the second private key to an analysis result block, and broadcasting to each node in the block chain system; the second private key is a private key of the data server.
The user node is also used for downloading the analysis result message and the second public key from the analysis result block; and decrypting the analysis result message through the second public key to obtain a service analysis result.
In one embodiment, the user node is further configured to encrypt the service data and the account of the user node by a first private key.
And the user node is also used for decrypting the analysis result message through the second public key to obtain a service analysis result and an account.
The user node is also used for comparing the account obtained by decryption with the account of the user node; and after the account comparison is passed, performing corresponding application processing on the service analysis result according to the type of the analysis result block.
In one embodiment, the traffic data includes user behavior data. The service analysis result comprises information to be recommended. And the information to be recommended is obtained by carrying out data analysis on the user behavior data by the data server. And the user node is also used for pushing the information to be recommended to the front end when the type of the analysis result block is the information recommendation type.
In one embodiment, the data server is further configured to store the service data to a big data middlebox system; the big data middle platform system is a system arranged in the data server; and respectively optimizing the model parameters of the big data analysis model associated with the business data block from which each business data is downloaded according to the business data historically stored to the big data central station system.
In one embodiment, the traffic data includes user behavior data. The big data analysis model comprises an information recommendation model. The service analysis result comprises information to be recommended. The data server is also used for inputting the user behavior data obtained by decryption into the information recommendation model and outputting the information to be recommended.
It should be understood that although the steps in the flowcharts of fig. 2 and 3 are shown in order as indicated by the arrows, the steps are not necessarily performed in order as indicated by the arrows. The steps are not performed in the exact order shown and described, and may be performed in other orders, unless explicitly stated otherwise. Moreover, at least some of the steps in fig. 2 and 3 may include multiple steps or multiple stages, which are not necessarily performed at the same time, but may be performed at different times, which are not necessarily performed in sequence, but may be performed in turn or alternately with other steps or at least some of the other steps.
In one embodiment, as shown in fig. 5, there is provided a data processing apparatus 500 based on a blockchain, the apparatus being disposed in a user node in a blockchain system, the apparatus including: a service data acquisition module 502, a first encryption module 504, a first upload module 506, a first download module 508, and a first decryption module 510, wherein:
the service data acquisition module 502 is configured to acquire service data in a user node and determine the type of the service data.
A first encryption module 504, configured to encrypt the service data with a first private key; the first private key is a private key of the user node.
The first uploading module 506 is configured to upload the encrypted data and a first public key corresponding to the first private key to a service data block corresponding to the type of the service data, and broadcast the first public key to each node in the block chain system, so that a data server in the block chain system decrypts the encrypted data through the first public key, and then invokes a big data analysis model associated with the service data block to perform data analysis on the decrypted service data, thereby obtaining a service analysis result.
A first downloading module 508, configured to download, from the analysis result block, an analysis result message that is uploaded by the data server and generated by encrypting the service analysis result through the second private key, and a second public key corresponding to the second private key; the second private key is a private key of the data server.
The first decryption module 510 is configured to decrypt the analysis result packet through the second public key to obtain a service analysis result.
In one embodiment, the first encryption module 504 is further configured to encrypt the service data and the account of the user node by a first private key. The first decryption module 510 is further configured to decrypt the analysis result packet through the second public key to obtain a service analysis result and an account.
In one embodiment, as shown in fig. 6, the block chain based data processing apparatus 500 further includes:
the application processing module 512 is configured to compare the account obtained by decryption with an account of the user node; and after the account comparison is passed, performing corresponding application processing on the service analysis result according to the type of the analysis result block.
In one embodiment, the traffic data includes user behavior data. The service analysis result comprises information to be recommended. And the information to be recommended is obtained by carrying out data analysis on the user behavior data by the data server. The application processing module 512 is further configured to push information to be recommended to the front end when the type of the analysis result block is the information recommendation type.
In one embodiment, as shown in fig. 7, there is provided a blockchain-based data processing apparatus 700 disposed in a data server in a blockchain system, the apparatus including: a second download module 702, a second decryption module 704, a data analysis module 706, a second encryption module 708, and a second upload module 710, wherein:
a second downloading module 702, configured to download, from the service data block, data encrypted by the first private key and uploaded by the user node in the block chain system, and a first public key corresponding to the first private key; the data encrypted by the first private key is data obtained by encrypting the collected service data by the user node through the first private key; the first private key is a private key of the user node.
