Title
Privacy-preserving kNN query processing algorithms via secure two-party computation over encrypted database in cloud computing
Abstract
Since studies on privacy-preserving database outsourcing have been spotlighted in a cloud computing, databases need to be encrypted before being outsourced to the cloud. Therefore, a couple of privacy-preserving kNN query processing algorithms have been proposed over the encrypted database. However, the existing algorithms are either insecure or inefficient. Therefore, in this paper we propose a privacy-preserving kNN query processing algorithm via secure two-party computation on the encrypted database. Our algorithm preserves both data privacy and query privacy while hiding data access patterns. For this, we propose efficient and secure protocols based on Yao’s garbled circuit. To achieve a high degree of efficiency in query processing, we also propose a parallel kNN query processing algorithm using encrypted random value pool. Through our performance analysis, we verify that our proposed algorithms outperform the existing ones in terms of a query processing cost.
Year
DOI
Venue
2022
10.1007/s11227-021-04286-2
The Journal of Supercomputing
Keywords
DocType
Volume
Secure protocol, Privacy-preserving kNN query processing algorithm, Encrypted database, Database outsourcing, Cloud computing
Journal
78
Issue
ISSN
Citations 
7
0920-8542
1
PageRank 
References 
Authors
0.36
16
4
Name
Order
Citations
PageRank
Hyeong-Jin Kim194.25
Hyunjo Lee210.36
Yong-Ki Kim3459.88
Jae-Woo Chang410.36