CN115938527A - Method, system, equipment and medium for sharing and publishing medical data - Google Patents
Method, system, equipment and medium for sharing and publishing medical data Download PDFInfo
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- CN115938527A CN115938527A CN202211512170.9A CN202211512170A CN115938527A CN 115938527 A CN115938527 A CN 115938527A CN 202211512170 A CN202211512170 A CN 202211512170A CN 115938527 A CN115938527 A CN 115938527A
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Abstract
The invention discloses a method, a system, equipment and a medium for sharing and releasing medical data, wherein the method comprises the following steps: the medical facility registers with the CA server to qualify as a legitimate member node of the federation blockchain. The medical institution establishes a medical database to store medical data. In the medical data sharing process: the requester needs to pay the participants an incentive to encourage more medical institutions to participate in the sharing of medical data. The participants will process the raw medical data by using the KPrivBayes algorithm. The requester and the participants interact by calling the intelligent contracts which are already deployed on the block chain of the alliance, and medical data sharing transactions generated by the intelligent contracts are recorded and permanently stored. The medical data publishing process is completed through data interaction between the data publishing server and the medical data publishing platform. The invention has the advantages that: the medical data sharing and publishing method can efficiently share and publish the medical data and can avoid data privacy disclosure. The defect that effective privacy protection cannot be provided in the conventional medical system is overcome.
Description
Technical Field
The present invention relates to the field of block chain technology, and in particular, to a method, system, device, and medium for sharing and publishing medical data.
Background
Medical treatment is a data intensive field, with a large amount of medical data being recorded, stored and accessed each day, which data is generated throughout a patient's visit and indicates the patient's health status. Since the 4.0 era of medical care, medical services have increasingly relied on intelligent technologies driven by medical data sharing, which can greatly improve the quality of medical services, accelerate drug development, and reduce medical costs. The need to share and utilize medical data between medical institutions continues to rise, and in addition, some medical institutions need to publish their medical data to relevant departments for analysis and to draw valuable conclusions. For example, sharing and publishing infectious disease data is critical to preventing and controlling infectious diseases, helping to provide epidemic forewarning, and making scientific decisions. However, medical data contains a considerable amount of privacy information of patients, and the risk of privacy disclosure causes an information island problem, which prevents them from sharing and publishing the medical data, resulting in waste of medical resources. Therefore, there is an urgent need to find a safe medical data sharing and distribution scheme.
The key point is that a chained data structure is adopted to ensure that data cannot be falsified, trust is established through a consensus mechanism, and the cryptography technology is used to ensure transaction safety, so that the method has the characteristics of decentralization, high credibility, high fault tolerance, incapability of falsification and the like. At present, a lot of intensive research is being carried out in the field of application of block chains in the medical industry at home and abroad, for example, media Lab of the Massachusetts institute of technology proposes an electronic medical record management system MedRec [ Azaria, A., ekblaw, A., vieira, T., & Lippman, A. (2016, augst.) Medrec: using block chains for the direct data access and the permanent identification management. In 2016 and international conference On and Big Data (OBD) (pp.25-30) IEEE ], which uses block chains and intelligent contracts to manage the authorization of electronic medical records. Charache et al designed a medical data sharing system, medichar [ Xia, q.i., sifah, e.b., asamoah, k.o., gao, j., du, x, & Guizani, m. (2017) & Trus t-less medical data sharing apparatus via ieee access,5,14757-14767], which combines a block chain and cloud-based services, solving the problem of medical data sharing in an untrusted environment. The system uses intelligent contracts and access control mechanisms to efficiently track data activity and revoke access to violating entities if a violation of data permissions is found.
The existing medical system has the defects of low operation efficiency, large calculation cost, limited data storage capacity and the like due to the lagging of the adopted technical system structure. And most of the solutions based on only considering privacy protection in the aspect of access control mechanisms except for sensitive data, the requirements in the aspect of privacy protection in practical application cannot be completely met.
Disclosure of Invention
Aiming at the defects of the prior art, the invention provides a method, a system, equipment and a medium for sharing and publishing medical data. The method can not only efficiently share and release medical data, but also avoid data privacy disclosure. The defects that in the existing medical system, privacy protection measures are lacked, and effective privacy protection cannot be provided in the application occasions with strict privacy information of patients are overcome.
