CN115170231A - Data transaction method and data transaction platform based on block chain - Google Patents

Abstract

The invention provides a data transaction method based on a block chain, which is implemented on a data transaction platform, wherein the data transaction platform is constructed based on a block chain framework. The data transaction method comprises the following steps: the data seller node submits a seller order and sends the encrypted transaction data set to a storage space of the platform side node; the data buyer node submits a buyer order; the intelligent contract matches the seller orders submitted by the data seller nodes and the buyer orders submitted by the data buyer nodes; and the intelligent contract manages the data transaction between the successfully matched data seller node and the successfully matched data buyer node, and links the transaction information. According to the data transaction method provided by the invention, the data transaction process is controlled through an intelligent contract, the data service party serving as a manager is used as a node in a block chain as a data buyer and a data seller, and the transaction information is recorded and linked up, so that the fairness, the non-tampering property and the traceability of the whole transaction process are ensured.

Description

Data transaction method and data transaction platform based on block chain

Technical Field

The invention relates to the technical field of network communication and data processing, in particular to a data transaction method and a data transaction platform based on a block chain.

Background

With the advent of the big data era, how to effectively utilize data becomes a key issue. The data transaction can enable a data owner to obtain reward, so that data sharing behaviors are stimulated, and full utilization of data is promoted. A traditional data transaction mode adopts a centralized storage and management mode, the fairness of transactions depends on a third party to a large extent, a transaction data set is easy to tamper and steal, and the transaction process is difficult to trace.

Blockchains are a novel decentralized technique that includes distributed data storage, point-to-point transmission, consensus mechanisms, encryption algorithms, and other computer technologies. The method has the greatest characteristic that a plurality of nodes exist, and each node can maintain a set of same database, so that data stored in a block chain cannot be forged and falsified, and the transaction of the block chain is guaranteed to be authentic and credible. Due to the characteristics of high reliability, difficult data loss and the like, the block chain can realize a fair and transparent platform convenient for tracing.

Disclosure of Invention

In order to solve at least one of the above technical problems of the existing data transaction method, a first aspect of the present invention provides a data transaction method based on a block chain, which has the following specific technical solutions:

a data transaction method based on a block chain is implemented on a data transaction platform, and the data transaction platform is constructed based on a block chain framework;

the nodes in the data transaction platform at least comprise a platform side node, a plurality of data seller nodes and a plurality of data buyer nodes, wherein intelligent contracts are deployed on the platform side node, each data seller node and each data buyer node, and each data seller node and each data buyer node have public keys distributed by the intelligent contracts;

the data transaction method comprises the following steps:

each data seller node submits a seller order, encrypts a transaction data set by using a symmetric key, and sends the encrypted transaction data set to the platform side node data service center, wherein the symmetric key is automatically generated by the data seller node through a symmetric encryption algorithm;

each data buyer node submits a buyer order;

the platform side node completes identity verification of each data seller node and each data buyer node;

the platform side node calls an intelligent contract to match the seller orders submitted by each data seller node and the buyer orders submitted by each data buyer node, and the data seller nodes and the data buyer nodes which are successfully matched are determined;

and the platform side node calls the intelligent contract to manage the data transaction between the successfully matched data seller node and the successfully matched data buyer node, and records the transaction information to the block chain.

A second aspect of the present invention provides a data transaction platform, where the data transaction platform is constructed based on a block chain framework, and nodes in the data transaction platform at least include a platform side node, a plurality of data seller nodes, and a plurality of data buyer nodes, where the platform side node, each data seller node, and each data buyer node are deployed with an intelligent contract, and each data seller node and each data buyer node have a public key distributed by the contract;

the platform side node, each data seller node and each data buyer node implement data transaction according to the following process:

each data seller node submits seller orders, encrypts a transaction data set by using a symmetric key, and sends the encrypted transaction data set to the platform side node data service center, wherein the symmetric key is automatically generated by the data seller node through a symmetric encryption algorithm;

each data buyer node submits a buyer order;

the platform side node completes identity verification of each data seller node and each data buyer node;

the platform side node calls an intelligent contract to match the seller orders submitted by each data seller node and the buyer orders submitted by each data buyer node, and the data seller nodes and the data buyer nodes which are successfully matched are determined;

and the platform side node calls the intelligent contract to manage the data transaction between the successfully matched data seller node and data buyer node, and records the transaction information to the block chain.

