This paper considers the problem of providing security to statistical databases against
disclosure of confidential information. Security-control methods suggested in the literature …

As organizations increase their reliance on, possibly distributed, information systems for
daily business, they become more vulnerable to security breaches even as they gain …

Calibrating Noise to Sensitivity in Private Data Analysis Page 1 Journal of Privacy and
Confidentiality (2016-2017) 7, Number 3, 17–51 Calibrating Noise to Sensitivity in Private Data …

Over the past five years a new approach to privacy-preserving data analysis has born fruit
[13, 18, 7, 19, 5, 37, 35, 8, 32]. This approach differs from much (but not all!) of the related …

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 …

In 1977 Dalenius articulated a desideratum for statistical databases: nothing about an
individual should be learnable from the database that cannot be learned without access to …

Publishing data about individuals without revealing sensitive information about them is an
important problem. In recent years, a new definition of privacy called k-anonymity has …

• Part VI (three chapters) describes the impact of object technology on database systems.
Chapter 25 describes object systems specifically; Chapter 26 considers the possibility of a …

A fruitful direction for future data mining research will be the development of techniques that
incorporate privacy concerns. Specifically, we address the following question. Since the …

A firm foundation for private data analysis Page 1 86 communications of the acm | january
2011 | vol. 54 | no. 1 review articles This long history is a testament to the importance of the …