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Salmani et al. J Surveill Secur Saf 2020;1:79–101 Journal of Surveillance,
DOI: 10.20517/jsss.2020.16 Security and Safety

Original Article Open Access

Leakless privacy-preserving multi-keyword ranked

search over encrypted cloud data

1
Khosro Salmani , Ken Barker 2
1 Department of Mathematics and Computing, Mount Royal University, Calgary, AB T3E 6K6, Canada.
2 Department of Computer Science, University of Calgary, Calgary, AB T2N 1N4, Canada.

Correspondence to: Prof. Ken Barker, Department of Computer Science, University of Calgary, Calgary, AB T2N 1N4, Canada.
E-mail: kbarker@ucalgary.ca

How to cite this article: Salmani K, Barker K. Leakless privacy-preserving multi-keyword ranked search over encrypted cloud data.
J Surveill Secur Saf 2020;1:79–101. http://dx.doi.org/10.20517/jsss.2020.16

Received: 4 May 2020 First Decision: Revised: 28 Jue 2020 Accepted: 11 August 2020 Available online: 27 Sep 2020
Academic Editor: Xiaofeng Chen Copy Editor: Stella Zhang Production Editor: Jing Yu

Abstract
Aim: During the last decade, various type of cloud services have encouraged individuals and enterprises to store
personal data in the cloud. Despite its flexibility, cost efficiency, and convenient service, protecting security and
privacy of the outsourced data has always been a primary challenge. Although data encryption retains the outsourced
data’s security and privacy to some extent, it does not permit traditional plaintext keyword search mechanisms, and
it comes at the cost of efficiency. Hence, proposing an efficient encrypted cloud data search service would be an
important step forward. Related work focuses on single keyword search and even those which support multi-keyword
search suffer from private information leakage.

Methods: Our proposed method, employs the secure inner product similarity and our chaining encryption notion.
The former helps to provide sufficient search accuracy and the latter yields the privacy requirements.

Results: In this paper, we address the problem of leakless privacy-preserving multi-keyword ranked search over
encrypted cloud data (LRSE), and our new contributions address challenging problems of search pattern, and co-
occurrence information leakage in the cloud.

Conclusion: Our security and performance analysis shows that the proposed scheme guarantees a high level of pri-
vacy/security and efficiency.

Keywords: Data privacy, cloud security, multi-keyword ranked search, privacy-preserving data search

© The Author(s) 2020. Open Access This article is licensed under a Creative Commons Attribution 4.0
International License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, shar-
ing, adaptation, distribution and reproduction in any medium or format, for any purpose, even commercially, as long as you
give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate
if changes were made.

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