CN111639363B

CN111639363B - Data analysis method based on block chain and edge computing server

Info

Publication number: CN111639363B
Application number: CN202010445548.2A
Authority: CN
Inventors: 石高峰
Original assignee: Shenzhen Chengxin Technology Co Ltd
Current assignee: Shenzhen Chengxin Technology Co., Ltd
Priority date: 2020-05-24
Filing date: 2020-05-24
Publication date: 2020-12-25
Anticipated expiration: 2040-05-24
Also published as: CN112380569A; CN112380570A; CN111639363A

Abstract

The application relates to a data analysis method based on a block chain and an edge computing server. According to the method, firstly, safety verification is carried out between each block chain link point device, when the verification is passed, a target block chain link point device is determined according to a target log of the block chain link point device, then a communication record list of the target block chain link point device is periodically obtained, the communication record list is analyzed to obtain an analysis result, and finally data in a database of the target block chain link point device are classified according to the analysis result to obtain first-class service data and second-class service data. Therefore, the data of the target block chain node equipment can be classified, the block chain node equipment is indicated to encrypt the first class of service data, excessive operation resources consumed by the block chain node equipment for encrypting all the service data are avoided, and the service processing efficiency of the block chain node equipment is improved.

Description

Data analysis method based on block chain and edge computing server

Technical Field

The present application relates to the field of blockchain data processing technologies, and in particular, to a data analysis method and an edge calculation server based on a blockchain.

Background

Nowadays, the application of blockchain technology has been extended to a plurality of key fields such as digital finance, internet of things, intelligent manufacturing, supply chain management and digital asset transaction. The advantages of 'distributed' and 'non-falsification' attached to the block chain technology can effectively improve the interaction efficiency of digital information and reduce the maintenance cost of a communication network. However, in practical applications, when node devices in a block chain interact with each other, the service data corresponding to each node device is deeply encrypted according to the principle of cryptography, so that excessive computing resources of the node devices in the block chain are consumed, and the service processing efficiency of the node devices in the block chain is reduced.

Disclosure of Invention

The application provides a data analysis method based on a block chain and an edge calculation server, so as to solve the technical problems in the prior art.

According to a first aspect of embodiments of the present application, there is provided a block chain-based data analysis method applied to an edge computing server in communication with a plurality of block chain link point devices communicating with each other, the method including:

determining interface information of each block link point device from the obtained access request of each block link point device, generating a target dynamic random number and a target agreed key according to the interface information and the mac address of the corresponding block link point device, verifying and calculating the generated access request for accessing the database of the block link point device by using the target dynamic random number and the target agreed key to obtain a first verification result, and sending the first verification result and the access request to each block link point device; wherein the check result is a CRC check result;

when receiving confirmation information sent by each block chain node device when judging that a second check result obtained by carrying out check calculation on the access request according to the interface information and the mac address of the block chain is consistent with the received first check result, calling a target log of the block chain node device from a database of each block chain node device; the target log is a log obtained by encrypting data in a database by using a block chain node device;

analyzing each target log to obtain an operation resource allocation record of the block chain node equipment corresponding to the target log; if the occupancy rate of the operation resource for performing encryption operation represented by the operation resource allocation record reaches a set rate, determining the block chain node point equipment corresponding to the operation resource allocation record as target block chain node point equipment;

periodically acquiring a communication record list of target block chain node equipment, and analyzing the communication record list to obtain an analysis result;

classifying data in a database of the target block link node equipment according to the analysis result to obtain first-class service data and second-class service data; the first type of service data is privacy service data of the target block node point equipment, and the second type of service data is process service data and/or redundant data of the target block node point equipment.

Optionally, the periodically obtaining a communication record list of the target block link point device includes:

determining the real-time accumulated quantity of other block chain link point devices with effective communication behaviors with the target block chain node device;

and determining an acquisition time interval of the communication record list according to the real-time accumulated quantity, and acquiring the communication record list of the target block chain node equipment according to the acquisition time interval.

Optionally, determining an obtaining duration interval of the communication record list according to the real-time accumulated quantity includes:

and determining the time interval corresponding to the real-time accumulated quantity according to a preset relation list.

