An Integrated Framework for Database Privacy Protection

Abstract

One of the central objectives of studying database privacy protection is to protect sensitive information held in a database from being inferred by a generic database user. In this paper, we present a framework to assist in the formal analysis of the database inference problem. The framework is based on an association network which is composed of a similarity measure and a Bayesian network model.

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Document Details

Document Type
Technical Report
Publication Date
Jan 01, 2001
Accession Number
ADA465125

Entities

People

  • Ira A. Moskowitz
  • Liwu Chang

Organizations

  • United States Naval Research Laboratory

Tags

Communities of Interest

  • Biomedical

DTIC Thesaurus Topics

  • Abstracts
  • Availability
  • Bayesian Networks
  • Classification
  • Computations
  • Computers
  • Contracts
  • Databases
  • Identification
  • Information Operations
  • Instructions
  • Military Research
  • Models
  • Monitoring
  • Security
  • Standards

Fields of Study

  • Computer science

Readers

  • Artificial Intelligence
  • Government and Public Administration Law.

Technology Areas

  • AI & ML