CN117828410A - Block chain-based data partitioning system - Google Patents
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- 238000000034 method Methods 0.000 claims description 24
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Abstract
The invention discloses a data partitioning system based on a block chain, which comprises a data owner, a data storage device and a data storage device, wherein the data owner encrypts local data and sets an access control strategy for the data; the data owner encrypts the plaintext data in a homomorphic encryption mode, generates ciphertext data and uploads the ciphertext data to the data storage server; the data owner establishes a corresponding data access strategy for the data uploaded by the data owner and limits the user nodes accessing the data; after a data request party sends a sharing request for certain data, verifying that the access control strategy of the data is met; after the data request party obtains the access data, the same encryption scheme is adopted to encrypt the local original data, and a data set is jointly generated to train a classification algorithm model; the method outputs the model classification precision under the combined training model, writes the transaction into the block chain according to the intelligent contract content to achieve block consensus.
Description
Technical Field
The invention relates to the technical field of blockchains, in particular to a data partitioning system based on a blockchain.
Background
The classification is to analyze and learn an input known training sample set to finally obtain a decision model, then predict and classify an unknown sample, the classification problem widely exists in large data application scenes such as voice and image recognition, computer vision analysis and processing, in the process of designing various classification algorithms, the training generation of the classification learning model is a critical loop, the classification precision of the obtained learning model is generally higher on the premise that the data quantity of the training set is large enough and the corresponding data quality is higher, the expansion of the data scale depends on a data sharing scheme, the potential value of the data is mined, the long-term monopoly of the data is broken, but the existing data sharing method has some defects, such as lag of information construction caused by internal sharing and leakage of private data caused by a data sharing scheduling mode of a third party. Therefore, it is necessary to design a blockchain-based data partitioning system that improves classification accuracy and facilitates data sharing.
Disclosure of Invention
The present invention is directed to a data partitioning system based on blockchain to solve the above-mentioned problems.
In order to solve the technical problems, the invention provides the following technical scheme: a blockchain-based data partitioning system, comprising:
the data owner encrypts local data and sets an access control strategy for the data;
after a data request party sends a sharing request for certain data, verifying that the access control strategy of the data is met;
after the data request party obtains the access data, the same encryption scheme is adopted to encrypt the local original data, and a data set is jointly generated to train a classification algorithm model;
and outputting model classification precision under the combined training model, executing transaction according to intelligent contract content, and writing into a blockchain to achieve block consensus.
According to the above technical solution, the step of the data owner encrypting the local data and setting an access control policy for the data includes:
the data owner encrypts the plaintext data in a homomorphic encryption mode, generates ciphertext data and uploads the ciphertext data to the data storage server;
the data owner establishes a corresponding data access strategy for the data uploaded by the data owner, and limits the user nodes accessing the data.
According to the above technical solution, after the data requester sends a sharing request for a certain data, verifying that the access control policy meets the data specifically includes:
the data request sends a data sharing request to the accounting node, and meanwhile, the accounting node needs to submit own identity attribute, and verifies whether the identity accords with the access control condition corresponding to the requested data.
According to the above technical solution, after the data requester obtains the access data, the same encryption scheme is adopted to encrypt the local original data, and the data set is jointly generated, and the step of training the classification algorithm model includes:
in the data sharing process, the nodes participate in the establishment of intelligent contracts and call the intelligent contracts on the chain;
the data requesting party encrypts the local data by using an encryption scheme adopted by the encryption data set acquired in the node verification stage;
and generating the combined local encryption data and the shared encryption data, and training a classification algorithm model after generating a data set.
According to the above technical scheme, the step of outputting model classification accuracy under the joint training model, writing into the blockchain after executing the transaction according to the intelligent contract content to achieve the block consensus comprises the following steps:
the data request party generates an encryption test data set after encryption operation on the local test set, and inputs the encryption test data set into the model to calculate classification accuracy;
transmitting money from the data requesting party wallet address to the data owner according to the intelligent contract for realizing deployment, and generating a transaction;
after accounting node achieves consensus, the transaction amount is accessed after being packed into a block.
