This method formulates and executes access control for multi-owner data sharing, suggesting enhanced security and autonomy.
With the rapid development of artificial intelligence, multi-party collaboration based on data sharing has become an inevitable trend. However, in practical applications, shared data often originate from multiple providers. Therefore, achieving secure and efficient data sharing while protecting the rights and interests of each data provider is a key challenge currently faced. Existing access control methods have the following shortcomings in multi-owner data scenarios. Most methods rely on centralized management, which makes it difficult to solve conflicts caused by inconsistent permission policies among multiple owners. There are problems such as poor consistency of permission management, low security, and lack of protection for the autonomous will of each owner. To this end, our paper proposes a fine-grained decentralized autonomous access control scheme based on blockchain, which includes three core stages: formulation, deployment, and execution of access control policies. In the access control policy formulation stage, the scheme constructs a multi-owner data policy matrix and introduces a benefit function based on a Stackelberg game to balance conflicting attributes to form a unified access policy. Secondly, in the access control policy deployment stage based on smart contracts, all data owners vote on the access control policy by calculating their own benefits to achieve a consensus on joint decision-making on the policy. Finally, in the policy execution and joint authorization phase, a decentralized authorization method based on threshold passwords is used to distribute access keys to each owner, ensuring that data is only granted after receiving authorization from a sufficient number of owners, thereby ensuring the ultimate control of each owner and the fine-grained access control. Finally, we verified the feasibility of the solution through case analysis and experiments.
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Li et al. (2025) studied this question.
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