Description
Book SynopsisMost of the research aimed at counterterrorism, fraud detection, or other forensic applications assumes that this is a specialized application domain for mainstream knowledge discovery. Unfortunately, knowledge discovery changes completely when the datasets being used have been manipulated in order to conceal some underlying activity. Knowledge Discovery for Counterterrorism and Law Enforcement operates from the premise that detection algorithms must be rethought to be effective in this domain, and presents a new approach based on cutting-edge analysis for use in adversarial settings.
Reveals How Criminals Conceal Information
This volume focuses on four main forms of knowledge discovery: prediction, clustering, relationship discovery, and textual analysis. For each of these application areas, the author discusses opportunities for concealment that are available to crimi
Trade Review
The writing is organized, clear, and free of technical jargon and mathematical notation. ... In summary, this is a highly readable introduction to an interesting field. While it is certainly a valuable introductory resource for the technically adept, it is also appropriate for those with the desire to understand the applicability, potential, and limitations of computer-assisted knowledge discovery techniques in counterterrorism and law enforcement. -Computing Reviews, September 2009
Table of Contents
Introduction. Data. High-Level Principles. Looking for Risk - Prediction and Anomaly Detection. Looking for Similarity – Clustering. Looking Inside Groups - Relationship Discovery. Discovery from Public Textual Data. Discovery in Private Communication. Discovering Mental and Emotional State. The Bottom Line.
