Privacy-preserving Complex Query Evaluation over Semantically Secure Encrypted Data
Abstract
In the last decade, several techniques have been proposed to evaluate different types of queries (e.g., range and aggregate queries) over encrypted data in a privacy-preserving manner. However, solutions supporting the privacy-preserving evaluation of complex queries over encrypted data have been developed only recently. Such recent techniques, however, are either insecure or not feasible for practical applications. In this paper, we propose a novel privacy-preserving query processing framework that supports complex queries over encrypted data in the cloud computing environment and addresses the shortcomings of previous approaches. At a high level, our framework utilizes both homomorphic encryption and garbled circuit techniques at different stages in query processing to achieve the best performance, while at the same time protecting the confidentiality of data, privacy of the user's input query and hiding data access patterns. Also, as a part of query processing, we provide an efficient approach to systematically combine the predicate results (in encrypted form) of a query to derive the corresponding query evaluation result in a privacy-preserving manner. We theoretically and empirically analyze the performance of this approach and demonstrate its practical value over the current state-of-the-art techniques. Our proposed framework is very efficient from the user's perspective, thus allowing a user to issue queries even using a resource constrained device (e.g., PDAs and cell phones). © 2014 Springer International Publishing Switzerland.
Recommended Citation
B. K. Samanthula et al., "Privacy-preserving Complex Query Evaluation over Semantically Secure Encrypted Data," Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 8712 LNCS, no. PART 1, pp. 400 - 418, Springer, Jan 2014.
The definitive version is available at https://doi.org/10.1007/978-3-319-11203-9_23
Department(s)
Computer Science
Keywords and Phrases
cloud computing; complex Query; encryption; privacy
International Standard Book Number (ISBN)
978-331911202-2
International Standard Serial Number (ISSN)
1611-3349; 0302-9743
Document Type
Article - Conference proceedings
Document Version
Citation
File Type
text
Language(s)
English
Rights
© 2024 Springer, All rights reserved.
Publication Date
01 Jan 2014
