Diophantine Inferences from Statistical Aggregates on Few-Valued Attributes,

Abstract

Research on protection of statistical databases from revelation of private or sensitive information has rarely examined situations where domain-dependent structure exits for a data attribute such that only a very few independent variables can characterize it. Such circumstances can lead to Diophantine (integer-solution) equations whose solution can lead to surprising or compromising inferences on quite large data populations. In many cases the Diophantine equations are linear, allowing efficient algorithmic solution. Probabilistic models can also be used to rank solutions by reasonability, further pruning the search space. Unfortunately, it is difficult to protect against this form of data compromise, and all countermeasures have disadvantages. (Author)

Document Details

Document Type
Technical Report
Publication Date
Jan 01, 1984
Accession Number
ADA138365

Entities

People

  • N. C. Rowe

Organizations

  • Naval Postgraduate School

Tags

DTIC Thesaurus Topics

  • Countermeasures
  • Databases
  • Digital Data
  • Equations
  • Models
  • Probabilistic Models

Fields of Study

  • Computer science

Readers

  • Economics
  • Neural Network Machine Learning.
  • Theoretical Analysis.

Technology Areas

  • AI & ML
  • AI & ML - Machine Learning Algorithms
  • Space