CN114664432B

CN114664432B - Industry big data-oriented intelligent analysis system

Info

Publication number: CN114664432B
Application number: CN202210260033.4A
Authority: CN
Inventors: 薛敏; 郑楠; 胡彭; 于浩
Original assignee: Nanjing Debbies Network Technology Co ltd
Current assignee: Nanjing Debbies Network Technology Co ltd
Priority date: 2022-03-16
Filing date: 2022-03-16
Publication date: 2024-06-07
Anticipated expiration: 2042-03-16
Also published as: CN114664432A

Abstract

The application provides an intelligent analysis system for industry big data. The analysis system comprises a block chain, a receiving unit, a sending unit and a certification unit. The blockchain includes analyzing a smart contract. The receiving unit receives medical information provided by a first user and invokes the analysis intelligent contract to generate an analysis event. The sending unit sends the analysis event to a plurality of second users so that the plurality of second users can analyze the medical information to obtain analysis result information and transfer second virtual resources to the plurality of second users through the analysis intelligent contract. The certification unit invokes the analysis intelligent contract, certifies the medical information under the condition that the medical information is determined to have reliability, and transfers the first virtual resource to the first user. Therefore, the enthusiasm of the first user and the second user for providing the medical information and the reliability of the medical information can be improved.

Description

Industry big data-oriented intelligent analysis system

Technical Field

The application relates to a computer technology, in particular to an intelligent analysis system for industry big data.

Background

Some diseases can be realized through self-help medical treatment, so that time and labor are saved, and medical resources are released. While achieving self-help medical treatment requires a great deal of reliable industry data as support. Wherein the industry data may be medical information.

At present, the enthusiasm of users for providing medical information is generally not high, the collected medical information is mixed with a fish bone, and the reliability is also not high.

Disclosure of Invention

In view of the above, the application discloses an intelligent analysis system for industry big data. The analysis system comprises a block chain, a receiving unit, a sending unit and a certification unit, wherein the receiving unit, the sending unit and the certification unit are connected with the block chain; the blockchain comprises blockchain nodes which are subjected to consensus in advance and an analysis intelligent contract for analyzing data; the block chain node is used for realizing interaction between the receiving unit, the sending unit and the certification unit and the block chain respectively. The receiving unit is used for receiving medical information provided by the first user client and constructing an intelligent contract calling transaction in response to the received medical information, calling the analysis intelligent contract and generating an analysis event; wherein the medical information includes disorder information and corresponding diagnostic information; the sending unit is configured to obtain the analysis event and send the analysis event to a plurality of pre-authenticated second user clients, so that the plurality of second users respond to the analysis event to analyze the medical information to obtain analysis result information and call the analysis intelligent contract, and transfer second virtual resources corresponding to the analysis to second contract accounts corresponding to the plurality of second users; the certification unit is used for acquiring the analysis result information fed back by the plurality of second users, calling the analysis intelligent contracts, determining and analyzing the number of the second users with the reliability of the medical information according to the analysis result information, certifying the medical information and the analysis result information aiming at the medical information to the blockchain when the number reaches a first threshold, and transferring first virtual resources corresponding to the medical information to a first contract account corresponding to the first user.

In some embodiments, the first user signs the medical information with its own corresponding private key; the receiving unit is used for: and verifying the medical information by using the public key corresponding to the first user, and constructing an intelligent contract invoking transaction under the condition that verification is passed.

In some embodiments, the first user client is a pre-authenticated trusted client; the analysis system further comprises an encryption unit deployed at the first user client; the encryption unit is used for responding to the received medical information and sending reminding information to the first user so that the first user can respond to the reminding information to upload a target image for generating a secret key; receiving the target image, and performing random number sliding in a preset sliding direction according to a preset step length by utilizing a sliding frame with a preset size; generating a secret key based on pixel values of a first pixel point included in the sliding frame after the sliding is completed; encrypting the medical information based on the key.

In some embodiments, the analysis event includes the random number, the target image, and the encrypted medical information; the second user client is a trusted client which is verified in advance; the analysis system further comprises a decryption unit deployed at the second user client; the decryption unit is used for: after the analysis event is acquired, analyzing the analysis event to obtain the random number, the target image and the encrypted medical information; performing the random number of slides on the target image by using the sliding frame of the preset size in the same sliding manner as in the encryption unit; generating a secret key based on pixel values of a second pixel point included in the sliding frame after the sliding is completed; decrypting the medical information based on the key to obtain decrypted medical information; and analyzing the decrypted medical information.

In some embodiments, the smart contract is to post the generated analysis event to the blockchain after generating the analysis event; the sending unit is configured to: and monitoring event information released in the blockchain, and sending the medical information to the plurality of second user clients under the condition that the analysis event is monitored, so that the plurality of second users analyze the received medical information.

In some embodiments, candidate user clients corresponding to a plurality of candidate users are connected to the transmitting unit; the sending unit is configured to: and after the analysis event is acquired, the medical information is sent to the candidate user clients so that the candidate users analyze the received medical information.

In some embodiments, the blockchain further includes a first altering unit to: according to the analysis result information, counting the analysis accuracy of each second user and each candidate user; the second user and the candidate user are respectively ordered according to the analysis accuracy at regular intervals; and exchanging identities of N second users with the analysis correct rate ranked later and N candidate users with the analysis correct rate ranked earlier.

In some embodiments, the blockchain further includes a second altering unit to: according to the analysis result information, counting the analysis accuracy of each candidate user of each second user; periodically mixing and sorting the second user and the candidate users according to the analysis accuracy; the M users with the analysis accuracy rate ranked first are determined as second users, and the rest users are determined as candidate users.