The data transaction method provided by the invention is implemented on a data transaction platform with a blockchain architecture. The data transaction process is controlled through an intelligent contract, a platform party serving as a platform manager is the same as a data buyer and a data seller, and both the platform party and the data buyer and the data seller serve as nodes in a block chain, and transaction information is recorded and linked up, so that fairness, non-falsification and traceability of the whole transaction process are guaranteed.

In addition, the transaction data set is encrypted and then sent to the storage space of the platform side node in an out-of-link transmission mode, only the data buyer which is finally successfully matched can obtain the encrypted transaction data set, and decryption of the data is completed, so that the transaction data set is prevented from being tampered and stolen.

Drawings

In order to more clearly illustrate the embodiments of the present invention and the technical solutions in the designed system architectures, the following briefly introduces the embodiments of the present invention and the system architectures and the drawings used in the technical solutions, which are described below, obviously, the drawings described below are only some embodiments of the present invention, and for those skilled in the art, other drawings can be obtained according to these drawings without creative efforts.

FIG. 1 is an architecture diagram of a data transaction platform in an embodiment of the present invention;

FIG. 2 is a flow chart illustrating the implementation of a data transaction method according to an embodiment of the present invention;

FIG. 3 is a flowchart illustrating a portion of the steps performed in a data transaction method according to an embodiment of the present invention;

FIG. 4 is a flowchart illustrating the execution of an intelligent contract deployed on a platform-side node in an embodiment of the present invention;

FIG. 5 is a flow chart illustrating the execution of an intelligent contract deployed at a seller node in an embodiment of the present invention.

Detailed Description

It is to be understood that the following detailed description is exemplary and intended to provide an indicative description of the invention, and it is to be noted that all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention belongs.

The system architecture and the prior art solutions in the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present invention, and it should be noted that the described embodiments are only for explaining and illustrating the present invention, and not for all purposes. On the basis of the embodiments provided by the present invention, all other embodiments obtained by a person of ordinary skill in the art without any creative effort are within the protection scope of the present application.

Summary of the application

A traditional data transaction mode adopts a centralized storage and management mode, the fairness of transactions depends on a third party to a large extent, a transaction data set is easy to tamper and steal, and the transaction process is difficult to trace.

Blockchains are a novel decentralized technique that includes distributed data storage, point-to-point transmission, consensus mechanisms, encryption algorithms, and other computer technologies. The method has the greatest characteristic that a plurality of nodes exist, and each node can maintain a set of same database, so that data stored in a blockchain cannot be forged and falsified, and the transaction of the blockchain is guaranteed to be authentic and credible. Due to the characteristics of high reliability, difficult data loss and the like, the block chain can realize a fair and transparent platform convenient for tracing.

The block chain technology is utilized to optimize the existing data transaction platform, the advantages of the block chain technology can be fully utilized, and the fairness, the non-falsification and the traceability of the data transaction process can be ensured. In view of this, the present invention provides a data transaction platform and a data transaction method based on a block chain.

Referring to fig. 1, the data transaction platform provided by the present invention is constructed based on a block chain framework, and the nodes of the data transaction platform include a platform side node, a plurality of data seller nodes, and a plurality of data buyer nodes. Wherein: the platform side nodes, the data seller nodes and the data buyer nodes are all provided with intelligent contracts, and the data seller nodes and the data buyer nodes are also provided with public keys distributed by the intelligent contracts and legal certificates.

