A Secure Clustering Algorithm for Distributed Data Streams

Omaha, Nebraska, USA October 28-October 31

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http://doi.ieeecomputersociety.org/10.1109/ICDMW.2007.65

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	Geetha Jagannathan, Krishnan Pillaipakkamnatt, D. Umano, "A Secure Clustering Algorithm for Distributed Data Streams," Data Mining Workshops, International Conference on, pp. 705-710, Seventh IEEE International Conference on Data Mining Workshops (ICDMW 2007), 2007.

	BibTex	x
	@article{ 10.1109/ICDMW.2007.65, author = {Geetha Jagannathan and Krishnan Pillaipakkamnatt and D. Umano}, title = {A Secure Clustering Algorithm for Distributed Data Streams}, journal ={Data Mining Workshops, International Conference on}, volume = {0}, year = {2007}, isbn = {0-7695-3033-8}, pages = {705-710}, doi = {http://doi.ieeecomputersociety.org/10.1109/ICDMW.2007.65}, publisher = {IEEE Computer Society}, address = {Los Alamitos, CA, USA}, }

	RefWorks Procite/RefMan/Endnote	x
	TY - CONF JO - Data Mining Workshops, International Conference on TI - A Secure Clustering Algorithm for Distributed Data Streams SN - 0-7695-3033-8 SP705 EP710 A1 - Geetha Jagannathan, A1 - Krishnan Pillaipakkamnatt, A1 - D. Umano, PY - 2007 VL - 0 JA - Data Mining Workshops, International Conference on ER -

Geetha Jagannathan

Krishnan Pillaipakkamnatt

D. Umano

We present a distributed privacy-preserving protocol for the clustering of data streams. The participants of the se- cure protocol learn cluster centers only on completion of the protocol. Our protocol does not reveal intermediate candidate cluster centers. It is also efficient in terms of communication. The protocol is based on a new memory- efficient clustering algorithm for data streams. Our experi- ments show that, on average, the accuracy of this algorithm is better than that of the well known k-means algorithm, and compares well with BIRCH, but has far smaller mem- ory requirements.

Citation:

Geetha Jagannathan, Krishnan Pillaipakkamnatt, D. Umano, "A Secure Clustering Algorithm for Distributed Data Streams," icdmw, pp.705-710, Seventh IEEE International Conference on Data Mining Workshops (ICDMW 2007), 2007

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