GP^2S: Generic Privacy-Preservation Solutions for Approximate Aggregation of Sensor Data (concise contribution)

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2008 Sixth Annual IEEE International Conference on Pervasive Computing and Communications

March 17-March 21

ISBN: 978-0-7695-3113-7

	ASCII Text	x
	Wensheng Zhang, Chuang Wang, Taiming Feng, "GP^2S: Generic Privacy-Preservation Solutions for Approximate Aggregation of Sensor Data (concise contribution)," Pervasive Computing and Communications, IEEE International Conference on, pp. 179-184, 2008 Sixth Annual IEEE International Conference on Pervasive Computing and Communications, 2008.

	BibTex	x
	@article{ 10.1109/PERCOM.2008.60, author = {Wensheng Zhang and Chuang Wang and Taiming Feng}, title = {GP^2S: Generic Privacy-Preservation Solutions for Approximate Aggregation of Sensor Data (concise contribution)}, journal ={Pervasive Computing and Communications, IEEE International Conference on}, volume = {0}, year = {2008}, isbn = {978-0-7695-3113-7}, pages = {179-184}, doi = {http://doi.ieeecomputersociety.org/10.1109/PERCOM.2008.60}, publisher = {IEEE Computer Society}, address = {Los Alamitos, CA, USA}, }

	RefWorks Procite/RefMan/Endnote	x
	TY - CONF JO - Pervasive Computing and Communications, IEEE International Conference on TI - GP^2S: Generic Privacy-Preservation Solutions for Approximate Aggregation of Sensor Data (concise contribution) SN - 978-0-7695-3113-7 SP179 EP184 A1 - Wensheng Zhang, A1 - Chuang Wang, A1 - Taiming Feng, PY - 2008 KW - null VL - 0 JA - Pervasive Computing and Communications, IEEE International Conference on ER -

Wensheng Zhang

Chuang Wang

Taiming Feng

DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/PERCOM.2008.60

Protecting privacy in sensor networks poses new challenges because of the potential incompatibilities between new privacy-preserving mechanisms and mechanisms already implemented in sensor networks (such as in-network data aggregation). To address this problem, we propose in this paper a set of new privacy-preservation data aggregation schemes. Different from past research, our solutions have the following features: supporting data aggregation for a variety of queries; providing privacy protection for both individual data and aggregate data; being resilient to any number of node collusion; being highly efficient.

Citation:

Wensheng Zhang, Chuang Wang, Taiming Feng, "GP^2S: Generic Privacy-Preservation Solutions for Approximate Aggregation of Sensor Data (concise contribution)," percom, pp.179-184, 2008 Sixth Annual IEEE International Conference on Pervasive Computing and Communications, 2008

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