Optionally, parsing the communication record list to obtain a parsing result includes:

determining at least one piece of first recording information in the communication recording list and registration information of a first block link point device corresponding to the at least one piece of first recording information, wherein the registration information is used for indicating whether the first block link point device is in a link conduction state or not;

extracting the equipment information of the at least one piece of first recorded information to obtain at least two pieces of second block chain link point equipment corresponding to the first block chain link point equipment, wherein the equipment information extraction comprises at least one of equipment identification extraction, equipment model determination and equipment state detection;

performing communication interaction frequency statistics on the at least one piece of first recording information and the at least two pieces of second block chain node point equipment to obtain at least two groups of communication interaction frequencies with different communication time periods corresponding to each piece of first block chain node point equipment and each piece of second block chain node point equipment;

extracting a communication protocol of the target block chain node device based on at least two groups of communication interaction frequencies with different communication time periods to obtain a communication protocol message of the target block chain node device, wherein the communication protocol message comprises a first message sequence between the target block chain node device and the first block chain node device and a second message sequence between the target block chain node device and the second block chain node device;

acquiring a field attribute value of any message field of the first message sequence, and determining a message field with the minimum message authority in the second message sequence as a reference message field; mapping the field attribute value to the reference message field according to the time efficiency description information corresponding to the registration information to obtain a mapping attribute value in the reference message field, and generating first communication thread information between the target block chain node device and the first block chain link point device and second communication thread information between the target block chain link point device and the second block chain link point device according to the field attribute value and the mapping attribute value; the first communication thread information and the second communication thread information both include identification information of a data traffic packet corresponding to the target block link node device.

Optionally, classifying data in the database of the target blockchain node device according to the analysis result to obtain first-class service data and second-class service data, including:

listing first identification information of a first data traffic packet corresponding to the target block chain node point device in the first communication thread information, listing second identification information of a second data traffic packet corresponding to the target block chain node point device in the second communication thread information, and inputting the first identification information and the second identification information into a trained convolutional neural network to obtain an identification information set;

acquiring identification logic information and each third identification information of the identification information set; if the identification information set contains the associated identification category based on the identification logic information, determining a first clustering coefficient between each piece of third identification information of the identification information set under the independent identification category and each piece of third identification information of the identification information set under the associated identification category according to the third identification information of the identification information set under the associated identification category and the identification authority level of the third identification information; adjusting third identification information meeting preset clustering conditions between the third identification information of the identification information set under the independent identification category and the third identification information of the identification information set under the associated identification category to be under the associated identification category according to the first clustering coefficient;

if the independent identification category corresponding to the identification information set comprises a plurality of pieces of third identification information, determining a second clustering coefficient between the pieces of third identification information of the identification information set in the independent identification category based on the pieces of third identification information of the identification information set in the associated identification category and the identification permission levels thereof, and clustering the pieces of third identification information of the independent identification category corresponding to the identification information set according to the clustering coefficient between the pieces of third identification information to obtain a plurality of pieces of fourth identification information;

setting classification weight for each fourth identification information according to the third identification information and the identification permission level of the identification information set under the associated identification category, sorting the fourth identification information according to the descending order of the classification weight to obtain an identification information sorting sequence, and adjusting a set number of fourth identification information in the identification information sorting sequence, which is sorted in the front, to the associated identification category;

and classifying data in a database of the target block link node equipment according to the data traffic packet corresponding to the identification information under the associated identification category and the data traffic packet corresponding to the identification information under the independent identification category to obtain the first-class service data and the second-class service data.

Optionally, classifying data in the database of the target block link node device according to the data traffic packet corresponding to the identification information in the associated identification category and the data traffic packet corresponding to the identification information in the independent identification category to obtain the first type of service data and the second type of service data, including:

acquiring a first data set determined in the database based on a data traffic packet corresponding to the identification information under the associated identification category and a second data set determined in the database based on a data traffic packet corresponding to the identification information under the independent identification category;

determining a first updating frequency of the first data set in a preset time period based on a first accumulated updating time of the first data set in the preset time period and a second accumulated updating time of the second data set in the preset time period;

determining a second updating frequency of the second data set between two adjacent preset time periods according to the updating frequencies of the first data set in the two adjacent preset time periods;

and determining the data with the first updating frequency larger than a first set threshold value in the database as the first type of service data, and determining the data with the second updating frequency smaller than a second set threshold value in the database as the second type of service data.

