Dynamic multi-keyword fuzzy ranked search with leakage resilience over encrypted cloud data

To achieve the confidentiality and retrievability of outsourced data simultaneously, a dynamic multi-keyword fuzzy ranked search scheme (DMFRS) with leakage resilience over encrypted cloud data based on two-level index structure was proposed. The first level index adopts inverted index and orthogonal list, combined with 2-gram and location-sensitive Hashing (LSH) to realize a fuzzy match. The second level index achieves user search permission decision and search result ranking by combining coordinate matching with term frequency-inverse document frequency (TF-IDF). A verification token is generated within the results to verify the search results, which prevents the potential malicious tampering by cloud service providers (CSP). The semantic security of DMFRS is proved by the defined leakage function, and the performance is evaluated based on simulation experiments. The analysis results demonstrate that DMFRS gains certain advantages in security and performance against similar schemes, and it meets the needs of storage and privacy-preserving for outsourcing sensitive data. © 2023, Beijing University of Posts and Telecommunications. All rights reserved.