Title: One privacy-preserving multi-keyword ranked search scheme revisited

Authors: Zhengjun Cao; Xiqi Wang; Lihua Liu

Addresses: Department of Mathematics, Shanghai University, Shangda Road, 99, Shanghai, China ' Department of Mathematics, Shanghai University, Shangda Road, 99, Shanghai, China ' Department of Mathematics, Shanghai Maritime University, Haigang Ave, 1550, Shanghai, China

Abstract: Searchable encryption is a useful tool which allows a user to securely search over encrypted data through keywords and retrieve documents of interest. It plays a key role in big data and outsourcing computation scenarios. In this paper, we show that the privacy-preserving multi-keyword ranked search scheme over encrypted cloud data (Cao et al., 2014) is flawed, because the introduced similarity scores do not represent the true similarities between indexing vectors and a querying vector. The returned documents by cloud server could be irrelevant to the queried keyword. We also present a revision based on the technique introduced by Wong et al. (2009).

Keywords: cloud computing; multi-keyword ranked search; privacy-preserving search; scalar-product-preserving encryption; SPPE.

DOI: 10.1504/IJICS.2021.10042546

International Journal of Information and Computer Security, 2021 Vol.16 No.3/4, pp.375 - 384

Received: 18 Jan 2019
Accepted: 20 Jun 2019

Published online: 15 Nov 2021 *

Full-text access for editors Access for subscribers Purchase this article Comment on this article