In some embodiments, the second user client analyzes the received medical information, including: the second user client side extracts the disease information and the diagnosis information included in the medical information by utilizing an OCR technology; analyzing whether the disorder information is matched with the diagnosis information according to the disorder information; and determining that the medical information has reliability in the case that the condition information is matched with the diagnosis information.

In some embodiments, the receiving unit, the sending unit and the authentication unit are both disposed on a BaaS platform.

In the foregoing scheme, firstly, the collection process of the medical information can be driven by using the analysis intelligent contract, on one hand, each link of the collection process is automatically executed, and the rights and interests of a medical information provider (first user) and an analyzer (second user) are ensured; on the other hand, the collection process can be supervised, and the reliability of medical information is improved.

Second, after the medical information provided by the first user is received, the medical information can be analyzed and verified by the second user authenticated in advance, and when the number of the second users considering that the medical information has reliability reaches the first threshold, the medical information is stored, so that the reliability of the medical information is improved.

Thirdly, by utilizing the analysis intelligent contract, on one hand, after the second user analyzes the medical information, second virtual resources are allocated to a second contract account corresponding to the second user node; on the other hand, under the condition that the medical information provided by the first user is determined to have reliability, the first virtual resource can be allocated to the first contract account corresponding to the first user, so that the benefit of the first user is ensured; through the two aspects, the participation enthusiasm of the first user and the second user can be improved, and further, more medical information can be collected.

Fourth, by utilizing the characteristic that the blockchain is not tamperable, the true reliability of the stored medical information is improved, and further the realization of self-service medical treatment is promoted.

Drawings

The drawings that are required for use in the description of the embodiments or the related art will be briefly described below.

FIG. 1 is a schematic diagram of an analysis system according to an embodiment of the present application;

FIG. 2 is a flow chart of a method for analyzing medical messages according to an embodiment of the present application;

FIG. 3 is a schematic diagram of an analysis system according to an embodiment of the present application;

FIG. 4 is a flow chart of an encryption method according to an embodiment of the present application;

FIG. 5 is a schematic diagram of an analysis system according to an embodiment of the present application;

FIG. 6 is a flow chart of an analysis method according to an embodiment of the present application;

Fig. 7 is a schematic structural diagram of an analysis device according to an embodiment of the present application.

Detailed Description

Reference will now be made in detail to exemplary embodiments, examples of which are illustrated in the accompanying drawings. When the following description refers to the accompanying drawings, the same numbers in different drawings refer to the same or similar elements, unless otherwise indicated. The implementations described in the following exemplary examples do not represent all implementations consistent with the application. Rather, they are merely examples of apparatus and methods consistent with aspects of the application as detailed in the accompanying 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 specification 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 or all possible combinations of one or more of the associated listed items. It will also be appreciated that the term "if," as used herein, may be interpreted as "at … …" or "at … …" or "in response to a determination" depending on the context.

Blockchain technology, also known as distributed ledger technology, is an emerging technology that is commonly engaged in "accounting" by several computing devices, together maintaining a complete distributed database. The blockchain technology has the characteristics of decentralization, disclosure transparency, capability of participating in database recording by each computing device and capability of rapidly performing data synchronization among the computing devices, so that the blockchain technology is widely applied in a plurality of fields.

Blockchains are generally divided into three types: public chain (Public Blockchain), private chain (Private Blockchain) and federated chain (Consortium Blockchain). In addition, there are many types of combinations, such as different combinations of private chain+federation chain, federation chain+public chain, and the like.

The blockchain provides the functionality of the smart contract. The smart contracts may be defined in the form of codes.

By smart contract creation transactions, smart contracts can be deployed in blockchains. After the contract is created, a contract account corresponding to the intelligent contract appears on the blockchain and has a specific address, and the contract code and account store are stored in the contract account. The behavior of the smart contract is controlled by the contract code, while the account store (Storage) of the smart contract maintains the state of the contract. In other words, the smart contract causes a virtual account to be generated on the blockchain that includes the contract code and account store.

Invoking the transaction through the smart contract may invoke execution logic within the smart contract to complete the corresponding steps. The application utilizes the characteristic of the intelligent contract to collect medical information.

The application provides an intelligent analysis system for industry big data. The analysis system comprises a block chain, a receiving unit, a sending unit and a certification unit, wherein the receiving unit, the sending unit and the certification unit are connected with the block chain; the blockchain comprises blockchain nodes which are subjected to consensus in advance and an analysis intelligent contract for analyzing data; the block chain node is used for realizing interaction between the receiving unit, the sending unit and the certification storing unit and the block chain respectively;

The receiving unit is used for receiving medical information initiated by the first user client and constructing an intelligent contract calling transaction in response to the received medical information, calling the analysis intelligent contract and generating an analysis event; wherein the medical information includes disorder information and corresponding diagnostic information;

The sending unit is used for obtaining the analysis event and sending the analysis event to a plurality of pre-authenticated second user clients so that a plurality of second users respond to the analysis event to analyze the medical information to obtain analysis result information and call the analysis intelligent contract, and transferring second virtual resources corresponding to the verification to second contract accounts respectively corresponding to the plurality of second users;

the certification unit is used for acquiring the analysis result information fed back by the plurality of second users, calling the analysis intelligent contracts, determining and analyzing the number of the second users with the reliability of the medical information according to the analysis result information, certifying the medical information and the analysis result information aiming at the medical information to the blockchain when the number reaches a first threshold, and transferring first virtual resources corresponding to the medical information to a first contract account corresponding to the first user.

