Two-party privacy-preserving agglomerative document clustering

Chunhua Su, Jianying Zhou, Feng Bao, Tsuyoshi Takagi, Kouichi Sakurai

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

5 Citations (Scopus)

Abstract

Document clustering is a powerful data mining technique to analyze the large amount of documents and structure large sets of text or hypertext documents. Many organizations or companies want to share their documents in a similar theme to get the joint benefits. However, it also brings the problem of sensitive information leakage without consideration of privacy. In this paper, we propose a cryptography-based framework to do the privacy-preserving document clustering among the users under the distributed environment: two parties, each having his private documents, want to collaboratively execute agglomerative document clustering without disclosing their private contents.

Original languageEnglish
Title of host publicationInformation Security Practice and Experience - Third International Conference, ISPEC 2007, Proceedings
Pages193-208
Number of pages16
Publication statusPublished - Dec 20 2007
Event3rd International Conference on Information Security Practice and Experience, ISPEC 2007 - Hong Kong, Hong Kong
Duration: May 7 2007May 9 2007

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume4464 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Other

Other3rd International Conference on Information Security Practice and Experience, ISPEC 2007
CountryHong Kong
CityHong Kong
Period5/7/075/9/07

Fingerprint

Document Clustering
Privacy Preserving
Cryptography
Data mining
Hypertext
Industry
Distributed Environment
Leakage
Large Set
Privacy
Data Mining

All Science Journal Classification (ASJC) codes

  • Theoretical Computer Science
  • Computer Science(all)

Cite this

Su, C., Zhou, J., Bao, F., Takagi, T., & Sakurai, K. (2007). Two-party privacy-preserving agglomerative document clustering. In Information Security Practice and Experience - Third International Conference, ISPEC 2007, Proceedings (pp. 193-208). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 4464 LNCS).

Two-party privacy-preserving agglomerative document clustering. / Su, Chunhua; Zhou, Jianying; Bao, Feng; Takagi, Tsuyoshi; Sakurai, Kouichi.

Information Security Practice and Experience - Third International Conference, ISPEC 2007, Proceedings. 2007. p. 193-208 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 4464 LNCS).

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

Su, C, Zhou, J, Bao, F, Takagi, T & Sakurai, K 2007, Two-party privacy-preserving agglomerative document clustering. in Information Security Practice and Experience - Third International Conference, ISPEC 2007, Proceedings. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 4464 LNCS, pp. 193-208, 3rd International Conference on Information Security Practice and Experience, ISPEC 2007, Hong Kong, Hong Kong, 5/7/07.
Su C, Zhou J, Bao F, Takagi T, Sakurai K. Two-party privacy-preserving agglomerative document clustering. In Information Security Practice and Experience - Third International Conference, ISPEC 2007, Proceedings. 2007. p. 193-208. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).
Su, Chunhua ; Zhou, Jianying ; Bao, Feng ; Takagi, Tsuyoshi ; Sakurai, Kouichi. / Two-party privacy-preserving agglomerative document clustering. Information Security Practice and Experience - Third International Conference, ISPEC 2007, Proceedings. 2007. pp. 193-208 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).
@inproceedings{ac8d0ff3babe4e979ab817d04b1c2720,
title = "Two-party privacy-preserving agglomerative document clustering",
abstract = "Document clustering is a powerful data mining technique to analyze the large amount of documents and structure large sets of text or hypertext documents. Many organizations or companies want to share their documents in a similar theme to get the joint benefits. However, it also brings the problem of sensitive information leakage without consideration of privacy. In this paper, we propose a cryptography-based framework to do the privacy-preserving document clustering among the users under the distributed environment: two parties, each having his private documents, want to collaboratively execute agglomerative document clustering without disclosing their private contents.",
author = "Chunhua Su and Jianying Zhou and Feng Bao and Tsuyoshi Takagi and Kouichi Sakurai",
year = "2007",
month = "12",
day = "20",
language = "English",
isbn = "3540721592",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
pages = "193--208",
booktitle = "Information Security Practice and Experience - Third International Conference, ISPEC 2007, Proceedings",

}

TY - GEN

T1 - Two-party privacy-preserving agglomerative document clustering

AU - Su, Chunhua

AU - Zhou, Jianying

AU - Bao, Feng

AU - Takagi, Tsuyoshi

AU - Sakurai, Kouichi

PY - 2007/12/20

Y1 - 2007/12/20

N2 - Document clustering is a powerful data mining technique to analyze the large amount of documents and structure large sets of text or hypertext documents. Many organizations or companies want to share their documents in a similar theme to get the joint benefits. However, it also brings the problem of sensitive information leakage without consideration of privacy. In this paper, we propose a cryptography-based framework to do the privacy-preserving document clustering among the users under the distributed environment: two parties, each having his private documents, want to collaboratively execute agglomerative document clustering without disclosing their private contents.

AB - Document clustering is a powerful data mining technique to analyze the large amount of documents and structure large sets of text or hypertext documents. Many organizations or companies want to share their documents in a similar theme to get the joint benefits. However, it also brings the problem of sensitive information leakage without consideration of privacy. In this paper, we propose a cryptography-based framework to do the privacy-preserving document clustering among the users under the distributed environment: two parties, each having his private documents, want to collaboratively execute agglomerative document clustering without disclosing their private contents.

UR - http://www.scopus.com/inward/record.url?scp=37149042707&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=37149042707&partnerID=8YFLogxK

M3 - Conference contribution

AN - SCOPUS:37149042707

SN - 3540721592

SN - 9783540721598

T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

SP - 193

EP - 208

BT - Information Security Practice and Experience - Third International Conference, ISPEC 2007, Proceedings

ER -