Privacy-preserving Outsourced Similarity Search

J 2014

Privacy-preserving Outsourced Similarity Search

KOZÁK, Štěpán; David NOVÁK a Pavel ZEZULA

Základní údaje

Originální název

Privacy-preserving Outsourced Similarity Search

Autoři

KOZÁK, Štěpán; David NOVÁK a Pavel ZEZULA

Vydání

Journal of Database Management, IGI Global, 2014, 1063-8016

Další údaje

Jazyk

angličtina

Typ výsledku

Článek v odborném periodiku

Obor

10201 Computer sciences, information science, bioinformatics

Stát vydavatele

Spojené státy

Utajení

není předmětem státního či obchodního tajemství

Impakt faktor

Impact factor: 0.179

Označené pro přenos do RIV

Ano

Kód RIV

RIV/00216224:14330/14:00073231

Organizační jednotka

Fakulta informatiky

Klíčová slova anglicky

Cloud; EM-Index; Outsourcing; Privacy; Similarity Search

Štítky

DISA

Příznaky

Mezinárodní význam, Recenzováno

Změněno: 9. 9. 2019 12:55, RNDr. Pavel Šmerk, Ph.D.

Anotace

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.

Návaznosti

GBP103/12/G084, projekt VaV

Název: Centrum pro multi-modální interpretaci dat velkého rozsahu

Investor: Grantová agentura ČR, Centrum pro multi-modální interpretaci dat velkého rozsahu

VF20102014004, projekt VaV

Název: Multimediální analýza (Akronym: Multimediální analýza)

Investor: Ministerstvo vnitra ČR, Multimediální analýza

Citovat

KOZÁK, Štěpán; David NOVÁK a Pavel ZEZULA. Privacy-preserving Outsourced Similarity Search. Journal of Database Management. IGI Global, 2014, roč. 25, č. 3, s. 48-71. ISSN 1063-8016. Dostupné z: https://doi.org/10.4018/jdm.2014070103.

@article{1192666,
   author = {Kozák, Štěpán and Novák, David and Zezula, Pavel},
   article_number = {3},
   doi = {https://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 a Pavel ZEZULA. Privacy-preserving Outsourced Similarity Search. \textit{Journal of Database Management}. IGI Global, 2014, roč.~25, č.~3, s.~48-71. ISSN~1063-8016. Dostupné z: https://doi.org/10.4018/jdm.2014070103.

Přehled o publikaci