Journal article
VeriFuzzy: A Dynamic Verifiable Fuzzy Search Service Framework for Encrypted Cloud Data
IEEE transactions on services computing, Vol.19(1), pp.780-793
01/2026
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Abstract
Enabling search over encrypted cloud data is essential for privacy-preserving data outsourcing. While searchable encryption has evolved to support individual requirements like fuzzy matching (tolerance to typos and variants in query keywords), dynamic updates, and result verification, designing a service that supports Dynamic Verifiable Fuzzy Search (DVFS) over encrypted cloud data remains a fundamental challenge due to inherent conflicts between underlying technologies. Existing approaches struggle with simultaneously achieving efficiency, functionality, and security, often forcing impractical trade-offs. This paper presents VeriFuzzy , a novel DVFS service framework that cohesively integrates three innovations: an Enhanced Virtual Binary Tree (EVBTree) that decouples fuzzy semantics from index logic to support O(\log n) search/updates; a blockchain-reconstructed verification mechanism that ensures result integrity with logarithmic complexity; and a dual-repository state management scheme that achieves IND-CKA2 security by neutralizing branch leakage. Extensive evaluation on 3,500+ documents shows VeriFuzzy achieves 41% faster search, 5\times more efficient verification, and constant-time index updates compared to state-of-the-art alternatives. Our code and dataset are now open source, hoping to inspire future DVFS research.
Details
- Title
- VeriFuzzy: A Dynamic Verifiable Fuzzy Search Service Framework for Encrypted Cloud Data
- Creators
- Jie Zhang - Tianjin UniversityXiaohong Li - Tianjin UniversityMan Zheng - Xiong’an New Area Power Supply Company (China)Ruitao Feng - Southern Cross UniversityShanshan Xu - East China Normal UniversityZhe Hou - Griffith UniversityGuangdong Bai - City University of Hong Kong
- Publication Details
- IEEE transactions on services computing, Vol.19(1), pp.780-793
- Publisher
- IEEE; LOS ALAMITOS
- Grant note
- National Key Research and Development Program of China: 2023YFB3107103 National Natural Science Foundation of China: 62262073, 62332005 Beijing-Tianjin-Hebei Natural Science Foundation Joint Cooperation Program: 25JJJJC0034
This work was supported in part by the National Key Research and Development Program of China under Grant 2023YFB3107103, in part by the National Natural Science Foundation of China under Grant 62262073 and Grant 62332005, and in part by the Beijing-Tianjin-Hebei Natural Science Foundation Joint Cooperation Program under Grant 25JJJJC0034.
- Identifiers
- 991013339190902368
- Academic Unit
- Faculty of Science and Engineering
- Language
- English
- Resource Type
- Journal article