According to the technical scheme, the method is applied to a data partitioning system based on a block chain, and the system comprises the following steps:
a data owner as a provider of data sharing;
a data requesting party, which is used as a requesting party for data sharing;
and the classification model generation module is used for generating a classification model.
According to the above technical solution, the data owner includes:
the data encryption module is used for encrypting the data;
the access setting module is used for formulating a corresponding data access strategy for the data;
and the consensus mechanism unit is used for verifying the transaction through the consensus node.
According to the above technical solution, the data requester includes:
the sharing request unit is used for sending out a data sharing request;
the access verification module is used for carrying out identity verification on the access request;
and the access data encryption module is used for encrypting the acquired access data.
According to the above technical solution, the classification model generating module includes:
the data set generation module is used for generating a data set by combining the local encrypted data and the shared encrypted data;
the classification algorithm model training module is used for training a decision classification algorithm model;
and the model classification precision output module is used for outputting data classification precision.
Compared with the prior art, the invention has the following beneficial effects: according to the invention, by arranging the data owner, the data requester and the classification model generation module, the data owner encrypts the plaintext data and formulates a corresponding data access strategy for the uploaded data, so that the leakage of private data and the theft of the data by a cloud data storage server are avoided; generating joint encrypted data by combining the local encrypted data and the shared encrypted data, generating a data set, and performing model training on the encrypted data set while protecting the data privacy to ensure the complete control of a data owner on the data; the local test set is subjected to encryption operation to generate an encryption test data set, the encryption test data set is input into a model to calculate classification accuracy, transaction is generated, the transaction chain is accessed after the transaction is agreed through a node, so that encryption data sharing is carried out between related data owners which are mutually not trusted on the basis of intelligent contracts to ensure that the data set scale is large enough, and the classification accuracy of a classification learning algorithm is improved.
Drawings
The accompanying drawings are included to provide a further understanding of the invention and are incorporated in and constitute a part of this specification, illustrate the invention and together with the embodiments of the invention, serve to explain the invention. In the drawings:
FIG. 1 is a flow chart of a method for partitioning data based on a blockchain according to an embodiment of the present invention;
fig. 2 is a schematic block diagram of a block chain based data partitioning system according to a second embodiment of the present invention.
Detailed Description
The following description of the embodiments of the present invention will be made clearly and completely with reference to the accompanying drawings, in which it is apparent that the embodiments described are only some embodiments of the present invention, but not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
Embodiment one:
fig. 1 is a flowchart of a blockchain-based data partitioning method according to an embodiment of the present invention, where the method may be implemented by a blockchain-based data partitioning system according to an embodiment of the present invention, and the system is composed of a plurality of software and hardware modules, and the method specifically includes the following steps:
s101, a data owner encrypts local data and sets an access control strategy for the data;
in some embodiments of the present invention, a data owner encrypts plaintext data in a homomorphic encryption manner, generates ciphertext data, uploads the ciphertext data to a data storage server, obtains a download address of a file, utilizes the public and non-tamperable properties of an account book in a blockchain, and ensures data security by building a coalition chain in which members can join through identity authentication, and uploads the encrypted data to the data storage server in the coalition chain, thereby avoiding leakage of private data and theft of data by the cloud data storage server, and each node participating in the blockchain network can verify the integrity and availability of the data; since the blockchain has a consensus mechanism, ledger data can be securely updated, and the data owner can add newly generated data to the chain.
In some embodiments of the present invention, a data owner calculates a hash value of ciphertext data to verify the integrity of data at a data storage end, and establishes a corresponding data access policy for the data uploaded by the data owner, limits user nodes accessing the data, and stores the policy in a ledger in a plaintext form, wherein a node meeting the access policy can acquire ciphertext data files; the encrypted data and the access strategy are packaged into a transaction, and the transaction is submitted and waited for a consensus node in the blockchain to confirm and be packaged on a block and added to the blockchain.
In the embodiment of the invention, the consensus node is selected by the number of the data resources, the node with higher calculation power in the consensus process performs further data classification mining for acquiring more data so as to ensure the safe operation of the system, the accounting node packages the transaction in a period of time to generate a block, obtains the random number after calculation, obtains the accounting right, broadcasts the accounting right to the whole network, adds the block to the blockchain, and all the nodes of the whole network update own blockchain account book.