Optionally, the method further comprises:

acquiring a target instruction for modifying the first set threshold and the second set threshold;

and modifying the first set threshold and the second set threshold according to the target instruction.

According to a second aspect of embodiments of the present application, there is provided an edge computing server in communication with a plurality of block-linked point devices in communication with each other, the edge computing server configured to:

According to a third aspect of embodiments of the present application, there is provided an edge computing server, including: the system comprises a processor, a memory and a network interface, wherein the memory and the network interface are connected with the processor; the network interface is connected with a nonvolatile memory in the edge computing server; when the processor is operated, the computer program is called from the nonvolatile memory through the network interface, and the computer program is operated through the memory so as to execute the method.

According to a fourth aspect of the embodiments of the present application, a readable storage medium applied to a computer is provided, where a computer program is burned in the readable storage medium, and the computer program implements the method when running in a memory of an edge computing server.

When the data analysis method based on the block chain and the edge computing server are applied, firstly, safety verification is conducted between each access request of each block chain link point device and each block chain link point device, when the safety verification is passed, a target log is called from each block chain node device to determine a target block chain node device according to the target log, then a communication record list of the target block chain link point device is periodically obtained and analyzed to obtain an analysis result, and finally data in a database of the target block chain node device are classified according to the analysis result to obtain first-type service data and second-type service data. It can be understood that the first type of service data is privacy service data of the target block link node device, and the second type of service data is process service data and/or redundant data of the target block link node device. Therefore, the data of the target block chain node equipment can be classified, the block chain node equipment is indicated to encrypt the first class of service data, excessive operation resources consumed by the block chain node equipment for encrypting all the service data are avoided, and the service processing efficiency of the block chain node equipment is improved.

It is to be understood that both the foregoing general description and the following detailed description are exemplary and explanatory only and are not restrictive of the application.

Drawings

The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the present application and together with the description, serve to explain the principles of the application.

Fig. 1 is a communication architecture diagram of a data analysis system based on a blockchain according to an exemplary embodiment of the present application.

Fig. 2 is a flow chart illustrating a method for blockchain-based data analysis according to an exemplary embodiment of the present application.

Fig. 3 is a block diagram illustrating an embodiment of a blockchain-based data analysis apparatus according to an exemplary embodiment of the present application.

Fig. 4 is a hardware configuration diagram of an edge computing server where the data analysis device based on the blockchain according to the present invention is located.

Detailed Description

Reference will now be made in detail to the exemplary embodiments, examples of which are illustrated in the accompanying drawings. When the following description refers to the accompanying drawings, like numbers in different drawings represent the same or similar elements unless otherwise indicated. The embodiments described in the following exemplary embodiments do not represent all embodiments consistent with the present application. Rather, they are merely examples of apparatus and methods consistent with certain aspects of the present application, as detailed in the appended claims.

The terminology used herein is for the purpose of describing particular embodiments only and is not intended to be limiting of the application. As used in this application and the appended claims, the singular forms "a", "an", and "the" are intended to include the plural forms as well, unless the context clearly indicates otherwise. It should also be understood that the term "and/or" as used herein refers to and encompasses any and all possible combinations of one or more of the associated listed items.

It is to be understood that although the terms first, second, third, etc. may be used herein to describe various information, such information should not be limited to these terms. These terms are only used to distinguish one type of information from another. For example, first information may also be referred to as second information, and similarly, second information may also be referred to as first information, without departing from the scope of the present application. The word "if" as used herein may be interpreted as "at … …" or "when … …" or "in response to a determination", depending on the context.

The inventor researches and analyzes the block chain node point equipment applied to a plurality of fields, and finds that the block chain node point equipment can encrypt all stored service data in a service mode. For some process data with low feature degree and identification degree or some redundant data without traceability generated during the operation of equipment, if the data is also encrypted, the operation resources of the block chain node equipment can be greatly occupied.

