CN116226062A - Data sharing method and device based on privacy protection - Google Patents

Abstract

Embodiments of the present disclosure relate to a method, node, distributed system and storage medium for data sharing under the premise of privacy protection, and relate to the computer field. According to the method, private data is obtained from local data including private data and first non-private data, the first non-private data is associated with the private data; a hash value of the private data is generated; a local identifier for the local data is generated The first association with the hash value; generate a global identifier for indexing the hash value in the distributed system, which is associated with the current node; generate the second between the global identifier and the hash value associating; and sending the second association to other nodes in the distributed system, so as to store the second association in the distributed system for connection sharing of the first non-private data. As a result, non-private data can be shared safely under the premise of protecting local private data.

Description

A data sharing method and device based on privacy protection

technical field

The embodiments of the present disclosure generally relate to the computer field, and specifically relate to a method for data sharing under the premise of privacy protection, a data providing node, a data using node, a distributed system, and a computer storage medium.

Background technique

In the era of artificial intelligence, data has become an important strategic resource. Based on the strategic and security needs of countries and enterprises, the protection of data privacy is becoming more and more stringent. On the other hand, data analysis and artificial intelligence model training often require a large amount of data. How to conduct data analysis and artificial intelligence model training under the premise of protecting data privacy has become a very important research direction in the current computer field.

Contents of the invention

Provided are a method for data sharing, a data providing node, a data using node, a distributed system, and a computer storage medium, capable of safely sharing non-private data on the premise of protecting local private data.

According to a first aspect of the present disclosure, a method for data sharing is provided. The method includes: obtaining private data from local data including private data and first non-private data, the first non-private data being associated with the private data; generating a hash value of the private data; generating a local identifier for the local data The first association with the hash value; generate a global identifier for indexing the hash value in the distributed system, which is associated with the current node; generate the second between the global identifier and the hash value associating; and sending the second association to other nodes in the distributed system, so as to store the second association in the distributed system for connection sharing of the first non-private data.

According to a second aspect of the present disclosure, a method for data sharing is provided. The method includes: generating data condition information based on joint metadata stored in a distributed system, the joint metadata at least includes associations between global identifiers and multiple attribute information of multiple non-private data, global identifiers and private data The hash value is associated, the private data is associated with multiple non-private data, and multiple non-private data are located in multiple data providing nodes in the distributed system; data requests are sent to multiple data providing nodes, and the data requests include data conditions information; and receiving at least one item of non-private data matching the data condition information from at least one data providing node among the plurality of data providing nodes.

According to a third aspect of the present disclosure, a data providing node is provided. The data providing node includes: at least one processor, and a memory communicatively connected to the at least one processor, wherein the memory stores instructions executable by the at least one processor, and the instructions are executed by the at least one processor, so that at least one processing A device capable of performing the method according to the first aspect.

According to a fourth aspect of the present disclosure, a data usage node is provided. The data usage node includes: at least one processor, and a memory communicatively connected to the at least one processor, wherein the memory stores instructions executable by the at least one processor, and the instructions are executed by the at least one processor, so that the at least one processing The device is capable of performing the method according to the second aspect.

According to a fifth aspect of the present disclosure, a distributed system is provided. The distributed system includes: a plurality of data providing nodes according to the third aspect of the present disclosure; and a data using node according to the fourth aspect of the present disclosure.

In a sixth aspect of the present disclosure, a computer-readable storage medium is provided, on which a computer program is stored, and when the program is executed by a processor, the method according to the first aspect or the second aspect of the present disclosure is implemented.

It should be understood that what is described in this section is not intended to identify key or important features of the embodiments of the present disclosure, nor is it intended to limit the scope of the present disclosure. Other features of the present disclosure will be readily understood through the following description.

Description of drawings

The above and other features, advantages and aspects of the various embodiments of the present disclosure will become more apparent with reference to the following detailed description when taken in conjunction with the accompanying drawings. In the drawings, the same or similar reference numerals denote the same or similar elements.

FIG. 1 is a schematic diagram of a distributed system 100 according to an embodiment of the present disclosure.

FIG. 2 is a schematic diagram of a method 200 for data sharing according to an embodiment of the present disclosure.

FIG. 3 is a schematic diagram of a method 300 for data sharing according to an embodiment of the present disclosure.

FIG. 4 is a schematic diagram of a method 400 for data sharing according to an embodiment of the present disclosure.

FIG. 5 is a schematic diagram of a method 500 for data sharing according to an embodiment of the present disclosure.

FIG. 6 is a schematic diagram of a method 600 for data sharing according to an embodiment of the present disclosure.

FIG. 7 is a schematic diagram of a method 700 for data sharing according to an embodiment of the present disclosure.

FIG. 8 is a block diagram of an electronic device used to implement the method for data sharing according to an embodiment of the present disclosure.

Detailed ways

Exemplary embodiments of the present disclosure are described below in conjunction with the accompanying drawings, which include various details of the embodiments of the present disclosure to facilitate understanding, and they should be regarded as exemplary only. Accordingly, those of ordinary skill in the art will recognize that various changes and modifications of the embodiments described herein can be made without departing from the scope and spirit of the disclosure. Also, descriptions of well-known functions and constructions are omitted in the following description for clarity and conciseness.

As used herein, the term "comprise" and its variants mean open inclusion, ie "including but not limited to". The term "or" means "and/or" unless otherwise stated. The term "based on" means "based at least in part on". The terms "one example embodiment" and "one embodiment" mean "at least one example embodiment." The term "another embodiment" means "at least one further embodiment". The terms "first", "second", etc. may refer to different or the same object. Other definitions, both express and implied, may also be included below.