Therefore, in the invention, the platform side, the data buyer and the data seller are used as nodes in the block chain, each participant implements data interaction with the data transaction platform through the corresponding node, and the data transaction process is controlled through an intelligent contract, thereby ensuring fairness, non-falsification and traceability of the whole transaction process.

Optionally, the blockchain in the present invention adopts a federation chain architecture.

As shown in fig. 2, the platform side node, each data seller node and each data buyer node carry out the data transaction process as follows.

And S100, submitting a seller order by each data seller node, encrypting a transaction data set by using a symmetric key, and sending the encrypted transaction data set to a data service center of the platform side node, wherein the symmetric key is automatically generated by the data seller node through a symmetric encryption algorithm.

In particular, the method comprises the following steps of,

setting data vendors

To sell the transaction data set D, the data seller, upon submitting the seller's order

Using self-generated symmetric keys k _sys，a Encrypting the transaction data set to obtain an encrypted transaction data set D _ENc ＝ENC(k _sys，a ，D)。

Next, the data seller

And sending the encrypted transaction data set to a data management center provided by the platform side.

The seller order at least comprises seller quotes given by the data seller for the transaction data set, and also comprises the description information of the data and the like.

After the data seller node submits the seller order, the intelligent contract completes the identity verification of the data seller node and the check of the transaction data set. The seller order information is then stored on the blockchain.

Other data seller nodes, each data seller node, can obtain seller order information from the blockchain.

The seller price quoted by the data seller is determined by the data seller according to the transaction situation. Of course, it is preferred that the data seller also employ various known data resource pricing models to determine seller quotes in order to effect transactions as quickly as possible and to achieve predetermined transaction goals.

For example, in some embodiments, the pricing process for a transaction data set by a data seller is as follows:

data vendors' pricing for data is based primarily on cost dimension considerations. The cost of the transaction data set D to be sold is mainly divided into two aspects, namely the cost of collecting the data and the cost C required for the potential privacy disclosure of the data _p (. Cndot.). Wherein:

for data collection cost:

can be considered as a function C only related to the amount of data _c (. Cndot.) is expressed as follows

C _c (D) L = l | D |, where l is a cost parameter, determined by the data vendor from its own collected data, l ∈ [0,1 |)]。

For privacy costs:

since the data seller grasps the private data contained in the transaction data set and the degree of desensitization of the final sale data is determined by the data seller, the data seller is priced differently for privacy costs than the data buyer.

The embodiment of the invention emphasizes the cost which is additionally paid by a data seller for acquiring the transaction data set containing the privacy, wherein the privacy cost is expressed as follows:

wherein h is the privacy-removing processing parameter set by the data seller, such as the proportion of noise added,

the seller of the data is required to pay additional cost for obtaining such private data.

In this way, the data seller can calculate the cost C (D) of the transaction data set D to be sold,

C(D)＝w _cc C _c (D)+w _cp C _p (D)；

wherein, ω is _cc 、ω _cp Is a weight parameter, omega, set by the data seller for each cost according to the self preference _cc +ω _cp ＝1。

Finally, the data seller gives the seller's offer for the transaction data set according to the cost C (D) of the transaction data set D, such as the seller's offer is equal to the cost C (D), or higher than the cost C (D), and so on.

And S200, submitting a buyer order by each data buyer node.

Data buyer

If the data in the seller orders submitted by the data sellers are interested, the buyer orders can be submitted through the corresponding data buyer nodes, and the buyer orders at least comprise the data buyers

A buyer quote is given for the transaction data set.

Similarly, the buyer price quoted by the data buyer can be determined by the data buyer according to the transaction situation, and of course, in order to achieve the transaction as soon as possible and achieve the predetermined transaction goal, the data buyer can also use various known pricing models to determine the buyer price.