In order to realize the purpose of the invention, the technical scheme adopted by the invention is as follows:
a method of medical data sharing and publishing, comprising the steps of:
step 1: before the healthcare institutions participate in medical data sharing, they should register with the CA server to qualify as a legitimate member node of the federation blockchain.
And 2, step: the medical institution establishes a medical database to store medical data, and then judges whether the medical data needs privacy protection processing or not, and the data which is not subjected to the privacy protection processing is only limited to local access and cannot be shared.
And 3, step 3: in the medical data sharing process, there are two types of entities: a requestor and a participant. Requestors of medical data sharing need to pay rewards to participants in order to encourage more medical institutions to participate in medical data sharing. The participants will process the raw medical data using KPrivBayes algorithm to protect individual privacy in the medical data and to determine a privacy budget agreed upon by both parties. The requester and the participants interact by calling the intelligent contracts which are already deployed on the block chain of the alliance, and medical data sharing transactions generated by the intelligent contracts are recorded and permanently stored.
And 4, step 4: whether the medical data need to be published is judged, the medical data publishing process is completed through data interaction between the data publishing server and the medical data publishing platform, and the shared medical data can be published outwards to meet the public demand for the medical data.
Further, the registration process in step 1 is as follows:
first, the information provided by the medical institution needs to be verified at the CA server to ensure the authenticity of the medical institution identity.
Then, the other members in the federation blockchain are required to perform a review by invoking an intelligent contract defined based on the BFT algorithm. Specifically, if the join application obtains approval of more than 2/3 member authorities, the candidate authority will be allowed to enter the federation blockchain and join the intelligent contract as a member of the verifier.
Further, the medical database in step 2 employs IPFS to store medical data.
Further, the KPrivBayes algorithm flow in step 3 is as follows:
step 3-1: the data set is first partitioned using the DP-k-prototype algorithm. (1) randomly partitioning the data points into n × k clusters. And (2) calculating a clustering center. (3) assigning the data point to the closest cluster. (4) And (4) repeating the steps (2) and (3) until the maximum iteration number is reached. (5) merging the n × k clusters into k clusters. (6) returning k clusters as results.
Step 3-2: a bayesian network is constructed from the data set.
Step 3-3: and generating a conditional distribution by using the Bayesian network constructed in the step 3-2, and adding noise by using a differential privacy technology.
Step 3-4: and synthesizing a privacy protection data set by using the Bayesian network constructed in the step 3-2 and the noise condition distribution generated in the step 3-3.
The invention also discloses a system for sharing and publishing medical data, which can be used for implementing the method for sharing and publishing the medical data, and specifically comprises the following steps: the system comprises a CA server, an intelligent contract module, a medical database, a requester module, a participant module, a data publishing server and a medical data publishing platform;
the CA server: the method is used for registering the medical institution to the CA server before the medical institution participates in medical data sharing, and the authenticity of the medical institution identity is ensured through verification on the CA server, so that the qualification of becoming a legal member node of the block chain of the alliance is obtained.
The intelligent contract module: a review is made of the medical institutions applying for participation in medical data sharing. Upon approval, the candidate organization will be allowed to enter the federation blockchain and join the intelligent contract as a member of the verifier.
A medical database: for storing medical data
A requester module: for paying rewards to participants to incentivize more medical institutions to participate in medical data sharing and to interact with participant modules.
A participant module: for processing raw medical data using the KPrivBayes algorithm to protect individual privacy in the medical data and to determine a privacy budget agreed upon by both parties and to interact with the requester module.
The data release server: and the data storage module is used for storing the data to be issued.
Medical data publishing platform: the medical data sharing system is used for publishing the shared medical data to the outside so as to meet the public demand for the medical data.
The invention also discloses computer equipment which comprises a memory, a processor and a computer program stored on the memory and capable of running on the processor, wherein the processor executes the program to realize the medical data sharing and publishing method.
The invention also discloses a computer readable storage medium, on which a computer program is stored, which when executed by a processor implements the above method of medical data sharing and publishing.
Compared with the prior art, the invention has the advantages that:
the blockchain and differential privacy technology are combined, so that medical data can be shared and published more safely and efficiently. The KPrivBayes algorithm is designed to generate a synthetic data set meeting the difference privacy, and the synthetic data set is applied to the medical data sharing process to protect the medical data privacy of the patient. Secondly, a decentralized framework is provided by utilizing the block chain, information barriers among medical institutions are broken, high-efficiency intercommunication of medical data is realized, and the application requirements are met.