As mentioned above, in actual data analysis and artificial intelligence model training tasks, it is often necessary to use data from different nodes or regions (including individuals, companies or countries). According to the data security law, the privacy data related to personal identity of each node or area cannot leave the node or area. In general information system design, local data in nodes or regions can be queried and extracted through local identification codes (LID, Local ID). Each LID is often used to uniquely identify different individuals in the data, including but not limited to patient numbers and customer numbers. Because the generation methods of LID in the system design of different nodes or regions are often inconsistent, the LIDs of the local data of the same individual in different nodes or regions are often different.

In addition, due to data privacy protection requirements between various nodes or regions, it is impossible to directly share all source data. In data analysis and artificial intelligence model training, it is often desired to associate data from different nodes or regions, so as to improve the data coverage and result accuracy of data analysis and model training. How to associate and share non-private data content in different areas under the premise of protecting private data for relevant data analysis and artificial intelligence model training is a very important issue.

In order to at least partially address one or more of the above-mentioned problems as well as other potential problems, example embodiments of the present disclosure propose a scheme for data sharing. In this solution, the data providing node acquires private data from local data including private data and first non-private data, and the first non-private data is associated with the private data. The data providing node generates a hash value of the private data, and generates a first association between the local identifier for the local data and the hash value. The data providing node generates a global identifier for indexing the hash value in the distributed system associated with the current node, and generates a second association between the global identifier and the hash value. Subsequently, the data providing node sends the second association to other nodes in the distributed system, so as to store the second association in the distributed system for connection sharing of the first non-private data. In this way, the first association between the local identifier of the local data and the hash value of the private data stored locally and the relationship between the global identifier and the hash value of the private data stored in the distributed system can be The second association can safely share non-private data under the premise of protecting local private data. In addition, the second association between the global identifier stored in the distributed system and the hash value of the private data also facilitates associating different non-private data at different nodes in the distributed system for data analysis and model training.

Hereinafter, specific examples of this solution will be described in more detail with reference to the accompanying drawings.

FIG. 1 shows a schematic diagram of an example of a distributed system 100 according to an embodiment of the present disclosure. The distributed system 100 may include a data usage node 110 and a plurality of data providing nodes 120 - 1 to 120 - n (hereinafter collectively referred to as 120 ), where n is greater than or equal to two.

Examples of data usage nodes 110 and data provider nodes 120 include, but are not limited to, personal computers, desktop computers, laptop computers, tablet computers, wearable devices, personal digital assistants, smartphones, vehicle electronics, server computers, multiprocessor systems , a large computer, a distributed computing environment including any one of the above-mentioned systems or devices, and the like.

Each data providing node 120 may store local data. The local data may have a local data identifier (LID) for identifying and indexing the local data at the data providing node 120 . Local data may include private data and non-private data, where non-private data is associated with private data. Privacy data is related to personal identity, which may include but not limited to ID number, mobile phone number, name, address and zip code, etc. Non-private data has nothing to do with personal identity, which may include but not limited to age, gender, city, disease history, commodity purchase history, etc. Non-private data can include one or more attribute information, such as cancer drugs, high blood pressure drugs, etc. Different data providing nodes 120 may have different non-private data associated with the same private data. For example, the data providing node 120-1 may have user A's cancer drug information, and the data providing node 120-2 may have user A's high blood pressure drug information.

Different data providing nodes 120 may be located in different regions, eg belong to different individuals, companies or countries.

In some embodiments, the distributed system 100 may be a blockchain system, and the data using nodes 110 and the data providing nodes 120 may be blockchain nodes.

The data providing node 120 can be used to obtain private data from local data including private data and first non-private data, the first non-private data is associated with the private data; generate a hash value (PHash) of the private data; generate a hash value (PHash) for the local A first association (LID-PHash) between the local identifier (LID) of the data and the hash value; generate a global identifier (GID, Global ID) for indexing the hash value in the distributed system 100, distributed The system 100 associates with the current node; generates a second association (GID-PHash) between the global identifier and the hash value; n and the data usage node 110) send the second association to store the second association in the distributed system 100 for connection sharing of the first non-private data.

In addition, the data providing node 120-1 can also be used to obtain the first attribute information of the first non-private data from the current node; 2 to 120-n) Obtain one or more second attribute information of one or more second non-private data, and one or more second non-private data are associated with private data; based on the second association, generate Federation metadata (Federated Metadata), federated metadata at least includes the global identifier, the association between the first attribute information and one or more second attribute information; and other nodes in the distributed system 100 (such as data Provider nodes 120-2 to 120-n and data usage nodes 110) send joint metadata to store joint metadata in distributed system 100 for the first non-private data and one or more second non-private data Data connection sharing.

The data usage node 110 can be used to generate data condition information based on the joint metadata stored in the distributed system 100. The joint metadata includes at least the association between the global identifier and multiple attribute information of multiple non-private data, and the global identifier The symbol is associated with the hash value of the privacy data, and the privacy data is associated with a plurality of non-privacy data, and the plurality of non-privacy data are located in the multiple data providing nodes 120 in the distributed system 100; sending data to the multiple data providing nodes 120 request, the data request includes data condition information; and at least one item of non-private data matching the data condition information is received from at least one data providing node among the plurality of data providing nodes 120 .

Thus, through the first association between the local identifier of the local data and the hash value of the private data stored locally and the second association between the global identifier and the hash value of the private data stored in the distributed system Two associations can safely share non-private data on the premise of protecting local private data. In addition, the second association between the global identifier stored in the distributed system and the hash value of the private data also facilitates associating different non-private data at different nodes in the distributed system for data analysis and model training. In addition, by storing joint metadata associated with different attribute information of different non-private data at different data providing nodes in the distributed system, the data using nodes can easily know what information exists in the entire system without knowing any private data. attribute information.

Fig. 2 shows a flowchart of a method 200 for data sharing according to an embodiment of the present disclosure. For example, the method 200 may be performed by the data providing node 120-1 as shown in FIG. 1 . It should be understood that method 200 may also include additional blocks not shown and/or blocks shown may be omitted, and that the scope of the present disclosure is not limited in this respect. It should also be understood that although the data providing node 120-1 is used as an example for illustration, it may also be implemented by other data providing nodes 120-2 to 120-n, and the scope of the present disclosure is not limited here.

