Research On Data Security And Trusted Transaction Scheme Based On Alliance Chai

The rapid development of the digital economy has made data an important strategic resource.In order to increase the utilization and commercial value of data,the emergence of data markets has effectively promoted data sharing and trading,driven by interests,greatly reducing the generation of data silos.However,there are still some problems that have not been well solved in the current data market,such as excessive centralization of the market,unfair transaction processes,easy leakage of private data,inconsistent data pricing,and data abuse.Blockchain technology,with its characteristics of decentralization,traceability,low cost,and tamper resistance,has been widely applied in various fields.Applying it to data trading can solve problems that are difficult to solve with traditional solutions,such as excessive reliance on third-party platforms,lack of trust between transaction parties,and unfair transaction processes.At the same time,attribute-based encryption technology serves as an effective means of solving data sharing access control.Compared with traditional public key encryption methods,the advantage of attributebased encryption technology is that its public and private keys are not a one-to-one relationship.Data can be shared with different users with just one encryption,and users only need to meet the access policies specified by the encryptor to obtain the corresponding attribute key and decrypt the data,achieving fine-grained data access control,which can effectively increase the value of data.This article uses blockchain,game theory,attribute-based encryption and other technologies to conduct research on data pricing,fair transactions,and data security issues in data trading.The specific work is as follows:(1)A multi-dimensional data utility evaluation and pricing model is proposed.Firstly,a multi-dimensional data utility evaluation method is proposed based on three data quality dimensions: data size,availability,and integrity.Secondly,a big data trading market model is designed,which includes Data Providers(DP),Service Providers(SP),and Service Users(SU).A pricing scheme based on Stackelberg game theory is proposed using the above data utility evaluation method to maximize the profit of participants in the big data trading market.(2)A data trading scheme based on attribute-based encryption and smart contracts is proposed.To meet the need for fine-grained access control of Data Sellers(DS),ciphertext policy attribute-based encryption technology is used to protect the security of the data for sale,ensuring that only Data Buyers(DB)with specific attributes can purchase and correctly decrypt the data.To balance privacy protection and regulatory traceability in data transactions,a consortium chain and group signature technology are used to achieve secure and trustworthy as well as anonymous and traceable data transactions.Specifically,DS and DB publish and trade data through smart contracts deployed on the consortium chain,and group signature algorithms are used to sign the transactions.When necessary,regulatory nodes on the consortium chain can open group signatures to track the identity of malicious users and punish them through an arbitration mechanism.