Investigating privacy-aware distributed query evaluation

Nicholas L. Farnan, Adam J. Lee, Ting Yu

Research output: Chapter in Book/Report/Conference proceedingConference contribution

4 Citations (Scopus)

Abstract

Historically, privacy and efficiency have largely been at odds with one another when querying remote data sources: traditional query optimization techniques provide efficient retrieval by exporting information about the intension of a query to data sources, while private information retrieval (PIR) schemes hide query intension at the cost of extreme computational or communication overheads. Given the increasing use of Internet-scale distributed databases, exploring the spectrum between these two extremes is worthwhile. In this paper, we explore the degree to which query intension is leaked to remote data sources when a variety of existing query processing and view materialization techniques are used. We show that these information flows can be quantified in a concrete manner, and investigate the notion of privacy-aware distributed query evaluation. We then propose two techniques to improve the balance between privacy and efficiency when processing distributed queries, and discuss a number of interesting directions for future work.

Original languageEnglish
Title of host publicationProceedings of the ACM Conference on Computer and Communications Security
Pages43-52
Number of pages10
DOIs
Publication statusPublished - 21 Dec 2010
Externally publishedYes
Event9th Annual ACM Workshop on Privacy in the Electronic Society, WPES '10, Co-located with CCS'10 - Chicago, IL, United States
Duration: 4 Oct 20108 Oct 2010

Other

Other9th Annual ACM Workshop on Privacy in the Electronic Society, WPES '10, Co-located with CCS'10
CountryUnited States
CityChicago, IL
Period4/10/108/10/10

Fingerprint

Query processing
Information retrieval
Internet
Concretes
Communication
Processing

Keywords

  • database
  • distributed query processing
  • mutant query plan
  • p2p
  • privacy

ASJC Scopus subject areas

  • Software
  • Computer Networks and Communications

Cite this

Farnan, N. L., Lee, A. J., & Yu, T. (2010). Investigating privacy-aware distributed query evaluation. In Proceedings of the ACM Conference on Computer and Communications Security (pp. 43-52) https://doi.org/10.1145/1866919.1866926

Investigating privacy-aware distributed query evaluation. / Farnan, Nicholas L.; Lee, Adam J.; Yu, Ting.

Proceedings of the ACM Conference on Computer and Communications Security. 2010. p. 43-52.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Farnan, NL, Lee, AJ & Yu, T 2010, Investigating privacy-aware distributed query evaluation. in Proceedings of the ACM Conference on Computer and Communications Security. pp. 43-52, 9th Annual ACM Workshop on Privacy in the Electronic Society, WPES '10, Co-located with CCS'10, Chicago, IL, United States, 4/10/10. https://doi.org/10.1145/1866919.1866926
Farnan NL, Lee AJ, Yu T. Investigating privacy-aware distributed query evaluation. In Proceedings of the ACM Conference on Computer and Communications Security. 2010. p. 43-52 https://doi.org/10.1145/1866919.1866926
Farnan, Nicholas L. ; Lee, Adam J. ; Yu, Ting. / Investigating privacy-aware distributed query evaluation. Proceedings of the ACM Conference on Computer and Communications Security. 2010. pp. 43-52
@inproceedings{0a9f2f57f3c3437a8b46052d05e7da3f,
title = "Investigating privacy-aware distributed query evaluation",
abstract = "Historically, privacy and efficiency have largely been at odds with one another when querying remote data sources: traditional query optimization techniques provide efficient retrieval by exporting information about the intension of a query to data sources, while private information retrieval (PIR) schemes hide query intension at the cost of extreme computational or communication overheads. Given the increasing use of Internet-scale distributed databases, exploring the spectrum between these two extremes is worthwhile. In this paper, we explore the degree to which query intension is leaked to remote data sources when a variety of existing query processing and view materialization techniques are used. We show that these information flows can be quantified in a concrete manner, and investigate the notion of privacy-aware distributed query evaluation. We then propose two techniques to improve the balance between privacy and efficiency when processing distributed queries, and discuss a number of interesting directions for future work.",
keywords = "database, distributed query processing, mutant query plan, p2p, privacy",
author = "Farnan, {Nicholas L.} and Lee, {Adam J.} and Ting Yu",
year = "2010",
month = "12",
day = "21",
doi = "10.1145/1866919.1866926",
language = "English",
isbn = "9781450300964",
pages = "43--52",
booktitle = "Proceedings of the ACM Conference on Computer and Communications Security",

}

TY - GEN

T1 - Investigating privacy-aware distributed query evaluation

AU - Farnan, Nicholas L.

AU - Lee, Adam J.

AU - Yu, Ting

PY - 2010/12/21

Y1 - 2010/12/21

N2 - Historically, privacy and efficiency have largely been at odds with one another when querying remote data sources: traditional query optimization techniques provide efficient retrieval by exporting information about the intension of a query to data sources, while private information retrieval (PIR) schemes hide query intension at the cost of extreme computational or communication overheads. Given the increasing use of Internet-scale distributed databases, exploring the spectrum between these two extremes is worthwhile. In this paper, we explore the degree to which query intension is leaked to remote data sources when a variety of existing query processing and view materialization techniques are used. We show that these information flows can be quantified in a concrete manner, and investigate the notion of privacy-aware distributed query evaluation. We then propose two techniques to improve the balance between privacy and efficiency when processing distributed queries, and discuss a number of interesting directions for future work.

AB - Historically, privacy and efficiency have largely been at odds with one another when querying remote data sources: traditional query optimization techniques provide efficient retrieval by exporting information about the intension of a query to data sources, while private information retrieval (PIR) schemes hide query intension at the cost of extreme computational or communication overheads. Given the increasing use of Internet-scale distributed databases, exploring the spectrum between these two extremes is worthwhile. In this paper, we explore the degree to which query intension is leaked to remote data sources when a variety of existing query processing and view materialization techniques are used. We show that these information flows can be quantified in a concrete manner, and investigate the notion of privacy-aware distributed query evaluation. We then propose two techniques to improve the balance between privacy and efficiency when processing distributed queries, and discuss a number of interesting directions for future work.

KW - database

KW - distributed query processing

KW - mutant query plan

KW - p2p

KW - privacy

UR - http://www.scopus.com/inward/record.url?scp=78650198251&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=78650198251&partnerID=8YFLogxK

U2 - 10.1145/1866919.1866926

DO - 10.1145/1866919.1866926

M3 - Conference contribution

AN - SCOPUS:78650198251

SN - 9781450300964

SP - 43

EP - 52

BT - Proceedings of the ACM Conference on Computer and Communications Security

ER -