Multi-keywords fuzzy search encryption supporting dynamic update in an intelligent edge network

Abstract

In an intelligent edge network, data owners encrypt data and outsource it to the edge servers to prevent the leakage of data and user information. It is a research issue to achieve efficient search and data update of the ciphertext stored in the edge servers. For the above problems, we construct a fuzzy multi-keyword search scheme based on a two-level tree index, where the first-level tree index stores keyword tags and the second-level stores encrypted file identifiers and counting bloom filters (CBFs). By constructing a two-level tree index, efficient multi-keyword search is realised, and it also has obvious time advantages when performing the single-keyword search. In addition, the proposed scheme supports index updating by introducing the CBF, and it can realise fuzzy search by calculating the inner product between the CBF in index and search trapdoor. At last, the proposed scheme is proved to be semantically secure under the known ciphertext attack model. Theoretical analysis and simulation test indicate that the proposed scheme spends lower computation overhead than other related schemes, especially in the search phase; as the number of matching files or query keywords grows, it costs less time, at around 2–10 ms.