Calibrating Noise to Sensitivity in Private Data Analysis-Reference-Cited by-同舟云学术

Calibrating Noise to Sensitivity in Private Data Analysis

Published:2006 Issue: Volume: Page:265-284
ISSN:0302-9743
Container-title:Theory of Cryptography
language:
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Author:

Dwork Cynthia,McSherry Frank,Nissim Kobbi,Smith Adam

Publisher

Springer Berlin Heidelberg

Link

http://link.springer.com/content/pdf/10.1007/11681878_14.pdf

Reference16 articles.

1. Adam, N.R., Wortmann, J.C.: Security-control methods for statistical databases: a comparative study. ACM Computing Surveys 25(4) (December 1989)

2. Agrawal, D., Aggarwal, C.C.: On the design and quantification of privacy preserving data mining algorithms. In: Proceedings of the Twentieth ACM SIGACT-SIGMOD-SIGART Symposium on Principles of Database Systems. ACM, New York (2001)

3. Agrawal, R., Srikant, R.: Privacy-preserving data mining. In: Chen, W., Naughton, J.F., Bernstein, P.A. (eds.) SIGMOD Conference, pp. 439–450. ACM, New York (2000)

4. Ben-Sasson, E., Harsha, P., Raskhodnikova, S.: Some 3cnf properties are hard to test. In: STOC, pp. 345–354. ACM, New York (2000)

5. Web page for the Bertinoro CS-Statistics workshop on privacy and confidentiality (July 2005), Available from, http://www.stat.cmu.edu/~hwainer

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