Novel Frequency Based Natural Language Query Search in Cloud Computing

Abstract

Cloud data owners prefer to outsource data because of ease in maintenance. Data confidentiality of this outsourced sensitive data is a major task. Applying cryptographic techniques to outsourced data is the most secure way to achieve confidentiality. Searchable encryption techniques help in searching on encrypted data without actually decrypting it. These techniques limit the usability of data in the sense that it is difficult to search on encrypted data. As the volume of data increases the size of indexing structure increases. This makes it more difficult to design cipher text based search scheme which facilitates reliable, memory efficient, fast retrieval on a huge volume of encrypted data. In this paper, keyword frequency based code method is presented to minimize the size of the index which makes fast retrieval of data inside a big data environment. The proposed system also supports secured, ranked retrieval using hash-based mapping structures. A hash-based technique efficiently retrieves the data using key-value pair data structure. The resulting system is able to handle queries which are written in natural language. Through extensive experiments using standard dataset, the performance of the system is validated. The results show that the proposed system requires very less space for index storage and hence also improves the retrieval time.