Paper Info
Title
Achieving Efficient and Privacy-Preserving Set Containment Search Over Encrypted Data
Abstract
Set containment search, which aims to retrieve all set records containing a specific query set, has received considerable attention. Meanwhile, due to the dramatic growth of data, data owners tend to outsource their data to the cloud and deploy the cloud server to offer the set containment search services. However, as the cloud server is not fully trustable and the data may be sensitive, a straightforward strategy for the data owners is to encrypt the data before outsourcing them. Although the encryption technique can preserve data privacy, it inevitably hinders the functionality of set containment search. Many existing studies on the set containment search over outsourced data still suffer from the search efficiency and security issues. In this article, aiming at the above issues, we propose an efficient and privacy-preserving set containment search scheme. Specifically, we first deploy an asymmetric scalar-product-preserving encryption technique to design a set containment/intersection encryption (SCIE-Enc) scheme. Then, we build a radix tree to represent the set records. Based on the radix tree and SCIE-Enc construction, we present our scheme that can achieve efficient set containment search while preserving the privacy of set records, query sets, and query results, as indicated in our security analysis and performance evaluation.
Year
DOI
Venue
2022
10.1109/TSC.2021.3065240
IEEE Transactions on Services Computing
Keywords
DocType
Volume
Set containment search,cloud computing,scalar product computation,radix tree,privacy-preserving
Journal
15
Issue
ISSN
Citations 
5
1939-1374
1
PageRank 
References 
Authors
0.36
18
5
Name
Order
Citations
PageRank
Yandong Zheng1206.38
Rongxing Lu25091301.87
Yunguo Guan3275.82
Jun Shao416525.53
Hui Zhu58317.00