Drawings
FIG. 1 is a flow chart of a method for sharing and publishing medical data according to an embodiment of the invention;
fig. 2 is a flow chart of the KPrivBayes algorithm according to an embodiment of the invention.
Detailed Description
In order to make the objects, technical solutions and advantages of the present invention more apparent, the present invention will be further described in detail below with reference to the accompanying drawings by way of examples.
As shown in fig. 1, a method for sharing and publishing medical data includes the following steps:
step 1: before the healthcare institutions participate in medical data sharing, they should register with the CA server to qualify as a legitimate member node of the federation blockchain. The registration process can be divided into two phases. First, the information provided by the medical institution needs to be verified at the CA server to ensure the authenticity of the medical institution identity. Then, the other members in the federation blockchain are required to perform a review by invoking an intelligent contract defined based on the BFT algorithm. Specifically, if the join application obtains approval of more than 2/3 member enterprises, the candidate enterprise will be allowed to enter the federation blockchain and join the intelligent contract as a member of the verifier.
Step 2: in the scheme, the storage efficiency of the block chain technology to large-scale data is low, and the cost is high, so that the IPFS is adopted to store the medical data. Because IPFS assigns a unique hash value according to file content, the IPFS can ensure the uniqueness of data in a medical scene, which is of great significance in practical application. And then judging whether privacy protection processing is needed or not, wherein the data which is not subjected to the privacy protection processing is only locally accessed and cannot be shared.
And step 3: in the medical data sharing process, there are two types of entities: a requestor and a participant. The requester of medical data sharing needs to pay the participants an incentive to encourage more medical institutions to participate in the medical data sharing. The participants will process the raw medical data using the KPrivBayes algorithm to protect individual privacy in the medical data and to determine a privacy budget agreed upon by both parties. The requester and the participants interact by calling the intelligent contracts which are already deployed on the block chain of the alliance, and medical data sharing transactions generated by the intelligent contracts are recorded and permanently stored.
The kprivvbies algorithm proposed by the present invention is described in further detail below in conjunction with fig. 2.
Step 3-1: the data set is first partitioned using the DP-k-prototype algorithm. (1) randomly partitioning the data points into n × k clusters. And (2) calculating a clustering center. (3) assigning the data point to the closest cluster. (4) And (4) repeating the steps (2) and (3) until the maximum iteration number is reached. (5) merging the n × k clusters into k clusters. (6) returning k clusters as results.
Step 3-2: a bayesian network is constructed from the data set.
Step 3-3: generating a conditional distribution using the Bayesian network constructed in step 3-2, and adding noise using a differential privacy technique.
Step 3-4: and synthesizing a privacy protection data set by using the Bayesian network constructed in the step 3-2 and the noise condition distribution generated in the step 3-3.
And 4, step 4: whether the medical data need to be published is judged, the medical data publishing process is completed through data interaction between the data publishing server and the medical data publishing platform, and the shared medical data can be published outwards to meet the public demand for the medical data.
In another embodiment of the present invention, a system for sharing and publishing medical data is provided, where the system can be used to implement the method for sharing and publishing medical data described above, and specifically includes: the system comprises a CA server, an intelligent contract module, a medical database, a requester module, a participant module, a data publishing server and a medical data publishing platform;
the CA server: the method is used for registering the medical institution to the CA server before the medical institution participates in medical data sharing, and the authenticity of the medical institution identity is ensured through verification on the CA server, so that the qualification of becoming a legal member node of the block chain of the alliance is obtained.
The intelligent contract module: a review is made of the medical institutions applying for participation in medical data sharing. Upon approval, the candidate organization will be allowed to enter the federation blockchain and join the intelligent contract as a member of the verifier.
A medical database: for storing medical data
The requester module: for paying rewards to participants to incentivize more medical institutions to participate in medical data sharing and to interact with participant modules.
A participant module: for processing raw medical data using the KPrivBayes algorithm to protect individual privacy in the medical data and to determine a privacy budget agreed upon by both parties and to interact with the requester module.
The data release server: used for storing the data to be issued.
Medical data publishing platform: the medical data sharing system is used for publishing the shared medical data to the outside so as to meet the public demand for the medical data.
