Document Type
Conference Proceeding
Publication Date
9-2014
Abstract
Hosting data query services in public clouds is an attractive solution for its great scalability and significant cost savings. However, data owners also have concerns on data privacy due to the lost control of the infrastructure. This demonstration shows a prototype for efficient and confidential range/kNN query services built on top of the random space perturbation (RASP) method. The RASP approach provides a privacy guarantee practical to the setting of cloudbased computing, while enabling much faster query processing compared to the encryption-based approach. This demonstration will allow users to more intuitively understand the technical merits of the RASP approach via interactive exploration of the visual interface.
Repository Citation
Alavi, Z. S.,
Zhou, L.,
Powers, J. L.,
& Chen, K.
(2014). RASP-QS: Efficient and Confidential Query Services in the Cloud. .
https://corescholar.libraries.wright.edu/knoesis/1096
Included in
Bioinformatics Commons, Communication Technology and New Media Commons, Databases and Information Systems Commons, OS and Networks Commons, Science and Technology Studies Commons
Comments
This work is licensed under the Creative Commons AttributionNonCommercial-NoDerivs 3.0 Unported License. To view a copy of this license, visit http://creativecommons.org/licenses/by-nc-nd/3.0/. Obtain permission prior to any use beyond those covered by the license.
Presented at the 40th International Conference on Very Large Data Bases, Hangzhou, China, September 1-5, 2014.