Efficient and Provably Secure Data Selective Sharing and Acquisition in Cloud-Based Systems

Abstract

Towards the large amount of data generated everyday, data selective sharing and acquisition is one of the most significant data services in cloud-based systems, which enables data owners to selectively share their data to some particular users, and users to selectively acquire some interested data. However, it is challenging to protect data security and user privacy during data selective sharing and selective acquisition, because cloud servers are curious about the data or user’s interests, and even send data to some unauthorized users or some uninterested users. In this paper, we propose an efficient and provably secure Data selective Sharing and Acquisition ( DSA ) scheme for cloud-based systems. Specifically, we first formulate a generic data selective sharing and acquisition problem in cloud-based systems by identifying several design goals in terms of correctness, soundness, security and efficiency. Then, we propose the DSA scheme to enable data owners to control the access of their data in a fine-grained manner, and enable users to refine the data acquisition without revealing their interests. Technically, a brand new cryptographic framework is developed to integrate attribute-based encryption with searchable encryption. Finally, we prove that the proposed DSA scheme is correct, sound, secure in the random oracle model, and efficient in practice.

Publication
IEEE Transactions on Information Forensics and Security, vol. 18, pp. 71-84, 2023. (中科院大类一区, CCF A 类期刊)
Ruitao Xie
Ruitao Xie
Associate Professor

My research interests include scheduling system resources to improve the performance of AI applications, edge computing, cloud computing, and mobile computing.