In the system, firstly, the collection process of the medical information can be driven by utilizing the analysis intelligent contract, on one hand, each link of the collection process is automatically executed, and the rights and interests of a medical information provider (first user) and an analyzer (second user) are ensured; on the other hand, the collection process can be supervised, and the reliability of medical information is improved.

Referring to fig. 1, fig. 1 is a schematic structural diagram of an analysis system according to an embodiment of the application.

As shown in fig. 1, the analysis system 100 may include a blockchain 110, and a receiving unit 120, a transmitting unit 130, and a certification unit 140 connected to the blockchain 110.

It should be noted that, the functional units (including the receiving unit, the sending unit and the certification unit) referred to in the present application include corresponding software functional logic and hardware devices for executing the software functional logic.

BaaS (Blockchain AS A SERVICE), "blockchain as a service" refers to embedding a blockchain framework into a cloud computing platform, and provides a convenient and high-performance blockchain ecological environment and ecological supporting service for a developer by utilizing deployment and management advantages of a cloud service infrastructure, and supports business expansion and operation support of the developer.

The BaaS platform can be understood as a service end and provides interaction service with the blockchain for the user end, so that the user end can be prevented from directly interacting with the blockchain, the deployment difficulty of the user end is simplified, and the safety of the blockchain can be improved.

In some implementations, the receiving unit, sending unit, and the certification unit may be deployed at BaaS platform and interact with blockchain nodes or clients in the blockchain by developing corresponding interfaces.

The blockchain 110 includes a plurality of blockchain nodes that are commonly known in advance. These block link points provide decentralized distributed services. The receiving unit, sending unit and the checking unit may access the blockchain nodes to perform tasks such as data checking, issuing contracts, invoking contracts, and the like.

In some implementations, developers may develop and analyze smart contracts in advance, which include a number of computing logic, such as analysis event generation logic, event verification logic, and event certification logic.

The analysis event generation logic may generate analysis events based on the entered medical information and issue the analysis events in the blockchain. The event verification logic may determine that the medical information is indeed reliable when the input analysis result information indicates that the number of second users who analyze the medical information to be reliable reaches a first threshold. The event certification logic may certify the medical information in a blockchain if it is determined that the medical information is indeed reliable.

The receiving unit 120 may be configured to receive medical information provided by the first user client, and construct an intelligent contract invoking transaction in response to the received medical information, invoke the analysis intelligent contract, and generate an analysis event; wherein the medical information includes condition information and corresponding diagnostic information.

The first user refers to a user who uploads medical information. The first user may be a doctor, a student with medical knowledge, or the like.

The medical information includes condition information and corresponding diagnostic information. The condition information may include disease symptoms. Such as fever, headache, cough, lumbago, skelalgia, etc. The diagnostic information includes methods, drugs, etc. that can treat or alleviate the condition. For example, the diagnostic information may include a medication name, instructions for use, a rehabilitation exercise method, and the like. It should be noted that the medical information is licensed by the information owner, and the data is not such data as name, address, age, etc. which are not suitable for disclosure, which are related to the patient.

The first user client refers to a software client deployed in a terminal device. The terminal device may be a notebook computer, a server, a mobile phone, a palm computer (Personal DIGITAL ASSISTANT, PDA), etc. The type of the terminal device is not particularly limited in the present application.

A first user may operate the first user client, enter the medical information in the first client, and trigger a send button.

The first client may invoke a corresponding software interface of the receiving unit 120 in response to the send button being triggered to send the medical information to the receiving unit 120.

The receiving unit 120 may receive the medical information through the software interface, and in response to receiving the medical information, generate an intelligent contract invocation transaction, and issue the transaction in a blockchain. The transaction includes an account address of the analysis intelligent contract, and the blockchain can acquire and execute the analysis intelligent contract according to the account address.

The blockchain may run analysis event generation logic included in the analysis intelligence contract to generate analysis events based on the medical information.

The sending unit 130 may obtain the analysis event and send the analysis event to a plurality of pre-authenticated second user clients, so that the plurality of second users may respond to the analysis event to analyze the medical information to obtain analysis result information and call the analysis intelligent contract, and transfer second virtual resources corresponding to the amount of verification to second contract accounts corresponding to the plurality of second users.

In some aspects, the smart contract is to post the generated analysis event to the blockchain after generating the analysis event. The analysis events may be stored in a contract account and stored synchronously in a hardware store of the blockchain node, for example. The sending unit 130 may obtain the analysis event by listening to the hardware storage of the blockchain node.

In some implementations, an SDK (software package) can be installed in the blockchain node. Through the SDK, the sending unit can monitor the hardware storage of the blockchain node. For example, the SDK may monitor whether an analysis event is received in the blockchain node, and after receiving the analysis event, transmit the analysis event to the transmitting unit 130.

In some approaches, the listening may be accomplished through a message subscription mode. For example, the blockchain node may send the received analysis event to a message server, which may send the analysis event to the sending unit 130 subscribing to the topic.

The transmitting unit 130 transmits the medical information to the plurality of second user clients after acquiring the analysis event (in case of monitoring the analysis event) so that the plurality of second users analyze the received medical information.

The second user is a pre-authenticated authority. These second users have the ability to analyze the authenticity of the medical information, and to distinguish whether the medical information includes disorder information and diagnostic information that match.

