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STOC
1999
ACM
85views Algorithms» more  STOC 1999»
13 years 9 months ago
A Theorem on Sensitivity and Applications in Private Computation
In this paper we prove a theorem that gives an (almost) tight upper bound on the sensitivity of a multiple-output Boolean function in terms of the sensitivity of its coordinates an...
Anna Gál, Adi Rosén
STOC
2007
ACM
112views Algorithms» more  STOC 2007»
14 years 5 months ago
Smooth sensitivity and sampling in private data analysis
We introduce a new, generic framework for private data analysis. The goal of private data analysis is to release aggregate information about a data set while protecting the privac...
Kobbi Nissim, Sofya Raskhodnikova, Adam Smith
CSE
2009
IEEE
14 years 1 days ago
Private Buddy Search: Enabling Private Spatial Queries in Social Networks
—With the abundance of location-aware portable devices such as cellphones and PDAs, a new emerging application is to use this pervasive computing platform to learn about the wher...
Ali Khoshgozaran, Cyrus Shahabi
WWW
2003
ACM
14 years 6 months ago
SHOCK: communicating with computational messages and automatic private profiles
A computationally enhanced message contains some embedded programmatic components that are interpreted and executed automatically upon receipt. Unlike ordinary text email or insta...
Rajan M. Lukose, Eytan Adar, Joshua R. Tyler, Caes...
FSTTCS
2009
Springer
13 years 12 months ago
Functionally Private Approximations of Negligibly-Biased Estimators
ABSTRACT. We study functionally private approximations. An approximation function g is functionally private with respect to f if, for any input x, g(x) reveals no more information ...
André Madeira, S. Muthukrishnan