In order to solve the above problem, the service data stored in each blockchain node device needs to be analyzed to determine the flow data and the redundant data, so as to instruct the blockchain node device to bypass the flow data and the redundant data when encrypting data. Therefore, the embodiments of the present invention provide a block chain-based data analysis method and an edge calculation server, so as to analyze service data in each block chain node device in a block chain, thereby implementing classification of the service data and avoiding excessive consumption of computing resources due to encryption of all service data by the block chain node device.

In order to better understand the data analysis method based on the blockchain disclosed in the present application, a data analysis system used in the embodiment of the present application is first described, as shown in fig. 1, which is a schematic connection diagram of a communication architecture of the data analysis system 100 based on the blockchain provided in the embodiment of the present invention, the data analysis system 100 may include an edge computing server 200 and a plurality of blockchain node devices 300 that communicate with each other. The multiple block-link node device 300 can be applied to multiple business scenarios, such as internet of things, smart cities, smart manufacturing, smart medical and supply chain management, and the like, and is not limited herein.

Further, referring to fig. 2, a data analysis method applicable to the edge computing server 200 shown in fig. 1 is provided in the embodiment of the present invention, and the data analysis method may include the following steps S21-S25.

Step S21, determining interface information of each block link point device from the obtained access request of each block link node device, generating a target dynamic random number and a target agreed key according to the interface information and the mac address of the corresponding block link point device, performing a verification calculation on the generated access request for accessing the database of the block link point device by using the target dynamic random number and the target agreed key to obtain a first verification result, and sending the first verification result and the access request to each block link point device.

In this embodiment, the mac address of the block-link point device may be obtained when the block-link point device communicates with the edge calculation server, and the check result may be a CRC check result.

Step S22, when receiving confirmation information sent by each blockchain node device when determining that the second check result obtained by performing the check calculation on the access request according to the interface information and the mac address of the blockchain is consistent with the received first check result, retrieving the target log of the blockchain node device from the database of each blockchain node device.

In this embodiment, the target log is a log in which the block link point device encrypts data in the database.

Through steps S21 to S22, security check between the edge calculation server 200 and the blockchain node device 300 can be realized, the blockchain node device 300 is prevented from exposing the interface of the database at will, and data security of the blockchain node device 300 can be ensured.

Step S23, analyzing each target log to obtain the operation resource distribution record of the block chain node point device corresponding to the target log; and if the occupancy rate of the operation resource for performing encryption operation represented by the operation resource allocation record reaches a set rate, determining the block chain node equipment corresponding to the operation resource allocation record as target block chain node equipment.

In this embodiment, the calculation resource allocation record is updated in the target log in real time. The set ratio can be adjusted according to the equipment parameters of the block link point equipment, and is not limited herein. When the occupancy rate of the computing resources for encryption operation reaches a set rate, the device representing the block-linked nodes allocates excessive computing resources for data encryption, and in this case, the computing resources of the block-linked node device need to be reallocated through data classification. The data classification of the tile link point device may refer to steps S24 and S25.

Step S24, periodically obtain a communication record list of the target block link point device, and analyze the communication record list to obtain an analysis result.

Step S25, classifying the data in the database of the target block link node device according to the analysis result to obtain first-class service data and second-class service data.

In this embodiment, the first type of service data is privacy service data of the target block node device, and the second type of service data is process service data and/or redundant data of the target block node device.

When the contents described in the above steps S21 to S25 are executed, firstly, security check is performed between each block link point device and each access request of each block link point device, and when the check passes, a target log is called from each block link node device to determine a target block link node device according to the target log, then a communication record list of the target block link point device is periodically obtained and analyzed to obtain an analysis result, and finally, data in a database of the target block link node device is classified according to the analysis result to obtain first-type service data and second-type service data. It can be understood that the first type of service data is privacy service data of the target block link node device, and the second type of service data is process service data and/or redundant data of the target block link node device. Therefore, the data of the target block chain node equipment can be classified, the block chain node equipment is indicated to encrypt the first class of service data, excessive operation resources consumed by the block chain node equipment for encrypting all the service data are avoided, and the service processing efficiency of the block chain node equipment is improved.