For example, in some embodiments, the pricing process for the transaction data set by the data buyer is as follows:

the data buyer prices the transaction data set from four dimensions of timeliness, privacy content, data quality and data quantity. If a transaction data set available for purchase is denoted by D and the data size is | D |, the pricing method for the transaction data set is described as follows:

1. aging property

The data is backed by information, generally speaking, the newer the information is, the more valuable the information is, but there are some situations where the more valuable the scarce data is, and therefore the embodiment of the invention designs a pricing function including both situations. According to the embodiment of the invention, age of Information (AoI) is used for measuring the timeliness of data, and the AoI is defined as follows:

Δ(D，t)＝tH _t (D)；

where t represents the current time, H _t (D) A timestamp representing the last time the data set D was updated before time t.

Considering that the value and the AoI respectively have negative correlation and positive correlation under the conditions that the newer value of the data is higher and the older value of the data is higher, the correlation between the AoI and the data value is represented by using rela epsilon { -1,1}, namely, rela =1, namely, positive correlation, and rela = -1, namely, negative correlation, and the parameter is selected by a data buyer according to the preference of the data buyer, the timeliness of the data can be priced as follows:

wherein the content of the first and second substances,

is a factor that the buyer sets according to his own preferences,

2. privacy content

Since the data may contain some potentially private information, the data buyer may purchase the transaction D = { t = through its existing analysis model f _j |1≤j≤|D| converted into the space S in which the private data is located, t _j And the privacy content of D is defined as follows:

then the corresponding data privacy value P _p (D) The pricing can be as follows:

3. data quality and data volume

A value measure of data quality may be derived from aggregated information accuracy (E) ₁ (. DEG)), effective data characteristic quality (E) ₂ (. -) and data application model effects (E) ₃ (. The)) and the specific details are as follows:

accuracy of summarized information:

when selling data, a data seller generally needs to provide summary information of the sold data so that a buyer can know the content contained in the data and further evaluate the value. While the data seller provides the summarized data, it also needs to provide the accuracy assessment of the summarized data, i.e. E ₁ (D) Optionally, setting E ₁ (·)∈[0，1]。

Effective data characteristic quality:

when using data for model training or analysis, the effective characteristics of the data have a great influence on the result. Null values, abnormal values, and the like contained in the data affect the validity of the data characteristics. Therefore, the effective data feature quality E can be calculated by counting the ratio of null, outlier, and error type values included in the data feature ₂ (·)。

Data application model effects:

since most of the transaction data sets purchased by sellers are analyzed by applying the transaction data sets to corresponding target application models, the data quality directly affects the analysis effect of the models. Thus, a measure of data quality can be achieved through an evaluation of the model.

Assuming that a data buyer can acquire a sample data set before purchasing data, model training is performed using the sample data set to represent model training of the data set D, and the model training effect E ₃ (D) May be measured by accuracy, mean square error, etc.

The data quality can be evaluated by integrating the results of the three aspects, the data quality can be priced by combining the data quantity, and the mathematical expression is as follows:

where TD represents the total data that the data buyer will use when applying the model and ξ represents the revenue that the total data application is expected to obtain in the model.

And finally, by integrating the pricing of the four dimensions, the estimation pricing of the data buyer to the data can be obtained:

P(D)＝w _t P _t (D)+w _p P _p (D)+w _q P _q (D)；

wherein, ω is _t ，ω _p ，ω _q Weights, ω, set for buyers to several dimensions according to their preferences _t +ω _p +ω _q ＝1。

And S300, the platform side node calls an intelligent contract to match the seller orders submitted by each data seller node and the buyer orders submitted by the data buyer nodes, and the data seller nodes and the data buyer nodes which are successfully matched are determined.

As will be appreciated by those of ordinary skill in the art, there will often be multiple data sellers who have the same or similar transaction data sets during the same time period, and there must be a competing relationship between these data sellers. Similarly, there may be multiple data buyers interested in the same transaction data set, and there must be a competitive relationship between the data buyers. The data seller may, as the case may be, give the price of the transaction data set that it is prepared to sell, and the data buyer may, as the case may be, give the price of the transaction data set that it is prepared to purchase.

