KOZÁK, Štěpán, David NOVÁK and Pavel ZEZULA. Privacy-preserving Outsourced Similarity Search. Journal of Database Management. IGI Global, vol. 25, No 3, p. 48-71. ISSN 1063-8016. doi:10.4018/jdm.2014070103. 2014.
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Basic information
Original name Privacy-preserving Outsourced Similarity Search
Authors KOZÁK, Štěpán (203 Czech Republic, belonging to the institution), David NOVÁK (203 Czech Republic, guarantor, belonging to the institution) and Pavel ZEZULA (203 Czech Republic, belonging to the institution).
Edition Journal of Database Management, IGI Global, 2014, 1063-8016.
Other information
Original language English
Type of outcome Article in a journal
Field of Study 10201 Computer sciences, information science, bioinformatics
Country of publisher United States of America
Confidentiality degree is not subject to a state or trade secret
Impact factor Impact factor: 0.179
RIV identification code RIV/00216224:14330/14:00073231
Organization unit Faculty of Informatics
Doi http://dx.doi.org/10.4018/jdm.2014070103
UT WoS 000344365400003
Keywords in English Cloud; EM-Index; Outsourcing; Privacy; Similarity Search
Tags DISA
Tags International impact, Reviewed
Changed by Changed by: RNDr. Pavel Šmerk, Ph.D., učo 3880. Changed: 9/9/2019 12:55.
Abstract
The general trend in data management is to outsource data to 3rd party systems that would provide data retrieval as a service. This approach naturally brings privacy concerns about the (potentially sensitive) data. Recently, quite extensive research has been done on privacy-preserving outsourcing of traditional exact-match and keyword search. However, not much attention has been paid to outsourcing of similarity search, which is essential in content-based retrieval in current multimedia, sensor or scientific data. In this paper, the authors propose a scheme of outsourcing similarity search. They define evaluation criteria for these systems with an emphasis on usability, privacy and efficiency in real applications. These criteria can be used as a general guideline for a practical system analysis and we use them to survey and mutually compare existing approaches. As the main result, the authors propose a novel dynamic similarity index EM-Index that works for an arbitrary metric space and ensures data privacy and thus is suitable for search systems outsourced for example in a cloud environment. In comparison with other approaches, the index is fully dynamic (update operations are efficient) and its aim is to transfer as much load from clients to the server as possible.
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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