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. doi:10.1007/978-3-642-32873-2_9.
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Basic information
Original name Secure Metric-Based Index for Similarity Cloud
Authors KOZÁK, Štěpán (203 Czech Republic, belonging to the institution), David NOVÁK (203 Czech Republic, belonging to the institution) and Pavel ZEZULA (203 Czech Republic, guarantor, belonging to the institution).
Edition 7482. vyd. Berlin / Heidelberg, Secure Data Management : Proceedings of 9th VLDB Workshop, SDM 2012, Istanbul, Turkey, August 27, 2012, p. 130-147, 18 pp. 2012.
Publisher Springer
Other information
Original language English
Type of outcome Proceedings paper
Field of Study 10201 Computer sciences, information science, bioinformatics
Country of publisher Germany
Confidentiality degree is not subject to a state or trade secret
Publication form printed version "print"
WWW DOI
Impact factor Impact factor: 0.402 in 2005
RIV identification code RIV/00216224:14330/12:00057633
Organization unit Faculty of Informatics
ISBN 978-3-642-32872-5
ISSN 0302-9743
Doi http://dx.doi.org/10.1007/978-3-642-32873-2_9
Keywords in English similarity search; data privacy; cloud computing; data security
Tags DISA
Tags International impact, Reviewed
Changed by Changed by: RNDr. David Novák, Ph.D., učo 4335. Changed: 27. 2. 2013 10:02.
Abstract
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.
Links
GBP103/12/G084, research and development projectName: Centrum pro multi-modální interpretaci dat velkého rozsahu
Investor: Czech Science Foundation
VF20102014004, research and development projectName: Multimediální analýza (Acronym: Multimediální analýza)
Investor: Ministry of the Interior of the CR
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  • a concrete person RNDr. Štěpán Kozák, učo 255615
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  • a concrete person prof. Ing. Pavel Zezula, CSc., učo 47485
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