An Ad Omnia Approach to Defining and Achieving Private Data Analysis

  • Cynthia Dwork
Conference paper

DOI: 10.1007/978-3-540-78478-4_1

Part of the Lecture Notes in Computer Science book series (LNCS, volume 4890)
Cite this paper as:
Dwork C. (2008) An Ad Omnia Approach to Defining and Achieving Private Data Analysis. In: Bonchi F., Ferrari E., Malin B., Saygin Y. (eds) Privacy, Security, and Trust in KDD. Lecture Notes in Computer Science, vol 4890. Springer, Berlin, Heidelberg

Abstract

We briefly survey several privacy compromises in published datasets, some historical and some on paper. An inspection of these suggests that the problem lies with the nature of the privacy-motivated promises in question. These are typically syntactic, rather than semantic. They are also ad hoc , with insufficient argument that fulfilling these syntactic and ad hoc conditions yields anything like what most people would regard as privacy. We examine two comprehensive, or ad omnia, guarantees for privacy in statistical databases discussed in the literature, note that one is unachievable, and describe implementations of the other.

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

Copyright information

© Springer-Verlag Berlin Heidelberg 2008

Authors and Affiliations

  • Cynthia Dwork
    • 1
  1. 1.Microsoft Research 

Personalised recommendations