In practical implementation, the inventors found that, in order to ensure the accuracy of the analysis result, the registration information of other block-link point devices in the communication record list and the interaction frequency between the other block-link point devices and the target block-link point device need to be considered. In order to achieve the above purpose, in step S24, the parsing of the communication record list to obtain a parsing result may specifically include the contents described in the following steps S241 to S245.

Step S241, determining at least one piece of first recording information in the communication recording list and registration information of a first block link point device corresponding to the at least one piece of first recording information, where the registration information is used to indicate whether the first block link point device is in a link conducting state.

Step S242, performing device information extraction on the at least one piece of first recorded information to obtain at least two second block link point devices corresponding to the first block link point device, where the device information extraction includes at least one of device identifier extraction, device model determination, and device state detection.

Step S243, performing communication interaction frequency statistics on the at least one piece of first record information and the at least two second block chain node point devices to obtain at least two groups of communication interaction frequencies with different communication time periods corresponding to each of the first block chain node point devices and the second block chain node point devices.

Step S244, performing communication protocol extraction on the target block chain node device based on at least two groups of communication interaction frequencies with different communication time periods to obtain a communication protocol packet of the target block chain node device, where the communication protocol packet includes a first packet sequence between the target block chain node device and the first block chain node device and a second packet sequence between the target block chain node device and the second block chain node device.

Step S245, acquiring a field attribute value of any message field of the first message sequence, and determining the message field with the minimum message authority in the second message sequence as a reference message field; mapping the field attribute value to the reference message field according to the time efficiency description information corresponding to the registration information to obtain a mapping attribute value in the reference message field, and generating first communication thread information between the target block chain node device and the first block chain link point device and second communication thread information between the target block chain link point device and the second block chain link point device according to the field attribute value and the mapping attribute value; the first communication thread information and the second communication thread information both include identification information of a data traffic packet corresponding to the target block link node device.

It can be understood that, through the steps S241 to S245, the registration information of other block link point devices in the communication record list and the interaction frequency of the other block link point devices and the target block link point device can be analyzed, so that the first communication thread information and the second communication thread information can be determined, and thus, the accuracy of the analysis result can be ensured.

In an alternative embodiment, the step of periodically obtaining the communication record list of the target block link point device described in step S24 may specifically include the following steps: determining the real-time accumulated quantity of other block chain link point devices with effective communication behaviors with the target block chain node device; and determining an acquisition time interval of the communication record list according to the real-time accumulated quantity, and acquiring the communication record list of the target block chain node equipment according to the acquisition time interval.

In specific implementation, through the content described in the above steps, the acquisition frequency of the communication record list can be adjusted according to the communication density of the target block link point device, so that network resources can be effectively saved, and it is convenient to quickly and timely classify the service data of the target block link point device by subsequently utilizing more network resources.

In a possible implementation manner, the determining the obtaining duration interval of the communication record list according to the real-time accumulated quantity described in the above step specifically includes: and determining the time interval corresponding to the real-time accumulated quantity according to a preset relation list.

In specific implementation, the inventor finds that, when business data is classified, there may be an association between different data, and in this case, if the data is directly classified, the classification result may be inaccurate, and part of private business data may be classified into the second class of business data, which may affect the data security of the target block chain node device. In order to improve the above problem, it is necessary to consider the correlation between different data, so in step S25, the data in the database of the target blockchain node device is classified according to the analysis result to obtain the first type of service data and the second type of service data, which may specifically include the contents described in steps S251 to S255 below.

Step S251, listing first identification information of a first data traffic packet corresponding to the target block link point device in the first communication thread information, listing second identification information of a second data traffic packet corresponding to the target block link point device in the second communication thread information, and inputting the first identification information and the second identification information into a trained convolutional neural network to obtain an identification information set.

Step S252, acquiring the identification logic information and each third identification information of the identification information set; if the identification information set contains the associated identification category based on the identification logic information, determining a first clustering coefficient between each piece of third identification information of the identification information set under the independent identification category and each piece of third identification information of the identification information set under the associated identification category according to the third identification information of the identification information set under the associated identification category and the identification authority level of the third identification information; and adjusting third identification information meeting preset clustering conditions between the third identification information of the identification information set under the independent identification category and the third identification information of the identification information set under the associated identification category to be under the associated identification category according to the first clustering coefficient.