For simplicity, for a certain transaction data set, the intelligent contract may calculate the difference between the buyer quotation given by each data buyer and the seller quotation given by each data seller, and determine the successfully matched data seller node and data buyer node by using the seller order and buyer order with the smallest difference as the successfully matched order pair.

Of course, the intelligent contract may also adopt various known mature game models, auction bidding models, and other strategies to more scientifically match the seller orders submitted by each data seller node and the buyer orders submitted by each data buyer node.

For example, in some embodiments, the smart contract employs a continuous bi-directional auction strategy to match the seller orders submitted by each data seller node with the buyer orders submitted by each data buyer node, thereby determining the data seller node and the data buyer node that are successfully matched.

Here, it should be noted that the continuous two-way auction strategy is an auction bidding algorithm well known to those skilled in the art, and the algorithm principle and implementation procedure thereof are not the subject of the present invention, so that the detailed algorithm principle and implementation procedure thereof will not be described in detail herein for the sake of brevity. In practicing the present invention, one skilled in the art can refer to the open literature: zhang J, mcBurney P, music K.conversion of mapping sequences in connecting double extraction marks with boundary-oriented network derivatives [ J ]. Review of Quantitative Finance and Accounting,2018,50 (1): 301-352.

And S400, the platform side node calls the intelligent contract to manage the data transaction between the successfully matched data seller node and the successfully matched data buyer node, and records the transaction information to the block chain.

As shown in fig. 3, step S400 includes the following sub-steps:

s401, the successfully matched data seller nodes adopt public keys distributed by the intelligent contract and asymmetric keys to encrypt the symmetric keys, and the encrypted keys are submitted to the intelligent contract, wherein the asymmetric keys are automatically generated by the data seller nodes through an asymmetric encryption algorithm.

Specifically, the method comprises the following steps:

the successfully matched data seller nodes adopt an asymmetric encryption algorithm to generate a pair of asymmetric keys by themselves

Encrypting using a second key of an asymmetric key pair

Encrypting the symmetric key k employed by the data vendor node in encrypting the transaction data set _sys，a To obtain a third key

Public key distributed by intelligent contract

Encrypting a first key of an asymmetric key pair

Get the fourth key

Finally, the third key _sys，a The fourth key

AsAnd submitting the encrypted key to the intelligent contract.

And S402, completing payment by the data buyer node which is successfully matched.

And S403, after the intelligent contract determines that the payment is successful, the encrypted secret key is sent to the successfully matched data buyer node, the data buyer node decrypts the encrypted secret key by using the public key distributed by the intelligent contract to obtain a symmetric secret key, and decrypts the encrypted transaction data set downloaded from the storage space of the platform side node by using the symmetric secret key to obtain the decrypted transaction data set.

Specifically, the method comprises the following steps:

after the intelligent contract determines that the payment is successful, the third key is used _sys，a And a fourth key

Sending the data to the data buyer node with successful matching

Meanwhile, the matched data buyer node

Encrypted transaction data set D downloaded from storage space of platform side node _ENC 。

Next, the data buyer node

Public key distributed using intelligent contracts

From the third key _sys，a And a fourth key

In order to decrypt the symmetric key k _sys，a 。

Finally, a symmetric key k is used _sys，a Decrypting the encrypted transaction data set D _ENC Obtaining the originalThe transaction data set D.

And S404, the intelligent contract records the transaction information to the block chain.

As mentioned above, in the present invention, the platform side node, the data seller node and the data buyer node are all configured with intelligent contracts, and the data transaction of the present invention is controlled and executed by the intelligent contracts.

In order to make the technical solution of the present invention more clearly understood by those skilled in the art, the following describes an exemplary implementation process of the intelligent contract involved in the present invention, specifically as follows:

as shown in fig. 4, the platform side node sets up and implements an intelligent contract having the following flow.