In yet another embodiment of the present invention, a terminal device is provided that includes a processor and a memory for storing a computer program comprising program instructions, the processor being configured to execute the program instructions stored by the computer storage medium. The Processor may be a Central Processing Unit (CPU), or may be other general purpose Processor, a Digital Signal Processor (DSP), an Application Specific Integrated Circuit (ASIC), an off-the-shelf Programmable gate array (FPGA) or other Programmable logic device, a discrete gate or transistor logic device, a discrete hardware component, etc., which is a computing core and a control core of the terminal, and is adapted to implement one or more instructions, and is specifically adapted to load and execute one or more instructions to implement a corresponding method flow or a corresponding function; the processor of the embodiment of the invention can be used for the operation of the method for sharing and publishing the medical data, and comprises the following steps:
step 1: before the healthcare institutions participate in medical data sharing, they should register with the CA server to qualify as a legitimate member node of the federation blockchain.
Step 2: the medical institution establishes a medical database to store medical data, and then judges whether the medical data needs privacy protection processing or not, and the data which is not subjected to the privacy protection processing is only limited to local access and cannot be shared.
And 3, step 3: in the medical data sharing process, there are two types of entities: a requester and a participant. The requester of medical data sharing needs to pay the participants an incentive to encourage more medical institutions to participate in the medical data sharing. The participants will process the raw medical data using KPrivBayes algorithm to protect individual privacy in the medical data and to determine a privacy budget agreed upon by both parties. The requester and the participants interact by calling the intelligent contract which is already deployed on the block chain of the alliance, and the medical data sharing transaction generated by the intelligent contract is recorded and permanently stored.
And 4, step 4: whether the medical data need to be published is judged, the medical data publishing process is completed through data interaction between the data publishing server and the medical data publishing platform, and the shared medical data can be published outwards to meet the public demand for the medical data.
In still another embodiment of the present invention, the present invention further provides a storage medium, specifically a computer-readable storage medium (Memory), which is a Memory device in a terminal device and is used for storing programs and data. It is understood that the computer readable storage medium herein may include a built-in storage medium in the terminal device, and may also include an extended storage medium supported by the terminal device. The computer-readable storage medium provides a storage space storing an operating system of the terminal. Also, the memory space stores one or more instructions, which may be one or more computer programs (including program code), adapted to be loaded and executed by the processor. It should be noted that the computer readable storage medium may be a high-speed RAM memory, or a non-volatile memory (non-volatile memory), such as at least one disk memory.
One or more instructions stored in the computer-readable storage medium may be loaded and executed by the processor to implement the corresponding steps of the method for sharing and publishing medical data in the above embodiment; one or more instructions in the computer readable storage medium are loaded by the processor and perform the steps of:
step 1: before healthcare institutions participate in medical data sharing, they should register with the CA server to qualify as a legitimate member node of the federation blockchain.
Step 2: the medical institution establishes a medical database to store medical data, and then judges whether the medical data needs privacy protection processing or not, and the data which is not subjected to the privacy protection processing is only limited to local access and cannot be shared.
And step 3: in the medical data sharing process, there are two types of entities: a requestor and a participant. The requester of medical data sharing needs to pay the participants an incentive to encourage more medical institutions to participate in the medical data sharing. The participants will process the raw medical data using the KPrivBayes algorithm to protect individual privacy in the medical data and to determine a privacy budget agreed upon by both parties. The requester and the participants interact by calling the intelligent contract which is already deployed on the block chain of the alliance, and the medical data sharing transaction generated by the intelligent contract is recorded and permanently stored.
And 4, step 4: whether the medical data need to be published is judged, the medical data publishing process is completed through data interaction between the data publishing server and the medical data publishing platform, and the shared medical data can be published outwards to meet the public demand for the medical data.
As will be appreciated by one skilled in the art, embodiments of the present invention may be provided as a method, system, or computer program product. Accordingly, the present invention may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, the present invention may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, and the like) having computer-usable program code embodied therein.
The present invention is described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the invention. It will be understood that each flow and/or block of the flowchart illustrations and/or block diagrams, and combinations of flows and/or blocks in the flowchart illustrations and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instruction means which implement the function specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
It will be appreciated by those of ordinary skill in the art that the examples described herein are intended to assist the reader in understanding the manner in which the invention is practiced, and it is to be understood that the scope of the invention is not limited to such specifically recited statements and examples. Those skilled in the art, having the benefit of this disclosure, may effect numerous modifications thereto and changes may be made without departing from the scope of the invention in its aspects.