At block 202, the data providing node 120-1 obtains private data from local data including private data and first non-private data, the first non-private data being associated with the private data.

For example, private data may include but not limited to ID card number, name + address zip code or name + mobile phone number, etc.

At block 204, the data providing node 120-1 generates a hash value (PHash) of the private data.

For example, a hash function (Hash Function) calculation can be performed on private data such as ID number, name + address zip code or name + mobile phone number to generate a hash value. Hash functions include, but are not limited to, SHA-256, SHA-512, and the like, for example.

In some embodiments, the data providing node 120-1 may process the private data based on a predetermined format to generate formatted private data, and perform hash function calculation on the formatted private data to generate a hash value. The predetermined format is the same for different data providing nodes, so as to ensure the consistency of hash calculation results.

At block 206, the data providing node 120 generates a first association (LID-PHash) between a local identifier (LID) for the local data and a hash value (PHash).

At the current or the same node, the hash value (PHash) of the private data and the local identifier (LID) can be in one-to-one correspondence. In different nodes, for the same individual, such as the same patient, the local identifier (LID) is often different, but the hash value (PHash) of the private data is the same. Through the hash value (PHash) of private data, non-private data of the same individual at different nodes can be associated. The hash value (PHash) of private data can be shared in a distributed system outside the node for data connection. Due to the one-way hidden property of the hash function (Hiding Property), the data user node has no way to deduce any private data information related to personal identity based on the hash value, so as to effectively protect the local private data.

At block 208, the data providing node 120-1 generates a global identifier (GID) for indexing the hash value (PHash) in the distributed system 100 associated with the current node.

Global identifiers (GIDs) may be generated according to any suitable identifier indexing requirements.

In some embodiments, the data providing node 120 - 1 may first determine whether there is a global identifier associated with the hash value in the distributed system 100 . If it is determined that there is no global identifier associated with the hash value, a global identifier for indexing the hash value (PHash) in the distributed system 100 is generated. If it is determined that there is a global identifier associated with the hash value, the global identifier for indexing the hash value (PHash) in the distributed system 100 is not generated.

At block 210, the data providing node 120-1 generates a second association (GID-PHash) between the global identifier (GID) and the hash value (PHash).

At block 212, the data providing node 120-1 sends the second association to other nodes in the distributed system 110 to store the second association in the distributed system 110 for connection sharing of the first non-private data . It should be understood that the connection sharing here means that the first non-private data can be connected or associated with other non-private data associated with the same private data at other data providing nodes and shared with the data using node.

For example, the data providing node 120-1 may send the second association to the data providing nodes 120-2 to 120-n and the data using node 110 in the distributed system 100, so that these nodes store the second association, thereby realizing The second association is stored in system 110 .

There is a one-to-one correspondence between the global identifier (GID) and the hash value (PHash). Since the hash values of the same user or patient at different nodes are the same, their corresponding global identifiers (GID) are also consistent. Global identifiers are visible across different nodes, and data consumers can use global identifiers to generate data requests.

In some embodiments, the distributed system 100 can be a blockchain system, and the second association (GID-PHash) between the global identifier and the hash value can be stored in the blockchain system, that is, attached to in the blockchain. The blockchain system can be a permissionless chain or a permissioned chain.

Thus, through the first association between the local identifier of the local data and the hash value of the private data stored locally and the second association between the global identifier and the hash value of the private data stored in the distributed system Two associations can safely share non-private data on the premise of protecting local private data. In addition, the second association between the global identifier stored in the distributed system and the hash value of the private data also facilitates associating different non-private data at different nodes in the distributed system for data analysis and model training.

In addition, the private data, the non-private data, and the first association between the local identifier (LID) and the hash value (PHash) for the local data are stored locally, and the association between the global identifier and the hash value The second association is stored in the blockchain, realizing a hybrid storage architecture, which not only ensures that the second association cannot be tampered with, but also avoids the problem of low storage efficiency in the blockchain system.

After the second association between the global identifier and the hash value is generated and stored in the distributed system, the second association can also be used to associate different non-private data at different nodes. Description will be made below with reference to FIG. 3 .

Fig. 3 shows a flowchart of a method 300 for data sharing according to an embodiment of the present disclosure. For example, the method 300 may be performed by the data providing node 120-1 as shown in FIG. 1 . It should be appreciated that method 300 may also include additional blocks not shown and/or blocks shown may be omitted, and that the scope of the present disclosure is not limited in this respect. It should also be understood that although the data providing node 120-1 is used as an example for illustration, it may also be implemented by other data providing nodes 120-2 to 120-n, and the scope of the present disclosure is not limited here.

At block 302, the data providing node 120-1 acquires first attribute information of the first non-private data from the current node.

The first non-private data may include first attribute information and first attribute value information. An example of the first attribute information includes the item "cancer drug". Examples of the first attribute value information include cancer drug information, such as the name and serial number of the cancer drug.

At block 304, the data providing node 120-1 obtains one or more second non-private One or more pieces of second attribute information of the data, and one or more pieces of second non-private data associated with the private data.

The second non-private data may include second attribute information and second attribute value information. Examples of the second attribute information include the item "hypertension drug", the item "rheumatism drug", and the like. Examples of the second attribute value information include hypertension drug information, rheumatism drug information, such as hypertension drug name, rheumatism drug name, and the like.

At block 306, the data providing node 120-1 generates and stores joint metadata in the distributed system 100 based on the second association, the joint metadata includes at least a global identifier (GID), first attribute information, and one or more The association between the second attribute information of the item.