C100: and receiving orders of the buyer and the seller, receiving encrypted data corresponding to the orders of the seller, and storing the encrypted data to the data service center.

The intelligent contract deployed on the platform side node needs to be capable of managing the orders of the buyer and the seller, and is responsible for controlling the storage of the encrypted data corresponding to the order of the seller to the data service center, and the storage position should meet the requirement of rapidly acquiring the encrypted data corresponding to the required order of the seller. The manner of storage for the data service center may be varied, e.g., in some embodiments, the data service center may use a relational database to store data. Of course, the data service center may use various types of databases such as a distributed database, a file database, and the like to store data more scientifically for a specific scenario.

C200: the order is added to the trading pool and the order arrival message is broadcast.

The transaction pool contains all unmatched buy and sell orders, and the order data in the transaction pool can be temporarily stored in a local database of the platform side node to wait for matching. The process of broadcasting the order arrival message is known to those skilled in the art and will not be described in detail herein.

C300: matching the buyer and seller orders in the trading pool.

The specific contents of the matching process are the same as those described in S300.

C400: and informing the successful matched buyer and seller nodes to perform a transaction confirmation process.

After order matching is completed, the intelligent contract deployed on the platform side node is responsible for communication between the buyer and seller nodes which are successfully matched, and informs the buyer and seller nodes to start a transaction confirmation process. The buyer node automatically pays the required fee through an intelligent contract arranged on the buyer node, and generates and returns transaction confirmation completion information to complete the transaction confirmation process of the buyer. The seller node automatically sends the prepared encrypted key information through the smart contract deployed on its node to complete the seller transaction confirmation process.

If the transaction confirmation process cannot be completed due to network fluctuation and other reasons, different disposal modes can be set according to specific implementation scenes. If, in some embodiments, the transaction confirmation process cannot be completed, the corresponding order is considered invalid.

C500: and executing the consensus algorithm after the transaction is confirmed.

As known to those skilled in the art, the consensus algorithm can be divided into a CFT-type algorithm and a BFT-type algorithm according to whether a byzantine error is tolerated or not, a corresponding consensus algorithm can be set in an intelligent contract according to different implementation requirements, and different consensus algorithms can be run in different node groups in a block chain. For example, in some embodiments, the consensus process is performed uniformly in the federation chain using the PBFT consensus algorithm.

C600: and recording the transaction information to the blockchain after the consensus is achieved.

As shown in FIG. 5, the data seller node sets up and enforces an intelligent contract with the flow described below.

SC100: the seller generates a seller order upon submitting the request and transmits the seller order along with the encrypted data.

After the seller submits the related selling information such as quotation, encrypted data and the like, a corresponding order is automatically generated by an intelligent contract deployed at the data seller node, and the order and the encrypted data are sent to the platform side node.

The SC200: the encrypted key information is stored in a controllable storage area in the data vendor node.

At the same time that the seller submits the quote, the corresponding encrypted key information should also be submitted to the smart contract deployed on its node. The key information should be stored under the control of the smart contract in an area where only the smart contract has access rights, so as to facilitate automatic delivery of the encrypted key information in the transaction confirmation process.

SC300: and receiving a transaction confirmation notice and automatically sending the encrypted key information.

When the intelligent contract deployed at the data seller node receives a transaction confirmation notification from the platform side node, the corresponding encrypted key information should be automatically sent to complete the transaction confirmation process.

The intelligent contract deployed on the data buyer node has a simpler process, only needs two steps of automatic generation and sending of the order and buyer order confirmation, and therefore, detailed description of the process diagram is not used. The automatic order generation and transmission process is similar to the SC100, and after the buyer submits the related purchase information such as quote, the corresponding order is automatically generated by the intelligent contract deployed in the data buyer node and transmitted to the platform side node. In the buyer order confirmation process, the required fee should be paid automatically by the intelligent contract deployed on the data buyer node to complete the buyer order confirmation.

