Privacy-preserving multi-keyword fuzzy search over encrypted data in the cloud
INFOCOM(2014)
摘要
Enabling keyword search directly over encrypted data is a desirable technique for effective utilization of encrypted data outsourced to the cloud. Existing solutions provide multi-keyword exact search that does not tolerate keyword spelling error, or single keyword fuzzy search that tolerates typos to certain extent. The current fuzzy search schemes rely on building an expanded index that covers possible keyword misspelling, which lead to significantly larger index file size and higher search complexity. In this paper, we propose a novel multi-keyword fuzzy search scheme by exploiting the locality-sensitive hashing technique. Our proposed scheme achieves fuzzy matching through algorithmic design rather than expanding the index file. It also eliminates the need of a predefined dictionary and effectively supports multiple keyword fuzzy search without increasing the index or search complexity. Extensive analysis and experiments on real-world data show that our proposed scheme is secure, efficient and accurate. To the best of our knowledge, this is the first work that achieves multi-keyword fuzzy search over encrypted cloud data.
更多查看译文
关键词
locality-sensitive hashing technique,fuzzy set theory,index file size,predefined dictionary,data privacy,cryptography,privacy-preserving multikeyword fuzzy search,encrypted cloud data,algorithmic design,database indexing,search problems,computational complexity,fuzzy matching,file organisation,cloud computing,search complexity
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络