Lower bounds in differential privacy
Cryptography and Security
2011-12-23 v2 Computational Complexity
Abstract
This is a paper about private data analysis, in which a trusted curator holding a confidential database responds to real vector-valued queries. A common approach to ensuring privacy for the database elements is to add appropriately generated random noise to the answers, releasing only these {\em noisy} responses. In this paper, we investigate various lower bounds on the noise required to maintain different kind of privacy guarantees.
Keywords
Cite
@article{arxiv.1107.2183,
title = {Lower bounds in differential privacy},
author = {Anindya De},
journal= {arXiv preprint arXiv:1107.2183},
year = {2011}
}
Comments
Corrected some minor errors and typos. To appear in Theory of Cryptography Conference (TCC) 2012