The invention has been described above with a certain degree of particularity. It will be understood by those of ordinary skill in the art that the descriptions of the embodiments are merely exemplary and that all changes and modifications made without departing from the true spirit and scope of the present invention shall fall within the protective scope of the present invention. The scope of the invention is defined by the appended claims rather than by the foregoing description of the embodiments.

Claims (10)

1. The data transaction method based on the block chain is characterized by being implemented on a data transaction platform, wherein the data transaction platform is constructed based on a block chain framework;

the nodes in the data transaction platform at least comprise a platform side node, a plurality of data seller nodes and a plurality of data buyer nodes, wherein intelligent contracts are deployed on the platform side node, each data seller node and each data buyer node, and each data seller node and each data buyer node have public keys distributed by the intelligent contracts;

the data transaction method comprises the following steps:

each data seller node submits a seller order, encrypts a transaction data set by using a symmetric key, and sends the encrypted transaction data set to a data service center of the platform side node, wherein the symmetric key is automatically generated by the data seller node through a symmetric encryption algorithm;

each data buyer node submits a buyer order;

the platform side node completes identity verification of each data seller node and each data buyer node;

the platform side node calls an intelligent contract to match the seller orders submitted by each data seller node and the buyer orders submitted by each data buyer node so as to determine the successfully matched data seller nodes and data buyer nodes;

and the platform side node calls the intelligent contract to manage the data transaction between the successfully matched data seller node and the successfully matched data buyer node, and records the transaction information to the block chain.

2. The blockchain-based data transaction method of claim 1 wherein the platform-side node invoking intelligent contract management of data transactions between successfully matched data seller nodes and data buyer nodes includes:

the data seller nodes which are successfully matched adopt a public key and an asymmetric key distributed by the intelligent contract to encrypt the symmetric key, and submit the encrypted key to the intelligent contract, wherein the asymmetric key is automatically generated by the data seller nodes through an asymmetric encryption algorithm;

the matched data buyer node completes payment;

and after the intelligent contract determines that the payment is successful, the encrypted key is sent to the successfully matched data buyer node, the encrypted key is decrypted by the data buyer node by adopting a public key distributed by the intelligent contract to obtain the symmetric key, and the encrypted transaction data set downloaded from the storage space of the platform side node is decrypted by adopting the symmetric key to obtain the decrypted transaction data set.

3. The blockchain-based data transaction method of claim 2, wherein the data seller node that successfully matches encrypts the symmetric key using the public key and the asymmetric key distributed by the smart contract to obtain an encrypted key, and submits the encrypted key to the smart contract, including:

self-generating a first key and a second key in pair by adopting an asymmetric encryption algorithm;

encrypting the symmetric key by using the second key to obtain a third key;

encrypting the first key by adopting the public key distributed by the intelligent contract to obtain a fourth key;

and submitting the third key and the fourth key to the intelligent contract as encrypted keys.

4. A data transaction method as claimed in claim 1, wherein:

the seller orders at least comprise seller quotes which are given by corresponding data seller sections and are aimed at the transaction data sets, and the buyer orders at least comprise buyer quotes which are given by corresponding data buyer nodes and are aimed at the transaction data sets;

and the intelligent contract matches the seller orders submitted by the data seller nodes and the buyer orders submitted by the data buyer nodes by adopting a two-way auction strategy.

5. The data transaction method of claim 4, wherein the data seller node determines a seller offer for the transaction data set by steps comprising:

determining a collection cost of the transaction data set:

C _c (D)＝l·|D|，

d is a transaction data set, | D | is the data volume of the transaction data set, l is a collection cost parameter of a unit transaction data set, and l is more than or equal to 0 and less than or equal to 1;

determining a privacy cost of the transaction data set:

wherein, the first and the second end of the pipe are connected with each other,

h is a privacy removal processing parameter, and h is more than or equal to 0 and less than or equal to 1, so as to obtain the extra cost needed by the transaction data set of the unit;

based on the collection cost and the privacy cost, calculating a seller offer for the transaction data set:

