| KOZÁK, Štěpán, David NOVÁK and Pavel ZEZULA. Secure Metric-Based Index for Similarity Cloud. In Jonker, Willem and Petkovic, Milan. Secure Data Management : Proceedings of 9th VLDB Workshop, SDM 2012, Istanbul, Turkey, August 27, 2012. 7482nd ed. Berlin / Heidelberg: Springer, 2012, p. 130-147. ISBN 978-3-642-32872-5. Available from: https://dx.doi.org/10.1007/978-3-642-32873-2_9. |
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@inproceedings{1067779,
author = {Kozák, Štěpán and Novák, David and Zezula, Pavel},
address = {Berlin / Heidelberg},
booktitle = {Secure Data Management : Proceedings of 9th VLDB Workshop, SDM 2012, Istanbul, Turkey, August 27, 2012},
doi = {http://dx.doi.org/10.1007/978-3-642-32873-2_9},
edition = {7482},
editor = {Jonker, Willem and Petkovic, Milan},
keywords = {similarity search; data privacy; cloud computing; data security},
howpublished = {tištěná verze "print"},
language = {eng},
location = {Berlin / Heidelberg},
isbn = {978-3-642-32872-5},
pages = {130-147},
publisher = {Springer},
title = {Secure Metric-Based Index for Similarity Cloud},
url = {http://dx.doi.org/10.1007/978-3-642-32873-2_9},
year = {2012}
}
TY - JOUR
ID - 1067779
AU - Kozák, Štěpán - Novák, David - Zezula, Pavel
PY - 2012
TI - Secure Metric-Based Index for Similarity Cloud
PB - Springer
CY - Berlin / Heidelberg
SN - 9783642328725
KW - similarity search
KW - data privacy
KW - cloud computing
KW - data security
UR - http://dx.doi.org/10.1007/978-3-642-32873-2_9
L2 - http://dx.doi.org/10.1007/978-3-642-32873-2_9
N2 - We propose a similarity index that ensures data privacy and thus is suitable for search systems outsourced in a cloud. The proposed solution can exploit existing efficient metric indexes based on a fixed set of reference points. The method has been fully implemented as a security extension of an existing established approach called M-Index. This Encrypted M-Index supports evaluation of standard range and nearest neighbors queries both in precise and approximate manner. In the first part of this work, we analyze various levels of privacy in existing or future similarity search systems; the proposed solution tries to keep a reasonable privacy level while relocating only the necessary amount of work from server to an authorized client. The Encrypted M-Index has been tested on three real data sets with focus on various cost components.
ER -
KOZÁK, Štěpán, David NOVÁK and Pavel ZEZULA. Secure Metric-Based Index for Similarity Cloud. In Jonker, Willem and Petkovic, Milan. \textit{Secure Data Management : Proceedings of 9th VLDB Workshop, SDM 2012, Istanbul, Turkey, August 27, 2012}. 7482nd ed. Berlin / Heidelberg: Springer, 2012, p.~130-147. ISBN~978-3-642-32872-5. Available from: https://dx.doi.org/10.1007/978-3-642-32873-2\_{}9.
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