Uncertainty-Sensitive Heterogeneous Information Fusion: Assessing Threat with Soft, Uncertain, and Conflicting Evidence

Abstract

Military and other government organizations put substantial effort into detecting and thwarting attacks such as those by suicide bombers or involving improvised explosive devices. Such attacks may be against military or government installations in the United States or abroad, civilian infrastructure, or any of many other targets. An element of thwarting such attacks is observing suspicious individuals over time with such diverse means as cameras, scanners, and other devices; travel records; behavioral observations; and intelligence sources. Such observations provide data that are often both complex and softi.e. qualitative, subjective, fuzzy, or ambiguousand also contradictory or even deceptive (as when humans lie). The problem, then, is how to fuse the heterogeneous data. This report summarizes our research on heterogeneous fusion methods. The context is military and civilian counterterrorism,

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Document Details

Document Type
Technical Report
Publication Date
Jan 01, 2016
Accession Number
AD1014451

Entities

People

  • David Manheim
  • John S. Hollywood
  • Paul K. Davis
  • Walter L. Perry

Organizations

  • RAND Corporation

Tags

Communities of Interest

  • C4I
  • Engineered Resilient Systems
  • Ground and Sea Platforms

DTIC Thesaurus Topics

  • Bayesian Networks
  • Computational Science
  • Computer Programming
  • Computers
  • Counterterrorism
  • Data Mining
  • Information Science
  • Machine Learning
  • National Security
  • Probability
  • Probability Distributions
  • Psychology
  • Reliability
  • Risk Analysis
  • Social Sciences
  • Spreadsheet Software
  • Stochastic Processes

Readers

  • Personnel Management and Statistics in the Military and Department of Defense
  • Sensor Fusion and Tracking Systems.
  • Strategic Security Studies