For example, the first attribute information includes the item "cancer drug", and the items of second attribute information include the item "hypertension drug" and the item "rheumatology drug", and an example of joint metadata includes the global identifier (GID), the item Association between "Cancer Drugs", the entry "Hypertension Drugs", and the entry "Rheumatology Drugs". In addition, the joint metadata may also include description information for the Global Identifier (GID), the item "Cancer Drug", the item "Hypertension Drug", and the item "Rheumatology Drug".

At block 308, the data providing node 120-1 sends joint metadata to other nodes in the distributed system 100 to store the joint metadata in the distributed system 100 for the first non-private data and one or more Item 2 Connection sharing of non-private data.

For example, the data providing node 120-1 may send the joint metadata to the data providing nodes 120-2 to 120-n and the data using node 110 in the distributed system 100, so that these nodes store the joint metadata, thereby realizing Federation metadata is stored in system 100 . After the joint metadata is stored in the distributed system 100, the data usage node 110 can know which GIDs, which attribute information are in the distributed system 100 based on the joint metadata, and what the relationship between them looks like, so as to generate data according to the requirements condition information to make a data request.

In some embodiments, the distributed system 100 may be a blockchain system, and federation metadata may be stored in the blockchain system, eg, appended to the blockchain.

Therefore, by storing joint metadata associated with different attribute information of different non-private data at different data providing nodes in the distributed system, data using nodes can easily know the existence of the entire system without knowing any private data. Which attribute information, as well as the convenience of associating and sharing different data provide different non-private data at nodes for data analysis and artificial intelligence model training, etc. It can support complex data analysis or artificial intelligence model training tasks that cannot be performed or are very inefficient under the traditional privacy protection computing mode, and the obtained data analysis and model results are often more accurate.

In addition, the private data, the non-private data, and the first association between the local identifier (LID) and the hash value (PHash) for the local data are stored locally, and the association between the global identifier and the hash value The second association and joint metadata are stored in the blockchain, realizing a hybrid storage architecture, which not only ensures that the second association cannot be tampered with, but also avoids the problem of low storage efficiency in the blockchain system.

After the joint metadata is generated and stored in the distributed system, the data using node 110 can use the joint metadata to make a data request, and the data providing node 120 can obtain corresponding non-private data for sharing according to the data request. Description will be made below with reference to FIG. 4 .

FIG. 4 shows a flowchart of a method 400 for data sharing according to an embodiment of the present disclosure. For example, the method 400 may be performed by the data providing node 120-1 as shown in FIG. 1 . It should be appreciated that method 400 may also include additional blocks not shown and/or blocks shown may be omitted, and that the scope of the present disclosure is not limited in this regard. It should also be understood that although the data providing node 120-1 is used as an example for illustration, it may also be implemented by other data providing nodes 120-2 to 120-n, and the scope of the present disclosure is not limited here.

At block 402, the data providing node 120-1 receives a data request from the data using node 110 in the distributed system 100, the data request includes data condition information generated based on federated metadata.

For example, data usage node 110 may generate data condition information based on attribute information in federated metadata. An example of data condition information may be "SELECT GID, cancer medicine, hypertension medicine, age FROM Metadata WHERE age>=20AND age<=40", where "GID", "cancer medicine", "hypertension medicine", and "age" It can be the global identifier and attribute information included in the joint metadata. The data condition information means that a global identifier of age between 20-40 years old, cancer drug information, high blood pressure information, and age information are required.

As another example, the data usage node 110 can generate data condition information based on the global identifier in the federation metadata. For example, data condition information includes one or more global identifiers.

In some embodiments, the distributed system 100 includes a blockchain system, and the data providing node 120 and the data using node 110 are blockchain nodes. Receiving the data request from the data usage node 110 includes receiving a first smart contract from the data usage node 110, the first smart contract including data condition information. Due to the non-tamperable nature of blockchain data, once a smart contract is deployed, it cannot be directly modified on the original contract. This makes it easier to trace data usage footprints in the future and ensure that shared non-private data is not misused.

At block 404, the data providing node 120-1 acquires first non-private data matching the data condition information.

Taking the above data condition information "SELECT GID, cancer medicine, hypertension medicine, age FROM Metadata WHERE age>=20AND age<=40" as an example, if the first non-private data includes the first attribute information "cancer medicine", the corresponding If the first attribute value information and the age attribute value are 30, then the first non-private data matches the data condition information.

In the case that the data condition information includes the global identifier, the data providing node 120-1 may determine the global identifier related to the global identifier based on the second association between the global identifier stored in the distributed system 100 and the hash value of the private data. The associated, private data hash. Subsequently, the data providing node 120-1 may determine the local identifier associated with the hash value of the private data based on the locally stored first association between the local identifier and the hash value of the private data, and acquire the local identification The first non-private data in the local data corresponding to the symbol is used as the first non-private data matching the data condition information.

In some embodiments, the data request also includes the node address of the data using node 110 . The data providing node 120-1 may also determine whether the node address of the data using node 110 matches a preset node address. For example, the data usage node 110 and the data providing node 120-1 may negotiate in advance to use the address of the data usage node 110 as the preset node address.

If the data providing node 120-1 determines that the node address of the data using node 110 matches the preset node address, it acquires the first non-private data matching the data condition information. Thus, only the data request from the preset node address will be processed by the data providing node, thus the directional sharing of data.

At block 406, the data providing node 120-1 may also obtain one or more first At least one item of second attribute information of at least one item of second non-private data in the two non-private data, at least one item of second attribute information matches the data condition information.

The acquired at least one item of second attribute information of at least one item of second non-private data may be obtained from at least one additional data providing node based on the data condition information in response to receiving a data request from the data usage node 110. The local data of the data provider node is acquired and sent.

At block 408, the data providing node 120-1 generates a third association between the global identifier, the first attribute information and at least one item of second attribute information based on the second association (GID-PHash).

