Article

Privacy-preserving k-means clustering over vertically partitioned data

Authors:

Jaideep Vaidya,

Chris CliftonAuthors Info & Claims

KDD '03: Proceedings of the ninth ACM SIGKDD international conference on Knowledge discovery and data mining

Pages 206 - 215

https://doi.org/10.1145/956750.956776

Published: 24 August 2003 Publication History

Abstract

Privacy and security concerns can prevent sharing of data, derailing data mining projects. Distributed knowledge discovery, if done correctly, can alleviate this problem. The key is to obtain valid results, while providing guarantees on the (non)disclosure of data. We present a method for k-means clustering when different sites contain different attributes for a common set of entities. Each site learns the cluster of each entity, but learns nothing about the attributes at other sites.

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Cited By

Hu CLiu JXia HDeng SYu J(2024)A Lightweight Mutual Privacy Preserving $k$-Means Clustering in Industrial IoTIEEE Transactions on Network Science and Engineering10.1109/TNSE.2023.333782811:2(2138-2152)Online publication date: Mar-2024
https://doi.org/10.1109/TNSE.2023.3337828
Fu JCheng KSong AXia YChang ZShen Y(2024)FSS-DBSCAN: Outsourced Private Density-Based Clustering via Function Secret SharingIEEE Transactions on Information Forensics and Security10.1109/TIFS.2024.344623319(7759-7773)Online publication date: 2024
https://doi.org/10.1109/TIFS.2024.3446233
Zhou QWu SJiang CZhang RJing X(2024)Cloud-Edge–Terminal Collaboration-Enabled Device-Free Sensing Under Class-Imbalance ConditionsIEEE Internet of Things Journal10.1109/JIOT.2023.331294111:4(5980-5992)Online publication date: 15-Feb-2024
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Privacy-preserving k-means clustering over vertically partitioned data

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cover image ACM Conferences

KDD '03: Proceedings of the ninth ACM SIGKDD international conference on Knowledge discovery and data mining

August 2003

736 pages

ISBN:1581137370

DOI:10.1145/956750

Conference Chair:
Lise Getoor
University of Maryland, College Park
,
General Chair:
Ted Senator
DARPA
,
Program Chairs:
Pedro Domingos
University of Washington
,
Christos Faloutsos
Carnegie Mellon University

Copyright © 2003 ACM.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Published: 24 August 2003

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KDD03

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KDD03: The Ninth ACM SIGKDD International Conference on Knowledge Discovery and Data Mining

August 24 - 27, 2003

Washington, D.C.

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KDD '03 Paper Acceptance Rate 46 of 298 submissions, 15%;

Overall Acceptance Rate 1,133 of 8,635 submissions, 13%

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Cited By

Hu CLiu JXia HDeng SYu J(2024)A Lightweight Mutual Privacy Preserving $k$-Means Clustering in Industrial IoTIEEE Transactions on Network Science and Engineering10.1109/TNSE.2023.333782811:2(2138-2152)Online publication date: Mar-2024
https://doi.org/10.1109/TNSE.2023.3337828
Fu JCheng KSong AXia YChang ZShen Y(2024)FSS-DBSCAN: Outsourced Private Density-Based Clustering via Function Secret SharingIEEE Transactions on Information Forensics and Security10.1109/TIFS.2024.344623319(7759-7773)Online publication date: 2024
https://doi.org/10.1109/TIFS.2024.3446233
Zhou QWu SJiang CZhang RJing X(2024)Cloud-Edge–Terminal Collaboration-Enabled Device-Free Sensing Under Class-Imbalance ConditionsIEEE Internet of Things Journal10.1109/JIOT.2023.331294111:4(5980-5992)Online publication date: 15-Feb-2024
https://doi.org/10.1109/JIOT.2023.3312941
Shankar ABrouwer HHai RChen L(2024)SiloFuse: Cross-silo Synthetic Data Generation with Latent Tabular Diffusion Models2024 IEEE 40th International Conference on Data Engineering (ICDE)10.1109/ICDE60146.2024.00016(110-123)Online publication date: 13-May-2024
https://doi.org/10.1109/ICDE60146.2024.00016
Vyas SKarmore S(2024)Design and Development of Privacy Preservation Approach in Data Mining Using Noise Additive Model in Continuous and Multi-Dimensional Data Set2024 IEEE 13th International Conference on Communication Systems and Network Technologies (CSNT)10.1109/CSNT60213.2024.10546012(272-279)Online publication date: 6-Apr-2024
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Zhu BZhang YChen TZhong S(2024)Differentially Private K-Means Publishing with Distributed Dimensions2024 27th International Conference on Computer Supported Cooperative Work in Design (CSCWD)10.1109/CSCWD61410.2024.10580021(3263-3268)Online publication date: 8-May-2024
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Shi CHuang XYu P(2024) On the Security of Distributed Multi-Agent K -Means Clustering With Local Differential Privacy IEEE Access10.1109/ACCESS.2024.345482312(124751-124763)Online publication date: 2024
https://doi.org/10.1109/ACCESS.2024.3454823
Sadhukhan PHalder LPalit S(2024)Approximate DBSCAN on obfuscated dataJournal of Information Security and Applications10.1016/j.jisa.2023.10366480:COnline publication date: 17-Apr-2024
https://dl.acm.org/doi/10.1016/j.jisa.2023.103664
Qiu GZhao YGui X(2024)Efficient privacy-preserving outsourced k-means clustering on distributed dataInformation Sciences: an International Journal10.1016/j.ins.2024.120687674:COnline publication date: 1-Jul-2024
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Cook JShyani MMishra NOh ANaumann TGloberson ASaenko KHardt MLevine S(2023)Creating a public repository for joining private dataProceedings of the 37th International Conference on Neural Information Processing Systems10.5555/3666122.3669244(71294-71326)Online publication date: 10-Dec-2023
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