Title: Multi-keyword synonym search over encrypted cloud data using classified category-dictionary and BMIS tree

Authors: Veerraju Gampala; Sreelatha Malempati

Addresses: Department of Computer Science and Engineering, GMR Institute of Technology, Rajam, India; Computer Science and Engineering, Acharya Nagarjuna University, Guntur, Andhra Pradesh, India ' Department of Computer Science and Engineering, R.V.R. and J.C. College of Engineering, Chowdavaram, Guntur, Andhra Pradesh, India

Abstract: Due to the emerging popularity of cloud computing (CC), the individuals and organisations are driven to outsource their private data onto the cloud service provider (CSP) in order to achieve less maintenance cost, great flexibility, and ease of access. The data normally encrypt before outsourced to the CSP, which obsolete plain-text searching techniques over encrypted cloud-data. Thus, this paper presents an efficient and accurate multi-keyword synonym ranked search method over encrypted cloud data (MKSRSE). The objectives of MKSRSE are as follows: 1) to build a balanced m-way index search (BMIS) tree; 2) propose a modified depth first search (MDFS) technique to search for the top score ranked documents; 3) propose a classified category-dictionary; 4) propose a methodology to extract keywords from each category documents to form the category sub-dictionary. An extensive research shows that the proposed mechanisms provide better search efficiency and accuracy in comparison with other existing techniques.

Keywords: multi-keyword search; synonym-ranked search; BMIS tree; MDFS technique; classified category-dictionary; index dynamic update.

DOI: 10.1504/IJTIP.2019.099205

International Journal of Technology Intelligence and Planning, 2019 Vol.12 No.3, pp.223 - 241

Received: 21 Mar 2018
Accepted: 03 Jun 2018

Published online: 23 Apr 2019 *

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