S102, after a data request party sends a sharing request for certain data, verifying that the data accords with an access control strategy;
in some embodiments of the present invention, the data request sends a request for data sharing to the accounting node, and meanwhile, the accounting node needs to submit its identity attribute, verifies whether its identity meets the access control condition corresponding to the requested data, and then obtains the requested encrypted data and the encryption scheme through the blockchain ledger download after the verification is successful, otherwise, resubmisses the data to send a sharing request; and the check information of the uploaded data is recorded in the blockchain account book, so that the data is prevented from being tampered and the data integrity is prevented from being lost.
S103, after the data requesting party acquires the access data, encrypting the local original data by adopting the same encryption scheme, and jointly generating a data set to train a classification algorithm model;
in some embodiments of the present invention, during the data sharing process, the nodes participate in the establishment of the intelligent contract and invoke the on-chain intelligent contract, and after accounting nodes in the alliance chain reach consensus, the data owners may be required to obtain part of the encrypted data as rewards to encourage data sharing.
In some embodiments of the present invention, the data requester encrypts the local data using an encryption scheme adopted by the encrypted data set acquired in the node verification stage, generates joint encrypted data by combining the local encrypted data and the shared encrypted data, and performs training of the classification algorithm model after generating the data set.
Specifically, in the embodiment of the invention, the classification model is trained through a decision tree classification algorithm, from the construction of a decision tree root node, the information gain of all possible attribute features is calculated for the node, the attribute with the largest information gain is selected as the attribute feature of the node, and the sub-nodes of the node are divided according to different values of the attribute; then recursively calling the method for each sub-node to construct a decision tree; and (3) until the information gain of all the attributes is very small or no attribute can be selected, finally obtaining a complete decision tree, and inputting a data set generated by combining the local encrypted data and the shared encrypted data into a decision tree classification algorithm for model training, thereby generating a decision tree model.
In the embodiment of the invention, the data encryption method and the secret key generated by the homomorphic encryption scheme are both stored by the data owner, and the data requester is required to combine with the local data through data sharing so as to train a better classification model, so that the encryption method must be acquired from the data owner, the data privacy is protected, and model training is performed on the encrypted data set, so that the data owner is ensured to fully control the data.
S104, outputting model classification precision under the combined training model, executing transaction according to intelligent contract content, and then writing into a blockchain to achieve block consensus;
in some embodiments of the present invention, a data requester generates an encrypted test data set after encryption operation, inputs the encrypted test data set into a model to calculate classification accuracy, outputs model classification accuracy under a joint training model, triggers an intelligent contract, sends money from a wallet address of the data requester to a data owner according to the deployed intelligent contract, generates a transaction, packages the transaction in a network for a period of time into a block after accounting nodes agree, can be accessed into a transaction chain after full network verification, and the accounting nodes agree can acquire electronic money as rewards to promote stability of the network.
Embodiment two:
in a second embodiment of the present invention, a data partitioning system based on a blockchain is provided, and fig. 2 is a schematic diagram of a module configuration of the data partitioning system based on a blockchain provided in the second embodiment, as shown in fig. 2, the system includes:
a data owner as a provider of data sharing;
a data requesting party, which is used as a requesting party for data sharing;
and the classification model generation module is used for generating a classification model.
In some embodiments of the invention, the data owner comprises:
the data encryption module is used for encrypting the data;
the access setting module is used for formulating a corresponding data access strategy for the data;
and the consensus mechanism unit is used for verifying the transaction through the consensus node.
In some embodiments of the invention, the data requestor includes:
the sharing request unit is used for sending out a data sharing request;
the access verification module is used for carrying out identity verification on the access request;
and the access data encryption module is used for encrypting the acquired access data.
In some embodiments of the invention, the classification model generation module comprises:
the data set generation module is used for generating a data set by combining the local encrypted data and the shared encrypted data;
the classification algorithm model training module is used for training a decision classification algorithm model;
and the model classification precision output module is used for outputting data classification precision.
