Toward Efficient Multi-Keyword Fuzzy Search Over Encrypted Outsourced Data With Accuracy Improvement
Nanjing University of Information Science and Technology · University at Buffalo, State University of New York
Abstract
Keyword-based search over encrypted outsourced data has become an important tool in the current cloud computing scenario. The majority of the existing techniques are focusing on multi-keyword exact match or single keyword fuzzy search. However, those existing techniques find less practical significance in real-world applications compared with the multi-keyword fuzzy search technique over encrypted data. The first attempt to construct such a multi-keyword fuzzy search scheme was reported by Wang et al., who used locality-sensitive hashing functions and Bloom filtering to meet the goal of multi-keyword fuzzy search. Nevertheless, Wang's scheme was only effective for a one letter mistake in keyword but was not…
Citation impact
- FWCI
- 155.04
- Percentile
- 100%
- References
- 34
Authors
5- ZFZhangjie FuCorresponding
Nanjing University of Information Science and Technology, University at Buffalo, State University of New York
- XWXinle Wu
Nanjing University of Information Science and Technology
- CGChaowen Guan
University at Buffalo, State University of New York
- XSXingming Sun
Nanjing University of Information Science and Technology
- KRKui Ren
University at Buffalo, State University of New York
Topics & keywords
- Computer science
- Keyword density
- Data mining
- Approximate string matching
- Encryption
- Fuzzy logic
- Scheme (mathematics)
- Keyword search
- Quality Education