T. Allard, N. Anciaux, L. Bouganim, Y. Guo, L. Le-folgoc et al., Secure personal data servers, Proceedings of the VLDB Endowment, vol.3, issue.1-2, pp.25-35, 2010.
DOI : 10.14778/1920841.1920850
URL : https://hal.archives-ouvertes.fr/inria-00551875

L. Bottou and Y. Bengio, Convergence properties of the kmeans algorithm, ANIPS, 1995.

P. Bunn and R. Ostrovsky, Secure two-party k-means clustering, Proceedings of the 14th ACM conference on Computer and communications security , CCS '07, pp.486-497, 2007.
DOI : 10.1145/1315245.1315306
URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.149.6546

R. Chen, A. Reznichenko, P. Francis, and J. Gehrke, Towards statistical queries over distributed private user data, NSDI, pp.169-182, 2012.

L. Claret, M. Gupta, K. Han, A. Joshi, N. Sarapa et al., Evaluation of Tumor-Size Response Metrics to Predict Overall Survival in Western and Chinese Patients With First-Line Metastatic Colorectal Cancer, Journal of Clinical Oncology, vol.31, issue.17, pp.312110-2114, 2013.
DOI : 10.1200/JCO.2012.45.0973

I. Damgård and M. Jurik, A Generalisation, a Simplification and some Applications of Paillier???s Probabilistic Public-Key System, PKC, pp.119-136, 2001.
DOI : 10.7146/brics.v7i45.20212

L. D. Santos, A. G. Da-silva, B. Jacquin, M. Picard, D. Worms et al., Massive smart meter data storage and processing on top of hadoop, Int. Work. on End-to-end Man. of Big Data, 2012.

C. Dwork12-]-c, F. Dwork, K. Mcsherry, A. Nissim, S. Smith et al., Differential privacy A firm foundation for private data analysis Calibrating noise to sensitivity in private data analysis On private scalar product computation for privacy-preserving data mining, ICALP TCC ICISC14] O. Goldreich. Foundations of cryptography: a primer. Found. Trends in Theoretical Computer Science, pp.1-1286, 2004.

O. Goldreich, S. Micali, and A. Wigderson, How to play ANY mental game, Proceedings of the nineteenth annual ACM conference on Theory of computing , STOC '87, pp.218-229, 1987.
DOI : 10.1145/28395.28420

G. Jagannathan, K. Pillaipakkamnatt, and D. Umano, A Secure Clustering Algorithm for Distributed Data Streams, Seventh IEEE International Conference on Data Mining Workshops (ICDMW 2007), pp.705-710, 2007.
DOI : 10.1109/ICDMW.2007.65

G. Jagannathan, K. Pillaipakkamnatt, and R. N. Wright, A new privacy-preserving distributed k-clustering algorithm, SDM, pp.494-498, 2006.

G. Jagannathan, K. Pillaipakkamnatt, R. N. Wright, and D. Umano, Communication-efficient privacy-preserving clustering, Trans. Data Privacy, vol.3, issue.1, pp.1-25, 2010.

G. Jagannathan and R. N. Wright, Privacy-preserving distributed k-means clustering over arbitrarily partitioned data, Proceeding of the eleventh ACM SIGKDD international conference on Knowledge discovery in data mining , KDD '05, pp.593-599, 2005.
DOI : 10.1145/1081870.1081942
URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.114.200

M. Jelasity, A. Montresor, and O. Babaoglu, Gossip-based aggregation in large dynamic networks, ACM Transactions on Computer Systems, vol.23, issue.3, pp.219-252, 2005.
DOI : 10.1145/1082469.1082470

S. Jha, L. Kruger, and P. Mcdaniel, Privacy Preserving Clustering, ESORICS, pp.397-417, 2005.
DOI : 10.1007/11555827_23

D. Kempe, A. Dobra, and J. Gehrke, Gossip-based computation of aggregate information, 44th Annual IEEE Symposium on Foundations of Computer Science, 2003. Proceedings., pp.482-491, 2003.
DOI : 10.1109/SFCS.2003.1238221

S. Kotz, T. J. Kozubowski, K. Podgorski25, ]. W. Kowalczyk, and N. A. Vlassis, The Laplace Distribution and Generalizations, 26] X. Lin, C. Clifton, and M. Zhu. Privacy-preserving clustering with distributed EM mixture modeling. Know. Inf. Sys, pp.713-72068, 2001.
DOI : 10.1007/978-1-4612-0173-1

J. Liu, J. Z. Huang, J. Luo, and L. Xiong, Privacy preserving distributed DBSCAN clustering, Proceedings of the 2012 Joint EDBT/ICDT Workshops on, EDBT-ICDT '12, pp.177-185, 2012.
DOI : 10.1145/2320765.2320819
URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.298.9763

S. Lloyd, Least squares quantization in PCM, IEEE Transactions on Information Theory, vol.28, issue.2, pp.129-137, 1982.
DOI : 10.1109/TIT.1982.1056489

A. Machanavajjhala, D. Kifer, J. Abowd, J. Gehrke, and L. Vilhuber, Privacy: Theory meets Practice on the Map, 2008 IEEE 24th International Conference on Data Engineering, pp.277-286, 2008.
DOI : 10.1109/ICDE.2008.4497436

A. Montresor and M. Jelasity, PeerSim: A scalable P2P simulator, 2009 IEEE Ninth International Conference on Peer-to-Peer Computing, pp.99-100, 2009.
DOI : 10.1109/P2P.2009.5284506

M. Newborough and P. Augood, Demand-side management opportunities for the UK domestic sector, IEE Proceedings - Generation, Transmission and Distribution, vol.146, issue.3, pp.283-293, 1999.
DOI : 10.1049/ip-gtd:19990318

A. Prudenzi, A neuron nets based procedure for identifying domestic appliances pattern-of-use from energy recordings at meter panel, 2002 IEEE Power Engineering Society Winter Meeting. Conference Proceedings (Cat. No.02CH37309), pp.941-946, 2002.
DOI : 10.1109/PESW.2002.985144

V. Rastogi and S. Nath, Differentially private aggregation of distributed time-series with transformation and encryption, Proceedings of the 2010 international conference on Management of data, SIGMOD '10, pp.735-746, 2010.
DOI : 10.1145/1807167.1807247

J. Sakuma, S. Kobayashi36, ]. E. Shi, T. H. Chan, E. G. Rieffel et al., Large-scale k-means clustering with user-centric privacy preservation Privacy-preserving aggregation of time-series data, PAKDD NDSS, 2011. [37] A. C. Yao. Protocols for secure computations. In FOCS, pp.320-332, 1982.