The second user client is a client developed for the second user and is deployed in terminal equipment corresponding to the second user. The sending unit may establish a transit connection (e.g., a TCP connection) with the second client so that the analysis event may be sent to the second client. The second client may present the medical information to a second later for analysis by a second user.

The sending unit may further construct an intelligent contract call transaction, call resource transfer logic in the analysis intelligent contract, and transfer second virtual resources corresponding to the analysis to second contract accounts corresponding to the plurality of second users respectively.

In some modes, the intelligent contract is used for confirming the quantity of the disease information or the diagnosis information included in the medical information, obtaining second virtual resources, such as a certain number of Token, of the analysis corresponding to the amount according to the unit virtual resource quantity, and transferring the second virtual resources to contract accounts corresponding to a plurality of second users.

The second user may extract virtual resources stored by the contract account for value exchange, such as shopping.

In some embodiments, the medical information is uploaded in the form of a medical picture.

Referring to fig. 2, fig. 2 is a flow chart of a method for analyzing medical messages according to an embodiment of the application. As shown in FIG. 2, the method may include S202-S206. The order of execution of these steps is not limited unless specifically described.

And S202, the second user client extracts the disease information and the diagnosis information included in the medical information by utilizing an OCR technology.

OCR (Optical Character Recognition ) refers to the process of checking characters printed on a picture, determining their shape by detecting dark and light patterns, and then translating the shape into computer text using a character recognition method.

In particular, a medical picture may be input into an OCR system. The medical picture can be cut according to the characters to obtain a plurality of picture segments containing the characters, and then each picture segment on the side is used for determining the characters in each picture segment by utilizing a character recognition neural network which is trained in advance, so that character recognition is completed, and disorder information and diagnosis information are obtained.

It is worth mentioning that, in training the character recognition neural network, besides using a regular font as a sample, a handwriting font of a doctor may be used as a sample, so that the character recognition capability of the character recognition neural network may be improved.

In some embodiments, after completing the character recognition of the medical picture, the character may be deleted according to the specific meaning of the character, so as to delete the character data unsuitable for disclosure.

For example, if characters such as name, address, age, etc. are recognized, a predetermined number of characters following the characters may be deleted, so that character data unsuitable for disclosure may be deleted, avoiding disclosure of the data.

Condition information and diagnostic information are identified, which may be presented to a second user.

S204, analyzing whether the disease information is matched with the diagnosis information according to the disease information.

In some ways, these second users may empirically analyze whether the condition information matches the diagnostic information.

S206, determining that the medical information has reliability when the disease information is matched with the diagnosis information. And otherwise, determining that the medical information is not reliable.

After the second user completes the analysis of the medical information, the second user client may input the analysis result of whether the medical information is reliable. The second user client may generate analysis result information according to the analysis result and transmit the analysis result information to the certification unit 140.

The certification unit 140 may be configured to obtain the analysis result information fed back by the plurality of second users, and invoke the analysis intelligent contract, so as to determine, according to the analysis result information, the number of second users that analyze that the medical information has reliability, and when the number reaches a first threshold, certify the medical information and the analysis result information about the medical information to the blockchain, and transfer a first virtual resource corresponding to the medical information to a first contract account corresponding to the first user.

Specifically, the certification unit 140 may construct a contract call transaction, calling the certification logic of the analysis intelligent contract. The analysis result information uploaded by each second user can be acquired and summarized through the certification logic, and the number of the second users considering that the medical information has reliability can be counted. The number may then be compared to a first threshold, and if the number reaches the first threshold, the medical information is deemed to be reliable.

The first threshold is an empirical threshold and can be set according to requirements. For example, the first threshold may be 90% of the total number of second users. I.e. assuming a total of 100 persons for the second user, the first threshold may be set to 90.

If it is determined that the medical information is indeed reliable, the medical information may be verified in a blockchain.

In some implementations, the medical information base is included in a contract account to which the analyzed smart contract corresponds. The medical information base stores the disease information and the diagnosis information in association. The medical information may be stored in the medical information repository to complete the certification.

If it is determined that the medical information is indeed reliable, a relevant reward may also be made to the first user. After the certification logic is completed, the resource transfer logic may be continued to transfer the first virtual resource corresponding to the medical information to the first contract account corresponding to the first user.

The resource transfer logic may be configured to count the number of medical information counted condition information or diagnostic information, determine a current first virtual resource amount based on the unit resource amount, and complete the transfer.

The first user may extract these virtual resources from the first contract for the relevant value exchange.

In some embodiments, it may be ensured that the medical information is uploaded after the first user approval. The first user may be assigned a unique public-private key pair when the analysis system registers for an account. Wherein the public key is published in the blockchain in a public state. The private key is private to the first user.

When the first user uploads the medical information, the first user can sign by using the private key of the first user. Whereby the private key is added to the medical information to indicate that the medical information was indeed approved for uploading.

In some embodiments, the receiving unit may sign the medical information using a public key corresponding to the first user and, if the verification passes, construct an intelligent contract invocation transaction. Otherwise, the smart contract is not allowed to be invoked. Thereby, the medical information is ensured to be the data authorized by the first user permission, the negative influence is avoided, and the data security can be improved.

In some embodiments, to promote the security of the medical information, the medical information may be encrypted with a key. It is worth mentioning that the key used in this encryption is randomly generated, and the method of generating the key is not public and can not be broken. In some ways, the method of generating the key is deployed in the trusted execution environment TEE in the form of a trusted program TA. Only when the secret key is generated, the secret key can be called, but the process of generating the secret key is unknown to the outside, so that the safety of the secret key is improved, and the safety of medical information is further improved.

