Abstract
Recently, searching over encrypted cloud-data outsourcing has attracted the current researcher. Using cloud computing (CC), individuals and organizations are motivated to outsource their private and sensitive data onto the cloud service provider (CSP) due to less maintenance cost, great flexibility, and ease of access. However, the data should be encrypted using encryption techniques such as DES and AES before uploading to the CSP in order to provide data privacy and protection, which obsolete plaintext searching techniques over encrypted cloud data. Thus, this article proposes an efficient multi-keyword synonym-based ranked searching technique over encrypted cloud data (EMSRSE), which supports dynamic insertion and deletion of documents. The main objectives of EMSRSE are 1. To build an index search tree in order to store encrypted index vectors of documents and 2. To achieve better searching efficiency, a searching technique over the encrypted index tree is proposed. An extensive research and empirical result analysis show that the proposed EMSRSE scheme achieves better efficiency in comparison with other existing methods.
Highlights
As cloud service provider (CSP) cannot be trusted in terms of data outsourcing, the data encryption is recommended to provide data privacy, before it is uploaded to CSP
The Term Frequency-Inverse Document Frequency (TFIDF) [23] model is employed in order to retrieve ranked search results, which are used in searchable encryption schemes
The experiments are conducted for existing scheme BDMRS [6] and SMSRQE [28] in addition to the proposed EMSRSE
Summary
Various searching techniques have been proposed over encrypted cloud data. S. Cong Wang et al [10] proposes a method named ranked keyword pursuit over encrypted cloud data using techniques such as keyword frequency and orderpreserving encryption It supports only a single keyword at a time. Cao et al [11] have proposed a system, which supports conjunctive keywords search It is a privacy-preserving multi-keyword ranked pursuit technique using symmetric encryption. The authors in [16] propose a model for a single keyword semanticbased pursuit over cloud data encryption affirming similarity ranking This method returns the exact keyword matched files, and the files comprise semantically related to the query keyword. The authors in [18] present two techniques to support multi-keyword ranked pursuit to attain more accurate pursuit results and the synonym-based pursuit to support synonym queries over encrypted cloud data. Offer a privacypreserving multi-keyword ranked system for multi-keyword ranked pursuit over encrypted cloud data (MRSE) that uses coordinate matching
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