Privacy-preserving Outsourced Similarity Search

J 2014

Privacy-preserving Outsourced Similarity Search

KOZÁK, Štěpán, David NOVÁK and Pavel ZEZULA

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

Language

English

Type of outcome

Článek v odborném periodiku

Field of Study

10201 Computer sciences, information science, bioinformatics

Country of publisher

United States of America

Confidentiality degree

není předmětem státního či obchodního tajemství

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

Abstract

V originále

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 project

Name: Centrum pro multi-modální interpretaci dat velkého rozsahu

Investor: Czech Science Foundation

VF20102014004, research and development project

Name: Multimediální analýza (Acronym: Multimediální analýza)

Investor: Ministry of the Interior of the CR

Citovat

KOZÁK, Štěpán, David NOVÁK and Pavel ZEZULA. Privacy-preserving Outsourced Similarity Search. Journal of Database Management. IGI Global, 2014, vol. 25, No 3, p. 48-71. ISSN 1063-8016. Available from: https://dx.doi.org/10.4018/jdm.2014070103.

@article{1192666,
   author = {Kozák, Štěpán and Novák, David and Zezula, Pavel},
   article_number = {3},
   doi = {http://dx.doi.org/10.4018/jdm.2014070103},
   keywords = {Cloud; EM-Index; Outsourcing; Privacy; Similarity Search},
   language = {eng},
   issn = {1063-8016},
   journal = {Journal of Database Management},
   title = {Privacy-preserving Outsourced Similarity Search},
   volume = {25},
   year = {2014}
}

TY  - JOUR
ID  - 1192666
AU  - Kozák, Štěpán - Novák, David - Zezula, Pavel
PY  - 2014
TI  - Privacy-preserving Outsourced Similarity Search
JF  - Journal of Database Management
VL  - 25
IS  - 3
SP  - 48-71
EP  - 48-71
PB  - IGI Global
SN  - 10638016
KW  - Cloud
KW  - EM-Index
KW  - Outsourcing
KW  - Privacy
KW  - Similarity Search
N2  - 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.
ER  -

KOZÁK, Štěpán, David NOVÁK and Pavel ZEZULA. Privacy-preserving Outsourced Similarity Search. \textit{Journal of Database Management}. IGI Global, 2014, vol.~25, No~3, p.~48-71. ISSN~1063-8016. Available from: https://dx.doi.org/10.4018/jdm.2014070103.

Detailed Information on Publication Record