Practical privacy
Carnegie Mellon University · Microsoft (United States) · +1 more institution
Abstract
We consider a statistical database in which a trusted administrator introduces noise to the query responses with the goal of maintaining privacy of individual database entries. In such a database, a query consists of a pair (S, f) where S is a set of rows in the database and f is a function mapping database rows to {0, 1}. The true answer is ΣiεS f(di), and a noisy version is released as the response to the query. Results of Dinur, Dwork, and Nissim show that a strong form of privacy can be maintained using a surprisingly small amount of noise -- much less than the sampling error -- provided the total number of queries is sublinear in the number of database rows. We call this query and (slightly) noisy reply…
Citation impact
- FWCI
- 30.78
- Percentile
- 100%
- References
- 20
Authors
4Topics & keywords
- Computer science
- Row
- Differential privacy
- View
- Sublinear function
- Database
- Noise (video)
- Set (abstract data type)
- Peace, Justice and strong institutions