At block 410, the data providing node 120-1 sends the third association to other nodes in the distributed system 100, so as to store the third association in the distributed system 100, so that the data usage node 110, based on the third association, will send the third association from The first non-private data obtained by the current node is associated with at least one item of second non-private data obtained from at least one other data providing node.

At block 412 , the data providing node 120 - 1 sends the acquired first non-private data to the data consuming node 110 .

For example, the first non-private data may be sent to the data usage node through an open API or Web service or direct file download. In some embodiments, the data providing node 120 - 1 may send the obtained first non-private data to the data using node 110 after receiving the data request from the data using node 110 . In some other embodiments, the data providing node 120 - 1 may directly send the obtained first non-private data to the data using node 110 without a request from the data using node 110 .

As a result, the data usage node can generate data condition information based on the joint metadata stored in the distributed system for data request, and the data provider node can obtain the matching non-private data and send it to the data usage node, so that the data usage node does not Realize the safe sharing of non-private data under the premise of knowing any private data. In addition, attribute information of multiple non-private data matching data condition information at multiple data providing nodes can be associated to facilitate data usage nodes to obtain multiple non-private data at multiple data providing nodes for data analysis and modeling train.

FIG. 5 shows a flowchart of a method 500 for data sharing according to an embodiment of the present disclosure. For example, the method 500 may be performed by the data providing node 120-1 as shown in FIG. 1 . It should be appreciated that method 500 may also include additional blocks not shown and/or blocks shown may be omitted, and that the scope of the present disclosure is not limited in this respect. It should also be understood that although the data providing node 120-1 is used as an example for illustration, it may also be implemented by other data providing nodes 120-2 to 120-n, and the scope of the present disclosure is not limited here. It should be understood that, in the embodiment related to FIG. 5 , the distributed system 110 is a blockchain system.

At block 502, the data providing node 120-1 receives a first smart contract from the data using node 110, the first smart contract includes data condition information and incentive mechanism information for data sharing, the data condition information is determined based on joint metadata generate.

At block 504, the data providing node 120-1 determines whether there is first non-private data matching the data condition information in the local data.

If at block 504 the data providing node 120-1 determines that there is first non-private data matching the data condition information in the local data, then at block 506 it is determined whether the incentive mechanism information passes the evaluation.

In some embodiments, determining whether the incentive information passes the evaluation may include prompting the incentive information, and determining whether a positive acknowledgment for the prompt was received. If a positive confirmation is received, it is determined that the incentive mechanism information has passed the evaluation, otherwise it is determined that the incentive mechanism information has not passed the evaluation.

In some other embodiments, determining whether the incentive mechanism information passes the evaluation may include determining whether the incentive mechanism information satisfies a preset condition, and if it is determined that the incentive mechanism information meets the preset condition, then determining that the incentive mechanism information passes the evaluation, otherwise determining that the incentive mechanism information Failed the assessment.

If at block 506, the data providing node 120-1 determines that the incentive mechanism information has passed the evaluation, then at block 508, a second smart contract is generated and deployed in the blockchain system. The second smart contract includes data condition information, incentive mechanism information, The data uses the node address and digital wallet address of the node and the node address and digital wallet address of the current node.

At block 510, the data providing node 120-1 determines whether the second smart contract is deployed in the blockchain system.

If at block 510 the data providing node 120-1 determines that the second smart contract is deployed in the blockchain system, then at block 512 the first non-private data matching the data condition information is obtained.

At block 514, the data providing node 120-1 may also obtain one or more first At least one item of second attribute information of at least one item of second non-private data in the two non-private data, at least one item of second attribute information matches the data condition information.

The acquired at least one item of second attribute information of at least one item of second non-private data may be obtained from at least one additional data providing node based on the data condition information in response to receiving a data request from the data usage node 110. The local data of the data provider node is acquired and sent.

At block 516, the data providing node 120-1 may generate a third association between the global identifier, the first attribute information and at least one item of second attribute information based on the second association (GID-PHash).

At block 518, the data providing node 120-1 sends the third association to other nodes in the blockchain system to store the third association in the blockchain system, so that the data usage node 110 will, based on the third association, obtain The first non-private data obtained by the current node is associated with at least one item of second non-private data obtained from at least one other data providing node.

At block 520 , the data providing node 120 - 1 sends the acquired first non-private data to the data consuming node 110 . The sending method of the first non-private data is similar to the above, and will not be repeated here.

As a result, data usage nodes can generate data condition information based on the joint metadata stored in the blockchain system and request data through smart contracts, and data providing nodes can obtain matching non-private data and send it to data usage nodes, thereby The secure sharing of non-private data is realized on the premise that the data using nodes do not know any private data. Once the data request is uploaded to the chain through the smart contract, the record cannot be changed, so that it is convenient to trace the data usage footprint in the future and ensure that the shared non-private data will not be abused. In addition, it is possible to correlate the attribute information of multiple non-private data at multiple data providing nodes that match the data condition information, which facilitates data usage nodes to associate multiple non-private data at multiple data providing nodes for data processing. Analysis and model training. In addition, smart contracts are used to establish a data sharing incentive mechanism, and a more effective data sharing platform can be established through the design of digital rights and interests sharing. At the same time, it also ensures that data providing nodes can get a fair return of interest after contributing non-private data to data analysis or artificial intelligence model training tasks.

In some embodiments, the data providing node 120-1 may also determine whether the sending of the first non-private data is completed.

If the data providing node 120-1 determines that the sending of the first non-private data is completed, the transfer of the first non-private data from the digital wallet address of the data usage node to the digital wallet address of the current node is performed based on the incentive mechanism information through the second smart contract. Corresponding digital rights and interests.

For example, by sending a message to the address of the second smart contract to call the relevant code in the second smart contract based on the incentive mechanism information to perform the transfer from the digital wallet address of the data usage node to the digital wallet address of the current node and the first non-privacy Digital rights corresponding to data.

In this way, after the data providing node completes the data sharing, the transfer of the corresponding data rights and interests can be realized, thereby realizing the incentive for data sharing.

