D. P. Bertsekas, A new algorithm for the assignment problem, Mathematical Programming, vol.19, issue.1, pp.152-171, 1981.
DOI : 10.1007/BF01584237

I. Bienaymé, Considérations à l'appui de la découverte de Laplace sur la loi de probabilité dans la méthode des moindres carrés. Imprim, 1853.

G. Blair, K. Imai, and Y. Zhou, Design and Analysis of the Randomized Response Technique, Journal of the American Statistical Association, vol.6, issue.511, pp.1304-1319, 2015.
DOI : 10.1007/s00184-007-0131-x

J. Doerner and D. , Evans, and a. shelat. Secure stable matching at scale, Proc. of ACM CCS '16, pp.1602-1613, 2016.

C. Dwork, Differential Privacy, Proc. of ICALP '06, pp.1-12, 2006.
DOI : 10.1007/11787006_1

C. Dwork, Differential Privacy: A Survey of Results, pp.1-19, 2008.
DOI : 10.1007/978-3-540-79228-4_1

C. Dwork and A. Roth, The Algorithmic Foundations of Differential Privacy, Foundations and Trends?? in Theoretical Computer Science, vol.9, issue.3-4, pp.3-4211, 2014.
DOI : 10.1561/0400000042

H. Kajino, Privacy-Preserving Crowdsourcing, 2016.

T. Kandappu, V. Sivaraman, A. Friedman, and R. Boreli, Loki: A privacy-conscious platform for crowdsourced surveys, 2014 Sixth International Conference on Communication Systems and Networks (COMSNETS), pp.1-8, 2014.
DOI : 10.1109/COMSNETS.2014.6734877

URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=

S. P. Kasiviswanathan, H. K. Lee, K. Nissim, S. Raskhodnikova, and A. Smith, What can we learn privately?, Proc. of IEEE FOCS '08, pp.531-540, 2008.
DOI : 10.1137/090756090

URL : http://arxiv.org/abs/0803.0924

H. W. Kuhn, The Hungarian method for the assignment problem, Naval Research Logistics Quarterly, vol.3, issue.1-2, pp.83-97, 1955.
DOI : 10.1002/nav.3800020109

URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=

P. Mavridis, D. Gross-amblard, and Z. Miklós, Using Hierarchical Skills for Optimized Task Assignment in Knowledge-Intensive Crowdsourcing, Proceedings of the 25th International Conference on World Wide Web , WWW '16, pp.843-853, 2016.
DOI : 10.1145/2872427.2883070

URL : https://hal.archives-ouvertes.fr/hal-01306481

F. Mcsherry, Privacy integrated queries: an extensible platform for privacypreserving data analysis, Proc. of ACM SIGMOD '09, pp.19-30, 2009.

F. Mcsherry and I. Mironov, Differentially private recommender systems, Proceedings of the 15th ACM SIGKDD international conference on Knowledge discovery and data mining, KDD '09, pp.627-636, 2009.
DOI : 10.1145/1557019.1557090

P. Paillier, Public-Key Cryptosystems Based on Composite Degree Residuosity Classes, EUROCRYPT '99, pp.223-238, 1999.
DOI : 10.1007/3-540-48910-X_16

URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=

H. To, G. Ghinita, and C. Shahabi, A framework for protecting worker location privacy in spatial crowdsourcing, Proc. VLDB Endow, pp.919-930, 2014.
DOI : 10.14778/2732951.2732966

S. L. Warner, Randomized Response: A Survey Technique for Eliminating Evasive Answer Bias, Journal of the American Statistical Association, vol.60, issue.309, pp.63-69, 1965.
DOI : 10.1080/01621459.1965.10480775

A. Waseda and R. Nojima, Analyzing Randomized Response Mechanisms Under Differential Privacy, ISC '16, pp.271-282, 2016.
DOI : 10.1007/978-3-319-45871-7_17

Ú. Erlingsson, V. Pihur, and A. Korolova, RAPPOR, Proceedings of the 2014 ACM SIGSAC Conference on Computer and Communications Security, CCS '14, 2014.
DOI : 10.1145/2660267.2660348