全球智库信息集成服务系统

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Objective Analysis. Effective Solutions.

An element of thwarting terrorist attacks is observing suspicious individuals over time with such diverse means as scanners and other devices, travel records, behavioral observations, and intelligence sources. Such observations provide data that are often both complex and "soft" — i.e., qualitative, subjective, fuzzy, or ambiguous — and also contradictory or even deceptive. Analysts face the challenge of heterogeneous information fusion — that is, combining such data to form a realistic assessment of threat. This report presents research on various heterogeneous information fusion methods and describes a research prototype system for fusing uncertainty-sensitive heterogeneous information. The context is counterterrorism, for both military and civilian applications, but the ideas are also applicable in intelligence and law enforcement.

• Chapter One

  Introduction

• Chapter Two

  Concepts, Methods, and a Research Platform

• Chapter Three

  Creating Synthetic Data: Vignettes for Testing

• Chapter Four

  Simple and Bayesian Fusion Methods

• Chapter Five

  The Maximum Entropy/Minimum Penalty Fusion Method

• Chapter Six

  Illustrative Analysis

• Chapter Seven

  Conclusions and Recommendations

• Appendix A

  Defining Threat

• Appendix B

  A Factor-Tree Model for Propensity for Terrorism (PFT)

• Appendix C

  Extending Elementary Bayes Updating