A Decentralized Big Data Trading Model Based On Blockchain And Smart Contracts

Big data plays an important role in modern science technology and social activities.On the one hand,a large number of new applications and technologies are integrated into our lives,and a mass of data is generated from the use of these new technologies.On the other hand,as an important digital asset,big data supports the development of many new technologies.The analysis and use of high-quality data can help companies or organizations significantly improve their competitiveness.Currently,researchers have proposed some big data trading solutions.At the same time,there are numerous data trading platforms providing services for data generation and use.These solutions and platforms facilitate the sharing and circulation of data.However,there are still some major problems:(1)State-of-the-art solutions are mostly based on the centralized thirdparty data trading platform,there are facing the problem of a single point of failure(SPOF),opaque transactions,uncontrollable,and untraceable,as well as the problems of data and identity privacy security.(2)The traditional data quality assessment schemes based on third-party assessment centers are not very suitable for decentralized data trading.(3)The existing data trading pricing models are difficult to meet the requirements of dynamic price negotiation and value feedback of blockchain-based big data trading pricing.This dissertation is conducted to resolve the above issues from the following aspects:First of all,this dissertation proposes a big data trading platform based on blockchain and smart contracts,which is able to achieve secure and reliable trading of data in a distributed environment which does not rely on third-party data trading platforms.The design of blockchain can provide more trusted and irreversible data information and transaction records for both parties(the requester and the provider)of big data trading.The design of smart contracts improves the intelligence and automation of big data trading,guaranteeing data provider's autonomous control over big data trading and the fairness of data revenue distribution.Apply proxy re-encryption technology to data transmission scheme further improves the security of data trading.Secondly,this dissertation designs a data quality evaluation and pricing model and data price negotiation model in a decentralized environment.According to the specific data requirements,the data requester gives a quality evaluation through data application and processing.Based on the quality evaluation,the contract implements the dynamic pricing of the data set.This scheme guarantees that high-quality data achieves high-quality reward,and thus guarantees the fairness of data trading.In addition,the price negotiation model based on smart contracts completes the pricing of data,ensuring that data providers and requesters make bids in turn under the price game rules.Smart contracts recommend bid for the next stage in each stage of bidding to help bidders make more reasonable bids,which improves the efficiency of data negotiation pricing to a certain extent.Finally,this dissertation designs and implements a decentralized big data trading application proposed above,and tests the time spent on block consensus and data encryption and decryption,the experimental results show the availability of system modules.By deploying smart contracts on the Ethereum blockchain,it does not require third parties to participate in trading,the contract implements the intelligent trading of big data and the negotiation process of data prices.