Abstract | ||
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We continue a line of research initiated in [10,11]on privacy-preserving statistical databases. Consider a trusted server that holds a database of sensitive information. Given a query function f mapping databases to reals, the so-called true answer is the result of applying f to the database. To protect privacy, the true answer is perturbed by the addition of random noise generated according to a carefully chosen distribution, and this response, the true answer plus noise, is returned to the user. Previous work focused on the case of noisy sums, in which f = ∑ig(xi), where xi denotes the ith row of the database and g maps database rows to [0,1]. We extend the study to general functions f, proving that privacy can be preserved by calibrating the standard deviation of the noise according to the sensitivity of the function f. Roughly speaking, this is the amount that any single argument to f can change its output. The new analysis shows that for several particular applications substantially less noise is needed than was previously understood to be the case. The first step is a very clean characterization of privacy in terms of indistinguishability of transcripts. Additionally, we obtain separation results showing the increased value of interactive sanitization mechanisms over non-interactive. |
Year | DOI | Venue |
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2006 | 10.1007/11681878_14 | TCC |
Keywords | Field | DocType |
query function,calibrating noise,clean characterization,so-called true answer,xi denotes,random noise,true answer,statistical databases,g maps database row,private data analysis,mapping databases,general function,generating function,standard deviation,data analysis | Row,Semantic security,Laplace distribution,Differential privacy,Cryptography,Computer science,Theoretical computer science,Information sensitivity,Information privacy,Standard deviation | Conference |
Volume | ISSN | ISBN |
3876 | 0302-9743 | 3-540-32731-2 |
Citations | PageRank | References |
1007 | 49.75 | 12 |
Authors | ||
4 |
Name | Order | Citations | PageRank |
---|---|---|---|
Cynthia Dwork | 1 | 9137 | 821.87 |
Frank McSherry | 2 | 4289 | 288.94 |
Kobbi Nissim | 3 | 5089 | 324.63 |
Adam Smith | 4 | 4183 | 229.81 |