Details
| Original language | English |
|---|---|
| Title of host publication | Proceedings of the 12th International Conference on Extending Database Technology |
| Subtitle of host publication | Advances in Database Technology, EDBT'09 |
| Publisher | Association for Computing Machinery (ACM) |
| Pages | 439-449 |
| Number of pages | 11 |
| ISBN (print) | 9781605584225 |
| Publication status | Published - 24 Mar 2009 |
| Event | 12th International Conference on Extending Database Technology: Advances in Database Technology, EDBT'09 - Saint Petersburg, Russian Federation Duration: 24 Mar 2009 → 26 Mar 2009 |
Publication series
| Name | Proceedings of the 12th International Conference on Extending Database Technology: Advances in Database Technology, EDBT'09 |
|---|
Abstract
Privacy-preserving document exchange among collaboration groups in an enterprise as well as across enterprises requires techniques for sharing and search of access-controlled information through largely untrusted servers. In these settings search systems need to provide confidentiality guarantees for shared information while offering IR properties comparable to the ordinary search engines. Top-k is a standard IR technique which enables fast query execution on very large indexes and makes systems highly scalable. However, indexing access-controlled information for top-k retrieval is a challenging task due to the sensitivity of the term statistics used for ranking. In this paper we present ZERBER+R - a ranking model which allows for privacy-preserving top-k retrieval from an outsourced inverted index. We propose a relevance score transformation function which makes relevance scores of different terms indistinguishable, such that even if stored on an untrusted server they do not reveal information about the indexed data. Experiments on two real-world data sets show that ZERBER+R makes economical usage of bandwidth and offers retrieval properties comparable with an ordinary inverted index.
ASJC Scopus subject areas
- Computer Science(all)
- Computer Science Applications
- Computer Science(all)
- Software
Cite this
- Standard
- Harvard
- Apa
- Vancouver
- BibTeX
- RIS
Proceedings of the 12th International Conference on Extending Database Technology: Advances in Database Technology, EDBT'09. Association for Computing Machinery (ACM), 2009. p. 439-449 (Proceedings of the 12th International Conference on Extending Database Technology: Advances in Database Technology, EDBT'09).
Research output: Chapter in book/report/conference proceeding › Conference contribution › Research › peer review
}
TY - GEN
T1 - ZERBER+R
T2 - 12th International Conference on Extending Database Technology: Advances in Database Technology, EDBT'09
AU - Zerr, Sergej
AU - Olmedilla, Daniel
AU - Nejdl, Wolfgang
AU - Siberski, Wolf
PY - 2009/3/24
Y1 - 2009/3/24
N2 - Privacy-preserving document exchange among collaboration groups in an enterprise as well as across enterprises requires techniques for sharing and search of access-controlled information through largely untrusted servers. In these settings search systems need to provide confidentiality guarantees for shared information while offering IR properties comparable to the ordinary search engines. Top-k is a standard IR technique which enables fast query execution on very large indexes and makes systems highly scalable. However, indexing access-controlled information for top-k retrieval is a challenging task due to the sensitivity of the term statistics used for ranking. In this paper we present ZERBER+R - a ranking model which allows for privacy-preserving top-k retrieval from an outsourced inverted index. We propose a relevance score transformation function which makes relevance scores of different terms indistinguishable, such that even if stored on an untrusted server they do not reveal information about the indexed data. Experiments on two real-world data sets show that ZERBER+R makes economical usage of bandwidth and offers retrieval properties comparable with an ordinary inverted index.
AB - Privacy-preserving document exchange among collaboration groups in an enterprise as well as across enterprises requires techniques for sharing and search of access-controlled information through largely untrusted servers. In these settings search systems need to provide confidentiality guarantees for shared information while offering IR properties comparable to the ordinary search engines. Top-k is a standard IR technique which enables fast query execution on very large indexes and makes systems highly scalable. However, indexing access-controlled information for top-k retrieval is a challenging task due to the sensitivity of the term statistics used for ranking. In this paper we present ZERBER+R - a ranking model which allows for privacy-preserving top-k retrieval from an outsourced inverted index. We propose a relevance score transformation function which makes relevance scores of different terms indistinguishable, such that even if stored on an untrusted server they do not reveal information about the indexed data. Experiments on two real-world data sets show that ZERBER+R makes economical usage of bandwidth and offers retrieval properties comparable with an ordinary inverted index.
UR - http://www.scopus.com/inward/record.url?scp=70349110963&partnerID=8YFLogxK
U2 - 10.1145/1516360.1516412
DO - 10.1145/1516360.1516412
M3 - Conference contribution
AN - SCOPUS:70349110963
SN - 9781605584225
T3 - Proceedings of the 12th International Conference on Extending Database Technology: Advances in Database Technology, EDBT'09
SP - 439
EP - 449
BT - Proceedings of the 12th International Conference on Extending Database Technology
PB - Association for Computing Machinery (ACM)
Y2 - 24 March 2009 through 26 March 2009
ER -