C(D)＝ω _cc C _c (D)+ω _cp C _p (D) Wherein, ω is _cc 、ω _cp To collect weights for cost, privacy cost, ω _cc +ω _cp ＝1。

6. The data transaction method of claim 4, wherein the data buyer node determines a buyer offer for the transaction data set by:

determining a time-based pricing for the transaction data set;

determining privacy content pricing for the transaction data set;

determining data quality pricing for the transactional data set;

calculating a buyer offer for the transaction data set based on the timeliness pricing, privacy content pricing, and data quality pricing of the transaction data set:

P(D)＝ω _t P _t (D)+ω _p P _p (D)+w _q P _q (D) Wherein P is _t (D) Time-sensitive pricing for transaction data sets, P _p (D) Privacy content pricing for transactional data sets, P _q (D) Pricing data quality for transactional data sets, omega _t ，ω _p ，ω _q Weighting, omega, of time-sensitive pricing of transaction data sets, privacy content pricing of transaction data sets, data quality pricing of transaction data sets _t +ω _p +ω _q ＝1。

7. The data trafficking method of claim 6 wherein the determining a time-sensitive pricing of the traffic data set comprises:

calculating a timeliness metric for the transaction data set:

Δ(D，t)＝t-H _t (D) Where t represents the current time, H _t (D) A timestamp indicating the last time the data set D was updated before time t;

calculating timeliness pricing:

wherein, rela represents the correlation between the timeliness measure and the data value, rela =1 is positive correlation, rela = -1 is negative correlation,

is a data buyer preference factor.

8. The data transaction method of claim 6, wherein the determining the privacy content pricing of the transaction data set comprises:

will trade data set D = { t = { t = } _j Converting |1 is more than or equal to j and less than or equal to | D | into a space S where the privacy data are located;

obtaining data items t in a transaction data set _j The privacy content of (b):

calculating the privacy content of the transaction data set:

calculating a privacy content pricing for the transaction data set based on the privacy content of the transaction data set:

9. the data trafficking method of claim 6 wherein determining the data quality pricing for the traffic data set includes:

obtaining an information accuracy E of the transaction data set ₁ (D)；

Obtaining a valid data characteristic quality E of the transaction data set ₂ (D)；

Obtaining a data application model effectiveness measure E of the transaction data set applied in a target application model ₃ (D)；

Calculating the data quality of the transaction data set based on the information accuracy, effective data feature quality and data application model effectiveness metric of the transaction data set:

calculating a data quality pricing for the transactional dataset based on a data quality of the transactional dataset:

where TD represents all data that the data buyer will use in the target application model, and ξ represents all dataThe application to the target application model predicts the gains that can be obtained.

10. A data transaction platform based on a block chain is characterized in that the data transaction platform is constructed based on a block chain framework;

the nodes in the data transaction platform at least comprise a platform side node, a plurality of data seller nodes and a plurality of data buyer nodes, wherein intelligent contracts are deployed on the platform side node, each data seller node and each data buyer node, and each data seller node and each data buyer node have public keys distributed by the intelligent contracts;

the platform side node, each data seller node and each data buyer node implement data transaction according to the following processes:

each data seller node submits a seller order, encrypts a transaction data set by using a symmetric key, and sends the encrypted transaction data set to the platform side node data service center, wherein the symmetric key is automatically generated by the data seller node through a symmetric encryption algorithm;

each data buyer node submits a buyer order;

the platform side node completes identity verification of each data seller node and each data buyer node;

the platform side node calls an intelligent contract to match the seller orders submitted by each data seller node and the buyer orders submitted by each data buyer node, and the data seller nodes and the data buyer nodes which are successfully matched are determined;

and the platform side node calls the intelligent contract to manage the data transaction between the successfully matched data seller node and the successfully matched data buyer node, and records the transaction information to the block chain.

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