Referring to fig. 3, fig. 3 is a schematic structural diagram of an analysis system according to an embodiment of the application.

As shown in fig. 3, the analysis system 300 includes a blockchain 310, and a receiving unit 320, a transmitting unit 330, a certification unit 340, and an encryption unit 350 and a decryption unit 360 connected to the blockchain 310. The descriptions of the receiving unit, the transmitting unit, and the authentication unit may refer to the descriptions of the relevant functional units in the analysis system shown in fig. 1, and will not be described in detail herein.

The first user client and the second user client are pre-authenticated trusted clients. In some modes, when the client is installed, the user can be authenticated, and the client is allowed to be installed only under the condition that the authentication is passed, so that the credibility of the client is ensured. In some ways, the method of key generation may be installed as a TA in the TEE of the terminal device.

The first user client may call the encryption unit 350 to complete encryption after receiving the medical information input by the first user.

Referring to fig. 4, fig. 4 is a flow chart of an encryption method according to an embodiment of the application. As shown in fig. 4, the method may include S402-S408. These methods are applied to the encryption unit 350. The order of execution of these steps is not limited unless specifically described.

And S402, sending reminding information to the first user in response to the received medical information, so that the first user uploads a target image for generating a key in response to the reminding information.

In some modes, the encryption unit can send a prompt to the first user in a popup window or page skip mode to request the first user to upload the target image.

In some implementations, the first user may select an image from the terminal device for uploading.

In some modes, the first user client can call the camera to enable the first user to take a picture in real time, so that a real-time picture is obtained, and the first user can upload the real-time picture as a target image. The adoption of the real-time image can increase the randomness of the image, so that the security of the secret key is improved.

S404, receiving the target image, and performing random number sliding in a preset sliding direction according to a preset step length by utilizing a sliding frame with a preset size.

The sliding frame, the step length and the sliding direction can be set according to the requirements. For example, the sliding frame may be 3*3, the step size is 3, and the sliding direction is from left to right and from top to bottom. The random number is a number randomly generated during encryption, so that the difficulty of cracking the key is increased, and the security of the key is improved.

And S406, generating a key based on the pixel value of the first pixel point included in the sliding frame after the sliding is completed.

After the sliding of the preset number of words is completed, the sliding frame comprises a plurality of first pixel points. The pixel values of these first pixels may be used to generate a key. For example, the key may be obtained by sequentially stitching or calculating the pixel values of the first pixel points. The operation may be a weighted addition, a weighted multiplication, or the like.

And S408, encrypting the medical information based on the key.

In this step, encryption may be performed by using a symmetric encryption method. The encryption method can refer to the related art, and is not described in detail herein.

Through the steps recorded in S402-S408, on one hand, the secret key can not be directly transmitted, on the other hand, the secret key can be calculated by utilizing the random number and the pixel data of the target image uploaded by the user, and the secret key security can be enhanced, the secret key cracking difficulty is increased, and the medical information security is further improved through the two aspects.

After the encryption of the medical information is completed, the first user client may transmit the random number, the target image, and the encrypted medical information to the receiving unit 320 for a subsequent operation.

The decryption unit 360 may parse the analysis event after the analysis event is acquired, to obtain the random number, the target image and the encrypted medical information; performing the random number of slides on the target image by using the sliding frame of the preset size in the same sliding manner as in the encryption unit; generating a secret key based on pixel values of a second pixel point included in the sliding frame after the sliding is completed; decrypting the medical information based on the key to obtain decrypted medical information; and analyzing the decrypted medical information.

In the encryption and decryption method, on one hand, an encryption unit is deployed at a trusted first user client, and a decryption unit is deployed at a trusted second user client, wherein the encryption unit and the decryption unit contain the same method for calculating a key, so that the key is not required to be directly transmitted when an analysis event is transmitted, and on the other hand, the key can be calculated by using random number and pixel data of a target image uploaded by a user; by means of the two aspects, the key safety can be enhanced, the key cracking difficulty is increased, and the medical information safety is further improved.

In some embodiments, the second user may be periodically replaced to facilitate the second user's careful analysis of the medical information to ensure the reliability of the medical information.

Referring to fig. 5, fig. 5 is a schematic structural diagram of an analysis system according to an embodiment of the application.

As shown in fig. 5, the analysis system 500 includes a blockchain 510, and a receiving unit 520, a transmitting unit 530, a certification unit 540, an encrypting unit 550, a decrypting unit 560, a first changing unit 570, and a second changing unit 580 connected to the blockchain 510. The descriptions of the receiving unit, the transmitting unit, the authentication unit, the encrypting unit, and the decrypting unit may refer to the descriptions of the relevant functional units in the analysis system shown in fig. 3, and are not described in detail herein.

The sending unit 530 may send the medical information to the plurality of candidate user clients after the analysis event is acquired, so that the plurality of candidate users analyze the received medical information.

The candidate users refer to users who want to join in the medical information analysis process, and the users also participate in the analysis of the medical information, but the analysis results of the users do not influence the confirmation of the reliability of the medical information.

The candidate user clients refer to clients corresponding to candidate users, and the candidate user clients are deployed in terminal equipment.

The transmitting unit may transmit the medical information to the candidate user client and the second user client. These candidate user clients may present medical information for analysis by the candidate user and the second user client may present medical information for analysis by the second user. The analysis results of the candidate user and the second user for the medical information may be uploaded to the first modification unit 570 and/or the second modification unit 580.

The first changing unit 570 may count analysis accuracy of each of the second users and each of the candidate users according to the analysis result information.