FIG. 6 shows a flowchart of a method 600 for data sharing according to an embodiment of the present disclosure. For example, method 600 may be performed by data usage node 110 as shown in FIG. 1 . It should be appreciated that method 600 may also include additional blocks not shown and/or blocks shown may be omitted, and that the scope of the present disclosure is not limited in this respect.

At block 602, the data usage node 110 generates data condition information based on the joint metadata stored in the distributed system 100, the joint metadata includes at least the association between the global identifier and multiple attribute information of multiple non-private data, The global identifier is associated with the hash value of the private data, the private data is associated with multiple non-private data, and the multiple non-private data are located in multiple data providing nodes in the distributed system. The joint metadata is stored in the distributed system by multiple data providing nodes 120 in the distributed system 100 according to the method 300 described above.

At block 604, the data consuming node 110 sends a data request to a plurality of data providing nodes 120, the data request including data condition information.

In some embodiments, the data request may also include the node address of the data usage node 110 .

In some embodiments, the distributed system 100 is a blockchain system. Additionally, data requests can be sent in the form of smart contracts.

At block 606, the data usage node 110 receives at least one item of non-private data matching the data condition information from at least one data providing node among the plurality of data providing nodes 120 .

As a result, the data usage node can generate data condition information based on the joint metadata stored in the distributed system for data request, and the data provider node can obtain the matching non-private data and send it to the data usage node, so that the data usage node does not Realize the safe sharing of non-private data under the premise of knowing any private data.

FIG. 7 shows a flowchart of a method 700 for data sharing according to an embodiment of the present disclosure. For example, method 700 may be performed by data usage node 110 as shown in FIG. 1 . It should be appreciated that method 700 may also include additional blocks not shown and/or blocks shown may be omitted, and that the scope of the present disclosure is not limited in this regard.

At block 702, the data usage node 110 generates data condition information based on the joint metadata stored in the blockchain system, the joint metadata includes at least the association between the global identifier and multiple attribute information of multiple non-private data, The global identifier is associated with the hash value of the private data, the private data is associated with multiple non-private data, and the multiple non-private data are located in multiple data providing nodes in the distributed system. The joint metadata is stored in the blockchain system by one or more data providing nodes 120 in the blockchain system according to the method 300 described above.

At block 704, the data using node 110 sends a first smart contract to multiple data providing nodes 120 in the blockchain system, the first smart contract includes data condition information and incentive mechanism information for data sharing.

The data use node can call the system smart contract template to modify or directly write and generate the first smart contract according to its own needs, and deploy the first smart contract to the blockchain, thereby issuing data requests to each node in the blockchain system. Due to the non-tamperable nature of blockchain data, once a smart contract is deployed, it cannot be directly modified on the original contract. If the terms of the smart contract need to be modified, the system will call the contract destruction sub-module to destroy the original smart contract on the premise that the participating blockchain nodes reach a consensus, and generate a new smart contract for deployment according to new requirements. All contract generation and destruction records will be recorded on the immutable blockchain block data, which is convenient for tracking data request sharing and better protecting data security.

At block 706, the data using node 110 acquires at least one node address of at least one data providing node 120 based on at least one second smart contract stored in the blockchain system, and at least one second smart contract is provided by at least one data providing node Stored in the blockchain system in response to the first smart contract, each second smart contract in at least one second smart contract includes data condition information, incentive mechanism information, node address and digital wallet address of the data usage node, and corresponding The data provides the node address and digital wallet address of the node. At least one second smart contract is stored in the blockchain system by at least one data providing node 120 through the method 500 described above.

At block 708, the data usage node 110 acquires at least one item of non-private data matching the data condition information from at least one data providing node 120 based on at least one node address.

As a result, data usage nodes can generate data condition information based on the joint metadata stored in the blockchain system and request data through smart contracts, and data providing nodes can obtain matching non-private data and send it to data usage nodes, thereby The secure sharing of non-private data is realized on the premise that the data using nodes do not know any private data. Once the data request is uploaded to the chain through the smart contract, the record cannot be changed, so that it is convenient to trace the data usage footprint in the future and ensure that the shared non-private data will not be abused. In addition, smart contracts are used to establish a data sharing incentive mechanism, and a more effective data sharing platform can be established through the design of digital rights and interests sharing. At the same time, it also ensures that data providing nodes can get a fair return of interest after contributing non-private data to data analysis or artificial intelligence model training tasks.

In some embodiments, acquiring from at least one data providing node 120 at least one item of non-private data matching the data condition information includes acquiring at least two items of non-private data matching the data condition information from at least two data providing nodes 120 . The data usage node 110 may also associate at least two items of non-private data based on the association between the global identifier and at least two items of attribute information stored in the distributed system. The association between the global identifier and at least two items of attribute information is stored in the blockchain system by at least two data providing nodes in response to the first smart contract.

In this way, based on the association between at least two items of non-private data at least two items of non-private data that match the data condition information at multiple data providing nodes, after at least two items of non-private data at least two data providing nodes are associated It is used for data analysis and model training, which is conducive to improving the accuracy of data analysis and model training.

FIG. 8 shows a schematic block diagram of an example device 800 that may be used to implement embodiments of the present disclosure. For example, the data usage node 110 and the data providing node 120 shown in FIG. 1 may be implemented by the device 800 . As shown, the device 800 includes a central processing unit (CPU) 801 that can execute commands according to computer program instructions stored in a read only memory (ROM) 802 or loaded from a storage unit 808 into a random access memory (RAM) 803 computer program instructions to perform various appropriate actions and processes. In the random access memory 803, various programs and data necessary for the operation of the device 800 can also be stored. The central processing unit 801 , the read-only memory 802 and the random-access memory 803 are connected to each other through a bus 804 . An input/output (I/O) interface 805 is also connected to the bus 804 .