Claims (7)
1. A method for sharing and publishing medical data is characterized by comprising the following steps:
step 1: before the medical institutions participate in medical data sharing, they should register with the CA server to qualify as a legitimate member node of the federation blockchain;
step 2: the medical institution establishes a medical database to store medical data, and then judges whether the medical data needs privacy protection processing or not, and the data which is not subjected to the privacy protection processing is only limited to local access and cannot be shared;
and 3, step 3: in the medical data sharing process, there are two types of entities: a requestor and a participant; the requester of the medical data sharing needs to pay the reward to the participants to encourage more medical institutions to participate in the medical data sharing; the participants will process the raw medical data by using the KPrivBayes algorithm to protect individual privacy in the medical data and to determine a privacy budget agreed by both parties; the requester and the participant interact by calling an intelligent contract which is already deployed on the block chain of the alliance, and medical data sharing transaction generated by the intelligent contract is recorded and permanently stored;
and 4, step 4: whether the medical data need to be published is judged, the medical data publishing process is completed through data interaction between the data publishing server and the medical data publishing platform, and the shared medical data can be published outwards to meet the public demand for the medical data.
2. The method for sharing and publishing medical data according to claim 1, wherein the registration process in step 1 is as follows:
firstly, the information provided by the medical institution needs to be verified on a CA server to ensure the authenticity of the identity of the medical institution;
then, other members in the alliance block chain need to carry out examination by calling an intelligent contract defined based on a BFT algorithm; specifically, if the join application obtains approval of more than 2/3 member authorities, the candidate authority will be allowed to enter the federation blockchain and join the intelligent contract as a member of the verifier.
3. The method for sharing and publishing medical data according to claim 1, wherein: step 2 the medical database uses IPFS to store medical data.
4. The method for sharing and publishing medical data according to claim 1, wherein the KPrivBayes algorithm flow in step 3 is as follows:
step 3-1: firstly, segmenting a data set by using a DP-k-prototype algorithm; (1) randomly dividing the data points into n x k clusters; (2) calculating a clustering center; (3) assigning the data point to the closest cluster; (4) Repeating the steps (2) and (3) until the maximum iteration number is reached; (5) merging the n × k clusters into k clusters; (6) returning k clusters as results;
step 3-2: constructing a Bayesian network from the data set;
step 3-3: generating conditional distribution by using the Bayesian network constructed in the step 3-2, and adding noise by using a differential privacy technology;
step 3-4: and synthesizing a privacy protection data set by using the Bayesian network constructed in the step 3-2 and the noise condition distribution generated in the step 3-3.
5. A system for sharing and publishing medical data, comprising: the system can be used to implement the method of medical data sharing and publishing according to one of claims 1 to 4, the system comprising: the system comprises a CA server, an intelligent contract module, a medical database, a requester module, a participant module, a data publishing server and a medical data publishing platform;
the CA server: before the medical institution participates in medical data sharing, the medical institution registers in the CA server and verifies the medical institution through the CA server to ensure the authenticity of the medical institution identity and obtain the qualification of becoming a legal member node of the block chain of the alliance;
the intelligent contract module: examining medical institutions applying for participation in medical data sharing; after approval, the candidate organization is allowed to enter the block chain of the alliance and join the intelligent contract as a member of the verifier;
a medical database: for storing medical data
A requester module: for paying rewards to the participants to incentivize more medical institutions to participate in medical data sharing and to interact with the participant modules;
a participant module: for processing raw medical data using KPrivBayes algorithm to protect individual privacy in the medical data and to determine a privacy budget agreed upon by both parties and to interact with the requester module;
the data release server: the system is used for storing data to be issued;
medical data publishing platform: the medical data publishing system is used for publishing the shared medical data to meet the public demand for the medical data.
6. A computer device, characterized by: comprising a memory, a processor and a computer program stored on the memory and executable on the processor, the processor implementing the method of sharing and publishing medical data according to one of claims 1 to 4 when executing the program.
7. A computer-readable storage medium characterized by: a computer-readable storage medium having stored thereon a computer program which, when executed by a processor, implements the method of sharing and publishing medical data according to one of claims 1 to 4.
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| US20200388359A1 (en) * | 2019-02-01 | 2020-12-10 | Rekha Bhandari | Methods and system of blockchain-based medical service management |
| US20200327969A1 (en) * | 2019-04-12 | 2020-10-15 | International Business Machines Corporation | System and method to share and utilize healthcare data |
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