Characterizing and Detecting Unrevealed Elements of Network Systems

Abstract

This dissertation addresses the problem of discovering and characterizing unknown elements in network systems. It is not uncommon to have incomplete knowledge of network systems due to either passive circumstances, e.g. limited resources to observe a network, or active circumstances, e.g. intentional acts of concealment, or some combination of active and passive influences. This research suggests statistical and graph theoretic approaches for such situations, including those in which nodes are causally related. A related aspect of this research is accuracy assessment. It is possible an analyst could fail to detect a network element, or be aware of network elements, but incorrectly conclude the associated network system structure. Consequently, this dissertation provides a framework to evaluate accuracy.

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Document Details

Document Type
Technical Report
Publication Date
Mar 01, 2009
Accession Number
ADA494778

Entities

People

  • James A. Leinart

Organizations

  • Air Force Institute of Technology

Tags

Communities of Interest

  • Energy and Power Technologies

DTIC Thesaurus Topics

  • Accuracy
  • Air Force
  • Artificial Intelligence
  • Bayesian Networks
  • Computational Science
  • Computer Networks
  • Data Analysis
  • Data Mining
  • Data Science
  • Factor Analysis
  • Families (Human)
  • Information Science
  • Network Science
  • Operations Research
  • Probability
  • Probability Distributions
  • Regression Analysis

Fields of Study

  • Computer science

Readers

  • Sensor Fusion and Tracking Systems.
  • Theoretical Analysis.