Step S253, if the independent identification category corresponding to the identification information set includes a plurality of third identification information, determining a second clustering coefficient between the third identification information of the identification information set in the independent identification category based on the third identification information of the identification information set in the associated identification category and the identification permission level thereof, and clustering the third identification information of the independent identification category corresponding to the identification information set according to the clustering coefficient between the third identification information to obtain a plurality of fourth identification information.

Step S254, a classification weight is set for each fourth identification information according to the third identification information and the identification permission level of the identification information set in the associated identification category, the fourth identification information is sorted according to the descending order of the classification weight to obtain an identification information sorting sequence, and a set number of fourth identification information in the identification information sorting sequence that is sorted in the top order is adjusted to the associated identification category.

Step S255, classifying the data in the database of the target block link node device according to the data traffic packet corresponding to the identification information in the associated identification category and the data traffic packet corresponding to the identification information in the independent identification category to obtain the first type service data and the second type service data.

It can be understood that based on the above steps S251 to S255, the identification information of the data traffic packets can be classified by taking the correlation between different data into consideration, so that the data traffic packets corresponding to the identification information after classification can be given to classify the data in the database of the target blockchain node device. Therefore, the accuracy of the classification result can be ensured, and partial privacy service data are prevented from being classified into the second type of service data, so that the data security of the target block chain node equipment is ensured.

In a possible implementation manner, in order to accurately classify the first type of service data and the second type of service data from the database, in the step S255, the data in the database of the target block chain node device is classified according to the data traffic packet corresponding to the identification information in the associated identification category and the data traffic packet corresponding to the identification information in the independent identification category, so as to obtain the first type of service data and the second type of service data, which may specifically include the contents described in the following steps S2551 to S2554.

Step S2551, obtaining a first data set determined in the database based on the data traffic packet corresponding to the identification information in the association identification category and a second data set determined in the database based on the data traffic packet corresponding to the identification information in the independent identification category.

Step S2552, determining a first update frequency of the first data set in a preset time period based on a first cumulative update frequency of the first data set in the preset time period and a second cumulative update frequency of the second data set in the preset time period.

Step S2553, determining a second update frequency of the second data set between two adjacent preset time periods according to the update frequency of the first data set in the two adjacent preset time periods.

Step S2554, determining the data in the database, of which the first update frequency is greater than a first set threshold, as the first type of service data, and determining the data in the database, of which the second update frequency is less than a second set threshold, as the second type of service data.

It can be understood that through the contents described in the above steps S2551 to S2554, the first-type service data and the second-type service data can be accurately classified from the database based on the data update frequency corresponding to the data.

Further, the method may further comprise the steps of: and acquiring a target instruction for modifying the first set threshold and the second set threshold, and modifying the first set threshold and the second set threshold according to the target instruction. In this way, the first set threshold and the second set threshold can be modified according to the actual service scene, so that the flexibility and timeliness of data classification are ensured.

In an alternative embodiment, on the basis of the above steps S21-S25, the following steps S26 may be included.

Step S26, generating encryption indication information according to the first label of the first type of service data and the second label of the second type of service data, and sending the encryption indication information to the target block link node device so that the target block link node device encrypts the first type of service data.

It can be understood that, through the content described in the above step S26, the target blockchain node device can be instructed to selectively encrypt the data, so as to improve the data processing efficiency while ensuring the data security of the target blockchain node device.

In another alternative embodiment, the communication record list further records a delivery track of each service data packet, so that when the communication record list is parsed, the delivery track information of each service data packet can be determined, and thus data in the database of the target blockchain node device can be quickly classified according to the delivery track information. The above-mentioned fast classification of data in the database of the target blockchain node device according to the transfer trajectory information may be specifically implemented by the method described in the following steps (1) to (5).

(1) Acquiring a track node sequence of each group of transmission track information, and positioning a target track node from the track node sequence of each group of transmission track information; the target track node is used for representing the track node with the highest activity in the track node sequence.

(2) And judging whether the target track node in the track node sequence of each group of transmission track information is changed relative to the target track node in the last transmission state of the track node sequence of each group of transmission track information.