In an exemplary embodiment of the present invention, the system may be applied to realize sharing of private data among related industries, for example, each medical industry, each financial industry, each service industry, etc., to break the situation of monopoly of inter-industry data, so that each enterprise improves its classification precision in the data mining classification prediction process, so as to obtain more effective data value.
It is noted that relational terms such as first and second, and the like are used solely to distinguish one entity or action from another entity or action without necessarily requiring or implying any actual such relationship or order between such entities or actions. Moreover, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus.
Finally, it should be noted that: the foregoing description is only a preferred embodiment of the present invention, and the present invention is not limited thereto, but it is to be understood that modifications and equivalents of some of the technical features described in the foregoing embodiments may be made by those skilled in the art, although the present invention has been described in detail with reference to the foregoing embodiments. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present invention should be included in the protection scope of the present invention.
Claims (9)
1. The data partitioning method based on the block chain is characterized by comprising the following steps of: comprising the following steps:
the data owner encrypts local data and sets an access control strategy for the data;
after a data request party sends a sharing request for certain data, verifying that the access control strategy of the data is met;
after the data request party obtains the access data, the same encryption scheme is adopted to encrypt the local original data, and a data set is jointly generated to train a classification algorithm model;
and outputting model classification precision under the combined training model, executing transaction according to intelligent contract content, and writing into a blockchain to achieve block consensus.
2. The blockchain-based data partitioning method of claim 1, wherein: the step of the data owner encrypting the local data and setting an access control policy for the data comprises the following steps:
the data owner encrypts the plaintext data in a homomorphic encryption mode, generates ciphertext data and uploads the ciphertext data to the data storage server;
the data owner establishes a corresponding data access strategy for the data uploaded by the data owner, and limits the user nodes accessing the data.
3. The blockchain-based data partitioning method of claim 1, wherein: after the data requesting party sends out a sharing request for certain data, verifying that the access control strategy accords with the data specifically comprises:
the data request sends a data sharing request to the accounting node, and meanwhile, the accounting node needs to submit own identity attribute, and verifies whether the identity accords with the access control condition corresponding to the requested data.
4. The blockchain-based data partitioning method of claim 1, wherein: after the data requesting party obtains the access data, the same encryption scheme is adopted to encrypt the local original data, and the data sets are jointly generated, so that the training of the classification algorithm model comprises the following steps:
in the data sharing process, the nodes participate in the establishment of intelligent contracts and call the intelligent contracts on the chain;
the data requesting party encrypts the local data by using an encryption scheme adopted by the encryption data set acquired in the node verification stage;
and generating the combined local encryption data and the shared encryption data, and training a classification algorithm model after generating a data set.
5. The blockchain-based data partitioning method of claim 1, wherein: the step of outputting model classification precision under the combined training model, writing into a blockchain after executing transaction according to intelligent contract content, and achieving block consensus comprises the following steps:
the data request party generates an encryption test data set after encryption operation on the local test set, and inputs the encryption test data set into the model to calculate classification accuracy;
transmitting money from the data requesting party wallet address to the data owner according to the intelligent contract for realizing deployment, and generating a transaction;
after accounting node achieves consensus, the transaction amount is accessed after being packed into a block.
6. The data partitioning system based on the block chain is characterized in that: the system comprises:
a data owner as a provider of data sharing;
a data requesting party, which is used as a requesting party for data sharing;
and the classification model generation module is used for generating a classification model.
7. The blockchain-based data partitioning system of claim 6, wherein: the data owner includes:
the data encryption module is used for encrypting the data;
the access setting module is used for formulating a corresponding data access strategy for the data;
and the consensus mechanism unit is used for verifying the transaction through the consensus node.
8. The blockchain-based data partitioning system of claim 6, wherein: the data requester includes:
the sharing request unit is used for sending out a data sharing request;
the access verification module is used for carrying out identity verification on the access request;
and the access data encryption module is used for encrypting the acquired access data.
9. The blockchain-based data partitioning system of claim 6, wherein: the classification model generation module comprises:
the data set generation module is used for generating a data set by combining the local encrypted data and the shared encrypted data;
the classification algorithm model training module is used for training a decision classification algorithm model;
and the model classification precision output module is used for outputting data classification precision.
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