Advertisement

Applications to Information Management: How to Measure Loss of Privacy

  • Hung T. Nguyen
  • Vladik Kreinovich
  • Berlin Wu
  • Gang Xiang
Part of the Studies in Computational Intelligence book series (SCI, volume 393)

Abstract

In this chapter, we use the experience of measuring a degree of mismatch between probability models, p-boxes, etc., described in Chapter 30, to measure loss of privacy. Some of our privacy-related results first appeared in [58].

Formulation and Analysis of the Problem, and the Corresponding Results

Measuring loss of privacy is important. Privacy means, in particular, that we do not disclose all information about ourselves. If some of the originally undisclosed information is disclosed, some privacy is lost. To compare different privacy protection schemes, we must be able to gauge the resulting loss of privacy.

Keywords

Blood Pressure Heart Attack Insurance Rate Irrelevant Information Medical Expense 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

Copyright information

© Springer-Verlag Berlin Heidelberg 2012

Authors and Affiliations

  • Hung T. Nguyen
    • Vladik Kreinovich
      • Berlin Wu
        • Gang Xiang

          There are no affiliations available

          Personalised recommendations