(3) If so, determining the target track node positioned from the track node sequence of each group of transmission track information as a reference track node of the track node sequence of each group of transmission track information.

(4) Otherwise, weighting the target track node positioned in each group of track node sequences for transmitting track information with the reference track node at the corresponding position in the last transmission state to obtain the current track node, and determining the current track node as the reference track node of each group of track node sequences for transmitting track information.

(5) And judging whether the number of the reference track nodes in each group of transmission track information reaches a set value, if so, determining that the data in the database corresponding to each group of transmission track information is the first-class service data, otherwise, determining that the data in the database corresponding to each group of transmission track information is the second-class service data.

It can be understood that through the contents described in the above steps (1) to (5), data in the database of the target blockchain node device can be quickly classified according to the delivery track information, so as to obtain the first type service data and the second type service data.

On the basis of the above, please refer to fig. 3, which is a block diagram of a block chain-based data analysis apparatus 210 according to the present disclosure, and the description of the data analysis apparatus 210 is as follows.

A1. An apparatus for blockchain-based data analysis for use in an edge computing server in communication with a plurality of inter-communicating blockchain node devices, the apparatus comprising:

the request checking module 211 is configured to determine interface information of each block link point device from an obtained access request of each block link point device, generate a target dynamic random number and a target agreed key according to the interface information and a mac address of the block link point device corresponding to the interface information, perform checking calculation on a generated access request for accessing a database of the block link point device by using the target dynamic random number and the target agreed key to obtain a first checking result, and send the first checking result and the access request to each block link point device; wherein the check result is a CRC check result;

a log retrieving module 212, configured to, when receiving confirmation information sent by each block chain node device when determining that a second check result obtained by performing check calculation on the access request according to the interface information and the mac address of the block chain is consistent with the received first check result, retrieve a target log of the block chain node device from a database of each block chain node device; the target log is a log obtained by encrypting data in a database by using a block chain node device;

the device determining module 213 is configured to analyze each target log to obtain an operation resource allocation record of the block link point device corresponding to the target log; if the occupancy rate of the operation resource for performing encryption operation represented by the operation resource allocation record reaches a set rate, determining the block chain node point equipment corresponding to the operation resource allocation record as target block chain node point equipment;

the list processing module 214 is configured to periodically obtain a communication record list of the target block link point device, and analyze the communication record list to obtain an analysis result;

a data classification module 215, configured to classify, according to the analysis result, data in the database of the target blockchain node device to obtain first-class service data and second-class service data; the first type of service data is privacy service data of the target block node point equipment, and the second type of service data is process service data and/or redundant data of the target block node point equipment;

a data encryption module 216, configured to generate encryption indication information according to the first tag of the first type of service data and the second tag of the second type of service data, and send the encryption indication information to the target block link node device, so that the target block link node device encrypts the first type of service data.

A2. The blockchain-based data analysis apparatus according to a1, the manifest processing module 214 is specifically configured to:

A3. The blockchain-based data analysis apparatus according to a2, the manifest processing module 214 is specifically configured to:

A4. The blockchain-based data analysis apparatus according to a1, the manifest processing module 214 is specifically configured to:

A5. The block chain-based data analysis apparatus according to a4, the data classification module 215 is specifically configured to:

A6. The block chain-based data analysis apparatus according to a5, the data classification module 215 is specifically configured to:

A7. The blockchain-based data analysis apparatus according to a6, the data classification module 215 is further configured to:

The implementation process of the functions and actions of each module in the above device is specifically described in the implementation process of the corresponding step in the above method, and is not described herein again.

For the device embodiments, since they substantially correspond to the method embodiments, reference may be made to the partial description of the method embodiments for relevant points. The above-described embodiments of the apparatus are merely illustrative, wherein the modules described as separate parts may or may not be physically separate, and the parts displayed as modules may or may not be physical modules, may be located in one place, or may be distributed on a plurality of network modules. Some or all of the modules can be selected according to actual needs to achieve the purpose of the scheme of the application. One of ordinary skill in the art can understand and implement it without inventive effort.

Further, on the basis of the above, a data analysis system based on the block chain is also provided, and the scheme about the system is described as follows.

