Privacy preserving spectral clustering over vertically partitioned data sets

Zhenmin Lin; Jerzy W. Jaromczyk

doi:10.1109/FSKD.2011.6019699

Privacy preserving spectral clustering over vertically partitioned data sets

Zhenmin Lin, Jerzy W. Jaromczyk

Computer Science

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

4 Scopus citations

Abstract

Spectral clustering is one of the most popular modern clustering techniques that often outperforms other clustering techniques. When data owned by different parties are used for analysis, the cooperating parties may need to perform spectral clustering jointly, even if the parties may not be willing to disclose their private data to each other. In this paper we develop privacy preserving spectral clustering protocols over vertically partitioned data sets. Such protocols allow various parties to analyze their data jointly while protecting their privacy.

Original language	English
Title of host publication	Proceedings - 2011 8th International Conference on Fuzzy Systems and Knowledge Discovery, FSKD 2011
Pages	1206-1211
Number of pages	6
DOIs	https://doi.org/10.1109/FSKD.2011.6019699
State	Published - 2011
Event	2011 8th International Conference on Fuzzy Systems and Knowledge Discovery, FSKD 2011, Jointly with the 2011 7th International Conference on Natural Computation, ICNC'11 - Shanghai, China Duration: Jul 26 2011 → Jul 28 2011

Publication series

Name	Proceedings - 2011 8th International Conference on Fuzzy Systems and Knowledge Discovery, FSKD 2011
Volume	2

Conference

Conference	2011 8th International Conference on Fuzzy Systems and Knowledge Discovery, FSKD 2011, Jointly with the 2011 7th International Conference on Natural Computation, ICNC'11
Country/Territory	China
City	Shanghai
Period	7/26/11 → 7/28/11

Keywords

privacy preserving
spectral clustering

ASJC Scopus subject areas

Computational Theory and Mathematics
Computer Science Applications
Applied Mathematics

Access to Document

10.1109/FSKD.2011.6019699

Cite this

Lin, Z., & Jaromczyk, J. W. (2011). Privacy preserving spectral clustering over vertically partitioned data sets. In Proceedings - 2011 8th International Conference on Fuzzy Systems and Knowledge Discovery, FSKD 2011 (pp. 1206-1211). Article 6019699 (Proceedings - 2011 8th International Conference on Fuzzy Systems and Knowledge Discovery, FSKD 2011; Vol. 2). https://doi.org/10.1109/FSKD.2011.6019699

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abstract = "Spectral clustering is one of the most popular modern clustering techniques that often outperforms other clustering techniques. When data owned by different parties are used for analysis, the cooperating parties may need to perform spectral clustering jointly, even if the parties may not be willing to disclose their private data to each other. In this paper we develop privacy preserving spectral clustering protocols over vertically partitioned data sets. Such protocols allow various parties to analyze their data jointly while protecting their privacy.",

keywords = "privacy preserving, spectral clustering",

author = "Zhenmin Lin and Jaromczyk, {Jerzy W.}",

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booktitle = "Proceedings - 2011 8th International Conference on Fuzzy Systems and Knowledge Discovery, FSKD 2011",

note = "2011 8th International Conference on Fuzzy Systems and Knowledge Discovery, FSKD 2011, Jointly with the 2011 7th International Conference on Natural Computation, ICNC'11 ; Conference date: 26-07-2011 Through 28-07-2011",

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Lin, Z & Jaromczyk, JW 2011, Privacy preserving spectral clustering over vertically partitioned data sets. in Proceedings - 2011 8th International Conference on Fuzzy Systems and Knowledge Discovery, FSKD 2011., 6019699, Proceedings - 2011 8th International Conference on Fuzzy Systems and Knowledge Discovery, FSKD 2011, vol. 2, pp. 1206-1211, 2011 8th International Conference on Fuzzy Systems and Knowledge Discovery, FSKD 2011, Jointly with the 2011 7th International Conference on Natural Computation, ICNC'11, Shanghai, China, 7/26/11. https://doi.org/10.1109/FSKD.2011.6019699

Privacy preserving spectral clustering over vertically partitioned data sets. / Lin, Zhenmin; Jaromczyk, Jerzy W.
Proceedings - 2011 8th International Conference on Fuzzy Systems and Knowledge Discovery, FSKD 2011. 2011. p. 1206-1211 6019699 (Proceedings - 2011 8th International Conference on Fuzzy Systems and Knowledge Discovery, FSKD 2011; Vol. 2).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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AB - Spectral clustering is one of the most popular modern clustering techniques that often outperforms other clustering techniques. When data owned by different parties are used for analysis, the cooperating parties may need to perform spectral clustering jointly, even if the parties may not be willing to disclose their private data to each other. In this paper we develop privacy preserving spectral clustering protocols over vertically partitioned data sets. Such protocols allow various parties to analyze their data jointly while protecting their privacy.

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Privacy preserving spectral clustering over vertically partitioned data sets

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Keywords

ASJC Scopus subject areas

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