And the first change unit maintains the analysis accuracy corresponding to each second user and each candidate user. The denominator of the analysis accuracy comprises the number of times that the user participates in medical information analysis, and the numerator is the number of times that the analysis result of the user is consistent with the final analysis result. The final analysis result refers to a final analysis result obtained according to the analysis result of each second user. If the number of second users who consider the medical information to be reliable reaches a first threshold, determining that the medical information is reliable finally, and if the number is lower than the first threshold, determining that the medical information is not reliable.

After the analysis of the medical information is completed each time, the analysis accuracy corresponding to each second user and each candidate user can be updated in the first changing unit.

The first changing unit 570 may also sort the second user and the candidate user according to the analysis accuracy rate periodically.

In practical application, a preset duration may be set, and after the preset duration passes through the first changing unit, the ordering may be started. For example, the second user and the candidate user may be respectively ranked according to the order from high to low, so as to obtain two ranking results.

After the sorting result is obtained, the N second users with the analysis correct rate being ranked back and the N candidate users with the analysis correct rate being ranked front can be subjected to identity exchange.

The N is an empirical threshold. For example, 3 or 4.

Through the first changing unit, the second user with lower analysis accuracy can be changed into the candidate user at regular intervals, and the candidate user with higher analysis accuracy is changed into the second user, so that the second user can be kept to have higher analysis accuracy all the time, the credibility of medical information is improved, the second user can be subjected to a whip action, and the credibility of the medical information is improved.

The second changing unit 580 may count analysis accuracy of each of the second users and each of the candidate users according to the analysis result information.

And the second changing unit maintains the analysis accuracy corresponding to each second user and each candidate user. The denominator of the analysis accuracy comprises the number of times that the user participates in medical information analysis, and the numerator is the number of times that the analysis result of the user is consistent with the final analysis result. The final analysis result refers to a final analysis result obtained according to the analysis result of each second user. If the number of second users who consider the medical information to be reliable reaches a first threshold, determining that the medical information is reliable finally, and if the number is lower than the first threshold, determining that the medical information is not reliable.

After the analysis of the medical information is completed each time, the analysis accuracy corresponding to each second user and each candidate user can be updated in the second changing unit.

The second changing unit 580 may also perform a mixed ranking on the second user and the candidate user according to the analysis accuracy rate periodically.

In practical application, a preset duration may be set, and after the preset duration passes through the second changing unit, the sorting may be started. For example, the second user and the candidate user may be mixed and ranked in order from high to low, so as to obtain a ranking result.

After the sorting result is obtained, M users with the analysis accuracy rate ranked first may be determined as the second user, and the remaining users may be determined as candidate users.

The M is an empirical threshold. For example, may be 100.

Through the second changing unit, the analysis accuracy of the second user can be always kept at a relatively high level, so that the credibility of the medical information is improved, and the second user can be subjected to a whipping effect, so that the credibility of the medical information is improved.

The application also provides an analysis method. The method is applied to the intelligent analysis system shown in any of the previous embodiments. The analysis system comprises a block chain, a receiving unit, a sending unit and a certification unit, wherein the receiving unit, the sending unit and the certification unit are connected with the block chain; the blockchain comprises blockchain nodes which are subjected to consensus in advance and an analysis intelligent contract for analyzing data; the block chain node is used for realizing interaction between the receiving unit, the sending unit and the certification unit and the block chain respectively.

Referring to fig. 6, fig. 6 is a schematic flow chart of an analysis method according to an embodiment of the application.

As shown in fig. 6, the method includes:

s602, receiving medical information provided by a first user client through the receiving unit, constructing an intelligent contract calling transaction in response to the received medical information, calling the analysis intelligent contract, and generating an analysis event; wherein the medical information includes disorder information and corresponding diagnostic information;

S604, acquiring the analysis event and transmitting the analysis event to a plurality of pre-authenticated second user clients through the transmitting unit, so that a plurality of second users respond to the analysis event to analyze the medical information to obtain analysis result information and call the analysis intelligent contract, and transferring second virtual resources corresponding to the analysis to second contract accounts respectively corresponding to the plurality of second users;

S606, acquiring analysis result information fed back by the plurality of second users through the evidence storage unit, calling the analysis intelligent contracts, determining and analyzing the number of the second users with the reliability of the medical information according to the analysis result information, storing the medical information and the analysis result information aiming at the medical information into the blockchain when the number reaches a first threshold, and transferring first virtual resources corresponding to the medical information to a first contract account corresponding to the first user.

In the method, firstly, the collection process of the medical information can be driven by utilizing the analysis intelligent contract, on one hand, each link of the collection process is automatically executed, and the rights and interests of a medical information provider (first user) and an analyzer (second user) are ensured; on the other hand, the collection process can be supervised, and the reliability of medical information is improved.

In some embodiments, the first user signs the medical information with its own corresponding private key; the method further comprises the steps of: and through the receiving unit, the medical information is checked by using the public key corresponding to the first user, and an intelligent contract invoking transaction is constructed under the condition that the verification is passed.

In some embodiments, the first user client is a pre-authenticated trusted client; the analysis system further comprises an encryption unit deployed at the first user client;

The method further comprises the steps of: sending reminding information to the first user by using the encryption unit in response to the received medical information, so that the first user can upload a target image for generating a secret key in response to the reminding information;

receiving the target image, and performing random number sliding in a preset sliding direction according to a preset step length by utilizing a sliding frame with a preset size;

generating a secret key based on pixel values of a first pixel point included in the sliding frame after the sliding is completed;

encrypting the medical information based on the key.