B1. A data analysis system based on a block chain comprises an edge calculation server and a plurality of block chain link point devices which are communicated with each other;

the edge computing server is to:

a target blockchain node device of the plurality of blockchain node devices is to:

updating a communication record list in real time during communication;

the edge computing server is to:

periodically acquiring the communication record list of the target block chain node equipment, analyzing the communication record list to obtain an analysis result, and classifying data in a database of the target block chain node equipment according to the analysis result to obtain first-class service data and second-class service data; the first type of service data is privacy service data of the target block node point equipment, and the second type of service data is process service data and/or redundant data of the target block node point equipment; generating encryption indicating information according to the first label of the first type of service data and the second label of the second type of service data, and sending the encryption indicating information to the target block link point device;

the target blockchain node device is configured to:

and encrypting the first class of service data according to the encryption indication information.

B2. As in the data analysis system based on the blockchain described in B1, the edge calculation server is specifically configured to:

B3. As in the data analysis system based on the blockchain described in B2, the edge calculation server is specifically configured to:

B4. As in the data analysis system based on the blockchain described in B1, the edge calculation server is specifically configured to:

B5. As in the data analysis system based on the blockchain described in B4, the edge calculation server is specifically configured to:

B6. As in the data analysis system based on the blockchain described in B5, the edge calculation server is specifically configured to:

B7. As in the data analysis system based on the blockchain described in B6, the edge calculation server is specifically configured to:

For a detailed description of the above system, reference is made to the above description of the above method, which is not further described here.

On the basis of the above, please refer to fig. 4 in combination, which provides an edge computing server 200, including: a processor 221, and a memory 222 and a network interface 223 connected to the processor 221; the network interface 223 is connected with the non-volatile memory 224 in the edge computing server 200; the processor 221, when running, retrieves the computer program from the non-volatile memory 224 via the network interface 223 and runs the computer program via the memory 222 to perform the above-described method.

On the basis of the above, a readable storage medium applied to a computer is also provided, and the readable storage medium is burned with a computer program, and the computer program realizes the above method when running in the memory 222 of the edge computing server 200.

Other embodiments of the present application will be apparent to those skilled in the art from consideration of the specification and practice of the invention disclosed herein. This application is intended to cover any variations, uses, or adaptations of the invention following, in general, the principles of the application and including such departures from the present disclosure as come within known or customary practice within the art to which the invention pertains. It is intended that the specification and examples be considered as exemplary only, with a true scope and spirit of the application being indicated by the following claims.

It will be understood that the present application is not limited to the precise arrangements described above and shown in the drawings and that various modifications and changes may be made without departing from the scope thereof. The scope of the application is limited only by the appended claims.

Claims

1. A blockchain-based data analysis method applied to an edge computing server in communication with a plurality of blockchain link point devices in communication with each other, the method comprising:

2. The method of claim 1, wherein periodically obtaining a list of communication records for a target blockchain link point device comprises:

3. The blockchain-based data analysis method of claim 2, wherein determining the acquisition duration interval of the communication record list according to the real-time cumulative amount comprises:

4. The blockchain-based data analysis method of claim 1, wherein parsing the communication record list to obtain a parsing result comprises:

5. The blockchain-based data analysis method according to claim 4, wherein classifying the data in the database of the target blockchain node device according to the analysis result to obtain a first class of service data and a second class of service data includes:

6. The method according to claim 5, wherein classifying data in the database of the target blockchain node device according to the data traffic packet corresponding to the identification information in the association identification category and the data traffic packet corresponding to the identification information in the independent identification category to obtain the first type service data and the second type service data comprises:

7. The blockchain-based data analysis method of claim 6, further comprising:

8. An edge computing server in communication with a plurality of block-linked point devices in communication with each other, the edge computing server configured to:

9. An edge computing server, comprising:

a processor, and

a memory and a network interface connected with the processor;

the network interface is connected with a nonvolatile memory in the edge computing server;

the processor, when running, retrieves a computer program from the non-volatile memory via the network interface and runs the computer program via the memory to perform the method of any of claims 1-7.

10. A readable storage medium applied to a computer, wherein the readable storage medium is burned with a computer program, and the computer program realizes the method of any one of the above claims 1 to 7 when the computer program runs in the memory of the edge computing server.