Split keyword fuzzy and synonym search over encrypted cloud data

A substitute solution for various organizations of data owners to store their data in the cloud using storage as a service(SaaS). The outsourced sensitive data is encrypted before uploading into the cloud to achieve data privacy. The encrypted data is search based on keywords and retrieve interested files by data user using a lot of traditional Search scheme. Existing search schemes supports exact keyword match or fuzzy keyword search, but synonym based multi-keyword search are not supported. In the real world scenario, cloud users may not know the exact keyword for searching and they might give synonym of the keyword as the input for search instead of exact or fuzzy keyword due to lack of appropriate knowledge of data. In this paper, we describe an efficient search approach for encrypted data called as Split Keyword Fuzzy and Synonym Search (SKFS). Multi-keyword ranked search with accurate keyword and Fuzzy search supports synonym queries are a major contribution of SKFS. The wildcard Technique is used to store the keywords securely within the index tree. Index tree helps to search faster, accurate and low storage cost. Extensive experimental results on real-time data sets shows, the proposed solution is effective and efficient for multi-keyword ranked search and synonym queries Fuzzy based search over encrypted cloud data. © 2017 Springer Science+Business Media, LL

Efficient Fuzzy Search on Encrypted Data

We study the problem of efficient (sub-linear) fuzzy search on encrypted outsourced data, in the symmetric-key setting. In particular, a user who stores encrypted data on a remote untrusted server forms queries that enable the server to efficiently locate the records containing the requested keywords, even though the user may misspell keywords or provide noisy data in the query. We define an appropriate primitive for a general \emph{closeness} function on the message space that we call \emph{efficiently fuzzy-searchable encryption} (\emph{EFSE}). Next we identify an optimal security notion for EFSE. We demonstrate that existing schemes do not meet our security definition and propose a new scheme that we prove secure under basic assumptions. Unfortunately, the scheme requires large ciphertext length, but we show that, in a sense, this space-inefficiency is unavoidable for a general, optimally-secure scheme. Seeking the right balance between efficiency and security, we then show how to construct schemes that are more efficient and satisfy a weaker security notion that we propose. To illustrate, we present and analyze a more space-efficient scheme for supporting fuzzy search on biometric data that achieves the weaker notion