Multiple components in the device 800 are connected to the input/output interface 805, including: an input unit 806, such as a keyboard, mouse, microphone, etc.; an output unit 807, such as various types of displays, speakers, etc.; a storage unit 808, such as a disk, CD, etc.; and a communication unit 809, such as a network card, a modem, a wireless communication transceiver, and the like. The communication unit 809 allows the device 800 to exchange information/data with other devices over a computer network such as the Internet and/or various telecommunication networks.

The various procedures and processes described above, such as the methods 200-700, can be executed by the central processing unit 801. For example, in some embodiments, methods 200 - 700 may be implemented as a computer software program tangibly embodied on a machine-readable medium, such as storage unit 808 . In some embodiments, part or all of the computer program may be loaded and/or installed onto the device 800 via the read-only memory 802 and/or the communication unit 809 . When the computer program is loaded into random access memory 803 and executed by central processing unit 801, one or more actions of methods 200-700 described above may be performed.

The present disclosure relates to methods, apparatuses, systems, electronic devices, computer readable storage media and/or computer program products. A computer program product may include computer readable program instructions for carrying out various aspects of the present disclosure.

A computer readable storage medium may be a tangible device that can retain and store instructions for use by an instruction execution device. A computer readable storage medium may be, for example, but is not limited to, an electrical storage device, a magnetic storage device, an optical storage device, an electromagnetic storage device, a semiconductor storage device, or any suitable combination of the foregoing. More specific examples (a non-exhaustive list) of computer-readable storage media include: portable computer diskettes, hard disks, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM), or flash memory), static random access memory (SRAM), compact disc read only memory (CD-ROM), digital versatile disc (DVD), memory stick, floppy disk, mechanically encoded device, such as a printer with instructions stored thereon A hole card or a raised structure in a groove, and any suitable combination of the above. As used herein, computer-readable storage media are not to be construed as transient signals per se, such as radio waves or other freely propagating electromagnetic waves, electromagnetic waves propagating through waveguides or other transmission media (e.g., pulses of light through fiber optic cables), or transmitted electrical signals.

Computer-readable program instructions described herein may be downloaded from a computer-readable storage medium to a respective computing/processing device, or downloaded to an external computer or external storage device over a network, such as the Internet, a local area network, a wide area network, and/or a wireless network. The network may include copper transmission cables, fiber optic transmission, wireless transmission, routers, firewalls, switches, gateway computers, and/or edge servers. A network adapter card or a network interface in each computing/processing device receives computer-readable program instructions from the network and forwards the computer-readable program instructions for storage in a computer-readable storage medium in each computing/processing device .

Computer program instructions for performing the operations of the present disclosure may be assembly instructions, instruction set architecture (ISA) instructions, machine instructions, machine-dependent instructions, microcode, firmware instructions, state setting data, or Source or object code written in any combination, including object-oriented programming languages—such as Smalltalk, C++, etc., and conventional procedural programming languages—such as the “C” language or similar programming languages. Computer readable program instructions may execute entirely on the user's computer, partly on the user's computer, as a stand-alone software package, partly on the user's computer and partly on a remote computer, or entirely on the remote computer or server implement. In cases involving a remote computer, the remote computer can be connected to the user computer through any kind of network, including a local area network (LAN) or a wide area network (WAN), or it can be connected to an external computer (such as via the Internet using an Internet service provider). connect). In some embodiments, an electronic circuit, such as a programmable logic circuit, field programmable gate array (FPGA), or programmable logic array (PLA), can be customized by utilizing state information of computer-readable program instructions, which can Various aspects of the present disclosure are implemented by executing computer readable program instructions.

Aspects of the present disclosure are described herein with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems) and computer program products according to embodiments of the disclosure. It should be understood that each block of the flowcharts and/or block diagrams, and combinations of blocks in the flowcharts and/or block diagrams, can be implemented by computer-readable program instructions.

These computer readable program instructions may be provided to a processing unit of a general purpose computer, special purpose computer, or other programmable data processing apparatus to produce a machine such that when executed by the processing unit of the computer or other programmable data processing apparatus , producing an apparatus for realizing the functions/actions specified in one or more blocks in the flowchart and/or block diagram. These computer-readable program instructions can also be stored in a computer-readable storage medium, and these instructions cause computers, programmable data processing devices and/or other devices to work in a specific way, so that the computer-readable medium storing instructions includes An article of manufacture comprising instructions for implementing various aspects of the functions/acts specified in one or more blocks in flowcharts and/or block diagrams.

It is also possible to load computer-readable program instructions into a computer, other programmable data processing device, or other equipment, so that a series of operational steps are performed on the computer, other programmable data processing device, or other equipment to produce a computer-implemented process , so that instructions executed on computers, other programmable data processing devices, or other devices implement the functions/actions specified in one or more blocks in the flowcharts and/or block diagrams.

The flowchart and block diagrams in the figures illustrate the architecture, functionality, and operation of possible implementations of systems, methods and computer program products according to various embodiments of the present disclosure. In this regard, each block in a flowchart or block diagram may represent a module, a portion of a program segment, or an instruction that includes one or more Executable instructions. In some alternative implementations, the functions noted in the block may occur out of the order noted in the figures. For example, two blocks in succession may, in fact, be executed substantially concurrently, or they may sometimes be executed in the reverse order, depending upon the functionality involved. It should also be noted that each block of the block diagrams and/or flowchart illustrations, and combinations of blocks in the block diagrams and/or flowchart illustrations, can be implemented by a dedicated hardware-based system that performs the specified function or action , or may be implemented by a combination of dedicated hardware and computer instructions.

Having described various embodiments of the present disclosure above, the foregoing description is exemplary, not exhaustive, and is not limited to the disclosed embodiments. Many modifications and alterations will be apparent to those of ordinary skill in the art without departing from the scope and spirit of the described embodiments. The terminology used herein is chosen to best explain the principles of the various embodiments, practical applications or technical improvements over technologies in the market, or to enable other persons of ordinary skill in the art to understand the various embodiments disclosed herein.

