DACSC: Dynamic and Fine-Grained Access Control for Secure Data Collaboration in Cloud Computing
Qinlong Huang, Nan Li, Yixian Yang · 2018
Data collaboration is more and more popular in cloud computing. In a typical collaboration scenario, data owner outsources the data to cloud platforms, and users can access and re-upload the data. In consideration of the semi-trusted cloud platform, attribute-based encryption (ABE) has been utilized to guarantee data confidentiality and fine-grained access control. However, how to allow the collaborative data to be accessed only by authorized users in a flexible and dynamic manner is a challenging problem. In this paper, we propose DACSC, a dynamic and fine-grained access control scheme for secure data collaboration in cloud computing. First of all, we adopt ciphertext-policy ABE technique to define the original access policy of outsourced data. Second, we introduce a tree-based policy extending framework which allows users who satisfy the original access policy to customize a new access policy and add it to current access policies in a non-restrictive or restrictive way. Furthermore, we achieve integrity checking during the policy extending procedure based on ABE with equality test algorithm, which ensures that the added access policy comes from authorized user. The security analysis and experimental results indicate that DACSC is secure and efficient, and is suitable for the data collaboration scenario in cloud computing.