Approximate Keyword-based Search over Encrypted Cloud Data

To protect the privacy, users have to encrypt their sensitive data before outsourcing it to the cloud. However, the traditional encryption schemes are inadequate since they make the application of indexing and searching operations more challenging tasks. Accordingly, searchable encryption systems are developed to conduct search operations over a set of encrypted data. Unfortunately, these systems only allow their clients to perform an exact search but not approximate search, an important need for all the current information retrieval systems. Recently, an increased attention has been paid to the approximate searchable encryption systems to find keywords that match the submitted queries approximately. Our work focuses on constructing a flexible secure index that allows the cloud server to perform the approximate search operations without revealing the content of the query trapdoor or the index content. Specifically, the most recently cryptographic primitive, order preserving symmetric encryption (OPSE), has been employed to protect our keywords. Our proposed scheme divides the search operation into two steps. The first step finds the candidate list in terms of secure pruning codes. In particular, we have developed two methods to construct these pruning codes. The second step uses a semi honest third party to determine the best matching keyword depending on secure similarity function. We intend to reveal as little information as possible to that third party. We hope that developing such a system will enhance the utilization of retrieval information systems and make these systems more user-friendly.