ESA: Privacy-Preserving Data Sharing Framework With Efficient Fuzzy Search and Access Control

Cloud-assisted data sharing offers substantial convenience to resource-constrained users, enabling them to outsource data to public clouds and permit authorized users to perform retrievals. However, ensuring data privacy remains a significant challenge. Attribute-Based Keyword Search (ABKS) facilitates authorized searches over encrypted data, yet most existing ABKS schemes are primarily tailored for exact searches. They lack effective support for fuzzy search, which severely limits the practicality and efficiency. In this paper, we propose ESA, a novel privacy-preserving framework supporting multi-keyword fuzzy search with arbitrary Boolean semantics and fine-grained access control in data sharing. ESA introduces the Prime Filter, a novel data structure, along with a divide-and-conquer access control mechanism to achieve secure, efficient, and accurate fuzzy search. To enable authorized multi-keyword fuzzy search, the Prime Filter is designed as a unified primitive for both indexing and querying. It seamlessly integrates fuzzy search and access-policy enforcement by leveraging the indivisibility of prime numbers. To ensure reliable access control during both the search and decryption phases, ESA proposes a divide-and-conquer mechanism that leverages blockchain to coordinate the off-chain and on-chain indexes. Finally, we extend ESA from the perspective of non-repudiation. Formal security analysis demonstrates that ESA is secure under the known background model. Extensive evaluations confirm ESA’s advantages, demonstrating search speeds up to 2–$86\times$ faster than state-of-the-art methods, with precision exceeding 95%.