Claims (17)

1. A method for data sharing, comprising:

obtaining private data from local data comprising the private data and first non-private data, the first non-private data being associated with the private data;

generating a hash value of the private data;

generating a first association between a local identifier for the local data and the hash value;

generating a global identifier for indexing the hash value in a distributed system, the distributed system being associated with a current node;

generating a second association between the global identifier and the hash value; and

The second association is sent to other nodes in the distributed system to store the second association in the distributed system for connection sharing of the first non-private data.

2. The method of claim 1, further comprising:

acquiring first attribute information of the first non-private data from a current node;

obtaining one or more items of second attribute information of one or more items of second non-private data from one or more further data providing nodes in the distributed system, the one or more items of second non-private data being associated with the private data;

generating, based on the second association, federated metadata including at least an association between the global identifier, the first attribute information, and the one or more items of second attribute information; and

the federated metadata is sent to the other nodes in the distributed system to store the federated metadata in the distributed system for connection sharing of the first non-private data and the one or more second non-private data.

3. The method of claim 2, further comprising:

receiving a data request from a data usage node in the distributed system, the data request including data condition information, the data condition information being generated based on the federated metadata;

Acquiring first non-private data matched with the data condition information; and

and sending the acquired first non-private data to the data using node.

4. A method according to claim 3, further comprising:

obtaining, from at least one of the one or more further data providing nodes, at least one item of second attribute information of at least one item of second non-private data of the one or more items of second non-private data, the at least one item of second non-private data matching the data condition information;

generating a third association between the global identifier, the first attribute information, and the at least one item of second attribute information based on the second association; and

the third association is sent to other nodes in the distributed system to store the third association in the distributed system, so that the data usage node associates the first non-private data acquired from the current node with the at least one second non-private data acquired from the at least one further data providing node based on the third association.

5. The method of claim 3 or 4, wherein the data request further includes a node address of the data usage node, and acquiring first non-private data that matches the data condition information includes:

Determining whether the node address is matched with a preset node address; and

and if the node address is determined to be matched with the preset node address, acquiring first non-private data matched with the data condition information.

6. The method of claim 3 or 4, wherein the distributed system comprises a blockchain system, and receiving a data request from a data-using node comprises receiving a first smart contract from the data-using node, the first smart contract comprising the data condition information.

7. The method of claim 6, wherein the first smart contract further includes incentive mechanism information for data sharing, and acquiring first non-private data that matches the data condition information comprises:

determining whether first non-private data matched with the data condition information exists in the local data;

if it is determined that first non-private data matched with the data condition information exists in the local data, determining whether the incentive mechanism information passes evaluation;

generating and deploying a second smart contract in the blockchain system if it is determined that the incentive mechanism information passes the evaluation, the second smart contract including the data condition information, the incentive mechanism information, a node address and a digital wallet address of the data usage node, and a node address and a digital wallet address of a current node; and

If it is determined that the second smart contract is deployed in the blockchain system, first non-private data that matches the data condition information is obtained.

8. The method of claim 7, further comprising:

if it is determined that the transmission of the first non-private data is completed, performing, by the second smart contract, transfer of digital rights corresponding to the first non-private data from the digital wallet address of the data usage node to the digital wallet address of the current node based on the incentive mechanism information.

9. A method for data sharing, comprising:

generating data condition information based on joint metadata stored in a distributed system, the joint metadata comprising at least an association between a global identifier and a plurality of items of attribute information of a plurality of items of non-private data, the global identifier being associated with a hash value of private data, the private data being associated with the plurality of items of non-private data, the plurality of items of non-private data being located at a plurality of data providing nodes in the distributed system;

transmitting a data request to the plurality of data providing nodes, the data request including the data condition information; and

At least one item of non-private data matching the data condition information is received from at least one data providing node of the plurality of data providing nodes.

10. The method of claim 9, wherein the distributed system comprises a blockchain system.

11. The method of claim 9, wherein sending the data request to the plurality of data providing nodes comprises sending a first smart contract to the plurality of data providing nodes, the first smart contract comprising the data condition information.

12. The method of claim 11, wherein the smart contract further includes incentive mechanism information for data sharing, and the obtaining at least one item of non-private data matching the data condition information from at least one of the plurality of data providing nodes comprises:

obtaining at least one node address of the at least one data providing node based on at least one second smart contract stored in the blockchain system, the at least one second smart contract stored by the at least one data providing node in response to the first smart contract, each of the at least one second smart contract including the data condition information, the incentive mechanism information, a node address and a digital wallet address of the data using node, and a node address and a digital wallet address of a corresponding data providing node; and

At least one item of non-private data matching the data condition information is acquired from the at least one data providing node based on the at least one node address.

13. The method of any of claims 9-12, wherein receiving at least one item of non-private data from at least one of the plurality of data providing nodes that matches the data condition information comprises receiving at least two items of non-private data from at least two of the plurality of data providing nodes that match the data condition information, and the method further comprises:

the plurality of non-private data is associated based on an association between the global identifier and at least two items of attribute information stored in the distributed system, the association between the global identifier and at least two items of attribute information being stored by at least two data providing nodes in the blockchain system in response to the first smart contract.

14. A data providing node, comprising:

at least one processor; and

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

the memory stores instructions executable by the at least one processor to enable the at least one processor to perform the method of any one of claims 1-8.

15. A data usage node, comprising:

at least one processor; and

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

the memory stores instructions executable by the at least one processor to enable the at least one processor to perform the method of any one of claims 9-13.

16. A distributed system, comprising:

a plurality of data providing nodes according to claim 14; and

the data usage node of claim 15.

17. A computer readable storage medium having stored thereon a computer program which, when executed by a processor, implements the method of any of claims 1-13.

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