DocumentCode
243620
Title
Privacy-Preserving Queries over Outsourced Data with Access Pattern Protection
Author
Shun-Pun Li ; Man-Hon Wong
Author_Institution
Dept. of Comput. Sci. & Eng., Chinese Univ. of Hong Kong, Shatin, China
fYear
2014
fDate
14-14 Dec. 2014
Firstpage
581
Lastpage
588
Abstract
One of the concerns about database outsourcing is that the service provider may not be trustworthy. Besides protecting data against outsiders, it is necessary to hide sensitive information from the service provider. For single-server environments, data encryption is commonly used to protect data confidentiality. To use server computational resources for processing queries, data are encrypted in tuple-level. Indexing tags are computed and attached to the encrypted tuples such that the server can check if an encrypted tuple satisfies the query predicate without learning exact data values. However, with additional information of some time-based events, service providers can still infer information of the encrypted data through query access patterns if there are observed linkages between the access patterns and the time-based events. In this paper, we study the problem of information disclosure in such a scenario. We first illustrate how to launch the inference attack. Then, we formally define the problem and propose techniques for protecting access privacy. Instead of providing total privacy with a high overhead, our approach aims to lower the confidence of service providers´ inferences. Experiment results show that a high level of access privacy can be achieved with a reasonable overhead.
Keywords
cryptography; data encapsulation; data privacy; database management systems; indexing; outsourcing; query processing; access pattern protection; data confidentiality protection; data encryption; database outsourcing; encrypted tuples; indexing tags; inference attack; information disclosure; outsourced data; privacy-preserving queries; query access patterns; query predicate; query processing; sensitive information hiding; server computational resources; single-server environments; time-based events; Couplings; Databases; Encryption; Medical services; Privacy; Servers; access pattern protection; access privacy; database outsourcing; privacy-preserving query;
fLanguage
English
Publisher
ieee
Conference_Titel
Data Mining Workshop (ICDMW), 2014 IEEE International Conference on
Conference_Location
Shenzhen
Print_ISBN
978-1-4799-4275-6
Type
conf
DOI
10.1109/ICDMW.2014.51
Filename
7022649
Link To Document