The second decryption module 704 is configured to decrypt, through the first public key, the data encrypted by the first private key to obtain the service data.
And the data analysis module 706 is configured to, when a big data analysis model associated with the service data block exists, input the decrypted service data into the big data analysis model, and output a service analysis result.
The second encryption module 708 is configured to encrypt the service analysis result by using a second private key, so as to generate an analysis result message; the second private key is a private key of the data server.
The second uploading module 710 is configured to upload the analysis result packet and a second public key corresponding to the second private key to the analysis result block, and broadcast the analysis result packet and the second public key to each node in the block chain system, so that the user node decrypts the analysis result packet and the second public key from the analysis result block, and obtains a service analysis result.
In one embodiment, as shown in fig. 8, the data processing apparatus 700 further includes:
the model optimization module 712 is used for storing the service data to a big data middle platform system; the big data middle platform system is a system arranged in the data server; and respectively optimizing the model parameters of the big data analysis model associated with the business data block from which each business data is downloaded according to the business data historically stored to the big data central station system.
In one embodiment, the traffic data includes user behavior data. The big data analysis model includes an information recommendation model. The service analysis result comprises information to be recommended. The data analysis module 706 is further configured to input the decrypted user behavior data into the information recommendation model, and output information to be recommended.
In the data processing device based on the block chain, the user node encrypts and uploads the service data of the user node to the service data block, then the data server downloads and decrypts the data from the service data block, and calls a big data analysis model associated with the service data block to perform data analysis on the service data to obtain a service analysis result, and uploads the service analysis result to the analysis result block after being encrypted, and the user node downloads and decrypts the data from the analysis result block to obtain the service analysis result. Therefore, data are transmitted in an encryption and decryption mode through a public key and a private key based on the block chain system to process data, the problem of data leakage in the data transmission process can be avoided, and the safety of data processing is improved. In addition, different types of service data are uploaded to different service data blocks, and different service data can be subjected to different data analysis by performing data analysis on the service data through a big data analysis model associated with the service data blocks, so that the intelligence of data processing is improved, and the information amount in a service analysis result obtained by data processing is increased. Because the blockchain system integrates various big data analysis models, the method can be applied to various scenes needing big data mining and analysis, such as: intelligent marketing or enterprise wind control, and the like.
For specific definition of the data processing apparatus based on the blockchain, reference may be made to the above definition of the data processing method based on the blockchain, and details are not described here. The respective modules in the above block chain-based data processing apparatus may be wholly or partially implemented by software, hardware, and a combination thereof. The modules can be embedded in a hardware form or independent of a processor in the computer device, and can also be stored in a memory in the computer device in a software form, so that the processor can call and execute operations corresponding to the modules.
In one embodiment, a computer device is provided, which may be a terminal, and its internal structure diagram may be as shown in fig. 9. The computer device includes a processor, a memory, a communication interface, a display screen, and an input device 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 comprises a nonvolatile storage medium and an internal memory. The non-volatile storage medium stores an operating system and a computer program. The internal memory provides an environment for the operation of an operating system and computer programs in the non-volatile storage medium. The communication interface of the computer device is used for communicating with an external terminal in a wired or wireless manner, and the wireless manner can be realized through WIFI, an operator network, NFC (near field communication) or other technologies. The computer program is executed by a processor to implement a block chain based data processing method. The display screen of the computer equipment can be a liquid crystal display screen or an electronic ink display screen, and the input device of the computer equipment can be a touch layer covered on the display screen, a key, a track ball or a touch pad arranged on the shell of the computer equipment, an external keyboard, a touch pad or a mouse and the like.
In one embodiment, a computer device is provided, which may be a server, and its internal structure diagram may be as shown in fig. 10. 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 comprises a nonvolatile storage medium and an internal memory. The non-volatile storage medium stores an operating system, a computer program, and a database. The internal memory provides an environment for the operating system and the computer program to run on the non-volatile storage medium. The database of the computer device is used for storing business data. The network interface of the computer device is used for communicating with an external terminal through a network connection. The computer program is executed by a processor to implement a block chain based data processing method.