In some embodiments, the analysis event includes the random number, the target image, and the encrypted medical information; the second user client is a trusted client which is verified in advance; the analysis system further comprises a decryption unit deployed at the second user client; the method further comprises the steps of: analyzing the analysis event after acquiring the analysis event by using the decryption unit to obtain the random number, the target image and the encrypted medical information;

performing the random number of slides on the target image by using the sliding frame of the preset size in the same sliding manner as in the encryption unit;

Generating a secret key based on pixel values of a second pixel point included in the sliding frame after the sliding is completed;

decrypting the medical information based on the key to obtain decrypted medical information;

and analyzing the decrypted medical information.

In some embodiments, the smart contract is to post the generated analysis event to the blockchain after generating the analysis event; the method further comprises the steps of: and monitoring event information released in the blockchain by using the sending unit, and sending the medical information to the plurality of second user clients under the condition of monitoring the analysis event so as to enable the plurality of second users to analyze the received medical information.

In some embodiments, candidate user clients corresponding to a plurality of candidate users are connected to the transmitting unit; the method further comprises the steps of: and after the analysis event is acquired by the transmitting unit, transmitting the medical information to the plurality of candidate user clients so as to enable the plurality of candidate users to analyze the received medical information.

In some embodiments, the blockchain also includes a first alteration unit. The method further comprises the step of counting the analysis accuracy of each second user and each candidate user by using the first changing unit according to the analysis result information;

the second user and the candidate user are respectively ordered according to the analysis accuracy at regular intervals;

And exchanging identities of N second users with the analysis correct rate ranked later and N candidate users with the analysis correct rate ranked earlier.

In some embodiments, the blockchain also includes a second altering unit. The method further comprises the step of counting the analysis accuracy of each candidate user of each second user by using the second changing unit according to the analysis result information;

periodically mixing and sorting the second user and the candidate users according to the analysis accuracy;

the M users with the analysis accuracy rate ranked first are determined as second users, and the rest users are determined as candidate users.

In some embodiments, the second user client analyzes the received medical information, including:

The second user client side extracts the disease information and the diagnosis information included in the medical information by utilizing an OCR technology;

Analyzing whether the disorder information is matched with the diagnosis information according to the disorder information;

And determining that the medical information has reliability in the case that the condition information is matched with the diagnosis information.

Corresponding to any embodiment, the application also provides an analysis device. The device is applied to the intelligent analysis system shown in any of the previous embodiments. The analysis system comprises a block chain, a receiving unit, a sending unit and a certification unit, wherein the receiving unit, the sending unit and the certification unit are connected with the block chain; the blockchain comprises blockchain nodes which are subjected to consensus in advance and an analysis intelligent contract for analyzing data; the block chain node is used for realizing interaction between the receiving unit, the sending unit and the certification unit and the block chain respectively.

Referring to fig. 7, fig. 7 is a schematic structural diagram of an analysis device according to an embodiment of the application. As shown in fig. 7, the illustrated analysis apparatus 700 may include:

The receiving module 710 is configured to receive, through the receiving unit, medical information provided by the first user client, and construct an intelligent contract invoking transaction in response to the received medical information, invoke the analysis intelligent contract, and generate an analysis event; wherein the medical information includes disorder information and corresponding diagnostic information;

A sending module 720, configured to obtain the analysis event and send the analysis event to a plurality of pre-authenticated second user clients through the sending unit, so that a plurality of second users respond to the analysis event to analyze the medical information to obtain analysis result information, and invoke the analysis intelligent contract, and transfer second virtual resources corresponding to the analysis to second contract accounts corresponding to the plurality of second users respectively;

The certification storage module 730 is configured to obtain the analysis result information fed back by the plurality of second users through the certification storage unit, and call the analysis intelligent contract, so as to determine, according to the analysis result information, the number of the second users for analyzing that the medical information has reliability, and when the number reaches a first threshold, to store the medical information and the analysis result information about the medical information into the blockchain, and to transfer a first virtual resource corresponding to the medical information to a first contract account corresponding to the first user.

In some embodiments, the first user signs the medical information with its own corresponding private key; the receiving module 710 is further configured to:

and through the receiving unit, the medical information is checked by using the public key corresponding to the first user, and an intelligent contract invoking transaction is constructed under the condition that the verification is passed.

The analysis device 700 further includes an encryption module configured to send, with the encryption unit, alert information to the first user in response to the received medical information, so that the first user uploads, in response to the alert information, a target image for generating a key;

encrypting the medical information based on the key.

In some embodiments, the analysis event includes the random number, the target image, and the encrypted medical information; the second user client is a trusted client which is verified in advance; the analysis system further comprises a decryption unit deployed at the second user client;

the analysis device 700 further includes a decryption module, configured to parse the analysis event to obtain the random number, the target image and the encrypted medical information after the analysis event is acquired by using the decryption unit;

and analyzing the decrypted medical information.

In some embodiments, the smart contract is to post the generated analysis event to the blockchain after generating the analysis event; the sending module 720 is specifically configured to:

And monitoring event information released in the blockchain by using the sending unit, and sending the medical information to the plurality of second user clients under the condition of monitoring the analysis event so as to enable the plurality of second users to analyze the received medical information.

In some embodiments, candidate user clients corresponding to a plurality of candidate users are connected to the transmitting unit; the sending module 720 is specifically configured to: and after the analysis event is acquired by the transmitting unit, transmitting the medical information to the plurality of candidate user clients so as to enable the plurality of candidate users to analyze the received medical information.