Those skilled in the art will appreciate that the configurations shown in fig. 9 and 10 are merely block diagrams of some configurations relevant to the present disclosure, and do not constitute a limitation on the computing devices to which the present disclosure may be applied, and that a particular computing device may include more or less components than those shown, or combine certain components, or have a different arrangement of components.
In one embodiment, a computer device is further provided, which includes a memory and a processor, the memory stores a computer program, and the processor implements the steps of the above method embodiments when executing the computer program.
In an embodiment, a computer-readable storage medium is provided, on which a computer program is stored which, when being executed by a processor, carries out the steps of the above-mentioned method embodiments.
It will be understood by those skilled in the art that all or part of the processes of the methods of the embodiments described above can be implemented by hardware instructions of a computer program, which can be stored in a non-volatile computer-readable storage medium, and when executed, can include the processes of the embodiments of the methods described above. Any reference to memory, storage, database or other medium used in the embodiments provided herein can include at least one of non-volatile and volatile memory. Non-volatile Memory may include Read-Only Memory (ROM), magnetic tape, floppy disk, flash Memory, optical storage, or the like. Volatile Memory can include Random Access Memory (RAM) or external cache Memory. By way of illustration and not limitation, RAM can take many forms, such as Static Random Access Memory (SRAM) or Dynamic Random Access Memory (DRAM), for example.
All possible combinations of the technical features in the above embodiments may not be described for the sake of brevity, but should be considered as being within the scope of the present disclosure as long as there is no contradiction between the combinations of the technical features.
The above-mentioned embodiments only express several embodiments of the present application, and the description thereof is more specific and detailed, but not construed as limiting the scope of the invention. It should be noted that, for a person skilled in the art, several variations and modifications can be made without departing from the concept of the present application, which falls within the scope of protection of the present application. Therefore, the protection scope of the present patent shall be subject to the appended claims.

Claims (10)

1. A data processing method based on block chain is characterized in that the method is applied to user nodes in a block chain system; the method comprises the following steps:
collecting service data in the user node and determining the type of the service data;
encrypting the service data through a first private key; the first private key is a private key of the user node;
uploading encrypted data and a first public key corresponding to the first private key to a service data block corresponding to the type of the service data, and broadcasting a new message on the service data block to each node in the block chain system, so that after a data server in the block chain system decrypts the encrypted data through the first public key, the data server calls a big data analysis model associated with the service data block, and performs data analysis on the service data obtained by decryption to obtain a service analysis result;
downloading an analysis result message which is uploaded by the data server and generated after the business analysis result is encrypted through a second private key and a second public key corresponding to the second private key from an analysis result block; the second private key is a private key of the data server;
and decrypting the analysis result message through the second public key to obtain the service analysis result.
2. The method of claim 1, wherein the encrypting the traffic data with the first private key comprises:
encrypting the service data and the account of the user node through a first private key;
the decrypting the analysis result packet by the second public key to obtain the service analysis result includes:
decrypting the analysis result message through the second public key to obtain the service analysis result and the account;
after the analyzing result message is decrypted by the second public key to obtain the service analyzing result, the method further includes:
comparing the account obtained by decryption with the account of the user node;
and after the account comparison is passed, performing corresponding application processing on the service analysis result according to the type of the analysis result block.
3. The method of claim 2, wherein the traffic data comprises user behavior data; the service analysis result comprises information to be recommended; the information to be recommended is obtained by performing data analysis on the user behavior data by the data server;
the performing, according to the type of the analysis result block, corresponding application processing on the service analysis result includes:
and when the type of the analysis result block is an information recommendation type, pushing the information to be recommended to a front end.
4. A data processing method is characterized in that the method is applied to a data server in a block chain system; the method comprises the following steps:
downloading data which is uploaded by a user node in the block chain system and encrypted by a first private key and a first public key corresponding to the first private key from a service data block; the data encrypted by the first private key is obtained by encrypting the acquired service data by the user node through the first private key; the first private key is a private key of the user node;
decrypting the data encrypted by the first private key through the first public key to obtain the service data;
when a big data analysis model associated with the business data block exists, inputting the business data obtained by decryption into the big data analysis model, and outputting a business analysis result;
encrypting the service analysis result through a second private key to generate an analysis result message; the second private key is a private key of the data server;
and uploading the analysis result message and a second public key corresponding to the second private key to an analysis result block, and broadcasting the analysis result message and the second public key to each node in the block chain system, so that the user node decrypts the analysis result message through the second public key after downloading the analysis result message and the second public key from the analysis result block, and obtains a service analysis result.
5. The method according to claim 4, wherein after the decrypting the data encrypted by the first private key by the first public key to obtain the service data, the method further comprises:
storing the service data to a big data middle platform system; the big data middlebox system is a system arranged in the data server;
and respectively optimizing model parameters of the big data analysis model associated with the business data block from which each business data is downloaded according to the business data historically stored to the big data middle station system.
6. The method of claim 4, wherein the traffic data comprises user behavior data; the big data analysis model comprises an information recommendation model; the service analysis result comprises information to be recommended;
the step of inputting the service data obtained by decryption into the big data analysis model, and outputting a service analysis result comprises:
and inputting the user behavior data obtained by decryption into the information recommendation model, and outputting the information to be recommended.
7. A blockchain system, the system comprising at least one user node and at least one data server;
the user node is used for collecting service data in the user node and determining the type of the service data; encrypting the service data through a first private key; uploading the encrypted data and a first public key corresponding to the first private key to a service data block corresponding to the type of the service data, and broadcasting a new message on the service data block to each node in the block chain system; the first private key is a private key of the user node;
the data server is used for downloading the encrypted data and the first public key from the service data block; decrypting the encrypted data through the first public key to obtain the service data;
the data server is further used for inputting the service data obtained by decryption into the big data analysis model and outputting a service analysis result when the big data analysis model associated with the service data block exists;
the data server is further used for encrypting the service analysis result through a second private key to generate an analysis result message; uploading the analysis result message and a second public key corresponding to the second private key to an analysis result block, and broadcasting the analysis result message and the second public key to each node in the block chain system; the second private key is a private key of the data server;
the user node is further configured to download the analysis result packet and the second public key from the analysis result block; and decrypting the analysis result message through the second public key to obtain the service analysis result.
8. A data processing apparatus based on a blockchain, wherein the apparatus is disposed in a user node in a blockchain system; the device comprises:
the service data acquisition module is used for acquiring service data in the user node and determining the type of the service data;
the first encryption module is used for encrypting the service data through a first private key; the first private key is a private key of the user node;
the first uploading module is used for uploading the encrypted data and a first public key corresponding to the first private key to a service data block corresponding to the type of the service data, and broadcasting a new message on the service data block to each node in the block chain system, so that after a data server in the block chain system decrypts the encrypted data through the first public key, the data server calls a big data analysis model associated with the service data block, and performs data analysis on the service data obtained by decryption to obtain a service analysis result;
the first downloading module is used for downloading an analysis result message which is uploaded by the data server and generated after the business analysis result is encrypted through a second private key and a second public key corresponding to the second private key from the analysis result block; the second private key is a private key of the data server;
and the first decryption module is used for decrypting the analysis result message through the second public key to obtain the service analysis result.
9. A data processing device based on a block chain is characterized in that the device is arranged in a data server in a block chain system; the device comprises:
the second downloading module is used for downloading the data which is uploaded by the user node in the block chain system and encrypted by the first private key and the first public key corresponding to the first private key from the service data block; the data encrypted by the first private key is obtained by encrypting the acquired business data generated by the user operation by the user node through the first private key; the first private key is a private key of the user node;
the second decryption module is used for decrypting the data encrypted by the first private key through the first public key to obtain the service data;
the data analysis module is used for inputting the service data obtained by decryption into the big data analysis model and outputting a service analysis result when the big data analysis model associated with the service data block exists;
the second encryption module is used for encrypting the service analysis result through a second private key to generate an analysis result message; the second private key is a private key of the data server;
and the second uploading module is used for uploading the analysis result message and a second public key corresponding to the second private key to an analysis result block and broadcasting the analysis result block and the second public key to each node in the block chain system, so that the user node decrypts the analysis result message through the second public key after downloading the analysis result message and the second public key from the analysis result block to obtain a service analysis result.
10. A computer device comprising a memory and a processor, the memory storing a computer program, characterized in that the processor, when executing the computer program, implements the steps of the method of any of claims 1 to 6.
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