In some embodiments, the blockchain also includes a first alteration unit. The analysis device 700 further includes a first changing module, configured to utilize the first changing unit to count, according to the analysis result information, analysis accuracy rates of each of the second users and each of the candidate users;

In some embodiments, the blockchain also includes a second altering unit. The analysis device 700 further includes a second changing module, configured to utilize the second changing unit to count, according to the analysis result information, an analysis accuracy of each candidate user of each second user;

One skilled in the relevant art will recognize that one or more embodiments of the application may be provided as a method, system, or computer program product. Accordingly, one or more embodiments of the application may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, one or more embodiments of the application may take the form of a computer program product on one or more computer-usable storage media (which may include, but are not limited to, magnetic disk storage, CD-ROM, optical storage, etc.) having computer-usable program code embodied therein.

"And/or" in the present application means having at least one of them. The embodiments of the present application are described in a progressive manner, and the same and similar parts of the embodiments are all referred to each other, and each embodiment is mainly described in the differences from the other embodiments. In particular, for data processing apparatus embodiments, the description is relatively simple, as it is substantially similar to method embodiments, with reference to the description of method embodiments in part.

While the application contains many specific implementation details, these should not be construed as limiting the scope of any disclosure or the scope of the claims, but rather as primarily describing features of particular embodiments of the particular disclosure. Certain features that are described in this application in the context of separate embodiments can also be implemented in combination in a single embodiment. On the other hand, the various features described in the individual embodiments may also be implemented separately in the various embodiments or in any suitable subcombination. Furthermore, although features may be acting in certain combinations and even initially claimed as such, one or more features from a claimed combination can in some cases be excised from the combination, and the claimed combination may be directed to a subcombination or variation of a subcombination.

Similarly, although operations are depicted in the drawings in a particular order, this should not be understood as requiring that such operations be performed in the particular order shown or in sequential order, or that all illustrated operations be performed, to achieve desirable results. In some cases, multitasking and parallel processing may be advantageous. Moreover, the separation of various system modules and components in the embodiments described should not be understood as requiring such separation in all embodiments, and it should be understood that the described program components and systems can generally be integrated together in a single software product or packaged into multiple software products.

The foregoing description of the preferred embodiment(s) of the application is merely illustrative of the presently preferred embodiment(s) of the application, and is not intended to limit the embodiment(s) of the application to the particular form disclosed, since various modifications, equivalent arrangements, improvements, etc., may be made within the spirit and scope of the embodiment(s) of the application.

Claims

1. The intelligent analysis system for industry big data is characterized by comprising a block chain, a receiving unit, a sending unit and a certification unit, wherein the receiving unit, the sending unit and the certification unit are connected with the block chain; the blockchain comprises blockchain nodes which are subjected to consensus in advance and an analysis intelligent contract for analyzing data; the block chain node is used for realizing interaction between the receiving unit, the sending unit and the certification storing unit and the block chain respectively;

the receiving unit is used for receiving medical information provided by the first user client and constructing an intelligent contract calling transaction in response to the received medical information, calling the analysis intelligent contract and generating an analysis event; wherein the medical information includes disorder information and corresponding diagnostic information;

the sending unit is configured to obtain the analysis event and send the analysis event to a plurality of pre-authenticated second user clients, so that the plurality of second users respond to the analysis event to analyze the medical information to obtain analysis result information and call the analysis intelligent contract, and transfer second virtual resources corresponding to the analysis to second contract accounts corresponding to the plurality of second users;

2. The system of claim 1, wherein the first user signs the medical information with its own corresponding private key;

the receiving unit is used for:

And verifying the medical information by using the public key corresponding to the first user, and constructing an intelligent contract invoking transaction under the condition that verification is passed.

3. The system of claim 2, wherein the first user client is a pre-authenticated trusted client; the analysis system further comprises an encryption unit deployed at the first user client;

the encryption unit is used for responding to the received medical information and sending reminding information to the first user so that the first user can respond to the reminding information to upload a target image for generating a secret key;

encrypting the medical information based on the key.

4. The system of claim 3, wherein the analysis event comprises the random number, the target image, and the encrypted medical information; the second user client is a trusted client which is verified in advance; the analysis system further comprises a decryption unit deployed at the second user client;

the decryption unit is used for:

after the analysis event is acquired, analyzing the analysis event to obtain the random number, the target image and the encrypted medical information;

and analyzing the decrypted medical information.

5. The system of claim 1, wherein the smart contract is configured to post the generated analysis event to the blockchain after generating the analysis event;

The sending unit is configured to:

And monitoring event information released in the blockchain, and sending the medical information to the plurality of second user clients under the condition that the analysis event is monitored, so that the plurality of second users analyze the received medical information.

6. The system according to claim 1, wherein candidate user clients corresponding to a plurality of candidate users are connected to the transmitting unit;

The sending unit is configured to:

and after the analysis event is acquired, the medical information is sent to the candidate user clients so that the candidate users analyze the received medical information.

7. The system of claim 6, wherein the blockchain further comprises a first altering unit to:

According to the analysis result information, counting the analysis accuracy of each second user and each candidate user;

8. The system of claim 6, wherein the blockchain further comprises a second altering unit to:

according to the analysis result information, counting the analysis accuracy of each candidate user of each second user;

9. The system of claim 1, wherein the second user client analyzing the received medical information comprises:

10. The system of claim 1, wherein the receiving unit, the sending unit, and the certification unit are all deployed on a BaaS platform.